Identification and functional analysis of downy mildew effectors in ...

Identification and functional analysis
of downy mildew effectors
in lettuce and Arabidopsis
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Joost H.M. Stassen

Identification and functional analysis of
downy mildew effectors in lettuce and Arabidopsis
Joost H. M. Stassen

Cover and Layout: J.H.M. Stassen
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ISBN: 978-90-393-5843-6

Identification and functional analysis of
downy mildew effectors in lettuce and Arabidopsis
Identificatie en functionele analyse van
valse meeldauw effectoren in sla en Arabidopsis
(met een samenvatting in het Nederlands)
Proefschrift
ter verkrijging van de graad van doctor aan de Universiteit Utrecht
op gezag van de rector magnificus, prof.dr. G.J. van der Zwaan,
ingevolge het besluit van het college voor promoties
in het openbaar te verdedigen
op woensdag 24 oktober 2012 des ochtends te 10.30 uur
door
Johannes Hubertus Marie Stassen
geboren op 1 november 1984 te Woerden

Promotor:
Co-promotor:
Prof.dr.ir. C.M.J. Pieterse
Dr. A.F.J.M. van den Ackerveken
Dit proefschrift werd mede mogelijk gemaakt met financiële steun van het
Technologisch Topinstituut Groene Genetica.

Contents
Chapter 1: 7
How do oomycete effectors interfere with plant life
Outline 23
Chapter 2: 25
Identification of Hyaloperonospora arabidopsidis transcript sequences
expressed during infection reveals isolate-specific effectors
Chapter 3: 63
Effector identification in the lettuce downy mildew Bremia lactucae by
massively parallel transcriptome sequencing
Chapter 4: 95
Effectors of the lettuce downy mildew Bremia lactucae enhance host
susceptibility
Chapter 5: 131
Two GKLR proteins of the lettuce downy mildew Bremia lactucae induce
effector-triggered immunity
Chapter 6: 165
Discussion
Summary 181
Samenvatting 183
Acknowledgements 185
Curriculum vitae 187

9
Chapter 1:
How do oomycete effectors interfere with
plant life
Joost HM Stassen 1 and Guido Van den Ackerveken 1,2
1
Plant-Microbe Interactions, Department of Biology, Utrecht University,
Padualaan 8, 3584 CH Utrecht, The Netherlands
2
Centre for BioSystems Genomics, 6700 AB, Wageningen, The Netherlands
Current Opinion in Plant Biology (2011) 14: 407-14
doi: 10.1016/j.pbi.2011.05.002

10 Chapter 1
Introduction
Oomycetes are fungal-like microorganisms that belong to the kingdom Stramenopila
and are evolutionary related to brown algae. Many well-known plant
pathogens are oomycetes, ranging from the necrotrophic broad host range Pythium
species, through hemibiotrophic Phytophthora species, to obligate biotrophic
species such as white rust (Albugo) and narrow host-range downy mildews (e.g.
Hyaloperonospora and Bremia species). These oomycete pathogens interfere with
plant life for successful infection, utilising effector proteins to manipulate their
hosts. The sequencing of the genomes of Phytophthora ramorum and P. sojae [1] ,
P. infestans [2] , Pythium ultimum [3] , and Hyaloperonospora arabidopsidis [4] has
advanced the field enormously by enabling the identification of a large number
of genes encoding secreted effector proteins in this diverse group of pathogens
(Figure 1). In Phytophthora species many effector genes are found in gene-poor
regions that have recently expanded, probably driven by repeats (transposons) [2,5] .
These regions are linked to accelerated gene evolution after host jumps [5] and may
explain the evolutionary flexibility of these species. Also, more novel combinations
of known protein domains are present in oomycetes than in other species with
a similar single domain repertoire. These combinations are enriched in secreted
infection-related proteins, suggesting that oomycetes have evolved a unique
toolbox for host manipulation [6,7] .
Figure 1: The lifestyle of oomycetes of which a full genome sequence is available and the number of
members per family of selected effector types reported [1–4] . The presumed evolutionary relationship
between the species is indicated in the phylogenetic tree.
Here we discuss (summarised in Figure 2) recent advances in understanding the
roles of secreted oomycete effectors in successful infection of host plants.
Clearing the way
In early phases of the interaction, the invading oomycete needs to deal with
biochemical barriers in the plant apoplast. Both pathogen and host secrete proteins
and metabolites to control the extracellular environment. Three types of apoplastic
effectors from oomycetes have been shown to interfere with plant processes; inhib-

How do oomycete effectors interfere with plant life
11
Figure 2: Schematic representation of how oomycetes interfere with plant life. Details are described
in the main text under the headings; (a) Clearing the way, (b) Breaking in, (c) Quelling resistance, and
(d) Sweet rewards. Proteins produced in the oomycete cytoplasm (OC) are secreted over the oomycete
membrane (OM) and cell wall (OW). The haustorium (H) has breached the plant cell wall (PW) and
invaginated the host plasma membrane (PM). RXLR and Crinkler effectors (RXLRs and CRNs) are
secreted from the haustorium and arrive, for example in the plant cytoplasm (PC) and nucleus (N)
where they exert their activity on host cell processes.
itors of host enzymes, RGD (Arginine–Glycine–Aspartic acid)-containing proteins,
and toxins that lead to host cell death.
Enzyme inhibitors counter hydrolytic enzymes (e.g. chitinases, glucanases,
and proteases) that are secreted by the host. Plant proteases contribute to pathogen
defence, for example susceptibility of Nicotiana benthamiana to P. infestans is
increased when the apoplastic protease C14 genes are silenced [8] . Furthermore,
tomato cysteine protease rcr3 mutants are more susceptible to P. infestans infection
than wild-type tomato [9] . Inhibiting apoplastic proteases is therefore an effective
virulence strategy of pathogens. Rcr3 activity is reduced by the extracellular protease
inhibitors EPIC1 and EPIC2B, which also inhibit other proteases, for example
C14 [8,9] and PIP1 [10] . The EPICs show signs of recent evolution in P. infestans [10] ,
and also its host target, potato C14, is under diversifying selection [8] , indicating
these apoplastic effectors are locked in an evolutionary arms race. Whether
oomycetes secrete inhibitors to arm themselves against host hydrolytic enzymes

12 Chapter 1
or to protect their secreted proteinacious effectors from degradation remains to be
determined.
A second type of apoplastic effectors interferes with adhesion, and possibly
signalling, between host cell wall and plasma membrane, for example IPI-O of
P. infestans that seems to act at two cellular locations; inside the host cell, to
suppress defence, and extracellularly. The IPI-O RGD-motif disrupts the adhesion
between cell wall and plasma membrane [11] , possibly by binding to the Arabidopsis
legume-like lectin receptor kinase LecRK-I.9 [12] . Arabidopsis lecRK-I.9 mutants
and IPI-O overexpression lines are more susceptible to Phytophthora brassicae,
are altered in cell wall-integrity, and impaired in callose deposition [13] . IPI-O
mediated disruption of plasma membrane-cell wall contacts could interfere with
cell-wall-associated defences, thereby promoting infection.
A third type of apoplastic effectors represents toxins that are produced by
oomycetes that are necrotrophic (e.g. certain Pythium species) or hemibiotrophic
(most Phytophthora species). These toxins act in an offensive way by triggering
host cell death that could favour the necrotrophic phase of development. Two
families of toxic proteins are encoded in the genomes of most oomycetes; the
PcF/SCR proteins that are small, secreted, hydroxyproline-containing proteins,
and the NEP1-like proteins (NLPs), that are related to the necrosis and ethylene
inducing peptide (NEP1) from the fungus Fusarium oxysporum. NLPs can induce
cell death in dicots by acting on the outside of the host cell membrane, as shown
for NLP Pp
of Phytophthora parasitica [14] . The crystal structure of NLP Pya
from the
necrotroph Pythium aphanidermatum revealed structural homology to cytolytic
actinoporins [15] , suggesting that NLPs insert into the host membrane to form pores.
The cytolytic activity could be responsible for the necrotic response, however, cell
death induction by NLPs requires host defence signalling and active host metabolism
[14,16] . It was surprising to find a family of NLP genes in the obligate biotroph
H. arabidopsidis, as this pathogen is dependent on living plant cells and does not
induce host cell death. One of nine H. arabidopsidis NLPs (HaNLP3) belongs to
the clade of necrosis-inducing NLPs, but is not capable of inducing cell death [4] .
Also Phytophthora species have many non-cytolytic NLPs that, like HaNLP3,
could have an alternative function. One proposed alternative function is attachment
to the host, as NLP Pya
also shows structural homology to fungal lectins that could
bind surface-exposed compounds such as glucans [15] .
Breaking in
The (hemi)biotrophic oomycetes engage in an intimate relation with plant cells by
forming haustoria that serve a dual role; nutrient uptake from the host and delivery
of effectors to the host. Haustoria penetrate the host cell wall, invaginate the host

How do oomycete effectors interfere with plant life
13
membrane, contain specific membrane proteins required for pathogenicity [17] , and
have been implicated as a site of effector production and secretion [18] . Effectors
are secreted from the pathogen, and those that carry host-translocation signals are
transported into the plant cell.
Two classes of host-translocated effectors are currently known in oomycetes.
The first, the RXLR-effectors, are named after a four amino acid (Arginine, any
amino acid, Leucine, Arginine; in short: RXLR) motif that was found in 2005 to
be common among all then known oomycete avirulence (AVR) proteins, which are
recognised inside the host cell [19] . The RXLR-effectors have an N-terminal domain
consisting of a signal peptide, an RXLR-like motif, an optional amino acid motif
(consisting of two glutamic acid residues and an arginine residue, often preceded
by an aspartic acid residue) known as the dEER-motif, and a C-terminal effector
domain. A stunning 563 RXLR-effectors are predicted for P. infestans [2] , whereas
they are absent in Pythium ultimum [3] and Aphanomyces euteiches [20] , suggesting
these effectors have recently evolved within the Peronosporales [3] .
RXLR-effectors of different species show extensive sequence divergence,
though in P. sojae and P. ramorum most have been suggested to belong to a single
superfamily [21] . There is little overlap in the RXLR gene repertoire between the
different sequenced Phytophthora species, but also compared to H. arabidopsidis,
suggesting recent species-specific evolution and expansion [21] . Accelerated evolution
of effector genes was confirmed by analysis of genomes of four P. infestans
sister species [5] .
The RXLR-motif has been shown to be involved in translocation into the
host [18,22] . A possible mechanism by which this occurs is by binding of the motif
to phosphatidylinositol-3-phosphate (PI3P) and subsequent lipid-raft dependent
uptake [23] . However, this mechanism and its supporting experiments are strongly
debated. Other mechanisms of binding/entry of effectors, for example via other
negatively charged molecules, are being proposed but are, however, not yet
published. Entry after binding phospholipids has been shown for effectors from
different pathogens, including fungi [23] . However, for one of the tested fungal
effectors, AvrL567, lipid binding could not be reproduced by another laboratory,
though background binding of phospholipids was observed [24] . Such lipid binding
assays appear technically demanding and condition-dependent, warranting caution
when interpreting their results. Furthermore, lipid binding properties of AvrM
can be separated from the sequence required for uptake [24] . These observations on
AvrL567 and AvrM do not support the idea that lipid binding by the RXLR-like
amino acid motifs is required for translocation of fungal effectors. Indications
that the RXLR-motif may not be essential for uptake of oomycete effectors are
found in effectors of Pseudoperonospora cubensis, in which the EER-motif has a
more important role than the RXLR-motif or RXLR-like-motif QXLR, which is

14 Chapter 1
prevalent in this species [25] . Furthermore ATR5 of H. arabidopsidis has no clear
RXLR-motif, but does have an EER-motif and is translocated as it is recognised
intracellularly [26] . More examples of variants of the RXLR-motif or EER-motif
found in proteins that can translocate into the host cell will undoubtedly emerge
in the near future, enlarging the known effector arsenal of oomycete species even
further.
The second class of host intracellular effectors encompasses the Crinklers.
These effectors have conserved N-termini, which contain a signal peptide, an
LXLFLAK-motif followed by a conserved DWL-domain and an HVLVXXP-motif
[2] . The LXLFLAK-motif has been shown to be required for host intracellular
localisation of the Crinklers, as this N-terminal motif, but not mutated forms,
enable transport of the C-terminal half of AVR3a into the plant cell, where AVR3a
triggers cytoplasmic recognition in the presence of the resistance protein R3a [27] .
Like the RXLR-effectors, the modular C-terminal effector domains of the Crinklers
are highly diverse. Several C-terminal domains of P. infestans Crinklers have been
shown to target the host nucleus, and/or induce cell death when expressed within
plant cells [2,27] . The rapid evolution and expansion of genes encoding host-translocated
effectors stresses the presumed importance of these proteins in establishing a
successful infection. The positive selection, which is observed for many effectors,
highlights the evolutionary adaptation to overcome the immune system of the plant.
Box 1: Plant defence in brief
A first line of activated plant defence against invading microorganisms is triggered
by pathogen-associated molecular patterns (PAMPs) that are recognised by pattern
recognition receptors (PRRs), inducing PAMP-triggered immunity (PTI) [45] .
Oomycetes secrete several proteins that can act as PAMPs, for example elicitins,
transglutaminase, and cellulose-binding proteins [46] . Oomycete cell wall derived
fragments, for example β-glucan fragments, can also act as PAMPs [47] . The BAK1
PRR co-receptor is required for immunity to P. infestans in Nicotiana benthamiana
[48] , however, no plant genes encoding PRRs that detect oomycete PAMPs
have been cloned so far. Pathogens have evolved effector proteins to suppress PTI
and have thereby established effector-triggered susceptibility (ETS). Plants have
evolved resistance proteins to recognise these effectors or their activity. This second
line of defence, named effector-triggered immunity (ETI), confers race-specific
resistance within plant species and can be very effectively phenotyped. This has
been instrumental in the cloning of many oomycete effector genes (see Table 1),
which are also named avirulence (AVR) genes as they confer incompatibility on
host plants that carry the corresponding resistance (R) gene.

How do oomycete effectors interfere with plant life
15
Quelling resistance
The suppression of plant defence, that is PAMP-triggered immunity (PTI) that is
activated upon invasion of pathogens (see Box 1), is key to successful infection of
the host. This is well documented for bacterial pathogens that use host-translocated
(type III-secreted) effectors to interfere with host defence responses. It is evident
that oomycete pathogens actively suppress innate immunity too. A striking example
is the suppression of host cell death in the Arabidopsis lesion mimic mutant lsd1 by
the white rust pathogen Albugo candida [28] . Moreover, for many effectors that have
been predicted from oomycete genomes a putative defence-suppressive or susceptibility-inducing
activity has been found. However, the molecular mechanisms by
which host-translocated effectors interfere with plant life are still largely unknown.
Table 1 gives an overview of oomycete host-translocated effectors that are active in
plant cells, either as suppressors or as inducers of defence.
A challenging goal is to determine the function of oomycete effectors, as the
availability of powerful bioassays is limited. Most currently used assays monitor
the suppression of PTI. An elegant method is the use of Pseudomonas bacteria for
type III delivery of oomycete effectors in the host. Bacteria that translocate the H.
arabidopsidis ATR1 and ATR13 proteins were able to grow to higher densities indicating
that susceptibility of the plant was enhanced [29] . ATR13 suppresses PTI as
transgenic plants showed reduced PAMP-triggered callose deposition [29] . A similar
activity was observed for the RXLR29 protein, that is an isolate-specific effector
of H. arabidopsidis [30] . Another method to suppress PTI responses is by Agrobacterium-mediated
transient expression of effector genes. Co-expression of the P.
infestans AVR3a protein was shown to suppress PTI-associated cell death induced
by the elicitin INF1 [31] . Expression of the C-terminal domain only, without signal
peptide and RXLR-DEER domain, was sufficient for AVR3a effector function. An
alternative way to test effectors in planta is by particle bombardment, for example
by monitoring the suppression of cell death induced by the mouse pro-apoptotic
protein BAX. Reduction of cell death was observed by co-bombardment with the
P. sojae AVR1b gene which encodes a protein with conserved C-terminal W and
Y motifs that are present in many Phytophthora effectors [32] . These motifs are
required for suppression of cell death, suggesting that this activity is a major function
of oomycete effectors. Cell death-suppression assays have been used by many
groups to test candidate effectors. A screen of 32 P. infestans RXLR effectors for
suppression of elicitin INF1-induced cell death was used to reveal effector activity
of the PexRD8 and PexRD36 45‐1
RXLR proteins [33] . One would expect that the
suppression of defence is vital to the virulence of oomycetes, however, in vivo data
that support this idea are missing for most effectors as knocking out genes is not an
established method in oomycete research. Nevertheless, gene silencing of Avr3a in

16 Chapter 1
Table 1: Host-translocated effectors of oomycete pathogens with described in planta effects. Class:
CRN; Crinkler effector, RXLR; RXLR-motif effector, RXLR; RXLR-like motif effector. ETI:
corresponding in planta R–gene. Species (Sp.): Ae; Aphanomyces euteiches, Ha; H. arabidopsidis, Pi;
P. infestans, Ps; P. sojae
Effector Sp. Class ETI Effects Target Ref.
AeCRN5 Ae CRN Cell death (via nucleus)
[27]
ATR1 Ha RXLR AtRPP1 Contributes to virulence
[19]
ATR13 Ha RXLR AtRPP13
Suppresses callose
deposition and ROS
secretion
[49]
AVR1 Pi RXLR R1
[50]
AVR2 Pi RXLR R2
[50]
AVR3a Pi RXLR R3a Stabilises host E3-ligase CMPG1
[34,51]
AVR3b/10/11 Pi RXLR R3b/R10/R11
[52]
AVR4 Pi RXLR R4
[53]
AVRBlb2 Pi RXLR Rpi-Blb2
Interferes with protease
secretion
[50]
IPI-O1 Pi RXLR
Rpi-Blb1/Rpi- Disruption PM-CW
Sto1/Rpi-Pta1 integrity
IPI-O2 Pi RXLR
Rpi-Blb1/Rpi-
Sto1/Rpi-Pta1
[36]
IPI-O4 Pi RXLR
Suppresses IPI-O1/IPI-O2
ETI
[37]
PexRD36 45‐1
Pi RXLR Suppresses INF1 PTI
[33]
PexRD8 Pi RXLR Suppresses INF1 PTI
[33]
SNE1 Pi RXLR
Suppresses Avr3a ETI and
NLP-induced cell death
[38]
Various CRNs
(e.g. CRN Pi CRN Cell death (via nucleus)
[2,27]
1,2,8,16)
AVR1a Ps RXLR Rps1a
[54]
AVR1b-1 Ps RXLR Rps1b
Suppresses BAX-induced
cell death
[32][55]
AVR1k Ps RXLR Rps1k
[50]
AVR3a Ps RXLR Rps3a
[54]
AVR3c Ps RXLR Rps3c
[56]
AVR4/6 Ps RXLR Rps4/Rps6
[57]
PsCRN115 Ps CRN
Suppresses PsCRN63/
NLP-induced cell death
[35]
PsCRN63 Ps CRN Cell death (via nucleus)
[35]
LecRK-I.9 [12,13,36]

How do oomycete effectors interfere with plant life
17
P. infestans [34] , and of the Crinklers PsCRN115 and PsCRN63 in P. sojae resulted in
reduced virulence [35] .
Other RXLR effectors are able to suppress cell death that is associated with
effector triggered immunity (ETI, see Box 1). IPI-O4, a sequence divergent
member of the P. infestans IPI-O family, can suppress cell death induced by variants
of IPI-O1 and IPI-O2 (now renamed to AVR-blb1) in potato plants carrying
the resistance gene Rpi-blb1 [36,37] . A broad ETI suppressive activity was detected
for suppressor of necrosis 1 (SNE1), a P. infestans protein with a RXLR-like
motif (RQLG) [38] . SNE1 was able to suppress ETI triggered by the recognition
of avirulence proteins from oomycetes (AVR3a), bacteria (AvrPto), fungi (Avr9)
and viruses (PVX coat protein). Furthermore, it also suppressed NLP-induced
cell death. As SNE1 expression is high during the biotrophic stage, and drops
when NLP expression rises, SNE1 could be important in timing the onset of the
necrotrophic phase.
For most of the effectors discussed a virulence target in the host cell has
not yet been identified. An exception is the well studied P. infestans AVR3a
protein that targets a host ubiquitin E3-ligase, CMPG1 [34] . CMPG1 is one of
three host ubiquitin E3-ligases known to be involved in plant defence [39] . AVR3a
manipulates the host ubiquitin proteasome system by stabilising CMPG1 and
suppresses plant immunity. More oomycete effectors are expected to act on the
ubiquitination systems of the host, however, recognisable domains are absent in
predicted host-translocated effectors. Effectors could have structural similarities to
ubiquitination-related proteins, for example the bacterial AvrPtoB effector that was
recognised as an E3 ligase based on its structure, rather than homology [40] .
Sweet rewards
Interfering with plant metabolism is another anticipated activity of oomycete
pathogens, especially in biotrophic interactions. In contrast to hemibiotrophs, that
switch to necrotrophy in the course of infection possibly by using NLPs and other
effectors that trigger cell death, obligate biotrophs do not kill their host cells, but
rather keep plants cells alive while they retrieve nutrients from the host. Analysis
of metabolic pathways, based on predicted oomycete proteomes has confirmed that
the Phytophthora and Pythium species are autotrophic (besides their requirement
of sterols) and can hence make use of a broad range of nutrients that are available
in the host [1‐3] . By contrast, the obligate biotroph H. arabidopsidis lacks several
important enzymes in nitrate and sulfate metabolism suggesting that it is dependent
on the host to provide other sources of reduced nitrogen and sulfur [4] .
One can envision that effectors not only act on plant defence pathways, but
also interfere with host metabolic pathways or transporters, redirecting nutrients

18 Chapter 1
and changing host metabolism. Bacterial and fungal pathogens manipulate host
sugar transport by activating SWEET transporter genes during infection. In rice, a
bacterial effector of the TALE class binds to the OsSWEET11 promoter to activate
the sugar transporter gene [41] . Changes in host physiology and metabolism that are
possibly manipulated by pathogen effectors have been observed in oomycete-infected
plants, for example the repression of photosynthesis and induction of sink
status increasing the availability of assimilates for pathogens [42] . Genome-wide
expression studies of host responses during infection have, unfortunately, not
provided a clear picture of transcriptional changes related to host metabolism.
Comparison of a compatible and incompatible (plant is resistant) interaction of
Arabidopsis inoculated with H. arabidopsidis showed a large overlap in expression
changes of defence-associated genes between the treatments. By contrast, only
a limited number of 17 compatible-specific genes were identified of which none
could be directly linked to metabolism [43] , suggesting that pathogen-induced
metabolic reprogramming of the host is mainly post-transcriptional.
Conclusion
Recent findings highlight the unique complement of effectors that make the oomycetes
such remarkable pathogens. More and more effectors that act inside the host
cell are being identified while the debate on the mechanism of their translocation
continues. The next step is to unravel their effect on host processes and the molecular
mechanisms by which they carry out their virulence function. The discovery of
CMPG1 as a host target is an important first step towards understanding the activity
of the oomycete effector complement. Major challenges remain the development of
robust effector bioassays and gene knockout protocols for oomycetes, in particular
for the obligate biotrophs. Emerging studies on host protein-effector interactors
and structural data on effectors will be instrumental in elucidating the functions
of effectors. Plant-oomycete interactions are reaching a complexity that requires
a systems biology approach [44] that, as a bonus, will also provide better insights in
the physiology of the plant and the host immune network.
Acknowledgements
JHMS is supported by a grant from TTI-Green Genetics. We thank the reviewers
and editors for constructive comments on the manuscript.

How do oomycete effectors interfere with plant life
19
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oomycete plant pathogen genomes reveals unique protein organization. Plant Physiology 155,
628-44.

20 Chapter 1
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triggers RPP5-mediated defense in Arabidopsis. Molecular Plant-Microbe Interactions 24,
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27 Schornack S, Van Damme M, Bozkurt TO, Cano LM, Smoker M, Thines M, Gaulin E, Kamoun S
& Huitema E (2010) Ancient class of translocated oomycete effectors targets the host nucleus.
Proceedings of the National Academy of Sciences of the United States of America 107, 17421-6.
28 Cooper AJ, Latunde-Dada AO, Woods-Tör A, Lynn J, Lucas JA, Crute IR & Holub EB (2008)
Basic compatibility of Albugo candida in Arabidopsis thaliana and Brassica juncea causes broadspectrum
suppression of innate immunity. Molecular Plant-Microbe Interactions 21, 745-56.
29 Sohn KH, Lei R, Nemri A & Jones JDG (2007) The downy mildew effector proteins ATR1 and
ATR13 promote disease susceptibility in Arabidopsis thaliana. The Plant Cell 19, 4077-90.
30 Cabral A, Stassen JHM, Seidl MF, Bautor J, Parker JE & Van den Ackerveken G (2011)
Identification of Hyaloperonospora arabidopsidis transcript sequences expressed during infection
reveals isolate-specific effectors. PLoS ONE 6, e19328.
31 Bos JIB, Kanneganti T-D, Young C, Cakir C, Huitema E, Win J, Armstrong MR, Birch PRJ
& Kamoun S (2006) The C-terminal half of Phytophthora infestans RXLR effector AVR3a is
sufficient to trigger R3a-mediated hypersensitivity and suppress INF1-induced cell death in
Nicotiana benthamiana. The Plant Journal 48, 165-76.

22 Chapter 1
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Thakur PB, McDowell JM, Wang Y & Tyler BM (2008) Conserved C-terminal motifs required for
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1118-33.
33 Oh S-K, Young C, Lee M, Oliva R, Bozkurt TO, Cano LM, Win J, Bos JIB, Liu H-Y, Van
Damme M, Morgan W, Choi D, Van der Vossen EAG, Vleeshouwers VGAA & Kamoun S (2009)
In planta expression screens of Phytophthora infestans RXLR effectors reveal diverse phenotypes,
including activation of the Solanum bulbocastanum disease resistance protein Rpi-blb2. The Plant
Cell 21, 2928-47.
34 Bos JIB, Armstrong MR, Gilroy EM, Boevink PC, Hein I, Taylor RM, Zhendong T, Engelhardt S,
Vetukuri RR, Harrower B, Dixelius C, Bryan G, Sadanandom A, Whisson SC, Kamoun S
& Birch PRJ (2010) Phytophthora infestans effector AVR3a is essential for virulence and
manipulates plant immunity by stabilizing host E3 ligase CMPG1. Proceedings of the National
Academy of Sciences of the United States of America 107, 9909-14.
35 Liu T, Ye W, Ru Y, Yang X, Gu B, Tao K, Lu S, Dong S, Zheng X, Shan W, Wang Y & Dou D
(2011) Two host cytoplasmic effectors are required for pathogenesis of Phytophthora sojae by
suppression of host defenses. Plant Physiology 155, 490-501.
36 Vleeshouwers VGAA, Rietman H, Krenek P, Champouret N, Young C, Oh S-K, Wang M,
Bouwmeester K, Vosman B, Visser RGF, Jacobsen E, Govers F, Kamoun S & Van der
Vossen EAG (2008) Effector genomics accelerates discovery and functional profiling of potato
disease resistance and phytophthora infestans avirulence genes. PLoS ONE 3, e2875.
37 Halterman DA, Chen Y, Sopee J, Berduo-Sandoval J & Sánchez-Pérez A (2010) Competition
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38 Kelley BS, Lee S-J, Damasceno CMB, Chakravarthy S, Kim B-D, Martin GB & Rose JKC (2010)
A secreted effector protein (SNE1) from Phytophthora infestans is a broadly acting suppressor of
programmed cell death. The Plant Journal 62, 357-66.
39 Van den Burg HA, Tsitsigiannis DI, Rowland O, Lo J, Rallapalli G, Maclean D, Takken FLW &
Jones JDG (2008) The F-box protein ACRE189/ACIF1 regulates cell death and defense responses
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40 Abramovitch RB, Janjusevic R, Stebbins CE & Martin GB (2006) Type III effector AvrPtoB
requires intrinsic E3 ubiquitin ligase activity to suppress plant cell death and immunity.
Proceedings of the National Academy of Sciences of the United States of America 103, 2851-6.
41 Chen L-Q, Hou B-H, Lalonde S, Takanaga H, Hartung ML, Qu X-Q, Guo W-J, Kim J-G,
Underwood W, Chaudhuri B, Chermak D, Antony G, White FF, Somerville SC, Mudgett MB &
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Nature 468, 527-32.
42 Berger S, Sinha AK & Roitsch T (2007) Plant Physiology meets phytopathology: plant primary
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43 Huibers RP, De Jong M, Dekter RW & Van den Ackerveken G (2009) Disease-specific expression
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44 Pritchard L & Birch P (2011) A systems biology perspective on plant-microbe interactions:
biochemical and structural targets of pathogen effectors. Plant Science 180, 584-603.
45 Jones JDG & Dangl JL (2006) The plant immune system. Nature 444, 323-9.
46 Kamoun S (2006) A catalogue of the effector secretome of plant pathogenic oomycetes. Annual
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47 Daxberger A, Nemak A, Mithöfer A, Fliegmann J, Ligterink W, Hirt H & Ebel J (2007) Activation
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48 Chaparro-Garcia A, Wilkinson RC, Gimenez-Ibanez S, Findlay K, Coffey MD, Zipfel C,
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49 Allen RL, Bittner-Eddy PD, Grenville-Briggs LJ, Meitz JC, Rehmany AP, Rose LE & Beynon JL
(2004) Host-parasite coevolutionary conflict between Arabidopsis and downy mildew. Science
306, 1957-60.
50 Tyler BM (2009) Effectors. In Oomycete Genetics and Genomics: Diversity, Plant and Animal
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Böhme U, Brooks K, Cherevach I, Hamlin N, White B, Fraser A, Lord A, Quail MA, Churcher C,
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52 Jiang RHY, Weide R, Van de Vondervoort PJI & Govers F (2006) Amplification generates
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54 Qutob D, Tedman-Jones J, Dong S, Kuflu K, Pham H, Wang Y, Dou D, Kale SD, Arredondo FD,
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55 Shan W, Cao M, Leung D & Tyler BM (2004) The Avr1b locus of Phytophthora sojae encodes an
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56 Dong S, Qutob D, Tedman-Jones J, Kuflu K, Wang Y, Tyler BM & Gijzen M (2009) The
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57 Dou D, Kale SD, Liu T, Tang Q, Wang X, Arredondo FD, Basnayake S, Whisson S, Drenth A,
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23, 425-35.

25
Outline
The aim of the research described in this thesis was to identify and functionally
analyse effectors of downy mildews, and was performed as part of a larger research
project entitled “Novel approaches for resistance breeding using pathogen effectors
and their host plant targets: towards durable resistance to Bremia in lettuce”.
Effectors were first identified in transcript sequences of the downy mildew
pathogen of Arabidopsis, H. arabidopsidis (Chapter 2). Transcriptome sequencing
proved to be a powerful tool for effector identification and revealed that the effector
arsenal differs between different isolates of the same pathogen species.
The Bremia lactucae – Lactuca sativa interaction was then investigated using
the 454 sequencing technology to analyse the transcriptome of Bremia-infected
lettuce and downy mildew spores, allowing for deep sampling of the Bremia
transcriptome (Chapter 3). Additionally, genomic DNA from Bremia spores was
sequenced to enable accurate selection of Bremia transcripts from the assembled
sequences. From these data >16,000 Bremia transcripts were assembled, of which
1023 were predicted to encode proteins that are secreted by Bremia and thus potentially
act on the host. Predicted effectors include 77 potential host-translocated
RXLR effectors and various types of potential apoplastic effectors.
The role of 34 candidate RXLR effectors in stimulating susceptibility was
investigated and described in Chapter 4. Transient expression of effector candidates
BLR16 and BLR27 significantly enhanced susceptibility of lettuce to Bremia
infection. A negative effect on host susceptibility was observed in leaf discs
transiently expressing BLR03. Analysis of the temporal expression of effectors
revealed the presence of BLR16 and BLR27 transcripts throughout infection, and
indicated that BLR03 expression strongly decreases from early infection onwards.
Effectors did not enhance susceptibility by repression of the biotic stress-response
genes of lettuce that were selected from transcriptome data. The identification of
susceptibility-enhancing effectors of Bremia opens up the way to investigate their
activity and host targets.
The recognition of Bremia effectors in Lactuca breeding lines was investigated
and described in chapter five. The effectors were transiently expressed in almost
130 different lines of Lactuca species that potentially contain novel sources of
resistance to Bremia. Two effectors containing a GXLR variant of the RXLR motif
were found to be recognised, and trigger ETI; BLG01 being recognised in many

26 Outline
L. saligna lines, whilst BLG03 was recognised in two Dm2-containing L. sativa
lines. BLG01 ETI was mapped to the short arm of chromosome 3 and BLG03 ETI
was shown to be linked to the Dm2 locus. Surprisingly, though these loci conferred
effector recognition, they did not confer resistance to the B. lactucae isolate from
which they were isolated.
The final chapter concerns a discussion of the work described in the thesis
and the use of effectors in the development of novel breeding strategies for more
durable resistance to downy mildew.

27
Chapter 2:
Identification of Hyaloperonospora arabidopsidis
transcript sequences expressed during infection
reveals isolate-specific effectors
Adriana Cabral 1 , Joost H. M. Stassen 1 , Michael F. Seidl 2,3 ,
Jaqueline Bautor 4 , Jane E. Parker 4 , Guido Van den Ackerveken 1,3
1
Department of Plant-Microbe Interactions, Department of Biology,
Utrecht University, Utrecht, The Netherlands
2
Theoretical Biology and Bioinformatics, Department of Biology,
Utrecht University, Utrecht, The Netherlands
3
Centre for BioSystems Genomics (CBSG), Wageningen, The Netherlands
4
Department of Plant-Microbe Interactions,
Max Planck Institute for Plant Breeding Research, Cologne, Germany
PLoS ONE (2011) 6: e19328.
doi: 10.1371/journal.pone.0019328

28 Chapter 2
Abstract
Biotrophic plant pathogens secrete effector proteins that are important for infection
of the host. The aim of this study was to identify effectors of the downy mildew
pathogen Hyaloperonospora arabidopsidis (Hpa) that are expressed during
infection of its natural host Arabidopsis thaliana. Infection-related transcripts
were identified from Expressed Sequence Tags (ESTs) derived from leaves of the
susceptible Arabidopsis Ws eds1-1 mutant inoculated with the highly virulent
Hpa isolate Waco9. Assembly of 6364 ESTs yielded 3729 unigenes, of which
2164 were Hpa-derived. From the translated Hpa unigenes, 198 predicted secreted
proteins were identified. Of these, 75 were found to be Hpa-specific and six
isolate Waco9-specific. Among 42 putative effectors identified there were three
Elicitin-like proteins, 16 Cysteine-rich proteins and 18 host-translocated RXLR
effectors. Sequencing of alleles in different Hpa isolates revealed that five RXLR
genes show signatures of diversifying selection. Thus, EST analysis of Hpa-infected
Arabidopsis is proving to be a powerful method for identifying pathogen
effector candidates expressed during infection. Delivery of the Waco9-specific
protein RXLR29 in planta revealed that this effector can suppress PAMP-triggered
immunity and enhance disease susceptibility. We propose that differences in host
colonization can be conditioned by isolate-specific effectors.

Isolate-specific effectors from Hyaloperonospora ESTs
29
Introduction
Plant pathogens secrete an arsenal of effector molecules that modulate host
responses to enable successful infection. Effector proteins constitute part of the
secretome of the invading organism and are regarded as being crucial for pathogenicity
[1] . Pathogen-derived effectors target different sites in host plant tissues.
While apoplastic effectors are secreted into the plant extracellular space, host-translocated
effectors are delivered into host cells after secretion from the pathogen [2–4] .
For successful colonization, several layers of defence have to be overcome by
the pathogen. An initial barrier is conferred by host membrane-resident receptors
recognizing pathogen-associated molecular patterns (PAMPs), molecules that are
structurally conserved among related pathogenic microorganisms and not present in
the host [5–7] . PAMP-triggered immunity (PTI) is a resistance response that generally
protects plants against a broad range of non-adapted microorganisms. Several
bacterial effector proteins delivered to host cells by the type III secretion system
(TTSS) have been shown to suppress PTI [8,9] . A second layer of defence (effector-triggered
immunity, ETI) can be activated through recognition of particular
pathogen effectors or their actions on host targets by Resistance (R) proteins. ETI
is a more acute plant reaction often involving programmed cell death at infection
sites. Effectors can modulate the ETI response or mutate to circumvent recognition
resulting in a co-evolutionary battle in which the pathogen attempts to evade host
resistance and new plant R genes evolve to restrict further pathogen growth [10,11] .
Therefore, pathogen effectors with high rates of gene loss, duplication or diversification
are likely to be elicitors and/or modulators of plant immunity depending on
the host genetic background they encounter [12,13] .
Some of the most highly co-evolved interactions are between plants and
biotrophic pathogens. At one end of the biotroph spectrum are hemibiotrophic
species that initially colonize living cells but then switch to necrotrophy. At the
other end are obligate biotrophs that maintain host cell integrity and depend
entirely on their host for growth and completion of their life cycle. Obligate
biotrophs have evolved sophisticated mechanisms for host cell manipulation and
defence suppression [14] . Characterizing the activities and targets of biotroph-secreted
effectors should therefore provide insights to how host-adapted pathogens
promote disease and avoid recognition.
The obligate biotroph Hyaloperonospora arabidopsidis (Hpa) naturally infects
the model plant Arabidopsis thaliana, causing downy mildew disease [15] . Hpa is
a highly specialized oomycete pathogen with a narrow host range. Analysis of
the Arabidopsis-Hpa interaction has been particularly informative because of the
extensive genetic variation in responses of different Arabidopsis accessions to a
correspondingly diverse set of natural pathogen isolates [16,17] . Strong differences

30 Chapter 2
in resistance of Arabidopsis accessions to particular Hpa isolates were found
to be conferred by R genes often residing at polymorphic loci [18–21] . Although
plant-infecting oomycetes exhibit a fungal-like morphology and feeding structures
(haustoria), they form a phylogenetically distinct group of eukaryotic pathogens
that, together with brown algae and diatoms, belong to the Stramenopile lineage
(heterokonts) [22] . The genomes of several agronomically important hemibiotrophic
oomycete pathogen species have been sequenced, such as Phytophthora sojae
(causing soybean root and stem rot), P. ramorum (sudden oak death) and P.
infestans (potato late blight) [23,24] . Recently, the genome sequence of the Hpa
isolate Emoy2 has also become available [25] . Extensive oomycete genome sequence
information combined with data from expression profiling of pathogen and host
genes at different infection stages is now serving as a basis to identify potentially
important pathogen effector genes [26–28] . To date, a number of oomycete effector
proteins triggering ETI have been identified [11,29–33] . Notably, these molecules
are characterized by a secretion signal followed by a conserved “RXLR” motif
(where X can be any amino acid residue) and often a stretch of acidic amino acids
ending with the motif “EER”. Whereas the RXLR motif is required for effector
translocation into the host cell, the C-terminal region comprises a more variable
“effector domain” [34–37] . ATR1 and ATR13 are two RXLR type effectors of Hpa
that are recognized by Arabidopsis R genes [11,30] . High levels of ATR1 and ATR13
polymorphism among Hpa isolates suggest that diversifying selection has driven
the evolution of both genes [11,13,30] .
Previous studies aimed at identifying Hpa pathogenicity genes by isolating
pathogen transcripts expressed during infection have so far resulted in the isolation
of only a few candidate effectors. A differential cDNA-amplified fragment
length polymorphism (AFLP) analysis was used by van der Biezen et al. [38] on
Hpa-infected Arabidopsis leaves leading to identification of 10 Hpa-derived cDNA
fragments. In another study, a suppression subtractive hybridization (SSH) strategy
was used to identify 25 Hpa-expressed genes from infected Arabidopsis [39] .
Here we report a transcript sequencing approach based on Expressed Sequence
Tag (EST) analysis of Hpa-infected Arabidopsis leaves. To increase the proportion
of Hpa transcripts in a mixed sample of plant and pathogen RNA we used a highly
virulent Hpa isolate (Waco9) to infect a hyper-susceptible Arabidopsis mutant
(eds1) [40] and collected tissues at a time point of maximum hyphal and haustorial
growth. From a set of 2164 Hpa unigenes we have identified and classified
Hpa-secreted proteins into several effector categories based on the presence of
characteristic domains/motifs. Eighteen of the Hpa proteins belong to the class of
host-targeted RXLR effectors. While several effector candidates are shared with

Isolate-specific effectors from Hyaloperonospora ESTs
31
other Hpa isolates, and in some cases oomycete species, six predicted effector proteins
from Waco9 are not detected in the genome of the sequenced isolate Emoy2,
highlighting the dynamic nature of Hpa pathogenicity.
Results
EST sequencing of Hpa-infected Arabidopsis tissue
Hpa isolates Emoy2, Emwa1, Noco2 and Waco9 were assessed for growth on the
Arabidopsis enhanced disease susceptibility 1 mutant Ws eds1-1 [40] . Microscopic
analysis of infected leaves after trypan blue staining revealed the extent of
pathogen growth. A higher level of colonization of Arabidopsis leaves, with
abundant hyphal growth and haustoria projections formed in adjacent plant cells,
was observed for Hpa isolate Waco9 compared to Emoy2 (Fig. S1) and other
isolates tested (results not shown). Waco9-infected leaves harvested at 5 dpi (before
sporulation) (Fig. 1A) were therefore used for the construction of a cDNA library.
Total RNA isolated from the Waco9-infected material revealed ribosomal
RNA (rRNA) peaks of Hpa and Arabidopsis (Fig. 1B). The observed peaks were
validated as rRNA originating from Hpa or Arabidopsis by comparing profiles
of infected leaves with those of RNA from Hpa conidiospores mixed in different
proportions with Arabidopsis leaf RNA (Fig. S2). This analysis showed that
~50% of RNA extracted from the Waco9-infected leaves was derived from Hpa.
Poly (A+) RNA was isolated from the infected leaf total RNA preparations and
size-fractionated cDNAs ranging from 500 to 5000 bp were used for cDNA library
construction.
7680 sequencing reactions corresponding to the 5′ end of the cDNAs were
performed. After vector trimming and removal of low quality sequences and
chimeras, 6364 ESTs remained ranging in length from 50 to 1000 nucleotides (nt).
A
0
20 30 40 50
Migration time (sec)
Figure 1: Hpa isolateWaco9-infected Arabidopsis seedlings used for cDNA library construction. (A)
Trypan blue staining of infected Arabidopsis leaves (Ws eds1-1) showing extensive hyphal growth in
the absence of asexual sporulation at 5 dpi. (B) Bioanalyzer profile of total RNA obtained from Hpa
Waco9-infected leaf material. The 28S rRNA peaks of Arabidopsis (At) and Waco9 (Hpa) are indicated.
B
Fluorescence
80
60
40
20
At
Hpa

32 Chapter 2
The majority (84%; 5321 sequences) of ESTs had a read length of more than 500 nt
(Fig. 2A). Assembly of ESTs yielded a total of 3729 unique sequences (unigenes)
consisting of 2810 (~75%) singletons and 919 (~25%) contigs with two or more
ESTs (Fig. 2B).
To define the origin of the unigene sequences, BLASTN searches were
performed against the genome sequences of Arabidopsis, Hpa, three oomycete
pathogens (P. infestans, P. sojae and P. ramorum) and the NCBI nr nucleotide
database. Almost all unigenes (3722; ~99.8%) showed significant similarity
(E

Isolate-specific effectors from Hyaloperonospora ESTs
33
remaining unigenes two had high identity scores with sequences of other non-plant
and non-oomycete organisms and seven did not show significant homology to
any sequence in the databases (unknown sequences in Fig. 2C), nor contained a
signal peptide in the predicted open reading frame and were therefore not further
analysed. Altogether, we defined 2164 unigenes as Hpa-derived to use them for
subsequently functional classification.
Identification of putative secreted Hpa proteins
Secreted proteins of fungal and oomycete plant pathogens have been shown to
function as pathogenicity factors [4,41,42] . We therefore performed a comprehensive
search for Hpa transcripts encoding secreted proteins. From the 2164 Hpa unigenes
a set of 198 unigenes (822 ESTs, 9.15% of unigenes) encoded proteins with a predicted
signal peptide as analyzed with SignalP software [43,44] , and without putative
transmembrane domains. The EST-derived unigenes are significantly enriched
(p = 4e−6) for transcripts encoding predicted secreted proteins when compared to
the genome wide percentage of 6.8% (Table S2).
To define which of the Hpa secreted proteins are shared with other organisms,
the 198 unigenes were compared to the genome sequences of three oomycete
pathogens (Phytophthora infestans, P. sojae, and P. ramorum) and sequences in
GenBank, excluding Hpa. Significant blast hits (E75%) were obtained for 123 unigenes (Fig. 3). The remaining 75 sequences
(38%) did not have a significant hit with other oomycetes or non-Hpa sequences
in GenBank, suggesting that these genes are Hpa-specific. As the Hpa genome
sequence is derived from isolate Emoy2 [25] and the ESTs isolated here are from
isolate Waco9, we searched for possible differences between these two isolates.
The 75 Hpa-specific unigenes were queried against the assembled Emoy2 genome
sequence and manually compared to Hpa trace files (http://www.ncbi.nlm.nih.
gov/BLAST) to search for sequences that might be missing from the Hpa genome
assembly. No significant hits were obtained for six sequences, suggesting that these
unigenes are present in Hpa isolate Waco9 but not in Emoy2.
A functional annotation of the 198 Hpa unigenes predicted to encode secreted
proteins was performed by comparison to the Pfam database of protein domains [45]
and by manual annotation to search for specific classes of effectors. No function
could be defined for 108 sequences that were therefore classified as unknowns.
Table S3 shows the putative functions or domains assigned to 90 unigene-encoded
proteins. A selection of categories potentially associated with pathogenicity
(adapted from Tyler et al. [23] ), and the number of ESTs and unigenes belonging
to each group, is shown in Table 1. Unigenes encoding putative pathogenicity
proteins (58 sequences) were classified into three categories: hydrolase enzymes,

34 Chapter 2
198 unigenes
NCBI nr database
(excluding Hpa - Emoy2)
Oomycetes
(proteome/assembly)
(excluding Hpa - Emoy2)
evalue cutoff 1e-5; >75% coverage
123 unigenes
75 unigenes
Hpa - specific
Hpa - Emoy2
(proteome/assembly/
trace files)
evalue cutoff 1e-10, identity ratio >80%
69 unigenes
6 unigenes
Hpa - Waco9 - specific
Figure 3: Scheme showing categorization of Hpa Waco9 unigenes encoding predicted secreted
proteins. Sequences with homologues in oomycetes (excluding Hpa) and other organisms are grouped
(123 sequences). The remaining 75 unigenes were used to search for homologues in the assembled
Emoy2 genome and trace files. A set of six unigenes with no significant similarity to any other sequence
is defined as Waco9-specific.
protection against oxidative stress, and effectors. These 58 unigenes, together with
the 108 sequences with unknown function, were then divided according to the
group of organisms in which homologues were identified. From the 108 unknown
sequences, 51 are categorized as Hpa-specific (Table 1). Homologues in other
oomycetes were identified for all unigenes predicted to function as hydrolases or in
protection against oxidative stress (Table 1), indicating that proteins in these classes
are conserved among oomycetes. We looked for various families of effectors that
are associated with the triggering or manipulation of host cell defences [46–48] . Putative
effector proteins formed the largest functional group identified, comprising 42
unigenes. In this category we assigned 16 proteins as Cysteine-rich (CR) proteins
and 18 as belonging to the RXLR family. The majority of both effector types (23
out of 34 unigenes) appear to be Hpa-specific since no related sequences were
detected in other oomycetes. Moreover, two CR proteins and four RXLRs were

Isolate-specific effectors from Hyaloperonospora ESTs
35
Table 1: Classification of predicted Hpa secreted proteins. The distribution in different pathogenicity
categories and organisms in which homologues were identified are shown. Functional classification is
based on Pfam searches and manual annotation.
Total
ESTs
Unigenes
Oomycetes specific
specific
Other Hpa-
Waco9-
Emoy2
Hydrolases 41 9 9 0 0 0
Cell Wall Degrading Enzymes 32 4 4 0 0 0
Serine proteases 5 1 1 0 0 0
Serine carboxypeptidases 2 2 2 0 0 0
Aspartyl proteinase/proteases 1 1 1 0 0 0
Cysteine protease/proteinases 1 1 1 0 0 0
Protection against oxidative stress 35 7 7 0 0 0
Glutathione s-transferases 1 1 1 0 0 0
Reductases 16 2 2 0 0 0
Glutaredoxins 3 1 1 0 0 0
Thioredoxins 15 3 3 0 0 0
Effectors 342 42 17 24 18 6
RXLRs 40 18 4 14 10 4
Cysteine-rich proteins 279 16 * 6 9 7 2
Elicitins 9 4 3 1 ** 1 0
Necrosis-inducing like proteins 3 2 2 0 0 0
Crinklers 1 1 1 0 0 0
Cyclophilins 2 1 1 0 0 0
unknowns 361 108 55 51 51 0
*
One predicted Cysteine-rich candidate has homology to Tetrahymena thermophila and to Hpa
sequences. No homologue was found in other oomycetes.
**
Elicitin HaELL2 is classified as Hpa-specific due to its extended specific C-terminal domain.
not identified in the Emoy2 genome suggesting they are isolate Waco9-specific.
Other classes of predicted effector proteins such as Necrosis-inducing like proteins,
elicitins, Crinklers and cyclophilin had homologues within other oomycetes, suggesting
that these sequences belong to a common core of putative effectors present
in oomycete organisms. The Crinkler identified carries a variation of the LxLFLAK
translocation motif (Fig. S3), which has also been described to be present in several
Crinklers of P. infestans [24] .
Elicitin signatures in Hpa
Elicitins (ELIs) are extracellular effectors characterized by a 98 amino acid
conserved domain with a core of six cysteines in a specific spacing pattern
allowing their classification into different groups. Elicitin-like proteins (ELLs)

36 Chapter 2
have more variation in the size and sequence of their elicitin domains [49] . Although
Pfam searches identified four ELL unigenes in Waco9 (Table 1), only three of
these sequences were further analysed (Fig. 4) since the fourth contained only
five cysteines and therefore did not classify as an ELI/ELL. The HaELL1-, 2- and
3-encoded proteins have fewer than 5% cysteine residues and are classified as
alpha-elicitins due to their acidic pI [50] . The different size and cysteine spacing
in the elicitin domain of these three HaELLs is shown in Fig. 4. While HaELL2
resembles Phytophthora ELL-1 proteins [49] , the Cys pattern in HaELL1 and 3
appears to be specific for Hpa. All three proteins have an extended C-terminal
region following the elicitin domain, a feature of other oomycete ELLs [49] . This
region is smaller in HaELL1 and 3 (57 and 53 amino acids, respectively) in comparison
to HaELL2 (137 amino acids). The C-terminal domain appears to have a
biased amino acid composition as it is rich in threonine, alanine and serine (Fig. 4).
The high abundance of threonine and serine residues in the C-terminal part of
HaELL1, 2 and 3 points to numerous potential sites for O-glycosylation (predicted
by NetOGlyc 3.1) that could link the proteins to the cell wall. A hydrophobic
region containing a GPI anchor was predicted in the C-terminal part of HaELL2,
suggesting that this protein might be anchored to the plasma membrane. O-glycosylation
sites and GPI anchor regions have been described for other Phytophthora
ELIs/ELLs [49] .
HaELL1
(175 aa)
C-23-C-23-C-4-C-14-C-22-C
97 aa
C
HaELL2
(175 aa)
N
C-16-C-22-C-4-C-14-C-18-C
85 aa
C
HaELL3
(175 aa)
N C-24-C-23-C-4-C-14-C-23-C
C1 C2
99 aa
Figure 4: Schematic representation of protein domains of three identified Hpa HaELLs. The predicted
signal peptide is shown in black. A region between the signal peptide and the elicitin domain found
in HaELL2 and 3, with respectively 23 and 8 amino acids, is shown (N). The pattern of cysteine
spacing and the size of the elicitin domain are depicted. The percentage of highly abundant amino acid
residues in the C-terminus is: HaELL1: T: 14%, A: 12%, S: 7%; HaELL2: T: 28%, A: 13%, S: 10%.
The C-terminus of HaELL3 is divided into two regions (C1 and C2). C1: S: 51%, T: 19%; C2: D;56%,
E:31%.
Hpa derived Cysteine-rich (CR) proteins
A number of CR proteins secreted by fungal pathogens have been shown to be
recognized by R proteins in resistant host plants [51–53] . The cysteines in these proteins
form disulphide bridges that contribute to their structural stability in the plant
apoplast, an environment rich in proteases. To identify HaCR candidates among

Isolate-specific effectors from Hyaloperonospora ESTs
37
the putative Hpa secreted proteins, we determined the relative number of cysteine
residues in the full-length translated sequences. A total of 16 HaCR proteins were
identified which contain more than 5% cysteines and range in size from 72 to 405
amino acids (Table 2). Nine of the HaCR candidates could be placed into two
groups based on the pattern and spacing of the cysteines (Fig. 5). The cysteine
motif in group I and II is repeated one or more times in most group members. As
shown in Tables 1 and 2, six HaCR candidates have homologues in other oomycete
pathogens. Candidates from Groups I and II do not have an obvious oomycete
counterpart. However for HaCR2 significant homology (blast E value

38 Chapter 2
Figure 5: Two groups of HaCR proteins identified with distinct cysteine spacing patterns. The boxes
show the pattern repeated in each protein.
HaCR1, represented by the highest number of ESTs (84) among the secreted
proteins, is a homologue of Ppat14 from Hpa isolate Maks9 [39] .
Classification of host-translocated Hpa RXLR proteins
RXLR proteins comprise a class of oomycete effectors that are translocated into the
plant cell [36] . All known oomycete effector proteins that are recognized by specific
plant R proteins belong to this class [11,29–33] . The Hpa unigenes encoding putative
secreted proteins were therefore mined for candidate RXLR effectors. Proteins containing
either an RXLR or RXLQ/RXLG motif in the mature protein were selected.
Variations in the last arginine of the RXLR still allows protein translocation into
the host cell [37] . We identified 18 RXLR candidates (including one RXLQ containing
protein) encoding relatively small proteins ranging from 115 to 340 amino
acids (Table 3). The distance between the RXLR/Q motif and the signal peptide
cleavage site varied from 15 to 51 amino acids indicating that the RXLR/Q motif

Isolate-specific effectors from Hyaloperonospora ESTs
39
Table 3: Sequence features of candidate Waco9 RXLR effector proteins.
Name
Hpa RXLR
Size RXLR
ESTs
gene IDs 1 (amino acids) distance 2 EER 3 Homologues 4
RXLR3 - 1 129 29 - Hpa-specific
RXLR4 - 3 134 29 - Waco9
RXLR5 - 1 340 30 - Oomycetes
RXLR6 HaRXL80 1 129 27 + (44) Hpa-specific
RXLR7 HaRXL17 1 285 20 + (32) Hpa-specific
RXLR9 HaRXL78 2 150 28 - Hpa-specific
RXLR12 - 3 125 28 - Waco9
RXLR13 HaRXL76 5 286 32 + (49) Hpa-specific
RXLR15 HaRXL77 3 129 15 + (37) Oomycetes
RXLR16
HaRXL30;
HaRXL79
3 198 28 + (41) Waco9
RXLR17 (RXLQ) HaRXL42 2 135 28 + (41) Hpa-specific
RXLR18 - 2 209 51 - Oomycetes
RXLR19 - 1 299 31 - Hpa-specific
RXLR20 HaRXL10 1 241 23 - Hpa-specific
RXLR21
HaRXL37;
HaRXL75
1 115 29 + (44) Oomycetes
RXLR22 - 1 137 29 - Waco9
RXLR23 HaRXL4 5 304 32 + (49) Hpa-specific
RXLR29 - 4 132 28 - Hpa-specific
1
Gene IDs refer to RXLR sequences identified in Emoy2 [25]
2
Distance to signal peptide cleavage site.
3
In brackets the distance to signal peptide cleavage site.
4
Homologues found based on blast searches as described for Figure 6.
is near the N-terminus. The presence of an acidic region (EER) downstream of the
RXLR motif was identified in eight RXLR candidates (Table 3) and two (RXLR3
and RXLR6) have a putative nuclear localization signal as predicted by Psort.
From the 18 RXLR sequences identified here, only four proteins have homology
with other oomycetes, indicating that the majority of the RXLR candidates are
Hpa-specific (Tables 1 and 3). Among these four RXLR proteins, RXLR5 and 18
showed a high degree of similarity with homologues in P. infestans (75% and 72%
identity, respectively, with 100% sequence coverage). From the 14 Hpa-specific
proteins, blast searches revealed that 10 RXLRs have corresponding genes in
Emoy2 (Tables 1 and 3). Further analysis of these sequences revealed that RXLR29
is represented by a null allele in Hpa Emoy2 caused by a frame-shift mutation
resulting in a premature stop codon (Fig. S4). For RXLR4, 12, 16 and 22 no significant
blast hits with the Emoy2 genome sequence were obtained (Tables 1 and 3). It
is possible that these RXLR genes are either highly polymorphic or absent from the
Emoy2 genome.

40 Chapter 2
Allelic diversity of RXLR effector candidate genes
Coding sequences of the 18 RXLR candidate effectors were deduced from seven
Hpa isolates. Table 4 shows the number of protein variants found for each RXLR
and their distribution among the different Hpa isolates. For example, RXLR3 is
represented by two allelic forms: Waco9, Noks1, Emco5 and Cala2 share variant
A, Emoy2 and Maks9 carry protein variant B and Hind2 has no RXLR3 gene.
Heterozygosity was also observed for some RXLRs (e.g. RXLR6 in Cala2 contains
both protein variants A and B). RXLR5 was the least variable gene with identical
proteins in all seven Hpa isolates.
Table 4: Allelic variants identified for 18 Hpa RXLR candidate proteins and their distribution among 7
Hpa isolates. The letters indicate protein variants present at each isolate (protein level). When 2 letters
are present it means that the Hpa isolate is heterozygous for that locus and has one copy of each allele.
Allele at the indicated Hpa isolate
Gene No. Alleles Cala2 Emco5 Emoy2 Hind2 Maks9 Noks1 Waco9
RXLR3 2 A A B - B A A
RXLR4 1 - - - A - - A
RXLR5 1 A A A A A A A
RXLR6 4 A,B C B D C C A
RXLR7 3 B C B B B B A
RXLR9 5 B;C E D B E D A
RXLR12 1 - - - - - - A
RXLR13 6 B A D E F C A
RXLR15 2 B B A;B B A B A
RXLR16 6 B C B;C D E F A
RXLR17 2 B B B B B B A
RXLR18 2 B A A A A B A
RXLR19 5 B C D E B D A
RXLR20 4 - A;B A C C D A
RXLR21 3 A A A;B C B B A
RXLR22 1 - - - - - - A
RXLR23 6 C D D E A;B F A
RXLR29 3 B B B B B;C B A
No allele sequences were amplified for RXLR12 and 22 in Emoy2 or in any
of the five other Hpa isolates, indicating that these are Waco9-specific. RXLR4
was only amplified from isolates Hind2 and Waco9. Although blast searches did
not reveal a significant hit for RXLR16 in the Emoy2 genome (Table 3), allele
sequences were obtained for Emoy2 as well as the other isolates. Due to a high
level of polymorphism between the RXLR16 protein sequences in Waco9 and
Emoy2, the blast hit obtained was excluded based on cut-off values.

Isolate-specific effectors from Hyaloperonospora ESTs
41
The RXLR29 gene was of particular interest because Waco9 is the only isolate
of these analysed that contains an intact full-length ORF. In the remaining six Hpa
isolates, RXLR29 displayed insertions/deletions giving rise to frame shifts resulting
in null alleles (Fig. S4). In Maks9 we also found two different truncated versions
of RXLR29. These results show that a functional RXLR29 protein is only present
in Waco9 suggesting that it has been counter-selected in the other Hpa isolates
examined.
Of the 13 RXLR candidate effectors with at least two different protein variants,
we defined the percentage of variable sites within the protein sequences (Fig. 6).
RXLR9, 13, 16, 19 and 23 are the most polymorphic effector proteins with more
than 10% variable sites among the isolates sequenced. The ratio of >1 non-synonymous
(dN) to synonymous (dS) nucleotide substitutions [54] in RXLR 9, 13, 16,
19 and 23 suggests that these genes are under positive selection to maintain amino
acid diversity (Table 5).
Figure 6: Polymorphic Hpa RXLR proteins. Numbers of variable sites were determined using Mega4
for RXLR proteins possessing two or more protein variants.
Hpa RXLR29 suppresses pathogen-induced callose deposition
Since only isolate Waco9 appears to have retained a functional RXLR29 protein,
we selected this gene to determine a potential effector activity. We used a bacterial
effector delivery vector (EDV) system which was previously shown to successfully
deliver the Hpa effector ATR13 to Arabidopsis leaf cells by fusion to the N-terminal
portion of a TTSS bacterial effector [42] . RXLR29 was cloned in the EDV system
and expressed in the Pseudomonas syringae pv tomato (Pst) DC3000ΔCEL mutant
strain which lacks the conserved effector locus (CEL) and is therefore unable to
efficiently suppress PTI [55,56] . Pathogen-induced deposition of callose at the cell
wall is used as a marker of PTI [57] . We therefore measured whether RXLR29
delivery affects the capacity of Pst DC3000ΔCEL to induce callose deposition
after infiltrating bacteria into leaves. In these experiments, YFP and ATR13 were

42 Chapter 2
Table 5: Ratio of non-synonymous (dN) and synonymous (dS) substitutions of RXLR genes. Nucleotide
sequences obtained for each RXLR candidate of Hpa isolates were used to calculate the ratio dN/dS.
Genes under positive selection exhibit a dN/dS ratio higher than 1 and a P-value

Isolate-specific effectors from Hyaloperonospora ESTs
43
A
ATR13 RXLR29 YFP
B
Amount callose spots
250
200
150
100
50
0
YFP
RXLR29 ATR13
Bacterial counts [Log (CFU/mg)]
7
6
5
4
3
2
1
0
YFP
ATR13
RXLR29
day 0 day 3
Figure 7: RXLR29 suppresses callose deposition
in bacteria-inoculated Arabidopsis leaves. Fiveweek-old
Col-0 leaves were hand-infiltrated with
1 x 108 cfu/ml Pst DC3000ΔCEL carrying YFP,
RXLR29 or ATR13, as indicated. Leaf samples
were taken at 12 h after infection and stained with
aniline blue to visualize callose (A). The number
of callose spots was quantified in each sample
(B). The experiment was repeated three times
with similar results.
Figure 8: RXLR29 enhances bacterial growth
in Arabidopsis leaves. Five-week-old Col-0
leaves were hand-infiltrated with 5×105 cfu/
ml Pst DC3000-LUX delivering YFP, ATR13
or RXLR29, as indicated. Bacterial growth in
leaves at 0 and 3 dpi was measured by number of
colony forming units (cfu) per mg of leaf tissue.
Error bars indicate the standard error of bacterial
counts. Enhanced growth was observed at day 3
for Pst delivering ATR13 or RXLR29 compared
to YFP (T-test p value

44 Chapter 2
frequency of ESTs encoding secreted proteins in interaction libraries [27] .
From the 198 Hpa secreted proteins, a putative function could be assigned to
90 sequences based on the presence of known domains/motifs, specific features
(e.g. relative number of cysteine residues) or similarity to known proteins (Table
S3). A set of 58 sequences comprising potential pathogenicity factors was further
classified into different categories of which the largest group (42 unigenes)
corresponded to putative effector proteins (Table 1). EST analysis has been shown
to be an effective method to identify pathogen genes encoding effector proteins.
For example, Crinklers were first described by analysing ESTs from Phytophthora
infestans [58] . Also, 25 Crinkler-like sequences and 17 ELIs/ELLs were identified in
a P. sojae EST data set [27] . Moreover, analysis of a haustorium specific EST library
of Melampsora lini, a fungal rust pathogen of flax, has enabled identification of
three secreted effector proteins that are recognized by specific R proteins [59] .
It is notable that no putative function could be assigned for 108 unigenes
corresponding to ~55% of the predicted secreted proteins identified in our study,
and therefore these sequences were classified as unknowns (Table 1). Further
characterization of the secreted proteins of unknown function should reveal new
aspects of the biology of oomycete pathogens as well as processes specific to Hpa
biotrophy, since ~47% of the unknowns (51 unigenes) appear to be Hpa-specific
sequences.
From the set of secreted Hpa proteins with a predicted function we identified
three Elicitin-like proteins. Although ELIs and ELLs have been described in
Phytophthora and Pythium [49,60] , it is likely that the number of oomycete species
in which these proteins are expressed will expand as more sequences become
available. Indeed, our blast searches identified a homologue of HaELL3 in
Saprolegnia parasitica. The cysteine spacing pattern allowed classification of
Phytophthora ELIs and ELLs in different groups [49] . Interestingly, HaELL2 has
the same pattern as some Phytophthora ELLs including INL1 (P. infestans) and
SOL1A (P. sojae) that belong to ELL-1 group. The spacing pattern of HaELL1 and
3 was not observed in Phytophthora. Further analysis of elicitins from different
oomycete species should establish if there are species-specific patterns of cysteine
spacing. Two beta-elicitins (cryptogein and cinnamomin) have been shown to
bind lipids [61,62] . The majority of the residues of cryptogein that interact with
ergosterol [63] are divergent in the three alpha HaELLs identified here as well as in
Phytophthora ELLs [49] . Therefore, ELLs may not bind sterols and their function in
the infection process remains unclear.
The 16 Cysteine-rich proteins identified in our survey belong to a specific class
of effectors with a high relative number of cysteine residues (>5%) and no homology
to other effectors [49,64] . The HaCRs are a heterogeneous group since some proteins
have homologues in other oomycetes, although the majority are Hpa-specific

Isolate-specific effectors from Hyaloperonospora ESTs
45
(Fig. 5; Table 2). So far no function could be assigned to the HaCR proteins based
on known domains. Blast searches against the Emoy2 genome sequence revealed
a high level of conservation of several HaCR proteins between these two isolates.
Analysis of more Hpa isolates will reveal whether this degree of conservation is
maintained in other isolates. Only HaCR7 was more divergent between the isolates
Waco9 and Emoy2 (Table 2). It is worth noting that HaCR6 and 16 are not found
in the Emoy2 genome, suggesting that a different combination of HaCR proteins
might be present in each Hpa isolate.
The majority of the 18 RXLR candidate effectors identified in our study were
Hpa-specific (Table 1). Five RXLR candidates comprise divergent protein variants
in seven Hpa isolates (Fig. 6) and significant numbers of non-synonymous relative
to synonymous nucleotide substitutions. These effector candidates add to a number
of interesting RXLR genes that appear to be under diversifying selection [12] including
the two Hpa effectors ATR1 and ATR13, known to that trigger ETI [11,30] .
We identified variations in the set of effectors produced by different Hpa
isolates. Six Waco9 effectors (two HaCRs and four HaRXLRs) are not present in
Emoy2, as determined by comparison with the Emoy2 genome sequence. Also,
allele sequencing in seven Hpa isolates revealed that three RXLRs are so far only
found in Waco9. The presence of an effector in some but not all isolates suggests
that the gene has become lost during host-pathogen co-evolution to avoid triggering
ETI. This has been described for effectors of different pathogens, including
Avr4 from Phytophthora infestans [65] and Avr2 from Cladosporium fulvum [66] , of
which truncated forms that are not recognized by R proteins have been identified
in several isolates [65] . However, delivery of RXLRs 12, 22 and 29 to leaves of 12
different Arabidopsis accessions using the EDV system did not reveal an obvious
host cell death response which would typify ETI (unpublished data). This may be
because the bacterial delivery system dampens recognition or doesn’t permit full
expression of ETI responses to specific Hpa effectors. Alternatively, isolate-specific
effectors might affect colonization by different Hpa isolates by interfering mostly
with host PAMP-triggered defences. Our finding that RXLR29, an effector that is
present only in the highly virulent Hpa isolate Waco9, is able to suppress PTI and
enhance susceptibility to bacterial infection, supports this idea. The categorization
of different effector protein types expressed by Hpa Waco9 during Arabidopsis
leaf tissue colonization and before the developmental transition to asexual and
sexual sporulation has allowed us to select effector candidates for further functional
studies on interference with the host immune system. The activities and interactions
of Waco9-derived effectors as well as the extensive allelic diversity of individual
RXLR genes among Hpa isolates and oomycete pathogen species provides a
rich source of material to trace the co-evolutionary history of this plant-biotroph
system.

46 Chapter 2
Materials and Methods
Hpa isolates and plant material
Hpa isolates used in this study were originally collected from Arabidopsis populations
within the UK (isolates Cala2, Emwa1, Emco5, Emoy2, Hind2, Maks9,
Noco2, Noks1) and the Netherlands (Waco9) [16,18,67,68] . Arabidopsis plants were
grown at 22°C with ~75% relative humidity (RH) and a 10 h light period. For Hpa
infections, conidiospore suspensions (5×104 conidiospores.ml -1 ) were spray inoculated
on 2-week-old Arabidopsis seedlings. Plants were allowed to dry for 1 h and
kept at 100% RH for 24 h in a growth chamber with 10 h light at 16°C. Plants were
then moved to ~75% RH for an additional 4 to 6 days to delay asexual sporulation.
Hpa growth on Arabidopsis leaves was visualized on whole-leaf mounts stained
with trypan blue as described previously [67] and examined by differential-interference
contrast microscopy.
RNA isolation and cDNA library construction
For RNA isolations, infected leaf material was ground to a fine powder in liquid
nitrogen. Total RNA of Waco9-infected Ws eds1-1 plants was isolated using the
RNeasy Plant Mini Kit (Qiagen), following manufacturer’s instructions. Poly (A+)
RNA was purified from 1.3 mg of total RNA using dynabeads oligo (dT)25 (Dynal
Biotech). To eliminate rRNA contamination, the mRNA was purified twice. RNA
concentrations were determined on a UV mini 1240 spectrophotometer (Shimadzu)
and quality was assessed with the bioanalyzer 2100 using the RNA 6000 Nano
Assay kit (Agilent Technologies). Poly (A+) RNA (5 µg) was used to construct a
directional cDNA library in the λ-Zap vector (ZAP-cDNA synthesis, GigapackIII
cloning kit, Agilent Technologies) following manufacturer’s instructions. cDNA
was synthesized containing EcoRI and XhoI sites at the 5′ and 3′ ends, respectively,
allowing unidirectional cloning of cDNA. Size fractionation of the synthesized
cDNA’s was performed and 12 fractions were collected and precipitated with 100%
ethanol. The pellet was resuspended in RNase-free water and verified on the Bioanalyzer
2100 using the DNA 7500 LabChip Kit (Agilent Technologies). Phagemid
DNA was excised without library amplification. DNA isolations and sequencing
were done by Macrogen (Korea). Sequencing reactions were performed from the 5′
end using a T3 promoter primer.

Isolate-specific effectors from Hyaloperonospora ESTs
47
Sequence processing and analysis
Base calling, quality clipping and vector screening were performed with pregap4,
which is part of the Staden sequence analysis package [69] . ESTs were assembled
into contigs using CAP3 [70] . To define sequence origins, the assembled sequences
were queried (BLASTN, e-value cutoff 1 e-5, no low complexity filtering) [71]
against versions 6, 8.3 and trace files of the Hpa genome [25] , version 8 of the TAIR
Arabidopsis genome [72] , version 1 of the Phytophthora infestans [24] , P. ramorum
and P. sojae [23] genomes and NCBI non-redundant (nr) nucleotide database [73] . EST
sequences were then split into subsets based on the best blast match. ESTs from Ha
were submitted to dbEST (NCBI).
The most likely ORF of the Hpa set of sequences was identified by translating
the assembled EST sequences and singletons in 3 positive frames and selecting the
longest ORF. Protein predictions shorter than 10 amino acids were discarded. For
selection of the secreted proteins, all protein models were trimmed to start with a
methionine. Signal peptide predictions were performed by SignalP version 3.0 [43,44] ,
using both the neural network method and the hidden markov model methods at
default cutoffs. Sequences with predicted transmembrane helices downstream
of the signal peptide determined by TMHMM version 2 (http://www.cbs.dtu.
dk/services/TMHMM/) [74] were discarded. Putative functions were assigned
by domain composition after scanning the sequences against Pfam [45] using the
gathering threshold as cut-off. Additionally, functions were manually assigned
based on homology derived by similarity matches to NCBI nr (using blast), amino
acid composition or presence of an RLXR, RXLQ or RXLG motif after the signal
peptide cleavage site (only considering proteins with 40 or more amino acids after
the RXL sequence). The number of effectors encoded in the Hpa genome was
either taken from the Hpa genome paper [25] , determined by Pfam searches, or by
manual annotation (e.g. for the number of cysteine residues). For the elicitins, the
pI was determined at http://www3.embl.de/cgi/pi-wrapper.pl. GPI anchor sites
were predicted by the program big-PI Plant Predictor [75] and potential sites for
O-glycosylation were predicted by NetOGlyc 3.1 [76] . Psort prediction (http://psort.
hgc.jp/) [77] was used to identify putative nuclear localization signals in RXLR
proteins. Sequences of the HaELL, HaCR and HaRXLR genes were submitted to
GenBank (accession numbers JF800099-JF800135).
Identification of Hpa- and isolate Waco9-specific sequences
For identification of secreted proteins specific to Hpa or to isolate Waco9,
similarity searches were conducted with BLASTP and TBLASTN with disabled
low complexity filtering and a fixed database size of 1.000.000 [70] . Sequences were

48 Chapter 2
queried against a local NCBI nr protein and nucleotide databases (downloaded
23rd June 2010) and a set of three oomycete genome sequences (P. infestans
version 1 [24] , P. sojae version 2, and P. ramorum version 2 [23] .Sequences with no
significant similarity against other organisms (Hpa sequences were excluded;
e-value cutoff 1e−5; covered for >75% to exclude hits with only local similarity)
were selected and defined as Hpa-specific sequences. The predicted proteome and
the genome assembly of Hpa isolate Emoy2 (versions 6.0 and 8.3) was searched
to identify sequences potentially specific for isolate Waco9. All sequences with
a significant hit (e-value cutoff 1e−10) and an identity ratio of >80% ((identity%
of alignment*length alignment)/length query) [26] were filtered. If two Waco9
sequences had the same Emoy2 sequence as a best hit, we excluded the better hit
and retained the other one. The remaining sequences were compared manually to
the Hpa Emoy2 trace files that also contain reads not present in genome assembly.
Sequences without significant blast hits were defined as Waco9-specific.
Hpa allele sequences and analysis
To sequence the RXLR alleles of Hpa isolates Cala2, Emco5, Emoy2, Hind2,
Maks9 and Noks1, genomic DNA was isolated from Hpa-infected Ws eds1-1
leaves using DNeasy Plant Mini Kit (Qiagen). Primer pairs (Table S1) flanking
or within the coding sequence were designed from Waco9 assembled sequences
and used to amplify alleles of the Hpa isolates from genomic DNA. If a single
amplification product was obtained, the PCR product was sequenced directly
using the amplification primers. If multiple PCR fragments were amplified from a
single isolate these were individually purified from gel using NucleoSpin Extract
II (Machery-Nagel) and sequenced. Obtained sequences that were not readable due
to amplification of different products of the same size, Phusion (Finnzymes)-amplified
PCR products were cloned in pENTR/D-TOPO (Invitrogen) and sequenced.
In cases where the obtained sequences were not full-length (3′or 5′ sequences
missing), new primers were designed based on the Emoy2 genome sequence
(Versions 6 and 8.3). When no PCR product was amplified, new reactions were
performed using up to three new primer sets.
The RXLR DNA and predicted protein sequences were analysed using Mega4
software [78] . Alignments of the obtained allele sequences (protein level) were performed
using the ClustalW option [79] and manually edited. The number of variable
sites was analysed by the Sequence Data Explorer tool. Alignments of the allele
sequences (nucleotide level) were used to calculate the rate of non-synonymous
(dN) and synonymous (dS) substitutions. The rates of substitutions were calculated
using the Nei and Gojobori’s method [80] , as implemented in the MEGA4 program.
Standard error was determined by 500 bootstrap replications. The null hypothesis

Isolate-specific effectors from Hyaloperonospora ESTs
49
of no selection (H0: dN = dS) versus the positive selection hypothesis (H1: dN >
dS) were tested using the Z-test: Z = (dN-dS)/ √(Var(dS)+Var(dN)).
RXLR29 delivery by Pseudomonas syringae
The coding sequences of Hpa Waco9 RXLR29 (without signal peptide) and YFP
were amplified by PCR and cloned in pENTR/D-TOPO (Invitrogen) using primers:
CACCATGGAGGTGGTCCTGATC (forward) and TTACTTGCCAGGACGCGC
(reverse) for RXLR29 and CACCATGGTGAGCAAGGGCGAGGAGCTGTTC
(forward) and AGTCTAGAGCTCTTACTTGTACAGCTCGTCCATGC (reverse)
for YFP. Following Gateway cloning procedures these genes were cloned into
pEDV6, a variant of the previously described pEDV3 [42] that has a gateway cassette
instead of a multiple cloning site (kindly provided by K. Sohn, G. Fabro and J.
Jones, Sainsbury Laboratory, Norwich, UK). Plasmids were mobilized from E. coli
DH5α to Pst DC3000ΔCEL or Pst DC3000-LUX, which has stable chromosomal
integration of the luxCDABE operon from Photorhabdus luminescens [81] , by
standard triparental mating using E. coli HB101 (pRK2013) as a helper strain. Pst
DC3000ΔCEL-ATR13 (Emco5) and Pst DC3000-LUX-ATR13 (Emco5) were
kindly provided by G. Fabro and J. Jones.
Callose staining and microscopic analysis
Leaves of 5-week-old Arabidopsis accession Col-0 plants were hand-infiltrated
with 1×10 8 cfu/ml Pst DC3000ΔCEL suspensions. A total of ~48 leaf samples were
taken for callose staining 12–14 h after infiltration. Leaves were cleared with 100%
ethanol, and re-hydrated and stained with aniline blue (0.05% in phosphate buffer
pH 8.0) for 24 h. Images were taken using an Olympus AX70 Microscope with UV
filter. Callose spots were counted using ImageJ (http://rsb.info.nih.gov/ij/) [82] .
Bacterial growth assay
Leaves of 5-week-old Arabidopsis accession Col-0 were hand-infiltrated with
a bacterial inoculum of 5×10 5 cfu/ml. Initially, PstDC3000-LUX was used for
assessment of bacterial growth by measuring increased luciferase activity as previously
published [81] . For colony counting, infected leaves were collected at 0 and
3 days after bacterial infiltration. A total of 12 leaves divided into three biological
replicates were harvested per sample and time point. Bacterial growth was measured
by grinding infected leaves and plating serial dilutions on solid KB medium
with appropriate antibiotics. Similar results were obtained in two independent
experiments.

50 Chapter 2
Acknowledgments
We thank Shinpei Katou, Joyce Elberse and Tale Sliedrecht for technical assistance,
Alessandro Guida and Henk van den Toorn for bioinformatics assistance, and Kee
Sohn, Georgina Fabro, and Jonathan Jones for kindly providing the EDV6 vector
and Pst ΔCEL mutant.

Isolate-specific effectors from Hyaloperonospora ESTs
51
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58 Chapter 2
Supplemental Information
A
B
C
D
Figure S1: Growth of Hpa Emoy2
and Waco9 isolates in Arabidopsis.
The level of colonization of
cotyledons of 2-week-old Arabidopsis
Ws eds1-1 seedlings infected with
Hpa isolates Emoy2 (A,B) and Waco9
(C,D) at 7 dpi is visualized by trypan
blue-staining and light microscopy.
Fluorescence
Fluorescence
60
50
40
30
20
10
0
120
100
80
60
40
20
0
At
120
25% Hpa 20% Hpa
100
20 25 30 35 40 45 50 55
Migration time (sec)
Hpa
80
50% Hpa 33% Hpa
Fluorescence
20 25 30 35 40 45 50 55 20 25 30 35 40 45 50 55
Migration time (sec)
Migration time (sec)
Fluorescence
60
40
20
0
80
60
40
20
0
20 25 30 35 40 45 50 55
Migration time (sec)
Figure S2: Determination of Hpa
rRNA peaks on the Bioanalyzer 2100.
Total RNA isolated from Hpa
conidiospores and Arabidopsis
leaves was mixed in different
proportions to allow identification
of the corresponding rRNA peaks of
Hpa and Arabidopsis in bioanalyzer
profiles. Peak sizes correlated with the
relative amount of plant and pathogen
total RNA.
HaCrinkler
(393 aa)
SP LRLYVAKR C
Figure S3: Schematic representation
of the Hpa Crinkler identified in the
Waco9 cDNA library.
The signal peptide (SP), the variable
CRN motif (LYVAK) and the
C-terminal domain (C) are shown.

Isolate-specific effectors from Hyaloperonospora ESTs
59
RXLR29_Emoy ATGCGTCTGTCTGC-ATCCTGTTCTTGATTGTGGCTCCCCTGCATCTTTGTGTCGGCGAG 59
RXLR29_Noks ATGCGTCTGTCTGC-ATCCTGTTCTTGATTGTGGCTCCCCTGCATCTTTGTGTCGGCGAG 59
RXLR29_Cala ATGCGTCTGTCTGC-ATCCTGTTCTTGATTGTGGCTCCCCTGCATCTTTGTGTCGGCGAG 59
RXLR29_Emco ATGCGTCTGTCTGC-ATCCTGTTCTTGATTGTGGCTCCCCTGCATCTTTGTGTCGGCGAG 59
RXLR29_Hind ATGCGTCTGTCTGC-ATCCTGTTCTTGATTGTGGCTCCCCTGCATCTTTGTGTCGGCGAG 59
RXLR29_Maks1 ATGCGTCTGTCTGC-ATCCTGTTCTTGATTGTGGCTCCCCTGCATCTTTGTGTCGGCGAG 59
RXLR29_Maks2 ATGCGTCTGTCTGCTATCCTGCCCTTGATTGTGGCTCCC-TGCATCTTTGTGTCGGCGAG 59
RXLR29_Waco ATGCGTCTGTCTGCTATCCTGCCCTTGATTGTGGCTCCCCTGCATCTTTGTGTCGGCGAG 60
************** ****** **************** ********************
RXLR29_Emoy GTGGTTCTGATCCCTGCGACGATGGAGAACCCACTTCTTCGTTCGGCTTCTTCTGCTGGT 119
RXLR29_Noks GTGGTTCTGATCCCTGCGACGATGGAGAACCCACTTCTTCGTTCGGCTTCTTCTGCTGGT 119
RXLR29_Cala GTGGTTCTGATCCCTGCGACGATGGAGAACCCACTTCTTCGTTCGGCTTCTTCTGCTGGT 119
RXLR29_Emco GTGGTTCTGATCCCTGCGACGATGGAGAACCCACTTCTTCGTTCGGCTTCTTCTGCTGGT 119
RXLR29_Hind GTGGTTCTGATCCCTGCGACGATGGAGAACCCACTTCTTCGTTCGGCTTCTTCTGCTGGT 119
RXLR29_Maks1 GTGGTTCTGATCCCTGCGACGATGGAGAACCCACTTCTTCGTTCGGCTTCTTCTGCTGGT 119
RXLR29_Maks2 GTGGTCCTGATCCCTGCGACGATGGAGAACCCACTTCTTCGTTCGGCTTCTTCTCCTGGT 119
RXLR29_Waco GTGGTCCTGATCCCTGCGACGATGGAGAACCCACTTCTTCGTTCGGCTTCTTCTGCTGGT 120
***** ************************************************ *****
RXLR29_Emoy GCTGG-GCACGCAACGACGGCCGATCCCTGCGAGAACTAAATTCAGCGGCTGGTATTGGC 178
RXLR29_Noks GCTGG-GCACGCAACGACGGCCGATCCCTGCGAGAACTAAATTCAGCGGCTGGTATTGGC 178
RXLR29_Cala GCTGG-GCACGCAACGACGGCCGATCCCTGCGAGAACTAAATTCAGCGGCTGGTATTGGC 178
RXLR29_Emco GCTGG-GCACGCAACGACGGCCGATCCCTGCGAGAACTAAATTCAGCGGCTGGTATTGGC 178
RXLR29_Hind GCTGG-GCACGCAACGACGGCCGATCCCTGCGAGAACTAAATTCAGCGGCTGGTATTGGC 178
RXLR29_Maks1 GCTGG-GCACGCAACGACGGCCGATCCCTGCGAGAACTAAATTCAGCGGCTGGTATTGGC 178
RXLR29_Maks2 GCTGGTGCACGCAACGACGGCCGATCCCTGCGAGAACTAAATTCAGCGGCTGGTATTGGC 179
RXLR29_Waco GCTGGTGCACGCAACGACGGCCGATCCCTGCGAGAACTAAATTCAGCGGCTGGTATTGGC 180
***** ******************************************************
RXLR29_Emoy GCGGAAATGTCGAAAGTAGTCTCCGAGTTCGGAGGACATTTCAAAGGGACAACAGGCACT 238
RXLR29_Noks GCGGAAATGTCGAAAGTAGTCTCCGAGTTCGGAGGACATTTCAAAGGGACAACAGGCACT 238
RXLR29_Cala GCGGAAATGTCGAAAGTAGTCTCCGAGTTCGGAGGACATTTCAAAGGGACAACAGGCACT 238
RXLR29_Emco GCGGAAATGTCGAAAGTAGTCTCCGAGTTCGGAGGACATTTCAAAGGGACAACAGGCACT 238
RXLR29_Hind GCGGAAATGTCGAAAGTAGTCTCCGAGTTCGGAGGACATTTCAAAGGGACAACAGGCACT 238
RXLR29_Maks1 GCGGAAATGTCGAAAGTAGTCTCCGAGTTCGGAGGACATTTCAAAGGGACAACAGGCACT 238
RXLR29_Maks2 GCGGAAATGTCGAAAGTAGCCTCCAAGTTTGGAGGACATTTCAAAGGGACAACAGGCACT 239
RXLR29_Waco GGGGAAATGTCGAAAGTAGTTTCCGAGTTCGGAGGACATTTCAAAGGGACAACAGGCACT 240
* ***************** *** **** ******************************
RXLR29_Emoy TCGGAGAGTGTTGCATCAAAGAAAGCCGAAGATGCAGCAATGGGGGCAGCAGATCGTGAT 298
RXLR29_Noks TCGGAGAGTGTTGCATCAAAGAAAGCCGAAGATGCAGCAATGGGGGCAGCAGATCGTGAT 298
RXLR29_Cala TCGGAGAGTGTTGCATCAAAGAAAGCCGAAGATGCAGCAATGGGAGCAGCAGATCGTGAT 298
RXLR29_Emco TCGGAGAGTGTTGCATCAAAGAAAGCCGAAGATGCAGCAATGGGAGCAGCAGATCGTGAT 298
RXLR29_Hind TCGGAGAGTGTTGCATCAAAGAAAGCCGAAGATGCAGCAATGGGAGCAGCAGATCGTGAT 298
RXLR29_Maks1 TCGGAGAGTGTTGCATCAAAGAAAGCCGAAGATGCAGCAATGGGGGCAGCAGATCGTGAT 298
RXLR29_Maks2 TCGGAGAGTGTCGCATCAAAGAAAGCCGAAGATGCAGCAATGAGGGCAGCAGATGATGAT 299
RXLR29_Waco TCGGAGAGTGTCGCATCAAAGAAAGCCAAAGATGCAGCAATGAGGGCAGCAGATGATGAT 300
*********** *************** ************** * ********* ****
RXLR29_Emoy GAAGGACCCATTTGGGCGACGAGAAAAGACCTCGAAGATGTTTTGAATGTTGGAAAAAAA 358
RXLR29_Noks GAAGGACCCATTTGGGCGACGAGAAAAGACCTCGAAGATGTTTTGAATGTTGGAAAAAAA 358
RXLR29_Cala GAAGGACCCATTTGGGCGACGAGAAAAGACCTCGAAGATGTTTTGAATGTTGGAAAAAAA 358
RXLR29_Emco GAAGGACCCATTTGGGCGACGAGAAAAGACCTCGAAGATGTTTTGAATGTTGGAAAAAAA 358
RXLR29_Hind GAAGGACCCATTTGGGCGACGAGAAAAGACCTCGAAGATGTTTTGAATGTTGGAAAAAAA 358
RXLR29_Maks1 GAAGGACCCATTTGGGCGACGAGAAAAGACCTCGAAGATGTTTTGAATGTTGGAAAAAAA 358
RXLR29_Maks2 GAAGGACCCATTTTTGCGACGAGAGAAGACCTCGATGATGTTATGAAAGCTGGAAAAGAA 359
RXLR29_Waco GAAGGACCCATTTTTGCGACGAAAGAAGACCTCGCTGATGTTTTGGCTGTTGGAAAAGAT 360
************* ******* * ********* ****** ** * ******* *
RXLR29_Emoy AAACTGAC-AAGAAAAAAA-GGCGCGTCCTGGCAAGTAA 395
RXLR29_Noks AAACTGAC-AAGAAAAAAA-GGCGCGTCCTGGCAAGTAA 395
RXLR29_Cala AAACTGAC-AAGAAAAAAAAGGCGCGTCCTGGCAAGTAA 396
RXLR29_Emco AAACTGAC-AAGAAAAAAAAGGCGCGTCCTGGCAAGTAA 396
RXLR29_Hind AAACTGAC-AAGAAAAAAAAGGCGCGTCCTGGCAAGTAA 396
RXLR29_Maks1 AA-CTGAC-AAGAAAAAAA-GGCGCGTCCTGGCAAGTAA 394
RXLR29_Maks2 AAACCGGCCAGGAAAAAAAAGGTGCGTCCTGGCAAGTAA 398
RXLR29_Waco AAACCGGCCAGGAAAAAAAAGGCGCGTCCTGGCAAGTAA 399
** * * * * ******** ** ****************
Figure S4: Multiple alignment of RXLR29 sequences from 7 Hpa isolates. Stop codons are shaded grey.

60 Chapter 2
Table S1: Primers used for RXLR allele sequencing.
Gene Forward Reverse
RXLR3 AGATGCGTCTTCACATCCTG TTGTTGTTATTCTGCTGCTGCT
RXLR4 GGAAAGATGCGTCTTCACAT ATTGTTGTTATTCTGCTGCTGCT
RXLR5 TTTTTCGTTGACAACCATGC CAATAACCTCGCTGGCTTACA
RXLR6 CACGTCGTAAGTTGACCATG ACATCGATTGCTCGCATCAC
RXLR7 CGTCCCGTCCGACATACTTA GTAGCTACCGCCACCCAGT
RXLR9 TCTCTTAAGCTTGTGCGATCTTC AAGTCCTCACCTCCAGTCCA
RXLR13 TCGACCCCTTCACCTGTTAC GACATCAGGTCTGCGTCTCA
RXLR15 CACAACGTCAAACCGACATC GGGTTTATTGCCGTTTCGTA
RXLR16 ATGCTGCCAGCTCGCGCAG TCAAATCGCCGCATTGATGTC
RXLR17 CACCCACCGAGAACGAGTAT TGAATGTCTATCCGCCGTCT
RXLR18 CAATTTAATAATAGAGGGAGAGTCACG AGGCTGCCAAAGCTTCAAGT
RXLR19 CGATTCATCGCCCTCACC CGGTTTCATCACCCACTACG
RXLR20 CTTTCACCTTGGGTCCTTCC AAGCACACTTAAGTTCTACTATTACGC
RXLR20 CGATATGCGACGGAGAGCTG CAGCTCTCCGTCGCATATCG
RXLR21 CGACGATGTAGGATCAGATACG TTTGTGTTTTAGCTGCTACGG
RXLR23 TCGACCCCTTCACCTGTTAC CCACGCACTACCTTAGCACA
RXLR29 AAGTCCTCACCTCCAGTCCA CATTGCCGTAGCTCCTTTGT

Isolate-specific effectors from Hyaloperonospora ESTs
61
Table S2: Enrichment of protein class members in the EST project compared to the genome-wide
occurunce.
A hypergeometric propability value

62 Chapter 2
Table S3: Functional classification of 90 unigenes based on Pfam domain predictions, BLASTX and
manual annotation (continued on next page). For manual annotations the IDs are given in lists.
Pfam domain predictions
ID Pfam ID Pfam name E-value
Pro3526IW PF00012.13 HSP70 2.8e-98
Pro1991IW PF00026.16 Asp 5e-58
Pro2490IW PF00043.18 GST_C 2.9e-06
Pro3738IW PF00056.16 Ldh_1_N 1.2e-35
Pro2968IW PF00085.13 Thioredoxin 6.1e-27
Pro2968IW PF00085.13 Thioredoxin 2e-27
Pro2875IW PF00085.13 Thioredoxin 2e-28
Pro2875IW PF00085.13 Thioredoxin 1.7e-26
Pro3759IW PF00085.13 Thioredoxin 6e-31
Pro3759IW PF00085.13 Thioredoxin 2.2e-31
TC1311MERGE PF00106.18 adh_short 1.3e-10
Pro2915IW PF00149.21 Metallophos 0.00014
Pro3807IW PF00150.11 Cellulase 6.1e-12
Pro3351IW PF00160.14 Pro_isomerase 4.9e-46
Pro3776IW PF00245.13 Alk_phosphatase 7.2e-76
Pro3221IW PF00254.21 FKBP_C 4.3e-32
Pro3019IW PF00300.15 PGAM 3.5e-10
Pro2270IW PF00400.25 WD40 1.3
Pro2270IW PF00400.25 WD40 0.00033
Pro2270IW PF00400.25 WD40 2.4e-10
Pro3224IW PF00428.12 Ribosomal_60s 2.2e-20
Pro3566IW PF00445.11 Ribonuclease_T2 5.6e-32
Pro1764IW PF00450.15 Peptidase_S10 2e-81
Pro2843IW PF00450.15 Peptidase_S10 1.5e-80
Pro534IW PF00462.17 Glutaredoxin 9.9e-20
Pro93IW PF00487.17 FA_desaturase 1.7e-23
Pro2024IW PF00614.15 PLDc 2.9e-09
Pro3222IW PF00639.14 Rotamase 1.1e-15
Pro3222IW PF00639.14 Rotamase 1.8e-16
Pro203IW PF00742.12 Homoserine_dh 3.8e-39
Pro2119IW PF00899.14 ThiF 1.6e-36
Pro3133IW PF00964.10 Elicitin 4.7e-07
HaELL1_Waco PF00964.10 Elicitin 4.6e-15
HaELL2_Waco PF00964.10 Elicitin 6.2e-15
HaELL3_Waco PF00964.10 Elicitin 3.8e-13
Pro3815IW PF01011.14 PQQ 1.5e-05
Pro3584IW PF01095.12 Pectinesterase 1.2e-48
Pro3481IW PF01263.13 Aldose_epim 2.5e-19
Pro3763IW PF01263.13 Aldose_epim 6.1e-17
Pro5506MERGE PF01341.10 Glyco_hydro_6 2.1e-53
Pro245IW PF01435.11 Peptidase_M48 1.7e-55
Pro2157IW PF01451.14 LMWPc 1e-25

Isolate-specific effectors from Hyaloperonospora ESTs
63
Pfam domain predictions
ID Pfam ID Pfam name E-value
Pro776IW PF02219.10 MTHFR 2.7e-83
Pro2250IW PF02466.12 Tim17 6.2e-12
Pro2490IW PF02798.13 GST_N 3.7e-16
Pro9IW PF02815.12 MIR 3.2e-12
Pro3738IW PF02866.11 Ldh_1_C 7.6e-34
Pro1884IW PF03330.11 DPBB_1 1.4e-09
Pro2846IW PF03372.16 Exo_endo_phos 4.7e-10
Pro35IW PF03388.6 Lectin_leg-like 2.4e-30
Pro985IW PF03446.8 NAD_binding_2 1.4e-29
Pro203IW PF03447.9 NAD_binding_3 1e-17
Pro2681IW PF03813.7 Nrap 1.7e-40
Pro1930IW PF04597.7 Ribophorin_I 3e-23
Pro1396IW PF04616.7 Glyco_hydro_43 5.4e-27
Pro3361IW PF04981.6 NMD3 8.9e-70
Pro3632IW PF05162.6 Ribosomal_L41 2.2e-08
HaNLP1_Waco9 PF05630.4 NPP1 2.4e-48
HaNLP2_Waco9 PF05630.4 NPP1 2.6e-45
Pro964IW PF07542.4 ATP12 2.2e-13
Pro3759IW PF07749.5 ERp29 3.1e-13
Pro3232IW PF09360.3 zf-CDGSH 1.6e-09
Pro2891IW PF10988.1 DUF2807 8e-07
Pro388IW PF11380.1 DUF3184 5.2e-17
Pro547IW PF11779.1 DUF3317 4.8e-07
Manual annotation (ID lists)
Cysteinerich
searches
BlastX
RXLR
HaCR1 RXLR3 Crinkler
HaCR2 RXLR4
HaCR3 RXLR5
HaCR4 RXLR6
HaCR5 RXLR7
HaCR6 RXLR9
HaCR7 RXLR12
HaCR8 RXLR13
HaCR9 RXLR15
HaCR10 RXLR16
HaCR11 RXLR17
HaCR12 RXLR18
HaCR13 RXLR19
HaCR14 RXLR20
HaCR15 RXLR21
HaCR16 RXLR22
RXLR23
RXLR29

65
Chapter 3:
Effector identification in the lettuce downy
mildew Bremia lactucae by massively parallel
transcriptome sequencing
Joost H. M. Stassen 1 , Michael F. Seidl 2,3 , Pim W. J. Vergeer 1 ,
Isaäc J. Nijman 4 , Berend Snel 2,3 , Edwin Cuppen 4 ,
Guido Van den Ackerveken 1,3
1
Plant-Microbe Interactions, Department of Biology, Utrecht University,
Padualaan 8, 3508 CH Utrecht, the Netherlands
2
Theoretical Biology and Bioinformatics, Department of Biology,
Utrecht University, Padualaan 8, 3508 CH Utrecht, the Netherlands
3
Centre for BioSystems Genomics (CBSG), Wageningen University,
Binnenhaven 5, 6709 PD Wageningen, the Netherlands
4
Hubrecht Institute, Developmental Biology and Stem Cell Research,
KNAW and University Medical Center Utrecht, Uppsalalaan 8, Utrecht,
the Netherlands
Molecular Plant Pathology.
doi: 10.1111/j.1364-3703.2011.00780.x

66 Chapter 3
Abstract
Lettuce downy mildew (Bremia lactucae) is a rapidly adapting oomycete pathogen
affecting commercial lettuce cultivation. Oomycetes are known to use a diverse
arsenal of secreted proteins (effectors) to manipulate their hosts. Two classes of
effector are known to be translocated by the host: the RXLRs and Crinklers. To
gain insight into the repertoire of effectors used by B. lactucae to manipulate its
host, we performed massively parallel sequencing of cDNA derived from B. lactucae
spores and infected lettuce (Lactuca sativa) seedlings. From over 2.3 million
454 GS FLX reads, 59 618 contigs were assembled representing both plant and
pathogen transcripts. Of these, 19 663 contigs were determined to be of B. lactucae
origin as they matched pathogen genome sequences (SOLiD) that were obtained
from >270 million reads of spore-derived genomic DNA. After correction of cDNA
sequencing errors with SOLiD data, translation into protein models and filtering,
16 372 protein models remained, 1023 of which were predicted to be secreted.
This secretome included elicitins, necrosis and ethylene-inducing peptide 1-like
proteins, glucanase inhibitors and lectins, and was enriched in cysteine-rich
proteins. Candidate host-translocated effectors included 77 protein models with
RXLR effector features. In addition, we found indications for an unknown number
of Crinkler-like sequences. Similarity clustering of secreted proteins revealed
additional effector candidates. We provide a first look at the transcriptome of
B. lactucae and its encoded effector arsenal.

Effector identification in B. lactucae
67
Introduction
Oomycete plant pathogens cause devastating diseases on a wide variety of crops.
These organisms resemble fungi, but are more closely related to brown algae. Wellknown
oomycete pathogens are the obligate biotrophic downy mildews and the
hemibiotrophic Phytophthora species, including P. infestans, the causative agent
of the Irish potato famine, and P. ramorum, which causes sudden oak death. The
downy mildews have a narrow host range, for instance Hyaloperonospora arabidopsidis
grows only on living Arabidopsis thaliana plants, Plasmopara viticola is
an important grape pathogen and Bremia lactucae is the most important pathogen
of lettuce (Lactuca sativa). The control of B. lactucae is an increasingly difficult
task as fungicides have been phased out because of environmental concerns, and
fungicide resistance is becoming more widespread [1] . Genetically controlled resistance
to B. lactucae is present in most commercial lettuce varieties, but is quickly
overcome by new rapidly evolving B. lactucae races.
The B. lactucae life cycle starts from a spore landing on the plant’s epidermis,
followed by penetration, hyphal colonization of host tissue and sporulation, leading
to the release of large numbers of spores. At all stages, B. lactucae is in contact
with its host, so that it can interfere with defence and manipulate host processes
to obtain nutrients. In contrast with many oomycetes, B. lactucae infection
usually starts with the direct germination of asexual spores, without a zoospore
intermediate stage. B. lactucae also does not rely on entry via stomata, but, instead,
usually penetrates directly through the cuticula into an epidermal cell. A primary
vesicle and, later, a secondary vesicle are then formed in the epidermal cell, after
which hyphae grow in the intercellular space of the mesophyll tissue. Haustoria
are formed in most mesophyll and epidermal cells encountered by the hyphae
(reviewed by Lebeda et al. [2] ). The B. lactucae–lettuce interaction is a classic
example of a gene-for-gene interaction, in which single dominant avirulence genes
in B. lactucae are genetically recognized by dominant resistance genes in lettuce
(reviewed by Michelmore and Wong [3] ). Knowledge on the molecular biology and
basis of B. lactucae pathogenicity, however, is mostly lacking.
Studies of oomycete–plant interactions at the molecular level are now revealing
more and more details on the molecular toolbox used by these remarkable
pathogens. The genomes of the sequenced oomycete species Albugo candida [4] ,
A. laibachii [5] , H. arabidopsidis [6] , P. infestans [7] , P. sojae [8] , P. ramorum [8] ,
Pseudoperonospora cubensis [9] and Pythium ultimum [10] represent a treasure
trove of information on the effector repertoires secreted by these pathogens to
manipulate their hosts. Various types of effectors are predicted to act in the apoplast
and, in addition, two classes of oomycete effector translocate into the host cell
(reviewed by Stassen and Van den Ackerveken [11] ). Effectors from one of the

68 Chapter 3
host-translocated classes are referred to as RXLR effectors, after the RXLR amino
acid motif contained by the first characterized effectors of this class [12] , although
variations in this motif also permit host translocation [13] . Examples of variants of
RXLR motifs include the QXLR motif found in host-translocating effectors of
the oomycete pathogen of cucumber, Ps. cubensis [9] , and the GXLR motif found
in the P. infestans effector SNE1 [14] . Furthermore, ATR5 of H. arabidopsidis is
recognized inside host cells and has homology to the RXLR motif-containing
effectors, but does not contain an RXLR motif [15] . A second class of host-translocated
effectors are the Crinklers, which contain two conserved amino acid motifs
preceding a modular C-terminal section. In a number of Crinklers, the domains
that form the modules in this C-terminal section induce cell death when expressed
in Nicotiana benthamiana [7] . Two Crinklers from P. sojae are even thought to
be indispensable for successful infection of soybean [16] . Although the effector
repertoire is generally highly divergent between species, features such as motifs
associated with host-translocated effectors allow for the identification of potential
effectors encoded by gene models or mRNA sequences.
Access to the catalogue of the effectors of a species allows for the cloning
and investigation of individual effector genes. This has led to the identification of
various activities of effectors on host processes. Examples include the disruption
of host cell wall–membrane adhesion [17] , suppression of defensive protease activity
[18‐20]
and suppression of effector-triggered immunity (e.g. [14,16] ). In addition, the
first cytoplasmic target and mode of action of a host-translocated effector has been
identified; host E3 ligase CMPG1 is stabilized by P. infestans effector AVR3a
[21]
, revealing more details about the mechanisms by which oomycetes establish a
successful infection of their hosts.
In this article, we investigate the potential effector arsenal of B. lactucae by
cDNA sequencing and de novo assembly of transcript sequences. Transcripts
obtained from B. lactucae-infected lettuce were compared with short reads of
B. lactucae genomic DNA (gDNA) to select for B. lactucae transcripts. From the
predicted B. lactucae secretome, we identified homologues of known effector
families as well as new groups of potential effector proteins.
Results
Bremia lactucae transcriptome sequencing
Two sources of RNA were used for B. lactucae transcriptome sequencing: RNA
isolated from asexual B. lactucae conidiospores and RNA isolated from B. lactucae-infected
lettuce leaves. Many effector genes are known to be differentially
expressed during different stages of infection, with transcripts of early-stage effec-

Effector identification in B. lactucae
69
tors being present in spores, and transcripts of later stage (hyphal growth) effectors
being expressed in B. lactucae growing in planta. To increase the number of
different infection stages and, as a result, transcript diversity, lettuce seedlings were
inoculated twice with a 3-day interval (see time line in Fig. 1A). Lettuce seedlings
were inoculated with conidiospores (Fig. 1B) that germinate on the leaf surface,
penetrate through epidermal cells and then continue to grow intercellular hyphae
in the mesophyll, forming haustoria in plant cells (Fig. 1C). Plants were kept under
low relative humidity and, as a result, when material was harvested for RNA isolation
(day 7), no B. lactucae sporulation was observed, although abundant growth of
intercellular hyphae and the formation of haustoria were visible (Fig. 1D).
Figure 1: Preparation of Bremia lactucae-infected lettuce leaves for transcriptome analysis. (A) Time
line of sampling. Light grey bars represent periods in which infected lettuce was kept at high humidity.
(B) Spores were spray inoculated at time point 0 and at a second time point at 3 days post-inoculation
(dpi). (C) Bremia lactucae establishes an infection and forms hyphae between plant cells, creating
haustoria in adjacent cells. (D) Leaf material heavily colonized with B. lactucae hyphae and haustoria
is harvested for RNA isolation at 7 dpi.
Transcript sequencing was performed using 454 sequencing technology on
cDNA of spores and B. lactucae-infected cotyledons generated by either oligo
dT priming and 5′ enrichment, or by random priming and normalization. An
overview of the number of obtained sequences per approach is given in Table 1.
Normalization selectively removes sequences present in relatively high abundance,
improving the sampling of rare transcripts. It is important to sample transcripts
that are present in low abundance, as effectors may be produced very locally and
can therefore be present at low abundance in the overall sample. We generated
random-primed cDNA to more evenly spread coverage over the entire length of the
transcripts. Pools 3 and 4 (Table 1) are random primed and normalized, and were
used to generate the majority of reads (>90%). We also sequenced the 450–650-bp

70 Chapter 3
fragments from both the 3′ and 5′ ends, as the expected ~200-bp read size of the
454 sequencing technology (GS FLX) used would otherwise probably miss the 3′
ends of transcripts. In addition, we sequenced the 5′-enriched non-normalized pools
to provide stronger coverage of the 5′ ends of transcripts that are most important
when looking for N-terminal signal peptides of secreted proteins.
Table 1: Materials and method of preparation of cDNA for transcriptome sequencing. The contribution
of each pool to the number of reads and number of bases is indicated.
Pool Material Strategy 5’ Reads 1 Total 5’ nt 3’ Reads 2 Total 3’ nt
1 Spores 5’ sequencing 86 352 22 212 388 nd nd
2 Interaction 5’ sequencing 115 413 30 335 206 nd nd
3 Interaction
Random-primed +
normalized
701 499 182 312 369
4 Mixed
Random-primed +
normalized
637 709 165 624 293
1 013 411 262 824 074
1
The DNA code in the adapter that links a read to a pool could not be resolved for 19,422 reads that are
not included in this table.
2
The DNA code was not sequenced in 3’ Reads.
A total of 523 477 146 bases from 2 349 338 cDNA reads (91.28% of all available
reads) was assembled into 59 618 contigs. The total length of contig consensus
sequences was 36 217 753 bases and the average coverage of these sequences was
14.6-fold. The average length of contig consensus sequences was 607.5 bases.
Further statistics relating to the assembled sequences can be found in Table 2.
Table 2: Assembly process statistics regarding the number of input reads, reads after filtering and
remaining singletons. The number and total length of contigs are given for all and large (>500
nucleotide) contigs.
Transcriptome assembly
Reads
Total number of reads 2 573 806
Number of reads after filtering 2 349 338 (91.28%)
Number of bases in reads after filtering 523 477 146 (90.65%)
Singletons remaining after assembly 82 194 (3.19%)
Contigs
Contigs 59 618
Bases in consensus sequences 36 217 753
Large contigs (>500bp) 26 358 (44.21%)
Bases in large contigs 26 543 633 (73.29%)
Average size of large contigs 1 007
N50 size of large contigs 1 087

Effector identification in B. lactucae
71
The assembled contigs are derived from both B. lactucae and lettuce, as most
transcript sequences were derived from RNA of infected plants. To determine
which transcripts are derived from B. lactucae and to correct 454 sequencing
errors, we generated additional sequence information by SOLiD sequencing of
B. lactucae gDNA. Conidiospores were used for gDNA isolation as they are the
only life stage of B. lactucae that can be well separated from its lettuce host. We
sequenced gDNA rather than mRNA from spores, as the transcript pool in spores
most probably lacks many transcripts that are involved in the interaction with the
host plant. The B. lactucae gDNA SOLiD sequencing data obtained consist of
173 428 926 reads of ~50 bp.
By mapping B. lactucae gDNA reads to the assembled 454 reads, contigs
representing B. lactucae transcripts can be differentiated from lettuce-derived or
poorly assembled sequences. Transcripts with high average gDNA read coverage
probably represent B. lactucae transcriptome sequences, whereas low or no coverage
indicates a lettuce or contaminant origin. A total of 20 925 of 59 618 contigs, or
35.2%, had at least one SOLiD gDNA read mapped to the sequence. The average
gDNA read coverage per contig peaked at 37–40-fold coverage, as shown in Fig. 2.
The shoulder seen at approximately half this coverage (18–20-fold coverage) in
Fig. 2 may represent alleles that have been assembled as separate transcripts. We
defined the B. lactucae transcriptome set as the 19 663 contigs with a 10-fold
or higher average SOLiD-sequenced gDNA read coverage. The vast majority
of excluded sequences had no gDNA read coverage and, of those that did, most
had an average gDNA read coverage of less than one-fold (Fig. 2). The average
length of the sequences in our B. lactucae transcriptome set of 19 663 contigs was
736.7 bp, up from 607.5 bp in the overall set, probably as a result of the exclusion
of short contaminant sequences. Of all the assembled spore-derived reads (pool 1),
over 93% were found in consensus sequences that were classified as B. lactucae.
Figure 2: Number of consensus sequences with indicated average genomic DNA (gDNA) read
coverage. Read coverages are assigned into groups by taking the integer + 1 of the actual average read
coverage.

72 Chapter 3
For the non-normalized, interaction-derived reads (pool 2), we found 20% of
reads in B. lactucae contigs, whereas, from normalized pools (pools 3 and 4), 47%
matched to B. lactucae. This suggests that the normalization procedure increased
the proportion of B. lactucae transcript sequences in the interaction cDNA. To
assess whether lettuce transcripts were successfully excluded, we compared our
assembled sequences with a collection of 226 050 expressed sequence tags (ESTs)
from Lactuca species (The Compositae Genome Project; http://cgpdb.ucdavis.edu).
For the sequences excluded from the B. lactucae transcriptome, we found matching
ESTs for ~70% of our sequences. More importantly, we found only 151 sequences
(

Effector identification in B. lactucae
73
tively. The B. lactucae transcripts represent the genes expressed during infection,
and may therefore not represent all genes that are present in the genome. With a
match of 79%, the B. lactucae transcriptome is well represented.
The protein sequences corresponding to a set of 119 core orthologous genes
were used to determine the place of B. lactucae in oomycete phylogeny by
comparison with six pathogenic oomycete species and four nonpathogenic
stramenochromes for which predicted proteomes are available. As depicted in
Fig. 3, the stramenochromes branch off first, after which Saprolegnia parasitica
and then Py. ultimum branch off in the evolutionary tree. We then find B. lactucae,
followed by H. arabidopsidis and, finally, three Phytophthora species. We can
therefore compare B. lactucae with the earlier branching necrotrophic oomycete
Py. ultimum and the later branching biotrophic downy mildew H. arabidopsidis and
hemibiotrophic Phytophthora species.
Saprolegnia parasitica
100
Pythium ultimum
100
Bremia lactucae
100
Hyaloperonospora
arabidopsidis
96
93
Phytophthora
spp.
0.2
Figure 3: Phylogeny of Bremia lactucae and related stramenochromes determined from a multiple
sequence alignment of 119 concatenated orthologous sequences. The scale bar represents 0.2
substitutions per amino acid. Numbers represent the bootstrap support for the given branch.
To define the B. lactucae secretome, we determined which protein models
contained a signal peptide but no transmembrane helix predictions. Of the 16 372
models considered, 1023 were predicted to be secreted. The size of the secretome
is close to that predicted for the downy mildew H. arabidopsidis (1016 predicted
secreted proteins) and Py. ultimum (1123 secreted proteins), as shown in Fig. 4.
The 1023 candidate secreted B. lactucae proteins were further analysed for protein
domains and other features related to effectors.

74 Chapter 3
B. lactucae
H. arabidopsidis
P. infestans
P. ramorum
P. sojae
P. ultimum
S. parasitica
Figure 4: The size of the secretome
encoded in the genomes of different
oomycetes, as determined from the
presence of signal peptides and the
absence of transmembrane helices in the
protein models of each species.
Domain composition of the B. lactucae secretome
An initial approach to catalogue the secretome was to determine which Pfam
domains, families and repeats were present. We obtained a total of 348 Pfam
annotations for 295 of the 1023 secretome protein models. Prevalent domains in
the B. lactucae secretome (Table 3) included various domains that may be linked
to pathogenicity. The most prevalent domain in the B. lactucae secretome was the
elicitin domain. Elicitins are small highly conserved secreted proteins characterized
by a domain that contains six cysteine residues important for structure. Of the 12
B. lactucae protein models with elicitin domain matches, nine contained at least
six cysteines in the predicted mature peptide. Phytophthora elicitins trigger a
hypersensitive response in host plants, an effect that is linked to sterol binding and
transporting activity for which a surface-exposed polar residue is important [23‐28] .
Elicitins may play a role in the uptake of sterols by oomycetes that do not synthesize
their own, as the presence of elicitins appears to be correlated with the loss of
the sterol biosynthetic pathway [28‐30] . Elicitins are found in higher numbers in the
hemibiotroph P. infestans and the necrotroph Py. ultimum than in H. arabidopsidis
and B. lactucae (Table 3), suggesting that they may be selected against in biotrophs
that adapt a more stealthy infection strategy. All of the B. lactucae elicitins are
α-elicitins [31] , which generally provoke a less marked host response than do
β-elicitins.
Trypsin domains, found in peptidases, are present in B. lactucae in numbers
similar to those in P. infestans and Py. ultimum, whereas fewer are found in
H. arabidopsidis. The role of oomycete proteases in pathogenesis has not been
determined, with only a single report of a P. infestans protease with an intact

Effector identification in B. lactucae
75
Table 3: Number of protein models in Bremia lactucae, Phytophthora infestans, Hyaloperonospora
arabidopsidis, and Pythium ultimum that are predicted to contain the domains that are most prevalent
in the B. lactucae secretome.
Pfam Domain B. lactucae H. arabidopsidis P. infestans P. ultimum
Elicitin 12 9 28 37
Trypsin 11 4 13 14
Jacalin 7 4 4 0
DnaJ 6 3 5 5
Cysteine-rich secretory protein family 6 7 14 9
Ricin-B-lectin 4 2 1 0
catalytic triad that is expressed during infection [32] . More common are catalytically
inactive trypsin-like proteins that act as glucanase inhibitors [33] . The B. lactucae
proteins with trypsin matches do not have intact catalytic residues in the active site
and could therefore function as glucanase inhibitors. Host glucanases can damage
the oomycete cell wall, impeding oomycete growth and releasing glucan-oligosaccharide
elictors [34] , and are therefore a potentially useful target for inhibition by an
invading oomycete.
Jacalin domains and Ricin-B-lectin domains, both found in lectins, are present
in larger numbers than in the other oomycetes. A Jacalin domain-matching
oomycete protein has been proposed to act in cell wall degradation [32] , and roles
in host attachment have been suggested on the basis of homology to lectins [35] and
lectin-like activities [36] . Host lectins, however, act in defence and may recognize
oomycete-derived carbohydrates or glycosylation features. Pathogen lectins could
therefore also be instrumental in masking these signals, as has been demonstrated
for the ECP6 effector of the plant-pathogenic fungus Cladosporium fulvum, which
masks chitin oligosaccharides that normally trigger plant immune responses [37] .
Cysteine-rich secreted proteins and proteins mediating disulphide bond formation
may play an important role in dealing with the protease-rich conditions in
the extracellular environment. Cysteine residues can form disulphide bridges that
may contribute to protein stability and protect against proteases. In addition, DnaJ
proteins may act as molecular chaperones to further stabilize apoplastic proteins.
Many protein families involved in pathogenicity, found in other oomycetes, are
small cysteine-rich proteins. Examples include the aforementioned elicitins,
Phytophthora PcFs [38‐40] and H. arabidopsidis PPATs [41] and HaCRs [42] . Although
there are six proteins matching the Pfam cysteine-rich secretory domain model,

76 Chapter 3
these protein models contain few cysteine residues. Nonetheless, 135 cysteine-rich
proteins (>5% cysteine) are found in the B. lactucae secretome. The majority
of these are short (

Effector identification in B. lactucae
77
Host-translocated effectors
To find potential host-translocated RXLR effectors, a search for the amino acid
motif RXLR was performed on the predicted B. lactucae secretome. This search
identified 44 potential RXLR effectors, counting only hits with the RXLR located
between positions 30 and 60 in proteins of at least 65 amino acids. As variants
of the RXLR motif also allow host entry, we expanded our search to include
protein models that are similar to known RXLRs. We therefore performed a blast
search with all H. arabidopsidis [6] and Phytophthora spp. [7] RXLRs against the
B. lactucae secretome. To rule out matches based on homology to conserved
signal peptide sequences, they were removed from the B. lactucae proteins. In this
search, 38 matches were found in the B. lactucae secretome, irrespective of the
presence or absence of an RXLR or RXLR-like motif. In a third approach to find
RXLR effectors, we selected the RXLR motif and 20 residues on either side in the
sequences that were identified by the motif search, and used these as input for a
jackhmmer search. jackhmmer is an iterative search that uses matches to an initial
input sequence to construct an alignment profile which is employed to search for
additional matches in the target database and to further refine the profile. Seven
new candidates were identified in a set of 52 that included 42 input sequences
and three sequences that were found by blast. Ten proteins were predicted by all
three methods (Fig. 5). The combined set consists of 77 unique potential RXLR
effectors, the details of which are provided in Table 4. We also found protein
models by blast comparison that did not have an RXLR motif or variant thereof,
but did have an EER motif, albeit slightly more N-terminal of the location at which
the RXLR motif would be expected. For 11 B. lactucae contigs encoding RXLR
and RXLR-like proteins, we observed clear
differential expression based on transcript
reads between spores and in planta stages
(Table S1). Most of the B. lactucae RXLR
and RXLR-like effectors were not found in
the genomes of other downy mildews. Bidirectional
blast matches (E-value < 1e-3 both
ways) were found for only seven B. lactucae
versus eight H. arabidopsidis RXLRs, and
none for Ps. cubensis. In addition, between
Ps. cubensis and H. arabidopsidis only three
RXLR matches were found.
23
2
10
32
Motif
3
7
Blast
HMM
Figure 5: Venn diagram depicting the
overlap of the three methods used for the
prediction of RXLR effectors. HMM,
hidden Markov model.

78 Chapter 3
Table 4 (continued next page): RXLR and RXLR-like motifs found in Bremia lactucae secretome
protein models identified as potential RXLR effectors based on a motif search, BLAST comparison
with RXLRs of other oomycetes or a jackhmmer search with B. lactucae RXLR motifs and surrounding
amino acids as input. All sequence coordinates are given in amino acids. Evidence codes are built up of
M (motif search), B (BLAST comparison) and H (jackhmmer search)
contig ID
RXLR
EER(like)
RXLR EER start
start
motif 1 Stop codon Evidence 2
16131 44 RRLR 55 EER 363 MBH
16134 41 RRLR 50 EER 454 MBH
23155 49 RLLR 61 EQEER - MBH
27267 55 RALR 68 EER - MBH
35642 42 RRLR 60 EDR - MBH
40355 50 RRLR 64 DER 270 MBH
42290 45 RGLR 200 NEK 333 MBH
43449 35 RMLR - - MBH
45396 53 RLLR - 130 MBH
49490 44 RRLR 57 DER - MBH
19377 49 RRLR - 269 MB
22293 45 RFLR 65 DEK - MB
07991 43 RQLR 78 EER 161 MH
08247 52 RSLR - 103 MH
08248 52 RSLR - 146 MH
08983 49 RRLR - - MH
16394 46 RRLR 59 QNDER - MH
18684 50 RRLR - 282 MH
18840 49 RPLR 61 NQEER - MH
20700 56 RELR - 252 MH
21364 47 RALR 58 EDK - MH
23333 35 RFLR - - MH
24965 57 RSLR 62 DENR 107 MH
29191 46 RKLR - 75 MH
31910 45 RLLR 54 DNNEER 160 MH
32917-1 47 RSLR 60 NDER - MH
33962 39 RILR - 74 MH
36117 38 RDLR - 424 MH
36219 45 RHLR 60 ENR 201 MH
38529 40 RQLR 91 EDK - MH
39974 41 RQLR 50 DER - MH
40514 44 RLLR 56 EER 126 MH
41799 42 RALR - 90 MH
41935 44 RLLR 53 DDNDER - MH
43687 55 RSLR - 91 MH
43968 33 RGLR - 185 MH

Effector identification in B. lactucae
79
contig ID
RXLR
EER(like)
RXLR EER start
start
motif 1 Stop codon Evidence 2
45726 42 RLLR - - MH
46714 45 RSLR 82 NQR - MH
48006 46 RALR 55 NEDR 92 MH
48013 55 RALR - 82 MH
50216 47 RSLR 60 DEER 102 MH
53213 43 RGLR 61 EER - MH
53460 47 RSLR 60 DEER - MH
59265 49 RLLR 62 EE - MH
22259 - 52 EER 375 BH
29756 36 RSLLQ 51 DER - BH
56090 42 RSLQ 55 EER - BH
07727 45 RRLK 63 EER - B
07952 - 65 NEER 304 B
08155 55 RRLQ 109 EEK 321 B
09272 - 58 DEER 346 B
09828 - 48 EEK 652 B
11813 - 49 EER 629 B
12298 63 RLKREQ - 612 B
13165 114 RSLR 360 DEK - B
14316 - 50 EER 365 B
16501 481 RKLR - 485 B
17177 - - - B
18477 42 QNLR - - B
19297 57 KVLR - 253 B
24419 - 54 DEER 434 B
24503 - - 520 B
28334 43 EKLR 53 ENR 479 B
29771 - - 263 B
35494 - - - B
35745 169 RSLR 72 EER - B
48427 62 RLLD - - B
51693 - 49 EER - B
51725 39 PSLR - - B
56746 - 49 EER - B
23857 42 GKLR 55 DER 243 H
25695 44 GKLR 57 DER 336 H
26201 58 RSLR 63 DENR 111 H
31920 44 GRLR 57 DER 233 H
38296 63 RRLR - - H
46806 43 QLRLR 57 DER - H
50948 41 GRLR 54 DER - H
1
Determined as [DENQ]{2,}[RK]
2
Evidence codes are as follows: M = Motif, B = Blast, H = jackhmmer.

80 Chapter 3
Using the collection of Crinkler effectors of Phytophthora species [7] , we performed
similarity searches to identify these effectors in the B. lactucae secretome.
We found six candidates, three of which contained an LXFLA amino acid motif
that was similar to the motifs reported in Phytophthora species. Interestingly,
gDNA read coverage was higher than expected for four candidates: two containing
the LXFLA motif (six- and three-fold) and two without this sequence (22- and
40-fold). This suggests that more gene copies or pseudogenes may be present in
the genome than are detected in our transcriptome set, or that multiple genes have
been assembled into a single sequence. The sequences containing an LXFLA motif
are not complete, suggesting problems with assembly. We therefore used the HMM
models of Crinkler domains [7] to screen all predicted peptides for the potential
presence of Crinkler domains. All peptides were included as many of the potential
Phytophthora Crinklers do not have a signal peptide and signal peptides may have
been assembled separately. We found a total of 75 sequences that had homology
to one or more of the reported Crinkler domains. In total, we found matches to 14
different C-terminal Crinkler domains in B. lactucae (Table 5), again with higher
than expected gDNA coverage. Interestingly, we also found traces of D2, DC and
DBF domains, which are also found in cell death-inducing P. infestans Crinklers [7] .
Table 5: Matches to hidden Markov models of Crinkler
domains (as defined by Haas et al [7] ) in the Bremia
lactucae transcriptome, and the predicted copy numbers
thereof.
Domain
Peptide
predictions
Predicted
copy number 1
N-terminal
LFLAK 15 64
DWL 13 101
C-terminal
D2 11 11
DAB 2 4
DBE 4 22
DBF 3 3
DC 2 1
DDB 3 2
DDC 2 1
DFA 2 2
DFB 8 111
DFC 9 68
DN17 1 1
DN7 1 1
DX9 1 1
DXX 15 135
1
The predicted copy number is determined
by dividing the observed average genomic
DNA coverage of the assembled transcripts
in which the indicated domains are encoded
by the average genomic coverage of all
assembled B. lactucae transcripts.

Effector identification in B. lactucae
81
Expanded sequence families in B. lactucae
The clustering of B. lactucae secretome sequences with those of six other oomycete
species and four stramenopile species was performed on the basis of a comparison
of all sequences with each other. A cluster of closely related genes may indicate
a recently expanded family of genes that plays an important role in pathogenesis
and adaptation to the host. Clustering revealed 85 groups of sequences containing
multiple B. lactucae members. We focused on eight clusters with three or more
B. lactucae members that contained significantly more B. lactucae members than
would be expected on the basis of the presence of members of six other oomycetes
and four other stramenopiles.
Two clusters could be categorized on the basis of Pfam domain hits. The first is
a B. lactucae-unique cluster containing a three-member subset of the Pfam elicitin
domain-matching sequences. The second cluster, with 11 B. lactucae members and
two H. arabidopsidis, five P. infestans, 10 P. sojae and 18 P. ramorum members,
contains all seven Jacalin domain-containing proteins. The members of this cluster
have blast hits in the NCBI NR protein database to P. infestans hypothetical
conserved proteins, but also to NPP1, an NLP, and putative adhesins. The
sequences are distinct from the sequences with a Pfam NLP prediction, as those
cluster together in another cluster, with eight B. lactucae, nine H. arabidopsidis, 25
P. infestans, 40 P. sojae and 56 P. ramorum members.
Of the remaining six clusters, five consist of three B. lactucae sequences each,
and one cluster consists of four B. lactucae sequences. All but one cluster could
be linked to identified RXLR effector candidates. The four-member cluster most
closely represents the ‘classic’ RXLR effector, with an RXLR motif in all members
and a DER motif in one of them. The four clusters of three sequences share
similar sequence features that are more apparent when these clusters are aligned
(Fig. 6). No significant similarity to sequences in the NCBI NR protein database
was found for sequences in these four clusters. All members of the C1 cluster had
already been identified as potential RXLR effectors, as well as a single member
of each of two other clusters (C4 contig18477 and C3 contig28334). One member
of C1, contig49490, has an intact RXLR motif that aligns with similar features in
sequences in all sequence clusters. The presence of these sequences in groups of
related sequences, with features similar to those found in known RXLR effectors,
suggests that these proteins may be host-translocated effectors. The cluster that
could not be linked to RXLR effectors has no RXLR-like motif (not shown) and
contains no members that were identified as potential RXLR effectors, although all
members contain an EER motif.

82 Chapter 3
Figure 6: Alignment of the sequences of four Bremia lactucae-specific clusters of predicted secreted
proteins. The columns in which potential RXLR and dEER-like motifs can be found are indicated
above the alignment.
The clustering of secreted sequences highlights three elicitins specific for B. lactucae.
It also shows that the family of jacalin domain proteins occurs in a cluster
with varying numbers of family members in other oomycete species, suggesting
that they might fulfil a species-specific role. Finally, it identifies other potential
host-translocated effectors that were not predicted by other methods.
Discussion
The B. lactucae transcriptome sequences that have been generated by next-generation
sequencing methods provide a first look at the toolbox used by B. lactucae to
manipulate its host. Potential apoplastic and host-translocated effectors could be
predicted from the assembled transcript sequences. We showed that 79% of a set of
conserved eukaryotic genes used to assess genome completion are represented in
the B. lactucae transcriptome, underlining a broad sampling of the transcriptome.
The transcriptome is far more plastic than the genome, and the remaining 21% of
conserved eukaryotic genes may not have been sampled because not all developmental
stages of B. lactucae were represented in our material (e.g. sporangiophore
formation, but also sexual reproduction). Another possibility is that the transcripts
have been sampled, but are not assembled as full-length transcripts and therefore
do not satisfy the cut-off values for the models of the conserved eukaryotic genes.
Protein predictions were based on the use of homology to known proteins to
select the most probable open reading frame (ORF) from the contigs. In 432 cases,
this suggested a model that spanned multiple ORFs in a single contig, in which
case these ORFs were taken together as a single protein model. Manual inspection
revealed that this may be a result of the inclusion of unprocessed introns in the
cDNA sample. Although introns are thought to be rare in oomycetes, one study [45]

Effector identification in B. lactucae
83
found that, of a total of 128 alternative splicing events detected in P. sojae, intron
skipping was the most common event, explaining 97 cases.
Sequencing of plant-pathogenic oomycetes has revealed a variable number of
RXLR effectors in different organisms. We identified 77 potential RXLR effectors
in the B. lactucae secretome, 43 of which contained a conserved RXLR motif. This
is a relatively small number compared with the 134 found in H. arabidopsidis [6]
and the 563 found in P. infestans [7] , but close to the 32 RXLR effectors found in
Ps. cubensis [9] . In addition, 29 potential effectors with a QXLR motif were found in
Ps. cubensis. There is evidence that QXLR motif proteins can also translocate into
the host [9] , illustrating that strict conformation to the RXLR motif is not required.
In B. lactucae, we identified four clusters of three related B. lactucae sequences
that all contain sequence features reminiscent of RXLR motifs.
We reported traces of Crinkler proteins in the B. lactucae transcriptome. These
sequences were not completely assembled and had a higher than expected coverage
of genomic DNA reads. This may indicate that our sampling strategy is suboptimal
for capturing Crinklers; EST sequencing of H. arabidopsidis material collected in a
similar manner revealed a single partially assembled Crinkler [42] . It may be that, in
these obligate biotrophs, Crinklers are expressed in smaller numbers or in a more
limited timeframe. Alternatively, key Crinkler-derived reads may be lost during
normalization and assembly because of high sequence similarity.
Sequencing of the transcriptome of B. lactucae has provided a wealth of
information about the proteins expressed during infection of the host. The protein
models described are an extensive source of potential effectors. Candidate effectors
can now be cloned and tested to study their role in the infection process, e.g. as
suppressors of host immunity. An important next challenge is to determine how
these proteins manipulate host processes. Ultimately, host susceptibility and
resistance genes can then be identified from Lactuca resources, allowing for novel
strategies in breeding for resistance against B. lactucae.
Experimental procedures
454 sequencing
Bremia lactucae isolate BL24 was grown on Lactuca sativa cultivar Olof and
the enhanced B. lactucae-susceptible Lactuca sativa cv. Olof × Lactuca saligna
recombinant inbred line BIL4.4 [61,62] . Plants were kept at 17 °C under 9 h light per
day (100 µE/m 2 /s). Bremia lactucae spores were spray inoculated at 150 spores/µL
suspension on 7-day-old soil-grown lettuce seedlings until run-off was imminent.
Inoculation was repeated at 3 days after the initial inoculation. After each inoculation,
plants were kept under high humidity for 24 h and thereafter at low humidity.

84 Chapter 3
Trypan blue staining was performed by boiling in staining solution for 5 min, and
otherwise as described for H. arabidopsidis [46] . Material was harvested 7 days after
the initial inoculation. For spore isolations, inoculated plants were kept at high
humidity for 7 days, after which spores were rinsed off leaves in water. Spores
were filtered through a double layer of miracloth and then spun down (3650 g) and
washed in water three times. Spores and infected leaf material were snap frozen
and ground using a mortar and pestle. RNA was isolated from ground material
using the Qiagen (Venlo, The Netherlands) plant RNA mini kit employing RLC
buffer according to the manufacturer’s instructions.
Isolated RNA was sent for preparation for sequencing to Vertis Biotechnologie
AG (Freising, Germany). Poly(A) RNA was selected from all samples. Two
cDNA synthesis strategies were then performed. In the first, the poly(A) RNA was
incubated with calf intestine phosphatase (CIP) and tobacco acid pyrophosphatase
(TAP), followed by ligation of an RNA adapter to the 5′-phosphate of decapped
mRNAs. First-strand cDNA synthesis was then performed with an adapter-random
hexamer primer and M-MLV-RNase H reverse transcriptase. The resulting cDNAs
were amplified with 21 cycles of long and accurate polymerase chain reaction
(LA-PCR). In the second approach, first-strand cDNA synthesis was primed with
a random hexamer primer, after which 454 adapters A and B were ligated to the 5′
and 3′ ends of the cDNA. The cDNA was finally amplified with PCR using a proof
reading enzyme (17 cycles). To normalize samples, one cycle of denaturation and
reassociation of the cDNA and subsequent separation of single-stranded cDNA
(normalized cDNA) of double-stranded RNA by hydroxylapatite chromatography
were performed. Normalized cDNA was amplified with eight PCR cycles. For both
approaches, cDNA in the size range 450–650 bp was eluted from agarose gel using
the Macherey & Nagel (Düren, Germany) NucleoSpin Extract II kit. Sequencing
was performed on the 454 GS FLX system, using standard reagents.
SOLiD sequencing
Lettuce leaves were surface sterilized in 4% bleach for 3 min, rinsed with water
and placed abaxial side up on wet filter paper. The leaves were then spray inoculated
(200 spores/µL) with B. lactucae isolate BL24 and kept at high humidity
for 8 days. Spores were snap frozen and lysed by bead beating and incubation
in cetyltrimethylammonium bromide (CTAB). DNA was extracted with phenol–
chloroform; 7 µg of DNA was sheared into 100–110-bp mean size fragments,
end-repaired with the End-It DNA End-Repair Kit (Epicentre Biotechnology,
Madison, WI, USA) according to the manufacturer’s instructions, and cleaned by
phenol–chloroform extraction. Adapters were ligated as recommended by Applied
Biosystems (Carlsbad, CA, USA) and cleaned by phenol–chloroform extraction.

Effector identification in B. lactucae
85
Fragments of 150–200 bp were excised from a 2% agarose electrophoresis gel and
purified using the QIAquick Gel Extraction Kit (Qiagen). Further steps in sample
preparation and sequencing were taken as recommended by Applied Biosystems.
Sequence analysis
The 454 transcriptome sequences were assembled using Roche (Basel, Switzerland)
gsAssembler (version 2.0.00) software with an expected coverage of 15-fold
(based on initial assembly coverage levels) and otherwise default settings. SOLiD
reads were mapped to the assembled 454 reads by Burrows–Wheeler Aligner
(BWA) [47] (version 0.5.8 r1442; maximum edit distance, 10; first 25 bases as seed;
maximally two mismatches in the seed; otherwise default settings for colourspace
alignment). Assembled sequences were corrected using insertion/deletion
information from the mapping process. Correction effectiveness was determined
by comparison with the NCBI NR database by blastx [48] (E-value < 1e-3, best hit).
Sequences with >10-fold average SOLiD read coverage were kept as B. lactucae
sequences. Proteins were predicted from these sequences by selecting an ORF
based on the blastx comparison with the NCBI NR database or, failing matches,
selecting the ORF(s) of greatest length. In cases in which blast comparison led to
the selection of adjacent ORFs, these ORFs were concatenated into a single model.
ORF lengths were determined from methionine to stop unless the ORF was at the
5′ or 3′ end, in which case the length was determined from the 5′ or up to the 3′,
respectively, as sequences may be incomplete. Sequences were trimmed to start
with a methionine and sequences shorter than 20 amino acids were removed before
signal peptide prediction by SignalP (3.0a) [49,50] (first 70 amino acids, eukaryote,
default cut-offs). Transmembrane helices were predicted using TMHMM (2.0)
(http://www.cbs.dtu.dk/services/TMHMM/). Secretome criteria were the prediction
of a signal peptide by both neural network and HMM prediction methods and no
predicted transmembrane helices (unless overlapping at least 10 amino acids of
the signal peptide). All blast comparisons were performed with an E-value cut-off
of 1e-3. HMM and jackhmmer (version 2.3.2; http://hmmer.org/) searches were
performed with an E-value cut-off of 1e-3 and otherwise default settings, except
for the genome completeness models, for which bit-score cut-offs were provided.
For jackhmmer searches using B. lactucae RXLRs, the RXLR motif and the 20
amino acids N- and C-terminal thereof were used as input. Pfam [51] searches were
performed at the gathering threshold.
To obtain a phylogeny of NLP proteins in B. lactucae and other oomycetes, we
predicted the presence of the NLP domain (PF05630, Pfam v24; http://pfam.sanger.
ac.uk/ [51] ) in their proteomes using hmmer3 (http://hmmer.org/) (gathering cut-off).
To predict full-length NLP domains, we retrieved the seed alignments from the

86 Chapter 3
Pfam database and created a calibrated hmmer2 model. hmmer2 (gathering cut-off)
was used with this model on the hmmer3-identified candidates. Short domain
hits (50% of both target and query sequences, and had >20% effective coverage
(fraction of covered amino acids), were taken into account, with the exception
that B. lactucae sequences did not need to span 50% of non-B. lactucae sequences.
Bremia lactucae sequences may be truncated and therefore not span 50% of the
non-B. lactucae sequence. The similarity network was then clustered into families
using the Markov-Cluster-Algorithm (MCL; http://micans.org/mcl/, v09-308,
1.008, inflation = 3) [57,58] . Clustered sequences were aligned in Jalview [59] using the
MAFFT web service [60] . We predicted a reliable species phylogeny utilizing a multi-protein
marker containing 119 concatenated 1 : 1 : 1 families retrieved from the
protein clusters determined beforehand. These families were aligned using mafft
(v6.713b; maxiterate 1000; localpair) [60] and subsequently concatenated. Positions
containing >20% gaps, as well as less conserved adjacent positions, were removed
until a conserved column with a median of the pairwise BLOSUM62 of ≥0 was
reached. The phylogenetic tree was predicted using RAxML [52] (v7.0.4; gamma
model of invariant sites, WAG substitution model, fast bootstrap approximation)
and the robustness of the topology was assessed by 1000 bootstrap replicates.

Effector identification in B. lactucae
87
Accession numbers
Bremia lactucae sequences longer than 200 nucleotides were deposited in the
NCBI Transcriptome Shotgun Assembly sequence database under accession
numbers JP948721-JP965883. All nucleotide data and protein translations are
available at http://web.science.uu.nl/pmi/data/bremia/.
Acknowledgements
This project was supported by the foundation TTI Green Genetics (TTI GG) in
collaboration with Wageningen University (Wageniningen, The Netherlands),
Enza zaden (Enkhuizen, The Netherlands), Nunhems (Nunhem, The Netherlands),
Syngenta (Enkhuizen, The Netherlands), Rijk-Zwaan (De Lier, The Netherlands)
and Vilmorin (La Ménitré, France). We thank Ewart de Bruijn and Patrick van Zon
for excellent technical assistance.

88 Chapter 3
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58 Enright AJ, Van Dongen S & Ouzounis CA (2002) An efficient algorithm for large-scale detection
of protein families. Nucleic Acids Research 30, 1575-84.
59 Waterhouse AM, Procter JB, Martin DMA, Clamp M & Barton GJ (2009) Jalview Version 2--a
multiple sequence alignment editor and analysis workbench. Bioinformatics 25, 1189-91.
60 Katoh K & Toh H (2008) Recent developments in the MAFFT multiple sequence alignment
program. Briefings in Bioinformatics 9, 286-98.
61 Zhang NW, Lindhout P, Niks RE & Jeuken MJW (2009) Genetic dissection of Lactuca saligna
nonhost resistance to downy mildew at various lettuce developmental stages. Plant Pathology 58,
923-32.
62 Zhang NW, Pelgrom K, Niks RE, Visser RGF & Jeuken MJW (2009) Three combined
quantitative trait loci from nonhost Lactuca saligna are sufficient to provide complete resistance
of lettuce against Bremia lactucae. Molecular plant-microbe interactions 22, 1160-8.

94 Chapter 3

Effector identification in B. lactucae
95
Supplemental Information
Figure S1 (previous page): Phylogenetic relationship between NLPs [necrosis and ethylene-inducing
peptide 1 (NEP1)-like proteins] from various oomycete plant pathogens.
Four of the NLPs in the Bremia lactucae secretome provided full-length NLP domain matches and
are included in the main tree, indicated in purple. The positions of fragments of the domains found
in the complete B. lactucae transcriptome were determined separately (indicated in the main tree by
stars), as they are difficult to locate based on the alignment of the full-length domain. Bremia lactucae
NLPs are spread more widely across the oomycete NLP gene tree than are the Hyaloperonospora
arabidopsidis NLPs (indicated in bold as clade or individual common names), and do not fall within
H. arabidopsidis or Pythium ultimum subclades. Bremia lactucae NLPs cluster close to the two H.
arabidopsidis NLPs outside of the H. arabidopsidis-specific subclade. NLP names indicated in blue
belong to NLPs that have been shown to induce necrosis when expressed in tobacco leaves. Scale bar
indicates 0.1 substitutions per amino acid. Stars indicate the location of subtrees that contain short
fragments (incomplete assembly) of Bremia NLPs that were assessed separately.
Table S1 (continued next page): Number of reads from spore and infection sequencing pools per contig
for those that show a five-fold or greater difference in the number of reads between spore and infection
stages as determined from 5′ end sequences of the non-normalized sequencing pools.
Differential expression was observed for contigs corresponding to protein models of all the indicated
categories, except for those encoding for DnaJ domain proteins and NLPs [necrosis and ethyleneinducing
peptide 1 (NEP1)-like proteins] for which no difference in abundance was found.
Overal Spores Interaction 1
Reads considered 67615 20169
Contigs containing reads 8667 6567
Average reads /
contig containing reads
7.8 3.1
Controls Spores Interaction
Actin
contig12283 3 9
Tubulin
contig12868 4 5
18s Ribosomal
contig01002 25 32
Phospholipase A2
contig36115 2 3
1
(counting only Bremia)

96 Chapter 3
Spores Interaction Spores Interaction
Elicitins
Trypsin
contig32983 26 1 contig34965 26 0
contig43325 0 11 contig56967 49 1
contig46242 20 1 >5% cysteine
contig48912 16 1 contig08246 54 2
Jacalin contig10442 20 1
contig06799 11 1 contig16641 6 1
contig12503 15 0 contig17422 17 2
contig14955 48 2 contig19602 0 8
CAP contig28850 6 0
contig36558 9 0 contig30126 1 9
Ricin-B-Lectin contig31077 10 0
contig22692 16 1 contig38644 46 5
contig28297 33 2 contig39684 14 1
RXLR and RXLR-likes contig40030 8 1
contig07991 1 8 contig40488 16 0
contig08248 35 3 contig44287 8 0
contig09272 2 14 contig44488 0 6
contig16131 6 0 contig44717 0 11
contig18840 17 0 contig44719 0 23
contig23155 135 0 contig50965 6 1
contig24965 0 29 contig52084 0 14
contig40514 0 19 contig56102 5 0
contig41935 11 0 contig57102 6 0
contig43968 0 12 contig57464 5 0
contig51725 6 0 contig57969 12 1
Table S2: Versions and sources of genomes used for analysis.
Species name Version Source TaxonID
Number
predicted References
proteins
Aureococcus anophagefferens 1 JGI 44056 11501
[56]
Phaeodactylum tricornutum 2 JGI 2850 10402
[54]
Thalassiosira pseudonana 3 JGI 35128 11776
[53]
Ectocarpus siliculosus 1 Gent 2880 16582
[55]
Phytophthora infestans 1 BROAD 4787 18138
[7]
Phytophthora ramorum 1 BROAD 164328 14394
[8]
Phytophthora sojae 1 BROAD 67593 16989
[8]
Pythium ultimum 4 BROAD 65071 15323
[10]
Hyaloperonospora arabidopsidis 8.3 VBI 272952 14910
[6]
Saprolegnia parasitica 1 BROAD 101203 18729
A
A
www.broadinstitute.org/annotation/genome/Saprolegnia_parasitica/MultiHome.html

97
Chapter 4:
Effectors of the lettuce downy mildew Bremia
lactucae enhance host susceptibility
Joost H. M. Stassen, Pim W. J. Vergeer, Annemiek Andel,
Guido Van den Ackerveken
Plant-Microbe Interactions, Department of Biology, Faculty of Science,
Utrecht University, Utrecht, The Netherlands

98 Chapter 4
Abstract
Bremia lactucae is an obligate biotrophic oomycete that causes downy mildew, an
important disease of lettuce. Bremia uses an arsenal of effector proteins that are
thought to manipulate the host and establish a successful infection. Among these
are RXLR effectors that are proposed to be host-translocated and to act inside
the host cell. A set of 34 potential RXLR effectors of Bremia was cloned and
sequence verified by Sanger sequencing. The contribution of each effector to host
susceptibility was investigated by Agrobacterium-mediated transient expression
of effector genes in lettuce leaf discs and subsequent inoculation with Bremia.
The number of spores formed by Bremia on these leaf discs provides a measure of
host susceptibility towards Bremia. A trend towards enhancing susceptibility was
observed for most potential effectors. Transient expression of two effector genes,
BLR16 and BLR27 significantly increased host susceptibility, whilst transient
expression of BLR03 significantly reduced host susceptibility. The temporal expression
of selected effectors during infection of lettuce by Bremia was determined,
revealing that BLR03 expression was limited to early infection stages, whereas
BLR16 and BLR27 were expressed at all infection stages. To analyse the enhanced
susceptibility phenotype, a set of biotic stress-associated markers was developed
from lettuce transcripts that are highly abundant during infection. Candidate
markers were selected based on homology to A. thaliana genes that are annotated
as biotic stress-responsive or were found to be responsive to biotic stress in data
from publicly available microarray experiments. Strong induction of five lettuce
biotic stress-associated markers was found in response to infection by both Bremia
and Agrobacterium. Using these markers, however, no evidence was found for
strong suppression of biotic stress-responses in leaf material transiently expressing
susceptibility-enhancing Bremia effector candidates. This work clearly shows that
several candidate effectors of Bremia enhance disease susceptibility. The identification
of these effectors of Bremia now opens the way to investigate their activity and
targets in the lettuce host.

Bremia effectors enhance host susceptibility
99
Introduction
Bremia lactucae is an obligate biotrophic oomycete that causes downy mildew
of lettuce. Losses in susceptible crops are large, and considerable effort is put
into breeding resistant lettuce cultivars. Many agricultural crops are attacked by
oomycetes, a diverse group of organisms with fungal-like features belonging to the
Stramenopiles. Oomycete pathogens differ in lifestyle, ranging from necrotrophic
species such as Pythium ultimum through hemibiotrophic Phytophthora species
(e.g. P. infestans and P. sojae) to the obligate biotrophic downy mildews. Examples
of crops affected by downy mildew are grapevine (caused by Plasmopara
viticola), sunflower (caused by Plasmopara halstedii) and cucurbits (caused by
Pseudoperonospora cubensis). Much of our current understanding of the molecular
biology of downy mildew-host interactions has been learnt from the interaction
between Hyaloperonospora arabidopsidis and Arabidopsis thaliana, which is a
prime host-pathogen model system (reviewed by Coates and Beynon [1] ), whereas
the lettuce-Bremia interaction has been mainly studied as model for gene-for-gene
interactions (reviewed by Michelmore and Wong [2] ). The lifestyle of H. arabidopsidis
is similar to that of Bremia, though there are clear differences. Bremia and
H. arabidopsidis infections start from a sporangio- or conidiospore germinating
on plant leaves. Bremia then forms an appressorium that serves to penetrate the
epidermis, allowing the establishment of a primary vesicle, and later a secondary
one, in an epidermal cell [3] . H. arabidopsidis does not penetrate through epidermal
cells, rather it forces a hyphae through the anticlinal wall between two epidermal
cells. Both pathogens then grow hyphae between mesophyll cells, penetrating the
cell walls and invaginating the host membrane to form protrusions called haustoria.
In order to successfully interact with their hosts, oomycetes use an arsenal of
different effectors. A number of these effectors act on the outside of the host cell,
whilst other types are translocated across the host cell wall and cell membrane into
intracellular compartments of the host (reviewed by Göhre and Robatzek [4] ). The
different lifestyles of oomycetes are reflected in the effectors of different groups
of pathogens. Whereas necrotrophic and hemibiotrophic oomycete species encode
effectors that are thought to act similar to toxins, biotrophs do not kill their host
and are thought to adapt a more stealthy lifestyle [5] . This requires extensive interference
with host cell processes to promote disease susceptibility in the broadest
sense. Effectors can serve to suppress immunity, but also to promote or alter host
metabolism and to redirect nutrient transport in favour of the pathogen.
Suppression of plant immunity by effectors of bacterial pathogens is a
well-studied phenomenon (Reviewed by Göhre and Robatzek [6] and Rodríguez-
Herva et al. [7] ). Gram-negative bacteria, e.g. those belonging to genera of
Pseudomonas or Xanthomonas, deliver effectors into host cells via a Type Three

100 Chapter 4
Secretion System (TTSS) to interfere with plant immunity by acting on host
targets. A recent example of surprising targets include the tomato PsbQ protein,
which is a member of the oxygen evolving complex of photosystem II [8] . Targeting
of this protein by the P. syringae pv tomato DC3000 effector HopN1 compromised
the production of defence-related reactive oxygen species and programmed cell
death. Effectors can also act on processes not related to plant immunity to enhance
disease susceptibility. For example, the PthXO1 effector of Xanthomonas oryzae
pv oryzae PXO99 induces the ectopic expression of the rice OsSWEET11 sugar
transporter by directly binding to the promoter of its encoding gene. Apparently
the activation of the sugar transporter is important for nutrient acquisition by the
invading pathogen [9] .
Oomycetes do not deploy a TTSS to introduce effectors into the host cell, but
rather use a two-step procedure. Effectors of oomycetes are thought to be secreted
from the haustorium, after which they are taken up or translocate across the hostcell
membrane [10] . Two motifs that are associated with host-cell entry have been
described in multiple oomycete species. Based on the presence of these motifs
the RXLR effectors and the Crinkler effectors are distinguished as major classes
of effectors. In downy mildews fewer Crinkler effectors appear to be expressed
compared to RXLR effectors [11–13] . The RXLR effectors contain a signal peptide for
secretion from the pathogen, and a translocation domain that contains the RXLR
motif, or a variant thereof, and an optional EER motif. The region C-terminal of the
translocation domain is referred to as the effector domain. Uptake of these effectors
by host cells appears to take place in absence of a pathogen-encoded machinery
and is associated with the RXLR motif [10,14,15] , though there are also reports of
translocation of effectors with a less conserved RXLR motifs or only an EER motif
[16–18]
. The exact mechanism of host-cell entry by RXLR effectors is under debate,
with reports of binding to cell surface-exposed phosphatidylinositol-3-phosphate in
plant and human cells [19] , and tyrosine-O-sulphate-modified cell surface molecules
in fish [15] as initial steps in host entry.
RXLR effectors have been predicted from the genomes of oomycetes based on
the presence of predicted signal peptides and RXLR motifs. Many of these effectors
have been functionally analysed for suppression of plant immunity. Two of
32 tested P. infestans effectors were found to suppress Infestin-1 (INF-1) induced
hypersensitive cell death when expressed by Agrobacterium transient transformation
24 hours before challenge inoculation with an Agrobacterium strain carrying
an INF-1 construct [20] . In a similar setup, the majority of a large collection of P.
sojae effectors was shown to suppress cell death induced by the mouse pro-apoptotic
protein BAX or by the INF-1 in Nicotiana benthamiana [21] . Constructs of
RXLR effectors of the downy mildew H. arabidopsidis fused with TTSS targeting
signal have been expressed in Pseudomonas syringae and targeted to the host

Bremia effectors enhance host susceptibility
101
cytoplasm via the TTSS. This revealed a surprisingly high number of effectors that
enhanced susceptibility to P. syringae infection and decreased defence-associated
callose deposition by the host [11,22,23] .
Details on the molecular mechanisms underlying the actions of host-translocated
oomycetes are largely unknown, but are beginning to be elucidated. Most
potential effectors do not contain any known domains or motifs other than the
motifs associated with translocation. An exception is Avr3b, a P. sojae-specific
effector, which is a functional Nudix hydrolase [24] . Details of the target and mode
of action are known for P. infestans effector Avr3a, which stabilises the host
E3 ligase CMPG1 in order to manipulate host immunity [25] . Host defences are
also affected by P. infestans AVRBlb2, which associates with C14, a papain-like
cysteine protease normally secreted by the host as a defence measure. This
association occurs around haustoria and blocks secretion of C14 [26] . The targets and
functions of other effectors remain to be elucidated, though there are indications
that multiple effectors of different species may share the same host targets.
High-throughput yeast-2-hybrid analysis of H. arabidopsidis effector candidates,
P. syringae effectors, and A. thaliana proteins revealed that, though separated by
two billion years of evolution, 18 of 165 effector targets are shared between both
pathogens [27] . Between the targets 139 protein-protein interactions were identified,
indicating that the direct targets are highly interconnected. In other words, both
pathogens act on a limited and overlapping set of target modules in plant defence.
Although the lettuce-Bremia interaction has been studied extensively, details
of Bremia effectors and their activities have only recently started to emerge.
Previously, we identified potential RXLR and RXLR-like effectors of Bremia from
the transcriptome of downy mildew-infected lettuce plants [13] . Here we investigate
the role of these potential effectors in modulating host susceptibility or suppressing
plant defence.
Results
A Bremia effector set for in planta expression
Previously, we predicted 77 potential RXLR and RXLR-like effectors from our
Bremia transcriptome data [13] . Based on these predictions we cloned a set of 16
full-length effector candidates that were verified by Sanger sequencing. We had
previously verified and cloned 12 potential effectors that were predicted in previous
preliminary assemblies. Finally, we also determined the full-length sequence of 6
potential effectors that were not full-length in the assembled 454-transcript data by
using additional data from short reads of spore-derived genomic DNA or 3’ RACE.
The complete set therefore comprises 34 Bremia effector candidates. An overview

102 Chapter 4
Table 1: Overview of cloned Bremia effector candidates. The first RXLR or RXLR-like motif and
position within 100 amino acids from the start codon are indicated. The first EER or EER-like motif
and position of which the first amino acid is within 20 amino acids of the first amino acid of the RXLR
motif are shown. Source: M – main assembly, 3 – 3’ RACE, E – transcript extended with SOLiD data,
P – preliminary assemblies.
RXLR-like
EER-like
ID Source Contig ID length start motif start motif
BLR01 P - 86 42 RKLR 52 EQK
BLR02 P - 146 85 RLLR
BLR03 P - 141 48 RFLR 59 EEER
BLR04 P - 76 45 RELR 60 DIK
BLR05 P - 97 32 RALR 58 DED
BLR06 P - 281 46 RCLR
BLR07 P - 253 47 RALR 68 EEER
BLR08 P - 135 38 RLLR
BLR09 P - 112 37 RRLR 81 EER
BLR10 P - 112 37 RRLR 81 EER
BLR11 P - 463 46 RRLR 57 DESER
BLR12 P - 123 49 RYLR 61 ELEK
BLR13 M 16131 363 44 RRLR 55 EER
BLR14 M 29191 75 46 RKLR
BLR15 M 50216 102 47 RSLR 60 DEER
BLR16 M 32917-1 98 47 RSLR 60 NDER
BLR17 M 18684 282 50 RRLR 64 DAEK
BLR18 M 48006 92 46 RALR 55 NEDR
BLR19 M 31910 160 45 RLLR 54 DNNEER
BLR20 M 45396 130 53 RLLR 69 DEAD
BLR21 M 33962 65 39 RILR
BLR22 M 43968 185 33 RGLR
BLR23 M 24965 107 57 RSLR 62 DENR
BLR24 M 43687 91 55 RSLR 74 ELEQ
BLR25 M 48013 82 55 RALR
BLR26 E 16394 187 46 RRLR 59 QNDER
BLR27 E 38529 434 40 RQLR
BLR28 3 08983 279 49 RRLR
BLR29 3 43449 311 35 RMLR 46 EES
BLR30 3 50216 101 47 RSLR 60 DEER
BLQ01 3 59265 79 49 QLLR 61 DEEQR
BLG01 M 25695 336 44 GKLR 57 DER
BLG02 M 31920 233 44 GRLR 57 DER
BLG03 M 23857 243 42 GKLR 55 DER

Bremia effectors enhance host susceptibility
103
of the cloned effector candidates is given in Table 1, and sequences can found in
Supplemental Information 1.
Our set of potential effectors consists of 30 RXLR proteins (BLR, for Bremia
lactucae RXLR) and four candidates with an RXLR-like motif. These Bremia
RXLR-like effector candidates were identified based on their similarity to effectors
of other oomycetes and by comparison to a hidden Markov model based on the
amino acid sequence surrounding the RXLR motifs of Bremia effectors with an
RXLR motif. In three of these RXLR-like motifs the first arginine is replaced by a
glycine (BLG01, BLG02 and BLG03), and in the fourth this residue is a glutamine
(BLQ01). EER-like domains (amino acid sequences rich in E,Q,D or N residues,
preferably ending in R or K) were found in the majority of effector candidates. The
length of the cloned effectors varies from 65 to 463 amino acids, with an average
length of just under 180 amino acids.
Constructs for Agrobacterium-mediated transient expression in planta were
created by engineering a new start codon upstream of the coding sequence of the
cleaved secreted protein, so that the first amino acid after the start codon in the
constructs corresponds to the codon for the first amino acid after the predicted
signal peptide cleavage site. In planta expression of the constructs is driven by
a 35S CaMV promoter. Because of the deletion of the signal peptide sequence,
the effector protein will be translated in the host cell cytoplasm, where it is also
expected to be present during infection by Bremia.
Bremia effectors modulate plant susceptibility
Modulation of host susceptibility by the Bremia RXLR effectors was tested in
a leaf-disc assay based on the idea that transient expression of effectors in leaf
tissue could enhance the susceptibility to Bremia infection, resulting in higher
colonisation and sporulation levels. To test our system we transiently expressed
the lettuce orthologue of a gene encoding a negative regulator of plant immunity,
DMR6 [28] , as positive control. A T-DNA GUS-intron construct (hereafter: GUS)
was used as a control for T-DNA transfer and transgene expression, and was used
to determine the effect of Agrobacterium infiltration on susceptibility to Bremia
in our assay. Figure 1 shows the amount of spores that could be recovered from
mock-infiltrated and DMR6 expressing leaf discs, relative to the amount of spores
recovered from leaf discs expressing GUS. Leaf discs that are infiltrated with only
infiltration medium are more susceptible to Bremia than those infiltrated with Agrobacterium,
probably because of the induction of plant defence. The Agrobacterium
stain carrying a GUS construct is therefore a more relevant control to investigate
the effect of the Bremia effector candidates on host susceptibility. DMR6 increases
host susceptibility to Bremia, as is evident from the increased numbers of spores

104 Chapter 4
Figure 1: Median relative amount of Bremia spores harvested from lettuce discs infiltrated with
infiltration medium (IM), GUS-Agrobacterium or DMR6-Agrobacterium. Based on 23 observations per
treatment. Error bars indicate 95% confidence interval.
that can be harvested from leaf discs transiently over-expressing DMR6. This is
in accordance with observations of enhanced susceptibility of A. thaliana DMR6
over-expression lines to the downy mildew H. arabidopsidis and the bacterial pathogen
P. syringae pv tomato DC3000 [28] . We verified that Bremia can be negatively
affected by effector-induced responses using the P. sojae effector PsojNIP, which
induces cell death in lettuce [29] . PsojNIP-expressing leaf discs underwent extensive
cell-death and no Bremia spores could be recovered from them as a result. This
leaf-disc assay is therefore capable of uncovering changes in susceptibility and can
be used to investigate the effect of Bremia effectors on host immunity.
We used the leaf-disc assay to test the 34 cloned Bremia effectors. The effect
of transient over-expression of Bremia effectors in advance of inoculation with
Bremia differs between tested effectors (Figure 2). Transient expression of all
but three effectors appeared to allow recovery of more Bremia spores from leaf
discs compared to GUS controls, though variation between replicates is high.
Expression of six effectors even led to sporulation levels higher then those on leaf
discs infiltrated with only medium. Sample sizes were small (4-23 observations)
and the assumption of homogeneity of variances is violated (p < 0.05), ruling out
the use of an ANOVA. All treatment groups were compared individually to GUS
to determine which Bremia effectors and controls significantly affect spore counts
using the Mann-Whitney U test, and correction for multiple testing was performed
using the Bonferroni method. Significantly enhanced susceptibility was observed
only for host tissue expressing BLR16 and BLR27. Leaf tissue in which either of

Bremia effectors enhance host susceptibility
105
Figure 2: Median relative amount of Bremia spores harvested from lettuce leaf-discs infiltrated with
Agrobacterium carrying indicated Bremia RXLR effector candidates, or control genes for GUS and
DMR6, or infiltration medium (IM). Striped bars indicate the treatments that did not include Bremia
effectors. Spores amounts are indicated relative to the number of spores harvested from Agrobacterium-
GUS infiltrated leaf discs. Values are based on minimally 4 observations. Error bars indicate 95%
confidence interval. Asterisks indicate treatments that differ significantly from Agrobacterium-GUS
treatment (p < 0.05) after Bonferroni correction.
these effectors is expressed supports spore production levels that lie closer to those
on DMR6-expressing tissue than those on GUS-expressing tissue. Conversely,
expression of BLR03 has a significant negative impact on host susceptibility
resulting in lower sporulation levels of Bremia. The number of spores harvested
from BLR03-expressing host tissue was generally around half of that harvested
from GUS-expressing control tissue.
To test if the presumed translocation domain is dispensable for the effects on
host susceptibility, we also expressed the effector domain only of BLR03 and
BLR16 in lettuce-leaf discs. Preliminary results indicate that reduction of host
susceptibility in leaf discs expressing BLR03 without translocation domain was
comparable to that found in leaf discs expressing BLR03 with translocation domain
(not shown). Likewise, susceptibility was comparably enhanced in leaf discs
expressing BLR16 without its translocation domain and similar to that of BLR16
with its translocation domain. These preliminary results suggest that the translocation
domain is not required for the in planta susceptibility-modulating activities of
these effectors, confirming that the effector domain starts after the EER-like motif.
Effectors are expressed at different stages of infection
To investigate at which stage of the infection process the potential effectors
are expressed, we determined the relative mRNA levels of selected effector genes.
The selection of effector genes was based on promising preliminary results in our

106 Chapter 4
leaf disc assay and includes the effectors that significantly affected susceptibility
to Bremia. All effectors were cloned from cDNA and were therefore already
known to be expressed in Bremia. A more detailed look at expression levels and
differential expression throughout the infection process is given in Figure 3.
Bremia Actin expression levels were compared to L. sativa Actin expression at
each time point by subtracting the number of qPCR cycles required for the L.
sativa Actin amplicon to reach a threshold, from the number of qPCR cycles of
the Bremia Actin amplicon to reach the same threshold (ΔC T
). Similarly, effector
gene expression was normalised to Bremia Actin. Relative Bremia Actin levels
indicate substantial relative Bremia growth during the entire time course (Figure 3,
Actin). Based on our transcriptome data, i.e. relative abundance of non-normalised
5’ reads in the spore-derived and inoculated-lettuce-derived pools, we predicted
BLR22 to be mainly present in spores, and BLR23 to be more highly expressed
during in planta growth [11] . Indeed, expression of BLR22 strongly decreased after
the first two days post inoculation (dpi), whilst the expression of BLR23 increased
Figure 3: Temporal expression of indicated Bremia genes. Bremia Actin expression was compared to
lettuce Actin expression. All other Bremia genes were normalised to Bremia Actin. As lower C T
values
indicate higher expression, the Y-axis scale has been reversed to ease interpretation. Error bars indicate
standard deviation from the mean of three technical replicates.

Bremia effectors enhance host susceptibility
107
from two dpi onwards (Figure 3). BLR05, BLR09 and BLR27 are more actively
transcribed during the spore stage and at 1 dpi, with expression slightly declining
until 3 dpi. BLG02 expression levels are much higher at 1 dpi compared to spores,
but expression decreases steadily from then on. BLR16, which shows a significant
positive effect on host-susceptibility, appears to be slightly up-regulated at 1 dpi,
with expression being lower at 2 dpi and steadily increasing again to higher levels
at the end of the time course, similar to that of BLR23. The expression of BLR03,
on the other hand, drops rapidly during early in planta stages, similar to that of
BLR22, though the low expression levels of BLR03 are reached at 3 dpi, whereas
expression of BLR22 is already low at 2 dpi. This suggests an early role for BLR03,
and could explain that when expressed outside of its normal window of expression
BLR03 can have a negative influence on host susceptibility, as we observed in the
leaf disc assay. The expression profiles of the Bremia effectors were found to be
similar in a second experiment on an independent time course (not shown).
Modulation of biotic stress-associated gene expression in lettuce
To address the question whether effectors change the expression of genes that are
responsive to biotic stress we set out to identify immunity-related marker genes in
lettuce. We identified lettuce sequences that are highly abundant in the transcriptome
of Bremia-infected lettuce plants. A non-normalised sequencing pool derived
from full-length mRNA of lettuce infected with Bremia was previously sequenced
from the 5’ end and used for de novo assembly of Bremia and lettuce transcripts [13] .
The number of reads derived from this pool that is assembled into each contig
allows an estimate of the relative abundance of the transcript represented by the
contig. Our transcript data did not include transcripts derived from uninfected
lettuce that could be used to identify Bremia-induced transcripts based on relative
abundance, so highly abundant transcripts were searched for biotic stress-associated
transcripts as follows. First, transcripts were compared with annotated
Arabidopsis gene models to identify homologous sequences. Potential markers
were then selected by two methods. Homologues of Arabidopsis genes annotated
as biotic stress-responsive were selected. Furthermore, Arabidopsis homologues of
the most highly present lettuce transcripts were investigated in over 6000 publicly
available Arabidopsis microarray experiments via Genevestigator [30] to determine
whether they were strongly responsive to biotic stresses. The selected genes, listed
in Table 2, were further investigated for their usefulness as markers.
We determined the response of the selected lettuce genes to Bremia infection
and Agrobacterium inoculation. Induction by Bremia was tested to determine
the relevance of the markers during Bremia infection of lettuce (Figure 4A). The
expression of all of the eleven tested marker candidates was induced during Bremia

108 Chapter 4
Table 2: Overview of lettuce biotic stress-associated marker candidates and their Arabidopsis
homologues.
ID
(contig)
5’
reads
Arabidopsis
gene ID
Blast
e-value
Symbols Description
00337 44 AT5G58600.2 2e-95 PMR5
Plant protein of unknown
function (DUF828)
00744 25 AT4G30210.2 0 ATR2, AR2 P450 reductase 2
03859 32 AT5G64120.1 1e-67 Peroxidase superfamily protein
04174 21 AT3G45640.1
ATMPK3, MPK3, Mitogen-activated protein
7e-64
ATMAPK3 kinase 3
06346 51 AT4G16260.1 2e-95
Glycosyl hydrolase superfamily
protein
08313 23 AT4G33430.1
BAK1, RKS10,
SERK3, ELG, BRI1-associated receptor kinase
ATSERK3, ATBAK1
07164 37 AT3G10985.1
SAG20, WI12,
2e-23
ATWI-12
Senescence associated gene 20
15736 37 AT1G70170.1 4e-42 MMP Matrix metalloproteinase
15964 22 AT2G39210.1 0
Major facilitator superfamily
protein
33411 99 AT2G36690.1 3e-119
2-oxoglutarate (2OG) and
Fe(II)-dependent oxygenase
superfamily protein
37274 22 AT2G25000.1 3e-39 WRKY60,
ATWRKY60
WRKY DNA-binding protein 60
infection. Induction of two marker genes, 3859 and 4174, was higher than 3 C T
and
three other markers, 15964, 33411 and 37274, showed a higher than 6 C T
induction.
The Bremia effector genes that we planned to investigate were to be tested by
Agrobacterium-mediated transient transformation. We therefore investigated
the lettuce response to Agrobacterium infiltration (Figure 4B) for marker gene
candidates that showed a greater than 3 C T
induction in Bremia-treated compared
to mock-treated leaf material. Induction was similar between Bremia and Agrobacterium
inoculation, with the largest differences in the level of induction of markers
3859 (stronger induction by Agrobacterium) and 37274 (stronger induction by
Bremia). The Agrobacterium infiltration of lettuce can therefore serve a dual
purpose: i, to induce biotic stress, and ii, for transient effector gene expression.
We investigated whether transient expression of any of the six effectors that
most strongly enhanced susceptibility in leaf discs, and BLR03, which reduces host
susceptibility (Figure 2), modulates expression of lettuce biotic stress-markers.
Background expression of the biotic stress-markers was determined in mocktreated
plants. All marker gene expression values were normalised to L. sativa
Actin (ΔC T
) and normalised values were compared between different treatments

Bremia effectors enhance host susceptibility
109
Figure 4: (A) Induction of expression of biotic-stress-responsive genes in Bremia inoculated lettuce.
All expression values were normalised towards L. sativa Actin and compared to normalised mocktreated
values, and are given as ΔΔC T
. Error bars indicate the standard deviation of the average of
three technical replicates. The experiment was repeated with similar results. The scale of the Y-axis
has been inverted to ease interpretation. (B) Induction of expression of biotic-stress-responsive genes
in Agrobacterium infiltrated lettuce. Values are calculated similar to those in (A). Error bars indicate
the standard deviation of the average of three technical replicates. The experiment was repeated with
similar results. The scale of the Y-axis has been inverted to ease interpretation.
and mock (ΔΔC T
). The induction level of biotic stress-markers in lettuce leaf
material transiently expressing individual effectors is shown in Figure 5. Baseline
Agrobacterium-induced marker expression can be determined in leaf material
transiently expressing GUS, as the encoded β-glucuronidase is not expected to
modulate host processes. Induction of biotic stress-markers is affected to a limited
degree by transient expression of DMR6, a negative regulator of host defence, with
a 1-1.5 C T
difference in induction of both 33411 and 37274 compared to expression
of GUS. No large differences in the expression of markers 3859 and 4174 were
found between GUS and individual Bremia effectors. A trend towards higher
expression of 15964 was found in response to the majority of effectors, whilst
expression of 33411 is reduced in response to nearly half of the effectors. Expression
of 37274 is also induced by a number of effectors, though it is suppressed by
expression of DMR6. Response of the markers to different Bremia effectors turned
out to be variable, when tested in an independent second experiment (not shown).
The biological variation in these experiments was too large to rule out minor
effects. We conclude that there is no strong major effect of any of the tested Bremia
effectors on the expression of the selected markers of biotic stress.

110 Chapter 4
Figure 5: Relative transcript abundance of L. sativa biotic stress-markers in leaf sections that were
infiltrated with Agrobacterium and transiently expressed indicated Bremia effectors, GUS, or L. sativa
DMR6. All expression values were normalised towards L. sativa Actin and compared to normalised
mock-treated values, and are given as ΔΔC T
. Error bars indicate the standard deviation of the average of
three technical replicates. The scale of the Y-axis has been inverted to ease interpretation (so that higher
bars indicate higher induction levels).
Discussion
A set of 34 predicted Bremia effectors was analysed for their contribution to
the modulation of host susceptibility. Effects of over-expression of effectors in
the pathogen itself have been reported for other species. For example, P. sojae
transformants constitutively expressing high levels of Avr1b-1 are more virulent on
soybean than wild-type isolates [31] . Silencing of effectors in Phytophthora species
has also revealed contributions to pathogenicity, e.g. by P. infestans AVR3a [25] and
P. sojae AVH238 [21] . Unfortunately, attempts at transformation of Bremia have been
unsuccessful so far, ruling out the possibility of manipulating expression of effectors
in the oomycete itself. We therefore transiently expressed Bremia effectors in
lettuce leaf material using Agrobacterium.
Most of the investigated Bremia effectors enhance susceptibility in the host.
The experimental setup we used measures the level of susceptibility by quantifying
spore-production of Bremia. Susceptibility is likely a combination of multiple
factors (see introduction) and by quantifying infection levels based on a late stage
of the pathogen life cycle, any manipulation of host processes that impacts both
early and late pathogen development can potentially be identified. The system is
potentially limited by its dependence on three different organisms (i.e. L. sativa,
Agrobacterium and Bremia) that each introduce their own variation. By using
appropriate controls and using fixed leaf area and inoculum size, we minimised

Bremia effectors enhance host susceptibility
111
variation.
Increased susceptibility by suppression of plant immunity has been more
extensively studied and appears to be a common function of effectors. In a P.
sojae effector screen, Wang and co-workers assayed for suppression of cell death
induced by BAX, other effectors, or INF-1 in N. benthamiana [21] . When expressed
24 hours before challenge, 107 of 169 effectors were able to suppress cell death,
suggesting that cell-death suppression is a common function of P. sojae effectors.
Hemibiotrophs such as P. sojae may use cell death suppressing effectors to tightly
regulate the onset of the necrotrophic phase [17] . A screen of effectors in the downy
mildew H. arabidopsidis by Fabro et al. [23] focused on the manipulation of immune
responses triggered by Ps. syringae pv tomato DC3000, which was also used as
effector delivery system. The authors conclude from the screen that many of the
tested effectors suppress immunity, but also that the effects of individual downy
mildew effectors are often weak and host accession-specific. Similar host-dependent
differences between Bremia effectors may await discovery.
Effector screens allow studying the effect of individual effector proteins on
a particular host process of interest. Currently these processes are still broadly
defined, e.g. ‘host susceptibility’. Effector activities can be assayed for in more
specific screens, though this requires better understanding of the specific components
that underlie host susceptibility. Based on the knowledge of non-oomycete
effectors, host susceptibility can be influenced at many levels. A previously
mentioned example is PthX01-induced OsSWEET11 expression that is thought
to result in a sugar efflux that feeds the bacterial pathogen [9] . The corn-smut
fungus Ustilago maydis directs a chorismate mutase to the host-cell cytoplasm to
metabolically prime the cell for infection, reducing the levels of salicylic acid and
thereby enhancing susceptibility [32] . Further investigation is required to elucidate
the mechanisms by which Bremia effectors enhance susceptibility.
We found one effector, BLR03, with a seemingly negative contribution to
virulence. This effector does not induce a hypersensitive response in host plants,
but does decrease susceptibility to Bremia when tested on its own. The effector
may fulfil a function during normal infection that is not detected in our assay. The
negative effect observed in our assay can be the result of the timing or high-level
of effector expression. Tight regulation of effector expression has been shown to be
important for pathogen virulence. For example, misexpression of P. sojae effector
genes Avh172 and Avh238 can disrupt infection [21] . Interestingly, both constitutive
over-expression and transient silencing of Avh238 in P. sojae led to reduced
virulence. The expression profile of BLR03 during infection shows a strong decline
of transcript levels during the first days of infection. The 35S-driven in planta
transient expression level of BLR03 is likely far higher than expression levels
in Bremia. The negative effect on host susceptibility in our leaf-disc assay may

112 Chapter 4
therefore be the effect of misexpression of the effector.
Using lettuce biotic stress-associated markers we show that both Bremia and
Agrobacterium induce strong transcriptional responses in lettuce. Over-expression
of DMR6, which encodes a negative regulator of plant immunity, appeared to
have a limited effect on marker expression levels. Variation in marker expression
levels in leaf material expressing different Bremia effectors between independent
experiments was too large to detect suppression by the effectors on marker gene
expression. The observations do, however, suggest that it is unlikely that the tested
Bremia effectors induce strong major changes in expression of biotic stress-markers.
Enhancement of host susceptibility by these Bremia effectors therefore is not
likely to act by general repression of biotic stress responses, but is more likely the
result of very specific and limited modulation of the host. Also, modulation of host
processes may not lead to detectable transcriptional changes; e.g. blocking of C14
secretion by AVRBlb2 [26] is not likely to induce a strong transcriptional response.
The basis of the susceptibility enhancing effects of Bremia effectors thus remains
to be determined. The identification of disease susceptibility-enhancing effectors of
Bremia now opens the way to investigate their activity and host targets.
Materials and methods
Cloning and sequencing
Effector predictions were sequence-verified from PCR product using flanking
primers and sequenced by Macrogen Inc. For primer sequences used in this study,
see Supplemental Table 1. Verified effector candidates were TOPO-cloned into
the pENTR vector using the pENTR/D-TOPO Cloning kit (Invitrogen) according
to manufacturer’s instructions starting from the sequence after the predicted
signal peptide cleavage site of the effectors, unless otherwise indicated, and were
preceded by a newly introduced start codon. Constructs were then recombined into
the pK2GW7 vector (Plant-Systems Biology VIB, Ghent). The PsojNIP construct
was previously described [33] . Clones were electro-transformed into Agrobacterium
tumefaciens strain C58C1 (pGV2260).
Leaf disc assays
Lactuca sativa cv. Olof was sown and kept at high humidity (closed tray with
transparent lid) at 17°C, 9 h of light (100 μE/m 2 /s) to germinate for one week.
Seedlings were then grown for 2 weeks at 21°C, 16 h of light (200 μE/m 2 /s), 70%
RH. Per experiment, a number of leaf discs (14 mm diameter) in excess of that
required for the experiment were punched from Lactuca sativa cv. Olof, mixed, and

Bremia effectors enhance host susceptibility
113
randomly divided over treatment conditions. Agrobacterium tumefaciens strains
containing the 35S-effector T-DNA were grown overnight in selective media at
28°C, 220 RPM. Cells were spun down at 2500 g for 10 minutes and re-suspended
in induction medium (1x M9 salts, 1% glucose, 50μM acetosyringone) with appropriate
antibiotics. After growth for 4 h at 28°C, 220 RPM, cells were spun down
at 2500 g for 10 min and re-suspended in infiltration medium (0.5x Murashige &
Skoog salts, 10mM MES, 0.5% fructose, 0.5% sucrose, 150μM acetosyringone).
Leaf discs were vacuum infiltrated with Agrobacterium suspension until fully suspension-logged.
Infiltrated leaf-discs were placed on 4 layers of 260x410mm filter
paper wet with 65ml dH 2
O and were kept at 21°C for 24 h. Drop-inoculation of 20
μl of 150 spores μl -1 spore suspension was performed the next day. Leaf discs were
from then on kept at 17°C and high humidity. Seven days post-inoculation lids
were sprayed with dH 2
O. Spores were harvested at 8 dpi by pooling 9 discs in 4 ml
H 2
O. Each observation is the average of the spore count in 5 x 1μl. All statistical
analyses were performed using SPSS 19 (IBM). The assumption of homogeneity
of variances was tested by Levene’s test. An independent samples median test was
performed to determine whether infiltration with different Agrobacterium strains
had a significant effect on spore counts. Spore counts of leaf discs infiltrated with
individual Agrobacterium strains were then compared to those of the discs infiltrated
with Agrobacterium-GUS (Mann-Whitney U test). Correction for multiple
testing was performed using the Bonferroni method.
qPCR analysis
For time-course experiments one-week old L. sativa cv. Olof seedlings were
spray-inoculated with 150 spores μl -1 until runoff was imminent. Seedlings were
grown under high humidity (closed tray with transparent lid) at 17°C with 9 h of
light (100 μE/m 2 /s) and kept under these conditions for the duration of the experiment.
Samples were taken and snap-frozen immediately after spraying and every
24 h until 5 days post-inoculation.
For the analysis of expression changes of biotic stress-responsive genes
Agrobacterium strains were prepared as described and pressure infiltrated with
a needleless syringe into three-week old lettuce leaves. Lettuce was grown as
described for leaf disc assays and kept at 21°C, 16 h of light (200 μE/m 2 /s), 70%
RH after infiltration. Infiltration sites were excised and snap-frozen 65 h post-infiltration.
Total RNA was extracted using the Spectrum Plant Total RNA Kit (Sigma
Life Science) and treated with DNAse (Fermentas). cDNA was synthesised using
RevertAid H minus Reverse Transcriptase (Fermentas) and Oligo(dT)15. Cycle
thresholds were determined in triplicate per transcript using the ABI PRISM 7900
HT or the Life technologies ViiA7 system using SYBR Green as reporter dye.

114 Chapter 4
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Supplemental Information
Supplemental Table 1 (continued next page): Overview of primers used in this study. Types are
Flanking, Cloning, qPCR, 3’ RACE, and Cloning Effector Domain. Reverse primers starting with TCM
yield products that include a stop codon (TGA) or a codon for Glycine (GGA) instead. Products without
stop codon can be used de generate constructs with a C-terminal tag (not used in this study).
Effector Type Forward Reverse
BLG01 F AAACGCGATAAGGTCTCAAAA TGACTTCGGTCCTCATTAAAC
BLG01 C CACCATGACTTTACAGTTGACGTCGGTA TCAATTTCGTTTGGCGTTGGG
BLG02 F AATTTCTATTGCGAGCACAGC GTTCGCATGACTCACACCTC
BLG02 C CACCATGACTTCACCACTGACGCTGG TCAAGTAGGTCGCAATTTGTTC
BLG02 q GACGAAGCAAGCGTGTACTG TCGGTTACGTCGAACGTTTT
BLG03 F AAGATGTCGCAACGCAGAG TCCACTTGGCAAAGAGCAC
BLG03 C CACCATGTCATCGGTAACTACTGAAGAAGGTG TCACATCTCAACGTCGCTAGGTG
BLQ01 3 CTCCAACACTTTCCGCTCTC -
BLQ01 C CACCATGTTTCCAATGGAGAAGATTTCGT TCAAAATASTTTTGGCAACCAAC
BLR01 F AGTGTGACTGATGAGGTTGCT TGTCTTTCACATCGTTGTCTTC
BLR01 C CACCATGCGAAACAACAGCCTGGTGAC TCMAAGAATTGCTTGAGCTTCTT
BLR02 F AGCACATGCGTTTAAATTTTCG ACACGACCATCACTCCTCCATT
BLR02 C CACCATGCAGCTGGACACTCACGAAA TCMCTCCTCCATTGAGCAAAC
BLR03 F GCTTTGACCTCGAGCAATAAAATAGC TTAGAGGCGCCCAAATGCTATGAAGC
BLR03 C CACCATGGCGGATGCAGCTAAAGTCAA TCMGTCTGGTCCTCTAATTATAAA
BLR03 E CACCATGTTAAGCATTTGGACCTCTTTTAAAG TCMGTCTGGTCCTCTAATTATAAA
BLR03 q TCAAAATGCTTACCCAGTCG TCTTCCTCTGCTTCGTCAATG
BLR04 F ACCATGGGATCGCTGCTCTTCAATCT GCAACTGTAGCCCGTTACAATACGCA
BLR04 C CACCATGCGCTGGATCGCTGAAC TCMGCAGCGAGAAAAAACATGC
BLR05 F TGGTTGATGGCGCTAACATTTGCCA TTGCGGTGATCCCTAAGACAGTTGA
BLR05 C CACCATGTATTACGAAATAGACGATGATTC TCMCAGGCAAAACGGAAGACAG
BLR05 q ATCTCTTGGCGTTGGTTGTC ACGGAAGGACGTAAGGCTCT
BLR06 F TGACGGTAGTTGCTAATCAAGGGGCA ACGTGAAAATGCAGGTCTACCAGTTCC
BLR06 C CACCATGGCTGAGAACGGATCAT TCMGGTTTGCCCAACATCAGA
BLR07 F CAACAACTTTTGCAATGGCGTA AACCACGTTGCAGCCATCTT
BLR07 C CACCATGACTATAGAAGGGTCCAAGCG TCAATTCGCTTTTTTCCCAGG
BLR08 F TGTCGATTGGTCAAATCTCTAAAA AGGCATGAAAGCAATTATTATTTAGG
BLR08 C CACCATGAACGCCGACCTCACTCC TCMGCTCGAGCGATACTTGA
BLR09 F AGTTTGCCGTCCAGCTATTATCCCGA TCGCATTGGTCCATGTCGCCAGTTTA
BLR09 C CACCATGACCAAGAACGTCACCCAAGT TCMAGTGATGCCGTAGCAAG
BLR09 q GTGAATTGGAAGAGCGAGGA ATGCCGTAGCAAGCAGAGAT
BLR10 F TAAATTTGTCGCATCGGACATT CCACGAGCAAATATGATTAGCAA
BLR10 C CACCATGAAGAACGTCACCCAAGTG TCMAGTGATGCCGTAGCAAGC
BLR11 F GCAGCGAAAACCTAAAACAATCC TTCTAATCTTTACCGAGTCTTTATTCACT
BLR11 C CACCATGGCCTTCCAACAAGTGCCAGC TCMATACTTGAGACCAGAGCTA
BLR12 F AATGGAAGGGAGGCGATTCGGTACAA ATGCACTGGAGCAGTCATTGTGAAGC
BLR12 C CCACATGGCTGTATTGAGCTCAACGC TCMCCGATTACAGACGTAGAA
BLR13 F CTCAGCTGTCTCTGTCGTTTTAGCA TGCATGTTATCAAAAGCGCCCCAGT
BLR13 C CACCATGGCACTGGTGGCTAGGGAG TCAAGATCCAGTTTTCTGCTTT
BLR14 F CCAACTTTCATCATTCCACCA GCTACCGGCTCCCTATCTTT
BLR14 C CACCATGGCGATGAATAGCGCTGCTC TCMACTGAAAACCTTGGACAATA
BLR15 F TCCACAAATGACTAGTCGCAAGCGT TTTATTGATCTCACGCAGCCAGCGA
BLR15 C CACCATGAAATTTAGCTTGGGCACTGCA TCAAGGATCTGGAGGAAAGAA
BLR16 F TTCGTGGATTAACGAAGCTTTT AAGCACCATTCACAGCTATCACA

118 Chapter 4
Effector Type Forward Reverse
BLR16 C CACCATGGAATCCAGCTTGGTCCGTGC TCMGATAGGAAGCGATCTGTAT
BLR16 E CACCATGATCAGTTTGAAAGATGTCGTGG TCMGATAGGAAGCGATCTGTAT
BLR16 q ATGGAGAGCCTCGAAGTCAA CTTTCCCACGACATCTTTCAA
BLR17 F ATCGTAATTTTCCCGCCAACCACCA CACGCCGTAGATGAAACATACAGCA
BLR17 C CACCATGCACAGTRTGTCCATATTTACGC TCMCGATTTTAGTAAGGCCTGA
BLR18 F TCCATAGACCACAAGAGCCTTT CGGGTTATGGTGTGAGAGCTT
BLR18 C CACCATGATTGAAACTCTAGAGGGTC TCMTTCGTTGAGAGCTTTCGC
BLR19 F AGCGACTTACCTGCTGACTTTG AAGCTGCGACATGCTTCTTTC
BLR19 C CACCATGCAAGACTCGGAAGCAGATC TCMCCTGCTGACTTTGTCCC
BLR20 F ACACCGCATGTGAACGACCAAAACT TGCCAAATCAAACTTGTCCTTAGCCCG
BLR20 C CACCATGAGTTGGGAGACCATTTCGGT TCMATGATGATTATTGTAGTATCGT
BLR21 F TATTCCTTGATTGCCGACTTCT CTGGAAGGTGGGGCAGAT
BLR21 C CACCATGTCCAACCCTGAAGACGACG TCMTTGCCTAGGGTCATTATACAG
BLR22 F GGCAAACAACAGTCAAAAGCAG CGAACAACAACACTCACGATGG
BLR22 C CACCATGGAAGTAGAATCCAGCATCGC TCMAACGGAAAGCAAATCAACTC
BLR22 q CGTCGCTAAACTTGAACTTGC TGACTCCCCGTTCTGATGTT
BLR23 F CTCCACATCATTGGCAAAAGC GAGCCCTTTGCCTGATTTCAA
BLR23 C CACCATGGATTTCCAAGCGGCTTCC TCMATTAATATGTTTGGCTGGATA
BLR23 q GGAAGTGATGCGAAAACGAT TGGCTGGATAAAATGGATTG
BLR24 F TGCAGCAATGAAGAATTGACGGCAC ACGCCTACCACCACGTCACTAACATT
BLR24 C CACCATGAAACATGGTAAAGCTGATAAGGA TCMTGTYAACTTAAAGTGAAGCA
BLR25 F TTTTATTTCTACCAAAGTATCAATTCG CGGAGAGAGTCTGCCTATGG
BLR25 C CACCATGAGTCCTAACACTATGACTCTTA TCAGAATGCCAACTTCCAGC
BLR26 F TTGTTGTACGCCTTGGCTGTCGATT ATTGGGTAGCGTTGCACAAAAGCCA
BLR26 C CACCATGGCAACAACAGCACCAAACGC TCMAAGGCTCAGCATGCATCGA
BLR27 F AAAATACCTTTTGTCTCATCTCATC TCGCATTGGTCCATGTCGCCAGTTTA
BLR27 C CACCATGATCGAGAACGTCGCGCTGA TCAAGCTATTTTGACCCCC
BLR27 q AGCACTCGTGACCAGACTTG ATAGCAAGGCCAACCACTTG
BLR28 3 ACCAGCTTCAAGACACCAAGAT -
BLR28 C CACCATGCATACTGTGGCGCTATCCAC TCATATTCCGAACTTTCGACAGAC
BLR29 3 CATCTCATAACTCCAACACTTT -
BLR29 C CACCATGTACACGGGTGCCGCATCCT TCAAGGCGGGGGGGATACG
BLR30 3 TTCACTTCTTCGTTCGCATC -
BLR30 C CACCATGGAGTCCAGCTTGGGCACTG TCAACGTTCTGGTAAGTGCTC
Gene Type Forward Reverse
337 q TCGCATTGGATACAGGCTTA TGGGTAGGGGACACTGATTG
744 q CGGATCTATGGAATTTGCTTTC ACAATGGTGTGGAGGGTTCT
3859 q ATGGACCCGACCCGTCTATT CCAGTATCAAGAGCCACACG
4174 q AATTACATGGATGCTAAGAGAACC CAGGTGGAGGAACTACATCTTTT
8313 q CCGATGTTTTTGGATATGGTG AGCAACATGACATCATCATCATT
6346 q CAGAGGGACAACAGGGACAC CTCCGACTCTTCACCAGGTT
7164 q GGCATAATCACTCAGGTACGG TAATGGAGCGGGATTTTGAA
15736 q TGATGCGGATGAAAATTGG ATGACCAAGCCCAAGAAGGT
15964 q AAAGCAGGGTGAGGATCTGA AAGCGAAATAAATGCACCAAA
33411 q CGTCACCAAAGCTCATTGAC TTGCACTTGAATTCCGAAGA
37274 q TTCAAATCTCCAAAGGAGGTG CAGCGAGCTCTTCAATGAAAT
Lettuce
Actin
q CTATCCAGGCTGTGCTTTCC ACCCTTCGTAGATCGGGACT
Bremia
Actin
q AGGCCGTGCTGTCTCTCTAC GCGCATAGCCTTCGTAGATT

Bremia effectors enhance host susceptibility
119
Supplemental Information 1: Amino acid and nucleotide sequences of cloned effectors.
Indicated in bold and underlined is the first codon after the predicted signal peptide cleavage site. All
effectors were cloned starting from this codon and preceded by a newly introduced start codon.
BLR01
1 M R L L H A A L K R L A D L L A Q I Y L
1 ATGAGGTTGCTGCATGCAGCGCTGAAAAGGCTTGCGGACTTGCTAGCGCAGATATACTTA
21 A T L N V A R S R N N S L V T R Y P I E
61 GCTACATTAAACGTAGCAAGATCTCGAAACAACAGCCTGGTGACGAGGTATCCGATCGAA
41 L R K L R R H S C E R E Q K M R N V G G
121 TTGCGCAAATTACGGAGGCATTCCTGCGAGCGCGAACAAAAAATGAGAAATGTAGGAGGA
61 S N A A S P Q A S E T N L Q E A Q A I L
181 AGCAATGCAGCATCACCGCAAGCAAGTGAAACAAATTTACAAGAAGCTCAAGCAATTCTT
81 -
241 TGA
BLR02
1 M R L N F R S F S D M M V V L L V F V S
1 ATGCGTTTAAATTTTCGTTCTTTTTCCGACATGATGGTTGTTCTGCTGGTCTTCGTATCG
21 G I V L H K A L A Q L D T H E S S A R V
61 GGGATTGTGCTTCACAAAGCTCTCGCCCAGCTGGACACTCACGAAAGTAGCGCAAGAGTC
41 N V W E R S F S A F R D T P A S I V E S
121 AACGTATGGGAAAGATCCTTTTCGGCTTTCAGGGACACTCCTGCTTCGATCGTCGAAAGC
61 M S F E V L Q Y N L F G R P Y E V S K D
181 ATGAGCTTTGAGGTGCTTCAGTACAATTTATTCGGCCGGCCGTATGAAGTGTCCAAGGAC
81 G Q R E R L L R V P E S L H R I S E T I
241 GGACAGAGAGAGCGGCTGCTGCGAGTACCGGAATCACTGCATCGGATCTCCGAAACAATT
101 D I V T F A E A D I Q T Q R D E M L T N
301 GACATTGTGACGTTTGCTGAGGCAGATATTCAAACTCAACGCGATGAAATGCTGACGAAT
121 F N N L D F I F G R R F C M T Q T R L R
361 TTCAACAATTTGGATTTCATTTTTGGACGACGATTTTGCATGACCCAGACCCGTTTACGA
141 V C S M E E -
421 GTTTGCTCAATGGAGGAGTGA
BLR03
1 M P R C L A V L S F A L F T C C I D A S
1 ATGCCCAGGTGCCTTGCTGTGCTCAGTTTTGCATTATTTACTTGCTGTATCGACGCTTCG
21 T A A D A A K V K M L T Q S R Y P G T V
61 ACAGCTGCGGATGCAGCTAAAGTCAAAATGCTTACCCAGTCGCGCTACCCCGGAACTGTT
41 D R I E K V A R F L R S H S I D E A E E
121 GACAGAATTGAGAAAGTCGCTAGATTCTTGCGTTCTCATAGCATTGACGAAGCAGAGGAA
61 E R L S I W T S F K E L L F G G P F S P
181 GAGAGATTAAGCATTTGGACCTCTTTTAAAGAGCTACTCTTTGGCGGTCCCTTTTCGCCG
81 T R L R A M T A D N A V V Q F T F S A W
241 ACTCGCTTGCGGGCCATGACGGCAGATAACGCAGTCGTTCAATTTACGTTCTCTGCGTGG
101 N K F S H V D I R K L L A E G M K D M D
301 AATAAATTTTCTCACGTCGACATTCGCAAGTTGCTTGCCGAAGGCATGAAGGACATGGAT
121 K Q E I E K L N S I I E L Y F I I R G P
361 AAACAAGAGATAGAGAAGTTGAACAGCATCATCGAGCTTTATTTTATAATTAGAGGACCA
141 D -
421 GACTAA

120 Chapter 4
BLR04
1 M A A L V A L L L A L Y V V G V L L P M
1 ATGGCGGCACTGGTGGCACTATTACTAGCGCTGTACGTCGTTGGTGTTCTATTGCCTATG
21 R W I A E Q E A G K A S A N R K Q P E T
61 CGCTGGATCGCTGAACAGGAGGCAGGTAAAGCTTCCGCAAATAGAAAGCAGCCAGAAACG
41 T S F R R E L R R R G S F S M S F V T D
121 ACGTCATTCCGTAGAGAGCTGCGGCGTCGGGGTAGCTTCAGCATGAGCTTTGTGACCGAT
61 I K A H V F S R C -
181 ATTAAGGCGCATGTTTTTTCTCGCTGCTAA
BLR05
1 M G P Q H L L A L V V V S I L V A A G N
1 ATGGGTCCTCAACATCTCTTGGCGTTGGTTGTCGTGTCCATACTAGTAGCTGCTGGAAAT
21 A Y Y E I D D D S V T R A L R P S V I A
61 GCGTATTACGAAATAGACGATGATTCTGTGACGAGAGCCTTACGTCCTTCCGTCATAGCC
41 D Q E H A V H A I P A T N F I S K D E D
121 GACCAAGAGCACGCAGTTCATGCTATTCCAGCCACAAATTTTATCTCAAAGGACGAAGAT
61 H S K N E K K E I E I I R I A I F S L L
181 CACAGCAAGAACGAGAAAAAGGAAATTGAAATTATAAGAATTGCAATATTTTCACTTCTC
81 V V G V F A I M A L R C L P F C L -
241 GTAGTGGGAGTTTTTGCAATTATGGCGCTTCGCTGTCTTCCGTTTTGCCTGTAG
BLR06
1 M H R X N A S T I A A L L T L L I C L T
1 ATGCACCGTCRAAACGCTTCCACCATCGCTGCGTTATTGACATTGCTCATCTGCCTTACC
21 S V T A A E N G S C S S H E G C C L L C
61 TCCGTCACAGCGGCTGAGAACGGATCATGCTCGTCACACGAGGGGTGCTGCTTGCTCTGC
41 G D E L E R C L R G P C S M H W I T R S
121 GGCGATGAGCTAGAGCGCTGTTTACGCGGTCCATGCAGCATGCATTGGATTACACGCTCT
61 F F S I S A P V I D V G F W D V A F S F
181 TTCTTCAGCATTAGCGCGCCCGTTATTGACGTGGGCTTCTGGGATGTCGCTTTTTCCTTT
81 Y G T V P Y L V P V A I L L D F I F Y C
241 TATGGCACAGTGCCATACCTCGTGCCAGTAGCGATACTGCTCGACTTTATATTTTACTGC
101 R S W T R L F A F L F I P I V G L L N S
301 CGTAGCTGGACGCGGCTTTTTGCATTTCTCTTCATTCCGATCGTAGGTTTATTAAATTCC
121 G I L V T I L G D C S D C P R P C G S C
361 GGCATTCTAGTAACGATTCTCGGTGACTGCAGCGATTGTCCTCGTCCGTGTGGTAGCTGC
141 V S S N G M P S G H A T T A I G L F M W
421 GTTTCCAGCAACGGAATGCCGTCGGGGCATGCCACTACTGCTATTGGATTATTCATGTGG
161 I L L E S L L G V G Y Q W K V V K K V A
481 ATACTACTTGAGTCGCTGCTGGGCGTTGGTTATCAGTGGAAGGTGGTAAAAAAGGTTGCT
181 V C V G I T L L F V P V P Y S R I Y L G
541 GTTTGTGTGGGCATCACCCTGCTTTTTGTACCTGTGCCATACAGCCGCATTTATCTGGGC
201 D H T R L Q V V I G C I N G V L F G L F
601 GATCACACAAGATTGCAAGTCGTCATTGGATGTATAAATGGCGTCTTGTTTGGCCTTTTC
221 Y F F V L R Y G L G R R L S V A T K R I
661 TATTTCTTTGTGCTTCGTTACGGATTAGGAAGACGGCTGTCCGTGGCCACGAAGCGCATT
241 N E G R F H F L H M V N D F H V D R R Y
721 AATGAAGGGCGATTTCATTTTCTGCACATGGTTAACGACTTTCACGTGGATCGTAGATAC
261 L L D S Q F N V E D Q Q F V R S D V G Q
781 TTGCTTGATTCACAATTTAATGTTGAAGACCAGCAGTTCGTCCGATCTGATGTTGGGCAA
281 T -
841 ACCTAA

Bremia effectors enhance host susceptibility
121
BLR07
1 M H L N H V A A I F L V G V V T C F T E
1 ATGCATCTCAACCACGTTGCAGCCATCTTCCTTGTTGGAGTCGTGACGTGCTTCACGGAG
21 T I E G S K R R S E I I R E H L A Y P V
61 ACTATAGAAGGGTCCAAGCGTCGAAGTGAAATCATTCGTGAACATCTTGCATATCCTGTA
41 D V A I G S R A L R H T V A S E V K D K
121 GATGTGGCCATCGGTTCACGAGCTCTACGGCATACGGTAGCCTCTGAGGTAAAAGACAAG
61 G D T G P D L E E E R A W W E N A V Q E
181 GGGGACACTGGACCAGATCTAGAGGAAGAGCGAGCTTGGTGGGAGAATGCTGTACAGGAG
81 L R W R L K G P G D F F K S L D A V R K
241 CTGCGGTGGCGACTAAAAGGGCCTGGCGACTTCTTTAAAAGCTTAGATGCCGTACGCAAA
101 G K D L H T D R S F Q W W L H R A A Q F
301 GGGAAAGATTTGCATACTGATCGATCTTTTCAATGGTGGCTGCATCGCGCAGCCCAGTTC
121 R N A H N G F D T S F L K V L Q Q E T S
361 AGGAATGCCCATAACGGGTTTGATACTTCTTTTTTAAAGGTCCTTCAGCAAGAAACATCG
141 Y E Q Q A K L F V W L Q Y S N F Y R D M
421 TACGAGCAACAGGCAAAGCTTTTTGTATGGCTTCAGTATTCCAATTTCTATCGTGATATG
161 N A F A K D Q L L I M E A N P A S R H A
481 AATGCATTTGCGAAAGATCAGCTACTGATTATGGAAGCCAACCCTGCTTCTCGTCACGCC
181 V Y E A W L Q D G K T P G D I C D S S R
541 GTGTATGAAGCATGGCTACAGGATGGAAAAACACCTGGAGATATCTGCGATTCCAGTCGA
201 I G L N F E S W L G Y V V Y Y R S K G N
601 ATCGGCCTTAACTTTGAGAGTTGGCTTGGTTACGTTGTTTATTACCGATCCAAAGGAAAT
221 Q F T N K D I L K T L T S Q D L I K E A
661 CAATTTACCAATAAAGACATTCTCAAGACGCTAACGAGTCAAGATTTGATTAAAGAGGCT
241 V K K L I L L P G K K A N -
721 GTGAAGAAATTGATTTTACTACCTGGGAAAAAAGCGAATTGA
BLR08
1 M A E F R F R P T T L L F L I V A L I F
1 ATGGCCGAGTTTCGGTTCCGCCCCACGACATTGCTATTCCTGATTGTTGCTTTGATCTTC
21 R C A I D P V S A N A D L T P S P R L L
61 AGGTGCGCCATCGACCCTGTCTCCGCCAACGCCGACCTCACTCCCAGCCCGCGATTACTG
41 R D L V Q F D A T Q T V A H T L S N S P
121 CGCGACCTAGTGCAATTCGACGCGACACAGACTGTTGCCCACACCCTATCCAACTCTCCG
61 S A S S S S A E A T V H P A A S A E A S
181 AGCGCCAGCAGCTCCAGTGCAGAAGCGACNGTTCACCCCGCTGCCTCTGCTGAAGCATCG
81 A I S N H T T D N A A S A E S S A E S K
241 GCGATATCGAATCACACTACCGACAATGCCGCCTCGGCTGAGTCCTCGGCTGAATCGAAG
101 H E L P S I M S F I G P A A A G V L A I
301 CACGAATTACCGTCCATCATGTCGTTCATCGGCCCAGCTGCTGCTGGCGTGCTAGCCATC
121 V L I G A V I A F K Y R S S K -
361 GTGCTTATTGGGGCCGTCATCGCTTTCAAGTATCGCTCGAGCAAGTAA
BLR09
1 M R H K C L L A M A V V A S M A F Y S V
1 ATGCGTCACAAGTGCCTCCTAGCTATGGCTGTGGTCGCCAGTATGGCTTTCTACAGCGTC
21 I S T K N V T Q V D T V Q Q E N R R L R
61 ATCAGTACCAAGAACGTCACCCAAGTGGATACGGTGCAACAAGAAAACCGCCGTTTGAGA
41 P R V E P T A N E L D K Q S D V D T K L
121 CCCCGCGTAGAGCCGACAGCTAATGAGTTGGATAAGCAGAGTGATGTCGATACGAAGCTA
61 E A D R R L G Y P G E S G F M L E G E L
181 GAAGCAGATCGACGTTTGGGATACCCTGGAGAGTCGGGTTTCATGCTGGAAGGTGAATTG

122 Chapter 4
81 E E R G G F P W R T F F L G L F A S V I
241 GAAGAGCGAGGAGGATTTCCTTGGAGAACATTTTTTCTTGGTTTATTCGCNTCTGTAATT
101 G V S I I S A C Y G I T -
301 GGTGTCAGCATCATCTCTGCTTGCTACGGCATCACTTAA
BLR10
1 M R H K C L L A M A V V A S M A F Y S V
1 ATGCGTCACAAGTGCCTCCTAGCTATGGCTGTGGTCGCCAGTATGGCTTTCTACAGCGTC
21 I S T K N V T Q V D T V Q Q E N R R L R
61 ATCAGTACCAAGAACGTCACCCAAGTGGATACGGTGCAACAAGAAAACCGCCGTTTGAGA
41 P R V E P T A N E L D K Q S D V D T K L
121 CCCCGCGTAGAGCCGACAGCTAATGAGTTGGATAAGCAGAGTGATGTCGATACGAAGCTA
61 E A D R R L G Y P G E S G F M L E G E L
181 GAAGCAGATCGACGTTTGGGATACCCTGGAGAGTCGGGTTTCATGCTGGAAGGTGAATTG
81 E E R G G F P W R T F F L G L F A S V I
241 GAAGAGCGAGGAGGATTTCCTTGGAGAACATTTTTTCTTGGTTTATTCGCTTCTGTAATT
101 G V S I I S A C Y G I T -
301 GGTGTCAGCATCATCTCTGCTTGCTACGGCATCACTTAA
BLR11
1 M V R L Y L A V L A T F L A Q G N S P L
1 ATGGTTCGATTGTATCTCGCAGTGCTGGCAACTTTCCTCGCTCAAGGCAACAGCCCACTA
21 T L A A F Q Q V P A D A E L L A P D Q E
61 ACTTTAGCTGCCTTCCAACAAGTGCCAGCTGATGCCGAATTGTTAGCTCCTGACCAGGAA
41 G G S L S R R L R V Y D E T S A D E S E
121 GGTGGTTCTTTATCGAGAAGATTACGAGTGTACGATGAAACAAGTGCTGACGAAAGTGAG
61 R G G V S S L L A K L N A S S K P K L E
181 CGAGGAGGAGTCAGCAGTTTGCTAGCAAAACTAAACGCATCTAGTAAGCCAAAACTGGAA
81 D I L A S A K L K V G L D H I L K F Y L
241 GACATATTGGCGTCTGCAAAGTTAAAGGTAGGTCTCGATCATATACTAAAATTTTATCTC
101 F R L E D L E K Q I V K Y N K Y L P K D
301 TTCAGGTTAGAAGATCTGGAGAAACAGATTGTAAAATACAACAAATACTTGCCGAAAGAC
121 K Q L S L Y K L L R E H Q S I P N I A T
361 AAGCAATTATCATTGTATAAGCTACTGAGAGAACATCAAAGCATCCCCAACATAGCAACG
141 A L Y A A K V H I G D E L P P L I A R L
421 GCGCTATACGCCGCTAAAGTGCACATTGGCGACGAGTTGCCACCACTAATTGCTCGTCTA
161 W E D F R N E W K G I D G G I Q K L A N
481 TGGGAGGATTTTCGGAACGAATGGAAAGGAATCGACGGAGGCATACAGAAGCTTGCAAAC
181 E L D M V A D G K E A I L N G K V A V L
541 GAACTTGACATGGTCGCTGATGGTAAAGAAGCCATTCTTAATGGAAAGGTTGCGGTATTG
201 R D Y I A S F S K E N E V D T I L R E Q
601 CGGGACTATATTGCGTCATTCTCGAAAGAGAATGAAGTCGATACCATATTGCGCGAGCAA
221 L T I V F G G E K N L V S I L A K L Y S
661 TTGACGATCGTGTTTGGTGGTGAGAAGAACTTGGTGTCTATTCTTGCGAAACTTTATTCA
241 S A L G N R S A F L E I K P A L P I I E
721 TCGGCACTTGGGAATCGCTCTGCATTCCTTGAAATTAAACCGGCCTTGCCAATTATTGAA
261 S I Q L S V F D K W L K E G L S L N Q V
781 AGCATTCAATTATCTGTCTTTGACAAGTGGCTGAAGGAGGGCCTGTCGCTGAACCAAGTT
281 W S L I V S G R N K G Q D L S I G E Y S
841 TGGTCCCTTATAGTGTCCGGTAGAAACAAGGGCCAAGATCTTTCGATTGGGGAATATTCG
301 V F K A Y A N A F L D R Q M T L K S D K
901 GTGTTTAAAGCGTACGCAAACGCCTTTTTAGATCGTCAAATGACTCTCAAATCAGACAAA

Bremia effectors enhance host susceptibility
123
321 F V L Y S V K D I S A A P E A T F L D Y
961 TTTGTGCTTTATAGCGTAAAAGACATCTCGGCGGCACCCGAAGCGACTTTTCTCGATTAT
341 Y D L V L D M S L L D G E R L F F L L D
1021 TACGATTTGGTTTTGGATATGAGCCTTTTGGATGGCGAACGTTTATTTTTTCTATTGGAT
361 R V G A S S F V F E P D F Y R K L Q G F
1081 CGGGTCGGAGCTTCCTCATTTGTATTTGAGCCCGATTTCTATCGAAAACTTCAAGGATTT
381 D K T G D L P G L I T E A I A A K E K T
1141 GATAAAACCGGTGACCTTCCTGGTTTGATTACTGAAGCTATTGCGGCAAAAGAGAAAACG
401 F K L L N T N G E A I K T A K K R G T F
1201 TTCAAGTTACTTAATACAAACGGTGAGGCCATCAAGACTGCAAAAAAACGTGGAACTTTC
421 D V V T P E A K K I N H L Q N K W K Q D
1261 GATGTAGTTACGCCGGAAGCTAAGAAAATCAACCATCTTCAAAATAAGTGGAAGCAAGAC
441 M S F L L K A K H V A S S A K A R S S G
1321 ATGTCGTTTTTACTAAAAGCCAAGCACGTGGCAAGCAGCGCTAAGGCGCGTAGCTCTGGT
461 L K Y -
1381 CTCAAGTATTGA
BLR12
1 M G P G F S F T L L I F T L L T Y Y N E
1 ATGGGTCCTGGCTTCTCCTTCACTCTGCTCATCTTTACTCTACTTACGTACTACAATGAG
21 L S S A A V L S S T H S T S T D I A S S
61 CTTTCAAGTGCGGCTGTATTGAGCTCAACGCATTCAACGTCCACCGATATTGCTAGTAGC
41 R S I V R I A R R Y L R E T A A M E G Q
121 CGCAGCATCGTCCGTATCGCCCGTCGGTACCTTCGGGAGACCGCAGCTATGGAAGGACAG
61 E L E K N L G F D Q T I K N V K K P S L
181 GAGCTGGAAAAGAATCTTGGTTTTGACCAGACTATCAAGAACGTGAAGAAGCCCTCACTT
81 P Q K V Y E N V L E Y L G R M N G K S K
241 CCTCAGAAAGTCTATGAAAACGTACTCGAGTACCTTGGAAGAATGAATGGTAAATCGAAA
101 R D K F F V I A T L L L L P F G I F Y V
301 AGAGATAAGTTTTTCGTCATCGCGACTCTCTTGCTGCTTCCGTTCGGCATCTTCTACGTC
121 C N R -
361 TGTAATCGGTAG
BLR13
1 M K F V F V F G A L F A L F I R L N C A
1 ATGAAGTTTGTTTTTGTGTTTGGAGCGCTTTTTGCTCTCTTCATACGCTTGAATTGTGCC
21 A L V A R E A N S L E L S H D R A N F R
61 GCACTGGTGGCTAGGGAGGCAAATTCACTTGAATTGAGCCACGACCGAGCGAATTTTCGT
41 T I T R R L R I D T L N A S E E R N I F
121 ACAATCACGAGGAGGCTAAGAATTGACACTTTGAACGCTAGTGAAGAGAGAAACATCTTT
61 N F W R R K K H A N W E G L L N V D D V
181 AATTTCTGGCGTCGGAAAAAGCATGCAAACTGGGAGGGTCTTTTGAACGTTGATGATGTG
81 P Q F T P R Q I Q E N I K W S K K D L K
241 CCCCAATTCACTCCTCGTCAAATTCAAGAAAATATCAAGTGGTCGAAGAAGGACTTGAAA
101 E V L T A L N F R K V T S P E V T R Q K
301 GAAGTCTTGACGGCGCTGAACTTTCGCAAAGTGACAAGCCCAGAAGTTACGAGACAGAAG
121 M F Q L D E Y L D S L D L K T E V K T M
361 ATGTTCCAACTCGACGAGTATCTCGATTCGCTGGACCTAAAGACAGAGGTTAAGACGATG
141 D E I V A K R L K V L G M L K G N D W E
421 GACGAAATTGTAGCGAAAAGGTTGAAGGTCTTAGGCATGCTTAAAGGAAATGATTGGGAG
161 H T K E L K R H L A H V W V I K R I P V
481 CACACGAAGGAATTGAAGAGACATTTGGCTCATGTTTGGGTTATTAAAAGGATTCCTGTG

124 Chapter 4
181 R N V Y R G L K M N E E E S L E N L F S
541 AGAAACGTCTACAGGGGCCTAAAAATGAATGAAGAAGAGTCTTTGGAAAACCTTTTCTCG
201 I R S G E E T L D F F L D F F Y A T R K
601 ATTCGAAGCGGCGAAGAGACGCTTGACTTTTTCCTTGATTTCTTTTACGCCACTCGTAAA
221 Y H N D K E E L A E L F L E T Y D V A T
661 TACCACAATGATAAGGAAGAGTTGGCTGAATTGTTTCTCGAGACGTACGATGTAGCAACT
241 V L H L I N V G S R L D S A Q V F V A Q
721 GTCTTGCATTTAATAAATGTCGGATCGCGACTAGACTCAGCACAAGTATTTGTAGCGCAG
261 L E H S L H R K W S S M S H N K V F F D
781 TTGGAGCATAGTCTTCACCGCAAGTGGAGCTCAATGAGCCACAATAAGGTGTTTTTCGAT
281 I L H L D K K G S Q V F N T F E M Q T W
841 ATTCTTCACCTCGACAAAAAGGGATCTCAAGTCTTTAATACGTTTGAGATGCAGACGTGG
301 Y R F I K G T D P D E A E A K T L I F L
901 TACCGATTTATTAAAGGCACCGATCCTGACGAGGCAGAAGCCAAAACATTAATTTTTTTG
321 I H S Y G T A F L S D E L I R G Q G Q S
961 ATCCATAGCTATGGCACCGCTTTTCTCTCGGACGAGTTGATTCGTGGACAAGGACAATCG
341 I S S L R P I F R K A L L D H W A K Q K
1021 ATCTCATCGCTACGTCCGATTTTCCGAAAAGCGTTGCTTGATCATTGGGCAAAGCAGAAA
361 T G S -
1081 ACTGGATCTTAG
BLR14
1 M R L L D V L V A F V I L A A T S S A M
1 ATGCGTCTGCTTGACGTGCTCGTTGCTTTCGTTATCCTCGCTGCTACATCTTCGGCGATG
21 N S A A Q L T P S V D T Q L A D R K H S
61 AATAGCGCTGCTCAGCTTACGCCATCAGTCGACACACAATTGGCCGACAGAAAACATTCT
41 T E D V R R K L R G F N P I T Y L S L K
121 ACCGAGGATGTACGACGAAAATTACGAGGTTTCAATCCGATAACGTATCTAAGTCTCAAA
61 I K E N V A K K V L S K V F S -
181 ATCAAGGAGAACGTTGCCAAGAAGGTATTGTCCAAGGTTTTCAGTTGA
BLR15
1 M Q V C F H V T A L V M I N A L S I S S
1 ATGCAGGTCTGTTTCCACGTTACTGCGTTAGTCATGATCAATGCGCTGTCGATATCAAGT
21 L T S A K F S L G T A A F A L E P S H M
61 CTCACCTCGGCAAAATTTAGCTTGGGCACTGCAGCATTTGCACTTGAACCATCTCACATG
41 E S H E A M R S L R A Q Q T S T L D V D
121 GAGAGCCACGAAGCCATGCGATCGCTGCGGGCCCAACAAACTTCAACTCTCGACGTTGAC
61 E E R L R F K L T R L V G N I C E K I V
181 GAGGAGCGCTTACGCTTCAAACTTACACGTCTTGTGGGAAATATTTGTGAAAAGATTGTT
81 D A F Y R V K N R T K V F Q G E F F P P
241 GATGCTTTCTATAGAGTGAAGAACCGTACTAAGGTTTTCCAGGGTGAGTTCTTTCCTCCA
101 D P -
301 GATCCTTGA
BLR16
1 M Q L P F H V L A L V T T Y A L S T I S
1 ATGCAGCTTCCTTTCCACGTTTTAGCGTTAGTCACGACCTATGCGCTGTCAACGATTAGT
21 Q T S A E S S L V R A T F A H E R Y H M
61 CAAACCTCTGCAGAATCCAGCTTGGTCCGTGCAACATTCGCGCATGAGCGATATCATATG
41 E S L E V K R S L R G Q Q T S P L K D D
121 GAGAGCCTCGAAGTCAAGCGATCGCTAAGAGGCCAGCAGACTTCGCCTCTCAAAGATGAC
61 D E R I S L K D V V G K I K G I I R K I
181 GACGAGCGCATCAGTTTGAAAGATGTCGTGGGAAAGATTAAAGGCATAATCCGAAAAATT

Bremia effectors enhance host susceptibility
125
81 M P Q R K G T L R K T K T Y R S L P I -
241 ATGCCTCAAAGAAAAGGCACCTTACGAAAAACCAAAACATACAGATCGCTTCCTATCTAG
BLR17
1 M F S T V L F L V A A C A K S S Y G H S
1 ATGTTTAGCACGGTGCTTTTTCTTGTGGCTGCGTGCGCCAAGTCGTCGTATGGCCACAGT
21 V S I F T R D S T K Y I A S N F D E Y S
61 GTGTCCATATTTACGCGTGACTCTACTAAGTACATTGCGTCAAACTTCGACGAGTATTCG
41 T I P E D I D A K R R L R E A V G V D G
121 ACGATCCCAGAGGATATTGATGCAAAGCGCAGGCTTCGAGAAGCTGTTGGCGTGGATGGG
61 I A R D A E K T F A D I R H S L D R L N
181 ATTGCGCGCGATGCTGAAAAGACTTTTGCAGACATTAGACACTCACTCGATAGACTGAAT
81 K D F V R S N S F K N I N P L I T A E A
241 AAGGACTTTGTGCGTTCAAATTCATTTAAGAACATTAATCCATTAATAACGGCAGAAGCT
101 L V K Q P S F Y Q E A F L P L I T A R G
301 TTGGTCAAACAACCATCTTTTTATCAAGAAGCTTTCTTACCGCTCATAACAGCTCGTGGG
121 I K C S K D F E F A T M A L L G V S P G
361 ATAAAATGTAGCAAAGATTTTGAATTTGCCACAATGGCTTTGCTCGGTGTATCTCCGGGT
141 T L R Q K I Q V A A Q Q P S N I W S Y Q
421 ACTTTGAGACAGAAGATACAGGTAGCAGCACAACAACCCTCCAATATATGGAGTTACCAG
161 T S E Y N E H F V A S Y K K Y L D V V F
481 ACCTCGGAATACAATGAACATTTTGTCGCCAGCTACAAGAAGTATCTCGACGTTGTTTTT
181 M A P T I S E S S A F V K K H I S M S I
541 ATGGCACCGACCATATCAGAATCGTCCGCCTTTGTCAAGAAGCACATCTCAATGTCTATA
201 P E P S E M T Y K L L N A A V I Q L L Q
601 CCTGAGCCGTCCGAGATGACTTATAAGCTTCTCAACGCTGCCGTTATTCAACTGTTGCAG
221 L A I R N V D D V N E L A K L A T S V T
661 TTGGCCATTCGAAATGTAGATGATGTCAACGAGTTGGCGAAATTGGCGACATCGGTTACG
241 F K Y A L E H D E E F S T I M M F G N L
721 TTCAAGTACGCGCTAGAGCACGATGAAGAGTTTTCTACCATTATGATGTTTGGAAACCTG
261 E A W I S N P V L N K L L M V H Q V L L
781 GAAGCTTGGATTTCCAATCCCGTTTTGAACAAACTTCTTATGGTCCATCAGGTCTTACTA
281 K S -
841 AAATCGTAG
BLR18
1 M R T T F F L T V V I A M F C A C I T A
1 ATGCGCACGACATTTTTCCTGACCGTCGTGATAGCAATGTTCTGTGCTTGTATCACTGCG
21 I E T L E G P T T T G R E P N I A D A T
61 ATTGAAACTCTAGAGGGTCCAACTACAACGGGACGTGAGCCGAACATTGCGGACGCAACC
41 P T V V A R A L R G A V A F N E D R L D
121 CCTACTGTCGTTGCAAGGGCGTTGCGAGGTGCCGTGGCGTTCAATGAAGATCGACTTGAT
61 L E G L T N S V A T L F D G A L H E I N
181 CTCGAAGGTCTTACTAATTCCGTTGCTACTTTGTTTGATGGCGCGCTTCATGAAATAAAT
81 P E L V R T A K A L N E -
241 CCGGAGCTTGTGCGAACTGCGAAAGCTCTCAACGAATAA
BLR19
1 M L L S R A I S V V A L L A C I X C G A
1 ATGCTTCTTTCCCGCGCNATATCTGTCGTCGCCCTTCTCGCATGCATTCNTTGTGGGGCG
21 H A Q D S E V D L G T L L T T L D S S M
61 CACGCTCAAGACTCGGAAGTAGATCTCGGGACTCTATTGACCACCCTTGACAGTTCGATG
41 V T S Q R L L R T S V D L D N N E E R V
121 GTCACTTCGCAGCGGCTTCTCAGAACGAGCGTGGACTTGGACAACAACGAAGAACGCGTC

126 Chapter 4
61 K W P F Q N L V T D Y L N Q K A I R K S
181 AAATGGCCATTTCAAAATTTGGTCACTGATTATCTTAATCAGAAAGCAATCAGGAAAAGT
81 L V N Q A K K T V N A H D E N V L E E A
241 CTCGTAAATCAGGCCAAAAAAACAGTTAACGCTCACGATGAGAACGTATTGGAGGAAGCG
101 V K K E I N A G R V K N V K Q A L S K L
301 GTGAAGAAGGAGATAAATGCAGGTCGCGTGAAAAATGTCAAGCAAGCGTTAAGCAAACTG
121 K N G D P A K A K L Q R L Y N A E I L R
361 AAAAATGGCGATCCCGCAAAAGCTAAACTACAACGACTCTACAATGCTGAAATTTTAAGG
141 N L P K T H N S G Q V R I S R D K V S R
421 AATTTACCAAAAACACATAATTCAGGTCAAGTTAGGATCTCGAGGGACAAAGTCAGCAGG
161 -
481 TAA
BLR20
1 M R F I L V I F M T A A T I C A S W E T
1 ATGCGCTTTATTCTCGTCATTTTTATGACTGCAGCCACAATATGTGCAAGTTGGGAGACC
21 I S V E K D G E H D K L L V I T S T T R
61 ATTTCGGTTGAAAAGGATGGCGAACATGATAAACTTTTGGTAATAACTTCAACAACTCGC
41 Y L K E D Y G A V S N S R L L R V S V G
121 TACCTCAAGGAAGACTATGGTGCCGTCTCCAATTCGCGGCTTTTGCGCGTCAGCGTCGGC
61 S N Q S G T M Q D E A D I G E D S Y M D
181 TCCAACCAAAGTGGAACCATGCAAGACGAAGCGGACATTGGCGAAGACTCCTACATGGAT
81 T V Y F K L W R L I G K T P G E V Y T D
241 ACTGTGTACTTTAAGCTCTGGCGTTTGATTGGCAAGACGCCTGGTGAGGTATACACCGAC
101 S F G T M D P A S A A Q N P S Y N R Y I
301 TCATTCGGTACCATGGACCCAGCCTCTGCTGCCCAGAACCCAAGCTATAATAGGTATATT
121 R Y K R Y Y N N H H -
361 CGATACAAACGATACTACAATAATCATCATTAG
BLR21
1 M R T C F L I F V A G A T I L L S T K A
1 ATGCGTACTTGTTTCTTGATCTTTGTGGCTGGGGCAACGATTTTACTCAGCACTAAAGCT
21 S N P E D D V E D R G S A I G Q V R R I
61 TCCAACCCTGAAGACGACGTCGAAGACCGCGGATCAGCAATTGGTCAAGTGAGAAGAATT
41 L R P K T I N Y G A L E P G R S N P L Y
121 TTACGGCCTAAAACGATCAACTACGGGGCGTTGGAGCCTGGTCGATCAAATCCTCTGTAT
61 N D P R Q -
181 AATGACCCTAGGCAATAG
BLR22
1 M L S C K K T F A L C A T A A L I M S G
1 ATGCTTTCCTGCAAAAAAACTTTCGCGCTATGCGCAACTGCGGCTTTGATCATGTCTGGC
21 F S E V E S S I A S Y R R G L R E G A V
61 TTTTCAGAAGTAGAATCCAGCATCGCAAGTTACAGACGCGGCCTGAGGGAGGGCGCTGTA
41 S G E G Y S D K M D Y K R K H Y E H T D
121 AGCGGTGAAGGCTACAGCGACAAGATGGATTACAAGAGAAAACACTATGAACACACCGAT
61 S D G D V G H N G D D T V L Y Q D S Q L
181 TCGGATGGAGACGTTGGCCACAACGGCGATGATACGGTTTTGTATCAGGACTCGCAGCTA
81 H D G L I D I D L V A K L E L A L G L L
241 CATGACGGGCTCATTGATATCGACCTCGTCGCTAAACTTGAACTTGCACTTGGGCTATTG
101 R E D G V D L L S H H N G A L Q H Q N G
301 CGCGAAGATGGAGTCGACCTTTTGAGCCACCACAACGGCGCCTTACAACATCAGAACGGG
121 E S P L H L D D L L E I G V G L E I A I
361 GAGTCACCATTGCACTTGGATGACCTTCTCGAAATCGGCGTCGGTCTTGAAATTGCAATT

Bremia effectors enhance host susceptibility
127
141 D L L R E K G V G L L N H H G A E Q H Q
421 GATCTGTTGCGCGAAAAAGGAGTCGGCCTTTTGAACCACCACGGTGCTGAACAGCATCAA
161 N A E T P L H L D N I V D I D A D V G V
481 AACGCGGAGACGCCATTGCACTTGGATAACATTGTTGACATCGATGCCGATGTAGGAGTT
181 D L L S V -
541 GATTTGCTTTCCGTTTAA
BLR23
1 M R L R G S F V T L V A I I A V F Y Q G
1 ATGCGTCTTCGTGGTAGCTTCGTTACATTGGTCGCAATCATCGCGGTTTTCTACCAAGGT
21 E G M D F Q A A S A T F K H V R S P I Q
61 GAAGGTATGGATTTCCAAGCGGCTTCCGCCACCTTCAAGCATGTACGGTCTCCTATACAG
41 N P P N F E M E S V P S A Q M T R S L R
121 AACCCCCCAAACTTCGAAATGGAGAGTGTACCAAGCGCCCAGATGACTCGATCTCTAAGG
61 V D E N R N G G Q L G S D A K T I I T K
181 GTTGACGAAAATCGCAATGGAGGGCAGCTCGGAAGTGATGCGAAAACGATCATAACTAAG
81 V K F P K K A F E N L T M K I K H N P F
241 GTCAAGTTTCCAAAGAAGGCATTTGAAAACCTAACGATGAAGATTAAGCACAATCCATTT
101 Y P A K H I N -
301 TATCCAGCCAAACATATTAATTAA
BLR24
1 M T F A A V M E M S T V K I T L A L A V
1 ATGACATTTGCCGCGGTTATGGAGATGAGTACTGTGAAAATAACTTTAGCTCTGGCTGTT
21 A W G V L A K H G K A D K E E H L E I Y
61 GCATGGGGCGTACTCGCCAAACATGGTAAAGCTGATAAGGAAGAGCATTTGGAAATATAT
41 L C A P I G I E I G E K I L R S L R V Q
121 TTATGCGCTCCGATTGGAATAGAGATTGGCGAAAAAATATTGCGGTCGCTCCGCGTGCAG
61 S P R I S F S G C K K H Y E L E Q A G R
181 AGCCCAAGAATCTCGTTCTCCGGCTGCAAAAAACACTATGAATTAGAGCAGGCGGGGCGA
81 L W S Q L L H F K L T -
241 CTTTGGAGCCAATTGCTTCACTTTAAGTTRACATAA
BLR25
1 M V R S T S K G L T S C T V R R L M L L
1 ATGGTGCGCTCCACGTCCAAGGGTTTAACGTCTTGTACCGTGCGCAGACTCATGCTGCTG
21 A V F A L S A C V A T L S T S P N T M T
61 GCAGTTTTTGCTCTATCAGCGTGCGTGGCAACCCTCTCGACGAGTCCTAACACTATGACT
41 L S S Y R H L K E L P D T R R A L R F P
121 CTTAGCTCTTATCGACACTTGAAAGAGCTGCCTGACACACGACGAGCTCTGCGCTTTCCG
61 K T G S I R T T T C S K Q W L N S W K L
181 AAAACAGGCTCAATTCGTACTACGACTTGCTCAAAGCAATGGCTCAACAGCTGGAAGTTG
81 A F -
241 GCATTCTGA
BLR26
1 M M P V P S E L V I T Q H R R I L L L F
1 ATGATGCCTGTACCATCCGAGCTTGTAATAACTCAGCACAGGCGTATATTACTGCTATTT
21 L A L L A G V T I V M A A T T A P N A V
61 TTGGCTCTGCTGGCGGGCGTGACAATTGTCATGGCGGCAACAACAGCACCAAACGCTGTC
41 A G V F R R R L R E V P N A L V D G Q N
121 GCCGGTGTCTTCCGTCGACGATTAAGAGAGGTGCCAAACGCTCTTGTCGACGGGCAGAAC
61 D E R N S S P S I A V R Q I A E K S L A
181 GATGAAAGGAACAGCTCTCCAAGTATTGCCGTCCGGCAAATTGCGGAAAAGTCGTTGGCA

128 Chapter 4
81 S A K T K G I L P K N F E E F A E N F S
241 TCGGCGAAAACGAAAGGCATTTTGCCGAAGAACTTTGAAGAATTCGCCGAAAACTTTTCA
101 K N N Y S G N D D L D H R M Y A F L N A
301 AAGAACAATTACTCAGGGAATGACGACTTGGATCATCGCATGTACGCATTCCTCAATGCT
121 L T K N K R E A L E Y V F S P N W L Q K
361 CTTACAAAGAATAAAAGAGAAGCTTTGGAGTATGTATTTTCGCCAAATTGGTTGCAGAAA
141 P H A L R F Y N F L V N R W S K Q K L G
421 CCCCACGCGCTGAGATTTTACAATTTCTTAGTAAATCGGTGGTCTAAACAAAAATTAGGC
161 Q N L H L D G I S R E D L N A L I G L K
481 CAAAATTTGCACTTGGACGGGATAAGCCGAGAGGACCTAAATGCTTTGATTGGATTAAAA
181 T R L E K T L -
541 ACGCGACTCGAAAAAACATTATAA
BLR27
1 M T K Y K C S S L I C S L L L L S C Y H
1 ATGACCAAGTACAAGTGCTCGTCGTTGATCTGCTCCCTCCTCCTGCTATCCTGCTACCAC
21 V V T S I E N V A L I E A P V L G K S R
61 GTCGTGACAAGCATCGAGAACGTCGCGCTGATTGAGGCGCCAGTCCTCGGCAAGTCTCGA
41 Q L R S S V E L V E G L L L T S D K L A
121 CAATTACGCTCGAGTGTCGAGCTGGTGGAAGGATTATTGCTTACCTCAGATAAATTGGCC
61 K V I G T L P K N L A K E W L A T F K W
181 AAGGTTATAGGTACACTGCCAAAAAACCTGGCCAAGGAATGGCTCGCGACCTTCAAATGG
81 G I N H F K I L L A E D K V A A A G K I
241 GGTATCAATCATTTCAAGATCCTGCTCGCAGAGGACAAGGTCGCGGCCGCTGGTAAAATT
101 F P D D S A N P I M T K L F E S D A F L
301 TTCCCCGATGATTCGGCCAATCCCATAATGACAAAGCTCTTTGAAAGTGATGCCTTTCTA
121 W W E K L I R R T V D D T Q E E V D T I
361 TGGTGGGAAAAACTCATTCGACGAACTGTAGACGATACCCAAGAGGAAGTGGACACGATC
141 I T S A L V T R L G K G R A I K L F T E
421 ATTACTTCAGCACTCGTGACCAGACTTGGCAAAGGCAGGGCCATCAAACTCTTTACGGAA
161 A G F E A D A I N A K W L A L L Y H A L
481 GCAGGGTTCGAGGCCGATGCGATCAATGCCAAGTGGTTGGCCTTGCTATATCATGCATTG
181 D D E D M P K L F K E I V S S G G F D K
541 GACGATGAAGATATGCCGAAGTTATTTAAAGAGATCGTTTCGAGTGGAGGTTTCGATAAG
201 N S V E F F I K L C A R E N N K D A A Y
601 AACAGCGTCGAGTTTTTCATTAAGTTATGTGCAAGGGAGAACAATAAAGATGCCGCGTAT
221 E I I N S L L Q D K K E Y R E V Y Q K F
661 GAAATTATCAATAGTCTGCTGCAAGACAAGAAAGAATATCGGGAGGTTTATCAGAAATTC
241 D G V V E T Y R T K W D S L K S V Y F K
721 GATGGAGTTGTCGAAACGTACCGTACCAAATGGGATTCTCTCAAAAGCGTGTATTTCAAG
261 A V S D P K L D K S V S P M Q R L R N L
781 GCAGTATCCGATCCGAAACTTGATAAAAGTGTTTCACCAATGCAGAGGCTTCGGAATTTA
281 Y Q T E E L D P V S V A S K I A D I Y A
841 TACCAAACTGAAGAGCTCGATCCTGTGTCCGTGGCATCAAAAATTGCCGACATTTATGCC
301 K T S E G L H L L Q I V K Q T L H D K A
901 AAAACGTCGGAAGGTCTTCATTTACTTCAGATCGTAAAGCAGACGTTGCATGATAAGGCA
321 A T E A D K A F A G L V L D K V H V K W
961 GCAACGGAAGCTGATAAAGCGTTTGCTGGACTAGTCTTGGACAAAGTACATGTGAAGTGG
341 I Q T N Y D V G K M L K S L T R K I K P
1021 ATTCAAACTAATTATGACGTGGGCAAGATGCTCAAGTCTCTTACGCGCAAAATTAAACCA
361 V E T L L N T S E G V A F V F A I R E M
1081 GTCGAAACTCTTCTTAATACGTCAGAGGGTGTGGCATTTGTATTTGCCATAAGAGAAATG

Bremia effectors enhance host susceptibility
129
381 K A T E S E G Y S E A V G V F R K T F E
1141 AAGGCGACCGAGTCGGAAGGATATAGTGAGGCGGTCGGTGTGTTTCGAAAGACTTTTGAG
401 A D V L E K M M K N A N S D D T I V A G
1201 GCCGACGTTCTCGAAAAGATGATGAAAAACGCAAATTCAGATGACACTATTGTCGCGGGC
421 F I D A Y I E L M G V K I A -
1261 TTCATTGATGCCTATATAGAGCTTATGGGGGTCAAAATAGCTTAA
BLR28
1 M L R V V L F L V A A C A K T S Y S H T
1 ATGCTCCGTGTGGTGCTTTTTCTTGTGGCTGCGTGTGCCAAGACTTCGTACAGCCATACT
21 V A L S T R N S Q Y I A S K A N E H A T
61 GTGGCGCTATCCACGCGTAACTCGCAGTACATTGCGTCGAAAGCCAACGAGCATGCTACG
41 I P E D I N L N R R L R K A A V I T E V
121 ATTCCAGAGGACATCAACTTAAACCGCAGGCTTCGCAAAGCTGCTGTGATTACAGAGGTA
61 A E T L E S I I E A F N P L R T L R S D
181 GCCGAGACTCTTGAATCTATAATTGAAGCGTTCAATCCACTACGAACTTTAAGAAGTGAT
81 V R S E M S S K T K L E Q D A M L K E P
241 GTCAGATCGGAGATGTCATCGAAAACTAAACTCGAACAGGATGCAATGCTTAAGGAACCA
101 S F Y F R M L K P F S E F R I R A C F E
301 TCGTTTTATTTCAGAATGTTGAAACCTTTCTCTGAATTTCGAATTCGCGCATGTTTTGAG
121 V Y E I D T L I L F G T S P H L L K Q Y
361 GTTTATGAAATCGATACGTTGATTCTGTTTGGTACGTCTCCTCATTTATTGAAACAATAT
141 I Q N G I P R G I L P E S V T V L A T T
421 ATTCAAAATGGAATACCTCGAGGTATCCTCCCCGAAAGCGTAACTGTACTTGCAACTACT
161 G E K L K R F Q R Q F D I F F N P P T G
481 GGAGAAAAACTGAAGCGGTTTCAAAGGCAGTTCGATATATTTTTTAATCCGCCAACAGGG
181 S K P S K P S R A W P Y A R G P Q V Q A
541 TCAAAACCGAGTAAACCCAGTCGCGCTTGGCCTTACGCCCGGGGCCCTCAAGTTCAAGCG
201 N F K K I Y S S D H I K F L A Y A F H H
601 AATTTTAAAAAGATCTATAGTTCCGACCATATTAAATTTTTGGCATACGCCTTTCACCAT
221 L D D V N I L A K L S S S I I Y R F V L
661 CTTGATGATGTGAACATCTTGGCGAAATTGTCGTCATCAATTATTTACAGGTTCGTTCTC
241 D N F K E C R A T I R Y G T V E D W Y K
721 GACAATTTTAAAGAGTGCCGAGCTACTATTCGTTATGGAACGGTGGAAGACTGGTACAAA
261 H P M L N K L L R V H E V C R K F G I -
781 CATCCCATGCTGAACAAACTTCTTCGAGTGCATGAGGTCTGTCGAAAGTTCGGAATATAG
BLR29
1 M I G N F K K G L F V A A V A V A L A T
1 ATGATTGGAAATTTTAAGAAAGGTTTGTTCGTGGCCGCCGTGGCAGTGGCCCTGGCCACA
21 S V E G Y T G A A S Y E S K R M L R Q Q
61 AGTGTCGAAGGGTACACGGGTGCCGCATCCTATGAATCAAAGCGCATGCTTCGACAGCAG
41 T Q A I A E E S V A D D P E C G S L E M
121 ACGCAAGCAATTGCAGAGGAATCAGTTGCGGACGATCCCGAGTGCGGTTCGCTAGAAATG
61 A E I D D P E C G S L E M A E E N N D N
181 GCCGAGATTGACGACCCCGAGTGCGGATCGCTCGAAATGGCCGAAGAGAACAATGACAAC
81 N D N N D N T N D N N N N Y S S G N N G
241 AATGACAACAATGACAATACTAACGACAATAACAACAATTACTCAAGTGGCAACAATGGC
101 N N G N F W T P P D N G N N G N S G N Y
301 AACAATGGCAACTTTTGGACGCCGCCAGACAACGGCAACAACGGCAACAGTGGCAATTAT
121 W T P P D G K K N L H T G Q E G T P S G
361 TGGACGCCACCCGATGGCAAGAAGAATTTACATACGGGCCAAGAAGGAACGCCTTCTGGT

130 Chapter 4
141 Q D T K G N T V I Q T D D T V S N E A E
421 CAGGATACCAAGGGGAATACTGTAATCCAAACGGACGATACCGTGAGCAATGAGGCAGAG
161 T I D P E C G S L D M A E E D N G N E G
481 ACGATAGACCCCGAGTGTGGGTCTTTGGATATGGCCGAGGAGGACAATGGCAATGAAGGA
181 G N Q K S E N P S I K S N L N G G G N A
541 GGCAATCAGAAGTCTGAAAATCCGTCAATAAAGAGTAATTTGAACGGCGGCGGAAACGCT
201 G E K Q E S N K D E K K D G N T N T K E
601 GGCGAAAAACAAGAGTCTAACAAGGATGAGAAGAAAGATGGCAACACGAATACCAAGGAA
221 E N K E S N N G D K N T L Q Q D I G G D
661 GAGAACAAGGAATCCAACAATGGCGACAAGAATACGCTTCAACAAGACATTGGAGGCGAT
241 E V G K A G P Y G D G V E P E C G S L D
721 GAAGTAGGTAAAGCTGGACCCTACGGAGATGGCGTTGAGCCCGAGTGTGGGTCGCTTGAT
261 M A E D N D E C D S L E M A E I G Q E G
781 ATGGCCGAAGACAACGACGAGTGTGATTCGCTTGAAATGGCGGAAATTGGGCAAGAGGGC
281 K S D A V F T G S K S N L S F S P Y Q G
841 AAGAGCGATGCTGTGTTTACTGGATCAAAGTCGAACCTTTCCTTTTCGCCGTACCAAGGT
301 E V N V G T V S P P P -
901 GAGGTCAACGTTGGCACCGTATCCCCCCCGCCTTAA
BLR30
1 M Q V C F K I T A L V M I N A L S I S S
1 ATGCAGGTCTGTTTTAAGATTACTGCGTTAGTCATGATCAATGCGCTGTCGATATCAAGT
21 L I S A E S S L G T A A F A L K T P H M
61 CTCATCTCGGCAGAGTCCAGCTTGGGCACTGCAGCATTTGCGCTTAAAACACCTCACATG
41 E S H E A M R S L R A R H T S T L N V D
121 GAGAGCCACGAAGCCATGCGATCGCTGCGGGCCCGACATACTTCTACTCTCAACGTTGAC
61 E E R L R L K L L R R V E Y I C E K I V
181 GAGGAGCGTTTACGCCTCAAACTTTTACGTCGTGTGGAATATATTTGTGAAAAGATTGTT
81 E A Y N R V K N R N K V F H V E H L P E
241 GAAGCTTATAATAGAGTGAAGAACCGTAATAAGGTTTTCCATGTTGAGCACTTACCAGAA
101 R -
301 CGTTGA
BLQ01
1 M L A L S K I I E A V V I A S I L I G S
1 ATGCTTGCTCTATCCAAGATCATCGAAGCGGTGGTCATCGCATCAATACTCATTGGTAGT
21 S S S F P M E K I S S A T S N D Q T R H
61 AGCAGTTCTTTTCCAATGGAGAAGATTTCGTCAGCAACTTCGAATGACCAAACTCGTCAC
41 Y G F E Q G N G Q L L R G A E K T R L K
121 TACGGATTTGAACAAGGAAACGGACAGCTTTTACGTGGAGCCGAAAAGACGCGTCTCAAG
61 D E E Q R F F K F G L P S W L P K L F -
181 GACGAAGAACAAAGATTTTTTAAATTCGGTCTGCCAAGTTGGTTGCCAAAACTATTTTGA
BLG01
1 M V R V Y V A A L T G F L A L S A S A S
1 ATGGTTCGTGTCTACGTCGCCGCATTGACAGGTTTCCTCGCGCTTAGCGCGTCGGCCTCT
21 A T L Q L T S V N E S L A D A Y D S T A
61 GCTACTTTACAGTTGACGTCGGTAAACGAATCATTGGCTGATGCTTATGACAGTACCGCT
41 P A R G K L R A Y A A T N V E S D E R A
121 CCTGCACGAGGGAAATTACGCGCTTACGCAGCAACAAATGTCGAGAGCGACGAAAGAGCT
61 F S N L L E H L K T L N V L F S P L S K
181 TTCAGTAATTTACTTGAACATCTCAAAACCCTTAATGTTTTGTTCTCGCCGCTTTCAAAG

Bremia effectors enhance host susceptibility
131
81 E R M E A A I S K S D S S V V K H L S E
241 GAGCGCATGGAAGCAGCAATATCTAAAAGCGACAGCAGCGTGGTCAAGCATCTCTCGGAG
101 D G A V N E K K L G I G R D G V K A F E
301 GATGGAGCGGTCAACGAGAAGAAACTTGGAATTGGAAGAGATGGTGTAAAAGCTTTTGAA
121 P A K V S K V K M I L E D I F R K P Y N
361 CCTGCAAAAGTTTCGAAGGTGAAGATGATTCTAGAAGACATCTTTCGAAAGCCTTACAAT
141 K I L L K V L S K A N G G E R N L V R N
421 AAAATTTTGTTGAAAGTGCTTTCGAAAGCGAATGGGGGTGAGCGAAATCTAGTGCGCAAC
161 L A Q A E M L G Y K V F F L K S T L A S
481 TTAGCGCAAGCGGAAATGCTCGGTTATAAAGTGTTTTTTCTTAAGTCAACTCTCGCTTCC
181 K W E R D G V S L M D V W S Y I C K D V
541 AAGTGGGAGCGAGACGGTGTGTCGCTGATGGATGTCTGGTCATATATCTGCAAAGATGTG
201 K A P T E E E M K I F S H W C G Y A F V
601 AAAGCCCCAACTGAAGAGGAAATGAAGATTTTCTCGCACTGGTGTGGATATGCTTTTGTT
221 L S A K G K F S A E E T V I E K T L L K
661 CTATCGGCGAAAGGGAAATTCTCGGCAGAGGAGACTGTTATTGAAAAGACGCTCCTCAAA
241 V H N D N K N K K G K L A I N M L A Q I
721 GTTCATAATGACAACAAGAACAAGAAAGGCAAGCTTGCAATCAACATGCTGGCTCAGATT
261 H L S R K F K V D A N F F E L Y D P S P
781 CACCTGTCGCGCAAGTTTAAGGTCGATGCCAATTTCTTTGAATTGTATGATCCGTCACCT
281 S S L K K L L L E L E K S P R A C D L D
841 TCTTCACTCAAGAAATTATTGCTTGAACTTGAGAAGAGTCCGCGTGCTTGCGATCTCGAT
301 V E L Y R L L K Q A V T D D K F M K G I
901 GTAGAGTTATATCGACTTCTCAAACAGGCTGTAACCGACGATAAGTTCATGAAAGGCATT
321 W D R S T K K P E Q P N A K R N -
961 TGGGACAGATCGACCAAGAAGCCTGAACAGCCCAACGCCAAACGAAATTAG
BLG02
1 M V R I Y V A A L T V V L A F S A S C S
1 ATGGTTCGTATCTACGTAGCCGCATTGACCGTCGTCCTCGCGTTTAGTGCCTCGTGCTCT
21 A T S P L T L A K A T P V T A N G S G G
61 GCTACTTCACCACTGACGCTGGCAAAAGCTACACCAGTTACTGCTAATGGAAGTGGCGGT
41 R A Q G R L R A H T T T N V E I D E R S
121 CGTGCTCAAGGGAGATTACGCGCTCACACGACAACAAATGTCGAAATCGACGAGAGAAGC
61 I S D V I Y A I A R Q V A D H R S N L V
181 ATTTCTGACGTTATATATGCTATAGCTCGTCAAGTTGCAGACCACCGTTCTAATTTGGTA
81 Q A P K R T Y T T Y L A T L D L S L D K
241 CAGGCTCCAAAAAGAACATATACTACGTATTTAGCTACACTGGACTTATCCTTAGATAAA
101 V L E Q N W S E L R L L Y V K Q T K R K
301 GTTCTCGAACAGAATTGGAGTGAGCTTCGATTGTTGTACGTGAAGCAAACTAAAAGAAAG
121 R P K D F V S M Y E L L V K K Y G L L K
361 CGTCCAAAAGACTTTGTCTCAATGTATGAGCTGTTGGTAAAAAAGTATGGCCTCTTGAAA
141 L T D M M K K P D Y I S L S E T D N F K
421 TTGACTGACATGATGAAGAAGCCAGATTATATCTCATTAAGCGAAACGGACAATTTTAAG
161 Y L Y D E A S V Y W R K N S V L K Q Y A
481 TATCTGTACGACGAAGCAAGCGTGTACTGGAGAAAAAACAGCGTTTTAAAGCAGTATGCG
181 S E L Y D S K G N S K T F D V T D F E S
541 TCTGAACTATATGATAGCAAAGGGAATAGCAAAACGTTCGACGTAACCGACTTTGAAAGC
201 L Q P F F E R I G R R G D Y L E I T A A
601 CTGCAACCTTTTTTCGAACGCATCGGCCGTCGCGGTGATTATTTGGAGATTACTGCTGCC
221 E H E K W K T N K L R P T -
661 GAGCATGAGAAATGGAAAACGAACAAATTGCGACCTACTTAG

132 Chapter 4
BLG03
1 M V R V Y V A A L A A I F A L S A S A T
1 ATGGTTCGTGTCTACGTCGCCGCATTGGCAGCCATTTTCGCATTAAGTGCCTCTGCTACT
21 L H L T L A N A S S V T T E E G D G R P
61 TTACATTTGACGCTCGCAAACGCTTCATCGGTAACTACTGAAGAAGGTGACGGTCGTCCT
41 Q G K L R V N A A T N V E S D E R F L D
121 CAAGGGAAGTTACGCGTCAATGCAGCAACAAATGTCGAAAGCGACGAGAGATTTCTAGAC
61 G L K A L V R G F Y D L T P F A P R F Q
181 GGATTAAAAGCTCTTGTCCGTGGTTTCTATGACCTTACGCCTTTCGCACCACGCTTTCAG
81 K D T Y S N L L L K L N L S F E Q F S G
241 AAGGACACATATTCCAACCTTTTATTGAAACTGAATTTGTCTTTCGAACAGTTTTCTGGG
101 K D T L Q L R R F Y D A A R R H N K V N
301 AAGGACACCTTGCAGCTTCGGCGATTTTACGACGCCGCTAGGAGGCATAACAAGGTGAAT
121 P T N P V S V Y T G L V E K Y G E F E I
361 CCAACAAACCCTGTCTCGGTATATACAGGATTGGTAGAAAAGTATGGTGAGTTTGAAATA
141 V N M V Y S L K H A Q S S K S R D V L K
421 GTAAACATGGTGTATTCGCTAAAACATGCACAATCAAGCAAATCCCGTGATGTGCTCAAG
161 R L G K E E K W Y W K D K K D A G K M Y
481 CGACTCGGCAAAGAGGAAAAATGGTATTGGAAGGATAAGAAGGATGCGGGGAAAATGTAC
181 A E A L D L G N E F T V K N M V S K L S
541 GCAGAGGCGCTCGACCTGGGCAACGAGTTTACAGTGAAGAATATGGTTTCGAAATTATCG
201 K L E Q F L N R I D Q K A S E E Q L K A
601 AAGCTAGAACAGTTTTTAAATCGCATCGACCAAAAGGCTAGCGAGGAACAATTGAAAGCT
221 L V V A D I E R V K T K K E S V S P S D
661 TTGGTTGTTGCCGATATTGAGAGGGTGAAAACGAAAAAAGAAAGCGTTTCACCTAGCGAC
241 V E M -
721 GTTGAGATGTGA

133
Chapter 5:
Two GKLR proteins of the lettuce downy
mildew Bremia lactucae induce effectortriggered
immunity
Joost H.M. Stassen 1 , Erik den Boer 2 , Pim W. J. Vergeer 1 ,
Ursula Ellendorff 4 , Koen Pelgrom 2 , Mathieu Pel 3 ,
Johan Schut 4 , Olaf Zonneveld 5 , Marieke J.W. Jeuken 2 ,
and Guido Van den Ackerveken 1,6 .
1
Plant-Microbe Interactions, Department of Biology, Utrecht University,
Utrecht, 3584 CH, The Netherlands
2
Laboratory of Plant Breeding, Wageningen University,
Wageningen, 6700 AJ, The Netherlands
3
Enza zaden, Enkhuizen, 1600 AA, The Netherlands
4
Rijk Zwaan, De Lier, 2678 ZG, The Netherlands
5
Syngenta, Enkhuizen, 1601 BK, The Netherlands
6
Centre for BioSystems Genomics, Wageningen, 6700 AB, The Netherlands

134 Chapter 5
Abstract
Bremia lactucae, the downy mildew pathogen of lettuce (Lactuca sativa), causes
large losses in susceptible crops. Dominant downy mildew (Dm) resistance genes
have been used extensively by breeders to generate Bremia-resistant lettuce
cultivars. However, turnover of Dm genes has been rapid as Bremia is quick to
adapt. Understanding the mechanism of resistance gene-mediated recognition of
downy mildew effectors and resulting effector-triggered immunity (ETI), as well as
how Dm genes are rendered ineffective, is essential for the development of novel
resistance breeding approaches.
We have previously cloned the coding sequence of 34 potential effectors
of Bremia, based on transcriptome sequencing, that are RXLR and RXLR-like
proteins predicted to be translocated into the host cell, where they may induce
ETI. We screened a collection of 129 Lactuca lines, belonging to different species
and harbouring putative novel resistance traits, for specific effector recognition.
Two effectors induced ETI, visible as a hypersensitive response (cell death). The
first, BLG01 triggered a response in 52 lines, predominantly of L. saligna, that are
non-hosts of Bremia. The second, BLG03 was recognised in two L. sativa lines
containing the resistance gene Dm2. BLG01 and BLG03 have similar N-terminal
sequences containing a signal peptide and a GKLR variant of the RXLR translocation
motif, but have different C-terminal effector domains that are polymorphic
between Bremia isolates. BLG03 triggered ETI in lines that were susceptible to the
Bremia isolate from which it was cloned. Nevertheless, BLG03 ETI co-segregated
with resistance to a Dm2–incompatible Bremia isolate, indicating the locus
required for BLG03 ETI maps to the RGC2 cluster of resistance genes. The L.
saligna locus required for BLG01 ETI maps to the bottom of chromosome 9 in offspring
of a L. saligna x L. sativa cross. However, offspring that show BLG01 ETI
were susceptible to Bremia isolates that express BLG01. This suggests that these
virulent Bremia races can suppress the recognition of BLG effectors, possibly by
means of other host-translocated effectors that have not been identified so far. We
are exploring the Lactuca loci underlying the ETI responses for their application in
Bremia-resistance breeding of lettuce.

Bremia GKLR proteins induce ETI
135
Introduction
The lettuce downy mildew pathogen, Bremia lactucae (hereafter: Bremia), causes
large losses in susceptible host plants and has been classified as a pathogen with a
high risk of quick adaptation to lettuce resistance traits and chemical control [1,2] .
Its large effective population size, high gene flow and mixed (both sexual and
asexual) reproductive system contribute greatly to this risk. Bremia belongs to
the peronosporales, an order of the oomycetes that includes downy mildew- and
Phytophthora species. The downy mildews are obligate biotrophs that are found
on many plant species, including Arabidopsis (Hyaloperonospora arabidopsidis),
cucurbits (Pseudoperonospora cubensis), grapevine (Plasmopara viticola), and
sunflower (Plasmopara halstedii). Obligate biotrophs depend on the living host for
their growth and reproduction [3] . For successful infection it is therefore of prime
importance that biotrophs cope with inducible defences of the host, which can be
described as consisting of two overlapping layers of plant immunity [4–6] . The first is
triggered by the recognition of pathogen-derived molecules termed pathogen-associated
molecular patterns (PAMPs) by transmembrane pattern recognition receptors
(PRRs), and is referred to as PAMP-triggered immunity (PTI). Though pathogens
can avoid inducing PTI, e.g. by masking PAMPs, a more common mechanism
is the suppression of PTI within the host cell [5,7] . Pathogens can achieve this by
translocating proteins (effectors) into host intracellular compartments where they
can manipulate cellular processes, e.g. the suppression of plant defence responses,
leading to effector-triggered susceptibility (ETS). Gram-negative bacterial pathogens
deploy a type III secretion system to bring effectors into the host cytoplasm
by means of a pilus-like structure (reviewed by Büttner and He [8] ). Oomycetes get
in close contact with host cells by penetrating the plant-cell wall and invaginating
the plant cell membrane to form haustoria, feeding structures that are thought to
contribute to pathogenicity [3,9,10] . From the haustoria effectors are secreted from the
pathogen before they cross the host membrane [10] . In the case of the peronosporales
two main classes of effectors that enter host cells have been defined: Crinklers and
RXLR proteins (reviewed by Stassen and Van den Ackerveken [11] ). The canonical
RXLR effector contains an N-terminal signal peptide, and a translocation domain
that contains an RXLR amino acid motif and, optionally, a dEER motif. The
part C-terminal of the translocation domain is referred to as the effector domain.
Variation in the presence and exact sequence of motifs in the translocation domain
have been observed, e.g. QXLR motifs in P. cubensis effectors [12] and the presence
of an EER motif but no RXLR motif in H. arabidopsis ATR5 [13] .
A second layer of plant defence is triggered when host cells recognise pathogen
effectors. This effector-triggered immunity (ETI) is mediated by resistance (R)
proteins that can detect effectors or their activity on host targets. Most known

136 Chapter 5
R-proteins belong to the family of cytoplasmic nucleotide binding (NB) and leucine-rich
repeat (LRR) proteins [5,14,15] . Defence triggered by recognition of effectors
by R-proteins is often associated with the hypersensitive response (HR) that is
visible as programmed cell death of host tissue. Effectors that are recognised by
host R-proteins and trigger HR are termed avirulence proteins (AVRs). All AVRs
cloned from oomycete pathogens so far are RXLR and RXLR-like effectors [11,16] ,
with the exception of ATR5 [13] . RXLR effectors are predicted to be present in large
numbers in the genomes of oomycetes belonging to the peronosporales, from 134
in H. arabidopsidis [17] to 563 in P. infestans [18] . RXLR effectors are highly diverse
between species [19] and can also be differentially present within different isolates
of a pathogen species [16,20] . Oomycete pathogens rapidly evolve to overcome R
protein-mediated recognition or ETI by (i) amino acid substitutions in the effector
protein [21,22] , (ii) by down-regulation, loss, or silencing of the effector gene [23] , or
(iii) by suppression of ETI by other effectors [16,24,25] . Resistance is therefore the
outcome of a complex network of interactions between effectors and components
of the host’s defence machinery. Unravelling such a network requires knowledge
about the individual interactions between effectors, R-proteins and host targets.
The interaction between lettuce and Bremia has been extensively studied as a
host-pathogen model for gene-for-gene interactions (reviewed by Michelmore and
Wong, [26] ). More than 40 major downy mildew-resistance (Dm) genes are known,
as well as minor-effect resistance genes that may confer partial or field resistance.
A single Dm gene, Dm3, has been cloned and is part of a large locus of several
megabases known as Resistance Gene Candidate 2 locus (RGC2 locus) [27] that
contains at least 30 other NB-LRR genes [28] .
Cultivated lettuce (Lactuca sativa) can be crossed with some difficulty with
wild lettuce species that include Lactuca species that are considered Bremia
non-hosts (e.g. L. saligna). These wild lettuce species provide a pool of genetic
material from which new Dm genes and resistance QTLs have been identified [29–31] .
Dominant resistance genes have been used extensively by breeders to generate
Bremia-resistant lettuce cultivars. Turnover of Dm genes has, however, been rapid,
as Bremia is quick to adapt to newly introduced resistance genes. To understand
the molecular basis of ETI in the lettuce-Bremia interaction and to identify new
R‐genes for resistance breeding we deployed candidate RXLR and RXLR-like
effectors that were previously identified by transcriptome sequencing (Chapter 3
and 4, [32] ). Here, we describe the screening of a large collection of lettuce breeding
lines for the ability to recognise a selection of 34 Bremia effector candidates. We
discovered two GKLR proteins that are recognised in planta, one of which is
recognised by L. sativa cultivars containing the Dm2 resistance gene.

Bremia GKLR proteins induce ETI
137
Results
Bremia effectors and Lactuca accessions
Of 34 candidate effectors of Bremia isolate Bl:24 we cloned the coding sequence,
starting directly after the signal peptide-encoding sequence, into a T-DNA expression
vector under control of the 35S promoter. A new start codon was inserted
before the cloned sequence to construct a gene that encodes the translocation
domain and effector domain of each predicted effector. In our assay the effectors
are expressed in the host cell cytoplasm, where they are retained as no signal
peptide is encoded in our constructs. Intracellular recognition of effectors by
R-proteins is expected to induce a clearly visible cell death response.
Lactuca accessions were selected representing a large range of Bremia
resistance genes, both dominant Dm genes as well as partial resistance genes, (See
Supplemental Table 1) and other unknown sources of resistance to Bremia. They
were chosen on the basis of the differential sets EU-A and EU-B proposed by the
International Bremia Evaluation Board (IBEB, http://www.worldseed.org/isf/ibeb.
html), a set of resistant accessions proposed by Michelmore et al. [33] , parents of
RIL-populations segregating for Bremia-resistance [34–37] , and other known sources
of Bremia-resistance [31,38,39] . Also one resistant L. aculeata and two resistant L.
altaica accessions [31] were included to widen genetic diversity. To test whether any
of the 34 effectors are recognised in planta, we pressure-infiltrated suspensions
of the Agrobacterium tumefaciens (hereafter: Agrobacterium) strains carrying
the effector constructs into leaves of the selected lettuce lines. Visual responses
to transient expression of effector candidates were scored 5-8 days after Agrobacterium
infiltration. We included strains carrying a YFP-containing vector as a
negative control, and a Necrosis-inducing protein (NIP) gene-containing vector as
a positive control. Expression of YFP is not expected to elicit visible cell death, so
any response seen after infiltration with Agrobacterium carrying the YFP construct
is considered background. The NIP gene encoding PsojNIP that is derived from
Phytophthora sojae induces a cell death response in lettuce that is visible 1-2 days
after infiltration of the Agrobacterium strain and develops into a dark necrotic
lesion after 48 hours. Hence, the PsojNIP response serves as control for successful
T-DNA transfer and transient transgene expression.
Screening of Lactuca accessions reveals recognition of two effectors
Screening of the responses of 129 lettuce lines to each of the 34 effectors was performed.
To identify robust ETI observations were scored and averaged per lettuce/
effector combination. Scoring was based on the presence of no or few visible

138 Chapter 5
Table 1: Details of 34 Bremia effectors and the number of Lactuca lines in which robust ETI (average
score of ≥ 1.3 from ≥ 2 replicates) was observed.
RXLR-like EER-like
ID length start motif start motif Robust ETI
BLR01 86 42 RKLR 52 EQK 0
BLR02 146 85 RLLR 0
BLR03 141 48 RFLR 59 EEER 0
BLR04 76 45 RELR 60 DIK 0
BLR05 97 32 RALR 58 DED 0
BLR06 281 46 RCLR 0
BLR07 253 47 RALR 68 EEER 0
BLR08 135 38 RLLR 0
BLR09 112 37 RRLR 81 EER 0
BLR10 112 37 RRLR 81 EER 0
BLR11 463 46 RRLR 57 DESER 0
BLR12 123 49 RYLR 61 ELEK 0
BLR13 363 44 RRLR 55 EER 0
BLR14 75 46 RKLR 0
BLR15 102 47 RSLR 60 DEER 0
BLR16 98 47 RSLR 60 NDER 0
BLR17 282 50 RRLR 64 DAEK 0
BLR18 92 46 RALR 55 NEDR 0
BLR19 160 45 RLLR 54 DNNEER 0
BLR20 130 53 RLLR 69 DEAD 0
BLR21 65 39 RILR 0
BLR22 185 33 RGLR 0
BLR23 107 57 RSLR 62 DENR 0
BLR24 91 55 RSLR 74 ELEQ 0
BLR25 82 55 RALR 0
BLR26 187 46 RRLR 59 QNDER 0
BLR27 434 40 RQLR 0
BLR28 279 49 RRLR 0
BLR29 311 35 RMLR 46 EES 0
BLR30 101 47 RSLR 60 DEER 0
BLQ01 79 49 QLLR 61 DEEQR 0
BLG01 A 336 44 GKLR 57 DER 23
BLG01 E variant of BLG01 A 41
BLG02 233 44 GRLR 57 DER 0
BLG03 243 42 GKLR 55 DER 2

Bremia GKLR proteins induce ETI
139
symptoms (0), strong yellowing of the leaf (1) or cell death (2). The average scores
of all replicates per lettuce/effector combination are given in Supplemental Table
2. Details of the 34 effectors, as well as the number of lines showing robust ETI,
defined as an average score from at least two replicates ≥ 1.3, are given in Table 1.
Agrobacterium-mediated transient expression was robust in nearly all tested lines,
as can been seen from the cell death response that is induced by PsojNIP expression
(Supplemental Table 2). None of the tested lines showed a strong response to
the YFP-containing Agrobacterium strain.
Effector BLG01 was recognised in many of the tested wild lettuce lines. Of 129
lines, 23 showed a strong reproducible cell death response to BLG01. A variant of
the mature BLG01 protein (without signal peptide), BLG01 E - based on an allele
from Bremia isolates NL519 and F703, was found to induce an even stronger
response than the protein encoded by our reference strain Bl:24 (BLG01 A ). Of the
129 tested lines 41 gave a strong cell death response to BLG01 E (Table 1). Weak,
inconsistent or unverified responses to BLG01 A and BLG01 E were observed for 17
and 11 Lactuca lines, respectively (see Supplemental Figure 1 for a full overview).
The higher number of BLG01 E responsive lines is likely due to a stronger ETI
response that is more easily detected, as almost all lines that showed a weak
response to BLG01 A showed a strong response to BLG01 E . Additionally, 16 lines
respond only to BLG01 E . Most of the BLG01-responsive Lactuca lines in our
collection of Lactuca lines are of the L. saligna species.
A second effector, BLG03, was specifically recognised in two L. sativa lines,
Amplus and UCDM2 (Table 1, Figure 1). In other lines BLG03 did not induce
responses that could be distinguished from the GUS negative control (e.g. Olof,
Figure 4). The set of cultivated lettuce lines (L. sativa) included in the screen contains
differential lines that provide a wide range of genetically known R-genes and
can be used to determine R‐gene specificities. Both Amplus and UCDM2 contain
the Dm2 resistance specificity that is absent in all other L. sativa lines tested. The
Figure 1: ETI triggered by BLG03 in L. sativa cv. Amplus and L. sativa cv. UCDM2. NIP: GUS
and PsojNIP (NIP) serve as controls for responses to Agrobacterium and successful T-DNA transfer,
respectively.

140 Chapter 5
recognition of BLG03 could therefore be mediated by Dm2.
Strikingly, BLG01 and BLG03, which are recognized in specific Lactuca lines,
both contain the RXLR-like motif GKLR. In addition, the signal peptide- and
GKLR-containing N-termini of BLG01 and BLG03 are highly similar (Figure 2).
The N-terminus of a third Bremia protein, BLG02, also shows homology to these
effectors. However, BLG02 is not recognised in any of the lettuce lines tested. The
GKLR and DER motifs are identical in BLG01 and BLG03, whilst BLG02 has a
GRLR variant of the RXLR motif. The effector domains do not share the high level
of similarity that is seen for the signal peptides and G K / R
LR-containing N-termini.
BLG01 MVRVYVAALTGFLALSASASATLQLTSVNESLADAYDSTAPARGKLRAYAATNVESDERA 60
BLG02 MVRIYVAALTVVLAFSASCSATSPLTLAKATPVTANGSGGRAQGRLRAHTTTNVEIDERS 60
BLG03 MVRVYVAALAAIFALSA--SATLHLTLANASSVTTEEGDGRPQGKLRVNAATNVESDER- 57
***:*****: .:*:** *** ** .: : . : . . .:*:**. ::**** ***
BLG01 FSNLLEHLKTLNVLFSPLSKERMEAAISKSDSSVVKHLSEDGAVNEKKLGIGRDGVKAFE 120
BLG02 ISDVIYAIARQVADHRSNLVQAPKRTYTTYLATLDLSLDKVLEQNWSELRLLY--VKQTK 118
BLG03 FLDGLKALVRGFYDLTPFAPRFQKDTYSNLLLKLNLSFEQFSGKDTLQLRRLYDAARRHN 117
: : : : . . : : :. .: :.: : :* .: :
BLG01 PAKVSKVKMILEDIFRKPYNKILLKVLSKANGGERNLVRNLAQAEMLGYKVFFLKSTLAS 180
BLG02 RKRPKDFVSMYELLVKK-------------------------------YGLLKLTDMMKK 147
BLG03 KVNPTNPVSVYTGLVEK-------------------------------YGEFEIVNMVYS 146
. .. : :..* * : : . : .
BLG01 KWERDGVSLMDVWSYICKDVKAPTEEEMKIFSHWCGYAFVLSAKGKFSAEETVIEKTLLK 240
BLG02 PDYISLSET-DNFKYLYDEASVYWR-KNSVLK---QYASELYDSKGNSKTFDVTDFESLQ 202
BLG03 LKHAQSSKSRDVLKRLGKEEKWYWKDKKDAGK---MYAEALDLGNEFTVKNMVSKLSKLE 203
. . * . : .: . . : . . ** * : * . *:
BLG01 VHNDNKNKKGKLAINMLAQIHLSRKFKVDANFFELYDPSPSSLKKLLLELEKSPRACDLD 300
BLG02 PFFERIGRRGD-----YLEITAAEHEKWKT---NKLRPT--------------------- 233
BLG03 QFLNRIDQKASEEQLKALVVADIERVKTKK---ESVSPSDVEM----------------- 243
. :. .::.. : .: * . : *:
BLG01 VELYRLLKQAVTDDKFMKGIWDRSTKKPEQPNAKRN- 336
BLG02 -------------------------------------
BLG03 -------------------------------------
Figure 2: Alignment of the amino acid sequence of candidate effectors BLG01, BLG02 and BLG03.
Signal peptide and translocation domains are indicated above the alignment, the GXLR and DER motifs
are underlined in the alignment. Symbols under the alignment indicate the degree of conservation of the
above residues and indicate identical (*) residues, the presence of conserved substitutions (:) or semiconserved
substitutions (.). Numbers to the right of the alignment indicate the residue number of the last
residue in the column counted from the start of the protein, skipping gaps.
BLG01, BLG02 and BLG03 do not have significant homology to any sequences
in the NCBI non-redundant protein database (e-value < 1e-3), nor are there any
significant matches to Pfam [40] domains. The best BLAST matches in a combined
database of oomycete proteins (H. arabidopsidis, P. infestans, P. ramorum, P.
sojae, Pythium ultimum and Saprolegnia parasitica) were to a putative P. infestans
RXLR effector (PITG_15128, e-value 0.037) for BLG01, a P. sojae RXLR
effector (Ps_133875, e-value 0.81) for BLG03, and a P. ramorum RXLR effector
(Pr_97351, e-value 0.032) for BLG02 (Supplemental Information 2).

Bremia GKLR proteins induce ETI
141
Recognition of the BLG01 and BLG03 effectors is specific to a subset of
lettuce lines, making cell death responses as a result of over-loading the translation
machinery or recognition of the translocation domain unlikely. To verify whether
the translocation domain is indeed dispensable for the recognition we investigated
whether the effector domain of BLG01 is sufficient for recognition in lettuce.
Using the same Agrobacterium-mediated transient transformation system as used
to screen the collection of lettuce lines, we expressed BLG01 60-336 in L. saligna
line CGN05271, which showed a cell death response towards BLG01 with the
translocation domain (Figure 3). Cell death responses in the zones infiltrated with
BLG01 60-336 did not differ from those infiltrated with BLG01 with translocation
domain (BLG01 22-336 ), indicating that the translocation domain is not required for in
planta recognition in CGN05271. The same approach with effector BLG03 (with
translocation domain BLG01 20-243 , without BLG01 58-243 ) in Amplus and UCDM2
revealed that recognition of BLG03 is also independent of the translocation domain
(Shown for UCDM2 in Figure 4).
Figure 3: Recognition of BLG01 without signal
peptide (BLG01 22-336 ) and without signal peptide
and translocation domain (BLG01 60-336 ) in L.
saligna CGN05271. GUS and PsojNIP serve
as controls for responses to Agrobacterium and
successful T-DNA transfer, respectively. Pictures
were taken 8 dpi.
Figure 4: Recognition of BLG03 with (+TD;
BLG03 20-243 ) and without translocation domain
(-TD; BLG03 58-243 ) in L. sativa cv. UCDM2.
Neither is recognised in L. sativa cv. Olof.
GUS (G) and PsojNIP (N) serve as controls
for responses to Agrobacterium and successful
T-DNA transfer, respectively. Pictures were
taken 6 dpi.

142 Chapter 5
BLG gene expression and genetic variation
In order to be recognized in planta these G K / R
LR effectors need to be expressed
during the infection process. Expression in planta was already observed, as the
effector transcripts were identified by transcriptome sequencing of infected lettuce
leaves. To determine the changes in expression during the different stages of infection
we analysed a time-series by quantitative PCR (qPCR) (Figure 5). L. sativa
cv. Olof seedlings were spray-inoculated with spores of Bremia isolate Bl:24 after
which samples were taken every 24 hours starting immediately after spraying.
Within the first 24 hours, the majority of spores germinated and Bremia had penetrated
the epidermis. Substantial Bremia hyphal growth and formation of haustoria
in mesophyll cells occurred over the next four days. Conidiophores formed by six
days post inoculation (dpi), at which time sampling was stopped. Expression levels
were determined as the number of qPCR cycles required for the abundance of each
amplicon to reach threshold level (C T
), and were normalised to L. sativa Actin or
Bremia Actin (resulting in ΔC T
values). The expression of Bremia Actin relative
to L. sativa Actin shows the substantial relative growth of Bremia throughout the
entire time course (Figure 5). Expression of BLG03 increases immediately after
inoculation and appears to be stable from one dpi onwards. BLG01 gene expression
decreases slightly during the course of infection, with expression levels comparable
to those of BLG03 at the later stages of infection. BLG02 shows an increase of
expression at the first day after inoculation similar to that of BLG03. After one dpi
expression levels of BLG02 decline, approaching the level seen immediately after
inoculation. Similar expression patterns were detected in an independent biological
replicate of the time series.
Figure 5: Bremia isolate Bl:24 growth and effector gene expression during infection of L. sativa
cv. Olof. Growth is inferred by the increase of Bremia Actin relative to lettuce Actin throughout the
time course calculated as (ΔC T
). Effector gene expression is determined relative to Bremia Actin. The
difference in C T
required to reach threshold is given: as lower values indicate higher expression, the
Y-axis has been reversed to ease interpretation.

Bremia GKLR proteins induce ETI
143
Allelic diversity of the three G K / R
LR effectors in a selection of Bremia
isolates was investigated to test if the proteins show signs of selection. A set of
eight Bremia isolates was chosen as a group with high diversity based on their
R‐gene-specificities. As Bremia is not haploid isolates can be heterozygous resulting
in mixed peaks when sequencing PCR products. Therefore PCR products were
cloned and from each isolate a minimum of eight clones per gene were sequenced.
Seven different alleles were found for BLG01 and BLG03, and six alleles for
BLG02. The distribution of alleles is represented in Table 2, the protein translations
of the different alleles can be found in Supplemental Information 1. Two striking
observations can be made regarding BLG01. First, as can be seen from the allele
distribution, isolate Bl:5 appears to possess 4 alleles of this effector. Rather than
alleles, these may represent duplicated genes. Secondly, the allele sequences reveal
that no functional BLG01 proteins are encoded in isolates NL519 and F703 due to
a nonsense mutation in the fifth codon (TAC→TAA, Y→stop). The same stop is
found in one of the alleles of Bl:5, whereas two other Bl:5 alleles have premature
stops at other positions. In one of these alleles the stop (CAG→TAG, Q→stop) is
at amino acid position 24, the third residue after the predicted signal peptide cleavage
site (SA|TL), in the other case a two nucleotide deletion in the effector domain
(amino acid position 286) induces a frame shift that reads into a stop after two
amino acids. In contrast to NL519 and F703, a full-length copy of the effector is
present in Bl:5. For most isolates two different alleles of BLG02 and BLG03 were
found. BLG02 A and BLG02 B encode the same protein sequence and only have synonymous
nucleotide variants. All amino acid differences encoded in BLG02 alleles
were found in the effector domain. This is in contrast to BLG03, in which amino
acid polymorphisms are also found in the signal peptide and translocation domain.
Table 2: Distribution of alleles of BLG01, BLG02 and BLG03 over eight Bremia isolates. na: not
amplified.
Race BLG01 BLG02 BLG03
Bl:5 C,D 1 ,F 1 ,G 2 A,E B,G
Bl:16 A,B A,B 3 A
Bl:17 na A,C D,F 2
Bl:24 A A,B 3 A,C
NL519 E 1 B 3 ,C A,D
F703 E 1 C,D na
CA3 C A,F A
CA6 C A A,E
1
Premature stop codon before translocation domain
2
Premature stop codon after translocation domain
3
Encodes same protein sequence as A.

144 Chapter 5
Although one allele has an insertion of two amino acids in the signal peptide, all
BLG03 alleles are predicted to encode a signal peptide. BLG03 F , only present in
Bl:17, has a premature stop codon in the effector domain. Furthermore, BLG03 G ,
found in Bl:5, is more sequence divergent from the Bl:24 reference sequence than
all other BLG03 alleles. None of our effectors are predicted to be under positive
selection to maintain amino acid diversity based on the ratio of synonymous to
non-synonymous substitutions (codon-based test of positive selection averaging
over all sequence pairs; BLG01: Z-score = 0.05790, p = 0.47696; BLG02: Z-score
= 0.15217, p = 0.43965; BLG03: Z-score = -1.31461, p = 1.0). However, the many
different alleles and in particular the nonsense alleles suggest that BLG01 and
BLG03 have been under selective pressure.
The different BLG01 alleles were next used to make constructs of the effector
without signal peptide for in planta expression. Constructs with BGL01 alleles A,
B, C and E (see Supplemental Information 1) were tested in L. saligna CGN5271
to determine their potential to trigger cell death. As shown in Figure 6, the visible
symptoms differ in response to the alleles of the various isolates. Responses to
BLG01 A and BLG01 C appear comparable, whilst the response to BLG01 B appears
to be slightly stronger. Strikingly, BLG01 E triggered the strongest responses when
expressed in L. saligna CGN05271. However, as there is a premature stop in the
signal peptide of BLG01 E this protein will not be produced by the Bremia isolates
F703 and NL519.
Figure 6: Response to transient expression of indicated alleles of BLG01 (see also Table 2 and
Supplemental Figure 2) in four separate leaves of L. saligna CGN05271 at 6 dpi.

Bremia GKLR proteins induce ETI
145
Lactuca loci confer BLG recognition but not Bremia resistance
To genetically map the locus responsible for the response to BLG01, Backcross
Inbred Lines (BILs), which cover 96% of the L. saligna CGN05271 genome in a
L. sativa Olof background [41] , were tested by transient Agrobacterium-mediated
expression of the BLG01 alleles A and E. Unexpectedly, none of the BILs showed a
cell death response to BLG01 (Table 3). As 4% of the L. saligna genome is absent
in the set of 28 BILs the locus could be located in one of the four chromosomal
regions (bottom chr 3, top chr 5, top chr 7, bottom chr 9) that are not represented
in the BILs [41,42] . From the original L. saligna CGN05271 x L. sativa cv. Olof
mapping population [34] viable F3, F4 and BC1S1 families were obtained from
selfed parental lines that were heterozygous or homozygous L. saligna at one of the
four regions that were not represented in the BILs. Several families were found to
segregate for cell death in response to both allele BLG01 A and allele BLG01 E (Table
3). Most F3 plants that were responsive to the stronger BLG01 E allele were also
responsive to the BLG01 A allele. Only six plants responsive to BLG01 E were not
visually scored as responsive to BLG01 A probably because of the weaker response
to BLG01 A . This segregation was also observed in F3 plants from a cross between
the responsive L. saligna parent CGN11341 and the non-responsive L. sativa
parent cv. Norden (Table 3). Comparing the parental genotypes from the families
that showed cell-death, revealed that the response to BLG01 was linked to a region
at the bottom of Chromosome 9 that was always homozygous or heterozygous L.
saligna, indicating that the trait is dominant. This was confirmed in four F1 plants
obtained from a cross between CGN05271 and Olof that were all responsive to the
effector (Table 3). The position of the locus on chromosome 9 was further con-
Table 3: Response to BLG01 transient expression in L. saligna and L. sativa parental lines and progeny.
Numbers between brackets indicate the number of families.
Assay 1 and 2 Assay 3
Lines/Populations
# plants BLG01 E BLG01 A # plants BLG01 E
tested # cell death # cell death tested # cell death remark *
L. sativa cv. Olof 6 0 0 3 0 NRP
L. saligna CGN05271 6 6 6 3 3 RP
Set of 28 BILs 84 0 0
BC1S1 5 2 (1) 1 (1)
F3 48 15 (11) 13 (9) 74 19 (8)
F4 3 3 (1) 2 (1)
F1 4 4
L. sativa cv. Norden 4 0 0 2 0 NRP
L. saligna CGN11341 7 7 7 3 3 RP
F3 14 7 (4) 5 (4) 3 3 (2)
*
NRP: Non-responsive parent, RP: Responsive parent

146 Chapter 5
CLSM5902
cM
98.2
QGC18F20
CLS4696
CLSX3110
CLS4656
CLSX3880
CLS3349
QGF21K05
LE9038
LE0456
LE3016
F3 Plant Cell death
10_2 NO
30_3 YES
130_2 YES
91_3 YES
103.2
104.3
106.0
110.4
112.1
113.2
113.8
114.3
115.1
115.4
Figure 7: Locus of the BLG01 cell-death
response in L. saligna CGN05271 at the bottom
of Chromosome 9. Genotype graphs for four F3
plants with the closest recombination are shown.
Blue is homozygous L. sativa cv. Olof, yellow
is heterozygous, grey represent intervals with a
recombination event, and white means unknown
genotype. Green indicates the smallest region in
which the cell-death response to BLG01 is fine
mapped.
Table 4: Detached leaf assay at adult plant stage, ADTG with B. lactucae Bl:24 on genotyped BC1S2
populations from two BC1S1 plants that showed a cell-death response to BLG01 E .
Plant genotype bottom C9 # plants tested # leaf segments Race Bl:24 ISL
BC1S2 90_2
Hom L. sativa 3 18 84
Heterozygous 6 36 75
BC1S2 90_6
Hom L. sativa 3 18 75
Heterozygous 6 36 92
L. sativa cv. Olof Hom L. sativa 3 27 84
Figure 8: Response to BLG03 in Dm2-
containing lettuce cultivars. GUS and PsojNIP
(NIP) serve as controls for responses to
Agrobacterium and successful T-DNA transfer,
respectively.

Bremia GKLR proteins induce ETI
147
firmed and more precisely positioned using F3 families of which the F2 parent had
a recombination event near the candidate region. The locus could thus be mapped
to a region of 4.4 cM between markers CLSX3110 and CLSX4656 as shown by the
genotype of four informative F3 plants (Figure 7).
The BLG01-triggered response resembles ETI and was therefore expected to be
causally linked to Bremia resistance. As the responsive L. saligna line CGN05271
is a non-host for Bremia, because of multiple quantitative resistance loci [30,43] , we
tested segregating families for linkage of the response to BLG01 and the Bremia
resistance phenotype. Surprisingly, both BC1S2 families obtained from BC1S1
plants 90_2 and 90_6 that were responsive to BLG01 were as susceptible to
isolate Bl:24 as the L. sativa cv. Olof parent (Table 4) indicating that the locus on
chromosome 9 does not confer disease resistance. We conclude that the locus for
responsiveness to BLG01 does not confer resistance to Bremia isolate Bl:24 that
expresses the recognized effector protein.
BLG03 is recognised by lettuce lines Amplus and UCDM2 (Supplemental Table
2 and Figure 1), which carry known resistance loci to Bremia. Amplus contains
two R‐genes, Dm2 and Dm4, whereas UCDM2 contains a single locus, Dm2. These
two lines therefore have the Dm2 locus in common, which is absent from the other
tested lines. This raises the possibility that BLG03 recognition is mediated by the
Dm2-encoded R-protein. We investigated whether resistance to Bremia isolate Bl:5,
to which the lettuce Dm2 confers resistance, co-segregates with the ability to recognise
BLG03 in an F2 population of a UCDM2 x Cobham Green cross, in which the
Dm2 resistance locus segregates. The response to BLG03 was determined by Agrobacterium
infiltration in leaves, and resistance to Bremia Bl:5 was determined in
a leaf disc assay. Of 143 tested F2 plants all but 28 recognised BLG03, indicating
that the ability to recognise BLG03 is a dominant trait. All plants that recognised
BLG03 were resistant to Bl:5. Conversely, all plants that did not recognise BLG03
were susceptible to Bl:5. This indicates that Dm2 or a closely linked gene from
the Dm2 background is required for recognition of BLG03. To investigate this
further we tested BLG03 on additional Dm2-containing lines; Claret (Dm2+3+11),
Maurice (Dm2+16), Miranda (Dm2+7), and Parker (Dm2+11). Expression of
BLG03 triggered a cell death response in both Miranda and Parker, but only a very
weak response in Claret and no response in Maurice (Figure 8).
As Amplus and UCDM2 are susceptible to Bremia isolate Bl:24, from which
we cloned BLG03, we set out to investigate whether any of the other effectors
cloned from Bl:24 could suppress the cell death-response induced by BLG03. We
inoculated a mixture (total OD600 = 0.8) of BLG03 and individual other effector
genes at ratios of 1:2 (UCDM2) or 1:3 (Amplus). These ratios were determined as
the lowest Agrobacterium-BLG03:Agrobacterium-GUS ratio at which a consistent
cell death response could be seen. Using this setup we did not find any reduction of

148 Chapter 5
the cell death responses induced by BLG03 in combination with any of the 33 other
effectors compared to the combination of BLG03 and GUS (not shown). A similar
setup using BLG01 in L. saligna CGN05271 also did not reveal any reduction of
BLG01-induced cell death responses by other effectors (not shown).
Discussion
In planta effector recognition
Two Bremia RXLR-like effectors were found to be specifically recognised in
Lactuca breeding material. A large set of wild lettuce species were capable of
recognising BLG01 and mounting a cell death response. BLG03, in contrast, is
recognised specifically in two cultivated lettuce lines that share the Dm2 resistance
specificity. Our Bremia effector screen of effectors for in planta recognition has
uncovered potential gene-for-gene interactions. The screening of 54 effectors of the
oomycete P. infestans in 10 wild Solanum genotypes by transformation with potato
virus X (PVX) uncovered 36 specific interactions [44] . In contrast, screening of 60
effectors of the downy mildew H. arabidopsidis in 12 A. thaliana accessions using
Pseudomonas syringae pv. DC3000 for delivery did not uncover any hypersensitive
response (cell death) upon effector delivery [25] .
Wild Lactuca species that are Bremia non-hosts can be used to introgress resistance
genes or QTLs into lettuce cultivars. For example, the Dm3 resistance gene
originates from a L. serriola accession, but is very rare in natural populations, with
only a single accession of 1033 tested from 49 natural populations having an intact
Dm3 gene [45] . Dm3 is a fast evolving resistance gene from the RGC2 locus. This
locus encodes two types of resistance gene candidates, a fast evolving type and
a type that evolves at a much slower rate and is more conserved among different
accessions [28] . Recognition of the Bremia effector BLG01 appears to be relatively
common in L. saligna species and to only occur sporadically in other species. The
wide recognition of BLG01 may indicate recognition by a slowly evolving or more
ancient resistance gene. The exact nature of the recognition of BLG01 in L. saligna
and whether this recognition is dependent on the same gene in all lines remains to
be determined.
The recognition of BLG01 in L. saligna CGN05271 was mapped at the bottom
of chromosome 9, where no R‐gene clusters to Bremia in L. serriola and L. sativa
are known so far [37,46] . None of the 23 lettuce EST sequences from the Lettuce
SFP Chip Project (http://chiplett.ucdavis.edu) that are mapped within the 4.4 cM
region between our flanking markers (CLSX3110 & CLS4656) show homology
to NB-LRR-like resistance proteins. We are aware of only three R‐genes from L.
saligna that have been introgressed into L. sativa, none of which are located on

Bremia GKLR proteins induce ETI
149
chromosome 9 [47, 57, 58] . Interestingly, the cell death response to the P. syringae
effector AvrPto did map in the same region on chromosome 9 in a L. sativa x L.
serriola RIL population [48] .
BLG03 is recognised in only two lettuce breeding lines of the initial screen.
These lines share the Dm2 resistance locus, which maps in or near the RGC2
locus [27] . The Dm2 locus provides resistance to Bl:5, and recognition of BLG03
correlated with resistance to Bl:5 in 143 F2 plants of a UCDM2 x Cobham Green
cross, in which Dm2 segregates. This indicates that the response to BLG03 maps
to the RGC2 locus in UCDM2. Of four additional lines that are reported to contain
Dm2, two also showed a response towards BLG03. The two lines that did not show
a response to BLG03, Claret and Maurice, also have other resistance specificities
that map to the RGC2 locus. As we have not yet tested the response to BLG03
from Bl:5, it is too early to conclude that the effector is not recognised by the
Dm2-encoded protein.
Sequencing of BLG03 in eight different isolates revealed 7 different alleles.
Of the sequenced Bremia isolates, Bl:5 and F703 are unable to successfully infect
Dm2-containing hosts. Both Bl:5 BLG03 alleles were not found in other sequenced
Bremia isolates. We were not able to amplify BLG03 from Bremia isolate F703,
although the quality of DNA was not a problem as we could amplify BLG01 and
BLG02. The two Bl:5 BLG03 alleles remain to be cloned and tested in the different
Dm2-containing lines to determine whether responses to these alleles differ from
those to the Bl:24 reference allele.
Effector recognition versus resistance
In most reported cases effector recognition is linked to resistance. Recognition of
BLG01, however, was not linked to resistance to Bl:24 in laboratory assays, and
BLG03 was cloned from a Bremia isolate that can successfully infect the lettuce
lines in which BLG03 is recognised. Examples of a lack of correlation between
recognition of an effector and resistance to pathogen isolates that express the
effector have previously been reported. Screening of 54 P. infestans effectors in
Solanum species by Potato Virus X (PVX) expression uncovered two interactions
that were not correlated to resistance. In an F2 population of a cross between a
resistant and susceptible Solanum species no correlation between the ability to
recognise certain P. infestans effectors and resistance to P. infestans was found,
despite perfect correlation between recognition of other P. infestans effectors and
resistance [44] . Likewise, not all A. thaliana accessions that recognise ATR39-1 or
ATR1Emco5 are resistant to isolates that encode these alleles [49–51] .
An explanation for the lack of resistance in plants that can recognise individual
Bremia effectors is that Bremia uses additional effectors to suppress ETI. A study

150 Chapter 5
that investigated crosses of virulent and avirulent Bremia isolates revealed a
possible locus that inhibits avirulence triggered by Avr5/8, but no evidence for
other inhibitors of avirulence in Bremia [52] . The study highlights that inhibitor
loci exist, but that they are polymorphic. Since this study was performed over 20
years of selective pressure on Bremia has given rise to new isolates that break
various resistances. However, none of our 34 tested effectors were able to suppress
BLG01- or BLG03-induced cell death. We cannot rule out the existence of suppressors
of cell death as our selection of effectors is non-exhaustive and suppressors
may even be non-RXLR effectors, which we did not investigate.
Findings described for the P. infestans effector AvrSmira2 [53] provide an alternative
explanation for an apparent lack of correlation between effector recognition
and resistance. Agrobacterium-mediated transient transformation of potato cultivar
‘Sarpo Mira’ with AvrSmira2 induced a cell death response and indicates the presence
of a resistance factor named Rpi-Smira2. Cell death responses to AvrSmira2
were found to segregate in offspring of a cross between an Rpi-Smira2-containing
parent and a universally susceptible parent. As with our Bremia effector BLG03,
no resistance to P. infestans strains containing AvrSmira2 could be scored in plants
that show a cell death response towards AvrSmira2 in laboratory assays. Field
trials, however, revealed a partial resistance phenotype correlated with the ability
to recognise AvrSmira2. Therefore, field trials in plants containing the L. saligna
locus for recognition of BLG01 are important to determine whether the locus
confers a partial resistance phenotype and if the locus is of value for breeding
Bremia-resistant lettuce.

Bremia GKLR proteins induce ETI
151
Materials and Methods
Cloning, sequencing and qPCR experiments
Effectors were TOPO-cloned as described in Chapter 4. The PsojNIP and YFP
constructs were kindly provided by A. Cabral [54] . Clones were electro-transformed
into Agrobacterium tumefaciens strain C58C1_pGV2260. For sequencing of effector
alleles, DNA was PCR amplified using primers flanking the coding sequence,
blunt-end ligated into pJET1.2 (Fermentas), and transformed into E. coli DH5α
by heat-shock. Plasmid isolation and sequencing was carried out by Macrogen
Inc. Time-course sampling and qPCR analysis were performed as described in
chapter 4. All primers used are listed in Supplementary Table 3.
Agrobacterium-mediated transient transformation assay
Agrobacterium strains were prepared for infiltration as described in chapter 4.
Strains were then pressure infiltrated into leaves using a needleless syringe.
Responses in lettuce lines were scored 8 dpi, unless otherwise indicated.
Codon-based test for positive selection
Insertions and deletions were removed from sequences and sequences with internal
stop codons were removed. Substitution rates were calculated using Nei and
Gojobori’s method [55] , using MEGA4 [56] . Standard error was determined by 500
bootstrap replications. The null hypothesis of no selection (dN = dS) versus the
positive selection hypothesis (dN > dS) were determined using the Z-test: Z = (dNdS)/
√(Var(dS)+Var(dN)).
Materials for mapping the BLG01 response
Two crosses of L. saligna and L. sativa were previously made: Cross 1: L. saligna
CGN05271 x L. sativa cv. Olof and Cross 2: L. saligna CGN11341 x L. sativa cv.
Norden [34] . Materials for Assays 1, 2, and 3 were as follows. Assay 1: three replicates
of 28 BILs derived from Cross 1 that together cover 96% of the L. saligna
CGN5271 genome [41] , and the parental lines of Cross 1 and Cross 2. Assay 2: F3,
F4 and BC1S1 plants derived from Cross 1 and Cross 2. Assay 3: parental lines of
Cross 1 and Cross 2, F1 offspring of Cross 1, and F3 offspring of F2 plants of both
Cross 1 and Cross 2 with a recombination near the C9 locus.

152 Chapter 5
Marker development and genotyping
For fine mapping new markers were developed and selected to saturate the region.
Based on alignment of our F2 map (improved version of Jeuken 2001) with the
L. sativa x L. serriola RIL map by the Lettuce SFP Chip Project (http://chiplett.
ucdavis.edu) and the Compositae Genome Project Database (CGPDB) (http://
compgenomics.ucdavis.edu) we selected candidate EST sequences and markers.
Primers were developed, tested and in case of polymorphism run on the segregating
populations for mapping. Polymorphisms between L. sativa and L. saligna PCR
products of the EST markers were visualized by high-resolution melting curve
differences on a LightScanner System (Idaho Technology). All plants with a cell
death response in transient assay 2 and all the plants from assay 3 were genotyped
using the new markers.
Disease test on adult plants
A detached leaf assay was conducted on adult plants according the protocol of
ADTG as previously described [42] . Two genotyped BC1S2 populations from
BC1S1 plant that showed a cell death response towards BLG01 were tested with
Bremia Bl:24. From each plant at least six leaf squares were collected (2.5 x 2.5
cm). Leaf squares were inoculated with inoculum from Bremia isolate Bl:24 at
37 days post sowing containing 4 x 10 5 spores per ml. At 9 dpi the percentage of
the area of each leaf square that showed Bremia sporulation was determined. One
way Analysis of Variances was used to analyse the data (with as fixed factor: line
(offspring from one parent with genotype at C9 locus) and as block factor: each
different plant). For comparison between the heterozygous and homozygous L.
sativa genotypes from each BC1S1 parent with each other, a Duncan’s multiple
range test (α = 0.05) was performed with GenStat (14 th Edition) software.

Bremia GKLR proteins induce ETI
153
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158 Chapter 5
Supplemental Information
Supplemental Table 1: List of Lactuca lines used for screening Bremia effectors.
The universal name, as well as known synonyms are indicated. The species of Lactuca to which each
line belongs is indicated (Lactuca sp.). The ‘Gene(s)’ column indicates current knowledge of resistance
genes, if any, for each line. The use of the line as a parent for BIL crosses, or as a part of a differential
set is indicated under comments. Additional references (Ref.) are as follows:
A - http://calgreens.org/control/uploads/Michelmore_and_Ochoa_-_Breeding_Crisphead_Lettuce.pdf,
B - http://compgenomics.ucdavis.edu/morphodb/analysis/viewTrait.php,
C - http://www.worldseed.org/isf/ibeb.html,
D - http://documents.plant.wur.nl/cgn/website/downloads/download/Cnr06Trait406.zip,
Universal Name Synonym Lactuca sp. Gene(s) Comment Ref.
CGN15692 aculeata
[31]
CGN04664 altaica
[31]
CGN15711 altaica
[31]
CGN04662 saligna
[33]
CGN05147 saligna
[33]
CGN05157 saligna
[33]
CGN05265 saligna
[33]
CGN05267 saligna
[33]
CGN05271 saligna BIL-parent
[33,34]
CGN05282 saligna
[33]
CGN05301 saligna
[33]
CGN05304 saligna
[33]
CGN05306 saligna
[33]
CGN05308 PIVT1267 saligna
[33]
CGN05309 saligna
[33]
CGN05310 saligna
[33]
CGN05311 saligna
[33]
CGN05313 saligna
[33]
CGN05314 saligna
[33]
CGN05315 saligna
[33]
CGN05317 saligna
[33]
CGN05318 saligna
[33]
CGN05320 saligna
[33]
CGN05321 PIVT1346 saligna
[33]
CGN05322 saligna
[33]
CGN05323 saligna
[33]
CGN05324 saligna
[33]
CGN05325 saligna
[33]
CGN05327 saligna
[33]
CGN05329 saligna
[33]
CGN05330 saligna
[33]
CGN05796 saligna
[33]
CGN05882 saligna
[33]
CGN05895 saligna
[33]
CGN05947 saligna
[33]
CGN09311 saligna
[33]
CGN09313 saligna
[33]

Bremia GKLR proteins induce ETI
159
Universal Name Synonym Lactuca sp. Gene(s) Comment Ref.
CGN09314 saligna
[33]
CGN10888 saligna
[33]
CGN11341 UC83US1 saligna BIL-parent
[34]
CGN13326 PI491206 saligna
[33]
CGN13327 PI491204 saligna
[33]
CGN13330 saligna
[33]
CGN14263 saligna
[33]
HRI11140 saligna
[33]
LJ85314 saligna R33
[33],A
PI491000 saligna
[33],B
PI491207 saligna
[33]
PI491208 saligna
[33]
PI491226 saligna
[33],B
PI503623 saligna
[33]
PI509523 saligna
[33],B
PI509524 saligna
[33],B
UC94ISR1 saligna
[33]
UC94US104 saligna
[33]
AMPLUS sativa Dm2,Dm4 new DM-resistance
ARGELES sativa Dm24/38 EU-A/B differential set
C
BALESTA sativa R EU-B differential set
C
BEDFORD sativa R EU-B differential set
C
BELLISSIMO sativa R EU-B differential set
C
CAPITAN sativa Dm11 EU-A/B differential set
C
CG DM16 sativa Dm16 EU-B differential set
C
COBHAM
no
sativa
GREEN
Dm genes
EU-A differential set
C
COLORADO sativa Dm18 EU-A/B differential set
C
DANDIE sativa Dm3 EU-A/B differential set
C
DESIGN sativa R candidate differential set IBEB C
DISCOVERY
sativa
Dm7,
Dm36/37
EU-A/B differential set
C
GRAND RAPIDS sativa
[36]
GREEN TOWERS
sativa
no
Dm genes
EU-B differential set
C
HILDE sativa Dm12 EU-A/B differential set
C
ICEBERG sativa
[36,35]
KIGALIE sativa R candidate differential set IBEB C
LEDNICKY sativa Dm1 EU-A/B differential set
C
LJ85289
NINJA
sativa
(virosa)
sativa
R35
Dm3,
Dm11,
Dm36/37
R-gene originally from L. virosa [33],A
EU-A/B differential set
NORDEN sativa BIL-parent
[34]
NUN Dm15 sativa Dm15 EU-B differential set
C
NUN DM17 sativa Dm17 EU-B differential set
C
OLOF sativa BIL-parent
[34]
PENNLAKE sativa Dm13 EU-A/B differential set
C
PRIMUS sativa
[38]
R4T57D sativa Dm4 EU-A/B differential set
C
C

160 Chapter 5
Universal Name Synonym Lactuca sp. Gene(s) Comment Ref.
RYZ2164 sativa Dm25 EU-B differential set
C
RYZ910457 sativa R EU-B differential set
C
SABINE sativa Dm6 EU-A/B differential set
C
SALADIN sativa
[35]
UC2202 sativa R33
A
UC2203 sativa R34
A
UC2204 sativa R35
A
UC2205 sativa R28
A
UC2206 sativa R29
A
UCDM 10 sativa Dm10 EU-A/B differential set
C
UCDM 14 sativa Dm14 EU-A/B differential set
C
UCDM 2 sativa Dm2 EU-A/B differential set
C
VALMAINE sativa Dm5/8 EU-A/B differential set
C
CGN05913 serriola
[39]
CGN05916 serriola
[33]
CGN10887 serriola
D
CGN14255 serriola
[33]
CGN14271 serriola
[33]
CGN14278 serriola
[33]
LJ85292 serriola R34
[33],A
LS 102 serriola Dm17/25 EU-A differential set
C
LSE 57/15 serriola Dm7 EU-A differential set
C
LSE/18 serriola Dm16 EU-A differential set
C
PI491108 serriola
[33]
PIVT 1309 serriola Dm15 EU-A/B differential set
C
UC96US23 serriola
[37]
W66331A serriola R29
[33]
W66336A serriola R28
[33]
CGN04683 PIVT280 virosa
[33]
CGN05148 virosa
[33]
CGN05332 virosa
[33]
CGN05333 virosa
[33]
CGN05816 virosa
[31]
CGN05941 virosa
[31]
CGN05978 virosa
[31]
CGN09364 virosa
[31]
CGN09365 PIVT1398 virosa
[39]
CGN13302 virosa
[31]
CGN13339 virosa
[31]
CGN13356 virosa
[31]
CGN13357 virosa
[31]
CGN17436 virosa
[31]
CGN18635 virosa
[31]
CGN19040 virosa
[31]
CGN22690 virosa
[31]
CGN23887 virosa
[31]

Bremia GKLR proteins induce ETI
161
Supplemental Table 2 (next page and page thereafter): Recognition of effectors in lettuce breeding
lines.
The Lactuca species of each line is indicated under ‘Sp.’, acu: aculeata, alt: altaica, sal: saligna, sat:
sativa, ser: serriola, vir: virosa. More details of the Lactuca lines can be found in Supplemental Table 1.
Colours represent three scoring levels, green for a low average score (no effects observed, score ≤0.7),
yellow for an intermediate score (mild/inconsistent effects observed) and red for a high average score
(strong response observed, score ≥1.3). The number of biological replicates for each lettuce/effector
combination is indicated by the intensity of the colour. Lettuce/effector combinations for which no data
is available are indicated in grey.
Supplemental Table 3: Primers and markers used in this study
Gene Type Forward primer Reverse primer
BLG01 Flanking AAACGCGATAAGGTCTCAAAA TGACTTCGGTCCTCATTAAAC
BLG01 Cloning ED CACCATGGCTTTCAGTAATTTACTTGAACATCT TCAATTTCGTTTGGCGTTGGG
BLG01 qPCR GTGCTTGCGATCTCGATGTA GGCTTCTTGGTCGATCTGTC
BLG02 Flanking AATTTCTATTGCGAGCACAGC GTTCGCATGACTCACACCTC
BLG02 qPCR GACGAAGCAAGCGTGTACTG TCGGTTACGTCGAACGTTTT
BLG03 Flanking AAGATGTCGCAACGCAGAG TCCACTTGGCAAAGAGCAC
BLG03 Cloning ED CACCATGTTTCTAGACGGATTAAAAGCTCTTG TCACATCTCAACGTCGCTAGGTG
BLG03 qPCR AAAAGGCTAGCGAGGAACAA CACATCTCAACGTCGCTAGG
Lettuce
Actin2
qPCR CTATCCAGGCTGTGCTTTCC ACCCTTCGTAGATCGGGACT
Bremia
Actin2
qPCR AGGCCGTGCTGTCTCTCTAC GCGCATAGCCTTCGTAGATT
Marker name A Forward primer Reverse primer
CLSM5902 AGGTACGCGAATTTGACCAC CACAACGGAAGAAACCGAAT
QGC18F20 AGGTGACAGATGGGACCAAG GTATTCCGCCCACAGTTGAT
CLS4696 AATCTCCAGCTTCGGGTTTT ACTACGAAACGACCCATTGC
CLSX3110 CCACGGCTAGGGTCAGATTA TGAAGACATGGGAGACGACA
CLS4656 CCGTATGCCGTTCATCTTCT GCACTCCAATTGAATGATCG
CLSX3880 TTGCGAGATCCGTATCAGTG CTCCCACAGTTCCGCTAATC
CLS3349 CTTTTTGGAAGGCAATCTGG TCCAGGGAAAACCATCTTTG
QGF21K05 CAAAATGTTGCAGCGTCTGT GGGGGAGGGTCATAACAGTAA
LE9038 GATGGAGCGTCCGATCAGTGTCTG GGATCACCATCATAGTCAGCTTGT
LE0456 TTTGCTTGCTTGTTGGTTCA TCTGTGAAATCACCCTTGCC
LE3016 ACCACCGCTTTCTCACAGTT TGGCCATTCGACCTTTACTC
A
Markers that start their name with LE were derived from the Compositae Genome Project Database
(CGPDB)(http://compgenomics.ucdavis.edu). The original EST contigs from which those markers
were designed were QGD7H11.yd.ab1 for LE9038, QGG19L12.yg.ab1 for LE0456, and QG_CA_
Contig2163 for LE3016. Markers that start with C or Q were designed based on EST contigs in the
Lettuce SFP Chip Project (http://chiplett.ucdavis.edu).

162 Chapter 5

Bremia GKLR proteins induce ETI
163

164 Chapter 5
BLG01 E
Strong
10 0
23
BLG01 A
Strong
11
1
BLG01 A
Weak
4
1
6
BLG01 E
Weak
Supplemental Figure 1: Overlap in responses of Lactuca lines to BLG01 A and BLG01 E .
Based on data in Supplemental Table 2. Strong responses are those with a score > 1.3 (red colours in
Supplemental Table 2), and weak responses those > 0.7 but ≤ 1.3 (yellow colours in Supplemental
Table 2). For determining the overlap in responses to the effector alleles all scores were taken into
account, irrespective of the number of replicates on which the score is based (in contrast to the data in
Table 1, which only includes positive scores based on at least two replicates). Weak scores are more
likely to be the result of falsely scoring of infiltration damage as a response towards the effector, e.g.
all four lines that were scored as showing a weak response only to BLG01 A each have an average
score of 1 based on two replicates of which one was scored as 2 (strong interaction), but the other as 0
(no interaction).
Supplemental Information 2: Alignment of protein translations of different alleles of BLG01, BLG02
and BLG03.
BLG01
A MVRVYVAALTGFLALSASASATLQLTSVNESLADAYDSTAPARGKLRAYAATNVESDERA
B ...--.......................................................
C ............................................................
D .......................*....................................
E ....*.......................................................
F ....*...............................A.......................
G ............................................................
A FSNLLEHLKTLNVLFSPLSKERMEAAISKSDSSVVKHLSEDGAVNEKKLGIGRDGVKAFE
B ............................................................
C ............................................................
D ............................................................
E ........................................................E...
F ............................................................
G ............................................................
A PAKVSKVKMILEDIFRKPYNKILLKVLSKANGGERNLVRNLAQAEMLGYKVFFLKSTLAS
B .............................................I..F...........
C ............................................................
D ................................................F...........
E ............................................................
F ................................................F...........
G ................................................F...........

Bremia GKLR proteins induce ETI
165
A KWERDGVSLMDVWSYICKDVKAPTEEEMKIFSHWCGYAFVLSAKGKFSAEETVIEKTLLK
B ....................N.......................................
C ....................N.........................L.............
D ....................N.......................................
E ....................N.......................................
F ....................N.......................................
G ....................N.......................................
A VHNDNKNKKGKLAINMLAQIHLSRKFKVDANFFELYDPSPSSLKKLLLELEKSPRACDLD
B .........D..............................................Y...
C ............................................................
D ........................................................Y...
E .........D..............................F.T.............Y...
F ........................................................Y...
G .............................................IA*------------
A VELYRLLKQAVTDDKFMKGIWDRSTKKPEQPNAKRN
B ....................................
C ....................................
D ....................................
E ..........................T-........
F ......................SRPRSLNSPTPNEIX
G ------------------------------------
BLG02
A MVRIYVAALTVVLAFSASCSATSPLTLAKATPVTANGSGGRAQGRLRAHTTTNVEIDERS
B ............................................................
C ............................................................
D ............................................................
E ............................................................
F ............................................................
A ISDVIYAIARQVADHRSNLVQAPKRTYTTYLATLDLSLDKVLEQNWSELRLLYVKQTKRK
B ............................................................
C ............................................................
D ............................................................
E ..........................C.................................
F .L..V............G..........................................
A RPKDFVSMYELLVKKYGLLKLTDMMKKPDYISLSETDNFKYLYDEASVYWRKNSVLKQYA
B ............................................................
C ............................................................
D ............................................................
E ............................................................
F ............................................................
A SELYDSKGNSKTFDVTDFESLQPFFERIGRRGDYLEITAAEHEKWKTNKLRPT
B .....................................................
C .........G.K.........K....C..........................
D .........G.K.........K..............N................
E .....................................................
F .....................................................
BLG03
A MVRVYVAALAAIFALS--ASATLHLTLANASSVTTEEGDGRPQGKLRVNAATNVESDERF
B ................--..........................................
C ................--..........................................
D ................--..........................................
E ..............F.AS..........................................
F ..............F.--............P...A........................S
G ..............F.--............P...A.......H.................
A LDGLKALVRGFYDLTPFAPRFQKDTYSNLLLKLNLSFEQFSGKDTLQLRRFYDAARRHNK
B ............................................................
C ............................................................
D ............................................................
E .................................................Q..........
F ............................*....................Q..........
G ......F..............K....P......D..........................

166 Chapter 5
A VNPTNPVSVYTGLVEKYGEFEIVNMVYSLKHAQSSKSRDVLKRLGKEEKWYWKDKKDAGK
B ..............................D.............................
C ............................................................
D ............................................................
E ............................................................
F ............................................................
G L..RT....D.........................E........................
A MYAEALDLGNEFTVKNMVSKLSKLEQFLNRIDQKASEEQLKALVVADIERVKTKKESVSP
B ............................................................
C .....I......................................................
D ....................................................M.......
E .................I..................................M.......
F ....................................................M.......
G R...........................................................
A SDVEM
B .....
C .....
D ...A.
E ...A.
F ...A.
G .....
Supplemental Information 1: Best BLAST hit of BLG01, BLG02, and BLG03 to an oomycete protein.
BLG01
>PITG_15128T0 | PITG_15128 | Phytophthora infestans T30-4 RXLR effector family,
putative (332 aa)
Length = 331
Score = 37.4 bits (85), Expect = 0.037, Method: Compositional matrix adjust
Identities = 31/96 (32%), Positives = 46/96 (47%), Gaps = 12/96 (12%)
Query: 109 LGIGRDGVKAFEPAKVSKVKMILEDIFRK-----PYNKILLKVLSKANGGERNLVRNLAQ 163
L + DG+ K +LED K ++ L+KVL+K GE NLVR L Q
Sbjct: 34 LKLNDDGLNVLRSRKFE----VLEDYVTKLNHGQSVDETLVKVLTKHMDGEDNLVRLLDQ 89
Query: 164 AEMLGY---KVFFLKSTLASKWERDGVSLMDVWSYI 196
A+ K L++ L +KW+ + + M VWS +
Sbjct: 90 AKWSTRSLDKANHLETALLTKWQNEKLLPMSVWSRL 125
BLG02
>Pr_97351T0 | Pr_97351 | Phytophthora ramorum RxLR effector (533 aa)
Length = 532
Score = 37.0 bits (84), Expect = 0.032, Method: Compositional matrix adjust.
Identities = 50/171 (29%), Positives = 74/171 (43%), Gaps = 18/171 (10%)
Query: 1 MVRIYVAALTVVLAFSASCSATSPLTLAKA---TPVTANGSGGRAQGRLRAHTTTNVEID 57
M YV L +++A + + + TSP T+A A T A G G A+GR+ +T D
Sbjct: 1 MRYCYVMMLVLIVALAINAAQTSPATIANARVPTRWVAAGLNG-ARGRVLTSDSTAETTD 59
Query: 58 ERSISDVIYAIARQVADHRSNLVQAPKRTYTTYL---ATLD-----LSL----DKVLEQN 105
E I A A + A V+AP +T +L ++D LSL DK+L+
Sbjct: 60 EERAG--ISASAVEKAKALFTPVKAPTKTLQRWLNNGISVDDIFTHLSLAKAGDKLLDDT 117
Query: 106 WSELRLLYVKQTKRKRPKDFVSMYELLVKKYGLLKLTDMMKKPDYISLSET 156
L YV+ K P S L YG L M++ +S +E+
Sbjct: 118 QFMTWLQYVELFNFKNPAQTKSTITTLTAHYGDKGLFQMLEAAKRVSSTES 168
BLG03
>Ps_133875T0 | Ps_133875 | Phytophthora sojae RxLR effector (225 aa)
Length = 224
Score = 32.3 bits (72), Expect = 0.81, Method: Compositional matrix adjust.
Identities = 15/57 (26%), Positives = 31/57 (54%), Gaps = 2/57 (3%)
Query: 88 LLKLNLSFEQFSGKDTLQLRRLYDAARRHNKVNPTNPVSVYTGLVEKYGEFEIVNMV 144
LL+L+ E+ + L + + + N+ NP N V++ + ++ KYGE ++ M+
Sbjct: 98 LLQLDDGLEKLLSRKNLDTWKTF--VNKLNQQNPENQVTMMSAIINKYGEEQVARMI 152

167
Chapter 6:
Discussion

168 Chapter 6

Discussion
169
Identifying effectors
Microbial pathogens of plants and animals have evolved sophisticated ways to
interfere with host cell processes. To render the host susceptible to infection pathogens
deploy small molecules and proteins, also called effectors, which interfere
with host processes [1,2] . An important process to perturb is detection by the host
through recognition of molecular patterns that are present on the microbe’s surface
or are part of other exposed molecules (microbe-associated molecular patterns,
MAMPs) [3] . Successful pathogens use their effectors to suppress immune responses
that are triggered after recognition or avoid detection altogether [1,2,4] . The initial
interaction occurs mostly outside of host cells and pathogens deploy extracellular
effectors to interfere with MAMP recognition or other extracellular defences,
e.g. inhibition of hydrolytic host enzymes [5,6] . Interestingly, pathogens have also
evolved different ways to get effectors into the host cell. A well-studied mechanism
by which effectors are translocated from pathogens into host cells is the Type Three
Secretion System used by various Gram-negative bacterial pathogens (reviewed by
Büttner and He [7] ). Effectors containing a specific signal are targeted into the host
cell via a pilus-like structure that penetrates the host cell. Once inside, effectors act
on the host cellular machinery to suppress immunity and to establish a successful
infection. Eukaryotic pathogens such as the oomycetes do not appear to use a direct
injection-like mechanism, but rather secrete proteins that are then taken up by the
host.
Oomycetes are a remarkable and diverse group of fungal-like pathogens. Their
hyphal growth and spore production give them the appearance of fungi, though
they belong to the kingdom Stramenopila and are more closely related to brown
algae. Oomycete pathogens affect both animals and plants and include a number
of notorious pathogens of crops, such as Phytophthora infestans, the potato late
blight pathogen that is best known as the cause of the Irish potato famine. Like
other successful pathogens, oomycetes use an arsenal of effectors to establish
infection [8,9] . Bioinformatics analysis showed that oomycetes have evolved many
novel protein domain combinations compared to other species with a similar single
domain repertoire [10] . These novel combinations are enriched in secreted proteins,
suggesting they contribute to a diverse and unique effector repertoire. Analysis of
gene content has been instrumental in identifying the vast repertoire of effectors
and has revealed extensive effector diversity between oomycete species [8,9] .

170 Chapter 6
Genomes and transcriptomes
The genomes of Albugo candida, Pythium ultimum, the Phytophthora species
infestans, ramorum, sojae and capsici, and the downy mildew species Hyaloperonospora
arabidopsidis and Pseudoperonospora cubensis have been sequenced
and annotated [11–17] . Whilst these genome sequences have had great use in the
identification of potential effectors in these species, obtaining and analysing the
genome sequences has been a large combined effort, often involving many collaborators
with an interest in these particular pathogens. At the moment technologies
are still not sufficiently advanced and automated to investigate the genomes of all
possible pathogens in an efficient and rapid way. However, the gene content of
organisms can also be obtained by transcriptomics from which effectors can then
be discovered.
In this thesis the identification and functional analysis of Bremia lactucae
effectors from transcriptome-sequencing data is described. Sequencing the
transcriptome rather than the entire genome of Bremia has several advantages. The
resulting dataset consists of transcripts of genes that are expressed during infection,
whereas a genome-derived set of predicted genes is more likely to also contain
genes that are not expressed during infection or are even not expressed at all
(being pseudogenes). Careful planning of the sampling strategy is, however, more
important when sequencing a transcriptome, as sequencing will yield a snapshot of
the mRNA molecules present at the time of sampling. By inoculating leaf-material
twice, interspaced by three days, both earlier and later stages of pathogen growth
are included in the sample. This allows for a broad sampling of infection-related
transcripts, and enables identification of both effector candidates that are expressed
early (e.g. BLR03 and BLR22, Chapter 4) and those that are expressed late during
infection (e.g. BLR23, Chapter 4). Prediction of protein coding sequences from
transcripts is more straight-forward as introns do not disrupt the reading frames and
the largest open reading frame in each transcript is therefore most likely encoding
the correctly predicted protein. Furthermore, the transcriptome contains fewer
sequence repeats than a genome, which simplifies the assembly process. Another
issue that has less impact on the assembly of transcriptome sequencing data than
it has on the assembly of an entire genome is heterozygosity of the genome,
e.g. that of Bremia. Overall, less sequencing data is required to provide good
coverage of the transcriptome to allow robust assembly of full-length transcripts.
The advantages of sequencing the transcriptome also mean that computational
requirements to store, handle, and analyse data are lower, allowing such a project to
be performed with modest computing hardware.

Discussion
171
Host-translocated effectors
The focus of the research described in this thesis was on RXLR and RXLR-like
effectors. The RXLR motif was found to be common to all cloned avirulence
proteins of oomycetes known in 2005 [18] . Avirulence proteins, or their effects on
host proteins, are recognised by intracellular Resistance proteins belonging to the
NB-LRR class and were therefore suspected to be present in the host cytoplasm.
The fact that these proteins shared the RXLR motif suggested the motif was
involved in translocation of the effector into the host cell. Experiments using
effectors with mutated RXLR motifs indeed revealed the motif to be required for
translocation [19] . Translocation was shown to be independent of pathogen-encoded
machinery as effectors are taken up into host cells in the absence of the pathogen
[20,21]
. The mechanism by which translocation occurs, however, is still under debate.
One study suggests that the RXLR motif binds PIP3 and that effectors are subsequently
translocated in a lipid-raft-dependent manner [22] . This was also shown for
fungal effectors, and allowed entry into plant and human cells [22] . The lipid binding
properties of one of the fungal effectors could, however, not be confirmed in a
second study, which was also able to separate lipid binding properties of another
fungal effector from the sequence required for translocation [23] . Likewise, investigation
of P. infestans effector Avr3a revealed that lipid binding properties could be
separated from translocation, and that lipid binding was required for stabilisation
of Avr3a, but not for translocation [24] . Translocation of RXLR-motif-containing
SpHtp1 of the oomycete fish pathogen Saprolegnia parasitica has been reported
to be dependent on tyrosine-O-sulphate [21] . SpHtp1 did not, however, translocate
into plant and human cells, and in contrast to the secretomes of Peronosporales
there is no enrichment of the RXLR motif in the S. parasitica secretome. The exact
mechanism of RXLR-effector translocation thus remains to be determined.
The RXLR motif was instrumental in the identification of several hundreds of
potential effectors in the genomes of individual Phytophthora species. In downy
mildews the numbers of identified RXLR effectors and other pathogenicity genes
appeared to be lower [14,25] . Though amino acid motifs provide a useful tool to
identify oomycete effectors, the definition of the motifs may be too strict to detect
all related effectors. Recently the host-translocated effector ATR5 of H. arabidopsidis
was identified and found to lack a RXLR motif, though an RXLR-associated
EER domain was present. In Pseudoperonospora cubensis a variant of the RXLR
motif, QXLR is common and enables translocation into the host cell [25] . This
QXLR motif was previously thought to be incapable of enabling translocation, as
the amino acid substitution RXLR → QXLR in the P. sojae RXLR effector Avr1b
abolished the effector’s capability to re-enter soybean root cells in the absence of
a pathogen [22] . Mutated forms of Avr1b were expressed in and then secreted from

172 Chapter 6
soybean root cells after delivery of constructs by particle bombardment. The ability
to re-enter the cells was abolished in some of the tested mutants, but a wide range
of mutations did not appear to impact re-entry and suggested a highly redundant
motif ([RHK]X[LMIFYW]). In addition, mutations in EER-like motifs also had a
negative effect on effector re-entry. The ability of RXLR effectors to translocate
into host cells is therefore more likely to be dependent on the context in which the
motif occurs than the exact motif itself. Such findings warrant the investigation of
potential effectors that do not conform to the canonical RXLR effector with strict
RXLR- and EER motifs. In this regard the presence of the RXLR motif can be
seen as an indication of whether a protein may be a host-translocated effector, but
its absence should not be taken as a sign that the protein is not translocated. In this
thesis GKLR effectors are described that are recognised in specific Lactuca hosts
(Chapter 5). These effectors were identified based on similarity to other oomycete
effectors and were selected for further investigation despite the variant RXLR
motif. Effector candidates without a clear variant of the RXLR motif that do have
an EER motif (Chapter 3) were also identified, but these are yet to be investigated.
Other classes of non-RXLR host-translocated oomycete effector have been
identified, e.g. the Crinklers, which are thought to have a more ancient origin
based on their occurrence in phylogenetically more distant oomycete species such
as Albugo and Aphanomyces [26] . Downy mildews express relatively few Crinkler
proteins (Chapter 3, [27–29] ). RXLR and Crinkler effector sequences can be mined
from sequence databases by searching for the occurrence of the motifs that characterise
these effectors. Additional classes of effectors can be identified as clusters
of related sequences that are specific for the pathogen species. For example, in
the predicted secretome of the white rust Albugo laibachii an additional group
of 31 effectors that share a CHXC motif was identified [30] . The N-terminus of
one such effector, CHXC9, was shown to be as efficient as the N-terminus of a
Crinkler effector in translocating the AVR3a effector domain from Phytophthora
capsici into N. benthamiana cells, indicating that these CHXC proteins are genuine
host-translocated effectors. Searching the Bremia secretome for clusters of related
sequences identified additional RXLR-like effector candidates. It did not, however,
uncover novel types of effectors such as the Albugo CHXC effectors.
Targets and effector variation
A next challenge for effector research is the identification of the targets of effectors.
The network of interactions between H. arabidopsidis and P. syringae effectors
and Arabidopsis proteins based on a recent high-throughput yeast-two-hybrid study
indicate that different pathogens target a limited number of highly connected cellular
hubs [31] . The shared host targets are often involved in immunity and are highly

Discussion
173
interconnected. Some of the host targets are targeted by more than 20 different
effectors.
If a relatively small set of defence hubs are the main target of effectors, the
question remains why some pathogens encode many hundreds of effectors. A
study on downy mildews effectors in Arabidopsis revealed that many effectors
enhance disease susceptibility, although many with subtle effects and not on all of
the 12 accessions tested [32] . These accession dependent effects reflect the variation
in effectors and host targets. Variation in effectors between different isolates of a
species has been shown to include mutations resulting in amino acid substitutions,
but also loss or gain of entire effectors, differences in copy number and transcriptional
polymorphism [28,33–35] . The complete arsenal of effectors encoded by a single
species is therefore likely to be much larger than the reference sequence of the
species suggests. These different effectors may target subtly different variants of
the host target proteins, or provide functional redundancy and increased flexibility
in adapting to hostile environments.
Using effectors in resistance breeding
Identifying effector candidates by genome or transcriptome sequencing is becoming
increasingly affordable and achievable. The total number of candidate effectors
identified from genome sequences has already surpassed 1000 in Phytophthora
species alone. More pathogen species are being sequenced to learn more about
the basis of their pathogenicity. The ultimate goal is to apply knowledge about the
factors involved in pathogenicity to breed pathogen-resistant crop plants. Effectors
of pathogens can be used as tools to breed for novel resistances against pathogens,
an approach also referred to as effector-assisted breeding. Knowledge of the P.
infestans genome and the effectors encoded therein, has already provided useful
insights for breeding of late blight resistance in potato (reviewed by Vleeshouwers
et al. [36] )
Detecting R‐genes
The most direct way in which effectors can currently aid resistance breeding is by
using them to identify and genetically follow resistance (R) genes. As has been
done in the research described in this thesis and elsewhere [37–39] , effectors can be
used to screen for the presence of R-proteins that mediate their recognition. In
this thesis effectors BLG01 and BLG03 are examples of such effectors. Effector
BLG03 is recognised by either Dm2 or a gene closely linked to Dm2. In a
segregating population the response to BLG03 can be used as a marker for Dm2
without the need for DNA isolation and analysis. Effectors can therefore also act

174 Chapter 6
as useful markers to identify and track resistance genes in breeding lines. Recently,
the genetic basis of resistance of potato cultivar ‘Sarpo Mira’ to P. infestans was
dissected using effectors of P. infestans to screen offspring of a cross between
‘Sarpo Mira’ and a universally susceptible cultivar [40] . Resistance was found to be
based on recognition of at least five effectors. Recognition of one of these effectors,
AvrSmira2, correlated with field resistance, but not with resistance in laboratory
assays. The dissection of the basis of resistance in ‘Sarpo Mira’ would be too
complex using only different isolates of P. infestans and would likely have missed
the field resistance. Using effectors this resistance was uncovered, and a marker for
the presence of the trait, namely the effector itself, is immediately available. Furthermore,
R‐genes that are detected by effector screens can potentially be rapidly
identified, if the genome sequence of the host plant species that carries the R‐gene
is available. A library of NB-LRR resistance genes can be cloned and transiently
co-expressed with the effector. Co-expression sites that show a cell death response
express the R‐gene corresponding to the effector. The cloned R‐gene can then be
used for transgenic approaches, or its sequence can be used in marker-assisted
breeding.
Working with host targets
There is a relatively small number of pathogens whose effector arsenal is being
extensively studied, in the case of the oomycetes these are predominantly Phytophthora
species and H. arabidopsidis. Sequencing of multiple oomycete species has
revealed there is very little conservation of effector sequences between species.
This makes extrapolating knowledge of effector-target interactions uncovered in,
e.g., P. infestans to other pathogens difficult. Effectors identified in one model
system will often be unrecognisable in other related pathogen species. This is
also shown in chapter 3, where very little overlap is found between the predicted
effectors of the three downy mildew species, H. arabidopsidis, Bremia, and P.
cubensis. The strength of using the more extensively studied interaction between
H. arabidopsidis and its host Arabidopsis thaliana as a model pathosystem for the
Bremia-lettuce interaction lies not in the identification of the sequences of effectors,
but more in their utility in identifying host targets. H. arabidopsidis effectors
have been used to identify in planta interactors, which are likely the targets of these
effectors [31] . These interactors are highly interconnected and can be seen as hubs in
the plant immune machinery. Comparison of the non-receptor immune interactors
of pathogen effectors in A. thaliana and Papaya revealed a slow overall rate of
evolution, indicating that, in contrast to effectors of different species, host targets
are likely conserved between species. Indeed, H. arabidopsidis effector HaRxL96
was found to be able to suppress immunity in soybean, whilst a homologous P.

Discussion
175
sojae effector was found to suppress immunity in Arabidopsis, suggesting the
effectors are effective against conserved targets in divergent hosts, despite limited
homology between both effectors (26% identity, 43% similarity) [41] . When the
genome sequence of the host plant is available (expected in 2012/2013 for lettuce)
effector-target interactions can be investigated starting from the conserved host
targets and effector arsenal of the pathogen. Effectors modulate host targets to
enhance susceptibility or suppress defence. Changes in the host target may break
down the interaction between effector and target, leading to insensitivity to the
effector. Further understanding of the modifications of host targets by effectors
will allow for functional screening for effector-insensitive host-targets in breeding
material. Effector-insensitive host targets may provide a novel source of resistance
that can be used in addition to dominant R‐genes.
Gene-for-gene interactions and resistance
Pathogen species are often capable of rapidly adapting to new resistance traits
introduced by breeders. Given sufficient knowledge of the effector arsenal of
a pathogen species, screening of the effectors of resistance-breaking isolates
will allow for better understanding of the mechanisms that underlie this rapid
adaptation. In this thesis it is shown that plants from a Dm2 background are able
to recognise an allele of Bremia effector BLG03 of an isolate to which these plants
are not resistant. This suggests that host defence does not fail because of changes
to the effector that abolish recognition by Dm2 or a gene in proximity, but by other
changes in the effector complement that either block recognition of the effector
or signalling downstream of recognition. Similarly, introduction of the L. saligna
locus required for recognition of the Bremia effector BLG01 in L. sativa does not
appear to confer resistance. These observations are not unique to Bremia. In the
downy mildew H. arabidopsidis both ATR39-1 and ATR1Emco5 are recognised in
hosts that are susceptible to isolates that carry these effectors [18,39,42] . Observations
also indicate that intermediate resistance to H. arabidopsidis is relatively common
and plays an important role in the H. arabidopsidis - A. thaliana interaction. The
aforementioned field resistance towards AvrSmira2‐containing P. infestans isolates
in potato cultivar ‘Sarpo Mira’ is an illustration that such intermediate resistance
can also be relevant for resistance breeding. Krasileva et al. [42] point out that the
outcome of the interaction between host and pathogen cannot always be explained
by single gene-for-gene interactions, but is rather the result of genome-for-genome
interactions. Screening of resistance-breaking pathogens can assist in pinpointing
the components that allow the breaking of resistance. It also will allow assessment
of the level of allelic diversity of a recognised effector, which can provide an
indication of how durable a corresponding R‐gene will be.

176 Chapter 6
The zigzag model that describes the plant immune system [1,43] provides a model
for the lack of correlation between the outcome of a gene-for-gene interaction
and resistance to an invading pathogen. The model distinguishes different layers
of pathogen offence and plant defence. Hosts are normally resistant to potential
pathogens as they recognise MAMPs. Pathogens then use effectors to induce
susceptibility in hosts, so called effector-triggered susceptibility. Host species, in
return, evolved means of directly or indirectly recognising these effectors, restoring
an effective defence response, termed effector-triggered-immunity. The plant-pathogen
protein-protein-interactome network of Mukhtar et al. [31] indicates that many
interactors of the resistance proteins that recognise effectors are targeted by effectors,
rather than the resistance proteins themselves. In other words, pathogens use
effectors to suppress the defence responses triggered by other effectors to restore
effector-triggered susceptibility. Screening of effectors in soybean has indeed
revealed that many are capable of suppressing effector-induced cell death [34] .
Unravelling this web of interacting proteins is required to make predictions on how
to use the available pool of defence strategies most effectively for each different
crop species.
Future prospects: Breaking the cycle
Bremia is among the plant pathogens with the highest risk of evolving adaptations
to measures introduced to control disease [44] . Factors that contribute to this risk
include the large effective population size and mixed reproductive system. This risk
is not only dependent on the biology of the pathogen, as breeding efforts in lettuce
impose a strong directional selection on Bremia, which contributes to this risk.
Resistant cultivars often contain dominant resistant genes and are grown in large
monocultures in relatively large regions. With sequencing costs decreasing and
knowledge of pathogen effectors increasing, genetic screening of field isolates will
become a useful tool to more accurately type isolates and understand why resistance
breaks. Such screening is also invaluable for a localised rather than global
approach to deployment of resistant cultivars. By combining novel, broad range
resistance genes and alleles that are insensitive to specific effector action, more
durable forms of resistance can potentially be bred. This reduces the directional
selection on Bremia, and together with a more localised approach to resistance
can serve to reduce the evolutionary risk so that resistance is not easily broken or
rendered ineffective.

Discussion
177
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Discussion
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182

183
Summary
Oomycete pathogens cause large losses in many crop plants. Chemical control
measures becoming less effective and are being phased out. Resistance breeding
has traditionally made use of dominant resistance genes to which oomycete pathogens
have often been quick to adapt. Novel approaches towards resistance breeding
are, therefore, required to introduce new and more durable forms of resistance in
crops. A better understanding of host-pathogen interactions at the molecular level
is required to design new breeding approaches. Important molecular players, that
are the main subject of this study, are the effector proteins that downy mildews
use to manipulate their host and cause disease. Sequencing of Expressed Sequence
Tags of Hyaloperonospora arabidopsidis proved a powerful method of identifying
effectors that are active during infection. This revealed isolate-specific effectors
that increase susceptibility of the host. Scaling up this approach using massively
parallel transcriptome sequencing allowed for an extensive overview of genes that
are active during downy mildew infection of lettuce, caused by Bremia lactucae.
Bremia transcript sequences were identified from the mixed set of plant and pathogen
transcripts based on mapping of spore-derived short reads of Bremia genomic
DNA. Effector candidates were then identified based on sequence characteristics
known from effectors of other oomycetes. A set of 34 potential host-translocated
effectors with an RXLR or RXLR-like motif was cloned for further analysis. The
role of these effectors in promoting disease susceptibility on the lettuce host was
investigated, revealing two effectors, BLR16 and BLR27 that show a strong and
robust susceptibility-enhancing effect when transiently expressed. Many other
tested effectors showed a trend towards enhancing susceptibility, though a single
effector, BLR03, consistently reduced susceptibility. BLR16 and BLR27 were found
to be expressed throughout Bremia infection of lettuce, whilst a strong reduction in
the expression of BLR03 was observed already at one day post inoculation. Lettuce
markers of biotic stress-responses were developed based on high abundance and
homology to Arabidopsis biotic stress-induced genes. However, no evidence
was found that susceptibility is enhanced by a general repression of biotic-stress
responses of the host. Finally, 129 lettuce breeding lines were tested for their
response to the set of cloned effectors by Agrobacterium-mediated transient transformation
assays to reveal new resistance specificities. Two effectors containing
a GKLR-variant of the RXLR motif were found to be recognised resulting in the

184
induction of cell death; BLG01 in wild lettuce lines, and BLG03 in cultivated
lettuce lines that contain the known resistance locus Dm2. Recognition of BLG01
is dependent on a region on the short arm of chromosome 9 in L. saligna, and
recognition of BLG03 is linked to the Dm2 resistance locus. Bremia isolates carrying
these effectors were still able to cause disease, suggesting that recognition or
subsequent defence is suppressed by other effectors. The generation of an overview
of the Bremia effector arsenal, identification of susceptibility-enhancing activities
of Bremia effectors, and uncovering of recognition specificities are important steps
forward towards understanding the molecular mechanisms underlying disease
outcome.

185
Samenvatting
Ziekteverwekkers behorende tot de oömyceten veroorzaken grote schade in
vele gewassen. Chemische gewasbeschermingsmethoden zijn in afnemende
mate effectief en worden steeds meer ingeperkt. Bij de veredeling van gewassen
op ziekteresistentie wordt traditionelerwijze gebruik gemaakt van dominante
resistentiegenen. Die worden echter snel door oomyceetpathogenen omzeild.
Nieuwe methoden voor resistentieveredeling zijn dan ook gewenst om nieuwe,
duurzame vormen van resistentie in gewassen te verkrijgen. Een beter begrip
van waard-plantpathogeeninteracties op moleculair niveau is nodig voor nieuwe
strategieën in de resistentieveredeling. Belangrijke moleculaire spelers en het
hoofdonderwerp van dit proefschrift zijn de effectoreiwitten, die valse meeldauwsoorten
gebruiken om hun waardplanten te manipuleren en ziek te maken. Het
bepalen van de nucleotidesequenties van de valse meeldauw Hyaloperonospora
arabidopsidis ‘expressed sequence tags’ bleek een krachtige methode om
effectoreiwitten die actief zijn tijdens het infectieproces te voorspellen. Deze
aanpak onthulde isolaat-specifieke effectoreiwitten die de vatbaarheid van de
waardplant verhoogden. Door schaalvergroting door middel van ‘massively parallel
transcriptome sequencing’ kon een breed overzicht van de genen van de valse
meeldauw Bremia lactucae die actief zijn bij de infectie van sla worden verkregen.
Gebaseerd op vergelijkingen met korte genomische DNA-sequenties afkomstig uit
Bremia-sporen zijn de Bremia-eiwitten voorspeld. Effectorkandidaten zijn vervolgens
geïdentificeerd gebaseerd op de sequentiekenmerken die bekend zijn van
effectoreiwitten van andere oömyceten. Een set van 34 effectorkandidaten met een
RXLR- of RXLR-achtig aminozuurmotief is vervolgens gekloneerd voor verdere
analyse. De rol van deze kandidaten in het bevorderen van de vatbaarheid van sla
is onderzocht, wat onthulde dat twee effectoreiwitten, BLR16 en BLR27, een sterk
robuust vatbaarheidverhogende activiteit in de waardplant hebben. Veel van de
andere kandidaten bleken de vatbaarheid in mindere mate te verhogen, terwijl één
effector, BLR03, stelselmatig de vatbaarheid verlaagde. BLR16 en BLR27 bleken
gedurende de hele infectiecyclus tot expressie te komen, terwijl de expressie van
BLR03 al na één dag sterk verminderd was. Er werden merkers voor biotische
stress in sla ontwikkeld, gebaseerd op hoge relatieve aanwezigheid van transcripten
en gelijkenis met biotische stress-geïnduceerde Arabidopsisgenen. Deze genen
werden echter niet sterk onderdrukt door de geteste Bremia-effectoren, wat er

186
op duidt dat de vatbaarheidverhogende activiteit niet het gevolg is van een brede
onderdrukking van de biotische stress-respons. In een tweede groot experiment
werden 129 slalijnen getest op herkenning van de set gekloneerde effectoreiwitkandidaten
met behulp van Agrobacterium-gemedieerde transiënte expressie, om
nieuwe herkenningsspecificiteiten te onthullen. Twee effectoreiwitten met een
GKLR-variant van het RXLR-aminozuurmotief bleken herkend te worden, met
inductie van celdood tot gevolg. BLG01 en BLG03 werden herkend, in een aantal
wilde slalijnen, respectievelijk gecultiveerde slalijnen die de gekarakteriseerde
resistentielocus Dm2 bevatten. Een locus op de korte arm van chromosoom 9 van
L. saligna bleek verantwoordelijk voor herkenning van BLG01, terwijl herkenning
van BLG03 gekoppeld bleek te zijn aan de Dm2-locus. Bremia-isolaten die deze
effectoreiwitten gebruiken, bleken echter in staat ziekte te veroorzaken. Dit duidt
erop dat de herkenning van de effectoreiwitten of de daaropvolgende inductie
van de afweer mogelijk wordt onderdrukt door andere effectoreiwitten van deze
isolaten. Het in kaart brengen van het arsenaal van Bremia-effectoreiwitten, het
identificeren van hun vatbaarheidverhogende activiteiten en het onthullen van
nieuwe herkenningsspecificiteiten zijn belangrijke stappen in het begrijpen van de
moleculaire mechanismen die bepalend zijn voor de infectie van sla door Bremia.

187
Acknowledgements
I would like to use this place to thank everyone who contributed professionally to
my doctoral studies. Most importantly, I would like to thank the following people
who were especially closely involved:
First of all, thank you to all those involved in the project at the seed companies
and Wageningen University for the stimulating discussions during the project meetings
and the contribution of the lettuce lines and Bremia isolates used throughout
the project. I’m especially grateful for the screening of the effectors in the lettuce
lines. Coming from a molecular background it was interesting for me to get an
insight into the world of plant breeding. I wish you the best of luck in your efforts
to breed pest- and disease-resistant, easy to grow, nice-looking, tasty lettuce with a
long shelf life and all other required traits.
Guido van den Ackerveken and Marieke Jeuken, thanks for setting up this interesting
project with all those involved. I hope the proposal for additional Bremia
research will be funded. Guido, thanks for your supervision, first during my final
internship and later on as co-promoter. I hope your near-limitless optimism will
prove to have had its effect on me. Thanks for the opportunity to dig deeper into
the life of an oomycete, as well as for all the patience you have shown in dealing
with my occasional scepticism.
I am also grateful for the supervision by the rest of the Plant-Microbe Interactions
group: my promoter Corné Pieterse (for telling me to be more worried), ‘role
model’ Saskia van Wees (for telling me to be less worried) and Peter Bakker (for
the nuance).
Thanks Miek Andel, for the supervision during my internship, the clones for the
project and for being a paranymph. Pim Vergeer, my other paranymph and lettuce
trainer, I thank you for growing all the lettuce, taming the Agrobacterium strains,
and not getting too fed up with spore counting. Thank you Michael Seidl for all the
discussions and the use of your bioinformatics expertise. Hans van Pelt, thanks for
the excellent photographic support.
Since this is also my goodbye from PMI, I would like to thank all PMI-people
past and present for making my time at PMI all the more fun and interesting.
Keep up the good work,
Joost

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189
Curriculum vitae
Johannes (Joost) H.M. Stassen was born on 1 November, 1984 in Woerden, The
Netherlands. He finished his secondary education at Minkema College, Woerden
in 2002 and continued his education at University College Utrecht. In 2005 he
obtained his BSc degree and registered for the Master’s programme Biomolecular
Sciences. As part of this programme he performed a research project entitled
‘A Search for the Role of BAIAP3’ in the group of Dr Peter van der Sluis at the
Department of Cell Biology at the University Medical Centre, Utrecht. He worked
on a second research project, ‘Genetic Mapping of the Downy Mildew Resistance
Loci dmr4 and dmr2 in Arabidopsis thaliana’, in the group of Dr Guido van den
Ackerveken, which was initially part of the Molecular Genetics group at Utrecht
University, but fused with the Phytopathology group to form the Plant-Microbe
Interactions group. In 2007, he received his MSc degree and started work on the
project described in this thesis under supervision of Dr Guido van den Ackerveken
and Professor Corné Pieterse at the Plant-Microbe Interactions group at Utrecht
University.

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