genomewide characterization of host-pathogen interactions by ...

Maren Depke
Results
Kidney Gene Expression Pattern in an in vivo Infection Model
and inflammation related categories (e. g. Inflammatory / Immunological / Infectious Disease,
Antigen Presentation) and categories showing the impact of infection on the tissue (e. g. Cellular
Compromise, Cell Death) were significantly affected.
More detailed analysis of the tissue reaction is offered by the so-called Canonical Pathway
analysis in IPA. This tool contains predefined pathways and the associated genes, displayed in
order of cellular location and function, which can be overlaid with gene expression data, e. g. fold
change values. A p-value for enrichment of pathway members in the data set of interest
(compared to a reference set, e. g. the whole array) is calculated. Many pathways scored with a
highly significant p-value because of the large input data set. Additionally, a ratio of the
pathway’s genes included in the data set and the total number of genes in the pathway is given.
When data of such a Canonical Pathway analysis were ordered by p-value, “Acute Phase
Response Signaling” with p = 5.00E−21 and a ratio of 53/178 of genes from the data set included
in the pathway was the most significantly influenced reaction. This pathway includes signaling
chains starting with TNF-α, IL-1 and IL-6, their signal transduction molecules and transcription
factors and finally the genes whose transcription is induced or repressed. While the acute phase
response is located in hepatic tissue the pathway has a high overlap with a localized
infection/inflammation reaction and therefore is covered by the kidney infection vs. sham
infection data set to this high extent.
Directly infection related genes are included in the canonical pathways “Role of Pattern
Recognition Receptors in Recognition of Bacteria and Viruses” (p = 1.16E−13; ratio = 27/80,
Table R.2.2) and “Toll-like Receptor Signaling” (p = 7.72E−08; ratio = 16/54, Fig. R.2.7) which
contribute as part of the innate immune system to the first line of defense against pathogens. In
infected kidney tissue, an induction of different Toll-like receptors (Tlr1, Tlr2, Tlr4, Tlr6, Tlr7, Tlr8),
the bacterial or dsRNA receptor NALP3 (Nlrp3), and the beta-glucan receptor Dectin-1 (Clec7a)
was observed, and a tendency of induction in Tlr9 and the dsRNA receptors RIG-1 (Ddx58) and
Ifih1. Functionally associated receptors CD14 and LBP were also induced and, following infection,
even members of the signal transduction cascade showed an increased expression (Syk, Myd88,
Irak3, Map3k1, Irf7, Pik3cd, Pik3cg, Pik3r5, Casp1, Fos, Jun, Nfkb2, and a tendency of increase in
Irak4, Mapk13, Map4k4 and Nfkb1). Contrarily, the MAP-kinase-pathway component Map2k6
was repressed and the signal transducer Ecsit and transcription factor PPARα (Ppara) were
repressed by trend. The signaling ends in the transcription of pro-inflammatory cytokines, e. g.
TNFα, IL-6, and RANTES (Ccl5) whose induction was recorded in infected tissue.
Fig. R.2.7:
Toll-like Receptor Signaling (modified
from IPA, www.ingenuity.com).
Colors indicate direction and magnitude
of differential regulation: red – induction;
green – repression. More intense shade of
color is used for higher absolute fold
change values. A trend of induction is
shown in yellow, a trend of repression in
light blue.
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