genomewide characterization of host-pathogen interactions by ...

Maren Depke
Material and Methods
Gene Expression Pattern of Bone-Marrow Derived Macrophages after Interferon-gamma Treatment
Labeled cDNA for hybridization was prepared for each sample from 200 ng totalRNA using the
GeneChip Whole Transcript (WT) Sense Target Labeling Assay and hybridized to GeneChip Mouse
Gene 1.0 ST Arrays according to the manufacturer’s instructions (Affymetrix, Santa Clara, CA,
USA). Arrays were washed and stained using the GeneChip Hybridization, Wash, and Stain Kit in a
GeneChip Fluidics Station 450 and scanned with a GeneChip Scanner 3000 (all items from
Affymetrix, Santa Clara, CA, USA).
Resulting array image files (CEL-files) were imported to the Rosetta Resolver System (Rosetta
Biosoftware, Seattle, WA, USA). Signal intensities were extracted using the RMA algorithm and
differentially expressed probe sets were accessed with error-weighted one-way Analysis of
Variance (ANOVA) including Benjamini Hochberg False Discovery Rate (FDR) multiple testing
correction at the analysis levels of Intensity Profiles and sequences in log-transformed space.
Values of p* 0.01 on intensity profile level in Rosetta Resolver software) were not included in
statistical testing.
Each run of the statistical test compared two sample groups that consisted of three biological
replicates each. Four comparisons were included into statistical testing: 1) IFN-γ treated BALB/c
BMM versus medium control BALB/c BMM to access IFN-γ effects in BALB/c BMM, 2) IFN-γ
treated C57BL/6 BMM versus medium control C57BL/6 BMM to retrieve IFN-γ effects in C57BL/6
BMM, 3) medium control C57BL/6 BMM versus medium control BALB/c BMM to obtain strain
differences at the non-activated control level, and 4) IFN-γ treated C57BL/6 BMM versus IFN-γ
treated BALB/c BMM to elicit strain differences at the IFN-γ activated level.
The Rosetta Resolver software allows mapping of 28944 records of sequence level
information (i.e. the Affymetrix probe sets) to genes via the EntrezGene nomenclature resulting
in 20074 records. Additionally, the software calculates expression data for genes from the
original sequence level values. This function also combines intensities of two or more probe sets
for genes that are represented by more than one probe set. The lists of statistically significant
differentially expressed probe sets resulting from ANOVA were translated into lists of
differentially expressed genes by using the EntrezGene level annotation included in the Rosetta
Resolver software. In order to exclude biologically irrelevant small changes in expression level
from the statistically significant lists resulting from ANOVA, expression data on EntrezGene level
was restricted to a minimal absolute fold change of 1.5. Nevertheless, only a minority of
statistically significant genes did not pass this fold change cutoff.
Proteome analysis [performed by Dinh Hoang Dang Khoa]
Proteome analysis was performed by Dinh Hoang Dang Khoa using both gel-based and gelfree
approaches. Briefly, BMM protein extracts in urea/thiourea buffer were separated by Two
Dimensional Fluorescence Difference Gel Electrophoresis (2D-DIGE), and spots on the gels were
identified using MALDI-MS-MS. Tryptic peptides of the protein extracts were analyzed with LTQ-
FT-ICR mass spectrometer after liquid chromatographic (LC) prefractionation. Differential analysis
of label-free MS data was performed using the Rosetta Elucidator software package (Rosetta
Biosoftware, Seattle, WA, USA).
Comparison of transcriptome and gel-free LC-MS/MS proteome results
To compare results from transcriptome and gelfree proteome analysis, it was necessary to
map proteins from LC-MS/MS identification to genes available on the GeneChip Mouse Gene 1.0
ST array (Affymetrix). In order to do so, protein IPI identifiers were translated into EntrezGene IDs
using the PIPE (http://pipe.systemsbiology.net/pipe) and UniProt ID (www.uniprot.org) mapping
tools (Lars Brinkmann). Missing EntrezGene IDs were added manually if possible. The resulting list
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