genomewide characterization of host-pathogen interactions by ...
genomewide characterization of host-pathogen interactions by ...
genomewide characterization of host-pathogen interactions by ...
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Maren Depke<br />
Results<br />
Host Cell Gene Expression Pattern in an in vitro Infection Model<br />
and time point had the highest similarity to each other, and thus, the four treatment/time point<br />
groups defined the three lowest level clusters (Fig. R.4.2, orange dashed line). When further<br />
analyzing the next level <strong>of</strong> clustering the high similarity between the 2.5 h groups, i. e. infected<br />
samples and control samples, was obvious (Fig. R.4.2, red dashed line). In the following cluster<br />
level, the 6.5 h control samples showed higher similarity to both 2.5 h samples groups than to the<br />
6.5 h infected samples. Summing up, the biological replicates exhibited a high reproducibility. The<br />
highest similarity on the level <strong>of</strong> treatment groups was observed between 2.5 h infected and<br />
control samples, and not between the control samples <strong>of</strong> both time points as it might have been<br />
expected. The medium control samples <strong>of</strong> the 6.5 h timepoint were more similar to the 2.5 h<br />
samples (infection and control) than to the 6.5 h infected samples.<br />
medium control<br />
infected; GFP positive<br />
time point 2.5 h<br />
time point 6.5 h<br />
biological replicate 1<br />
biological replicate 2<br />
biological replicate 3<br />
biological replicate 4<br />
Fig. R.4.2: Hierarchical clustering <strong>of</strong> 16 array data sets from S9 infection experiment.<br />
The following clustering algorithms were applied on log-transformed data: Agglomerative clustering with average linkage using<br />
euclidian distance weighted <strong>by</strong> error as similarity measure. Sequences which were not expressed on all 16 arrays (defined <strong>by</strong> p > 0.01<br />
on intensity pr<strong>of</strong>ile level in Rosetta Resolver s<strong>of</strong>tware) and control sequences were excluded from the cluster analysis.<br />
The orange dashed line indicates the three lowest level clusters which led to a segmentation into the the four treatment/time point<br />
groups. The next level <strong>of</strong> clustering grouped the 6.5 h control samples next to 2.5 h control and infected samples (red dashed line).<br />
Comparison <strong>of</strong> treatment groups and assessment <strong>of</strong> differentially regulated genes<br />
For identification <strong>of</strong> differential gene expression, infected samples were compared to their<br />
time-matched controls. Additionally, same treatments were compared between the two time<br />
points for control purposes. In detail, four comparisons <strong>of</strong> sample groups were carried out:<br />
2.5 h infected GFP-positive samples vs. 2.5 h medium control<br />
6.5 h infected GFP-positive samples vs. 6.5 h medium control<br />
6.5 h infected GFP-positive samples vs. 2.5 h infected GFP-positive samples<br />
6.5 h medium control vs. 2.5 h medium control<br />
All comparisons are depicted <strong>by</strong> scatter plots (Fig. R.4.3). A small difference appeared<br />
between the infected and control samples 2.5 h after infection (Fig. R.4.3, panel ), while a<br />
strong reaction <strong>of</strong> infected cells compared to the time-matched control became visible after 6.5 h<br />
(Fig. R.4.3, panel ). Consequently, the infected samples strongly differed between both time<br />
points (Fig. R.4.3, panel ). But also in the control samples a certain change <strong>of</strong> signal intensities<br />
depending on incubation time was recorded. This change mainly consisted <strong>of</strong> lower signal values<br />
after 6.5 h than after 2.5 h (Fig. R.4.3, panel).<br />
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