SHC1 activation and its transcriptional regulation during infection

SHC1 activation is known to modulate survival, proliferation, and migration by transcriptional regulation, depending on the stimulus (Guo and Giancotti, 2004). Thus, the influence of SHC1 activation on transcription upon C. trachomatis cell entry was further investigated. Because of the expected delay between MEK/ERK activation and its transcriptional response, experiments were performed at 4 h p.i. (Figure 3-19), a time point at which the host cell exhibits a strong transcriptional response, but bacteria are still largely metabolically inactive (EB to RB conversion takes place at 8-10 h p.i.) (Mathews et al., 1999).

Figure 3-19. Workflow scheme of DNA microarray, qRT-PCR, and apoptosis experiments. Experimental time-scale of DNA microarray, qRT-PCR, and apoptosis experiments in this study. Blue bar shows time course of infection up to 10 h p.i.

Arrows indicate treatment of cells (blue) and sample collection (black).

Using human DNA microarrays, genes that were differentially expressed during infection of either control cells (without knockdown) or SHC1 knockdown cells were determined. Data from two biological replicates were combined and only correlated genes were used for further analysis (Figure 3-20, green spots).

Figure 3-20. Correlation analysis of DNA microarrays. Comparison plots showing regulated genes from two independent biological experiments during infection (A) or SHC1 knockdown and infection (B). Correlated genes are highlighted in green, anti-correlated genes in red.

Results and discussion: part I

First, infected and uninfected HeLa cells at 4 h p.i. were compared, revealing 182 differentially regulated genes: 76 genes were down-regulated (Figure 3-21, upper left green circle, and Table 6-2) and 106 genes were up-regulated (Figure 3-21, lower right red circle, and Table 6-2) in response to infection. Second, infected SHC1 knockdown and infected luciferase (control) knockdown HeLa cells were compared, indicating regulation of 449 SHC1-dependent genes: 332 genes were down-regulated (Figure 3-21, upper right green circle, and Table 6-3), whereas 117 genes were up-regulated (Figure 3-21, lower left red circle, and Table 6-3) following SHC1 knockdown in infected cells.

Figure 3-21. SHC1- and infection-dependent genes. Venn diagram showing differentially regulated genes during either infection alone or SHC1 knockdown and infection and genes regulated in both conditions. HeLa cells were infected for 4 h (C. trachomatis L2, MOI 20) before RNA isolation and array hybridization. Gene expression profiles of infected versus uninfected cells (Inf (vs. NI)) were compared to infected SHC1 knockdown versus infected luciferase knockdown cells (SHC1 KD + Inf (vs. Luci KD + Inf)) to determine infection- and SHC1-dependently regulated genes (n = 2, each with dye-reversal).

In total, 21 genes are regulated in a both SHC1- and infection-dependent manner (up-regulated genes are marked in red, down-regulated genes in green).

The observed approximately threefold increase of down-regulated genes as compared with up-regulated genes upon infection of SHC1 knockdown cells indicates a strong activating potential of SHC1 on gene expression during infection (Figure 3-21, lower left red circle and upper right green circle). Interestingly, infection of SHC1 knockdown cells down-regulated approximately fourfold more genes than infection of control (no knockdown) cells alone (Figure 3-21, green circles), most likely due to more genes being SHC1- rather than infection-dependently regulated. A comparison of genes regulated between all conditions identified a total of 21 SHC1- and infection-dependent genes (Figure 3-21, gray overlapping areas, and Table 3-3).

Results and discussion: part I

Table 3-3. and infection-dependently regulated genes. List of 21 genes regulated in an infection- and SHC1-dependent manner. Genes are grouped according to regulation pattern and functional sorting by IPA software. Full gene names and a short functional description including references are additionally provided.

Groupa Gene identifier Gene name Full name Function Reference Regulation array 1b p-value array 1b Regulation array 2c p-value array 2c Apoptosisd Cell growthd MEK/ERK dependentd

1 NM_000459 TEK tyrosine kinase, endothelial

1 NM_153032 FLJ32065 hypothetical protein

2 AF086541 DAPL1 death associated protein-like 1

2 NM_001956 EDN2 endothelin 2 21 AA peptide, activates endothelin receptors, raises

3 NM_002017 FLI1 Friend leukemia virus integ. 1

3 NM_145110 MAP2K3 mitogen-activated protein

3 NM_002999 SDC4 syndecan 4 transmembrane heparan sulfate proteoglycan,

4 NM_001511 CXCL1 chemokine (C-X-C motif) ligand 1

Results and discussion: part I

4 NM_013409 FST follistatin Activin binding protein, proliferation, differentiation and apoptosis

McDowall

et al., 2008 2.32 1.38E-33 1.98 1.04E-09 + + -

4 NM_005114 HS3ST1 heparan sulfate (glucosamine)

4 BC037430 PHLDA1 pleckstrin homology-like

a groups according to Figure 3-21

b array 1 (Inf. vs. NI)

c array 2 (SHC1 KD + Inf. vs. Luci KD + Inf.)

d functional sorting according to IPA

Functional analysis of these 21 differentially regulated genes using the IPA software revealed genes associated with apoptosis and cell growth regulation, with eight genes assigned to each category (Figure 3-22 and Table 3-3).

Figure 3-22. SHC1-dependent regulation of apoptosis and cell growth genes. Venn diagram showing color coded circles from Figure 3-21 with more detailed information on the 21 differentially regulated genes. The genes correlating with both infection and SHC1 signaling were further analyzed using the IPA software. Of these, eight genes are grouped into the functional category “apoptosis” and another eight genes are assigned to the category “cell growth”.

Indeed, these functional gene types were significantly enriched (p < 0.01) in this gene subset in comparison with the extended gene set, i.e., ~10 % of the 610 genes versus ~40 % of the 21 genes were apoptosis related (Figure 3-23).

Results and discussion: part I

Figure 3-23. Gene enrichment analysis. Gene enrichment analysis of the overlapping genes (21) compared with all regulated genes (610). Both functional categories “apoptosis” and “cell growth” are significantly enriched in the 21 overlapping genes (as determined by Fisher’s exact test).

Surprisingly, IPA analysis also indicated that, among these 21 genes, nine genes are associated with MEK/ERK signaling, whereas 12 genes are controlled by other pathways (Figure 3-22, magenta colored genes, Figure 3-24, and Table 3-3).

Figure 3-24. Putative SHC1 signaling. Model showing different pathways of SHC1 signaling in connection with the 21 SHC1-dependently regulated apoptosis and cell growth genes. Genes are grouped into the three categories “MEK/ERK-dependent regulation”, “MEK/ERK-in“MEK/ERK-dependent regulation” and “not assigned”. Among the 21 genes (depicted in green),

Results and discussion: part I

only nine genes were MEK/ERK-dependently regulated, whereas 12 genes are controlled by other pathways. Relationships were analyzed using IPA software (straight line, direct relationship; dashed line, indirect relationship; A, activation; E, expression; LO, localization; MB, group/complex membership; P, phosphorylation/dephosphorylation; PD, protein-DNA binding; PP, protein-protein binding; RB, regulation of binding; T, transcription; TR, translocation). Color coding is as follow:

yellow, potential Tarp interactions; blue, intermediate signaling molecules; red, terminal transcriptional regulators; and green, 21 infection- and SHC1-dependently regulated genes.

The regulation of the majority of the 21 infection- and SHC1-dependent genes was confirmed using qRT-PCR (Figure 3-25 and Table 6-4).

Figure 3-25. qRT-PCR confirmation of SHC1-dependent gene regulation. Bar diagrams showing gene expression of infected versus uninfected cells (black vs. dark blue bars) and infected SHC1 knockdown versus infected luciferase knockdown cells (white vs. light blue bars) (n = 2, error bars indicate SE, * denotes p < 0.05, ** denotes p < 0.01). HeLa cells were infected for 4 h (C. trachomatis L2, MOI 20). 10 genes identified in the array experiments and classified into apoptosis or growth regulation were selected for experimental verification by qRT-PCR. Figure shows comparison of qRT-PCR results with the Venn diagram (bottom); Table 6-4 confirms regulatory tendency of all genes tested.

Thus, the transcriptional data suggest that Tarp-mediated SHC1 activation after C. trachomatis infection is involved in the regulation of apoptosis and cell growth related genes.

Results and discussion: part I

Further analysis of the 21 gene subset revealed four distinct groups (Figure 3-22 and Table 3-3).

Group 1 comprises transcripts less abundant upon infection and more abundant in infected SHC1 knockdown cells (Figure 3-26). Therefore, expression of the genes in group 1 is likely inhibited by SHC1 activation. In contrast, group 3 comprises transcripts more abundant upon infection and less abundant in infected SHC1 knockdown cells (Figure 3-26). Consequently, expression of genes in group 3 is likely enhanced by SHC1 activation.

Figure 3-26. Model of the role of SHC1 during early infection-mediated gene regulation. C. trachomatis activates SHC1 leading to four groups of regulated genes. Expression of group 1 genes is likely inhibited by SHC1 activation, explaining their up-regulation after SHC1 knockdown in infected cells. In contrast, gene expression in group 3 is likely enhanced by SHC1 activation, causing a down-regulation of group 3 genes after SHC1 knockdown in infected cells. Genes of group 2 and 4 show an additional regulation by infection-independent of SHC1, remaining after SHC1 knockdown in infected cells.

Groups 2 and 4 include transcripts either less abundant (group 2) or more abundant (group 4) after both infection and SHC1 knockdown in infected cells (Figure 3-26). This can be explained by infection-dependent regulation of these genes in an SHC1-independent manner, counteracted by an SHC1-dependent regulation. Consequently, knockdown of SHC1 in infected cells leads to an enforced regulation due to the remaining SHC1-independent effects. Thus, the data have identified opposing gene regulatory circuits during Chlamydia infection – being dependent or independent of SHC1.