HIF1A, IRF1, and STAT1, were expressed to a greater extent in DBA/2 compared to selleck chemical C57BL/6 mice, and YY1 to a lesser extent.
STAT1 is the largest hub representing the transcription factor regulating the most differentially expressed genes and it was previously selected as a target for RT-qPCR confirmation from the top 100 modulated genes (P005091 mouse Figure 2). YY1 is a transcription factor whose “yin-yang” designation reflects its ability to both activate and repress transcription through interactions with histone acetylases and deacetylases, respectively . A novel finding from the protein network analysis was the hub HIF-1α, which is a transcription factor that plays a central role in the cellular and systemic responses to hypoxia. HIF-1α is regulated at the post-translational level, which CAL-101 in vivo results in increases in protein half-life, and also at the transcriptional level
by NF-κB [18, 19]. HIF1A was selected for gene expression confirmation by RT-qPCR, as was interleukin 6 (IL6), since it is a transcriptional target of both HIF-1α and Stat1 [20, 21]. Figure 6 Direct protein interaction network constructed from the genes differentially expressed with a fold change ≥ 2 or ≤ -2 (log 2 fold change ≥ 1 or ≤ -1, respectively) between DBA/2 and C57BL/6 mice at day 14 following C. immitis infection (N = 416). MetaCore was used to identify protein-protein and protein-DNA interactions L-NAME HCl between the protein products of differentially expressed genes and Cytoscape was used to visualize the network. Log2 fold changes were superimposed on this protein network such that red indicates greater expression in DBA/2 versus C57BL/6 mice, and blue
lesser expression, as indicated by the scale bar. Each node represents a gene and the size of a node is indicative of the number of interactions the product of each gene makes at the protein level. The largest nodes are labeled HIF1A, IRF1, STAT1 and YY1, and represent hubs that correspond to transcription factors. Stat1 and Irf1 are both transcription factors that upregulate the expression of ISGs and thus corroborate the presence of ISGs in the top 100 modulated genes (Figure 2), as well as the identification of chemokine related pathways (Figure 4). The well-characterized ISGs selected for RT-qPCR analysis, IRGM1, ISG20 and PSMB9[22, 23], were targets of Stat1 regulation in protein network analysis (Figure 6). In contrast, Ubd (also known as Fat10) and Cxcl9, were not identified as regulatory targets of STAT1 in protein network analysis. However, they were both retained for RT-qPCR analysis since these genes are clearly regulated by IFN-γ as previously demonstrated using promoter/reporter gene constructs in the case of Ubd[24, 25] and gene expression studies in the case of Cxcl9.