GO and pathway enrichment studies can detail many key aspects of the host response, but these biological functions and processes must be integrated to create host response models capable of linking the effects of transcription to the molecular and signaling events driving those effects. The differentially regulated host response network presented here represents a novel effort to combine various, independent analyses of DE genes into a coherent protein-protein/protein-cell type interaction architecture. This approach allowed us to link immune cells and their inflammatory activities with cell cycle regulation through the identification of a transcription factor (i.e., MAZ) that acts as an intermediary between these functional correlates of pH1N1 pathogenicity. While many studies have used microarrays to identify global transcriptional changes that characterize the host response to different influenza viruses in different systems, our integrated approach allows for a more specific understanding of the mechanisms of influenza virus-induced pathogenicity.
Prior to developing the differential host response network, we validated our transcriptional data by showing that it was, indeed, indicative of the pathological differences between the two infections (Figures and ). Initial functional enrichment results confirmed that the biological processes observed during the pathology examination (i.e., enhanced inflammation and increased immune cell infiltrates [11
]) were also detectable in the transcriptional differences between CA04- and KUTK4-infected lung tissue. Therefore, it seems very likely that any additional functionality or pathway information derived from these data should have a highly correlative, if not causal, relationship with the enhanced pathology of the CA04 infection.
The enhanced ability of the CA04 virus to replicate in lung tissue does not lead to large differences in the host response on day 3 of the infection. The enhanced IRF7 transcription factor activity in CA04-infected lung is consistent with the increased toll-like receptor/RIG-I signaling one expects when there are increased levels of viral single-stranded RNA present in a sample. Enhanced chemoattraction of NK cells, dendritic cells, neutrophils, and macrophages is consistent with the enhanced inflammatory infiltrates observed on histopathologic examination. Most interesting is the implied difference in regulatory T lymphocyte populations, evident from FOXP3 promoter site enrichment, and the potentially enhanced IL-1β expression as a result of greater up-regulation of CASP1 in the CA04 infection. Regulatory T lymphocytes manage immune system homeostasis, and imbalances in T cell populations are often associated with increased inflammation and immune-mediated cell death [41
]. The implicated regulatory T lymphocyte population change may be a factor in the enhanced inflammation and cell damage observed in CA04-infected lung tissue on day 3 p.i. Additionally, increased CASP1 induction of IL-1β could further promote inflammation in CA04-infected tissue.
In a previous study, lung samples infected with a highly pathogenic and mildly pathogenic pH1N1 virus were compared to KUTK4-infected tissue on day 1 p.i., and similar to the work presented here, enhanced inflammation and immune cell infiltration were identified as correlates of increased pH1N1 pathogenicity [7
]. This study found NFκB mediated transcription as a potential mechanism of enhanced pathogenesis, but the degree to which the observed gene regulation was independent of viral replication is unclear. Furthermore, of the 101 transcripts DE on day 3 of our study, only 11 were also DE in the previous work. While this does represent a significant overlap (Fisher Exact test; P < 0.001), none of the genes identified as DE early in pH1N1-infected lung tissue in both studies are related to the immune response. In all, both studies show that early in the course of the infection, there is no obvious dysregulation of the host response with the potential exception of an imbalance in regulatory T lymphocytes, noted above.
By day 7 p.i., several mechanisms up-regulated in CA04-infected lung tissue can account for the continued enhanced pathology [11
]. Lung tissue infected with CA04 on day 7 p.i. showed sustained activation and accumulation of immune cells despite the absence of replicating virus. In addition to the increased immune cell signaling and the activation of the adaptive immune response (evident by the B cell-specific PAX5 promoter site enrichment and GO enrichment analysis shown in Figure ) we observed increased enrichment for cell cycle arrest. Cell cycle arrest has a complicated relationship with virus replication and the immune response. Arrest during G1 phase promotes greater influenza virus replication [43
], but cell cycle arrest also often occurs in cells prior to apoptosis [44
]. Given that cell cycle arrest was observed late in the infection, this is likely to be a host-controlled event, possibly reflecting severely damaged host cells selecting an apoptotic fate.
The MAZ transcription factor activity (Table ) adds an additional layer of complexity between influenza infection-induced apoptosis, immune cell trafficking, and the observed cell cycle arrest. MAZ increases cyclin-dependent kinase inhibitor 1A (CDKN1A) expression [38
] and is known to regulate MYC transcription [45
] – two molecules with seemingly opposed effects on cell cycle. Increased CDKN1A transcription leads to cell cycle arrest and the production of serum amyloid A (SAA), which in turn leads to increased recruitment of immune cells to inflammatory sites [38
]. Increased MYC transcription is most often associated with increased proliferation but it has also been linked to increased cell cycle arrest in fibroblasts [37
]. Since the cell proliferation enriched subnetwork holds MYC in a highly central position (Figure D), the evidence suggests that the increased MAZ transcription is simultaneously inducing cell cycle arrest via CDKN1A and MYC pathways. Since lymphocytes typically proliferate in organized lymphoid tissue (e.g., in lymph nodes) and our samples were collected from within infected lung lesions, we suggest that regulation of cell cycle gene expression primarily occurs in infected epithelium or pneumocytes. Lastly, the fact that virus could not be isolated on day 7 for CA04 infected-lung tissue suggests that activation of the MAZ pathway may be in response to an overly aggressive immune response rather than virus replication. Further, while MAZ protein levels are directly correlated with chronic inflammation, the anti-inflammatory suppression of CCL2 transcription by CDKN1A [47
] was not observed in our microarray data. Thus, there are multiple interactions involving MAZ which we feel are suitable targets to mitigate inflammation during moderate to highly pathogenic influenza infections. Further study validating the significance of MAZ transcription to local inflammation is warranted.
The differentially regulated network developed here elucidates differences between a low pathogenic and a moderately pathogenic infection, and is likely a suitable model of enhanced pathology in humans, as macaque models of influenza virus infection are considered to be one of the best surrogates of human infection [48
]. Several chemokines and interleukins that are up-regulated in the CA04 infection are also up-regulated in the lungs of macaques infected with HPAI H5N1 virus [12
]; however, promoter enrichment analysis of avian virus-infected lung tissue may be needed to provide greater clarity on the precise mechanisms active during a highly pathogenic infection. Ultimately, we intend to develop a mathematical model that can quickly identify the correlates of pathogenicity from microarray experiments to equate transcriptional regulation to infection severity in humans. The network presented here is the first step toward developing such a model.