Hypergraph models of biological networks to identify genes critical to pathogenic viral response

Feng, Song; Heath, Emily; Jefferson, Brett; Joslyn, Cliff; Kvinge, Henry; Mitchell, Hugh D.; Praggastis, Brenda; Eisfeld, Amie J.; Sims, Amy C.; Thackray, Larissa B.; Fan, Shufang; Walters, Kevin B.; Halfmann, Peter; Westhoff-Smith, Danielle; Tan, Qing; Menachery, Vineet D.; Sheahan, Timothy P.; Cockrell, Adam S.; Kocher, Jacob; Stratton, Kelly G.; Heller, Natalie C.; Bramer, Lisa; Diamond, Michael S.; Baric, Ralph S.; Waters, Katrina M.; Kawaoka, Yoshihiro; McDermott, Jason; Purvine, Emilie

doi:10.1186/s12859-021-04197-2

Cited by 62 publications

(53 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…S-Betweenness centrality, an indicator of the strength by which nodes are connected by a given edge ( 33 ) – and inferred as the degree to which inflammation is coordinated – was the greatest at 1h of resuscitation in WT mice. In contrast, S-betweenness centrality was greatest at baseline (Ctrl) in TLR4 -/- mice ( Figure 8C ).…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Inferring Tissue-Specific, TLR4-Dependent Type 17 Immune Interactions in Experimental Trauma/Hemorrhagic Shock and Resuscitation Using Computational Modeling

et al. 2022

View full text Add to dashboard Cite

Trauma/hemorrhagic shock followed by resuscitation (T/HS-R) results in multi-system inflammation and organ dysfunction, in part driven by binding of damage-associated molecular pattern molecules to Toll-like Receptor 4 (TLR4). We carried out experimental T/HS-R (pseudo-fracture plus 2 h of shock followed by 0-22 h of resuscitation) in C57BL/6 (wild type [WT]) and TLR4-null (TLR4-/-) mice, and then defined the dynamics of 20 protein-level inflammatory mediators in the heart, gut, lung, liver, spleen, kidney, and systemic circulation. Cross-correlation and Principal Component Analysis (PCA) on data from the 7 tissues sampled suggested that TLR4-/- samples express multiple inflammatory mediators in a small subset of tissue compartments as compared to the WT samples, in which many inflammatory mediators were localized non-specifically to nearly all compartments. We and others have previously defined a central role for type 17 immune cells in human trauma. Accordingly, correlations between IL-17A and GM-CSF (indicative of pathogenic Th17 cells); between IL-17A and IL-10 (indicative of non-pathogenic Th17 cells); and IL-17A and TNF (indicative of memory/effector T cells) were assessed across all tissues studied. In both WT and TLR4-/- mice, positive correlations were observed between IL-17A and GM-CSF, IL-10, and TNF in the kidney and gut. In contrast, the variable and dynamic presence of both pathogenic and non-pathogenic Th17 cells was inferred in the systemic circulation of TLR4-/- mice over time, suggesting a role for TLR4 in efflux of these cells into peripheral tissues. Hypergraph analysis – used to define dynamic, cross compartment networks – in concert with PCA-suggested that IL-17A was present persistently in all tissues at all sampled time points except for its absence in the plasma at 0.5h in the WT group, supporting the hypothesis that T/HS-R induces efflux of Th17 cells from the circulation and into specific tissues. These analyses suggest a complex, context-specific role for TLR4 and type 17 immunity following T/HS-R.

show abstract

Section: Resultsmentioning

confidence: 99%

“…The resultant hypergraphs depict which inflammatory mediators are located within a given set of tissues at specific time point. Hypergraphs were created using the open-source package HyperNetX ( ) ( 33 ).…”

Section: Methodsmentioning

confidence: 99%

Inferring Tissue-Specific, TLR4-Dependent Type 17 Immune Interactions in Experimental Trauma/Hemorrhagic Shock and Resuscitation Using Computational Modeling

et al. 2022

View full text Add to dashboard Cite

show abstract

“…The size of the node represents how many genes are in the pathway. Edges and gene labels are color coordinated 33 .…”

Section: Methodsmentioning

confidence: 99%

Network preservation analysis reveals dysregulated metabolic pathways in human vascular smooth muscle cell phenotypic switching

Perry

Albarracin

Aherrahrou

et al. 2022

Preprint

View full text Add to dashboard Cite

Vascular smooth muscle cells (VSMCs) are key players involved in atherosclerosis, the underlying cause of coronary artery disease (CAD). They can play either beneficial or detrimental roles in lesion pathogenesis, depending on the nature of their phenotypic changes. An in-depth characterization of their gene regulatory networks can help better understand how their dysfunction may impact disease progression. We conducted a gene expression network preservation analysis in aortic SMCs isolated from 151 multi-ethnic heart transplant donors cultured under quiescent or proliferative conditions. We identified 86 groups of co-expressed genes (modules) across the two conditions and focused on the 18 modules that are least preserved between the phenotypic conditions. Three of these modules were significantly enriched for genes belonging to proliferation, migration, cell adhesion, and cell differentiation pathways, characteristic of phenotypically modulated proliferative VSMCs. The majority of the modules, however, were enriched for metabolic pathways consisting of both nitrogen-related and glycolysis-related processes. Therefore, we explored correlations between nitrogen metabolism related genes and CAD-associated genes and found significant correlations, suggesting the involvement of the nitrogen metabolism pathway in CAD pathogenesis. for six genes in the nitrogen metabolism pathway. We also created gene regulatory networks enriched for genes in glycolysis and predicted key regulatory genes driving glycolysis dysregulation. Our work suggests that dysregulation of VSMC metabolism participates in phenotypic transitioning, which may contribute to disease progression and suggests that AMT and MPI may play an important role in regulating nitrogen and glycolysis related metabolism in SMCs.

show abstract

“…Alsamman et al, compared the transcriptomic data of SARS-CoV-2 to MERS-CoV, SARS-CoV, H1N1 and Ebola virus (EBOV) in order to provide valid targets for potential therapy against SARS-CoV-2 36 . Feng et al, investigated the role of hypergraph models of biological networks that are inferred from transcriptomic data (Ebola Virus, Influenza Virus, MERS-CoV, SARS-CoV and West Nile Virus) for the identification of critical genes in viral infection 37 . There are also other transcriptomic studies in blood samples of patients infected with EBOV 38 , and microarray analyses in children 39 and patients with influenza H1N1/2009 40 .…”

Section: Introductionmentioning

confidence: 99%

Differing coronavirus genres alter shared host signaling pathways upon viral infection

Cruz-Pulido

Ouma

Kenney

2022

Sci Rep

View full text Add to dashboard Cite

Coronaviruses are important viral pathogens across a range of animal species including humans. They have a high potential for cross-species transmission as evidenced by the emergence of COVID-19 and may be the origin of future pandemics. There is therefore an urgent need to study coronaviruses in depth and to identify new therapeutic targets. This study shows that distant coronaviruses such as Alpha-, Beta-, and Deltacoronaviruses can share common host immune associated pathways and genes. Differentially expressed genes (DEGs) in the transcription profile of epithelial cell lines infected with swine acute diarrhea syndrome, severe acute respiratory syndrome coronavirus 2, or porcine deltacoronavirus, showed that DEGs within 10 common immune associated pathways were upregulated upon infection. Twenty Three pathways and 21 DEGs across 10 immune response associated pathways were shared by these viruses. These 21 DEGs can serve as focused targets for therapeutics against newly emerging coronaviruses. We were able to show that even though there is a positive correlation between PDCoV and SARS-CoV-2 infections, these viruses could be using different strategies for efficient replication in their cells from their natural hosts. To the best of our knowledge, this is the first report of comparative host transcriptome analysis across distant coronavirus genres.

show abstract

Hypergraph models of biological networks to identify genes critical to pathogenic viral response

Cited by 62 publications

References 34 publications

Inferring Tissue-Specific, TLR4-Dependent Type 17 Immune Interactions in Experimental Trauma/Hemorrhagic Shock and Resuscitation Using Computational Modeling

Inferring Tissue-Specific, TLR4-Dependent Type 17 Immune Interactions in Experimental Trauma/Hemorrhagic Shock and Resuscitation Using Computational Modeling

Network preservation analysis reveals dysregulated metabolic pathways in human vascular smooth muscle cell phenotypic switching

Differing coronavirus genres alter shared host signaling pathways upon viral infection

Contact Info

Product

Resources

About