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A systems genomics approach uncovers molecular associates of RSV severity.

ABSTRACT: Respiratory syncytial virus (RSV) infection results in millions of hospitalizations and thousands of deaths each year. Variations in the adaptive and innate immune response appear to be associated with RSV severity. To investigate the host response to RSV infection in infants, we performed a systems-level study of RSV pathophysiology, incorporating high-throughput measurements of the peripheral innate and adaptive immune systems and the airway epithelium and microbiota. We implemented a novel multi-omic data integration method based on multilayered principal component analysis, penalized regression, and feature weight back-propagation, which enabled us to identify cellular pathways associated with RSV severity. In both airway and immune cells, we found an association between RSV severity and activation of pathways controlling Th17 and acute phase response signaling, as well as inhibition of B cell receptor signaling. Dysregulation of both the humoral and mucosal response to RSV may play a critical role in determining illness severity.

SUBMITTER: McCall MN

PROVIDER: S-EPMC8746750 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Integrative systems immunology uncovers molecular networks of the cell cycle that stratify COVID-19 severity.

Project description:Several perturbations in the number of peripheral blood leukocytes, such as neutrophilia and lymphopenia associated with Coronavirus disease 2019 (COVID-19) severity, point to systemic molecular cell cycle alterations during severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. However, the landscape of cell cycle alterations in COVID-19 remains primarily unexplored. Here, we performed an integrative systems immunology analysis of publicly available proteome and transcriptome data to characterize global changes in the cell cycle signature of COVID-19 patients. We found significantly enriched cell cycle-associated gene co-expression modules and an interconnected network of cell cycle-associated differentially expressed proteins (DEPs) and genes (DEGs) by integrating the molecular data of 1469 individuals (981 SARS-CoV-2 infected patients and 488 controls [either healthy controls or individuals with other respiratory illnesses]). Among these DEPs and DEGs are several cyclins, cell division cycles, cyclin-dependent kinases, and mini-chromosome maintenance proteins. COVID-19 patients partially shared the expression pattern of some cell cycle-associated genes with other respiratory illnesses but exhibited some specific differential features. Notably, the cell cycle signature predominated in the patients' blood leukocytes (B, T, and natural killer cells) and was associated with COVID-19 severity and disease trajectories. These results provide a unique global understanding of distinct alterations in cell cycle-associated molecules in COVID-19 patients, suggesting new putative pathways for therapeutic intervention.

| S-EPMC10107240 | biostudies-literature

A systems genomics approach to uncover the molecular properties of cancer genes.

Project description:Genes involved in cancer are under constant evolutionary pressure, potentially resulting in diverse molecular properties. In this study, we explore 23 omic features from publicly available databases to define the molecular profile of different classes of cancer genes. Cancer genes were grouped according to mutational landscape (germline and somatically mutated genes), role in cancer initiation (cancer driver genes) or cancer survival (survival genes), as well as being implicated by genome-wide association studies (GWAS genes). For each gene, we also computed feature scores based on all omic features, effectively summarizing how closely a gene resembles cancer genes of the respective class. In general, cancer genes are longer, have a lower GC content, have more isoforms with shorter exons, are expressed in more tissues and have more transcription factor binding sites than non-cancer genes. We found that germline genes more closely resemble single tissue GWAS genes while somatic genes are more similar to pleiotropic cancer GWAS genes. As a proof-of-principle, we utilized aggregated feature scores to prioritize genes in breast cancer GWAS loci and found that top ranking genes were enriched in cancer related pathways. In conclusion, we have identified multiple omic features associated with different classes of cancer genes, which can assist prioritization of genes in cancer gene discovery.

| S-EPMC7591476 | biostudies-literature

A Stringent Systems Approach Uncovers Gene-Specific Mechanisms Regulating Inflammation

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

2016-01-18 | E-GEOD-67357 | biostudies-arrayexpress

A Stringent Systems Approach Uncovers Gene-Specific Mechanisms Regulating Inflammation

Project description:This SuperSeries is composed of the SubSeries listed below.

2016-01-18 | GSE67357 | GEO

A Stringent Systems Approach Uncovers Gene-Specific Mechanisms Regulating Inflammation.

Project description:Much has been learned about transcriptional cascades and networks from large-scale systems analyses of high-throughput datasets. However, analysis methods that optimize statistical power through simultaneous evaluation of thousands of ChIP-seq peaks or differentially expressed genes possess substantial limitations in their ability to uncover mechanistic principles of transcriptional control. By examining nascent transcript RNA-seq, ChIP-seq, and binding motif datasets from lipid A-stimulated macrophages with increased attention to the quantitative distribution of signals, we identified unexpected relationships between the in vivo binding properties of inducible transcription factors, motif strength, and transcription. Furthermore, rather than emphasizing common features of large clusters of co-regulated genes, our results highlight the extent to which unique mechanisms regulate individual genes with key biological functions. Our findings demonstrate the mechanistic value of stringent interrogation of well-defined sets of genes as a complement to broader systems analyses of transcriptional cascades and networks.

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A Stringent Systems Approach Uncovers Gene-Specific Mechanisms Regulating Inflammation [ChIP-seq]

Project description:Much has been learned about transcriptional cascades and networks from large-scale systems analyses of high-throughput data sets. However, analysis methods that optimize statistical power through simultaneous evaluation of thousands of ChIP-seq peaks or differentially expressed genes possess substantial limitations in their ability to uncover mechanistic principles of transcriptional control. By examining nascent transcript RNA-seq, ChIP-seq, and binding motif data sets from lipid A-stimulated macrophages with increased attention to the quantitative distribution of signals, we identified unexpected relationships between the in vivo binding properties of inducible transcription factors, motif strength, and transcription. Furthermore, rather than emphasizing common features of large clusters of co-regulated genes, our results highlight the extent to which unique mechanisms regulate individual genes with key biological functions. Our findings demonstrate the mechanistic value of stringent interrogation of well- defined sets of genes as a complement to broader systems analyses of transcriptional cascades and networks. Bone marrow-derived macrophages were stimulated with lipid A for 0, 15, 30, 60, and 120 minutes. Chromatin was immunoprecipitated with antibodies against RelA, SRF, or IRF3.

2016-01-18 | E-GEOD-67343 | biostudies-arrayexpress

A Stringent Systems Approach Uncovers Gene-Specific Mechanisms Regulating Inflammation [ATAC-seq]

Project description:Much has been learned about transcriptional cascades and networks from large-scale systems analyses of high-throughput data sets. However, analysis methods that optimize statistical power through simultaneous evaluation of thousands of ChIP-seq peaks or differentially expressed genes possess substantial limitations in their ability to uncover mechanistic principles of transcriptional control. By examining nascent transcript RNA-seq, ChIP-seq, and binding motif data sets from lipid A-stimulated macrophages with increased attention to the quantitative distribution of signals, we identified unexpected relationships between the in vivo binding properties of inducible transcription factors, motif strength, and transcription. Furthermore, rather than emphasizing common features of large clusters of co-regulated genes, our results highlight the extent to which unique mechanisms regulate individual genes with key biological functions. Our findings demonstrate the mechanistic value of stringent interrogation of well-defined sets of genes as a complement to broader systems analyses of transcriptional cascades and networks. Bone marrow-derived macrophages were stimulated with lipid A for 0 or 120 minutes. Chromatin was treated with Tn5 transposase to measure DNA accessibility

2016-01-18 | E-GEOD-74191 | biostudies-arrayexpress

A Stringent Systems Approach Uncovers Gene-Specific Mechanisms Regulating Inflammation [RNA-Seq]

Project description:Much has been learned about transcriptional cascades and networks from large-scale systems analyses of high-throughput data sets. However, analysis methods that optimize statistical power through simultaneous evaluation of thousands of ChIP-seq peaks or differentially expressed genes possess substantial limitations in their ability to uncover mechanistic principles of transcriptional control. By examining nascent transcript RNA-seq, ChIP-seq, and binding motif data sets from lipid A-stimulated macrophages with increased attention to the quantitative distribution of signals, we identified unexpected relationships between the in vivo binding properties of inducible transcription factors, motif strength, and transcription. Furthermore, rather than emphasizing common features of large clusters of co-regulated genes, our results highlight the extent to which unique mechanisms regulate individual genes with key biological functions. Our findings demonstrate the mechanistic value of stringent interrogation of well- defined sets of genes as a complement to broader systems analyses of transcriptional cascades and networks. Bone marrow-derived macrophages derived from C57Bl/6, Myd88-/-, Trif-/-, Irf3-/-, Ifnar-/-, and RelA-/- mice were stimulated with lipid A; C57Bl/6 macrophages were stimulated with lipid A in the presence of MAPK inhibitors or cycloheximide, or stimulated with PAM3CSK4 for 0, 15, 30, 60, and 120 minutes, or stimulated with lipid A for 0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, and 60 minutes. Two biological replicates were generated for each time point for each treatment type.

2016-01-18 | E-GEOD-67355 | biostudies-arrayexpress

Large molecular systems landscape uncovers T cell trapping in human skin cancer.

Project description:Immune surveillance of tumour cells is an important function of CD8 T lymphocytes, which has failed in cancer for reasons still unknown in many respect but mainly related to cellular processes in the tumour microenvironment. Applying imaging cycler microscopy to analyse the immune contexture in a human skin cancer we could identify and map 7,000 distinct cell surface-associated multi-protein assemblies. The resulting combinatorial geometry-based high-functional resolution led to discovery of a mechanism of T cell trapping in the epidermis, which involves SPIKE, a network of suprabasal keratinocyte projections piercing and interconnecting CD8 T cells. It appears initiated by clusters of infrabasal T and dendritic cells connected via cell projections across a fractured basal lamina to suprabasal keratinocytes and T lymphocytes.

| S-EPMC4725819 | biostudies-other

A Stringent Systems Approach Uncovers Gene-Specific Mechanisms Regulating Inflammation [RNA-Seq]

Project description:Much has been learned about transcriptional cascades and networks from large-scale systems analyses of high-throughput data sets. However, analysis methods that optimize statistical power through simultaneous evaluation of thousands of ChIP-seq peaks or differentially expressed genes possess substantial limitations in their ability to uncover mechanistic principles of transcriptional control. By examining nascent transcript RNA-seq, ChIP-seq, and binding motif data sets from lipid A-stimulated macrophages with increased attention to the quantitative distribution of signals, we identified unexpected relationships between the in vivo binding properties of inducible transcription factors, motif strength, and transcription. Furthermore, rather than emphasizing common features of large clusters of co-regulated genes, our results highlight the extent to which unique mechanisms regulate individual genes with key biological functions. Our findings demonstrate the mechanistic value of stringent interrogation of well- defined sets of genes as a complement to broader systems analyses of transcriptional cascades and networks.

2016-01-18 | GSE67355 | GEO

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