Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets

BackgroundSepsis is a dysfunctional host response to infection. The syndrome leads to millions of deaths annually (19.7% of all deaths in 2017) and is the cause of most deaths from severe Covid infections. High throughput sequencing or ‘omics’ experiments in molecular and clinical sepsis research ha...

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Main Authors: Arjun S. Baghela, Jasmine Tam, Travis M. Blimkie, Bhavjinder K. Dhillon, Robert E.W. Hancock
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-05-01
Series:Frontiers in Immunology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2023.1135859/full
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author Arjun S. Baghela
Jasmine Tam
Travis M. Blimkie
Bhavjinder K. Dhillon
Robert E.W. Hancock
author_facet Arjun S. Baghela
Jasmine Tam
Travis M. Blimkie
Bhavjinder K. Dhillon
Robert E.W. Hancock
author_sort Arjun S. Baghela
collection DOAJ
description BackgroundSepsis is a dysfunctional host response to infection. The syndrome leads to millions of deaths annually (19.7% of all deaths in 2017) and is the cause of most deaths from severe Covid infections. High throughput sequencing or ‘omics’ experiments in molecular and clinical sepsis research have been widely utilized to identify new diagnostics and therapies. Transcriptomics, quantifying gene expression, has dominated these studies, due to the efficiency of measuring gene expression in tissues and the technical accuracy of technologies like RNA-Seq.ObjectiveMost of these studies seek to uncover novel mechanistic insights into sepsis pathogenesis and diagnostic gene signatures by identifying genes differentially expressed between two or more relevant conditions. However, little effort has been made, to date, to aggregate this knowledge from such studies. In this study we sought to build a compendium of previously described gene sets that combines knowledge gained from sepsis-associated studies. This would enable the identification of genes most associated with sepsis pathogenesis, and the description of the molecular pathways commonly associated with sepsis.MethodsPubMed was searched for studies using transcriptomics to characterize acute infection/sepsis and severe sepsis (i.e., sepsis combined with organ failure). Several studies were identified that used transcriptomics to identify differentially expressed (DE) genes, predictive/prognostic signatures, and underlying molecular responses and pathways. The molecules included in each gene set were collected, in addition to the relevant study metadata (e.g., patient groups used for comparison, sample collection time point, tissue type, etc.).ResultsAfter performing extensive literature curation of 74 sepsis-related publications involving transcriptomics, 103 unique gene sets (comprising 20,899 unique genes) from thousands of patients were collated together with associated metadata. Frequently described genes included in gene sets as well as the molecular mechanisms they were involved in were identified. These mechanisms included neutrophil degranulation, generation of second messenger molecules, IL-4 and -13 signaling, and IL-10 signaling among many others. The database, which we named SeptiSearch, is made available in a web application created using the Shiny framework in R, (available at https://septisearch.ca).ConclusionsSeptiSearch provides members of the sepsis community the bioinformatic tools needed to leverage and explore the gene sets contained in the database. This will allow the gene sets to be further scrutinized and analyzed for their enrichment in user-submitted gene expression data and used for validation of in-house gene sets/signatures.
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spelling doaj.art-f08ced65fdcb4eb79b0d066964ca14f02023-05-26T04:40:32ZengFrontiers Media S.A.Frontiers in Immunology1664-32242023-05-011410.3389/fimmu.2023.11358591135859Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene setsArjun S. BaghelaJasmine TamTravis M. BlimkieBhavjinder K. DhillonRobert E.W. HancockBackgroundSepsis is a dysfunctional host response to infection. The syndrome leads to millions of deaths annually (19.7% of all deaths in 2017) and is the cause of most deaths from severe Covid infections. High throughput sequencing or ‘omics’ experiments in molecular and clinical sepsis research have been widely utilized to identify new diagnostics and therapies. Transcriptomics, quantifying gene expression, has dominated these studies, due to the efficiency of measuring gene expression in tissues and the technical accuracy of technologies like RNA-Seq.ObjectiveMost of these studies seek to uncover novel mechanistic insights into sepsis pathogenesis and diagnostic gene signatures by identifying genes differentially expressed between two or more relevant conditions. However, little effort has been made, to date, to aggregate this knowledge from such studies. In this study we sought to build a compendium of previously described gene sets that combines knowledge gained from sepsis-associated studies. This would enable the identification of genes most associated with sepsis pathogenesis, and the description of the molecular pathways commonly associated with sepsis.MethodsPubMed was searched for studies using transcriptomics to characterize acute infection/sepsis and severe sepsis (i.e., sepsis combined with organ failure). Several studies were identified that used transcriptomics to identify differentially expressed (DE) genes, predictive/prognostic signatures, and underlying molecular responses and pathways. The molecules included in each gene set were collected, in addition to the relevant study metadata (e.g., patient groups used for comparison, sample collection time point, tissue type, etc.).ResultsAfter performing extensive literature curation of 74 sepsis-related publications involving transcriptomics, 103 unique gene sets (comprising 20,899 unique genes) from thousands of patients were collated together with associated metadata. Frequently described genes included in gene sets as well as the molecular mechanisms they were involved in were identified. These mechanisms included neutrophil degranulation, generation of second messenger molecules, IL-4 and -13 signaling, and IL-10 signaling among many others. The database, which we named SeptiSearch, is made available in a web application created using the Shiny framework in R, (available at https://septisearch.ca).ConclusionsSeptiSearch provides members of the sepsis community the bioinformatic tools needed to leverage and explore the gene sets contained in the database. This will allow the gene sets to be further scrutinized and analyzed for their enrichment in user-submitted gene expression data and used for validation of in-house gene sets/signatures.https://www.frontiersin.org/articles/10.3389/fimmu.2023.1135859/fulldatabasegene set analysistranscriptomicsinflammationsepsis, systems immunology
spellingShingle Arjun S. Baghela
Jasmine Tam
Travis M. Blimkie
Bhavjinder K. Dhillon
Robert E.W. Hancock
Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets
Frontiers in Immunology
database
gene set analysis
transcriptomics
inflammation
sepsis, systems immunology
title Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets
title_full Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets
title_fullStr Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets
title_full_unstemmed Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets
title_short Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets
title_sort facilitating systems level analyses of all cause and covid mediated sepsis through septisearch a manually curated compendium of dysregulated gene sets
topic database
gene set analysis
transcriptomics
inflammation
sepsis, systems immunology
url https://www.frontiersin.org/articles/10.3389/fimmu.2023.1135859/full
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