Dataset Information

SC2sepsis: sepsis single-cell whole gene expression database.

ABSTRACT: Sepsis, one of the major challenges in the intensive care unit, is characterized by complex host immune status. Improved understandings of the phenotypic changes of immune cells during sepsis and the driving molecular mechanisms are critical to the elucidation of sepsis pathogenesis. Single-cell RNA sequencing (scRNA-seq), which interprets transcriptome at a single-cell resolution, serves as a useful tool to uncover disease-related gene expression signatures of different cell populations in various diseases. It has also been applied to studies on sepsis immunopathological mechanisms. Due to the fact that most sepsis-related studies utilizing scRNA-seq have very small sample sizes and there is a lack of an scRNA-seq database for sepsis, we developed Sepsis Single-cell Whole Gene Expression Database Website (SC2sepsis) (http://www.rjh-sc2sepsis.com/), integrating scRNA-seq datasets of human peripheral blood mononuclear cells from 45 septic patients and 26 healthy controls, with a total amount of 232 226 cells. SC2sepsis is a comprehensive resource database with two major features: (i) retrieval of 1988 differentially expressed genes between pathological and healthy conditions and (ii) automatic cell-type annotation, which is expected to facilitate researchers to gain more insights into the immune dysregulation of sepsis. http://www.rjh-sc2sepsis.com/.

SUBMITTER: Li Y

PROVIDER: S-EPMC9387141 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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SC2sepsis: sepsis single-cell whole gene expression database.

Li Yinjiaozhi Y Tan Ruoming R Chen Yang Y Liu Zhaojun Z Chen Erzhen E Pan Tingting T Qu Hongping H

Database : the journal of biological databases and curation 20220801

Sepsis, one of the major challenges in the intensive care unit, is characterized by complex host immune status. Improved understandings of the phenotypic changes of immune cells during sepsis and the driving molecular mechanisms are critical to the elucidation of sepsis pathogenesis. Single-cell RNA sequencing (scRNA-seq), which interprets transcriptome at a single-cell resolution, serves as a useful tool to uncover disease-related gene expression signatures of different cell populations in vari ...[more]

PMID: 35980286

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Project description:Sepsis is a life-threatening condition in which an uncontrolled inflammatory host response is triggered. The exact pathogenesis of sepsis remains unclear. The aim of the present study was to identify key genes that may aid in the diagnosis and treatment of sepsis. mRNA expression data from blood samples taken from patients with sepsis and healthy individuals was downloaded from the Gene Expression Omnibus database and differentially expressed genes (DEGs) between the two groups were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein‑protein interaction (PPI) network construction, was performed to investigate the function of the identified DEGs. Furthermore, for validation of these results, the expression levels of several DEGs were analyzed by reverse transcription quantitative‑polymerase chain reaction (RT‑qPCR) in three patients with sepsis and three healthy blood samples to support the results obtained from the bioinformatics analysis. Receiver operating characteristic analyses were also used to analyze the diagnostic ability of the identified DEGs for sepsis. The results demonstrated that a total of 4,402 DEGs, including 1,960 upregulated and 2,442 downregulated genes, were identified between patients with sepsis and healthy individuals. KEGG pathway analysis revealed that 39 DEGs were significantly enriched in toll‑like receptor signaling pathways. The top 20 upregulated and downregulated DEGs were used to construct the PPI network. Hub genes with high degrees, including interleukin 1 receptor‑associated kinase 3 (IRAK3), S100 calcium‑binding protein (S100)A8, angiotensin II receptor‑associated protein (AGTRAP) and S100A9, were demonstrated to be associated sepsis. Furthermore, RT‑qPCR results demonstrated that IRAK3, adrenomedullin (ADM), arachidonate 5‑lipoxygenase (ALOX5), matrix metallopeptidase 9 (MMP9) and S100A8 were significantly upregulated, while ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1) was upregulated but not significantly, in blood samples from patients with sepsis compared with healthy individuals, which was consistent with bioinformatics analysis results. Therefore, AGTRAP, IRAK3, ADM, ALOX5, MMP9, S100A8 and ENTPD1 were identified to have potential diagnostic value in sepsis. In conclusion, dysregulated levels of the AGTRAP, IRAK3, ADM, ALOX5, MMP9, S100A8 and ENTPD1 genes may be involved in sepsis pathophysiology and may be utilized as potential diagnostic biomarkers or therapeutic targets.

Dataset Information

SC2sepsis: sepsis single-cell whole gene expression database.

Publications

SC2sepsis: sepsis single-cell whole gene expression database.

Similar Datasets

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