Transcriptomic characteristics and impaired immune function of patients with sepsis
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ABSTRACT:
PROVIDER: PRJNA772247 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR16465804_1.fastq.gz | Fastqsanger.gz | |||
| SRR16465804_2.fastq.gz | Fastqsanger.gz | |||
| SRR16465805_1.fastq.gz | Fastqsanger.gz | |||
| SRR16465805_2.fastq.gz | Fastqsanger.gz | |||
| SRR16465806_1.fastq.gz | Fastqsanger.gz |
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Project description:Sepsis is a life-threatening condition caused by a dysregulated host response to infection.Although our understanding in the pathophysiological features of sepsis has increased significantly during the past decades, there is still lack of mechanism of sepis.Neutrophils are important regulators against invading pathogens, and their role during sepsis has been studied extensively. However, whether neutrophils could inhibit the immune response of CD8+T cells and the mechanism is unkown in sepsis.
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Project description:Characteristics of impaired dendritic cell function in patients with hepatitis B virus infection
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Project description:The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has gradually become a global public health crisis. Some patients who have recovered from COVID-19 subsequently tested positive again for SARS-CoV-2 after discharge (retesting-positive, RTP). However, the underlying mechanism is unknown. Here, 10 RTP patients, 6 convalescent patients, and 10 healthy controls were enrolled for analysis of the immunological characteristics of their peripheral blood mononuclear cells (PBMCs). We sought to comprehensively characterize the transcriptional changes in the three groups by transcriptome sequencing. Our findings provide insights into the impaired immune function and pathogenesis of RTP occurrence in COVID-19, which may contribute to the development of immunotherapy for RTP patients.
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Project description:Mitochondrial respiration and gene expression related to mitochondrial function were measured from the peripheral blood of infection and sepsis patients as well as healthy controls
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Project description:Dendritic cells are antigen-presenting cells with a central role in host immune response. This study analyzed gene expression and dendritic cell function in hepatitis B virus (HBV) patients and functions impaired due to HBV, and identified the genes related to these functions. Peripheral blood mononuclear cells from 23 HBV patients and 9 healthy controls were utilized. Mononuclear cells were isolated from side-scatter and forward-scatter gating using fluorescence-activated cell sorting (FACS), the lineage-negative HLA-DR-positive fraction was extracted, and was further divided into CD123-positive plasmacytoid DCs (pDCs) and CD11c-positive myeloid DCs (mDCs). Cell sorting was performed, and the number of DCs was measured and surface markers were analyzed. After cell sorting, CD11c and CD11b expression levels in the pDC and mDC fractions were confirmed using real-time PCR. RNA was extracted from sorted pDCs and subjected to gene expression analysis using Affymetrix Human 133U Plus 2.0 gene chip.
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Project description:Objective: It is unclear whether the host response of gram-positive sepsis differs from gram-negative sepsis at a transcriptome level. Using microarray technology, we compared the gene-expression profiles of gram-positive sepsis and gram-negative sepsis in critically ill patients. Design: A prospective cross-sectional study. Setting: A 20-bed general intensive care unit of a tertiary referral hospital. Patients: Seventy-two patients admitted to the intensive care unit. Interventions: Intravenous blood was collected for leukocyte separation and RNA extraction. Microarray experiements were then performed examing the expression level of 19,232 genes in each sample. Measurements and Main Results: There was no difference in the expression profile between gram-positive and gram-negative sepsis. The finding remained unchanged even when genes with lower expression level were included or after statistical stringency was lowered. There were, however, ninety-four genes differentially expressed between sepsis and control patients. These genes included those involved in immune regulation, inflammation and mitochondrial function. Hierarchical cluster analysis confirmed that the difference in gene expression profile existed between sepsis and control patients, but not between gram-positive and gram-negative patients. Conclusion: Gram-positive and gram-negative sepsis share a common host response at a transcriptome level. These findings support the hypothesis that the septic response is non-specific and is designed to provide a more general response that can be elicited by a wide range of different micro-organisms. Keywords: disease state analysis, gram-positive sepsis, gram-negative sepsis
2007-12-01 | GSE6535 | GEO
Project description:Objective: It is unclear whether the host response of gram-positive sepsis differs from gram-negative sepsis at a transcriptome level. Using microarray technology, we compared the gene-expression profiles of gram-positive sepsis and gram-negative sepsis in critically ill patients. Design: A prospective cross-sectional study. Setting: A 20-bed general intensive care unit of a tertiary referral hospital. Patients: Seventy-two patients admitted to the intensive care unit. Interventions: Intravenous blood was collected for leukocyte separation and RNA extraction. Microarray experiements were then performed examing the expression level of 19,232 genes in each sample. Measurements and Main Results: There was no difference in the expression profile between gram-positive and gram-negative sepsis. The finding remained unchanged even when genes with lower expression level were included or after statistical stringency was lowered. There were, however, ninety-four genes differentially expressed between sepsis and control patients. These genes included those involved in immune regulation, inflammation and mitochondrial function. Hierarchical cluster analysis confirmed that the difference in gene expression profile existed between sepsis and control patients, but not between gram-positive and gram-negative patients. Conclusion: Gram-positive and gram-negative sepsis share a common host response at a transcriptome level. These findings support the hypothesis that the septic response is non-specific and is designed to provide a more general response that can be elicited by a wide range of different micro-organisms. The study included seventy-two critically ill patients admitted to the intensive care unit (ICU) of Nepean Hospital, Sydney, Australia. Of these, fifty-five patients were diagnosed to have sepsis, as confirmed by microbiological culture. The remaining seventeen patients did not have sepsis and were therefore used as controls. The study was approved by the hospital ethics committee and informed consent was obtained from all patients or their relatives. Patient Samples. Whole blood was taken from each patient on admission to ICU. Neutrophils were separated from whole blood using density-gradient separation with Ficoll-PaqueP P(Amersham). Subsequent neutrophil RNA extraction was performed using guanidinium thiocyanate (Ambion). Microarray Experiment. The neutrophil RNA was converted to cDNA, fluorescently labeled and hybridized to its complimentary sequences on the microarray (Invitrogen). The fluorescent signals on each micrroarray were captured using the GenePix 4000B laser scanner (Axon Instruments). Expression level of each gene was represented by the intensity of its fluorescent signal. Data Extraction. All signal intensity values were processed using background-subtraction method. Prior to analysis, all values were log-transformed and normalized by fitting a print-tip group Lowess curve. Normalization minimizes bias due to dye chemistry, signal intensity or location of a gene on the array. It ensures the detection of genes that are truly differentially expressed, instead of those caused by experimental artifacts or variation in the hybridization process. After normalization, genes that had more than 50% of data missing were removed. We then selected genes that had at least 80% of the data showing two-fold changes from the geneâs median values. After filtering, 1617 genes were available for further analysis.
2010-05-25 | E-GEOD-6535 | biostudies-arrayexpress