Dataset Information

Tandem mass tagging (TMT) proteomics analysis of myocardium from 3 septic mice and 3 normal controls

ABSTRACT: Sepsis is often a cause of mortality in patients admitted to the intensive care unit. Notably, the heart is the organ most susceptible to the impact of sepsis.Mice injected intraperitoneally with LPS solution (20 mg/kg) were designated as the sepsis experimental group, while those injected intraperitoneally with physiological saline were designated as the control group.

ORGANISM(S): Mus Musculus

SUBMITTER: Bin Tan

PROVIDER: PXD059523 | iProX | Tue Jan 07 00:00:00 GMT 2025

REPOSITORIES: iProX

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Publications

Protective role of triiodothyronine in sepsis‑induced cardiomyopathy through phospholamban downregulation.

Xie Qiumin Q Yi Qin Q Zhu Jing J Tan Bin B Xiang Han H Wang Rui R Liu Huiwen H Chen Tangtian T Xu Hao H

International journal of molecular medicine 20250117 3

Sepsis is often a cause of mortality in patients admitted to the intensive care unit. Notably, the heart is the organ most susceptible to the impact of sepsis and this condition is referred to as sepsis‑induced cardiomyopathy (SIC). Low triiodothyronine (T3) syndrome frequently occurs in patients with sepsis, and the heart is one of the most important target organs for the action of T3. Phospholamban (PLN) is a key protein associated with Ca<sup>2+</sup>‑pump‑mediated cardiac diastolic function ...[more]

PMID: 39821325

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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. 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.

Dataset Information

Tandem mass tagging (TMT) proteomics analysis of myocardium from 3 septic mice and 3 normal controls

Publications

Protective role of triiodothyronine in sepsis‑induced cardiomyopathy through phospholamban downregulation.

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