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TLR4 genetic variation is associated with inflammatory responses in Gram-positive sepsis.

ABSTRACT: To identify important pathogen recognition receptor (PRR) pathways regulating innate immune responses and outcome in Staphylococcus aureus sepsis.We analysed whether candidate PRR pathway genetic variants were associated with killed S. aureus-induced cytokine responses ex vivo and performed follow-up in vitro studies. We tested the association of our top-ranked variant with cytokine responses and clinical outcomes in a prospective multicentre cohort of patients with staphylococcal sepsis.An intronic TLR4 polymorphism and expression quantitative trait locus, rs1927907, was highly associated with cytokine release induced by stimulation of blood from healthy Thai subjects with S. aureus ex vivo. S. aureus did not induce TLR4-dependent NF-?B activation in transfected HEK293 cells. In monocytes, tumor necrosis factor (TNF)-? release induced by S. aureus was not blunted by a TLR4/MD-2 neutralizing antibody, but in a monocyte cell line, TNF-? was reduced by knockdown of TLR4. In Thai patients with staphylococcal sepsis, rs1927907 was associated with higher interleukin (IL)-6 and IL-8 levels as well as with respiratory failure. S. aureus-induced responses in blood were most highly correlated with responses to Gram-negative stimulants whole blood.A genetic variant in TLR4 is associated with cytokine responses to S. aureus ex vivo and plasma cytokine levels and respiratory failure in staphylococcal sepsis. While S. aureus does not express lipopolysaccharide or activate TLR4 directly, the innate immune response to S. aureus does appear to be modulated by TLR4 and shares significant commonality with that induced by Gram-negative pathogens and lipopolysaccharide.

SUBMITTER: Chantratita N

PROVIDER: S-EPMC5218870 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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TLR4 genetic variation is associated with inflammatory responses in Gram-positive sepsis.

Chantratita N N Tandhavanant S S Seal S S Wikraiphat C C Wongsuvan G G Ariyaprasert P P Suntornsut P P Teerawattanasook N N Jutrakul Y Y Srisurat N N Chaimanee P P Mahavanakul W W Srisamang P P Phiphitaporn S S Mokchai M M Anukunananchai J J Wongratanacheewin S S Chetchotisakd P P Emond M J MJ Peacock S J SJ West T E TE

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases 20160908 1

<h4>Objectives</h4>To identify important pathogen recognition receptor (PRR) pathways regulating innate immune responses and outcome in Staphylococcus aureus sepsis.<h4>Methods</h4>We analysed whether candidate PRR pathway genetic variants were associated with killed S. aureus-induced cytokine responses ex vivo and performed follow-up in vitro studies. We tested the association of our top-ranked variant with cytokine responses and clinical outcomes in a prospective multicentre cohort of patients ...[more]

PMID: 27615723

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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.

Project description:Sepsis is an inflammatory response to pathogens (such as Gram?positive and Gram?negative bacteria), which has high morbidity and mortality in critically ill patients. The present study aimed to identify the key genes in Gram?positive and Gram?negative sepsis. GSE6535 was downloaded from Gene Expression Omnibus, containing 17 control samples, 18 Gram?positive samples and 25 Gram?negative samples. Subsequently, the limma package in R was used to screen the differentially expressed genes (DEGs). Hierarchical clustering was conducted for the specific DEGs in Gram?negative and Gram?negative samples using cluster software and the TreeView software. To analyze the correlation of samples at the gene level, a similarity network was constructed using Cytoscape software. Functional and pathway enrichment analyses were conducted for the DEGs using DAVID. Finally, stochastic perturbation was used to determine the significantly differential functions between Gram?positive and Gram?negative samples. A total of 340 and 485 DEGs were obtained in Gram?positive and Gram?negative samples, respectively. Hierarchical clustering revealed that there were significant differences between control and sepsis samples. In Gram?positive and Gram?negative samples, myeloid cell leukemia sequence 1 was associated with apoptosis and programmed cell death. Additionally, NADH:ubiquinone oxidoreductase subunit S4 was associated with mitochondrial respiratory chain complex I assembly. Stochastic perturbation analysis revealed that NADH:ubiquinone oxidoreductase subunit B2 (NDUFB2), NDUFB8 and ubiquinol?cytochrome c reductase hinge protein (UQCRH) were associated with cellular respiration in Gram?negative samples, whereas large tumor suppressor kinase 2 (LATS2) was associated with G1/S transition of the mitotic cell cycle in Gram?positive samples. NDUFB2, NDUFB8 and UQCRH may be biomarkers for Gram?negative sepsis, whereas LATS2 may be a biomarker for Gram?positive sepsis. These findings may promote the therapies of sepsis caused by Gram?positive and Gram?negative bacteria.

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TLR4 genetic variation is associated with inflammatory responses in Gram-positive sepsis.

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TLR4 genetic variation is associated with inflammatory responses in Gram-positive sepsis.

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