Dataset Information

Protection from lethal gram-negative bacterial sepsis by targeting Toll-like receptor 4.

ABSTRACT: Toll-like receptor 4 (TLR4), the signal-transducing molecule of the LPS receptor complex, plays a fundamental role in the sensing of LPS from gram-negative bacteria. Activation of TLR4 signaling pathways by LPS is a critical upstream event in the pathogenesis of gram-negative sepsis, making TLR4 an attractive target for novel antisepsis therapy. To validate the concept of TLR4-targeted treatment strategies in gram-negative sepsis, we first showed that TLR4(-/-) and myeloid differentiation primary response gene 88 (MyD88)(-/-) mice were fully resistant to Escherichia coli-induced septic shock, whereas TLR2(-/-) and wild-type mice rapidly died of fulminant sepsis. Neutralizing anti-TLR4 antibodies were then generated using a soluble chimeric fusion protein composed of the N-terminal domain of mouse TLR4 (amino acids 1-334) and the Fc portion of human IgG1. Anti-TLR4 antibodies inhibited intracellular signaling, markedly reduced cytokine production, and protected mice from lethal endotoxic shock and E. coli sepsis when administered in a prophylactic and therapeutic manner up to 13 h after the onset of bacterial sepsis. These experimental data provide strong support for the concept of TLR4-targeted therapy for gram-negative sepsis.

SUBMITTER: Roger T

PROVIDER: S-EPMC2650125 | biostudies-literature | 2009 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Protection from lethal gram-negative bacterial sepsis by targeting Toll-like receptor 4.

Roger Thierry T Froidevaux Céline C Le Roy Didier D Reymond Marlies Knaup MK Chanson Anne-Laure AL Mauri Davide D Burns Kim K Riederer Beat Michel BM Akira Shizuo S Calandra Thierry T

Proceedings of the National Academy of Sciences of the United States of America 20090130 7

Toll-like receptor 4 (TLR4), the signal-transducing molecule of the LPS receptor complex, plays a fundamental role in the sensing of LPS from gram-negative bacteria. Activation of TLR4 signaling pathways by LPS is a critical upstream event in the pathogenesis of gram-negative sepsis, making TLR4 an attractive target for novel antisepsis therapy. To validate the concept of TLR4-targeted treatment strategies in gram-negative sepsis, we first showed that TLR4(-/-) and myeloid differentiation primar ...[more]

PMID: 19181857

Similar Datasets

Project description:BackgroundToll-like receptors (TLRs) are essential in host defense against pathogens by virtue of their capacity to detect microbes and initiate the immune response. TLR2 is seen as the most important receptor for gram-positive bacteria, while TLR4 is regarded as the gram-negative TLR. Melioidosis is a severe infection caused by the gram-negative bacterium, Burkholderia pseudomallei, that is endemic in Southeast Asia. We aimed to characterize the expression and function of TLRs in septic melioidosis.Methods and findingsPatient studies: 34 patients with melioidosis demonstrated increased expression of CD14, TLR1, TLR2, and TLR4 on the cell surfaces of monocytes and granulocytes, and increased CD14, TLR1, TLR2, TLR4, LY96 (also known as MD-2), TLR5, and TLR10 mRNA levels in purified monocytes and granulocytes when compared with healthy controls. In vitro experiments: Whole-blood and alveolar macrophages obtained from TLR2 and TLR4 knockout (KO) mice were less responsive to B. pseudomallei in vitro, whereas in the reverse experiment, transfection of HEK293 cells with either TLR2 or TLR4 rendered these cells responsive to this bacterium. In addition, the lipopolysaccharide (LPS) of B. pseudomallei signals through TLR2 and not through TLR4. Mouse studies: Surprisingly, TLR4 KO mice were indistinguishable from wild-type mice with respect to bacterial outgrowth and survival in experimentally induced melioidosis. In contrast, TLR2 KO mice displayed a markedly improved host defenses as reflected by a strong survival advantage together with decreased bacterial loads, reduced lung inflammation, and less distant-organ injury.ConclusionsPatients with melioidosis displayed an up-regulation of multiple TLRs in peripheral blood monocytes and granulocytes. Although both TLR2 and TLR4 contribute to cellular responsiveness to B. pseudomallei in vitro, TLR2 detects the LPS of B. pseudomallei, and only TLR2 impacts on the immune response of the intact host in vivo. Inhibition of TLR2 may be a novel treatment strategy in melioidosis.

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

Protection from lethal gram-negative bacterial sepsis by targeting Toll-like receptor 4.

Publications

Protection from lethal gram-negative bacterial sepsis by targeting Toll-like receptor 4.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure