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      Functional Correlations of Pathogenesis-Driven Gene Expression Signatures in Tuberculosis

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          Abstract

          Tuberculosis remains a major health threat and its control depends on improved measures of prevention, diagnosis and treatment. Biosignatures can play a significant role in the development of novel intervention measures against TB and blood transcriptional profiling is increasingly exploited for their rational design. Such profiles also reveal fundamental biological mechanisms associated with the pathology of the disease. We have compared whole blood gene expression in TB patients, as well as in healthy infected and uninfected individuals in a cohort in The Gambia, West Africa and validated previously identified signatures showing high similarities of expression profiles among different cohorts. In this study, we applied a unique combination of classical gene expression analysis with pathway and functional association analysis integrated with intra-individual expression correlations. These analyses were employed for identification of new disease-associated gene signatures, identifying a network of Fc gamma receptor 1 signaling with correlating transcriptional activity as hallmark of gene expression in TB. Remarkable similarities to characteristic signatures in the autoimmune disease systemic lupus erythematosus (SLE) were observed. Functional gene clusters of immunoregulatory interactions involving the JAK-STAT pathway; sensing of microbial patterns by Toll-like receptors and IFN-signaling provide detailed insights into the dysregulation of critical immune processes in TB, involving active expression of both pro-inflammatory and immunoregulatory systems. We conclude that transcriptomics (i) provides a robust system for identification and validation of biosignatures for TB and (ii) application of integrated analysis tools yields novel insights into functional networks underlying TB pathogenesis.

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          Most cited references18

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          Human gene expression profiles of susceptibility and resistance in tuberculosis.

          Tuberculosis (TB) still poses a profound burden on global health, owing to significant morbidity and mortality worldwide. Although a fully functional immune system is essential for the control of Mycobacterium tuberculosis infection, the underlying mechanisms and reasons for failure in part of the infected population remain enigmatic. Here, whole-blood microarray gene expression analyses were performed in TB patients and in latently as well as uninfected healthy controls to define biomarkers predictive of susceptibility and resistance. Fc gamma receptor 1B (FCGRIB)was identified as the most differentially expressed gene, and, in combination with four other markers, produced a high degree of accuracy in discriminating TB patients and latently infected donors. We determined differentially expressed genes unique for active disease and identified profiles that correlated with susceptibility and resistance to TB. Elevated expression of innate immune-related genes in active TB and higher expression of particular gene clusters involved in apoptosis and natural killer cell activity in latently infected donors are likely to be the major distinctive factors determining failure or success in controlling M. tuberculosis infection. The gene expression profiles defined in this study provide valuable clues for better understanding of progression from latent infection to active disease and pave the way for defining predictive correlates of protection in TB.
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            The role of suppressors of cytokine signaling (SOCS) proteins in regulation of the immune response.

            Cytokines are an integral component of the adaptive and innate immune responses. The signaling pathways triggered by the engagement of cytokines with their specific cell surface receptors have been extensively studied and have provided a profound understanding of the intracellular machinery that translates exposure of cells to cytokine to a coordinated biological response. It has also become clear that cells have evolved sophisticated mechanisms to prevent excessive responses to cytokines. In this review we focus on the suppressors of cytokine signaling (SOCS) family of cytoplasmic proteins that completes a negative feedback loop to attenuate signal transduction from cytokines that act through the janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway. SOCS proteins inhibit components of the cytokine signaling cascade via direct binding or by preventing access to the signaling complex. The SOCS proteins also appear to target signal transducers for proteasomal destruction. Analyses of genetically modified mice in which SOCS proteins are overexpressed or deleted have established that this family of negative regulators has indispensable roles in regulating cytokine responses in cells of the immune system as well as other tissues. Emerging evidence also suggests that disruption of SOCS expression or activity is associated with several immune and inflammatory diseases, raising the prospect that manipulation of SOCS activity may provide a novel future therapeutic strategy in the management of immunological disorders.
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              Candidate biomarkers for discrimination between infection and disease caused by Mycobacterium tuberculosis.

              Infection with Mycobacterium tuberculosis is controlled by an efficacious immune response in about 90% of infected individuals who do not develop disease. Although essential mediators of protection, e.g., interferon-gamma, have been identified, these factors are insufficient to predict the outcome of M. tuberculosis infection. As a first step to determine additional biomarkers, we compared gene expression profiles of peripheral blood mononuclear cells from tuberculosis patients and M. tuberculosis-infected healthy donors by microarray analysis. Differentially expressed candidate genes were predominantly derived from monocytes and comprised molecules involved in the antimicrobial defense, inflammation, chemotaxis, and intracellular trafficking. We verified differential expression for alpha-defensin 1, alpha-defensin 4, lactoferrin, Fcgamma receptor 1A (cluster of differentiation 64 [CD64]), bactericidal permeability-increasing protein, and formyl peptide receptor 1 by quantitative polymerase chain reaction analysis. Moreover, we identified increased protein expression of CD64 on monocytes from tuberculosis patients. Candidate biomarkers were then assessed for optimal study group discrimination. Using a linear discriminant analysis, a minimal group of genes comprising lactoferrin, CD64, and the Ras-associated GTPase 33A was sufficient for classification of (1) tuberculosis patients, (2) M. tuberculosis-infected healthy donors, and (3) noninfected healthy donors.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                28 October 2011
                : 6
                : 10
                : e26938
                Affiliations
                [1 ]Department of Immunology, Max Planck Institute for Infection Biology, Berlin, Germany
                [2 ]Medical Research Council Laboratories, Banjul, The Gambia
                [3 ]Leibniz Institute for Farm Animal Biology, Genetics and Biometry, Dummersdorf, Germany
                Statens Serum Institute, Denmark
                Author notes

                Conceived and designed the experiments: JM MO DR SHEK. Performed the experiments: JM HJM PCH. Analyzed the data: JM JW HJM DR. Contributed reagents/materials/analysis tools: MO PCH JW. Wrote the paper: JM SHEK.

                Article
                PONE-D-11–15038
                10.1371/journal.pone.0026938
                3203931
                22046420
                3f6002b8-96bc-458a-9a6c-6c8aaae43504
                Maertzdorf et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 3 August 2011
                : 6 October 2011
                Page count
                Pages: 8
                Categories
                Research Article
                Biology
                Computational Biology
                Genomics
                Genome Analysis Tools
                Transcriptomes
                Genomics
                Genome Analysis Tools
                Transcriptomes
                Genome Expression Analysis
                Microbiology
                Immunity
                Immune Defense
                Host-Pathogen Interaction
                Medicine
                Clinical Immunology
                Immunity
                Immunity to Infections
                Diagnostic Medicine
                Pathology
                General Pathology
                Biomarkers
                Infectious Diseases
                Bacterial Diseases
                Tuberculosis
                Tropical Diseases (Non-Neglected)
                Tuberculosis

                Uncategorized
                Uncategorized

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