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GNPS Metabolomics Workbench ST001378 - GNPS Global metabolomics of COPD2020

ABSTRACT: b'To discover distinctive endogenous metabotype of patients with COPD associated with TB from those originated from Tabaco smoking. Cross-sectional metabolomic analyses of serum samples were performed for subjects including TB-associated COPD (T-COPD), smoking-associated COPD (S-COPD) and healthy subjects. To retain a broad spectrum of metabolites, technically distinct analyses (global metabolomic profiling using liquid chromatography quadrupole time-of-flight mass spectrometry) were employed. Frozen samples were diluted with either an acetonitrile:methanol:water (3:3:4) mixture. Each sample (5 L) was loaded onto an C18 column and was analyzed using an Agilent 6530 QTOF mass spectrometer (Agilent Technologies). Detailed protocol is obtained in this project'

INSTRUMENT(S): 6530A Q-TOF LC/MS

ORGANISM(S): Homo Sapiens

SUBMITTER: Da jung Kim

PROVIDER: MSV000086873 | GNPS | Mon Feb 15 17:16:00 GMT 2021

REPOSITORIES: GNPS

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Project description:Although host genetics influences susceptibility to tuberculosis, few genes determining disease outcome have been identified. We hypothesized that macrophages from individuals with different clinical manifestations of tuberculosis infection would have distinct gene expression profiles, and that polymorphisms in these genes may also be associated with susceptibility to TB. We measured gene expression levels of >38,500 genes from ex vivo Mtb- stimulated macrophages in 12 subjects with 3 clinical phenotypes: latent, pulmonary and meningeal tuberculosis (n=4 per group). After identifying differentially expressed genes, we confirmed these results in 34 additional subjects by real-time PCR. We also used a case-control study design to examine whether polymorphisms in differentially regulated genes were associated with susceptibility to these different clinical forms of TB. We compared gene expression profiles in Mtb-stimulated and unstimulated macrophages and identified 1608 and 199 genes that were differentially expressed by >2 and >5-fold, respectively. Using cluster analysis, we identified gene expression patterns that distinguished the different clinical forms of tuberculosis. In an independent sample set of 34 individuals and a subset of highly regulated genes, 90% of the microarray results were confirmed by RT-PCR, including expression levels of CCL1, which distinguished the 3 clinical groups. Furthermore, 6 single nucleotide polymorphisms (SNPs) in CCL1 were found to be associated with TB in a case-control genetic association study with 273 TB cases and 188 controls. To our knowledge, this is the first identification of CCL1 as a gene involved in host susceptibility to TB and the first study to combine microarray and DNA polymorphism studies to identify genes associated with TB susceptibility. These results suggest that genome-wide studies can provide an unbiased method to identify critical macrophage response genes that are associated with different clinical outcomes and that variation in innate immune response genes regulate susceptibility to tuberculosis. Experiment Overall Design: Latent TB (LTB) subjects were healthy nursing staff members who had worked at a tuberculosis hospital, for more than 20 years and were positive in ESAT-6 and CFP-10- specific IFN-ï?§ ELISPOT assays. All subjects with pulmonary (PTB) and meningeal (TBM) disease had been treated and were free of symptoms at the time of venipuncture. Gene expression of monocyte derived macrophages (MDMs) from subjects with three clinical forms of TB including LTB, PTB and TBM (n = 4 in each group) was examined by microarray. MDMs were stimulated either with a whole cell lysate of M. tuberculosis H37Rv or PBS for 4 hours. RNA expression was analyzed using a Human Genome U133 Plus 2.0 Array (Affymetrix, USA) which contains probe sets for 47,000 transcripts including 38,500 well-characterized human genes.

Project description:Tuberculosis (TB) is an ancient infectious disease that remains one of the major health threats in humans worldwide. 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. 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 gene signature analyses were employed for pathognomonic associations, 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, and functional gene clusters of immunoregulatory interactions provide detailed insights into the dysregulation of critical immune processes in TB. Transcriptomics thus (i) provides a robust system for identification and validation of biosignatures for TB diagnosis and (ii) application of integrated analysis tools yields novel insights into functional networks underlying TB pathogenesis. A total of 46 sputum smear and chest x-ray positive TB patients (TB), 25 latently infected healthy donors (LTBI, TB case contacts with Mantoux test induration >= 10mm) and 37 uninfected donors (NID, Mantoux test induration = 0mm) were included from a cohort in The Gambia. All subjects were HIV– and samples from TB patients were taken prior to chemotherapy. Whole blood RNA was extracted using the PAXgene Blood RNA Kit (PreAnalytix) and labeled with Agilents Fluorescent Linear Amplification Kit. Quantity and labeling efficiency were verified before hybridization of the samples to whole-genome 4×44k human expression arrays and scanned at 5 μm using an Agilent scanner.

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GNPS Metabolomics Workbench ST001378 - GNPS Global metabolomics of COPD2020

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