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High-resolution plasma metabolomics analysis to detect Mycobacterium tuberculosis-associated metabolites that distinguish active pulmonary tuberculosis in humans.

Jeffrey M Collins | Douglas I Walker | Dean P Jones | Nestani Tukvadze | Ken H Liu | ViLinh T Tran | Karan Uppal | Jennifer K Frediani | Kirk A Easley | Neeta Shenvi | Manoj Khadka | Eric A Ortlund | Russell R Kempker | Henry M Blumberg | Thomas R Ziegler
PloS one | 2018

Pulmonary tuberculosis (TB) is a major worldwide health problem that lacks robust blood-based biomarkers for detection of active disease. High-resolution metabolomics (HRM) is an innovative method to discover low-abundance metabolites as putative blood biomarkers to detect TB disease, including those known to be produced by the causative organism, Mycobacterium tuberculosis (Mtb).

Pubmed ID: 30308073

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

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Associated grants

  • Agency: NIAID NIH HHS, United States
    Id: P30 AI050409
  • Agency: NIGMS NIH HHS, United States
    Id: T32 GM008602
  • Agency: FIC NIH HHS, United States
    Id: D43 TW007124
  • Agency: NIAID NIH HHS, United States
    Id: K23 AI103044
  • Agency: NCATS NIH HHS, United States
    Id: UL1 TR002378

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This is a list of tools and resources that we have found mentioned in this publication.


xMSanalyzer (tool)

RRID:SCR_012144

A software package of utilities for data extraction, quality control assessment, detection of overlapping and unique metabolites in multiple datasets, and batch annotation of metabolites. xMSanalyzer comprises of utilities that can be classified into five main modules: 1) merging apLCMS or XCMS sample processing results from multiple sets of parameter settings, 2) evaluation of sample quality, feature consistency, and batch-effect, 3) feature matching, and 4) characterization of m/z using KEGG REST; 5) Batch-effect correction using ComBat.

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