The Metabolomics Core (B) is comprised of a Biosafety Level 3 suite for handling infectious samples, massively parallel detection of mycobacterial metabolites using Time of Flight mass spectrometry (Agilent Accurate Mass ToF 6230), specialized resources for identifying known mycobacterial compounds, and analytical capabilities to discover previously unknown compounds (Agilent Accurate Mass 6520, QTof, Thermo LXQ Advantage 2 Dimensional Ion Trap with MSn). The integrated technologies were assembled by the Moody laboratory and supported a Biomarker Discover Initiative of the Broad Institute, NIH U19 and ROl Projects. Dataflow involves receipt of mycobacteria (Project 3) or patient samples (Project 4), from which total metabolites are extracted and sterilized in organic solvents. Tissue or mycobacterial extracts enter into a liquid chromatography-mass spectrometry system, which was specifically designed to broadly detect the highly diverse and hydrophobic compounds in mycobacteria. In the first phase of whole organism analysis, the platform rapidly detects triplicate intensity values for ~10,000 distinct compounds in each sample. By aligning large datasets derived from different patients, clinical isolates or genetically engineered bacteria, in-house-designed software pipeline identifies all compounds that are changed at statistically significant levels. In a second, targeted phase, all changed compounds are ranked by biological or quantitative criteria to define compounds of interest, whose structures are solved by comparing their masses to the literature (MycoMass) and in-house (MycoMap) databases or are solved through collisional mass spectrometry. This system has discovered previously unknown compounds, identified strain-specific mycobacterial biomarkers in vitro and from tissues and identified lipids changed after gene deletion. This overview describes expansion of the substantial existing core facilities, including a new generation of high accuracy mass spectrometry and expansion of mycobacterial databases, as well as use of the Core to discover biomarkers in drug-resistant or latent mycobacteria or biomarkers of infection.
Mycobacterium tuberculosis is a highly contagious bacterial pathogen, which kills about 1.6 million people per year. This Metabolomics Core (B) can rapidly detect thousands of molecules in Mycobacterium tuberculosis from human patients at the Partners in Health Clinics, providing new methods to rapidly diagnose tuberculosis disease and understand how the bacterium escapes killing by drugs.
|Carette, Xavier; Platig, John; Young, David C et al. (2018) Multisystem Analysis of Mycobacterium tuberculosis Reveals Kinase-Dependent Remodeling of the Pathogen-Environment Interface. MBio 9:|
|Lehmann, Johannes; Cheng, Tan-Yun; Aggarwal, Anup et al. (2018) An Antibacterial ?-Lactone Kills Mycobacterium tuberculosis by Disrupting Mycolic Acid Biosynthesis. Angew Chem Int Ed Engl 57:348-353|
|Wun, Kwok S; Reijneveld, Josephine F; Cheng, Tan-Yun et al. (2018) T cell autoreactivity directed toward CD1c itself rather than toward carried self lipids. Nat Immunol 19:397-406|
|James, Charlotte A; Yu, Krystle K Q; Gilleron, Martine et al. (2018) CD1b Tetramers Identify T Cells that Recognize Natural and Synthetic Diacylated Sulfoglycolipids from Mycobacterium tuberculosis. Cell Chem Biol 25:392-402.e14|
|Mizoguchi, Fumitaka; Slowikowski, Kamil; Wei, Kevin et al. (2018) Functionally distinct disease-associated fibroblast subsets in rheumatoid arthritis. Nat Commun 9:789|
|Davenport, Emma E; Amariuta, Tiffany; Gutierrez-Arcelus, Maria et al. (2018) Discovering in vivo cytokine-eQTL interactions from a lupus clinical trial. Genome Biol 19:168|
|Madigan, Cressida A; Cambier, C J; Kelly-Scumpia, Kindra M et al. (2017) A Macrophage Response to Mycobacterium leprae Phenolic Glycolipid Initiates Nerve Damage in Leprosy. Cell 170:973-985.e10|
|Moody, D Branch (2017) How T cells grasp mycobacterial lipid antigens. Proc Natl Acad Sci U S A 114:13312-13314|
|Brennan, Patrick J; Cheng, Tan-Yun; Pellicci, Daniel G et al. (2017) Structural determination of lipid antigens captured at the CD1d-T-cell receptor interface. Proc Natl Acad Sci U S A 114:8348-8353|
|Rao, Deepak A; Gurish, Michael F; Marshall, Jennifer L et al. (2017) Pathologically expanded peripheral T helper cell subset drives B cells in rheumatoid arthritis. Nature 542:110-114|
Showing the most recent 10 out of 49 publications