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Current Molecular Medicine


ISSN (Print): 1566-5240
ISSN (Online): 1875-5666

Review Article

Understanding Mass Spectrometry-based Global Mycobacterial Lipidomics

Author(s): Zeeshan Fatima*, Shiv Nandan and Saif Hameed*

Volume 20, Issue 8, 2020

Page: [607 - 623] Pages: 17

DOI: 10.2174/1566524020666200206120840

Price: $65


Tuberculosis (TB) is the foremost cause of mortality from single infectious agent Mycobacterium tuberculosis (MTB). Current therapeutic regimes suffer from several problems, including side effects, costs and emergence of multidrug resistance (MDR). Moreover, conventional diagnostic methods are either too slow, or lack accurate and robust biomarkers. Under such circumstances, identification of rapid metabolite based biomarkers as novel drug targets could be a potential approach to circumvent MDR. In the era of “OMIC” sciences, lipidomics has gained significant attention to unravel the complexity of lipid-loaded Mycobacterium species. Lipidomics is a subbranch of metabolomics with extreme atomic diversity between the metabolites. There is no single principle on which the metabolite diversity can be defined, unlike other biomolecules viz. nucleic acid, proteins or carbohydrates. MTB encodes 10% of the genome for lipid metabolism and lipids account for 60% of its dry weight. Mycobacterium harbor a wide spectra of lipid repertoire ranging from highly apolar to highly polar lipids, adding complexity to their identification and analysis. Compared to targeted approaches, untargeted or global lipidomics of MTB is still more challenging. This review describes recent advances in lipidomics technology with regard to chromatography, detection methods and assessment on the existing mass spectrometry-based lipidomics tools to study the untargeted or global MTB lipidomics. It also identifies the limitations associated with present technologies as well as explores solutions to practical challenges concurrent with the establishment of MTB lipidome. Together we endorse that the emerging tools of lipidomics have provided a broader vision to comprehend the role of lipid molecules in MTB pathogenesis and the need for further improvements.

Keywords: Tuberculosis, lipids, LCMS, TLC, lipid database, lipidomics.

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