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BIOANALYTICAL

Gas Chromatography Time-Of-Flight Mass Spectrometry-Based Metabolomic Analysis of Human Macrophages Infected by M. tuberculosis

, , , , , , , , , & show all
Pages 1922-1936 | Received 07 Jan 2013, Accepted 06 Feb 2013, Published online: 25 Jul 2013
 

Abstract

Tuberculosis is a common infectious disease caused by a bacterium called M. tuberculosis. Invasion of human macrophages is a critical step for establishing a mycobacterial infection. Many protocols, such as M. tuberculosis genomics and proteomics, have been used to discuss the pathogenesis of M. tuberculosis. This work describes a GC/MS metabolomics approach to investigate the metabolome variation of human macrophages infected by different M. tuberculosis strains. The pathogenic mechanism of M. tuberculosis was discussed from the metabolic terminal of macrophages. It was quite remarkable that most of the differential metabolites had the very similar regularity and variation tendency after infection by different virulent strains. The results suggested that M. tuberculosis invaded and infected macrophages largely through three different pathways, including glutathione anabolic metabolism, lipid biosynthesis and metabolism, and carbohydrate biosynthesis and metabolism. These pathways were affected after the invasion of M. tuberculosis, and the immunomodulatory responses of macrophages were activated at the same time. Understanding the mechanisms of macrophages to respond to the invasion of M. tuberculosis from different perspectives will help developing more effective methods to prevent, diagnose, and treat tuberculosis in the future.

Acknowledgments

J. Cheng and N. Che contributed equally to this study.

This work was supported by funding from the Chinese Scientific and Technological Major Special Project (2012ZX09301003-001-010), the National Natural Science Foundation of China (21107141, 30973676, 81001419, and 81101332), the Major Infectious Disease Special Projects (2008ZX10002-016, 2013ZX10003002-006), the Ministry of Science and Technology of China Innovation Methods of Special Projects (2009IM031700), and Beijing Excellent Researcher Training Project (2010D003034000002).

Notes

N.D., not detected.

a P < 0.05 using t- test between the certain group and the control group.

b P < 0.01.

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