Progress in metabolomics research on tuberculosis

doi:10.3969/j.issn.1000-6621.2018.11.015

Abstract

Abstract:

World Health Organization (WHO) has proposed terminating tuberculosis epidemic globally by 2035.To achieve this goal, new breakthroughs are urgently needed through researches on the mechanism of drug resistance development in Mycobacterium tuberculosis, the search for new tuberculosis diagnostic markers, and the development of new anti-tuberculosis drugs. Metabolomics is an emerging omics technique for studying endogenous metabolic changes in the body. Compared with the issues, such as genetic complexity and post-transcriptional modification, etc., which are faced by other omics researches, metabolomics may directly reflect the changes in the body’s endogenous metabolic information, obtain the metabolic markers of the organisms for disease prevention through multivariate statistical analysis and can provide guidance on the diagnosis, treatment, prognosis of disease. At present, metabolomics has been widely applied in the research of tuberculosis and achievements have been made in terms of the diagnosis and treatment of tuberculosis. The recent progress of metabolomics in tuberculosis research is summarized in this paper.

Key words: Tuberculosis, Metabolomics, Etiology, Diagnosis and treatment, Prognosis

WEI Jin-tao,LI Hua,QIU En-ming.. Progress in metabolomics research on tuberculosis[J]. Chinese Journal of Antituberculosis, 2018, 40(11): 1226-1230. doi: 10.3969/j.issn.1000-6621.2018.11.015

References 50

[1]	World Health Organization . Global tuberculosis report 2018. Geneva: World Health Organization, 2018.
[2]	孙琳, 申阿东 . 代谢组学在结核病诊疗和病原学研究中的应用. 中国防痨杂志, 2016,38(3):175-179. doi: 10.3969/j.issn.1000-6621.2016.03.004
[3]	Houben RM, Dodd PJ . The global burden of latent tuberculosis infection: a re-estimation using mathematical modelling. PLoS Med, 2016,13(10):e1002152. doi: 10.1371/journal.pmed.1002152 URL pmid: 5079585
[4]	Martin SJ, Sabina EP . Malnutrition and associated disorders in tuberculosis and its therapy. J Diet Suppl, 2018: 1-9. [Epub ahead of print]. doi: 10.1080/19390211.2018.1472165 URL
[5]	Parida SK, Kaufmann SH . The quest for biomarkers in tuberculosis. Drug Discov Today, 2010,15(3-4):148-157. doi: 10.1016/j.drudis.2009.10.005 URL pmid: 19854295
[6]	Patti GJ, Yanes O, Siuzdak G . Innovation: Metabolomics: the apogee of the omics trilogy. Nat Rev Mol Cell Biol, 2012,13(4):263-269. doi: 10.1038/nrm3314 URL pmid: 22436749
[7]	徐超, 任立红 . 代谢组学在白血病中的应用. 医学综述, 2018,24(7):1294-1298.
[8]	杨帆, 谢树红, 黄惠娟 . 卵巢癌在代谢组学中的研究进展. 东南国防医药, 2018,20(2):160-163.
[9]	王晓东, 何秉淑, 何慧欣 , 等. 代谢组学方法在糖尿病肾病研究中的应用. 中央民族大学学报(自然科学版), 2017,26(3):58-64.
[10]	王双双, 曾范利, 李东 , 等. 结核分枝杆菌毒力相关因子的研究进展. 中国兽医科学, 2018,48(6):750-755.
[11]	Berney M, Berney-Meyer L . Mycobacterium tuberculosis in the Face of Host-Imposed Nutrient Limitation. Microbiol Spectr, 2017,5(3).
[12]	Puckett S, Trujillo C, Wang Z , et al. Glyoxylate detoxification is an essential function of malate synthase required for carbon assimilation in Mycobacterium tuberculosis. Proc Natl Acad Sci U S A, 2017,114(11):E2225-2232. doi: 10.1073/pnas.1617655114 URL pmid: 28265055
[13]	Ganapathy U, Marrero J, Calhoun S , et al. Two enzymes with redundant fructose bisphosphatase activity sustain gluconeogenesis and virulence in Mycobacterium tuberculosis. Nat Commun, 2015,6:7912. doi: 10.1038/ncomms8912 URL pmid: 26258286
[14]	Zimmermann M, Kogadeeva M, Gengenbacher M , et al. Integration of Metabolomics and Transcriptomics Reveals a Complex Diet of Mycobacterium tuberculosis during Early Macrophage Infection. mSystems, 2017,2(4):e00057-17. doi: 10.1128/mSystems.00057-17 URL pmid: 5566787
[15]	孙铭艳, 伊正君, 付玉荣 . 结核病与铁代谢关系的研究进展. 中华结核和呼吸杂志, 2014,37(10):780-781. doi: 10.3760/cma.j.issn.1001-0939.2014.10.020 URL
[16]	Kurthkoti K, Amin H, Marakalala MJ , et al. The Capacity of Mycobacterium tuberculosis To Survive Iron Starvation Might Enable It To Persist in Iron-Deprived Microenvironments of Human Granulomas. MBio, 2017,8(4):e01092-17. doi: 10.1128/mBio.01092-17 URL pmid: 5559634
[17]	李香社, 祝玉芬 . 我国结核分枝杆菌耐药现状及研究进展. 临床误诊误治, 2017,30(7):114-116. doi: 10.3969/j.issn.1002-3429.2017.07.035 URL
[18]	Nandakumar M, Nathan C, Rhee KY . Isocitrate lyase media-tes broad antibiotic tolerance in Mycobacterium tuberculosis. Nat Commun, 2014,5:4306. doi: 10.1038/ncomms5306 URL pmid: 24978671
[19]	Larrouy-Maumus G, Marino LB, Madduri AV , et al. Cell-Envelope Remodeling as a Determinant of Phenotypic Antibacterial Tolerance in Mycobacterium tuberculosis. ACS Infect Dis, 2016,2(5):352-360. doi: 10.1021/acsinfecdis.5b00148 URL pmid: 27231718
[20]	Loots DT . New insights into the survival mechanisms of rifampicin-resistant Mycobacterium tuberculosis. J Antimicrob Chemother, 2016,71(3):655-660. doi: 10.1093/jac/dkv406 URL pmid: 26679254
[21]	Loots DT . An altered Mycobacterium tuberculosis metabolome induced by katG mutations resulting in isoniazid resistance. Antimicrob Agents Chemother, 2014,58(4):2144-2149. doi: 10.1128/AAC.02344-13 URL pmid: 24468786
[22]	罗少军 . PPD试验在结核病诊断中的重要性及临床意义分析. 世界最新医学信息文摘, 2017,17(100):41.
[23]	唐方能, 杨仁国, 耿晓霞 , 等. γ-干扰素释放试验诊断活动性结核病分析. 寄生虫病与感染性疾病, 2017,15(1):42-46.
[24]	胡彦, 陈娟娟, 王小中 . 结核分枝杆菌实验室诊断方法及评价. 实验与检验医学, 2016,34(2):177-179, 182.
[25]	刘欣欣, 张曼林, 汤兵祥 . T-SPOT. TB与传统结核诊断方法对比研究. 河南医学研究, 2017,26(4):602-603. doi: 10.3969/j.issn.1004-437X.2017.04.010 URL
[26]	Isa F, Collins S, Lee MH , et al. Mass Spectrometric Identification of Urinary Biomarkers of Pulmonary Tuberculosis. E Bio Medicine, 2018,31:157-165. doi: 10.1016/j.ebiom.2018.04.014 URL
[27]	Luier L, Loots DT . Tuberculosis metabolomics reveals adaptations of man and microbe in order to outcompete and survive. Metabolomics, 2016,12(3):1-9. doi: 10.1007/s11306-015-0887-3 URL
[28]	Feng S, Du YQ, Zhang L , et al. Analysis of serum metabolic profile by ultra-performance liquid chromatography-mass spectrometry for biomarkers discovery: application in a pilot study to discriminate patients with tuberculosis. Chin Med J (Engl), 2015,128(2):159-168. doi: 10.4103/0366-6999.149188 URL pmid: 25591556
[29]	Sun L, Li JQ, Ren N , et al. Utility of Novel Plasma Metabolic Markers in the Diagnosis of Pediatric Tuberculosis: A Classification and Regression Tree Analysis Approach. J Proteome Res, 2016,15(9):3118-3125. doi: 10.1021/acs.jproteome.6b00228 URL pmid: 27451809
[30]	Kuntzel A, Oertel P, Fischer S , et al. Comparative analysis of volatile organic compounds for the classification and identification of mycobacterial species. PLoS One, 2018,13(3):e194348. doi: 10.1371/journal.pone.0194348 URL pmid: 29558492
[31]	Wang C, Peng J, Kuang Y , et al. Metabolomic analysis based on ¹H-nuclear magnetic resonance spectroscopy metabolic profiles in tuberculous, malignant and transudative pleural effusion . Mol Med Rep, 2017,16(2):1147-1156. doi: 10.3892/mmr.2017.6758 URL pmid: 28627685
[32]	Che N, Ma Y, Ruan H , et al. Integrated semi-targeted metabolomics analysis reveals distinct metabolic dysregulation in pleural effusion caused by tuberculosis and malignancy. Clin Chim Acta, 2018,477:81-88. doi: 10.1016/j.cca.2017.12.003 URL pmid: 29208371
[33]	Li Z, Du B, Li J , et al. Cerebrospinal fluid metabolomic profiling in tuberculous and viral meningitis: Screening potential markers for differential diagnosis. Clin Chim Acta, 2017,466:38-45. doi: 10.1016/j.cca.2017.01.002 URL pmid: 28063937
[34]	Mason S, Reinecke CJ, Solomons R . Cerebrospinal Fluid Amino Acid Profiling of Pediatric Cases with Tuberculous Meningitis. Front Neurosci, 2017,11:534. doi: 10.3389/fnins.2017.00534 URL pmid: 5623012
[35]	Rawat A, Chaturvedi S, Singh AK , et al. Metabolomics approach discriminates toxicity index of pyrazinamide and its metabolic products, pyrazinoic acid and 5-hydroxy pyrazinoic acid. Hum Exp Toxicol, 2017,37(4):373-389. doi: 10.1177/0960327117705426 URL pmid: 28425350
[36]	Cao J, Mi Y, Shi C , et al. First-line anti-tuberculosis drugs induce hepatotoxicity: A novel mechanism based on a urinary metabolomics platform. Biochemical Biophys Res Commun, 2018,497(2):485-491. doi: 10.1016/j.bbrc.2018.02.030 URL
[37]	曹俊 . 运用尿液代谢组学对抗结核药物肝毒性机制的研究. 苏州:苏州大学, 2017.
[38]	Ruan LY, Fan JT, Hong W , et al. Isoniazid-induced hepatotoxicity and neurotoxicity in rats investigated by ¹H NMR based metabolomics approach . Toxicol Lett, 2018,295:256-269. doi: 10.1016/j.toxlet.2018.05.032 URL
[39]	Li F, Wang P, Liu K , et al. A High Dose of Isoniazid Disturbs Endobiotic Homeostasis in Mouse Liver. Drug Metab Dispos, 2016,44(11):1742-1751. doi: 10.1124/dmd.116.070920 URL pmid: 27531952
[40]	Awasthi D, Freundlich JS . Antimycobacterial Metabolism: Illuminating Mycobacterium tuberculosis Biology and Drug Discovery. Trends Microbiol, 2017,25(9):756-767. doi: 10.1016/j.tim.2017.05.007 URL pmid: 28622844
[41]	Song L, Gao D, Li S , et al. Simultaneous quantitation of hydrazine and acetylhydrazine in human plasma by high performance liquid chromatography-tandem mass spectrometry after derivatization with p-tolualdehyde. J Chromatogr B Analyt Technol Biomed Life Sci, 2017,1063:189-195. doi: 10.1016/j.jchromb.2017.08.036 URL pmid: 28881295
[42]	Koen N, van Breda SV, Loots DT . Metabolomics of colistin methanesulfonate treated Mycobacterium tuberculosis. Tuberculosis (Edinb), 2018,111:154-160. doi: 10.1016/j.tube.2018.06.008 URL
[43]	Koen N, van Breda SV, Loots DT . Elucidating the antimicrobial mechanisms of colistin sulfate on Mycobacterium tuberculosis using metabolomics. Tuberculosis (Edinb), 2018,111:14-19. doi: 10.1016/j.tube.2018.05.001 URL pmid: 30029899
[44]	Baptista R, Fazakerley DM, Beckmann M , et al. Untargeted metabolomics reveals a new mode of action of pretomanid (PA-824). Sci Rep, 2018,8(1):5084. doi: 10.1038/s41598-018-23110-1 URL pmid: 29572459
[45]	Marshall DD, Halouska S, Zinniel DK , et al. Assessment of Metabolic Changes in Mycobacterium smegmatis Wild-Type and alr Mutant Strains: Evidence of a New Pathway of d-Alanine Biosynthesis. J Proteome Res, 2017,16(3):1270-1279. doi: 10.1021/acs.jproteome.6b00871 URL
[46]	Prosser GA, Rodenburg A, Khoury H , et al. Glutamate Racemase Is the Primary Target of beta-Chloro-d-Alanine in Mycobacterium tuberculosis. Antimicrob Agents Chemother, 2016,60(10):6091-6099. doi: 10.1128/AAC.01249-16 URL
[47]	Zampieri M, Szappanos B, Buchieri MV , et al. High-throughput metabolomic analysis predicts mode of action of uncharacterized antimicrobial compounds. Sci Transl Med, 2018, 10(429): pii: eaal3973. doi: 10.1126/scitranslmed.aal3973 URL
[48]	Das MK, Bishwal SC, Das A , et al. Deregulated tyrosine-phenylalanine metabolism in pulmonary tuberculosis patients. J Proteome Res, 2015,14(4):1947-1956. doi: 10.1021/acs.jproteome.5b00016 URL pmid: 25693719
[49]	Luies L, Reenen MV, Ronacher K , et al. Predicting tuberculosis treatment outcome using metabolomics. Biomark Med, 2017,11(12):1057-1067. doi: 10.2217/bmm-2017-0133 URL pmid: 29172670
[50]	Zetola NM, Modongo C, Matsiri O , et al. Diagnosis of pulmonary tuberculosis and assessment of treatment response through analyses of volatile compound patterns in exhaled breath samples. J Infect, 2017,74(4):367-376. doi: 10.1016/j.jinf.2016.12.006 URL pmid: 28017825