Global geographical pedigree distribution and drug resistance of <i>Mycobacterium tuberculosis</i> complex

WANG Yu-ting; TAO Bi-lin; LI Zhong-qi; WU Ji-zhou; DING Jie; WANG Jian-ming

doi:10.16462/j.cnki.zhjbkz.2022.11.002

Volume 26 Issue 11

Nov. 2022

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WANG Yu-ting, TAO Bi-lin, LI Zhong-qi, WU Ji-zhou, DING Jie, WANG Jian-ming. Global geographical pedigree distribution and drug resistance of Mycobacterium tuberculosis complex[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2022, 26(11): 1248-1251. doi: 10.16462/j.cnki.zhjbkz.2022.11.002

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WANG Yu-ting, TAO Bi-lin, LI Zhong-qi, WU Ji-zhou, DING Jie, WANG Jian-ming. Global geographical pedigree distribution and drug resistance of Mycobacterium tuberculosis complex[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2022, 26(11): 1248-1251. doi: 10.16462/j.cnki.zhjbkz.2022.11.002

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Global geographical pedigree distribution and drug resistance of Mycobacterium tuberculosis complex

doi: 10.16462/j.cnki.zhjbkz.2022.11.002

1.
Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
2.
Department of Chronic Infectious Disease Prevention and Control, Nanjing Center for Disease Control and Prevention Affiliated to Nanjing Medical University, Nanjing 210003, China

Funds:

National Natural Science Foundation of China 81973103

Medical Research Project of Jiangsu Health Commission ZDB2020013

Nanjing Major Science and Technology Project 2021-11005

More Information

Corresponding author: WANG Jian-ming, E-mail: jmwang@njmu.edu.cn
Received Date: 2022-03-28
Rev Recd Date: 2022-06-12

Available Online: 2022-12-21

Publish Date: 2022-11-10

Abstract

Abstract

Objective To map the global geographical distribution of Mycobacterium tuberculosis complex (MTBC) and describe the main MTBC lineage and drug resistance in different regions. Methods We used the whole-genome sequencing data from the TB-profiler platform to plot the global MTBC distribution map and visualized it according to the hierarchical structure of different regions and sub-lineages. Results Lineage 4 was widely distributed worldwide, while lineage 2 had the highest risk of drug resistance. Conclusions There was a significantly different geographic distribution pattern and drug resistance of MTBC lineages worldwide.
- Tuberculosis,
- Whole-genome sequencing,
- Mycobacterium tuberculosis complex,
- Lineage

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References(14)

References

[1]	WHO. Clobal tuberculosis report 2021[EB/OL]. (2021-10-14)[2022-03-01]. i.
[2]	Merker M, Kohl TA, Niemann S, et al. The evolution of strain typing in the Mycobacterium tuberculosis complex[J]. Adv Exp Med Biol, 2017, 1019: 43-78. DOI: 10.1007/978-3-319-64371-7_3.
[3]	Rivière E, Heupink TH, Ismail N, et al. Capacity building for whole genome sequencing of Mycobacterium tuberculosis and bioinformatics in high TB burden countries[J]. Brief Bioinform, 2021, 22(4): bbaa246. DOI: 10.1093/bib/bbaa246.
[4]	Cohen KA, Manson AL, Desjardins CA, et al. Deciphering drug resistance in Mycobacterium tuberculosis using whole-genome sequencing: progress, promise, and challenges[J]. Genome Med, 2019, 11(1): 45. DOI: 10.1186/s13073-019-0660-8.
[5]	Gröschel MI, Owens M, Freschi L, et al. GenTB: a user-friendly genome-based predictor for tuberculosis resistance powered by machine learning[J]. Genome Med, 2021, 13(1): 138. DOI: 10.1186/s13073-021-00953-4.
[6]	Blower SM, Chou T. Modeling the emergence of the 'hot zones': tuberculosis and the amplification dynamics of drug resistance[J]. Nat Med, 2004, 10(10): 1111-1116. DOI: 10.1038/nm1102.
[7]	Vasilyeva I, Mariandyshev A, Kazennyy B, et al. Early access to bedaquiline for extensively drug-resistant (XDR) and pre-XDR tuberculosis[J]. Eur Respir J, 2019, 54(1): 1802208. DOI: 10.1183/13993003.02208-2018.
[8]	Phelan JE, O'Sullivan DM, Machado D, et al. Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs[J]. Genome Med, 2019, 11(1): 41. DOI: 10.1186/s13073-019-0650-x.
[9]	Comas I, Coscolla M, Luo T, et al. Out-of-Africa migration and Neolithic coexpansion of Mycobacterium tuberculosis with modern humans[J]. Nat Genet, 2013, 45(10): 1176-1182. DOI: 10.1038/ng.2744.
[10]	Hershberg R, Lipatov M, Small PM, et al. High functional diversity in Mycobacterium tuberculosis driven by genetic drift and human demography[J]. PLoS Biol, 2008, 6(12): e311. DOI: 10.1371/journal.pbio.0060311.
[11]	Barbier M, Wirth T. The evolutionary history, demography, and spread of the Mycobacterium tuberculosis complex[J]. Microbiol Spectr, 2016, 4(4). DOI: 10.1128/microbiolspec.TBTB2-0008-2016.
[12]	Ford CB, Shah RR, Maeda MK, et al. Mycobacterium tuberculosis mutation rate estimates from different lineages predict substantial differences in the emergence of drug-resistant tuberculosis[J]. Nat Genet, 2013, 45(7): 784-790. DOI: 10.1038/ng.2656.
[13]	Hakamata M, Takihara H, Iwamoto T, et al. Higher genome mutation rates of Beijing lineage of Mycobacterium tuberculosis during human infection[J]. Sci Rep, 2020, 10(1): 179-197. DOI: 10.1038/s41598-020-75028-2.
[14]	Gygli SM, Borrell S, Trauner A, et al. Antimicrobial resistance in Mycobacterium tuberculosis: mechanistic and evolutionary perspectives[J]. FEMS Microbiol Rev, 2017, 41(3): 354-373. DOI: 10.1093/femsre/fux011.