Identification of novel single nucleotide variants in the drug resistance mechanism of Mycobacterium tuberculosis isolates by whole-genome analysis

Weiye Qian; Nan Ma; Xi Zeng; Mai Shi; Mingqiang Wang; Zhiyuan Yang; Stephen Kwok-Wing Tsui

doi:10.1186/s12864-024-10390-3

Identification of novel single nucleotide variants in the drug resistance mechanism of Mycobacterium tuberculosis isolates by whole-genome analysis

BMC Genomics. 2024 May 14;25(1):478. doi: 10.1186/s12864-024-10390-3.

Authors

Weiye Qian¹, Nan Ma¹, Xi Zeng², Mai Shi³, Mingqiang Wang⁴, Zhiyuan Yang^{5

6}, Stephen Kwok-Wing Tsui^{7

8}

Affiliations

¹ School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou, 310018, China.
² Agricultural Bioinformatics Key Laboratory of Hubei Province and 3D Genomics Research Centre, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China.
³ School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
⁴ Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA.
⁵ School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou, 310018, China. yangzhiyuan@link.cuhk.edu.hk.
⁶ School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China. yangzhiyuan@link.cuhk.edu.hk.
⁷ School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China. kwtsui@cuhk.edu.hk.
⁸ Hong Kong Bioinformatics Centre, The Chinese University of Hong Kong, Hong Kong SAR, China. kwtsui@cuhk.edu.hk.

Abstract

Background: Tuberculosis (TB) represents a major global health challenge. Drug resistance in Mycobacterium tuberculosis (MTB) poses a substantial obstacle to effective TB treatment. Identifying genomic mutations in MTB isolates holds promise for unraveling the underlying mechanisms of drug resistance in this bacterium.

Methods: In this study, we investigated the roles of single nucleotide variants (SNVs) in MTB isolates resistant to four antibiotics (moxifloxacin, ofloxacin, amikacin, and capreomycin) through whole-genome analysis. We identified the drug-resistance-associated SNVs by comparing the genomes of MTB isolates with reference genomes using the MuMmer4 tool.

Results: We observed a strikingly high proportion (94.2%) of MTB isolates resistant to ofloxacin, underscoring the current prevalence of drug resistance in MTB. An average of 3529 SNVs were detected in a single ofloxacin-resistant isolate, indicating a mutation rate of approximately 0.08% under the selective pressure of ofloxacin exposure. We identified a set of 60 SNVs associated with extensively drug-resistant tuberculosis (XDR-TB), among which 42 SNVs were non-synonymous mutations located in the coding regions of nine key genes (ctpI, desA3, mce1R, moeB1, ndhA, PE_PGRS4, PPE18, rpsA, secF). Protein structure modeling revealed that SNVs of three genes (PE_PGRS4, desA3, secF) are close to the critical catalytic active sites in the three-dimensional structure of the coding proteins.

Conclusion: This comprehensive study elucidates novel resistance mechanisms in MTB against antibiotics, paving the way for future design and development of anti-tuberculosis drugs.

Keywords: Mycobacterium tuberculosis; Single nucleotide variant; Whole-genome sequencing.

MeSH terms

Antitubercular Agents / pharmacology
Bacterial Proteins / genetics
Drug Resistance, Bacterial / genetics
Genome, Bacterial
Humans
Microbial Sensitivity Tests
Mutation
Mycobacterium tuberculosis* / drug effects
Mycobacterium tuberculosis* / genetics
Polymorphism, Single Nucleotide*
Whole Genome Sequencing*

Grants and funding

61903107/National Natural Science Foundation of China