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First insight of characteristics and prediction of Mycobacterium tuberculosis drug resistance by whole genome sequencing in Fujian Province, China
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  • Published: 16 February 2026

First insight of characteristics and prediction of Mycobacterium tuberculosis drug resistance by whole genome sequencing in Fujian Province, China

  • Shuzhen Wei1 na1,
  • Yong Zhao2 na1,
  • Jian Lin2,
  • Shufang Lin1,
  • Zhisong Dai1,
  • Yongming Lin2 &
  • …
  • Yanqin Deng1 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Diseases
  • Genetics
  • Microbiology

Abstract

To delineate the molecular characteristics and assess the drug resistance prediction value of whole-genome sequencing (WGS) for Mycobacterium tuberculosis (MTB) in Fujian Province, China. Representative MTB surveillance isolates underwent phenotypic drug susceptibility testing (pDST), followed by WGS(gDST), with resistance mutation analysis conducted on the SAM-TB platform. The rate of mono-resistance, poly-resistance, and multidrug-resistance (MDR) identified by pDST were 38.67%, 12.00% and 10.00% respectively. Lineage analysis revealed that L2 (60.0%) and L4 (38.7%) predominated. No statistically significant difference in drug-resistance rates among lineages (χ² = 4.85, P = 0.183). Total drug resistance rate by gDST was 67.03%, harboring 126 resistance-associated mutations. The most frequent mutations were KatG S315T (22.22%), rpoB S450L (10.32%), rpsL K43R (12.70%), embB M306I (4.76%), and gyrA D94G (7.94%). Using pDST as the reference standard, the sensitivity, specificity and concordance rate of gDST to RFP, INH, FQs, EMB, SM was 78.95%, 78.05%, 76.47%, 53.85%, 45.71%, and 98.47%, 94.50%, 93.98%, 97.08%, 95.65%, and 0.81, 0.74, 0.64, 0.55, 0.48, respectively. WGS provided rapid, comprehensive genotyping of MTB isolates, revealing the predominant lineages L2 and L4 in Fujian Province and reliably predicting resistance to RFP, INH, and FQ.

Data availability

The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive in National Genomics Data Center, China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences (CRA029438) that are publicly accessible at https:// ngdc. cncb. ac. cn/ gsa. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Global tuberculosis report 2024. Licence: CC BY-NC-SA 3.0 IGO (World Health Organization, 2024).

  2. Danica Helb, M. et al. Rapid detection of Mycobacterium tuberculosis and Rifampin resistance by use of on-demand, near-patient technology. J. Clin. Microbiol. 48, 229–237. https://doi.org/10.1128/JCM.01463-09 (2010).

    Google Scholar 

  3. Hillemann, D., Rüsch-Gerdes, S. & Richter, E. Feasibility of the genotype MTBDRsl assay for fluoroquinolone, amikacin-capreomycin, and ethambutol resistance testing of Mycobacterium tuberculosis strains and clinical specimens. J. Clin. Microbiol. 47, 1767–1772. https://doi.org/10.1128/JCM.00081-09 (2009).

    Google Scholar 

  4. Wang, J. et al. Analysis of Drug-Resistance characteristics and genetic diversity of Multidrug-Resistant tuberculosis based on Whole-Genome sequencing on the Hainan Island, China[J]. Infect. Drug Resist. 16, 5783–5798. https://doi.org/10.2147/IDR.S423955 (2023).

    Google Scholar 

  5. Wang, Z. & Sun, R. Characterization of Fluoroquinolone-Resistant and Multidrug-Resistant Mycobacterium tuberculosis isolates using Whole-Genome sequencing in Tianjin, China[J]. Infect. Drug Resist. 15, 1793–1803. https://doi.org/10.2147/IDR.S361635 (2022).

    Google Scholar 

  6. Chen, X. et al. Evaluation of Whole-Genome sequence method to diagnose resistance of 13 Anti-tuberculosis drugs and characterize resistance genes in clinical Multi-Drug resistance Mycobacterium tuberculosis isolates from China. Front. Microbiol. 10, 1–10. https://doi.org/10.3389/fmicb.2019.01741 (2019).

    Google Scholar 

  7. Zhao, Y. et al. National survey of drug-resistant tuberculosis in China. N Engl. J. Med. 366 (23), 2161–2170. https://doi.org/10.1056/NEJMoa1108789 (2012).

    Google Scholar 

  8. Pang, Y. et al. Spoligotyping and drug resistance analysis of Mycobacterium tuberculosis strains from National survey in China. PLoS One. 7 (3), e32976. https://doi.org/10.1371/journal.pone.0032976 (2012).

    Google Scholar 

  9. Shufang Lin, S. et al. The emergence of novel spoligotypes of highly Drug-Resistant Mycobacterium tuberculosis isolates in Fujian, China. Infect. Drug Resist. 155781–155793. https://doi.org/10.2147/IDR.S380950 (2022).

  10. Somerville, W. et al. Extraction of Mycobacterium tuberculosis dna:a questionof containment. J. Clin. Microbiol. 43 (6), 2996–2997. https://doi.org/10.1128/JCM.43.6.2996-2997.2005 (2005).

    Google Scholar 

  11. Bjorn-Mortensen, K. et al. Direct DNA extraction from Mycobacterium tuberculosis frozen stocks as a Reculture-Independent approach to Whole-Genome sequencing. J. Clin. Microbiol. 53 (8), 2716–2719. https://doi.org/10.1128/JCM.00662-15 (2015).

    Google Scholar 

  12. Jiang, Q. et al. Citywide transmission of multidrug-resistant tuberculosis under china’s rapid urbanization: a retrospective population-based genomic Spatial epidemiological study. Clin. Infect. Dis. 71, 142–151. https://doi.org/10.1093/cid/ciz790 (2020).

    Google Scholar 

  13. Yang, T. et al. SAM-TB: a whole genome sequencing data analysis website for detection of Mycobacterium tuberculosis drug resistance and transmission. Brief. Bioinform, 23:bbac030. doi: https://doi.org/10.1093/bib/bbac030. (2022).

  14. LiLi Zhao, H. C. Beijing genotype of Mycobacterium tuberculosis is less associated with drug resistance in South China. Int. J. Antimicrob. Agents. 54 (6), 766–770. https://doi.org/10.1016/j.ijantimicag.2019.08.005 (2019).

    Google Scholar 

  15. Zhang, H. et al. Characteristics and trend of Drug-Resistant tuberculosis at a major specialized hospital in Chongqing,China:2016 versus 2019. Disaster Med. Public. 17, e169. https://doi.org/10.1017/dmp.2022.88 (2022).

    Google Scholar 

  16. Tania, T. et al. Whole-genome sequencing analysis of multidrug-resistant Mycobacterium tuberculosis from Java, Indonesia. J. Med. Microbiol. 69 (7), 1013–1019. https://doi.org/10.1099/jmm.0.001221 (2020).

    Google Scholar 

  17. Du, J. et al. Distinguishing relapse from reinfection with Whole-Genome sequencing in recurrent pulmonary tuberculosis: A retrospective cohort study in Beijing, China[J]. Front. Microbiol. 12, 1–12. https://doi.org/10.3389/fmicb.2021.754352 (2021).

    Google Scholar 

  18. YuXin, X. & WanHsuan, K. H. L. Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan. Sci. Rep. 13, 2540. https://doi.org/10.1038/s41598-023-29652-3 (2023).

    Google Scholar 

  19. Stucki, D. et al. Mycobacterium tuberculosis lineage 4 comprises globally distributed and geographically restricted sublineages. Nat. Genet. 2016, 48, 1535–1543. https://doi.org/10.1038/ng.3704

  20. Netikul, T. et al. Estimation of the global burden of Mycobacterium tuberculosis lineage 1. Infect. Genet. Evol. 91, 104802. https://doi.org/10.1016/j.meegid.2021.104802 (2021).

    Google Scholar 

  21. Mariko Hakamata1 et al. Higher genome mutation rates of Beijing lineage of Mycobacterium tuberculosis during human infection. Sci. Rep. 10, 17997. https://doi.org/10.1038/s41598-020-75028-2 (2020).

    Google Scholar 

  22. Cryptic consortium and the 100 000-Genomes. -ProjecAllix-Béguec-C-Arandjelovic-I-Bi-Letl. Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing[J]. N. Engl. J. Med., 379(15): 1403–1415. doi: https://doi.org/10.1056/NEJMoa1800474. (2018).

  23. Catalogue of mutations in Mycobacterium tuberculosis complex and their association with drug resistance, second edition. Geneva: World Health Organization. Licence: CC BY-NC-SA 3.0 IGO. (2023).

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Funding

This study was sponsored by the Fujian Provincial Science and Technology Program (2022Y0048, 2023Y0044) and Fujian Provincial Health Technology Project (2023CXA031). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Author notes
  1. Shuzhen Wei and Yong Zhao contributed equally to this work.

Authors and Affiliations

  1. Fujian Key Laboratory of Zoonosis Research, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China

    Shuzhen Wei, Shufang Lin, Zhisong Dai & Yanqin Deng

  2. Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China

    Yong Zhao, Jian Lin & Yongming Lin

Authors
  1. Shuzhen Wei
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  2. Yong Zhao
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  3. Jian Lin
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  4. Shufang Lin
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  7. Yanqin Deng
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Contributions

Y.D. and Y.L. are the Corresponding Authors, and designed and supervised the study. S.W. and Y.Z. are the performers of this study, responsible for collecting information, conducting experiments and data analysis, preparing tables and figure, and drafting the manuscript. J.L. was participated in experiments, and data analysis. S.L., Z.D., and Y.L all participated in coordinating and managing the operations of TB drug resistance surveillance sites. Y.D. and Y.L. provided financial support. All authors reviewed and approved the manuscript.

Corresponding authors

Correspondence to Yongming Lin or Yanqin Deng.

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The authors declare no competing interests.

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The authors declare that they have no conflicts of interest.

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Cite this article

Wei, S., Zhao, Y., Lin, J. et al. First insight of characteristics and prediction of Mycobacterium tuberculosis drug resistance by whole genome sequencing in Fujian Province, China. Sci Rep (2026). https://doi.org/10.1038/s41598-026-40398-6

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  • Received: 20 August 2025

  • Accepted: 12 February 2026

  • Published: 16 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-40398-6

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