Evidence map›Paper›PMID 40596923›Full record

ArticleBMC infectious diseases2025

Nanopore-based targeted sequencing (NTS) for drug-resistant tuberculosis: an integrated tool for personalized treatment strategies and guidance for new drug development.

Chen Yang, Guangchuan Dai, Yicheng Guo, Tianzhen Wang, Weiwei Gao, Yi Zeng

Abstract read
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Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. A Comprehensive Review of Genetic Mechanisms ofInfection and drug resistance · 2026
    Review
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Chen Yang *Department of Tuberculosis, The Second Hospital of Nanjing, Nanjing, 211100, China.
Guangchuan Dai *Department of Tuberculosis, The Second Hospital of Nanjing, Nanjing, 211100, China.
Yicheng GuoDepartment of Tuberculosis, The Second Hospital of Nanjing, The School of Public Health of Nanjing Medical University, Nanjing, 211166, China.
Tianzhen WangDepartment of Tuberculosis, The Second Hospital of Nanjing, Nanjing, 211100, China.
Weiwei Gao *Department of Tuberculosis, The Second Hospital of Nanjing, Nanjing, 211100, China. weiweigao1106@163.com.
Yi Zeng *Department of Tuberculosis, The Second Hospital of Nanjing, Nanjing, 211100, China. 960559051@qq.com.

Funding

the Nanjing Health Science and Technology Development Special Fund M2021073
6 · The paper itself

Abstract

backgroundDrug-resistant tuberculosis has emerged as a major public health issue that requires immediate attention. NTS is an innovative method that allows for the direct detection of clinical samples without the need for culture. It could provide more accurate, reliable, and comprehensive information on drug resistance.

methodsWe collected clinical data retrospectively from patients suspected of having drug-resistant tuberculosis who visited the tuberculosis department at the Second Hospital of Nanjing in Jiangsu Province, China, from December 2023 to December 2024. The diagnostic efficiency of NTS for different types of drug-resistant tuberculosis and antimicrobial resistance was calculated. The relationship between resistance genes, mutated amino acids, and mutation sites was demonstrated.

resultsIn this study, a total of 107 patients with drug-resistant tuberculosis were included, comprising 43 cases of mono-drug resistant tuberculosis, 20 patients with poly-drug resistant tuberculosis, 22 cases of multidrug-resistant tuberculosis, 21 cases of pre-extensively drug-resistant tuberculosis and 1 case of extensively drug-resistant tuberculosis. The accuracy of NTS in diagnosing drug-resistant tuberculosis ranged from 42.9 to 93.0%. Except for second-line injectable drugs, NTS achieved a sensitivity of over 70% for other anti-tuberculosis drugs. Serine was identified as the most frequently mutated amino acid in both the rpoB gene (66.2%, 49/74) and the katG gene (86.3%, 44/51). Additionally, the most frequently mutated amino acids in the embB gene, rpsL gene, and gyrA gene were methionine (94.7%, 44/51), lysine (100%, 28/28), and aspartic acid (66.7%, 20/30), respectively.

conclusionNTS could effectively and precisely deliver comprehensive drug resistance results, assisting medical professionals to create more personalized treatment plans. Besides, it would encourage the development of new anti-tuberculosis drugs to broaden clinical treatment options for drug-resistant tuberculosis.

Indexed as

Antitubercular AgentsMycobacterium tuberculosisNanopore SequencingTuberculosis, Multidrug-ResistantAdultAgedBacterial ProteinsChinaDrug DevelopmentFemaleHumansMaleMiddle AgedMutationPrecision MedicineRetrospective StudiesAntitubercular AgentsBacterial ProteinsAmino acidsDrug-resistant genesDrug-resistant tuberculosis(DR-TB)Nanopore-based targeted sequencing(NTS)Targeted next-generation sequencing(tNGS)

Identifiers

PMID40596923
PMCPMC12220424

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.