Phylogenetically Informative Mutations in Drug Resistance Genes of Human-Infecting Mycobacterium bovis

IF 3.5 2区 农林科学 Q2 INFECTIOUS DISEASES
Yuhui Dong, Xichao Ou, Bing Zhao, Yuanzhi Wang, Yiduo Liu, Ziyi Liu, Haoran Wang, Xin Ge, Yue Nan, Yanlin Zhao, Xiangmei Zhou
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Abstract

The diagnosis of drug-resistant tuberculosis (TB) by molecular testing of Mycobacterium tuberculosis drug resistance genes is becoming increasingly common clinically. However, M. bovis, as an uncommon pathogen of human TB, may interfere with the test results. A comprehensive understanding of phylogenetically informative mutations in the drug resistance genes of M. bovis is required to distinguish true resistance-conferring mutations. We analyzed 53 drug resistance genes in 165 M. bovis isolated from humans using whole-genome sequencing data and found that 98.2% (162/165) of isolates have pyrazinamide intrinsic genotypic resistance, owing to the H57D mutation in the pncA gene. 12.1% (20/165) of M. bovis isolates were resistant to drugs other than pyrazinamide. Furthermore, we discovered 18 phylogenetically informative mutations that differed between M. bovis and the major lineages 1–4 of M. tuberculosis. Additionally, we reported false-positive ethambutol resistance caused by M. bovis infection due to the phylogenetically informative mutation embB E378A. This study is crucial for gaining insights into the genetic characterization and drug resistance of M. bovis prevalent in humans, as well as contributing to the development of more accurate molecular diagnostic methods and detection tools for drug resistance.

Abstract Image

人感染分枝杆菌耐药基因的系统发育信息突变
通过结核分枝杆菌耐药基因的分子检测诊断耐药结核病(TB)在临床上越来越常见。然而,牛分枝杆菌作为一种不常见的人类结核病病原体,可能会干扰检测结果。要区分真正的耐药性突变,就需要全面了解牛结核分枝杆菌耐药基因中具有系统发育信息的突变。我们利用全基因组测序数据分析了从人类分离的 165 株牛海绵状芽孢杆菌的 53 个耐药基因,发现 98.2%(162/165 株)的分离株具有吡嗪酰胺内在基因型耐药性,原因是 pncA 基因中的 H57D 突变。12.1%(20/165)的牛杆菌分离株对吡嗪酰胺以外的药物具有抗药性。此外,我们还发现了 18 个具有系统发育信息的突变,这些突变在牛海绵状芽孢杆菌和结核杆菌的主要 1-4 系之间存在差异。此外,我们还报告了由于系统发育信息突变embB E378A而导致的牛海绵状芽孢杆菌感染乙胺丁醇耐药性假阳性。这项研究对于深入了解流行于人类的牛结核杆菌的遗传特征和耐药性至关重要,同时也有助于开发更准确的分子诊断方法和耐药性检测工具。
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来源期刊
Transboundary and Emerging Diseases
Transboundary and Emerging Diseases 农林科学-传染病学
CiteScore
8.90
自引率
9.30%
发文量
350
审稿时长
1 months
期刊介绍: Transboundary and Emerging Diseases brings together in one place the latest research on infectious diseases considered to hold the greatest economic threat to animals and humans worldwide. The journal provides a venue for global research on their diagnosis, prevention and management, and for papers on public health, pathogenesis, epidemiology, statistical modeling, diagnostics, biosecurity issues, genomics, vaccine development and rapid communication of new outbreaks. Papers should include timely research approaches using state-of-the-art technologies. The editors encourage papers adopting a science-based approach on socio-economic and environmental factors influencing the management of the bio-security threat posed by these diseases, including risk analysis and disease spread modeling. Preference will be given to communications focusing on novel science-based approaches to controlling transboundary and emerging diseases. The following topics are generally considered out-of-scope, but decisions are made on a case-by-case basis (for example, studies on cryptic wildlife populations, and those on potential species extinctions): Pathogen discovery: a common pathogen newly recognised in a specific country, or a new pathogen or genetic sequence for which there is little context about — or insights regarding — its emergence or spread. Prevalence estimation surveys and risk factor studies based on survey (rather than longitudinal) methodology, except when such studies are unique. Surveys of knowledge, attitudes and practices are within scope. Diagnostic test development if not accompanied by robust sensitivity and specificity estimation from field studies. Studies focused only on laboratory methods in which relevance to disease emergence and spread is not obvious or can not be inferred (“pure research” type studies). Narrative literature reviews which do not generate new knowledge. Systematic and scoping reviews, and meta-analyses are within scope.
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