Whole genome sequencing and prediction of antimicrobial susceptibilities in non-tuberculous mycobacteria.
Whole genome sequencing and prediction of antimicrobial susceptibilities in non-tuberculous mycobacteria.
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非结核分枝杆菌全基因组测序及抗菌药物敏感性预测
DOI：
10.3389/fmicb.2022.1044515
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发表时间：
2022
影响因子：
5.2
通讯作者：
Satta G
中科院分区：
文献类型：
--
作者：
Solanki P;Lipman M;McHugh TD;Satta G
非结核分枝杆菌（NTM）是机会致病菌，通常引起慢性肺部疾病，这是众所周知的难以治疗。目前对NTM感染的治疗涉及至少三种活性药物（包括一种大环内酯类药物：克拉霉素或阿奇霉素）12个月或更长时间。目前，全球标准化的NTM体外表型药敏试验选择有限。正如在结核病中看到的那样，通过利用基因型方法，全基因组测序有可能改变NTM的药敏试验。结核病综合耐药性预测是一个用于预测结核分枝杆菌耐药性的数据库：目前没有类似的数据库可用于准确预测NTM耐药性。最近的研究表明，表型和基因型NTM耐药结果是一致的。为了从全基因组测序的优势中获益，需要在耐药预测方面取得进一步进展，以及获得关于新型药物突变的更好信息，并了解全基因组测序对NTM治疗结果的影响。
Non-tuberculous mycobacteria (NTM) are opportunistic pathogens commonly causing chronic, pulmonary disease which is notoriously hard to treat. Current treatment for NTM infections involves at least three active drugs (including one macrolide: clarithromycin or azithromycin) over 12 months or longer. At present there are limited phenotypic in vitro drug susceptibility testing options for NTM which are standardised globally. As seen with tuberculosis, whole genome sequencing has the potential to transform drug susceptibility testing in NTM, by utilising a genotypic approach. The Comprehensive Resistance Prediction for Tuberculosis is a database used to predict Mycobacterium tuberculosis resistance: at present there are no similar databases available to accurately predict NTM resistance. Recent studies have shown concordance between phenotypic and genotypic NTM resistance results. To benefit from the advantages of whole genome sequencing, further advances in resistance prediction need to take place, as well as there being better information on novel drug mutations and an understanding of the impact of whole genome sequencing on NTM treatment outcomes.
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DOI：
10.3390/antibiotics10121515
发表时间：
2021-12-10
期刊：
Antibiotics (Basel, Switzerland)
影响因子：
--
作者：
Maitra A;Solanki P;Sadouki Z;McHugh TD;Kloprogge F
通讯作者：
Kloprogge F
影响因子：
4.9
作者：
Lefebvre, Anne-Laure;Le Moigne, Vincent;Mainardi, Jean-Luc
通讯作者：
Mainardi, Jean-Luc
影响因子：
4.9
作者：
Alangaden, GJ;Kreiswirth, BN;Lerner, SA
通讯作者：
Lerner, SA
影响因子：
4.5
作者：
Dohál M;Porvazník I;Solovič I;Mokrý J
通讯作者：
Mokrý J
影响因子：
3.7
作者：
Bouzinbi N;Marcy O;Bertolotti T;Chiron R;Bemer P;Pestel-Caron M;Peuchant O;Guet-Revillet H;Fangous MS;Héry-Arnaud G;Ouedraogo AS;Bañuls AL;Godreuil S
通讯作者：
Godreuil S