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Whole genome sequencing and prediction of antimicrobial susceptibilities in non-tuberculous mycobacteria.
Solanki, Priya; Lipman, Marc; McHugh, Timothy D; Satta, Giovanni.
Affiliation
  • Solanki P; UCL-TB and UCL Centre for Clinical Microbiology, University College London, London, United Kingdom.
  • Lipman M; UCL-TB and UCL Respiratory, University College London, London, United Kingdom.
  • McHugh TD; Royal Free London NHS Foundation Trust, London, United Kingdom.
  • Satta G; UCL-TB and UCL Centre for Clinical Microbiology, University College London, London, United Kingdom.
Front Microbiol ; 13: 1044515, 2022.
Article in En | MEDLINE | ID: mdl-36523832
ABSTRACT
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.
Key words

Full text: 1 Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Microbiol Year: 2022 Type: Article Affiliation country: United kingdom

Full text: 1 Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Microbiol Year: 2022 Type: Article Affiliation country: United kingdom