Whole genome sequencing for predicting clarithromycin resistance in .

Lipworth, Samuel, Hough, Natasha, Leach, Laura, Morgan, Marcus, Jeffery, Katie, Andersson, Monique, Robinson, Esther, Smith, E Grace, Crook, Derrick, Peto, Tim and Walker, Timothy (2018) Whole genome sequencing for predicting clarithromycin resistance in . Antimicrobial agents and chemotherapy. ISSN 1098-6596.

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Official URL: https://aac.asm.org/content/early/2018/10/31/AAC.0...


is emerging as an important pathogen in chronic lung diseases with concern regarding patient to patient transmission. The recent introduction of routine whole genome sequencing (WGS) as a replacement for existing reference techniques in England provides an opportunity to characterise the genetic determinants of resistance. We conducted a systematic review to catalogue all known resistance determining mutations. This knowledge was used to construct a predictive algorithm based on mutations in the and genes which was tested on a collection of 203 sequentially acquired clinical isolates for which there was paired genotype/phenotype data. A search for novel resistance determining mutations was conducted using an heuristic algorithm.The sensitivity of existing knowledge for predicting resistance in clarithromycin was 95% (95% CI 89 - 98%) and the specificity was 66% (95% CI 54 - 76%). Subspecies alone was a poor predictor of resistance to clarithromycin. Eight potential new resistance conferring SNPs were identified. WGS demonstrates probable resistance determining SNPs in regions the NTM-DR line probe cannot detect. These mutations are potentially clinically important as they all occurred in samples predicted to be inducibly resistant, and for which a macrolide would therefore currently be indicated. We were unable to explain all resistance, raising the possibility of the involvement of other as yet unidentified genes.

Item Type: Article
Subjects: QW Microbiology. Immunology
Divisions: Clinical Support > Pathology
Related URLs:
Depositing User: Mrs Yolande Brookes
Date Deposited: 09 Nov 2018 15:09
Last Modified: 09 Nov 2018 15:09
URI: http://www.repository.uhblibrary.co.uk/id/eprint/1777

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