Literature DB >> 32303065

Bacterial population kinetics in heteroresistant Mycobacterium tuberculosis harbouring rare resistance-conferring mutations in gyrA and rpoB imply an epistatic interaction of mutations in a pre-XDR-TB patient.

Shiomi Yoshida1, Tomotada Iwamoto2, Kentaro Arikawa2, Tsuyoshi Sekizuka3, Makoto Kuroda3, Yoshikazu Inoue1, Satoshi Mitarai4, Taisuke Tsuji5, Kazunari Tsuyuguchi1, Katsuhiro Suzuki6.   

Abstract

OBJECTIVES: Bacterial population kinetics of strains harbouring drug resistance-conferring mutations within a patient often show cryptic resistance in clinical practice. We report a case that showed emergence and dominance of Mycobacterium tuberculosis with uncommon rpoB and gyrA mutations, followed by an rpoC compensatory mutation, during treatment.
METHODS: A pre-XDR-TB patient showed heteroresistance to rifampicin and levofloxacin during treatment as a result of intermittent self-cessation. WGS was applied to investigate intra-host strain composition using five pairs of isolates from sputum samples.
RESULTS: The subclone in this study possessed rare mutations conferring resistance to rifampicin (rpoB V170F) and levofloxacin (gyrA S91P) and it rapidly outcompeted other subclones during treatment that included levofloxacin but not rifampicin (<7 days). The high-probability compensatory mutation rpoC V483A also emerged and became dominant subsequent to the rpoB V170F mutation.
CONCLUSIONS: To the best of our knowledge, this is the first case showing the emergence of such a rare variant that dominated the population within a patient during treatment of TB.
© The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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Year:  2020        PMID: 32303065     DOI: 10.1093/jac/dkaa109

Source DB:  PubMed          Journal:  J Antimicrob Chemother        ISSN: 0305-7453            Impact factor:   5.790


  1 in total

1.  Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches.

Authors:  Stephanie Portelli; Yoochan Myung; Nicholas Furnham; Sundeep Chaitanya Vedithi; Douglas E V Pires; David B Ascher
Journal:  Sci Rep       Date:  2020-10-22       Impact factor: 4.379

  1 in total

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