Emergence of phenotypic and genotypic antimicrobial resistance in Mycobacterium tuberculosis

• Published in: Scientific reports Vol. 12; no. 1; p. 21429
• Main Authors: Kloprogge, Frank, Ortiz Canseco, Julio, Phee, Lynette, Sadouki, Zahra, Kipper, Karin, Witney, Adam A., Stoker, Neil, McHugh, Timothy D.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 11-12-2022; Nature Publishing Group; Nature Portfolio
• Subjects: 692/308; 692/308/153; Anti-Bacterial Agents; Antibiotics; Antimicrobial agents; Antimicrobial resistance; Bacteria; Clinical trials; Drug development; Drug dosages; Drug resistance; Drug Resistance, Bacterial - genetics; Genotype; Granuloma; HIV; Human immunodeficiency virus; Humanities and Social Sciences; Infections; Isoniazid; Isoniazid - pharmacology; multidisciplinary; Mycobacterium tuberculosis - genetics; Pharmacodynamics; Rifampin; Rifampin - pharmacology; Science; Science (multidisciplinary); Tuberculosis
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-022-25827-6

Concentration dependency of phenotypic and genotypic isoniazid-rifampicin resistance emergence was investigated to obtain a mechanistic understanding on how anti-mycobacterial drugs facilitate the emergence of bacterial populations that survive throughout treatment. Using static kill curve experiments, observing two evolution cycles, it was demonstrated that rifampicin resistance was the result of non-specific mechanisms and not associated with accumulation of drug resistance encoding SNPs. Whereas, part of isoniazid resistance could be accounted for by accumulation of specific SNPs, which was concentration dependent. Using a Hollow Fibre Infection Model it was demonstrated that emergence of resistance did not occur at concentration–time profiles mimicking the granuloma. This study showed that disentangling and quantifying concentration dependent emergence of resistance provides an improved rational for drug and dose selection although further work to understand the underlying mechanisms is needed to improve the drug development pipeline.