Comparative fitness analysis of D-cycloserine resistant mutants reveals both fitness-neutral and high-fitness cost genotypes

Evangelopoulos, D, Prosser, GA, Rodgers, A, Dagg, BM, Khatri, B, Ho, MM, Gutierrez, MG and Cortes, T. 2019. Comparative fitness analysis of D-cycloserine resistant mutants reveals both fitness-neutral and high-fitness cost genotypes. [Online]. Nature Communications. Available from: https://doi.org/10.1038/s41467-019-12074-z

Evangelopoulos, D, Prosser, GA, Rodgers, A, Dagg, BM, Khatri, B, Ho, MM, Gutierrez, MG and Cortes, T. Comparative fitness analysis of D-cycloserine resistant mutants reveals both fitness-neutral and high-fitness cost genotypes [Internet]. Nature Communications; 2019. Available from: https://doi.org/10.1038/s41467-019-12074-z

Evangelopoulos, D, Prosser, GA, Rodgers, A, Dagg, BM, Khatri, B, Ho, MM, Gutierrez, MG and Cortes, T (2019). Comparative fitness analysis of D-cycloserine resistant mutants reveals both fitness-neutral and high-fitness cost genotypes. [Data Collection]. Nature Communications. https://doi.org/10.1038/s41467-019-12074-z

Description

Drug resistant infections represent one of the most challenging medical problems of our time. D-cycloserine is an antibiotic used for six decades without significant appearance and dissemination of antibiotic resistant strains, making it an ideal model compound to understand what drives resistance evasion. We therefore investigated why Mycobacterium tuberculosis fails to become resistant to D-cycloserine. To address this question, we employed a combination of bacterial genetics, genomics, biochemistry and fitness analysis in vitro, in macrophages and in mice. Altogether, our results suggest that the ultra-low rate of emergence of D-cycloserine resistance mutations is the dominant biological factor delaying the appearance of clinical resistance to this antibiotic. Furthermore, we also identified potential compensatory mechanisms able to minimize the severe fitness costs of primary D-cycloserine resistance conferring mutations.

Methods

Data capture method	Experiment
Date (Date published in a 3rd party system)	13 September 2019
Language(s) of written materials	English

People & Groups

Data Creators	Evangelopoulos, D, Prosser, GA, Rodgers, A, Dagg, BM, Khatri, B, Ho, MM, Gutierrez, MG and Cortes, T
LSHTM Faculty/Department	Faculty of Infectious and Tropical Diseases
Participating Institutions	London School of Hygiene & Tropical Medicine