Tuberculosis treatment failure associated with evolution of antibiotic resilience

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Abstract

The widespread use of antibiotics has placed bacterial pathogens under intense pressure to evolve new survival mechanisms. Genomic analysis of 51,229 Mycobacterium tuberculosis ( Mtb ) clinical isolates has identified an essential transcriptional regulator, Rv1830 , herein called resR for resilience regulator, as a frequent target of positive (adaptive) selection. resR mutants do not show canonical drug resistance or drug tolerance but instead shorten the post-antibiotic effect, meaning that they enable Mtb to resume growth after drug exposure substantially faster than wild-type strains. We refer to this phenotype as antibiotic resilience. ResR acts in a regulatory cascade with other transcription factors controlling cell growth and division, which are also under positive selection in clinical isolates of Mtb . Mutations of these genes are associated with treatment failure and the acquisition of canonical drug resistance.

Resilient in the long term

Tuberculosis caused by Mycobacterium tuberculosis is a persistent, sometimes lifelong infection that needs long courses of multiple antibiotics to treat. Not surprisingly, antibiotic resistance is rife. In a large sample of whole-genome data from clinical isolates, Liu et al . repeatedly observed an elongated phenotype showing rapid regrowth after typical regimens of antibiotic treatment. Signals of positive selection pointed to an essential transcriptional regulator (resR) and specific intergenic regions, which act in concert to regulate growth. Up to 10% of strains from high-tuberculosis-burden countries showed fixed mutations in these regions. Mutations across this cascade are associated with antibiotic treatment failure and are precursors to the emergence of classical antibiotic resistance. —CA

Abstract

Identifying the evolutionary signatures of adaptation to antibiotics in Mycobacterium tuberculosis reveals traits that enhance bacterial survival.

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Michael Love, Wolfgang Huber, Simon Anders (2014)

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Heng Li, Bob Handsaker, Alec Wysoker … (2009)

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Ben Langmead, Steven L Salzberg (2022)

As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.