Abstract
Mycobacterium tuberculosis (Mtb) genetic micro-diversity in clinical isolates may underline mycobacterial adaptation to tuberculosis (TB) infection and provide insights to anti-TB treatment response and emergence of resistance. Herein we followed within-host evolution of Mtb clinical isolates in two cohorts of TB patients, either with delayed Mtb culture conversion (> 2 months), or with fast culture conversion (< 2 months). We captured the genetic diversity of Mtb isolates obtained in each patient, by focusing on minor variants detected as unfixed single nucleotide polymorphisms (SNPs). To unmask antibiotic tolerant sub-populations, we exposed these isolates to rifampicin (RIF) prior to whole genome sequencing (WGS) analysis. Thanks to WGS, we detected at least 1 unfixed SNP within the Mtb isolates for 9/15 patients with delayed culture conversion, and non-synonymous (ns) SNPs for 8/15 patients. Furthermore, RIF exposure revealed 9 additional unfixed nsSNP from 6/15 isolates unlinked to drug resistance. By contrast, in the fast culture conversion cohort, RIF exposure only revealed 2 unfixed nsSNP from 2/20 patients. To better understand the dynamics of Mtb micro-diversity, we investigated the variant composition of a persistent Mtb clinical isolate before and after controlled stress experiments mimicking the course of TB disease. A minor variant, featuring a particular mycocerosates profile, became enriched during both RIF exposure and macrophage infection. The variant was associated with drug tolerance and intracellular persistence, consistent with the pharmacological modeling predicting increased risk of treatment failure. A thorough study of such variants not necessarily linked to canonical drug-resistance, but which are prone to promote anti-TB drug tolerance, may be crucial to prevent the subsequent emergence of resistance. Taken together, the present findings support the further exploration of Mtb micro-diversity as a promising tool to detect patients at risk of poorly responding to anti-TB treatment, ultimately allowing improved and personalized TB management.