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Biology subjects

Lina, G.

Publications and source records attributed to Lina, G..

2 recordsLinked to original sources

Mycobacterium tuberculosis micro-diversity promotes intra-macrophagic persistence and antibiotic tolerance

Mycobacterium tuberculosis (Mtb) genetic micro-diversity in clinical isolates may underline mycobacterial adaptive response during the course of tuberculosis (TB) and provide insights to anti-TB treatment response and emergence of resistance. Herein we followed within-host evolution of Mtb clinical isolates in a cohort of patients with delayed Mtb culture conversion. We captured the genetic diversity of both the initial and the last Mtb isolate obtained in each patient, by focusing on minor variants detected as unfixed single nucleotide polymorphisms (SNPs). To unmask antibiotic tolerant sub-populations, we exposed the last Mtb isolate to rifampicin (RIF) prior to whole genome sequencing analysis. We were able to detect unfixed SNPs within the Mtb isolates for 9/12 patients, and non-synonymous (ns) SNPs in 6/12 patients. Furthermore, RIF exposure revealed 8 additional unfixed nsSNP unlinked to drug resistance. To better understand the dynamics of Mtb micro-diversity during the course of TB, we investigated the variant composition of a persistent Mtb clinical isolate before and after controlled stress experiments chosen to mimic 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 and which may be able 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. Author summaryTuberculosis (TB) is caused by Mycobacterium tuberculosis (Mtb), bacteria that are able to persist inside the patient for many months or years, thus requiring long antibiotic treatments. Here we focused on TB patients with delayed response to treatment and we performed genetic characterization of Mtb isolates to search for sub-populations that may tolerate anti-TB drugs. We found that Mtb cultured from 9/12 patients contained different sub-populations, and in vitro drug exposure revealed 8 other sub-populations, none related to known drug-resistance mechanisms. Furthermore, we characterized a Mtb variant isolated from a sub-population growing in the presence of rifampicin (RIF), a major anti-TB drug. We found that this variant featured a modified lipidic envelope, and that it was able to develop in the presence of RIF and inside human macrophage cells. We performed pharmacological modelling and found that this kind of variant may be related to a poor response to treatment. In conclusion, searching for particular Mtb sub-populations may help to detect patients at risk of treatment failure and provide additional guidance for TB management.

microbiology

Metapopulation ecology links antibiotic resistance, consumption and patient transfers in a network of hospital wards

Antimicrobial resistance (AMR) is a global threat. A better understanding of how antibiotic use and between ward patient transfers (or connectivity) impact hospital AMR can help optimize antibiotic stewardship and infection control strategies. Here, we used metapopulation ecology to explain variations in infection incidences of 17 ESKAPE pathogen variants in a network of 357 hospital wards. Multivariate models identified the strongest influence of ward-level antibiotic use on more resistant variants, and of connectivity on nosocomial species and carbapenem-resistant variants. Pairwise associations between infection incidence and the consumption of specific antibiotics were significantly stronger when such associations represented a priori AMR selection, suggesting that AMR evolves within the network. Piperacillin-tazobactam consumption was the strongest predictor of the cumulative incidence of infections resistant to empirical sepsis therapy. Our data establish that both antibiotic use and connectivity measurably influence hospital AMR and provide a ranking of key antibiotics by their impact on AMR.

ecology