The rise of antimicrobial resistance (AMR) in bacterial pathogens is acknowledged by the WHO as a major global health crisis. It is estimated that in 2050 annually up to 10 million people will die from infections with drug resistant pathogens if no efficient countermeasures are implemented. Evolution of pathogens lies at the core of this crisis, which enables rapid adaptation to the selective pressures imposed by antimicrobial usage in both medical treatment and agriculture, consequently promoting the spread of resistance genes or alleles in bacterial populations. Approaches developed in the field of Evolutionary Medicine attempt to exploit evolutionary insight into these adaptive processes, with the aim to improve diagnostics and the sustainability of antimicrobial therapy. Here, we review the concept of evolutionary trade-offs in the development of AMR as well as new therapeutic approaches and their impact on host-microbiome-pathogen interactions. We further discuss the possible translation of evolution-informed treatments into clinical practice, considering both the rapid cure of the individual patients and the prevention of AMR.

Bedaquiline (BDQ) and clofazimine (CFZ) are core drugs for treatment of multidrug resistant tuberculosis (MDR-TB), however, our understanding of the resistance mechanisms for these drugs is sparse which is hampering rapid molecular diagnostics. To address this, we employed a unique approach using experimental evolution, protein modelling, genome sequencing, and minimum inhibitory concentration data (MIC) combined with genomes from a global strain collection of over 14,151 Mycobacterium tuberculosis complex isolates. Overall, 189 genomic variants causing elevated BDQ and/or CFZ MICs could be discerned, with 175 (95.1%) variants affecting the transcriptional repressor (Rv0678) of an efflux system (MmpS5-MmpL5). Structural modelling of Rv0678 suggests four major mechanisms that confer resistance: impairment of DNA binding, reduction in protein stability, disruption of protein dimerization, and reduction in affinity for its fatty acid ligand. These modelling and experimental techniques will improve personalized medicine in an impending drug resistant era.

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Pre-existing and newly emerging resistant pathogen subpopulations (hetero-resistance) are potential risk factors for treatment failure of multi/extensively drug resistant (MDR/XDR) tuberculosis (TB). Intra-patient evolutionary dynamics of Mycobacterium tuberculosis complex (Mtbc) strains and their implications on treatment outcomes are still not completely understood. Methods To elucidate how Mtbc strains escape therapy, we analysed 13 serial isolates by whole genome sequencing from a German patient. Sequencing data was compared to phenotypic drug susceptibility profiles, and the patient’s collective 27-year treatment history, to further elucidate factors fostering intra-patient resistance evolution. Results The patient endured five distinct TB episodes, ending in resistances to 16 drugs and a nearly untreatable XDR-TB infection. The first isolate obtained, during the patient’s 5th TB episode, presented fixed resistance mutations to seven anti-TB drugs including isoniazid, rifampicin, streptomycin, pyrazinamide, prothionamide, para-aminosalicyclic acid and cycloserin/terizidone. Over the next 13 years a dynamic evolution with co-existing, heterogeneous subpopulations was observed in six out of 13 sequential bacterial isolates. The emergence of drug-resistant subpopulations coincided with frequent changes in treatment regimens, which often included two or less active compounds. This evolutionary arms race between competing sub-populations, ultimately resulted in the fixation of a single XDR variant. Conclusion Our data demonstrates the complex intra-patient microevolution of Mtbc subpopulations during failing MDR/XDR-TB treatment. Designing effective treatment regimens based on rapid detection of (hetero-) resistance is key to avoid resistance development and treatment failure.