Márton Simon Czikkely

Several new antibiotics target multidrug-resistant pathogens, yet resistance is still evaluated mainly by drug-susceptibility, leaving consequences for bacterial pathogenicity poorly understood. Here, we develop a framework integrating resistance evolution, genomic surveillance and host–pathogen phenotyping to classify antibiotics by resistance potential and pathogenic consequences. Applying this framework to Klebsiella pneumoniae identified functionally distinct antibiotic candidates associated with elevated virulence risk. Resistance evolution rapidly increased virulence through clinically-relevant mutations, without direct selection for pathogenicity. Despite distinct genetic routes, resistance converged on cell-envelope rewiring. A single resistance mutation increased epithelial adhesion, intracellular colonization, macrophage immune-evasion, and tissue persistence in murine infection models, transforming K. pneumoniae into a more invasive and cytotoxic pathogen. Risk-profile analysis revealed partial decoupling of resistance and pathogenicity, with some low-resistance antibiotics yielding highly-virulent populations. These findings establish resistance-driven virulence as an underappreciated translational hazard and call for incorporating host–pathogen interactions into resistance surveillance and preclinical antibiotic development.

Despite ongoing antibiotic development, evolution of resistance may render candidate antibiotics ineffective. Here we studied in vitro emergence of resistance to 13 antibiotics introduced after 2017 or currently in development, compared with in-use antibiotics. Laboratory evolution showed that clinically relevant resistance arises within 60 days of antibiotic exposure in Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii and Pseudomonas aeruginosa, priority Gram-negative ESKAPE pathogens. Resistance mutations are already present in natural populations of pathogens, indicating that resistance in nature can emerge through selection of pre-existing bacterial variants. Functional metagenomics showed that mobile resistance genes to antibiotic candidates are prevalent in clinical bacterial isolates, soil and human gut microbiomes. Overall, antibiotic candidates show similar susceptibility to resistance development as antibiotics currently in use, and the corresponding resistance mechanisms overlap. However, certain combinations of antibiotics and bacterial strains were less prone to developing resistance, revealing potential narrow-spectrum antibacterial therapies that could remain effective. Finally, we develop criteria to guide efforts in developing effective antibiotic candidates.

Several antibiotic candidates are in development against Gram-positive bacterial pathogens, but their long-term utility is unclear. To investigate this issue, we studied the laboratory evolution of resistance to antibiotics that have not yet reached the market. We found that, with the exception of compound SCH79797, antibiotic resistance generally readily evolves in Staphylococcus aureus . Cross-resistance was detected between such candidates and antibiotics currently in clinical use, including vancomycin, daptomycin, and the promising antibiotic candidate teixobactin. These patterns were driven by overlapping molecular mechanisms through mutations in regulatory systems. In particular, teixobactin-resistant bacteria displayed clinically relevant multidrug resistance and retained their virulence in an invertebrate infection model, raising concerns. More generally, we demonstrate that putative resistance mutations against candidate antibiotics are already present in natural bacterial populations. Therefore, antibiotic resistance in nature may evolve readily from the selection of preexisting genetic variants. Our work highlights the importance of predicting future evolution of resistance to antibiotic candidates at an early stage of drug development.

Despite the ongoing development of new antibiotics, the future evolution of bacterial resistance may render them ineffective. We demonstrate that antibiotic candidates currently under development are as prone to resistance evolution in Gram-negative pathogens as clinically employed antibiotics. Resistance generally stems from both genomic mutations and the transfer of antibiotic resistance genes from microbiomes associated with humans, both factors carrying equal significance. The molecular mechanisms of resistance overlap with those found in commonly used antibiotics. Therefore, these mechanisms are already present in natural populations of pathogens, indicating that resistance can rapidly emerge through selection of pre-existing bacterial variants. However, certain combinations of antibiotics and bacterial strains are less prone to developing resistance, emphasizing the potential of narrow-spectrum antibacterial therapies that could remain effective. Our comprehensive framework allows for predicting future health risks associated with bacterial resistance to new antibiotics.