Elvin Maharramov

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.

Gene loss is common, yet whether it is merely an evolutionary dead-end or can promote future adaptation to new environments remains debated. Here, we systematically tested whether harmful loss of metabolic genes, followed by compensatory evolution, generates preadaptations to alternative nutrients in Escherichia coli. Our analysis revealed a striking outcome beyond simple growth restoration, where repair of a genetic defect yielded growth exceeding the unperturbed wild type on carbon sources not encountered during evolution. Such latent growth gains occurred across multiple deletion backgrounds and carbon sources, with growth rate increases up to 46% relative to the wild type. In some cases, the corresponding ancestral deletion strain failed to grow on these carbon sources, indicating functional innovations relative to the deletion ancestor. Genetic reconstruction and transcriptomic profiling implicate regulatory reprogramming, particularly in carbon catabolite repression and nutrient uptake, as mechanisms underlying latent growth gains. In conclusion, evolutionary recovery from gene loss can rapidly produce preadaptations to future environments in the absence of direct selection.

Antibiotics that target multiple cellular functions are thought to be less susceptible to bacterial resistance. This thesis demonstrates that while dual-targeting strategies are essential, they are insufficient to prevent resistance. Instead, antibiotics that concurrently disrupt membrane integrity and inhibit an additional cellular pathway significantly reduce the development of resistance in Gram-negative ESKAPE pathogens, including Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa. To test the hypothesis, we focused on three antibiotic candidates, POL7306, Tridecaptin M152-P3, and SCH79797, all of which meet the above criteria, and evaluated several factors that could limit the evolution of resistance. First, mutations arising de novo led to only marginal increases in resistance, with detailed functional analyses revealing that conventional resistance pathways were not readily accessible. Second, resistance through gene amplification was unreachable. Third, mobile genetic elements encoding resistance to these antibiotics were infrequent in human-associated microbiomes and clinically significant pathogens. Additionally, an exceptionally rapid eradication of bacterial populations was observed following exposure to membrane-targeting antibiotics at toxic concentrations. These findings suggest that naturally occurring resistance mechanisms in bacterial pathogens provide only limited protection against these antibiotics. These results offer critical insights and practical recommendations for designing next-generation antibiotics that are more resilient to resistance, ensuring long-term efficacy in combating multidrug-resistant pathogens.

Antibiotics that target multiple cellular functions are anticipated to be less prone to bacterial resistance. Here we hypothesize that while dual targeting is crucial, it is not sufficient in preventing resistance. Only those antibiotics that simultaneously target membrane integrity and block another cellular pathway display reduced resistance development. To test the hypothesis, we focus on three antibiotic candidates, POL7306, Tridecaptin M152-P3 and SCH79797, all of which fulfill the above criteria. Here we show that resistance evolution against these antibiotics is limited in ESKAPE pathogens, including Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii and Pseudomonas aeruginosa, while dual-target topoisomerase antibiotics are prone to resistance. We discover several mechanisms restricting resistance. First, de novo mutations result in only a limited elevation in resistance, including those affecting the molecular targets and efflux pumps. Second, resistance is inaccessible through gene amplification. Third, functional metagenomics reveal that mobile resistance genes are rare in human gut, soil and clinical microbiomes. Finally, we detect rapid eradication of bacterial populations upon toxic exposure to membrane targeting antibiotics. We conclude that resistance mechanisms commonly found in natural bacterial pathogens provide only limited protection to these antibiotics. Our work provides guidelines for the future development of antibiotics.

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.