Clinically relevant mutations in core metabolic genes confer antibiotic resistance

The many roads to resistance Antibiotic resistance arising from mutation is common among pathogenic bacteria. However, this process is not well understood, and most of the mutations that have been identified to confer resistance do so by modification of the intracellular target or enzymes that can disable the antibacterial compound within the cell. Screening for the evolution of resistance at different temperatures, Lopatkin et al. found that mutations that affect microbial metabolism can result in antibiotic resistance (see the Perspective by Zampieri). These mutations targeted central carbon and energy metabolism and revealed novel resistance mutations in core metabolic genes, expanding the known means by which pathogenic microbes can evolve resistance. Science, this issue p. eaba0862; see also p. 783 In Escherichia coli, mutations in genes involved in central carbon and energy metabolism can lead to resistance to antibiotics. INTRODUCTION Despite the complexity of antibiotic lethality, canonical mechanisms of resistance are generally grouped into three broad categories: target modification, drug inactivation, and drug transport. Although metabolism has been shown to actively contribute to antibiotic lethality, antibiotic resistance mutations are infrequently identified in metabolic genes, and metabolic dysregulation is not a commonly cited mechanism of antibiotic resistance. One explanation is that previous approaches provide a limited view of the antibiotic resistance landscape. Indeed, laboratory evolutions paired with sequencing candidate genes and/or a small number of clonal isolates per condition highlight mutations that are either expected, or repeatedly occur, at high frequency. Moreover, antibiotic-mediated effects on bacterial metabolism involve numerous, complex, and coordinated biomolecular networks, which makes it challenging to predict candidates of likely resistance a priori. Additionally, the diversity of involved pathways increases the number of possible evolutionary outcomes, which reduces the likelihood for convergent mutations, and thus would be readily missed using previous methods. As a result, genetic mechanisms of antibiotic resistance related to metabolism are significantly understudied. RATIONALE The importance of population-level analyses for understanding the evolutionary landscape in response to drug treatment is becoming increasingly recognized. Low-frequency mutants make up most genetic diversity within a population, and in many cases, beneficial mutations may drift to extinction before becoming established. This is particularly relevant for genes involved in cellular metabolism, in which the diverse array of metabolic pathways can lead to a myriad of potential evolutionary outcomes compared with canonical drug targets. As such, we sought to use a more comprehensive view afforded by both population and clonal analyses to elucidate metabolic aspects of antibiotic resistance. Moreover, considering these constraints, typical laboratory evolution protocols and their analysis methods are not optimized to detect mutations in metabolism-related genes. Constant antibiotic exposure imposes growth-dependent selection, and a lack of metabolic-specific selection pressure further minimizes the likelihood of enriching for metabolic-specific pathways and processes. Thus, we reasoned that maximizing metabolic rather than growth adaptation would allow us to shift these dynamics and further tease out antibiotic-specific metabolic variants. RESULTS We sequenced and analyzed Escherichia coli adapted to three representative antibiotics at increasingly heightened metabolic states. Doing so revealed a variety of underappreciated noncanonical genes, such as those related to central carbon and energy metabolism, which are implicated in antibiotic resistance. These mutations in metabolic genes often arose in multiple independent populations and/or in response to more than one drug. Several of the identified metabolism-specific mutations are overrepresented in the genomes of >3500 clinical E. coli pathogens at levels similar to, and in some cases greater than, known resistance mutations indicating their clinical relevance. To evaluate whether these metabolic mutations confer resistance, we chose a representative subset of both genes related to metabolism and classic resistance on the basis of their prevalence and clinical significance. We expressed the wild-type and mutant variants of each gene from a medium-copy plasmid introduced into the corresponding chromosomal knockout strain. In all cases, metabolic mutations increased the minimum inhibitory concentration to at least one, and in many cases more than one, of the antibiotics. Finally, phenotypic and genotypic analyses of one representative mutation in the 2-oxoglutarate dehydrogenase (sucA) enzyme provides a preliminary picture of how altered metabolism gives rise to antibiotic resistance: Lower basal respiration prevents antibiotic-mediated induction of tricarboxylic acid cycle activity, thereby avoiding metabolic toxicity and minimizing lethality. CONCLUSION Our findings that metabolic mutations arise in response to antibiotic treatment, and that these mutations confer resistance and are highly prevalent in clinical pathogens, suggests that the three general antibiotic resistance categories may not be as representative, nor the mechanisms as comprehensive, as previously thought. Indeed, metabolic adaptation may represent a separate class of resistance mechanisms beyond conferring tolerance, whereby cells also alter their metabolic response to mitigate downstream toxic aspects of antibiotic lethality. Altered metabolic state confers antibiotic resistance. Cells were exposed to high antibiotic concentrations (red) for short durations under incrementally increasing metabolic states (blue), separated by rounds of drug-free growth (small flasks). Left to right indicates evolutionary time. Initially, antibiotic-mediated metabolic stimulation partially contributes to cell lethality (sensitive cell). Evolved cells acquire resistance caused by decreased basal metabolic activity that avoids antibiotic-mediated stimulation and subsequent lethality (resistant cell). Although metabolism plays an active role in antibiotic lethality, antibiotic resistance is generally associated with drug target modification, enzymatic inactivation, and/or transport rather than metabolic processes. Evolution experiments of Escherichia coli rely on growth-dependent selection, which may provide a limited view of the antibiotic resistance landscape. We sequenced and analyzed E. coli adapted to representative antibiotics at increasingly heightened metabolic states. This revealed various underappreciated noncanonical genes, such as those related to central carbon and energy metabolism, which are implicated in antibiotic resistance. These metabolic alterations lead to lower basal respiration, which prevents antibiotic-mediated induction of tricarboxylic acid cycle activity, thus avoiding metabolic toxicity and minimizing drug lethality. Several of the identified metabolism-specific mutations are overrepresented in the genomes of >3500 clinical E. coli pathogens, indicating clinical relevance.