The many paths to resistance
Resistance to antibiotics due to mutation is common among pathogenic bacteria. However, this process is not well understood, and most mutations that have been identified to confer resistance do so by modifying 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 resistance to antibiotics (see Zampieri’s Perspective). These mutations targeted central carbon and energy metabolism and revealed new resistance mutations in central metabolic genes, expanding the known means by which pathogenic microbes can develop resistance.
Science, this problem p. eaba0862; see also p. 783
Structured Summary
INTRODUCTION
Despite the complexity of the lethality of antibiotics, the canonical mechanisms of resistance are generally grouped into three major categories: modification of the target, inactivation of the medication and transport of the medication. Although metabolism has been shown to actively contribute to the lethality of antibiotics, mutations in antibiotic resistance are rarely identified in metabolic genes, and metabolic dysregulation is not a commonly cited mechanism of antibiotic resistance. One explanation is that the previous approaches provide a limited view of the antibiotic resistance landscape. In fact, laboratory developments paired with candidate sequencing genes and / or a small number of clonal isolates per condition highlight mutations that are expected or occur repeatedly at high frequency. In addition, the effects mediated by antibiotics on bacterial metabolism involve numerous, complex and coordinated biomolecular networks, which makes it a challenge to predict candidates of probable resistance a priori. In addition, the diversity of pathways involved increases the number of possible evolutionary results, which reduces the likelihood of convergent mutations and, therefore, would be easily lost using previous methods. As a result, the genetic mechanisms of resistance to antibiotics related to metabolism are significantly under-studied.
JUSTIFICATION
The importance of population-level analyzes for understanding the evolutionary scenario in response to drug treatment is becoming increasingly recognized. Low-frequency mutants constitute the majority of genetic diversity within a population and, in many cases, beneficial mutations can be driven to extinction before they establish themselves. This is particularly relevant for genes involved in cell metabolism, where the diversity of metabolic pathways can lead to a myriad of potential evolutionary results compared to canonical drug targets. As such, we seek to use a more comprehensive view provided by population and clonal analyzes to elucidate the metabolic aspects of antibiotic resistance. Furthermore, considering these restrictions, typical laboratory evolution protocols and their methods of analysis are not optimized to detect mutations in genes related to metabolism. Constant exposure to antibiotics imposes growth-dependent selection and a lack of specific metabolic selection pressure further minimizes the likelihood of enrichment for specific metabolic pathways and processes. Thus, we conclude that maximizing metabolic adaptation, instead of adaptation to growth, would allow us to change these dynamics and unravel the specific metabolic variants of antibiotics.
RESULTS
We sequence and analyze Escherichia coli adapted to three representative antibiotics in increasingly high metabolic states. This revealed a variety of underestimated non-canonical genes, such as those related to central carbon and energy metabolism, which are implicated in antibiotic resistance. These mutations in metabolic genes often appeared in multiple independent populations and / or in response to more than one drug. Several of the specific metabolism mutations identified are overrepresented in the genomes of> 3500 E. coli pathogens at levels similar to, and in some cases greater than, known resistance mutations, indicating their clinical relevance. To assess whether these metabolic mutations confer resistance, we chose a representative subset of both genes related to metabolism and classical resistance based on their prevalence and clinical significance. We expressed the wild-type and mutant variants of each gene of 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, antibiotics. Finally, phenotypic and genotypic analyzes of a representative mutation in the enzyme 2-oxoglutarate dehydrogenase (sucA) provide a preliminary picture of how altered metabolism gives rise to antibiotic resistance: Lower baseline breathing prevents antibiotic-mediated induction of cycle activity tricarboxylic acid, thus avoiding metabolic toxicity and minimizing lethality.
CONCLUSION
Our results that metabolic mutations arise in response to antibiotic treatment, and that these mutations confer resistance and are highly prevalent in clinical pathogens, suggest that the three general categories of antibiotic resistance may not be as representative, nor the mechanisms as comprehensive. , as previously thought. In fact, metabolic adaptation may represent a separate class of resistance mechanisms in addition to conferring tolerance, in which cells also alter their metabolic response to mitigate the toxic aspects downstream of the antibiotic’s lethality.
The cells were exposed to high concentrations of antibiotics (red) for short periods under incremental metabolic states (blue), separated by drug-free growth cycles (small vials). From left to right it indicates the evolutionary time. Initially, metabolic stimulation mediated by antibiotics partially contributes to cellular lethality (sensitive cell). The evolved cells acquire resistance caused by the decrease of the basal metabolic activity that avoids the stimulation mediated by antibiotics and subsequent lethality (resistant cell).
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The cells were exposed to high concentrations of antibiotics (red) for short periods under metabolic states of incremental increase (blue), separated by drug-free growth cycles (small vials). From left to right it indicates the evolutionary time. Initially, metabolic stimulation mediated by antibiotics partially contributes to cellular lethality (sensitive cell). The evolved cells acquire resistance caused by the decrease of the basal metabolic activity that avoids the stimulation mediated by antibiotics and subsequent lethality (resistant cell).
Summary
Although metabolism plays an active role in the lethality of antibiotics, antibiotic resistance is generally associated with modification of the drug target, enzyme inactivation and / or transport, rather than metabolic processes. Evolution experiments Escherichia coli depend on growth-dependent selection, which can provide a limited view of the antibiotic resistance scenario. We sequence and analyze E. coli adapted to representative antibiotics in increasingly intense metabolic states. This revealed several underestimated non-canonical genes, such as those related to central carbon and energy metabolism, which are implicated in antibiotic resistance. These metabolic changes lead to decreased baseline breathing, which prevents antibiotic-mediated induction of antibiotic-mediated tricarboxylic acid activity, avoiding metabolic toxicity and minimizing drug lethality. Several of the specific metabolism mutations identified are overrepresented in the genomes of> 3500 E. coli pathogens, indicating clinical relevance.