[ad_1]
The many paths of resistance
Resistance to antibiotics resulting from a 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 altering the intracellular target or enzymes that can deactivate the antibacterial compound in the cell. Screening of resistance development at different temperatures, Lopatkin et al. found that mutations that affect microbial metabolism can lead to 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 ways in which pathogens can develop resistance.
Science, this issue p. eaba0862; see also p. 783
Structured summary
INTRODUCTION
Despite the complexity of the lethality of antibiotics, canonical resistance mechanisms are generally grouped into three broad categories: target modification, drug inactivation, and drug transport. Although metabolism has been shown to actively contribute to the lethality of antibiotics, antibiotic resistance mutations are rarely identified in metabolic genes, and metabolic deregulation 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. Indeed, the laboratory evolutions associated with candidate sequencing genes and / or with a small number of clonal isolates by condition highlight expected or repeated mutations at high frequency. In addition, the effects of antibiotics on bacterial metabolism involve many complex and coordinated biomolecular networks, which makes it difficult a priori to predict candidates for probable resistance. Additionally, the diversity of pathways involved increases the number of possible evolutionary outcomes, which reduces the likelihood of convergent mutations, and would therefore be easily missed using previous methods. As a result, the genetic mechanisms of metabolic-related antibiotic resistance are considerably under-studied.
REASONING
The importance of population-level analyzes in understanding the changing landscape in response to drug treatment is increasingly recognized. Low frequency mutants make up most of the genetic diversity within a population, and in many cases beneficial mutations can drift into extinction before becoming established. This is particularly relevant for genes involved in cell metabolism, where the wide array of metabolic pathways can lead to a myriad of potential evolutionary outcomes relative to canonical drug targets. As such, we sought to use a more comprehensive view offered by population and clonal analyzes to elucidate the metabolic aspects of antibiotic resistance. In addition, given these constraints, typical laboratory evolution protocols and their analytical methods 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 thought that maximizing metabolism rather than adaptation to growth would allow us to shift this dynamic and further eliminate antibiotic-specific metabolic variants.
RESULTS
We have sequenced and analyzed Escherichia coli suitable for three representative antibiotics at increasingly elevated 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 have often occurred in multiple independent populations and / or in response to more than one drug. Several of the metabolism-specific mutations identified are overrepresented in genomes of more than 3,500 E. coli pathogens at levels similar, and in some cases higher, to known resistance mutations indicating clinical relevance. To assess whether these metabolic mutations confer resistance, we chose a representative subset of the two genes related to metabolism and classical 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, the 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 of the enzyme 2-oxoglutarate dehydrogenase (sucA) provide a preliminary picture of how an altered metabolism results in antibiotic resistance: lower basal respiration prevents induction by antibiotics of tricarboxylic acid cycle activity, thus avoiding metabolic toxicity and minimizing lethality.
CONCLUSION
Our findings that metabolic mutations occur in response to antibiotic treatment, and that these mutations confer resistance and are widespread in clinical pathogens, suggest that the three general categories of antibiotic resistance may not be as representative, nor the mechanisms as complete, as previously thought. Indeed, metabolic adaptation may represent a distinct class of resistance mechanisms beyond tolerance, whereby cells also modify their metabolic response to attenuate toxic aspects downstream of antibiotic lethality.
Cells were exposed to high concentrations of antibiotics (red) for short durations in gradually increasing metabolic states (blue), separated by cycles of drug-free growth (small vials). From left to right indicates the evolving time. Initially, antibiotic-mediated metabolic stimulation partially contributes to cell (sensitive cell) lethality. Evolved cells acquire resistance caused by decreased basal metabolic activity which avoids antibiotic stimulation and subsequent lethality (resistant cell).
Abstract
Although metabolism plays an active role in the lethality of antibiotics, antibiotic resistance is generally associated with modification of the drug target, enzymatic inactivation and / or transport rather than metabolic processes. Evolution experiences of Escherichia coli rely on growth-dependent selection, which may provide a limited view of the antibiotic resistance landscape. We have sequenced and analyzed E. coli suitable for representative antibiotics at increasingly elevated metabolic states. This revealed various underestimated non-canonical 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 the induction by antibiotics of tricarboxylic acid cycle activity, thereby avoiding metabolic toxicity and minimizing drug lethality. Several of the metabolic specific mutations identified are overrepresented in genomes of over 3,500 E. coli pathogenic, indicating clinical relevance.
[ad_2]
Source link