Ákos Nyerges

Genome-wide analysis captures the determinants of the antibiotic cross-resistance interaction network

Understanding how evolution of antimicrobial resistance increases resistance to other drugs is a challenge of profound importance. By combining experimental evolution and genome sequencing of 63 laboratory-evolved lines, we charted a map of cross-resistance interactions between antibiotics in Escherichia coli, and explored the driving evolutionary principles. Here, we show that (1) convergent molecular evolution is prevalent across antibiotic treatments, (2) resistance conferring mutations simultaneously enhance sensitivity to many other drugs and (3) 27% of the accumulated mutations generate proteins with compromised activities, suggesting that antibiotic adaptation can partly be achieved without gain of novel function. By using knowledge on antibiotic properties, we examined the determinants of cross-resistance and identified chemogenomic profile similarity between antibiotics as the strongest predictor. In contrast, cross-resistance between two antibiotics is independent of whether they show synergistic effects in combination. These results have important implications on the development of novel antimicrobial strategies.

A highly precise and portable genome engineering method allows comparison of mutational effects across bacterial species

Significance Current tools for bacterial genome engineering suffer from major limitations. They have been optimized for a few laboratory model strains, lead to the accumulation of numerous undesired, off-target modifications, and demand extensive modification of the host genome prior to large-scale editing. Herein, we address these problems and present a simple, all-in-one solution. By utilizing a highly conserved mutant allele of the bacterial mismatch-repair system, we were able to gain unprecedented precision in the control over the generation of desired modifications in multiple bacterial species. These results have broad implications with regards to both biotechnological and clinical applications. Currently available tools for multiplex bacterial genome engineering are optimized for a few laboratory model strains, demand extensive prior modification of the host strain, and lead to the accumulation of numerous off-target modifications. Building on prior development of multiplex automated genome engineering (MAGE), our work addresses these problems in a single framework. Using a dominant-negative mutant protein of the methyl-directed mismatch repair (MMR) system, we achieved a transient suppression of DNA repair in Escherichia coli, which is necessary for efficient oligonucleotide integration. By integrating all necessary components into a broad-host vector, we developed a new workflow we term pORTMAGE. It allows efficient modification of multiple loci, without any observable off-target mutagenesis and prior modification of the host genome. Because of the conserved nature of the bacterial MMR system, pORTMAGE simultaneously allows genome editing and mutant library generation in other biotechnologically and clinically relevant bacterial species. Finally, we applied pORTMAGE to study a set of antibiotic resistance-conferring mutations in Salmonella enterica and E. coli. Despite over 100 million y of divergence between the two species, mutational effects remained generally conserved. In sum, a single transformation of a pORTMAGE plasmid allows bacterial species of interest to become an efficient host for genome engineering. These advances pave the way toward biotechnological and therapeutic applications. Finally, pORTMAGE allows systematic comparison of mutational effects and epistasis across a wide range of bacterial species.

Conditional DNA repair mutants enable highly precise genome engineering

Oligonucleotide-mediated multiplex genome engineering is an important tool for bacterial genome editing. The efficient application of this technique requires the inactivation of the endogenous methyl-directed mismatch repair system that in turn leads to a drastically elevated genomic mutation rate and the consequent accumulation of undesired off-target mutations. Here, we present a novel strategy for mismatch repair evasion using temperature-sensitive DNA repair mutants and temporal inactivation of the mismatch repair protein complex in Escherichia coli. Our method relies on the transient suppression of DNA repair during mismatch carrying oligonucleotide integration. Using temperature-sensitive control of methyl-directed mismatch repair protein activity during multiplex genome engineering, we reduced the number of off-target mutations by 85%, concurrently maintaining highly efficient and unbiased allelic replacement.

Phenotypic heterogeneity promotes adaptive evolution

Genetically identical cells frequently display substantial heterogeneity in gene expression, cellular morphology and physiology. It has been suggested that by rapidly generating a subpopulation with novel phenotypic traits, phenotypic heterogeneity (or plasticity) accelerates the rate of adaptive evolution in populations facing extreme environmental challenges. This issue is important as cell-to-cell phenotypic heterogeneity may initiate key steps in microbial evolution of drug resistance and cancer progression. Here, we study how stochastic transitions between cellular states influence evolutionary adaptation to a stressful environment in yeast Saccharomyces cerevisiae. We developed inducible synthetic gene circuits that generate varying degrees of expression stochasticity of an antifungal resistance gene. We initiated laboratory evolutionary experiments with genotypes carrying different versions of the genetic circuit by exposing the corresponding populations to gradually increasing antifungal stress. Phenotypic heterogeneity altered the evolutionary dynamics by transforming the adaptive landscape that relates genotype to fitness. Specifically, it enhanced the adaptive value of beneficial mutations through synergism between cell-to-cell variability and genetic variation. Our work demonstrates that phenotypic heterogeneity is an evolving trait when populations face a chronic selection pressure. It shapes evolutionary trajectories at the genomic level and facilitates evolutionary rescue from a deteriorating environmental stress.

Perturbation of Iron Homeostasis Promotes the Evolution of Antibiotic Resistance

Evolution of antibiotic resistance in microbes is frequently achieved by acquisition of spontaneous mutations during antimicrobial therapy. Here, we demonstrate that inactivation of a central transcriptional regulator of iron homeostasis (Fur) facilitates laboratory evolution of ciprofloxacin resistance in Escherichia coli. To decipher the underlying molecular mechanisms, we first performed a global transcriptome analysis and demonstrated that the set of genes regulated by Fur changes substantially in response to antibiotic treatment. We hypothesized that the impact of Fur on evolvability under antibiotic pressure is due to the elevated intracellular concentration of free iron and the consequent enhancement of oxidative damage-induced mutagenesis. In agreement with expectations, overexpression of iron storage proteins, inhibition of iron transport, or anaerobic conditions drastically suppressed the evolution of resistance, whereas inhibition of the SOS response-mediated mutagenesis had only a minor effect. Finally, we provide evidence that a cell permeable iron chelator inhibits the evolution of resistance. In sum, our work revealed the central role of iron metabolism in the de novo evolution of antibiotic resistance, a pattern that could influence the development of novel antimicrobial strategies.

System-level genome editing in microbes

The release of the first complete microbial genome sequences at the end of the past century opened the way for functional genomics and systems-biology to uncover the genetic basis of various phenotypes. The surge of available sequence data facilitated the development of novel genome editing techniques for system-level analytical studies. Recombineering allowed unprecedented throughput and efficiency in microbial genome editing and the recent discovery and widespread use of RNA-guided endonucleases offered several further perspectives: (i) previously recalcitrant species became editable, (ii) the efficiency of recombineering could be elevated, and as a result (iii) diverse genomic libraries could be generated more effectively. Supporting recombineering by RNA-guided endonucleases has led to success stories in metabolic engineering, but their use for system-level analysis is mostly unexplored. For the full exploitation of opportunities that are offered by the genome editing proficiency, future development of large scale analytical procedures is also vitally needed.

A standardized workflow for surveying recombinases expands bacterial genome-editing capabilities

Bacterial recombineering typically relies on genomic incorporation of synthetic oligonucleotides as mediated by Escherichia coli λ phage recombinase β – an occurrence largely limited to enterobacterial strains. While a handful of similar recombinases have been documented, recombineering efficiencies usually fall short of expectations for practical use. In this work, we aimed to find an efficient Recβ homologue demonstrating activity in model soil bacterium Pseudomonas putida EM42. To this end, a genus‐wide protein survey was conducted to identify putative recombinase candidates for study. Selected novel proteins were assayed in a standardized test to reveal their ability to introduce the K43T substitution into the rpsL gene of P. putida. An ERF superfamily protein, here termed Rec2, exhibited activity eightfold greater than that of the previous leading recombinase. To bolster these results, we demonstrated Rec2 ability to enter a range of mutations into the pyrF gene of P. putida at similar frequencies. Our results not only confirm the utility of Rec2 as a Recβ functional analogue within the P. putida model system, but also set a complete workflow for deploying recombineering in other bacterial strains/species. Implications range from genome editing of P. putida for metabolic engineering to extended applications within other Pseudomonads – and beyond.

Directed evolution of multiple genomic loci allows the prediction of antibiotic resistance

Significance Antibiotic development is frequently plagued by the rapid emergence of drug resistance. However, assessing the risk of resistance development in the preclinical stage is difficult. By building on multiplex automated genome engineering, we developed a method that enables precise mutagenesis of multiple, long genomic segments in multiple species without off-target modifications. Thereby, it enables the exploration of vast numbers of combinatorial genetic alterations in their native genomic context. This method is especially well-suited to screen the resistance profiles of antibiotic compounds. It allowed us to predict the evolution of resistance against antibiotics currently in clinical trials. We anticipate that it will be a useful tool to identify resistance-proof antibiotics at an early stage of drug development. Antibiotic development is frequently plagued by the rapid emergence of drug resistance. However, assessing the risk of resistance development in the preclinical stage is difficult. Standard laboratory evolution approaches explore only a small fraction of the sequence space and fail to identify exceedingly rare resistance mutations and combinations thereof. Therefore, new rapid and exhaustive methods are needed to accurately assess the potential of resistance evolution and uncover the underlying mutational mechanisms. Here, we introduce directed evolution with random genomic mutations (DIvERGE), a method that allows an up to million-fold increase in mutation rate along the full lengths of multiple predefined loci in a range of bacterial species. In a single day, DIvERGE generated specific mutation combinations, yielding clinically significant resistance against trimethoprim and ciprofloxacin. Many of these mutations have remained previously undetected or provide resistance in a species-specific manner. These results indicate pathogen-specific resistance mechanisms and the necessity of future narrow-spectrum antibacterial treatments. In contrast to prior claims, we detected the rapid emergence of resistance against gepotidacin, a novel antibiotic currently in clinical trials. Based on these properties, DIvERGE could be applicable to identify less resistance-prone antibiotics at an early stage of drug development. Finally, we discuss potential future applications of DIvERGE in synthetic and evolutionary biology.

Antibiotic-resistant bacteria show widespread collateral sensitivity to antimicrobial peptides

Antimicrobial peptides are promising alternative antimicrobial agents. However, little is known about whether resistance to small-molecule antibiotics leads to cross-resistance (decreased sensitivity) or collateral sensitivity (increased sensitivity) to antimicrobial peptides. We systematically addressed this question by studying the susceptibilities of a comprehensive set of 60 antibiotic-resistant Escherichia coli strains towards 24 antimicrobial peptides. Strikingly, antibiotic-resistant bacteria show a high frequency of collateral sensitivity to antimicrobial peptides, whereas cross-resistance is relatively rare. We identify clinically relevant multidrug-resistance mutations that increase bacterial sensitivity to antimicrobial peptides. Collateral sensitivity in multidrug-resistant bacteria arises partly through regulatory changes shaping the lipopolysaccharide composition of the bacterial outer membrane. These advances allow the identification of antimicrobial peptide–antibiotic combinations that enhance antibiotic activity against multidrug-resistant bacteria and slow down de novo evolution of resistance. In particular, when co-administered as an adjuvant, the antimicrobial peptide glycine-leucine-amide caused up to 30-fold decrease in the antibiotic resistance level of resistant bacteria. Our work provides guidelines for the development of efficient peptide-based therapies of antibiotic-resistant infections.Multidrug-resistant Escherichia coli have a high frequency of collateral sensitivity to antimicrobial peptides, which may arise from changes in lipopolysaccharide regulation.

Phylogenetic barriers to horizontal transfer of antimicrobial peptide resistance genes in the human gut microbiota

The human gut microbiota has adapted to the presence of antimicrobial peptides (AMPs) that are ancient components of immune defence. Despite important medical relevance, it has remained unclear whether AMP resistance genes in the gut microbiome are available for genetic exchange between bacterial species. Here we show that AMP- and antibiotic-resistance genes differ in their mobilization patterns and functional compatibilities with new bacterial hosts. First, whereas AMP resistance genes are widespread in the gut microbiome, their rate of horizontal transfer is lower than that of antibiotic resistance genes. Second, gut microbiota culturing and functional metagenomics revealed that AMP resistance genes originating from phylogenetically distant bacteria only have a limited potential to confer resistance in Escherichia coli, an intrinsically susceptible species. Third, the phenotypic impact of acquired AMP resistance genes heavily depends on the genetic background of the recipient bacteria. Taken together, functional compatibility with the new bacterial host emerges as a key factor limiting the genetic exchange of AMP resistance genes. Finally, our results suggest that AMPs induce highly specific changes in the composition of the human microbiota with implications for disease risks.