A swapped genetic code prevents viral infections and gene transfer.

Engineering the genetic code of an organism has been proposed to provide a firewall from natural ecosystems by preventing viral infections and gene transfer1-6. However, numerous viruses and mobile genetic elements encode parts of the translational apparatus7-9, potentially rendering a genetic-code-based firewall ineffective. Here we show that such mobile transfer RNAs (tRNAs) enable gene transfer and allow viral replication in Escherichia coli despite the genome-wide removal of 3 of the 64 codons and the previously essential cognate tRNA and release factor genes. We then establish a genetic firewall by discovering viral tRNAs that provide exceptionally efficient codon reassignment allowing us to develop cells bearing an amino acid-swapped genetic code that reassigns two of the six serine codons to leucine during translation. This amino acid-swapped genetic code renders cells resistant to viral infections by mistranslating viral proteomes and prevents the escape of synthetic genetic information by engineered reliance on serine codons to produce leucine-requiring proteins. As these cells may have a selective advantage over wild organisms due to virus resistance, we also repurpose a third codon to biocontain this virus-resistant host through dependence on an amino acid not found in nature10. Our results may provide the basis for a general strategy to make any organism safely resistant to all natural viruses and prevent genetic information flow into and out of genetically modified organisms.

Strategies to identify and edit improvements in synthetic genome segments episomally.

Genome engineering projects often utilize bacterial artificial chromosomes (BACs) to carry multi-kilobase DNA segments at low copy number. However, all stages of whole-genome engineering have the potential to impose mutations on the synthetic genome that can reduce or eliminate the fitness of the final strain. Here, we describe improvements to a multiplex automated genome engineering (MAGE) protocol to improve recombineering frequency and multiplexability. This protocol was applied to recoding an Escherichia coli strain to replace seven codons with synonymous alternatives genome wide. Ten 44 402-47 179 bp de novo synthesized DNA segments contained in a BAC from the recoded strain were unable to complement deletion of the corresponding 33-61 wild-type genes using a single antibiotic resistance marker. Next-generation sequencing (NGS) was used to identify 1-7 non-recoding mutations in essential genes per segment, and MAGE in turn proved a useful strategy to repair these mutations on the recoded segment contained in the BAC when both the recoded and wild-type copies of the mutated genes had to exist by necessity during the repair process. Finally, two web-based tools were used to predict the impact of a subset of non-recoding missense mutations on strain fitness using protein structure and function calls.

Rational design of balanced dual-targeting antibiotics with limited resistance.

Antibiotics that inhibit multiple bacterial targets offer a promising therapeutic strategy against resistance evolution, but developing such antibiotics is challenging. Here we demonstrate that a rational design of balanced multitargeting antibiotics is feasible by using a medicinal chemistry workflow. The resultant lead compounds, ULD1 and ULD2, belonging to a novel chemical class, almost equipotently inhibit bacterial DNA gyrase and topoisomerase IV complexes and interact with multiple evolutionary conserved amino acids in the ATP-binding pockets of their target proteins. ULD1 and ULD2 are excellently potent against a broad range of gram-positive bacteria. Notably, the efficacy of these compounds was tested against a broad panel of multidrug-resistant Staphylococcus aureus clinical strains. Antibiotics with clinical relevance against staphylococcal infections fail to inhibit a significant fraction of these isolates, whereas both ULD1 and ULD2 inhibit all of them (minimum inhibitory concentration [MIC] ≤1 µg/mL). Resistance mutations against these compounds are rare, have limited impact on compound susceptibility, and substantially reduce bacterial growth. Based on their efficacy and lack of toxicity demonstrated in murine infection models, these compounds could translate into new therapies against multidrug-resistant bacterial infections.

Improved bacterial recombineering by parallelized protein discovery.

Exploiting bacteriophage-derived homologous recombination processes has enabled precise, multiplex editing of microbial genomes and the construction of billions of customized genetic variants in a single day. The techniques that enable this, multiplex automated genome engineering (MAGE) and directed evolution with random genomic mutations (DIvERGE), are however, currently limited to a handful of microorganisms for which single-stranded DNA-annealing proteins (SSAPs) that promote efficient recombineering have been identified. Thus, to enable genome-scale engineering in new hosts, efficient SSAPs must first be found. Here we introduce a high-throughput method for SSAP discovery that we call "serial enrichment for efficient recombineering" (SEER). By performing SEER in Escherichia coli to screen hundreds of putative SSAPs, we identify highly active variants PapRecT and CspRecT. CspRecT increases the efficiency of single-locus editing to as high as 50% and improves multiplex editing by 5- to 10-fold in E. coli, while PapRecT enables efficient recombineering in Pseudomonas aeruginosa, a concerning human pathogen. CspRecT and PapRecT are also active in other, clinically and biotechnologically relevant enterobacteria. We envision that the deployment of SEER in new species will pave the way toward pooled interrogation of genotype-to-phenotype relationships in previously intractable bacteria.

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

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.

Limited Evolutionary Conservation of the Phenotypic Effects of Antibiotic Resistance Mutations.

Multidrug-resistant clinical isolates are common in certain pathogens, but rare in others. This pattern may be due to the fact that mutations shaping resistance have species-specific effects. To investigate this issue, we transferred a range of resistance-conferring mutations and a full resistance gene into Escherichia coli and closely related bacteria. We found that resistance mutations in one bacterial species frequently provide no resistance, in fact even yielding drug hypersensitivity in close relatives. In depth analysis of a key gene involved in aminoglycoside resistance (trkH) indicated that preexisting mutations in other genes-intergenic epistasis-underlie such extreme differences in mutational effects between species. Finally, reconstruction of adaptive landscapes under multiple antibiotic stresses revealed that mutations frequently provide multidrug resistance or elevated drug susceptibility (i.e., collateral sensitivity) only with certain combinations of other resistance mutations. We conclude that resistance and collateral sensitivity are contingent upon the genetic makeup of the bacterial population, and such contingency could shape the long-term fate of resistant bacteria. These results underlie the importance of species-specific treatment strategies.

Mismatch repair hierarchy of Pseudomonas putida revealed by mutagenic ssDNA recombineering of the pyrF gene.

The mismatch repair (MMR) system is one of the key molecular devices that prokaryotic cells have for ensuring fidelity of DNA replication. While the canonical MMR of E. coli involves 3 proteins (encoded by mutS, mutL and mutH), the soil bacterium Pseudomonads putida has only 2 bona fide homologues (mutS and mutL) and the sensitivity of this abridged system to different types of mismatches is unknown. In this background, sensitivity to MMR of this bacterium was inspected through single stranded (ss) DNA recombineering of the pyrF gene (the prokaryotic equivalent to yeast's URA3) with mutagenic oligos representative of every possible mispairing under either wild-type conditions, permanent deletion of mutS or transient loss of mutL activity (brought about by the thermoinducible dominant negative allele mutLE36K ). Analysis of single nucleotide mutations borne by clones resistant to fluoroorotic acid (5FOA, the target of wild type PyrF) pinpointed prohibited and tolerated single-nucleotide replacements and exposed a clear grading of mismatch recognition. The resulting data unequivocally established the hierarchy A:G < C:C < G:A < C:A, A:A, G:G, T:T, T:G, A:C, C:T < G:T, T:C as the one prevalent in Pseudomonas putida. This information is vital for enabling recombineering strategies aimed at single-nucleotide changes in this biotechnologically important species.

Enzyme promiscuity shapes adaptation to novel growth substrates.

Evidence suggests that novel enzyme functions evolved from low-level promiscuous activities in ancestral enzymes. Yet, the evolutionary dynamics and physiological mechanisms of how such side activities contribute to systems-level adaptations are not well characterized. Furthermore, it remains untested whether knowledge of an organism's promiscuous reaction set, or underground metabolism, can aid in forecasting the genetic basis of metabolic adaptations. Here, we employ a computational model of underground metabolism and laboratory evolution experiments to examine the role of enzyme promiscuity in the acquisition and optimization of growth on predicted non-native substrates in Escherichia coli K-12 MG1655. After as few as approximately 20 generations, evolved populations repeatedly acquired the capacity to grow on five predicted non-native substrates-D-lyxose, D-2-deoxyribose, D-arabinose, m-tartrate, and monomethyl succinate. Altered promiscuous activities were shown to be directly involved in establishing high-efficiency pathways. Structural mutations shifted enzyme substrate turnover rates toward the new substrate while retaining a preference for the primary substrate. Finally, genes underlying the phenotypic innovations were accurately predicted by genome-scale model simulations of metabolism with enzyme promiscuity.

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.

Correction: Phenotypic heterogeneity promotes adaptive evolution.

[This corrects the article DOI: 10.1371/journal.pbio.2000644.].

Rapid Evolution of Reduced Susceptibility against a Balanced Dual-Targeting Antibiotic through Stepping-Stone Mutations.

Multitargeting antibiotics, i.e., single compounds capable of inhibiting two or more bacterial targets, are generally considered to be a promising therapeutic strategy against resistance evolution. The rationale for this theory is that multitargeting antibiotics demand the simultaneous acquisition of multiple mutations at their respective target genes to achieve significant resistance. The theory presumes that individual mutations provide little or no benefit to the bacterial host. Here, we propose that such individual stepping-stone mutations can be prevalent in clinical bacterial isolates, as they provide significant resistance to other antimicrobial agents. To test this possibility, we focused on gepotidacin, an antibiotic candidate that selectively inhibits both bacterial DNA gyrase and topoisomerase IV. In a susceptible organism, Klebsiella pneumoniae, a combination of two specific mutations in these target proteins provide an >2,000-fold reduction in susceptibility, while individually, none of these mutations affect resistance significantly. Alarmingly, strains with decreased susceptibility against gepotidacin are found to be as virulent as the wild-type Klebsiella pneumoniae strain in a murine model. Moreover, numerous pathogenic isolates carry mutations which could promote the evolution of clinically significant reduction of susceptibility against gepotidacin in the future. As might be expected, prolonged exposure to ciprofloxacin, a clinically widely employed gyrase inhibitor, coselected for reduced susceptibility against gepotidacin. We conclude that extensive antibiotic usage could select for mutations that serve as stepping-stones toward resistance against antimicrobial compounds still under development. Our research indicates that even balanced multitargeting antibiotics are prone to resistance evolution.

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

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.

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.

Synthetic genomes unveil the effects of synonymous recoding.

Engineering the genetic code of an organism provides the basis for (i) making any organism safely resistant to natural viruses and (ii) preventing genetic information flow into and out of genetically modified organisms while (iii) allowing the biosynthesis of genetically encoded unnatural polymers1-4. Achieving these three goals requires the reassignment of multiple of the 64 codons nature uses to encode proteins. However, synonymous codon replacement-recoding-is frequently lethal, and how recoding impacts fitness remains poorly explored. Here, we explore these effects using whole-genome synthesis, multiplexed directed evolution, and genome-transcriptome-translatome-proteome co-profiling on multiple recoded genomes. Using this information, we assemble a synthetic Escherichia coli genome in seven sections using only 57 codons to encode proteins. By discovering the rules responsible for the lethality of synonymous recoding and developing a data-driven multi-omics-based genome construction workflow that troubleshoots synthetic genomes, we overcome the lethal effects of 62,007 synonymous codon swaps and 11,108 additional genomic edits. We show that synonymous recoding induces transcriptional noise including new antisense RNAs, leading to drastic transcriptome and proteome perturbation. As the elimination of select codons from an organism's genetic code results in the widespread appearance of cryptic promoters, we show that synonymous codon choice may naturally evolve to minimize transcriptional noise. Our work provides the first genome-scale description of how synonymous codon changes influence organismal fitness and paves the way for the construction of functional genomes that provide genetic firewalls from natural ecosystems and safely produce biopolymers, drugs, and enzymes with an expanded chemistry.

Characterization of antibiotic resistomes by reprogrammed bacteriophage-enabled functional metagenomics in clinical strains.

Functional metagenomics is a powerful experimental tool to identify antibiotic resistance genes (ARGs) in the environment, but the range of suitable host bacterial species is limited. This limitation affects both the scope of the identified ARGs and the interpretation of their clinical relevance. Here we present a functional metagenomics pipeline called Reprogrammed Bacteriophage Particle Assisted Multi-species Functional Metagenomics (DEEPMINE). This approach combines and improves the use of T7 bacteriophage with exchanged tail fibres and targeted mutagenesis to expand phage host-specificity and efficiency for functional metagenomics. These modified phage particles were used to introduce large metagenomic plasmid libraries into clinically relevant bacterial pathogens. By screening for ARGs in soil and gut microbiomes and clinical genomes against 13 antibiotics, we demonstrate that this approach substantially expands the list of identified ARGs. Many ARGs have species-specific effects on resistance; they provide a high level of resistance in one bacterial species but yield very limited resistance in a related species. Finally, we identified mobile ARGs against antibiotics that are currently under clinical development or have recently been approved. Overall, DEEPMINE expands the functional metagenomics toolbox for studying microbial communities.

inPOSE: A Flexible Toolbox for Chromosomal Cloning and Amplification of Bacterial Transgenes.

Cloning the genes and operons encoding heterologous functions in bacterial hosts is now almost exclusively carried out using plasmid vectors. This has multiple drawbacks, including the need for constant selection and variation in copy numbers. The chromosomal integration of transgenes has always offered a viable alternative; however, to date, it has been of limited use due to its tedious nature and often being limited to a single copy. We introduce here a strategy that uses bacterial insertion sequences, which are the simplest autonomous transposable elements to insert and amplify genetic cargo into a bacterial chromosome. Transgene insertion can take place either as transposition or homologous recombination, and copy number amplification is achieved using controlled copy-paste transposition. We display the successful use of IS1 and IS3 for this purpose in Escherichia coli cells using various selection markers. We demonstrate the insertion of selectable genes, an unselectable gene and a five-gene operon in up to two copies in a single step. We continue with the amplification of the inserted cassette to double-digit copy numbers within two rounds of transposase induction and selection. Finally, we analyze the stability of the cloned genetic constructs in the lack of selection and find it to be superior to all investigated plasmid-based systems. Due to the ubiquitous nature of transposable elements, we believe that with proper design, this strategy can be adapted to numerous other bacterial species.

ssDNA recombineering boosts in vivo evolution of nanobodies displayed on bacterial surfaces.

ssDNA recombineering has been exploited to hyperdiversify genomically-encoded nanobodies displayed on the surface of Escherichia coli for originating new binding properties. As a proof-of-principle a nanobody recognizing the antigen TirM from enterohaemorrhagic E. coli (EHEC) was evolved towards the otherwise not recognized TirM antigen from enteropathogenic E. coli (EPEC). To this end, E. coli cells displaying this nanobody fused to the intimin outer membrane-bound domain were subjected to multiple rounds of mutagenic oligonucleotide recombineering targeting the complementarity determining regions (CDRs) of the cognate VHH gene sequence. Binders to the EPEC-TirM were selected upon immunomagnetic capture of bacteria bearing active variants and nanobodies identified with a new ability to strongly bind the new antigen. The results highlight the power of combining evolutionary properties of bacteria in vivo with oligonucleotide synthesis in vitro for the sake of focusing diversification to specific segments of a gene (or protein thereof) of interest.

Recombineering and MAGE.

Recombination-mediated genetic engineering, also known as recombineering, is the genomic incorporation of homologous single-stranded or double-stranded DNA into bacterial genomes. Recombineering and its derivative methods have radically improved genome engineering capabilities, perhaps none more so than multiplex automated genome engineering (MAGE). MAGE is representative of a set of highly multiplexed single-stranded DNA-mediated technologies. First described in Escherichia coli, both MAGE and recombineering are being rapidly translated into diverse prokaryotes and even into eukaryotic cells. Together, this modern set of tools offers the promise of radically improving the scope and throughput of experimental biology by providing powerful new methods to ease the genetic manipulation of model and non-model organisms. In this Primer, we describe recombineering and MAGE, their optimal use, their diverse applications and methods for pairing them with other genetic editing tools. We then look forward to the future of genetic engineering.