Robust genetic codes enhance protein evolvability

The standard genetic code defines the rules of translation for nearly every life form on Earth. It also determines the amino acid changes accessible via single-nucleotide mutations, thus influencing protein evolvability-the ability of mutation to bring forth adaptive variation in protein function. One of the most striking features of the standard genetic code is its robustness to mutation, yet it remains an open question whether such robustness facilitates or frustrates protein evolvability. To answer this question, we use data from massively parallel sequence-to-function assays to construct and analyze 6 empirical adaptive landscapes under hundreds of thousands of rewired genetic codes, including those of codon compression schemes relevant to protein engineering and synthetic biology. We find that robust genetic codes tend to enhance protein evolvability by rendering smooth adaptive landscapes with few peaks, which are readily accessible from throughout sequence space. However, the standard genetic code is rarely exceptional in this regard, because many alternative codes render smoother landscapes than the standard code. By constructing low-dimensional visualizations of these landscapes, which each comprise more than 16 million mRNA sequences, we show that such alternative codes radically alter the topological features of the network of high-fitness genotypes. Whereas the genetic codes that optimize evolvability depend to some extent on the detailed relationship between amino acid sequence and protein function, we also uncover general design principles for engineering nonstandard genetic codes for enhanced and diminished evolvability, which may facilitate directed protein evolution experiments and the bio-containment of synthetic organisms, respectively.

Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

Convenient Genetic Encoding of Phenylalanine Derivatives through Their α-Keto Acid Precursors

The activity and function of proteins can be improved by incorporation of non-canonical amino acids (ncAAs). To avoid the tedious synthesis of a large number of chiral phenylalanine derivatives, we synthesized the corresponding phenylpyruvic acid precursors. Escherichia coli strain DH10B and strain C321.ΔA.expΔPBAD were selected as hosts for phenylpyruvic acid bioconversion and genetic code expansion using the MmPylRS/pyltRNACUA system. The concentrations of keto acids, PLP and amino donors were optimized in the process. Eight keto acids that can be biotransformed and their coupled genetic code expansions were identified. Finally, the genetic encoded ncAAs were tested for incorporation into fluorescent proteins with keto acids.

Detection of High-Level Rifaximin Resistance in Enteric Bacteria by Agar Screen

Objectives: This study aimed at determining the prevalence of rifaximin resistance in a large collection of Enterobacterales resistant to third-generation cephalosporins. A simple agar screen was developed to detect high-level resistance. Methods: A total of 401 isolates nonsusceptible to third-generation cephalosporins (including 342 Escherichia coli and 39 Klebsiella spp. and 20 Enterobacter spp.) were tested by microdilution for their MICs of rifaximin and rifampicin. Isolates with a confirmed rifaximin minimal inhibitory concentration (MIC) of >64 mg/L and a number of high-level resistant, and susceptible control isolates were tested for growth on Mueller-Hinton agar supplemented with rifaximin or rifampicin at a concentration of 256 mg/L. Amino acid mutations in rpoB and the presence of rifaximin resistance-associated genes arabidopsis response regulator (arr) 2/3 were investigated. Results: Microdilution assays identified rifaximin resistance in nine E. coli and three Klebsiella spp. isolates with complete cross-resistance to rifampicin (MICs of both >64 mg/L). The rifaximin agar screen correctly identified 9/9 clinical E. coli isolates, 2/2 E. coli controls, and 3/3 Klebsiella spp. with high-level rifaximin resistance, and was negative in 45 control clinical isolates with rifaximin MICs ranging between 2 and 32 mg/L according to broth microdilution. All nine high-level rifaximin agar screen-positive E. coli clinical isolates (vs. none of the tested controls) had rpoB mutations or carried arr2/3. Conclusions: Our agar screen test has the potential to detect high-level rifaximin-resistant Enterobacterales. Such strains remain rare among extended spectrum beta-lactamase (ESBL)-positive enteric bacteria, but may emerge among patients receiving rifaximin for prevention of hepatic encephalopathy and spontaneous bacterial peritonitis or among patients receiving rifaximin for other indications.

Changes in Intrinsic Antibiotic Susceptibility during a Long-Term Evolution Experiment with Escherichia coli

High-level resistance often evolves when populations of bacteria are exposed to antibiotics, by either mutations or horizontally acquired genes. There is also variation in the intrinsic resistance levels of different bacterial strains and species that is not associated with any known history of exposure. In many cases, evolved resistance is costly to the bacteria, such that resistant types have lower fitness than their progenitors in the absence of antibiotics. Some longer-term studies have shown that bacteria often evolve compensatory changes that overcome these tradeoffs, but even those studies have typically lasted only a few hundred generations. In this study, we examine changes in the susceptibilities of 12 populations of Escherichia coli to 15 antibiotics after 2,000 and 50,000 generations without exposure to any antibiotic. On average, the evolved bacteria were more susceptible to most antibiotics than was their ancestor. The bacteria at 50,000 generations tended to be even more susceptible than after 2,000 generations, although most of the change occurred during the first 2,000 generations. Despite the general trend toward increased susceptibility, we saw diverse outcomes with different antibiotics. For streptomycin, which was the only drug to which the ancestral strain was highly resistant, none of the evolved lines showed any increased susceptibility. The independently evolved lineages often exhibited correlated responses to the antibiotics, with correlations usually corresponding to their modes of action. On balance, our study shows that bacteria with low levels of intrinsic resistance often evolve to become even more susceptible to antibiotics in the absence of corresponding selection.IMPORTANCE Resistance to antibiotics often evolves when bacteria encounter antibiotics. However, bacterial strains and species without any known exposure to these drugs also vary in their intrinsic susceptibility. In many cases, evolved resistance has been shown to be costly to the bacteria, such that resistant types have reduced competitiveness relative to their sensitive progenitors in the absence of antibiotics. In this study, we examined changes in the susceptibilities of 12 populations of Escherichia coli to 15 antibiotics after 2,000 and 50,000 generations without exposure to any drug. The evolved bacteria tended to become more susceptible to most antibiotics, with most of the change occurring during the first 2,000 generations, when the bacteria were undergoing rapid adaptation to their experimental conditions. On balance, our findings indicate that bacteria with low levels of intrinsic resistance can, in the absence of relevant selection, become even more susceptible to antibiotics.

Evolving Bacterial Fitness with an Expanded Genetic Code

Since the fixation of the genetic code, evolution has largely been confined to 20 proteinogenic amino acids. The development of orthogonal translation systems that allow for the codon-specific incorporation of noncanonical amino acids may provide a means to expand the code, but these translation systems cannot be simply superimposed on cells that have spent billions of years optimizing their genomes with the canonical code. We have therefore carried out directed evolution experiments with an orthogonal translation system that inserts 3-nitro-L-tyrosine across from amber codons, creating a 21 amino acid genetic code in which the amber stop codon ambiguously encodes either 3-nitro-L-tyrosine or stop. The 21 amino acid code is enforced through the inclusion of an addicted, essential gene, a beta-lactamase dependent upon 3-nitro-L-tyrosine incorporation. After 2000 generations of directed evolution, the fitness deficit of the original strain was largely repaired through mutations that limited the toxicity of the noncanonical. While the evolved lineages had not resolved the ambiguous coding of the amber codon, the improvements in fitness allowed new amber codons to populate protein coding sequences.

Refactoring the Genetic Code for Increased Evolvability

The standard genetic code is robust to mutations during transcription and translation. Point mutations are likely to be synonymous or to preserve the chemical properties of the original amino acid. Saturation mutagenesis experiments suggest that in some cases the best-performing mutant requires replacement of more than a single nucleotide within a codon. These replacements are essentially inaccessible to common error-based laboratory engineering techniques that alter a single nucleotide per mutation event, due to the extreme rarity of adjacent mutations. In this theoretical study, we suggest a radical reordering of the genetic code that maximizes the mutagenic potential of single nucleotide replacements. We explore several possible genetic codes that allow a greater degree of accessibility to the mutational landscape and may result in a hyperevolvable organism that could serve as an ideal platform for directed evolution experiments. We then conclude by evaluating the challenges of constructing such recoded organisms and their potential applications within the field of synthetic biology.

The conservative nature of the genetic code prevents bioengineers from efficiently accessing the full mutational landscape of a gene via common error-prone methods. Here, we present two computational approaches to generate alternative genetic codes with increased accessibility. These new codes allow mutational transitions to a larger pool of amino acids and with a greater extent of chemical differences, based on a single nucleotide replacement within the codon, thus increasing evolvability both at the single-gene and at the genome levels. Given the widespread use of these techniques for strain and protein improvement, along with more fundamental evolutionary biology questions, the use of recoded organisms that maximize evolvability should significantly improve the efficiency of directed evolution, library generation, and fitness maximization.

Microdiversity shapes the traits, niche space, and biogeography of microbial taxa

With rapidly improving sequencing technologies, scientists have recently gained the ability to examine diverse microbial communities at high genomic resolution, revealing that both free-living and host-associated microbes partition their environment at fine phylogenetic scales. This 'microdiversity,' or closely related (> 97% similar 16S rRNA gene) but ecologically and physiologically distinct sub-taxonomic groups, appears to be an intrinsic property of microorganisms. However, the functional implications of microdiversity as well as its effects on microbial biogeography are poorly understood. Here, we present two theoretical models outlining the evolutionary mechanisms that drive the formation of microdiverse 'sub-taxa.' Additionally, we review recent literature and reveal that microdiversity influences a wide range of functional traits across diverse ecosystems and microbes. Moving to higher levels of organization, we use laboratory data from marine, soil, and host-associated bacteria to demonstrate that the aggregated trait-based response of microdiverse sub-taxa modifies the fundamental niche of microbes. The correspondence between microdiversity and niche space represents a critical tool for future studies of microbial ecology. By combining growth experiments on diverse isolates with examinations of environmental abundance patterns, researchers can better quantify the fundamental and realized niches of microbes and improve understanding of microbial biogeography and response to future environmental change.

Efforts and Challenges in Engineering the Genetic Code

This year marks the 48th anniversary of Francis Crick’s seminal work on the origin of the genetic code, in which he first proposed the “frozen accident” hypothesis to describe evolutionary selection against changes to the genetic code that cause devastating global proteome modification. However, numerous efforts have demonstrated the viability of both natural and artificial genetic code variations. Recent advances in genetic engineering allow the creation of synthetic organisms that incorporate noncanonical, or even unnatural, amino acids into the proteome. Currently, successful genetic code engineering is mainly achieved by creating orthogonal aminoacyl-tRNA/synthetase pairs to repurpose stop and rare codons or to induce quadruplet codons. In this review, we summarize the current progress in genetic code engineering and discuss the challenges, current understanding, and future perspectives regarding genetic code modification.

Rapid and Inexpensive Evaluation of Nonstandard Amino Acid Incorporation in Escherichia coli

By introducing engineered tRNA and aminoacyl-tRNA synthetase pairs into an organism, its genetic code can be expanded to incorporate nonstandard amino acids (nsAAs). The performance of these orthogonal translation systems (OTSs) varies greatly, however, with respect to the efficiency and accuracy of decoding a reassigned codon as the nsAA. To enable rapid and systematic comparisons of these critical parameters, we developed a toolkit for characterizing any Escherichia coli OTS that reassigns the amber stop codon (TAG). It assesses OTS performance by comparing how the fluorescence of strains carrying plasmids encoding a fused RFP-GFP reading frame, either with or without an intervening TAG codon, depends on the presence of the nsAA. We used this kit to (1) examine nsAA incorporation by seven different OTSs, (2) optimize nsAA concentration in growth media, (3) define the polyspecificity of an OTS, and (4) characterize evolved variants of amberless E. coli with improved growth rates.