Mistranslation can enhance fitness through purging of deleterious mutations

The central role of transfer RNAs in mistranslation

Transfer RNAs (tRNA) are essential small non-coding RNAs that enable the translation of genomic information into proteins in all life forms. The principal function of tRNAs is to bring amino acid building blocks to the ribosomes for protein synthesis. In the ribosome, tRNAs interact with messenger RNA (mRNA) to mediate the incorporation of amino acids into a growing polypeptide chain following the rules of the genetic code. Accurate interpretation of the genetic code requires tRNAs to carry amino acids matching their anticodon identity and decode the correct codon on mRNAs. Errors in these steps cause the translation of codons with the wrong amino acids (mistranslation), compromising the accurate flow of information from DNA to proteins. Accumulation of mutant proteins due to mistranslation jeopardizes proteostasis and cellular viability. However, the concept of mistranslation is evolving, with increasing evidence indicating that mistranslation can be used as a mechanism for survival and acclimatization to environmental conditions. In this review, we discuss the central role of tRNAs in modulating translational fidelity through their dynamic and complex interplay with translation factors. We summarize recent discoveries of mistranslating tRNAs and describe the underlying molecular mechanisms and the specific conditions and environments that enable and promote mistranslation.

Fluorescent reporters give new insights into antibiotics-induced nonsense and frameshift mistranslation

We developed a reporter system based on simultaneous expression of two fluorescent proteins: GFP as a reporter of the capacity of protein synthesis and mutated mScarlet-I as a reporter of translational errors. Because of the unique stop codons or frameshift mutations introduced into the mScarlet-I gene, red fluorescence was produced only after a mistranslation event. These reporters allowed us to estimate mistranslation at a single cell level using either flow cytometry or fluorescence microscopy. We found that laboratory strains of Escherichia coli are more prone to mistranslation compared to the clinical isolates. As relevant for uropathogenic E. coli, growth in human urine elevated translational frameshifting compared to standard laboratory media, whereas different standard media had a small effect on translational fidelity. Antibiotic-induced mistranslation was studied by using amikacin (aminoglycoside family) and azithromycin (macrolide family). Bactericidal amikacin induced preferably stop-codon readthrough at a moderate level. Bacteriostatic azithromycin on the other hand induced both frameshifting and stop-codon readthrough at much higher level. Single cell analysis revealed that fluorescent reporter-protein signal can be lost due to leakage from a fraction of bacteria in the presence of antibiotics, demonstrating the complexity of the antimicrobial activity.

Fitness Effects of Phenotypic Mutations at Proteome-Scale Reveal Optimality of Translation Machinery

Errors in protein translation can lead to non-genetic, phenotypic mutations, including amino acid misincorporations. While phenotypic mutations can increase protein diversity, the systematic characterization of their proteome-wide frequencies and their evolutionary impact has been lacking. Here, we developed a mechanistic model of translation errors to investigate how selection acts on protein populations produced by amino acid misincorporations. We fitted the model to empirical observations of misincorporations obtained from over a hundred mass spectrometry datasets of E. coli and S. cerevisiae. We found that on average 20% to 23% of proteins synthesized in the cell are expected to harbor at least one amino acid misincorporation, and that deleterious misincorporations are less likely to occur. Combining misincorporation probabilities and the estimated fitness effects of amino acid substitutions in a population genetics framework, we found 74% of mistranslation events in E. coli and 94% in S. cerevisiae to be neutral. We further show that the set of available synonymous tRNAs is subject to evolutionary pressure, as the presence of missing tRNAs would increase codon-anticodon cross-reactivity and misincorporation error rates. Overall, we find that the translation machinery is likely optimal in E. coli and S. cerevisiae and that both local solutions at the level of codons and a global solution such as the tRNA pool can mitigate the impact of translation errors. We provide a framework to study the evolutionary impact of codon-specific translation errors and a method for their proteome-wide detection across organisms and conditions.

P, Molina CA, Castillejo P. Beta-Lactam Antibiotic Resistance Genes in the Microbiome of the Public Transport System of Quito, Ecuador

Multidrug-resistant bacteria present resistance mechanisms against β-lactam antibiotics, such as Extended-Spectrum Beta-lactamases (ESBL) and Metallo-β-lactamases enzymes (MBLs) which are operon encoded in Gram-negative species. Likewise, Gram-positive bacteria have evolved other mechanisms through mec genes, which encode modified penicillin-binding proteins (PBP2). This study aimed to determine the presence and spread of β-lactam antibiotic resistance genes and the microbiome circulating in Quito's Public Transport (QTP). A total of 29 station turnstiles were swabbed to extract the surface environmental DNA. PCRs were performed to detect the presence of 13 antibiotic resistance genes and to identify and to amplify 16S rDNA for barcoding, followed by clone analysis, Sanger sequencing, and BLAST search. ESBL genes bla_TEM-1 and bla_CTX-M-1 and MBL genes bla_OXA-181 and mecA were detected along QPT stations, blaTEM being the most widely spread. Two subvariants were found for bla_TEM-1, bla_CTX-M-1, and bla_OXA-181. Almost half of the circulating bacteria found at QPT stations were common human microbiota species, including those classified by the WHO as pathogens of critical and high-priority surveillance. β-lactam antibiotic resistance genes are prevalent throughout QPT. This is the first report of bla_OXA-181 in environmental samples in Ecuador. Moreover, we detected a new putative variant of this gene. Some commensal coagulase-negative bacteria may have a role as mecA resistance reservoirs.

Prediction of Antibiotic Resistance Evolution by Growth Measurement of All Proximal Mutants of Beta-Lactamase

The antibiotic resistance crisis continues to threaten human health. Better predictions of the evolution of antibiotic resistance genes could contribute to the design of more sustainable treatment strategies. However, comprehensive prediction of antibiotic resistance gene evolution via laboratory approaches remains challenging. By combining site-specific integration and high-throughput sequencing, we quantified relative growth under the respective selection of cefotaxime or ceftazidime selection in ∼23,000 Escherichia coli MG1655 strains that each carried a unique, single-copy variant of the extended-spectrum β-lactamase gene blaCTX-M-14 at the chromosomal att HK022 site. Significant synergistic pleiotropy was observed within four subgenic regions, suggesting key regions for the evolution of resistance to both antibiotics. Moreover, we propose PEARP and PEARR, two deep-learning models with strong clinical correlations, for the prospective and retrospective prediction of blaCTX-M-14 evolution, respectively. Single to quintuple mutations of blaCTX-M-14 predicted to confer resistance by PEARP were significantly enriched among the clinical isolates harboring blaCTX-M-14 variants, and the PEARR scores matched the minimal inhibitory concentrations obtained for the 31 intermediates in all hypothetical trajectories. Altogether, we conclude that the measurement of local fitness landscape enables prediction of the evolutionary trajectories of antibiotic resistance genes, which could be useful for a broad range of clinical applications, from resistance prediction to designing novel treatment strategies.

GroEL/S overexpression helps to purge deleterious mutations and reduce genetic diversity during adaptive protein evolution

Chaperones are proteins that help other proteins fold. They also affect the adaptive evolution of their client proteins by buffering the effect of deleterious mutations and increasing the genetic diversity of evolving proteins. We study how the bacterial chaperone GroE (GroEL + GroES) affects the evolution of green fluorescent protein (GFP). To this end we subjected GFP to multiple rounds of mutation and selection for its color phenotype in four replicate E. coli populations, and studied its evolutionary dynamics through high-throughput sequencing and mutant engineering. We evolved GFP both under stabilizing selection for its ancestral (green) phenotype, and to directional selection for a new (cyan) phenotype. We did so both under low and high expression of the chaperone GroE. In contrast to previous work, we observe that GroE does not just buffer but also helps purge deleterious (fluorescence reducing) mutations from evolving populations. In doing so, GroE helps reduce the genetic diversity of evolving populations. In addition, it causes phenotypic heterogeneity in mutants with the same genotype, helping to enhance their fluorescence in some cells, and reducing it in others. Our observations show that chaperones can affect adaptive evolution in more than one way.

Cellular Senescence limits Translational Readthrough

The origin and evolution of cancer cells is considered to be mainly fueled by DNA mutations. Although translation errors could also expand the cellular proteome, their role in cancer biology remains poorly understood. Tumor suppressors called caretakers block cancer initiation and progression by preventing DNA mutations and/or stimulating DNA repair. If translational errors contribute to tumorigenesis, then caretaker genes should prevent such errors in normal cells in response to oncogenic stimuli. Here, we show that the process of cellular senescence induced by oncogenes, tumor suppressors or chemotherapeutic drugs is associated with a reduction in translational readthrough (TR) measured using reporters containing termination codons withing the context of both normal translation termination or programmed TR. Senescence reduced both basal TR and TR stimulated by aminoglycosides. Mechanistically, the reduction of TR during senescence is controlled by the RB tumor suppressor pathway. Cells that escape from cellular senescence either induced by oncogenes or chemotherapy have an increased TR. Also, breast cancer cells that escape from therapy-induced senescence express high levels of AGO1x, a TR isoform of AGO1 linked to breast cancer progression. We propose that senescence and the RB pathway reduce TR limiting proteome diversity and the expression of TR proteins required for cancer cell proliferation.

Summary: We report that senescence and the RB pathway reduce translational readthrough (TR) limiting proteome diversity and the expression of TR proteins such as Ago1X required for cancer cell proliferation.

Mistranslation reduces mutation load in evolving proteins through negative epistasis with DNA mutations

Translational errors during protein synthesis cause phenotypic mutations that are several orders of magnitude more frequent than DNA mutations. Such phenotypic mutations may affect adaptive evolution through their interactions with DNA mutations. To study how mistranslation may affect the adaptive evolution of evolving proteins, we evolved populations of green fluorescent protein (GFP) in either high-mistranslation or low-mistranslation Escherichia coli hosts. In both hosts, we first evolved GFP under purifying selection for the ancestral phenotype green fluorescence, and then under directional selection toward the new phenotype yellow fluorescence. High-mistranslation populations evolved modestly higher yellow fluorescence during each generation of evolution than low-mistranslation populations. We demonstrate by high-throughput sequencing that elevated mistranslation reduced the accumulation of deleterious DNA mutations under both purifying and directional selection. It did so by amplifying the fitness effects of deleterious DNA mutations through negative epistasis with phenotypic mutations. In contrast, mistranslation did not affect the incidence of beneficial mutations. Our findings show that phenotypic mutations interact epistatically with DNA mutations. By reducing a population’s mutation load, mistranslation can affect an important determinant of evolvability.

Mistranslation can promote the exploration of alternative evolutionary trajectories in enzyme evolution

Darwinian evolution preferentially follows mutational pathways whose individual steps increase fitness. Alternative pathways with mutational steps that do not increase fitness are less accessible. Here, we show that mistranslation, the erroneous incorporation of amino acids into nascent proteins, can increase the accessibility of such alternative pathways and, ultimately, of high fitness genotypes. We subject populations of the beta‐lactamase TEM‐1 to directed evolution in Escherichia coli under both low‐ and high‐mistranslation rates, selecting for high activity on the antibiotic cefotaxime. Under low mistranslation rates, different evolving TEM‐1 populations ascend the same high cefotaxime‐resistance peak, which requires three canonical DNA mutations. In contrast, under high mistranslation rates they ascend three different high cefotaxime‐resistance genotypes, which leads to higher genotypic diversity among populations. We experimentally reconstruct the adaptive DNA mutations and the potential evolutionary paths to these high cefotaxime‐resistance genotypes. This reconstruction shows that some of the DNA mutations do not change fitness under low mistranslation, but cause a significant increase in fitness under high‐mistranslation, which helps increase the accessibility of different high cefotaxime‐resistance genotypes. In addition, these mutations form a network of pairwise epistatic interactions that leads to mutually exclusive evolutionary trajectories towards different high cefotaxime‐resistance genotypes. Our observations demonstrate that protein mistranslation and the phenotypic mutations it causes can alter the evolutionary exploration of fitness landscapes and reduce the predictability of evolution.

The impact of mistranslation on phenotypic variability and fitness

Phenotypic variation is widespread in natural populations, and can significantly alter population ecology and evolution. Phenotypic variation often reflects underlying genetic variation, but also manifests via non-heritable mechanisms. For instance, translation errors result in about 10% of cellular proteins carrying altered sequences. Thus, proteome diversification arising from translation errors can potentially generate phenotypic variability, in turn increasing variability in the fate of cells or of populations. However, the link between protein diversity and phenotypic variability remains unverified. We manipulated mistranslation levels in Escherichia coli, and measured phenotypic variability between single cells (individual-level variation), as well as replicate populations (population-level variation). Monitoring growth and survival, we find that mistranslation indeed increases variation across E. coli cells, but does not consistently increase variability in growth parameters across replicate populations. Interestingly, although any deviation from the wild-type (WT) level of mistranslation reduces fitness in an optimal environment, the increased variation is associated with a survival benefit under stress. Hence, we suggest that mistranslation-induced phenotypic variation can impact growth and survival and has the potential to alter evolutionary trajectories.

The Boggarts of biology: how non-genetic changes influence the genotype

The notion that there is a one-one mapping from genotype to phenotype was overturned a long time ago. Along with genotype and environment, 'non-genetic changes' orchestrated by altered RNA and protein molecules also guide the development of phenotype. The idea that there is a route through which changes in phenotype can lead to changes in genotype impinges on several phenomena of molecular, developmental, evolutionary and applied interest. Phenotypic changes that do not alter the underlying DNA sequence have been studied across model systems (eg: DNA and histone modifications, RNA editing, prion formation) and are known to play an important role in short-term adaptation. However, because of their transient nature and unstable inheritance, the role of such changes in long-term evolution has remained controversial. I classify and review three ways in which non-genetic changes can influence genotype and impact cellular fitness across generations, with an emphasis on the enticing idea that they may act as stepping stones for genetic adaptation. I focus on work from microbial systems and attempt to highlight recent experiments and models that bear on this idea. Overall, I review evidence which suggests that non-genetic changes can impact phenotype via their influence on the genotype, and thus play a role in evolutionary change.

Highly Contingent Phenotypes of Lon Protease Deficiency in Escherichia coli upon Antibiotic Challenge

Evolutionary trajectories and mutational landscapes of drug-resistant bacteria are influenced by cell-intrinsic and extrinsic factors. In this study, I demonstrated that loss of the Lon protease altered susceptibility of Escherichia coli to trimethoprim and that these effects were strongly contingent on the drug concentration and genetic background. Lon, an AAA⁺ ATPase, is a bacterial master regulator protease involved in cytokinesis, suppression of transposition events, and clearance of misfolded proteins. I show that Lon deficiency enhances intrinsic drug tolerance at sub-MIC levels of trimethoprim. As a result, loss of Lon, though disadvantageous under drug-free conditions, has a selective advantage at low concentrations of trimethoprim. At high drug concentrations, however, Lon deficiency is detrimental for E. coli I show that the former is explained by suppression of drug efflux by Lon, while the latter can be attributed to SulA-dependent hyperfilamentation. On the other hand, deletion of lon in a trimethoprim-resistant mutant E. coli strain (harboring the Trp30Gly dihydrofolate reductase [DHFR] allele) directly potentiates resistance by enhancing the in vivo stability of mutant DHFR. Using extensive mutational analysis at 3 hot spots of resistance, I show that many resistance-conferring mutations render DHFR prone to proteolysis. This trade-off between gaining resistance and losing in vivo stability limits the number of mutations in DHFR that can confer trimethoprim resistance. Loss of Lon expands the mutational capacity for acquisition of trimethoprim resistance. This paper identifies the multipronged action of Lon in trimethoprim resistance in E. coli and provides mechanistic insight into how genetic backgrounds and drug concentrations may alter the potential for antimicrobial resistance evolution.IMPORTANCE Understanding the evolutionary dynamics of antimicrobial resistance is vital to curb its emergence and spread. Being fundamentally similar to natural selection, the fitness of resistant mutants is a key parameter to consider in the evolutionary dynamics of antimicrobial resistance (AMR). Various intrinsic and extrinsic factors modulate the fitness of resistant bacteria. This study demonstrated that Lon, a bacterial master regulator protease, influences drug tolerance and resistance. Lon is a key regulator of several fundamental processes in bacteria, including cytokinesis. I demonstrated that Lon deficiency produces highly contingent phenotypes in E. coli challenged with trimethoprim and can expand the mutational repertoire available to E. coli to evolve resistance. This multipronged influence of Lon on drug resistance provides an illustrative instance of how master regulators shape the response of bacteria to antibiotics.

Low-abundance mutations in colorectal cancer patients and healthy adults

Detecting low-abundance mutations is very important for cancer diagnosis and treatment. Here we describe an improved targeted sequencing analysis that dramatically increases sequencing depth. Seven colorectal cancer (CRC) patients and seven healthy adults were enrolled in this study. We examined genetic mutations in tissue samples from the central and peripheral regions of tumors from the CRC patients and in blood cells from the healthy adults. We observed that each CRC carried larger numbers of mutations more than previously estimated. These included numerous deletion mutations in the tumor tissue. While the cellular morphology in the surrounding normal colonic tissues was healthy, these cells also carried many mutations. Similarly, the blood cells from the healthy donors carried numerous mutations. These findings shed new light on the processes of tumorigenesis and aging, and also present a potentially effective method for detecting low-abundance mutations for cancer diagnosis and targeted treatments.

Increased mistranslation protects E. coli from protein misfolding stress due to activation of a RpoS-dependent heat shock response

The misincorporation of an incorrect amino acid into a polypeptide during protein synthesis is considered a detrimental phenomenon. A mistranslated protein is often misfolded and degraded or nonfunctional and results in an increased cost to quality control machinery. Despite these costs, errors during protein synthesis are common in bacteria. Here, we report that mistranslation in Escherichia coli increase the protein level of the heat shock sigma factor RpoH and protect cells against heat stress. Surprisingly, this increase in RpoH due to mistranslation is dependent on the presence of the general stress response sigma factor RpoS. This report provides evidence for a protective function of mistranslation and suggests a novel regulatory role of RpoS in the heat shock response.

Translational regulation in mycobacteria and its implications for pathogenicity

Protein synthesis is a fundamental requirement of all cells for survival and replication. To date, vast numbers of genetic and biochemical studies have been performed to address the mechanisms of translation and its regulation in Escherichia coli, but only a limited number of studies have investigated these processes in other bacteria, particularly in slow growing bacteria like Mycobacterium tuberculosis, the causative agent of human tuberculosis. In this Review, we highlight important differences in the translational machinery of M. tuberculosis compared with E. coli, specifically the presence of two additional proteins and subunit stabilizing elements such as the B9 bridge. We also consider the role of leaderless translation in the ability of M. tuberculosis to establish latent infection and look at the experimental evidence that translational regulatory mechanisms operate in mycobacteria during stress adaptation, particularly focussing on differences in toxin-antitoxin systems between E. coli and M. tuberculosis and on the role of tuneable translational fidelity in conferring phenotypic antibiotic resistance. Finally, we consider the implications of these differences in the context of the biological adaptation of M. tuberculosis and discuss how these regulatory mechanisms could aid in the development of novel therapeutics for tuberculosis.

Translational control of antibiotic resistance

Many antibiotics available in the clinic today directly inhibit bacterial translation. Despite the past success of such drugs, their efficacy is diminishing with the spread of antibiotic resistance. Through the use of ribosomal modifications, ribosomal protection proteins, translation elongation factors and mistranslation, many pathogens are able to establish resistance to common therapeutics. However, current efforts in drug discovery are focused on overcoming these obstacles through the modification or discovery of new treatment options. Here, we provide an overview for common mechanisms of resistance to translation-targeting drugs and summarize several important breakthroughs in recent drug development.

Conditional accumulation of toxic tRNAs to cause amino acid misincorporation

To develop a system for conditional amino acid misincorporation, we engineered tRNAs in the yeast Saccharomyces cerevisiae to be substrates of the rapid tRNA decay (RTD) pathway, such that they accumulate when RTD is turned off. We used this system to test the effects on growth of a library of tRNASer variants with all possible anticodons, and show that many are lethal when RTD is inhibited and the tRNA accumulates. Using mass spectrometry, we measured serine misincorporation in yeast containing each of six tRNA variants, and for five of them identified hundreds of peptides with serine substitutions at the targeted amino acid sites. Unexpectedly, we found that there is not a simple correlation between toxicity and the level of serine misincorporation; in particular, high levels of serine misincorporation can occur at cysteine residues without obvious growth defects. We also showed that toxic tRNAs can be used as a tool to identify sequence variants that reduce tRNA function. Finally, we generalized this method to another tRNA species, and generated conditionally toxic tRNATyr variants in a similar manner. This method should facilitate the study of tRNA biology and provide a tool to probe the effects of amino acid misincorporation on cellular physiology.

Repertoires of tRNAs: The Couplers of Genomics and Proteomics

The pool of transfer RNA (tRNA) molecules in cells allows the ribosome to decode genetic information. This repertoire of molecular decoders is positioned in the crossroad of the genome, the transcriptome, and the proteome. Omics and systems biology now allow scientists to explore the entire repertoire of tRNAs of many organisms, revealing basic exciting biology. The tRNA gene set of hundreds of species is now characterized, in addition to the tRNA genes of organelles and viruses. Genes encoding tRNAs for certain anticodon types appear in dozens of copies in a genome, while others are universally absent from any genome. Transcriptome measurement of tRNAs is challenging, but in recent years new technologies have allowed researchers to determine the dynamic expression patterns of tRNAs. These advances reveal that availability of ready-to-translate tRNA molecules is highly controlled by several transcriptional and posttranscriptional regulatory processes. This regulation shapes the proteome according to the cellular state. The tRNA pool profoundly impacts many aspects of cellular and organismal life, including protein expression level, translation accuracy, adequacy of folding, and even mRNA stability. As a result, the shape of the tRNA pool affects organismal health and may participate in causing conditions such as cancer and neurological conditions.

Adaptive benefits from small mutation supplies in an antibiotic resistance enzyme

Populations with large mutation supplies adapt via the "greedy" substitution of the fittest genotype available, leading to fast and repeatable short-term responses. At longer time scales, smaller mutation supplies may in theory lead to larger improvements when distant high-fitness genotypes more readily evolve from lower-fitness intermediates. Here we test for long-term adaptive benefits from small mutation supplies using in vitro evolution of an antibiotic-degrading enzyme in the presence of a novel antibiotic. Consistent with predictions, large mutant libraries cause rapid initial adaptation via the substitution of cohorts of mutations, but show later deceleration and convergence. Smaller libraries show on average smaller initial, but also more variable, improvements, with two lines yielding alleles with exceptionally high resistance levels. These two alleles share three mutations with the large-library alleles, which are known from previous work, but also have unique mutations. Replay evolution experiments and analyses of the adaptive landscape of the enzyme suggest that the benefit resulted from a combination of avoiding mutational cohorts leading to local peaks and chance. Our results demonstrate adaptive benefits from limited mutation supplies on a rugged fitness landscape, which has implications for artificial selection protocols in biotechnology and argues for a better understanding of mutation supplies in clinical settings.