Phenotypic mutation rates and the abundance of abnormal proteins in yeast

Functional analysis of single enzymes combining programmable molecular circuits with droplet-based microfluidics

The analysis of proteins at the single-molecule level reveals heterogeneous behaviours that are masked in ensemble-averaged techniques. The digital quantification of enzymes traditionally involves the observation and counting of single molecules partitioned into microcompartments via the conversion of a profluorescent substrate. This strategy, based on linear signal amplification, is limited to a few enzymes with sufficiently high turnover rate. Here we show that combining the sensitivity of an exponential molecular amplifier with the modularity of DNA-enzyme circuits and droplet readout makes it possible to specifically detect, at the single-molecule level, virtually any D(R)NA-related enzymatic activity. This strategy, denoted digital PUMA (Programmable Ultrasensitive Molecular Amplifier), is validated for more than a dozen different enzymes, including many with slow catalytic rate, and down to the extreme limit of apparent single turnover for Streptococcus pyogenes Cas9. Digital counting uniquely yields absolute molar quantification and reveals a large fraction of inactive catalysts in all tested commercial preparations. By monitoring the amplification reaction from single enzyme molecules in real time, we also extract the distribution of activity among the catalyst population, revealing alternative inactivation pathways under various stresses. Our approach dramatically expands the number of enzymes that can benefit from quantification and functional analysis at single-molecule resolution. We anticipate digital PUMA will serve as a versatile framework for accurate enzyme quantification in diagnosis or biotechnological applications. These digital assays may also be utilized to study the origin of protein functional heterogeneity.

YMLA: A comparative platform to carry out functional enrichment analysis for multiple gene lists in yeast

Comparative analysis among multiple gene lists on their functional features is now a routine task due to the advancement of high-throughput experiments. Several enrichment analysis tools were developed in the past. However, these tools mainly focus on one gene list and contain only gene ontology or interaction features. What makes it worse, comparative investigation and customized feature set reanalysis are still unavailable. Therefore, we constructed the YMLA (Yeast Multiple List Analyzer) platform in this research. YMLA includes 39 yeast features and facilitates comparative analysis among multiple gene lists via tabular views, heatmaps, and network plots. Moreover, the customized feature set reanalysis function was implemented in YMLA to help form mechanism hypotheses based on a selected enriched feature subset. We demonstrated the biological applicability of YMLA via example lists consisting of genes with top/bottom translation efficiency values. The analysis results provided by YMLA reveal novel facts consistent with previous experiments. YMLA is available at https://cosbi7.ee.ncku.edu.tw/YMLA/.

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.

Effective Population Size Predicts Local Rates but Not Local Mitigation of Read-through Errors

In correctly predicting that selection efficiency is positively correlated with the effective population size (Ne), the nearly neutral theory provides a coherent understanding of between-species variation in numerous genomic parameters, including heritable error (germline mutation) rates. Does the same theory also explain variation in phenotypic error rates and in abundance of error mitigation mechanisms? Translational read-through provides a model to investigate both issues as it is common, mostly nonadaptive, and has good proxy for rate (TAA being the least leaky stop codon) and potential error mitigation via "fail-safe" 3' additional stop codons (ASCs). Prior theory of translational read-through has suggested that when population sizes are high, weak selection for local mitigation can be effective thus predicting a positive correlation between ASC enrichment and Ne. Contra to prediction, we find that ASC enrichment is not correlated with Ne. ASC enrichment, although highly phylogenetically patchy, is, however, more common both in unicellular species and in genes expressed in unicellular modes in multicellular species. By contrast, Ne does positively correlate with TAA enrichment. These results imply that local phenotypic error rates, not local mitigation rates, are consistent with a drift barrier/nearly neutral model.

Application of Random Mutagenesis and Synthetic FadR Promoter for de novo Production of ω-Hydroxy Fatty Acid in Yarrowia lipolytica

As a means to develop oleaginous biorefinery, Yarrowia lipolytica was utilized to produce ω-hydroxy palmitic acid from glucose using evolutionary metabolic engineering and synthetic FadR promoters for cytochrome P450 (CYP) expression. First, a base strain was constructed to produce free fatty acids (FFAs) from glucose using metabolic engineering strategies. Subsequently, through ethyl methanesulfonate (EMS)-induced random mutagenesis and fluorescence-activated cell sorting (FACS) screening, improved FFA overproducers were screened. Additionally, synthetic promoters containing bacterial FadR binding sequences for CYP expression were designed to respond to the surge of the concentration of FFAs to activate the ω-hydroxylating pathway, resulting in increased transcriptional activity by 14 times from the third day of culture compared to the first day. Then, endogenous alk5 was screened and expressed using the synthetic FadR promoter in the developed strain for the production of ω-hydroxy palmitic acid. By implementing the synthetic FadR promoter, cell growth and production phases could be efficiently decoupled. Finally, in batch fermentation, we demonstrated de novo production of 160 mg/L of ω-hydroxy palmitic acid using FmeN3-TR1-alk5 in nitrogen-limited media. This study presents an excellent example of the production of ω-hydroxy fatty acids using synthetic promoters with bacterial transcriptional regulator (i.e., FadR) binding sequences in oleaginous yeasts.

Origin of biomolecular games: deception and molecular evolution

Biological macromolecules encode information: some of it to endow the molecule with structural flexibility, some of it to enable molecular actions as a catalyst or a substrate, but a residual part can be used to communicate with other macromolecules. Thus, macromolecules do not need to possess information only to survive in an environment, but also to strategically interact with others by sending signals to a receiving macromolecule that can properly interpret the signal and act suitably. These sender-receiver signalling games are sustained by the information asymmetry that exists among the macromolecules. In both biochemistry and molecular evolution, the important role of information asymmetry remains largely unaddressed. Here, we provide a new unifying perspective on the impact of information symmetry between macromolecules on molecular evolutionary processes, while focusing on molecular deception. Biomolecular games arise from the ability of biological macromolecules to exert precise recognition, and their role as units of selection, meaning that they are subject to competition and cooperation with other macromolecules. Thus, signalling game theory can be used to better understand fundamental features of living systems such as molecular recognition, molecular mimicry, selfish elements and 'junk' DNA. We show how deceptive behaviour at the molecular level indicates a conflict of interest, and so provides evidence of genetic conflict. This model proposes that molecular deception is diagnostic of selfish behaviour, helping to explain the evasive behaviour of transposable elements in 'junk' DNA, for example. Additionally, in this broad review, a range of major evolutionary transitions are shown to be associated with the establishment of signalling conventions, many of which are susceptible to molecular deception. These perspectives allow us to assign rudimentary behaviour to macromolecules, and show how participation in signalling games differentiates biochemistry from abiotic chemistry.

Motion, fixation probability and the choice of an evolutionary process

Seemingly minor details of mathematical and computational models of evolution are known to change the effect of population structure on the outcome of evolutionary processes. For example, birth-death dynamics often result in amplification of selection, while death-birth processes have been associated with suppression. In many biological populations the interaction structure is not static. Instead, members of the population are in motion and can interact with different individuals at different times. In this work we study populations embedded in a flowing medium; the interaction network is then time dependent. We use computer simulations to investigate how this dynamic structure affects the success of invading mutants, and compare these effects for different coupled birth and death processes. Specifically, we show how the speed of the motion impacts the fixation probability of an invading mutant. Flows of different speeds interpolate between evolutionary dynamics on fixed heterogeneous graphs and well-stirred populations; this allows us to systematically compare against known results for static structured populations. We find that motion has an active role in amplifying or suppressing selection by fragmenting and reconnecting the interaction graph. While increasing flow speeds suppress selection for most evolutionary models, we identify characteristic responses to flow for the different update rules we test. In particular we find that selection can be maximally enhanced or suppressed at intermediate flow speeds.

Whether a mutation spreads in a population or not is one of the most important questions in biology. The evolution of cancer and antibiotic resistance, for example, are mediated by invading mutants. Recent work has shown that population structure can have important consequences for the outcome of evolution. For instance, a mutant can have a higher or a lower chance of invasion than in unstructured populations. These effects can depend on seemingly minor details of the evolutionary model, such as the order of birth and death events. Many biological populations are in motion, for example due to external stirring. Experimentally this is known to be important; the performance of mutants in E. coli populations, for example, depends on the rate of mixing. Here, we focus on simulations of populations in a flowing medium, and compare the success of a mutant for different flow speeds. We contrast different evolutionary models, and identify what features of the evolutionary model affect mutant success for different speeds of the flow. We find that the chance of mutant invasion can be at its highest (or lowest) at intermediate flow speeds, depending on the order in which birth and death events occur in the evolutionary process.

Robustness by intrinsically disordered C-termini and translational readthrough

During protein synthesis genetic instructions are passed from DNA via mRNA to the ribosome to assemble a protein chain. Occasionally, stop codons in the mRNA are bypassed and translation continues into the untranslated region (3′-UTR). This process, called translational readthrough (TR), yields a protein chain that becomes longer than would be predicted from the DNA sequence alone. Protein sequences vary in propensity for translational errors, which may yield evolutionary constraints by limiting evolutionary paths. Here we investigated TR in Saccharomyces cerevisiae by analysing ribosome profiling data. We clustered proteins as either prone or non-prone to TR, and conducted comparative analyses. We find that a relatively high frequency (5%) of genes undergo TR, including ribosomal subunit proteins. Our main finding is that proteins undergoing TR are highly expressed and have a higher proportion of intrinsically disordered C-termini. We suggest that highly expressed proteins may compensate for the deleterious effects of TR by having intrinsically disordered C-termini, which may provide conformational flexibility but without distorting native function. Moreover, we discuss whether minimizing deleterious effects of TR is also enabling exploration of the phenotypic landscape of protein isoforms.

How long to rest in unpredictably changing habitats?

In the present study, we investigated the optimum length of prolonged dormancy (developmental arrest extending over favourable periods) of organisms under uncertain environmental conditions. We used an artificial life model to simulate the evolution of suspended development in the ontogenesis of organisms inhabiting unpredictably changing habitats. A virtual population of semelparous parthenogenetic individuals that varied in a duration of developmental arrest competed for limited resources. At a constant level of available resources, uninterrupted development was the superior life strategy. Once population fluctuations appeared (generated by the stochastic variability of available resources), temporal developmental arrest became more advantageous than continuous development. We did not observe the selection of the optimum length of dormancy, but rather the evolution of a diversified period of developmental arrest. The fittest organisms employed bet-hedging strategy and produced diversified dormant forms postponing development for a different number of generations (from 0 to several generations, in decreasing or equal proportions). The maximum length of suspended development increased asymptotically with increasing environmental variability and was inversely related to the mortality of dormant forms. The prolonged dormancy may appear beneficial not only in erratic habitats but also in seasonal ones that are exposed to long-term variability of environmental conditions during the growing seasons. In light of our simulations the phenomenon of very long diapause (VLD), lasting tens to thousands of generations, which is occasionally observed in ontogenesis of some living creatures, may not be explained by the benefits of bet-hedging revival strategies. We propose an alternative reasoning for the expression of VLD.

Mistranslation: from adaptations to applications

BACKGROUND

The conservation of the genetic code indicates that there was a single origin, but like all genetic material, the cell's interpretation of the code is subject to evolutionary pressure. Single nucleotide variations in tRNA sequences can modulate codon assignments by altering codon-anticodon pairing or tRNA charging. Either can increase translation errors and even change the code. The frozen accident hypothesis argued that changes to the code would destabilize the proteome and reduce fitness. In studies of model organisms, mistranslation often acts as an adaptive response. These studies reveal evolutionary conserved mechanisms to maintain proteostasis even during high rates of mistranslation.

SCOPE OF REVIEW

This review discusses the evolutionary basis of altered genetic codes, how mistranslation is identified, and how deviations to the genetic code are exploited. We revisit early discoveries of genetic code deviations and provide examples of adaptive mistranslation events in nature. Lastly, we highlight innovations in synthetic biology to expand the genetic code.

MAJOR CONCLUSIONS

The genetic code is still evolving. Mistranslation increases proteomic diversity that enables cells to survive stress conditions or suppress a deleterious allele. Genetic code variants have been identified by genome and metagenome sequence analyses, suppressor genetics, and biochemical characterization.

GENERAL SIGNIFICANCE

Understanding the mechanisms of translation and genetic code deviations enables the design of new codes to produce novel proteins. Engineering the translation machinery and expanding the genetic code to incorporate non-canonical amino acids are valuable tools in synthetic biology that are impacting biomedical research. This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue.

The Evolutionary Potential of Phenotypic Mutations

Errors in protein synthesis, so-called phenotypic mutations, are orders-of-magnitude more frequent than genetic mutations. Here, we provide direct evidence that alternative protein forms and phenotypic variability derived from translational errors paved the path to genetic, evolutionary adaptations via gene duplication. We explored the evolutionary origins of Saccharomyces cerevisiae IDP3 - an NADP-dependent isocitrate dehydrogenase mediating fatty acids ß-oxidation in the peroxisome. Following the yeast whole genome duplication, IDP3 diverged from a cytosolic ancestral gene by acquisition of a C-terminal peroxisomal targeting signal. We discovered that the pre-duplicated cytosolic IDPs are partially localized to the peroxisome owing to +1 translational frameshifts that bypass the stop codon and unveil cryptic peroxisomal targeting signals within the 3'-UTR. Exploring putative cryptic signals in all 3'-UTRs of yeast genomes, we found that other enzymes related to NADPH production such as pyruvate carboxylase 1 (PYC1) might be prone to peroxisomal localization via cryptic signals. Using laboratory evolution we found that these translational frameshifts are rapidly imprinted via genetic single base deletions occurring within the very same gene location. Further, as exemplified here, the sequences that promote translational frameshifts are also more prone to genetic deletions. Thus, genotypes conferring higher phenotypic variability not only meet immediate challenges by unveiling cryptic 3'-UTR sequences, but also boost the potential for future genetic adaptations.

On the cause of aging and control of lifespan: heterogeneity leads to inevitable damage accumulation, causing aging; control of damage composition and rate of accumulation define lifespan

What the causes of aging are and which factors define lifespan are key questions in the understanding of aging. Here, it is argued that cellular life involves (i) inevitable accumulation of damage resulting from imperfectness and heterogeneity of every cellular process, and (ii) dilution of damage when cells divide. While severe damage is cleared by protective systems, milder damage can only be diluted. This is due to the high cost of accuracy, the greater number of damage forms compared to protective systems, and the constraints on cellular life inherited from the prokaryotic world. This strategy also applies to cancer cells, which are particularly dependent on damage dilution. Imposing restriction on cell division necessarily leads to aging. Interventions that extend lifespan act through metabolic reprogramming, thereby changing both damage composition and the rate of damage accumulation. Thus, heterogeneity leading to myriad mild damage forms represents the cause of aging, whereas the processes that affect the damage landscape and damage accumulation are lifespan regulators.

Protein homeostasis and the phenotypic manifestation of genetic diversity: principles and mechanisms

Changing a single nucleotide in a genome can have profound consequences under some conditions, but the same change can have no consequences under others. Indeed, organisms can be surprisingly robust to environmental and genetic perturbations. Yet, the mechanisms underlying such robustness are controversial. Moreover, how they might affect evolutionary change remains enigmatic. Here, we review the recently appreciated central role of protein homeostasis in buffering and potentiating genetic variation and discuss how these processes mediate the critical influence of the environment on the relationship between genotype and phenotype. Deciphering how robustness emerges from biological organization and the mechanisms by which it is overcome in changing environments will lead to a more complete understanding of both fundamental evolutionary processes and diverse human diseases.

Evolution of the mutation rate

Understanding the mechanisms of evolution requires information on the rate of appearance of new mutations and their effects at the molecular and phenotypic levels. Although procuring such data has been technically challenging, high-throughput genome sequencing is rapidly expanding knowledge in this area. With information on spontaneous mutations now available in a variety of organisms, general patterns have emerged for the scaling of mutation rate with genome size and for the likely mechanisms that drive this pattern. Support is presented for the hypothesis that natural selection pushes mutation rates down to a lower limit set by the power of random genetic drift rather than by intrinsic physiological limitations, and that this has resulted in reduced levels of replication, transcription, and translation fidelity in eukaryotes relative to prokaryotes.

Mutational clusters generated by non-processive polymerases: A case study using DNA polymerase betain vitro

Available DNA mutational spectra reveal that the number of mutants with multiple mutations ("multiples") is usually greater than expected from a random distribution of mutations among mutants. These overloads imply the occurrence of non-random clusters of mutations, probably generated during episodes of low-fidelity DNA synthesis. Excess multiples have been reported not only for viruses, bacteria, and eukaryotic cells but also for the DNA polymerases of phages T4 and RB69 in vitro. In the simplest case of a purified polymerase, non-random clusters may be generated by a subfraction of phenotypic variants able to introduce more errors per cycle of DNA synthesis than the normal enzyme. According to this hypothesis, excess multiples are not expected with non-processive polymerases even if they harbor rare mutator variants. DNA polymerase beta (Pol beta) is a mammalian DNA-repair polymerase with very low processivity. Although several Pol beta mutational spectra have been described, there is conflicting evidence on whether or not excess multiples occur, with spectra based on the HSV-tk system tending to show excess multiples. Excess multiples generated by Pol beta or any of its mutants might imply that the excesses of multiples observed in numerous other systems, especially those with processive polymerases, could be artifactual. Here, the distributions of mutations generated by native and recombinant rat Pol beta and by the Pol beta(Y265C) mutator were analyzed in the M13mp2 lacZalpha system. Our results present no evidence for a significant excess of multiples over the expected numbers with any of the Pol beta enzymes tested in this system. The reported excess of Pol beta-generated multiples in the HSV-tk system may reflect a reduced efficiency of detection of base substitutions that cause weak phenotypes, which in turn may artifactually increase the frequency of multiples.

Signatures of protein biophysics in coding sequence evolution

Since the early days of molecular evolution, the conventional wisdom has been that the evolution of protein-coding genes is primarily determined by functional constraints. Yet recent evidence indicates that the evolution of these genes is strongly shaped by the biophysical processes of protein synthesis, protein folding, and specific as well as nonspecific protein-protein interactions. Selection pressures related to these biophysical processes affect primarily the amino-acid sequence of genes, but they also leave their mark on synonymous sites at the nucleotide level. While evidence for specific selection pressures related to protein biophysics is strong, there is currently no unifying framework that integrates the various selection pressures on coding sequences and disentangles their relative importance.

GroEL dependency affects codon usage--support for a critical role of misfolding in gene evolution

Integrating genome-scale sequence, expression, structural and protein interaction data from E. coli we establish an interaction between chaperone (GroEL) dependency and optimal codon usage.

Highly expressed sporadic substrates of GroEL employ more optimal codons than expected, show enrichment for optimal codons at structurally sensitive sites and greater conservation of codon optimality under conditions of relaxed purifying selection.

We suggest that highly expressed genes cannot routinely utilize GroEL for error control so that codon usage has evolved to provide complementary error limitation, whereas obligate GroEL substrates experience relaxed selection on codon usage.

Our results support a critical role of misfolding prevention in gene evolution.

Errors during gene expression are relatively commonplace, which has prompted speculations that many features of gene and genome anatomy and organization have evolved to reduce or mitigate such errors. One type of error that can be particularly costly occurs when the polypeptide chain that emerges from the ribosome fails to fold into its native structure. Some aberrantly folded proteins, exposing hydrophobic residues that would normally be buried, may begin to promiscuously interact with other proteins, become toxic to the cell and thus pose a substantial fitness concern (Gregersen et al, 2006).

In trans, molecular chaperones have long been recognized to play crucial roles in misfolding prevention and remedy. In cis, it has recently been suggested that the use of optimal codons limits mistranslation-induced protein misfolding (Drummond and Wilke, 2008). Evidence for the latter is centred on the argument that synonymous codons differ in their propensity to cause mistranslation. Translationally optimal codons, typically represented by more abundant cognate tRNAs (Duret, 2000), are thought less likely to cause ribosomal stalling and/or incorporation of the wrong amino acid.

Here, we suggest that the role, if any, of error limitation in cis can be revealed by studying its interaction with well-established error management systems in trans (chaperones). If codon usage does indeed play a tangible role in misfolding prevention, we would expect selection on codon identity to vary with the degree to which a protein can rely on other error control mechanisms, namely chaperones. We use the E. coli chaperonin GroEL as a model system to explore whether there is any interaction between optimal codon usage and chaperone dependency.

Kerner et al (2005) had previously determined GroEL substrates on a genome-wide scale. Based on enrichment in GroEL complexes the authors assigned ∼250 proteins to three classes reflecting GroEL dependency: class-I proteins, only a small fraction of which (<1%) associates with GroEL and which spontaneously regain some activity; class-II proteins, which only exhibit spontaneous refolding at more permissive temperatures and class-III proteins, which are obligate substrates of GroEL and largely fail to refold even under more benign conditions. Notably, although on average less abundant than class-I/II proteins (‘sporadic clients'), class-III proteins (‘obligate clients') occupy ∼80% of GroEL's capacity in vivo. Consequently, a higher proportion (∼100% versus ∼20% for class-II and ∼1% for class-I) of these proteins is routinely processed by the GroEL system.

We demonstrate that sporadic but not obligate clients of GroEL exhibit enhanced codon adaptation, carefully controlling for possible confounding factors, notably expression level and protein length (Figure 1). We also point out that genes that recently entered the E. coli genome via horizontal gene transfer will distort equilibrium analyses of codon usage in bacteria and should thus be routinely eliminated from analysis.

Building on earlier work by Zhou et al (2009), we further show that sporadic substrates are conspicuously enriched for optimal codons at structurally sensitive sites, consistent with more severe fitness implications of codon choice for these proteins.

Lastly, we reveal that codon optimality in sporadic clients is more highly conserved in S. dysenteriae. S. dysenteriae is an E. coli clone that has diverged relatively recently from the E. coli K12 strain and has adopted an intracellular lifestyle (Balbi et al, 2009). Concomitant with that lifestyle, Shigella has experienced a lower effective population size and therefore reduced efficiency of purifying selection. This has generated conditions where, overall, codon optimality has started to decay. However, when we followed the fate of ancestrally optimal codons at buried sites in the S. dysenteriae and E. coli K12 genomes, we found that a lower fraction of buried sites has lost codon optimality in sporadic substrates (Figure 4), again consistent with greater structural importance of codon choice in these substrates.

Based on the these findings, we suggest the following explanation: As mentioned above, class-III substrates are defined not only by GroEL being critical for proper folding, but also by occupying most of GroEL's capacity (∼80%). With a high proportion of class-III protein passaged through the GroEL system, mistranslation errors in these proteins weigh less severely as GroEL can remedy at least some misfolding that ensues. In contrast, class-I and II genes are more highly expressed and cannot routinely rely on GroEL to rectify folding errors. Yet class-I/II proteins are clearly liable to misfold as testified by their sporadic association with GroEL. We argue that augmenting GroEL's capacity to address the misfolding propensity of these genes would be prohibitively costly to the organism and that, as an alternative strategy, these genes employ optimal codons to reduce the rate of misfolding error.

Our findings (a) reveal a cis–trans interaction between codon usage and chaperones in providing an integrated error management system, (b) provide independent evidence for a role of misfolding in shaping gene evolution and (c) suggest that the burden of deleterious mutations in long-term bottlenecking populations like that of the insect endosymbiont Buchnera not only comprises unfavourable amino-acid (Moran, 1996) but also synonymous substitutions.

It has recently been suggested that the use of optimal codons limits mistranslation-induced protein misfolding, yet evidence for this remains largely circumstantial. In contrast, molecular chaperones have long been recognized to play crucial roles in misfolding prevention and remedy. We propose that putative error limitation in cis can be elucidated by examining the interaction between codon usage and chaperoning processes. Using Escherichia coli as a model system, we find that codon optimality covaries with dependency on the chaperonin GroEL. Sporadic but not obligate substrates of GroEL exhibit higher average codon adaptation and are conspicuously enriched for optimal codons at structurally sensitive sites. Further, codon optimality of sporadic clients is more conserved in the E. coli clone Shigella dysenteriae. We suggest that highly expressed genes cannot routinely use GroEL for error control so that codon usage has evolved to provide complementary error limitation. These findings provide independent evidence for a role of misfolding in shaping gene evolution and highlight the need to co-characterize adaptations in cis and trans to unravel the workings of integrated molecular systems.

The evolutionary consequences of erroneous protein synthesis

Errors in protein synthesis disrupt cellular fitness, cause disease phenotypes and shape gene and genome evolution. Experimental and theoretical results on this topic have accumulated rapidly in disparate fields, such as neurobiology, protein biosynthesis and degradation and molecular evolution, but with limited communication among disciplines. Here, we review studies of error frequencies, the cellular and organismal consequences of errors and the attendant long-range evolutionary responses to errors. We emphasize major areas in which little is known, such as the failure rates of protein folding, in addition to areas in which technological innovations may enable imminent gains, such as the elucidation of translational missense error frequencies. Evolutionary responses to errors fall into two broad categories: adaptations that minimize errors and their attendant costs and adaptations that exploit errors for the organism's benefit.

Potential role of phenotypic mutations in the evolution of protein expression and stability

Phenotypic mutations (errors occurring during protein synthesis) are orders of magnitude more frequent than genetic mutations. Consequently, the sequences of individual protein molecules transcribed and translated from the same gene can differ. To test the effects of such mutations, we established a bacterial system in which an antibiotic resistance gene (TEM-1 beta-lactamase) was transcribed by either a high-fidelity RNA polymerase or its error-prone mutant. This setup enabled the analysis of individual mRNA transcripts that were synthesized under normal or error-prone conditions. We found that an increase of approximately 20-fold in the frequency of transcription errors promoted the evolution of higher TEM-1 expression levels and of more stable enzyme variants. The stabilized variants exhibited a distinct advantage under error-prone transcription, although under normal transcription they conferred resistance similar to wild-type TEM-1. They did so, primarily, by increasing TEM-1's tolerance to destabilizing deleterious mutations that arise from transcriptional errors. The stabilized TEM-1 variants also showed increased tolerance to genetic mutations. Thus, although phenotypic mutations are not individually subjected to inheritance and natural selection, as are genetic mutations, they collectively exert a direct and immediate effect on protein fitness. They may therefore play a role in shaping protein traits such as expression levels, stability, and tolerance to genetic mutations.