Variation in Mutational Robustness between Different Proteins and the Predictability of Fitness Effects

Determinants of Multiheme Cytochrome Extracellular Electron Transfer Uncovered by Systematic Peptide Insertion

The multiheme cytochrome MtrA enables microbial respiration by transferring electrons across the outer membrane to extracellular electron acceptors. While structural studies have identified residues that mediate the binding of MtrA to hemes and to other cytochromes that facilitate extracellular electron transfer (EET), the relative importance of these interactions for EET is not known. To better understand EET, we evaluated how insertion of an octapeptide across all MtrA backbone locations affects Shewanella oneidensis MR-1 respiration on Fe(III). The EET efficiency was found to be inversely correlated with the proximity of the insertion to the heme prosthetic groups. Mutants with decreased EET efficiencies also arose from insertions in a subset of the regions that make residue-residue contacts with the porin MtrB, while all sites contacting the extracellular cytochrome MtrC presented high peptide insertion tolerance. MtrA variants having peptide insertions within the CXXCH motifs that coordinate heme cofactors retained some ability to support respiration on Fe(III), although these variants presented significantly decreased EET efficiencies. Furthermore, the fitness of cells expressing different MtrA variants under Fe(III) respiration conditions correlated with anode reduction. The peptide insertion profile, which represents the first comprehensive sequence-structure-function map for a multiheme cytochrome, implicates MtrA as a strategic protein engineering target for the regulation of EET.

Fitness Effects of Mutations: An Assessment of PROVEAN Predictions Using Mutation Accumulation Data

Predicting fitness in natural populations is a major challenge in biology. It may be possible to leverage fast-accumulating genomic data sets to infer the fitness effects of mutant alleles, allowing evolutionary questions to be addressed in any organism. In this paper, we investigate the utility of one such tool, called PROVEAN. This program compares a query sequence with existing data to provide an alignment-based score for any protein variant, with scores categorized as neutral or deleterious based on a pre-set threshold. PROVEAN has been used widely in evolutionary studies, for example, to estimate mutation load in natural populations, but has not been formally tested as a predictor of aggregate mutational effects on fitness. Using three large published data sets on the genome sequences of laboratory mutation accumulation lines, we assessed how well PROVEAN predicted the actual fitness patterns observed, relative to other metrics. In most cases, we find that a simple count of the total number of mutant proteins is a better predictor of fitness than the number of proteins with variants scored as deleterious by PROVEAN. We also find that the sum of all mutant protein scores explains variation in fitness better than the number of mutant proteins in one of the data sets. We discuss the implications of these results for studies of populations in the wild.

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.

Forecasting of phenotypic and genetic outcomes of experimental evolution in Pseudomonas protegens

Experimental evolution with microbes is often highly repeatable under identical conditions, suggesting the possibility to predict short-term evolution. However, it is not clear to what degree evolutionary forecasts can be extended to related species in non-identical environments, which would allow testing of general predictive models and fundamental biological assumptions. To develop an extended model system for evolutionary forecasting, we used previous data and models of the genotype-to-phenotype map from the wrinkly spreader system in Pseudomonas fluorescens SBW25 to make predictions of evolutionary outcomes on different biological levels for Pseudomonas protegens Pf-5. In addition to sequence divergence (78% amino acid and 81% nucleotide identity) for the genes targeted by mutations, these species also differ in the inability of Pf-5 to make cellulose, which is the main structural basis for the adaptive phenotype in SBW25. The experimental conditions were changed compared to the SBW25 system to test if forecasts were extendable to a non-identical environment. Forty-three mutants with increased ability to colonize the air-liquid interface were isolated, and the majority had reduced motility and was partly dependent on the Pel exopolysaccharide as a structural component. Most (38/43) mutations are expected to disrupt negative regulation of the same three diguanylate cyclases as in SBW25, with a smaller number of mutations in promoter regions, including an uncharacterized polysaccharide synthase operon. A mathematical model developed for SBW25 predicted the order of the three main pathways and the genes targeted by mutations, but differences in fitness between mutants and mutational biases also appear to influence outcomes. Mutated regions in proteins could be predicted in most cases (16/22), but parallelism at the nucleotide level was low and mutational hot spot sites were not conserved. This study demonstrates the potential of short-term evolutionary forecasting in experimental populations and provides testable predictions for evolutionary outcomes in other Pseudomonas species.

Readthrough Errors Purge Deleterious Cryptic Sequences, Facilitating the Birth of Coding Sequences

De novo protein-coding innovations sometimes emerge from ancestrally noncoding DNA, despite the expectation that translating random sequences is overwhelmingly likely to be deleterious. The "preadapting selection" hypothesis claims that emergence is facilitated by prior, low-level translation of noncoding sequences via molecular errors. It predicts that selection on polypeptides translated only in error is strong enough to matter and is strongest when erroneous expression is high. To test this hypothesis, we examined noncoding sequences located downstream of stop codons (i.e., those potentially translated by readthrough errors) in Saccharomyces cerevisiae genes. We identified a class of "fragile" proteins under strong selection to reduce readthrough, which are unlikely substrates for co-option. Among the remainder, sequences showing evidence of readthrough translation, as assessed by ribosome profiling, encoded C-terminal extensions with higher intrinsic structural disorder, supporting the preadapting selection hypothesis. The cryptic sequences beyond the stop codon, rather than spillover effects from the regular C-termini, are primarily responsible for the higher disorder. Results are robust to controlling for the fact that stronger selection also reduces the length of C-terminal extensions. These findings indicate that selection acts on 3' UTRs in Saccharomyces cerevisiae to purge potentially deleterious variants of cryptic polypeptides, acting more strongly in genes that experience more readthrough errors.

Large-scale in silico mutagenesis experiments reveal optimization of genetic code and codon usage for protein mutational robustness

BACKGROUND

How, and the extent to which, evolution acts on DNA and protein sequences to ensure mutational robustness and evolvability is a long-standing open question in the field of molecular evolution. We addressed this issue through the first structurome-scale computational investigation, in which we estimated the change in folding free energy upon all possible single-site mutations introduced in more than 20,000 protein structures, as well as through available experimental stability and fitness data.

RESULTS

At the amino acid level, we found the protein surface to be more robust against random mutations than the core, this difference being stronger for small proteins. The destabilizing and neutral mutations are more numerous in the core and on the surface, respectively, whereas the stabilizing mutations are about 4% in both regions. At the genetic code level, we observed smallest destabilization for mutations that are due to substitutions of base III in the codon, followed by base I, bases I+III, base II, and other multiple base substitutions. This ranking highly anticorrelates with the codon-anticodon mispairing frequency in the translation process. This suggests that the standard genetic code is optimized to limit the impact of random mutations, but even more so to limit translation errors. At the codon level, both the codon usage and the usage bias appear to optimize mutational robustness and translation accuracy, especially for surface residues.

CONCLUSION

Our results highlight the non-universality of mutational robustness and its multiscale dependence on protein features, the structure of the genetic code, and the codon usage. Our analyses and approach are strongly supported by available experimental mutagenesis data.

Collateral fitness effects of mutations

The distribution of fitness effects of mutation plays a central role in constraining protein evolution. The underlying mechanisms by which mutations lead to fitness effects are typically attributed to changes in protein specific activity or abundance. Here, we reveal the importance of a mutation's collateral fitness effects, which we define as effects that do not derive from changes in the protein's ability to perform its physiological function. We comprehensively measured the collateral fitness effects of missense mutations in the Escherichia coli TEM-1 β-lactamase antibiotic resistance gene using growth competition experiments in the absence of antibiotic. At least 42% of missense mutations in TEM-1 were deleterious, indicating that for some proteins collateral fitness effects occur as frequently as effects on protein activity and abundance. Deleterious mutations caused improper posttranslational processing, incorrect disulfide-bond formation, protein aggregation, changes in gene expression, and pleiotropic effects on cell phenotype. Deleterious collateral fitness effects occurred more frequently in TEM-1 than deleterious effects on antibiotic resistance in environments with low concentrations of the antibiotic. The surprising prevalence of deleterious collateral fitness effects suggests they may play a role in constraining protein evolution, particularly for highly expressed proteins, for proteins under intermittent selection for their physiological function, and for proteins whose contribution to fitness is buffered against deleterious effects on protein activity and protein abundance.

Probabilistic Models for Predicting Mutational Routes to New Adaptive Phenotypes

Understanding the translation of genetic variation to phenotypic variation is a fundamental problem in genetics and evolutionary biology. The introduction of new genetic variation through mutation can lead to new adaptive phenotypes, but the complexity of the genotype-to-phenotype map makes it challenging to predict the phenotypic effects of mutation. Metabolic models, in conjunction with flux balance analysis, have been used to predict evolutionary optimality. These methods however rely on large scale models of metabolism, describe a limited set of phenotypes, and assume that selection for growth rate is the prime evolutionary driver. Here we describe a method for computing the relative likelihood that mutational change will translate into a phenotypic change between two molecular pathways. The interactions of molecular components in the pathways are modeled with ordinary differential equations. Unknown parameters are offset by probability distributions that describe the concentrations of molecular components, the reaction rates for different molecular processes, and the effects of mutations. Finally, the likelihood that mutations in a pathway will yield phenotypic change is estimated with stochastic simulations. One advantage of this method is that only basic knowledge of the interaction network underlying a phenotype is required. However, it can also incorporate available information about concentrations and reaction rates as well as mutational biases and mutational robustness of molecular components. The method estimates the relative probabilities that different pathways produce phenotypic change, which can be combined with fitness models to predict evolutionary outcomes.

Predicting mutational routes to new adaptive phenotypes

Predicting evolutionary change poses numerous challenges. Here we take advantage of the model bacterium Pseudomonas fluorescens in which the genotype-to-phenotype map determining evolution of the adaptive 'wrinkly spreader' (WS) type is known. We present mathematical descriptions of three necessary regulatory pathways and use these to predict both the rate at which each mutational route is used and the expected mutational targets. To test predictions, mutation rates and targets were determined for each pathway. Unanticipated mutational hotspots caused experimental observations to depart from predictions but additional data led to refined models. A mismatch was observed between the spectra of WS-causing mutations obtained with and without selection due to low fitness of previously undetected WS-causing mutations. Our findings contribute toward the development of mechanistic models for forecasting evolution, highlight current limitations, and draw attention to challenges in predicting locus-specific mutational biases and fitness effects.

Experimental Determination and Prediction of the Fitness Effects of Random Point Mutations in the Biosynthetic Enzyme HisA

The distribution of fitness effects of mutations is a factor of fundamental importance in evolutionary biology. We determined the distribution of fitness effects of 510 mutants that each carried between 1 and 10 mutations (synonymous and nonsynonymous) in the hisA gene, encoding an essential enzyme in the l-histidine biosynthesis pathway of Salmonella enterica. For the full set of mutants, the distribution was bimodal with many apparently neutral mutations and many lethal mutations. For a subset of 81 single, nonsynonymous mutants most mutations appeared neutral at high expression levels, whereas at low expression levels only a few mutations were neutral. Furthermore, we examined how the magnitude of the observed fitness effects was correlated to several measures of biophysical properties and phylogenetic conservation.We conclude that for HisA: (i) The effect of mutations can be masked by high expression levels, such that mutations that are deleterious to the function of the protein can still be neutral with regard to organism fitness if the protein is expressed at a sufficiently high level; (ii) the shape of the fitness distribution is dependent on the extent to which the protein is rate-limiting for growth; (iii) negative epistatic interactions, on an average, amplified the combined effect of nonsynonymous mutations; and (iv) no single sequence-based predictor could confidently predict the fitness effects of mutations in HisA, but a combination of multiple predictors could predict the effect with a SD of 0.04 resulting in 80% of the mutations predicted within 12% of their observed selection coefficients.

The road not taken: Could stress-specific mutations lead to different evolutionary paths?

Organisms often encounter stressful conditions, some of which damage their DNA. In response, some organisms show a high expression of error-prone DNA repair machinery, causing a temporary increase in the genome-wide mutation rate. Although we now have a detailed map of the molecular mechanisms underlying such stress-induced mutagenesis (SIM), it has been hotly debated whether SIM alters evolutionary dynamics. Key to this controversy is our poor understanding about which stresses increase mutagenesis and their long-term consequences for adaptation. In a new study with Escherichia coli, Maharjan and Ferenci show that while only some nutritional stresses (phosphorous and carbon limitation) increase total mutation rates, each stress generates a unique spectrum of mutations. Their results suggest the potential for specific stresses to shape evolutionary dynamics and highlight the necessity for explicit tests of the long-term evolutionary impacts of SIM.

Prediction of harmful variants on mitochondrial genes: Test of habitat-dependent and demographic effects in a euryhaline fish

Both effective population size and life history may influence the efficacy of purifying selection, but it remains unclear if the environment affects the accumulation of weakly deleterious nonsynonymous polymorphisms. We hypothesize that the reduced energetic cost of osmoregulation in brackish water habitat may cause relaxation of selective constraints at mitochondrial oxidative phosphorylation (OXPHOS) genes. To test this hypothesis, we analyzed 57 complete mitochondrial genomes of Pungitius pungitius collected from brackish and freshwater habitats. Based on inter‐ and intraspecific comparisons, we estimated that 84% and 68% of the nonsynonymous polymorphisms in the freshwater and brackish water populations, respectively, are weakly or moderately deleterious. Using in silico prediction tools (MutPred, SNAP2), we subsequently identified nonsynonymous polymorphisms with potentially harmful effect. Both prediction methods indicated that the functional effects of the fixed nonsynonymous substitutions between nine‐ and three‐spined stickleback were weaker than for polymorphisms within species, indicating that harmful nonsynonymous polymorphisms within populations rarely become fixed between species. No significant differences in mean estimated functional effects were identified between freshwater and brackish water nine‐spined stickleback to support the hypothesis that reduced osmoregulatory energy demand in the brackish water environment reduces the strength of purifying selection at OXPHOS genes. Instead, elevated frequency of nonsynonymous polymorphisms in the freshwater environment (P_n/P_s = 0.549 vs. 0.283; Fisher's exact test p = .032) suggested that purifying selection is less efficient in small freshwater populations. This study shows the utility of in silico functional prediction tools in population genetic and evolutionary research in a nonmammalian vertebrate and demonstrates that mitochondrial energy production genes represent a promising system to characterize the demographic, life history and potential habitat‐dependent effects of segregating amino acid variants.