Genetic constraints on protein evolution

Stabilizing Mutations Enhance Evolvability of BlaC β-lactamase by Widening the Mutational Landscape

Antimicrobial resistance is fueled by the rapid evolution of β-lactamases. However, a gain of new enzyme activity often comes at the expense of reduced protein stability. This evolutionary constraint is often overcome by the acquisition of stabilizing mutations that compensate for the loss of stability invoked by new function mutations. Here, we report three stabilizing mutations (I105F, H184R, and V263I) in BlaC, a serine β-lactamase from Mycobacterium tuberculosis. Using a severely destabilized variant as a template for random mutagenesis and selection, these three mutations emerged together and were able to fully restore resistance toward the antibiotic carbenicillin. In vitro characterization shows that all three mutations increase chemical and thermal stability, which leads to elevated protein levels in the periplasm of Escherichia coli. We demonstrate that the introduction of stabilizing mutations substantially enhances the evolvability of the enzyme. These findings illustrate the important role of stabilizing mutations in enzyme evolution by alleviating function-stability trade-offs and broadening the accessible evolutionary landscape.

Genome-wide analyses of Mycobacterium tuberculosis complex isolates reveal insights into circulating lineages and drug resistance mutations in The Gambia

Tuberculosis (TB), caused by the Mycobacterium tuberculosis complex (MTBC), remains a pressing global health challenge, with the West African region, including The Gambia, experiencing a substantial burden. This study explores the genetic diversity of MTBC strains circulating in The Gambia for nearly two decades (2002-2021) to enhance understanding of drug resistance dynamics and inform targeted diagnostic and treatment strategies. Using whole-genome sequencing (WGS) data from 1,803 TB isolates, we identified the predominance of lineage 4 (L4, 67.2%) and lineage 6 (L6, 26.6%) strains, with L4 showing more significant genetic variability over time. Drug susceptibility analysis of these isolates revealed that 78% (1421 isolates) were drug-susceptible, while 6.5% (119 isolates) exhibited resistance, primarily to isoniazid, rifampicin, and their combination. Additionally, 15.5% (282 isolates) were classified as Other, having potential drug-resistance mutations of uncertain significance by the WHO catalogue. Interestingly, our resistance-associated analysis showed the lineage 6 specific ethambutol uncertain significance (by WHO catalogue) mutation (embC Ala307Thr) more prevalent in The Gambia than in West Africa and globally. Structural analysis showed that first-line drug resistance mutations frequently occur in solvent-inaccessible and conserved regions of proteins, often impacting protein stability and reflecting a balance between resistance, fitness, and evolutionary adaptation. This study highlights the coexistence of globally prevalent and regionally restricted MTBC lineages, underscoring the importance of region-specific TB control measures. Integrating bioinformatic and structural analyses revealed many uncertain significant mutations by the WHO catalogue in The Gambian isolates compared to West Africa and globally. These findings reinforce the necessity of continuous genomic surveillance to address the evolving challenges of TB in high-burden settings like West Africa.

CspZ variant-specific interaction with factor H incorporates a metal site to support Lyme borreliae complement evasion

Polymorphic microbial immune evasion proteins dictate the pathogen species- or strain-specific virulence. Metals can impact how microbial proteins confer host-pathogen interactions, but whether this activity can be allelically variable is unclear. Here, we investigate the polymorphic CspZ protein of Lyme disease spirochete bacteria to assess the role of metals in protein-protein interaction. CspZ facilitates evasion of the complement system, the first line of immune defense through binding to the complement regulator factor H (FH). By obtaining a high-resolution cocrystal CspZ-FH structure, we identified a zinc coordinating the binding of FH SCR6-7 domains to a Glu65 on a loop from CspZ of Borrelia burgdorferi B31. However, zinc is dispensable for human FH binding for CspZ orthologs with a different loop orientation and/or lacking this glutamate. Phylogenetic analysis of all known human FH-binding CspZ variants further grouped the proteins into three unique lineages correlating with loop sequences. This suggests multiple FH-binding mechanisms evolved through Lyme disease spirochete-host interactions. Overall, this multidisciplinary work elucidates how the allelically specific immune evasion role of metals is impacted by microbial protein polymorphisms.

Targeting Efficient Features of Urate Oxidase to Increase Its Solubility

With the demand for mass production of protein drugs, solubility has become a serious issue. Extrinsic and intrinsic factors both affect this property. A homotetrameric cofactor-free urate oxidase (UOX) is not sufficiently soluble. To engineer UOX for optimum solubility, it is important to identify the most effective factor that influences solubility. The most effective feature to target for protein engineering was determined by measuring various solubility-related factors of UOX. A large library of homologous sequences was obtained from the databases. The data was reduced to six enzymes from different organisms. On the basis of various sequence- and structure-derived elements, the most and the least soluble enzymes were defined. To determine the best protein engineering target for modification, features of the most and least soluble enzymes were compared. Metabacillus fastidiosus UOX was the most soluble enzyme, while Agrobacterium globiformis UOX was the least soluble. According to the comparison-constant method, positive surface patches caused by arginine residue distribution are appropriate targets for modification. Two Arg to Ala mutations were introduced to the least soluble enzyme to test this hypothesis. These mutations significantly enhanced the mutant's solubility. While different algorithms produced conflicting results, it was difficult to determine which proteins were most and least soluble. Solubility prediction requires multiple algorithms based on these controversies. Protein surfaces should be investigated regionally rather than globally, and both sequence and structural data should be considered. Several other biotechnological products could be engineered using the data reduction and comparison-constant methods used in this study.

Cellular and epigenetic perspective of protein stability and its implications in the biological system

Protein stability is a fundamental prerequisite in both experimental and therapeutic applications. Current advancements in high throughput experimental techniques and functional ontology approaches have elucidated that impairment in the structure and stability of proteins is intricately associated with the cause and cure of several diseases. Therefore, it is paramount to deeply understand the physical and molecular confounding factors governing the stability of proteins. In this review article, we comprehensively investigated the evolution of protein stability, examining its emergence over time, its relationship with organizational aspects and the experimental methods used to understand it. Furthermore, we have also emphasized the role of Epigenetics and its interplay with post-translational modifications (PTMs) in regulating the stability of proteins.

Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis

Introduction

The sirtuin (Silent mating type information regulation 2 homolog)1(SIRT1) protein plays a vital role in many disorders such as diabetes, cancer, obesity, inflammation, and neurodegenerative and cardiovascular diseases. The objective of this in silico analysis of SIRT1's functional single nucleotide polymorphisms (SNPs) was to gain valuable insight into the harmful effects of non-synonymous SNPs (nsSNPs) on the protein. The objective of the study was to use bioinformatics methods to investigate the genetic variations and modifications that may have an impact on the SIRT1 gene's expression and function.

Methods

nsSNPs of SIRT1 protein were collected from the dbSNP site, from its three (3) different protein accession IDs. These were then fed to various bioinformatic tools such as SIFT, Provean, and I- Mutant to find the most deleterious ones. Functional and structural effects were examined using the HOPE server and I-Tasser. Gene interactions were predicted by STRING software. The SIFT, Provean, and I-Mutant tools detected the most deleterious three nsSNPs (rs769519031, rs778184510, and rs199983221).

Results

Out of 252 nsSNPs, SIFT analysis showed that 94 were deleterious, Provean listed 67 dangerous, and I-Mutant found 58 nsSNPs resulting in lowered stability of proteins. HOPE modelling of rs199983221 and rs769519031 suggested reduced hydrophobicity due to Ile 4Thr and Ile223Ser resulting in decreased hydrophobic interactions. In contrast, on modelling rs778184510, the mutant protein had a higher hydrophobicity than the wild type.

Conclusions

Our study reports that three nsSNPs (D357A, I223S, I4T) are the most damaging mutations of the SIRT1 gene. Mutations may result in altered protein structure and functions. Such altered protein may be the basis for various disorders. Our findings may be a crucial guide in establishing the pathogenesis of various disorders.

Empirical validation of ProteinMPNN's efficiency in enhancing protein fitness

Introduction: Protein engineering, which aims to improve the properties and functions of proteins, holds great research significance and application value. However, current models that predict the effects of amino acid substitutions often perform poorly when evaluated for precision. Recent research has shown that ProteinMPNN, a large-scale pre-training sequence design model based on protein structure, performs exceptionally well. It is capable of designing mutants with structures similar to the original protein. When applied to the field of protein engineering, the diverse designs for mutation positions generated by this model can be viewed as a more precise mutation range. Methods: We collected three biological experimental datasets and compared the design results of ProteinMPNN for wild-type proteins with the experimental datasets to verify the ability of ProteinMPNN in improving protein fitness. Results: The validation on biological experimental datasets shows that ProteinMPNN has the ability to design mutation types with higher fitness in single and multi-point mutations. We have verified the high accuracy of ProteinMPNN in protein engineering tasks from both positive and negative perspectives. Discussion: Our research indicates that using large-scale pre trained models to design protein mutants provides a new approach for protein engineering, providing strong support for guiding biological experiments and applications in biotechnology.

DeepTM: A deep learning algorithm for prediction of melting temperature of thermophilic proteins directly from sequences

Thermally stable proteins find extensive applications in industrial production, pharmaceutical development, and serve as a highly evolved starting point in protein engineering. The thermal stability of proteins is commonly characterized by their melting temperature (Tm). However, due to the limited availability of experimentally determined Tm data and the insufficient accuracy of existing computational methods in predicting Tm, there is an urgent need for a computational approach to accurately forecast the Tm values of thermophilic proteins. Here, we present a deep learning-based model, called DeepTM, which exclusively utilizes protein sequences as input and accurately predicts the Tm values of target thermophilic proteins on a dataset consisting of 7790 thermophilic protein entries. On a test set of 1550 samples, DeepTM demonstrates excellent performance with a coefficient of determination (R2) of 0.75, Pearson correlation coefficient (P) of 0.87, and root mean square error (RMSE) of 6.24 ℃. We further analyzed the sequence features that determine the thermal stability of thermophilic proteins and found that dipeptide frequency, optimal growth temperature (OGT) of the host organisms, and the evolutionary information of the protein significantly affect its melting temperature. We compared the performance of DeepTM with recently reported methods, ProTstab2 and DeepSTABp, in predicting the Tm values on two blind test datasets. One dataset comprised 22 PET plastic-degrading enzymes, while the other included 29 thermally stable proteins of broader classification. In the PET plastic-degrading enzyme dataset, DeepTM achieved RMSE of 8.25 ℃. Compared to ProTstab2 (20.05 ℃) and DeepSTABp (20.97 ℃), DeepTM demonstrated a reduction in RMSE of 58.85% and 60.66%, respectively. In the dataset of thermally stable proteins, DeepTM (RMSE=7.66 ℃) demonstrated a 51.73% reduction in RMSE compared to ProTstab2 (RMSE=15.87 ℃). DeepTM, with the sole requirement of protein sequence information, accurately predicts the melting temperature and achieves a fully end-to-end prediction process, thus providing enhanced convenience and expediency for further protein engineering.

Interaction between mutation type and gene pleiotropy drives parallel evolution in the laboratory

What causes evolution to be repeatable is a fundamental question in evolutionary biology. Pleiotropy, i.e. the effect of an allele on multiple traits, is thought to enhance repeatability by constraining the number of available beneficial mutations. Additionally, pleiotropy may promote repeatability by allowing large fitness benefits of single mutations via adaptive combinations of phenotypic effects. Yet, this latter evolutionary potential may be reaped solely by specific types of mutations able to realize optimal combinations of phenotypic effects while avoiding the costs of pleiotropy. Here, we address the interaction of gene pleiotropy and mutation type on evolutionary repeatability in a meta-analysis of experimental evolution studies with Escherichia coli. We hypothesize that single nucleotide polymorphisms (SNPs) are principally able to yield large fitness benefits by targeting highly pleiotropic genes, whereas indels and structural variants (SVs) provide smaller benefits and are restricted to genes with lower pleiotropy. By using gene connectivity as proxy for pleiotropy, we show that non-disruptive SNPs in highly pleiotropic genes yield the largest fitness benefits, since they contribute more to parallel evolution, especially in large populations, than inactivating SNPs, indels and SVs. Our findings underscore the importance of considering genetic architecture together with mutation type for understanding evolutionary repeatability. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

A Hitchhiker's Guide to Supplying Enzymatic Reducing Power into Synthetic Cells

The construction from scratch of synthetic cells by assembling molecular building blocks is unquestionably an ambitious goal from a scientific and technological point of view. To realize functional life-like systems, minimal enzymatic modules are required to sustain the processes underlying the out-of-equilibrium thermodynamic status hallmarking life, including the essential supply of energy in the form of electrons. The nicotinamide cofactors NAD(H) and NADP(H) are the main electron carriers fueling reductive redox reactions of the metabolic network of living cells. One way to ensure the continuous availability of reduced nicotinamide cofactors in a synthetic cell is to build a minimal enzymatic module that can oxidize an external electron donor and reduce NAD(P)+. In the diverse world of metabolism there is a plethora of potential electron donors and enzymes known from living organisms to provide reducing power to NAD(P)+ coenzymes. This perspective proposes guidelines to enable the reduction of nicotinamide cofactors enclosed in phospholipid vesicles, while avoiding high burdens of or cross-talk with other encapsulated metabolic modules. By determining key requirements, such as the feasibility of the reaction and transport of the electron donor into the cell-like compartment, we select a shortlist of potentially suitable electron donors. We review the most convenient proteins for the use of these reducing agents, highlighting their main biochemical and structural features. Noting that specificity toward either NAD(H) or NADP(H) imposes a limitation common to most of the analyzed enzymes, we discuss the need for specific enzymes─transhydrogenases─to overcome this potential bottleneck.

Computational compensatory mutation discovery approach: Predicting a PARP1 variant rescue mutation

The prediction of protein mutations that affect function may be exploited for multiple uses. In the context of disease variants, the prediction of compensatory mutations that reestablish functional phenotypes could aid in the development of genetic therapies. In this work, we present an integrated approach that combines coevolutionary analysis and molecular dynamics (MD) simulations to discover functional compensatory mutations. This approach is employed to investigate possible rescue mutations of a poly(ADP-ribose) polymerase 1 (PARP1) variant, PARP1 V762A, associated with lung cancer and follicular lymphoma. MD simulations show PARP1 V762A exhibits noticeable changes in structural and dynamical behavior compared with wild-type (WT) PARP1. Our integrated approach predicts A755E as a possible compensatory mutation based on coevolutionary information, and molecular simulations indicate that the PARP1 A755E/V762A double mutant exhibits similar structural and dynamical behavior to WT PARP1. Our methodology can be broadly applied to a large number of systems where single-nucleotide polymorphisms have been identified as connected to disease and can shed light on the biophysical effects of such changes as well as provide a way to discover potential mutants that could restore WT-like functionality. This can, in turn, be further utilized in the design of molecular therapeutics that aim to mimic such compensatory effect.

Drivers for mutation in amino acid sequences of two mitochondrial proteins (Cytb and COI) in Phytoseiidae mites (Acari: Mesostigmata)

Mutations in amino acid sequences can affect protein function. Such aspects have been poorly studied for arthropods. As recent studies have shown mutations in cytochrome b (Cytb) associated with geographic locations in several Phytoseiidae species, the present study aims at investigating (i) the mutation pattern in additional species for the Cytb fragment, (ii) the mutation pattern for another mitochondrial amino acid sequence, cytochrome c oxidase subunit 1 (COI), and (iii) factors affecting the mutations observed (taxonomy, plant support, climatic variables, wild vs. commercialised species). Mutations in amino acid sequences were assessed in seven Phytoseiidae species, with populations collected in contrasted environments. The DNA sequences were mainly obtained from published studies and some were newly obtained. Mutations were observed within and between the populations considered for both fragments, with higher mutation rates in Cytb than in COI sequences, confirming the robustness of this former fragment. Plant support and taxonomic position were not related to mutation patterns. A lower number of mutations was observed in commercialised populations than in wild ones. As preliminary tendencies, mutations in Cytb and COI sequences seem associated to temperature and moisture. Such a preliminary approach, attempting to relate mutation to functional adaptations, clearly opens new research tracks for better assessment of the drivers of mite adaptation, in a context of climate change.

Most cancers carry a substantial deleterious load due to Hill-Robertson interference

Cancer genomes exhibit surprisingly weak signatures of negative selection^1,2. This may be because selective pressures are relaxed or because genome-wide linkage prevents deleterious mutations from being removed (Hill-Robertson interference)³. By stratifying tumors by their genome-wide mutational burden, we observe negative selection (dN/dS ~ 0.56) in low mutational burden tumors, while remaining cancers exhibit dN/dS ratios ~1. This suggests that most tumors do not remove deleterious passengers. To buffer against deleterious passengers, tumors upregulate heat shock pathways as their mutational burden increases. Finally, evolutionary modeling finds that Hill-Robertson interference alone can reproduce patterns of attenuated selection and estimates the total fitness cost of passengers to be 46% per cell on average. Collectively, our findings suggest that the lack of observed negative selection in most tumors is not due to relaxed selective pressures, but rather the inability of selection to remove deleterious mutations in the presence of genome-wide linkage.

Identification of 121 variants of honey bee Vitellogenin protein sequences with structural differences at functional sites

Proteins are under selection to maintain central functions and to accommodate needs that arise in ever-changing environments. The positive selection and neutral drift that preserve functions result in a diversity of protein variants. The amount of diversity differs between proteins: multifunctional or disease-related proteins tend to have fewer variants than proteins involved in some aspects of immunity. Our work focuses on the extensively studied protein Vitellogenin (Vg), which in honey bees (Apis mellifera) is multifunctional and highly expressed and plays roles in immunity. Yet, almost nothing is known about the natural variation in the coding sequences of this protein or how amino acid-altering variants might impact structure-function relationships. Here, we map out allelic variation in honey bee Vg using biological samples from 15 countries. The successful barcoded amplicon Nanopore sequencing of 543 bees revealed 121 protein variants, indicating a high level of diversity in Vg. We find that the distribution of non-synonymous single nucleotide polymorphisms (nsSNPs) differs between protein regions with different functions; domains involved in DNA and protein-protein interactions contain fewer nsSNPs than the protein's lipid binding cavities. We outline how the central functions of the protein can be maintained in different variants and how the variation pattern may inform about selection from pathogens and nutrition.

An Optimal Lysis Time Maximizes Bacteriophage Fitness in Quasi-Continuous Culture

Optimality models have a checkered history in evolutionary biology. While optimality models have been successful in providing valuable insight into the evolution of a wide variety of biological traits, a common objection is that optimality models are overly simplistic and ignore organismal genetics. We revisit evolutionary optimization in the context of a major bacteriophage life history trait, lysis time. Lysis time refers to the period spanning phage infection of a host cell and its lysis, whereupon phage progenies are released. Lysis time, therefore, directly determines phage fecundity assuming progeny assembly does not exhaust host resources prior to lysis. Noting that previous tests of lysis time optimality rely on batch culture, we implemented a quasi-continuous culture system to observe productivity of a panel of isogenic phage λ genotypes differing in lysis time. We report that under our experimental conditions, λ phage productivity is maximized around optimal lysis times ranging from 60 to 100 min, and λ wildtype strain falls within this range. It would appear that natural selection on phage λ lysis time uncovered a set of genetic solutions that optimized progeny production in its ecological milieu relative to alternative genotypes. We discuss this finding in light of recent results that lysis time variation is also minimized in the strains with lysis times closer to the λ wild-type strain. IMPORTANCE Optimality theory presents the idea that natural selection acts on organismal traits to produce genotypes that maximize organismal survival and reproduction. As such, optimality theory is a valuable tool in guiding our understanding of the genetic constraints and tradeoffs organisms experience as their genotypes are selected to produce optimal solutions to biological problems. However, optimality theory is often critiqued as being overly simplistic and ignoring the roles of chance and history in the evolution of organismal traits. We show here that the wild-type genotype of a popular laboratory model organism, the bacteriophage λ, produces a phenotype for a major life history trait, lysis time, that maximizes the reproductive success of bearers of that genotype relative to other possible genotypes. This result demonstrates, as is rarely shown experimentally, that natural selection can achieve optimal solutions to ecological challenges.

Research gaps and new insights in the evolution of Drosophila seminal fluid proteins

While the striking effects of seminal fluid proteins (SFPs) on females are fairly conserved among Diptera, most SFPs lack detectable homologues among the SFP repertoires of phylogenetically distant species. How such a rapidly changing proteome conserves functions across taxa is a fascinating question. However, this and other pivotal aspects of SFPs' evolution remain elusive because discoveries on these proteins have been mainly restricted to the model Drosophila melanogaster. Here, we provide an overview of the current knowledge on the inter-specific divergence of the SFP repertoire in Drosophila and compile the increasing amount of relevant genomic information from multiple species. Capitalizing on the accumulated knowledge in D. melanogaster, we present novel sets of high-confidence SFP candidates and transcription factors presumptively involved in regulating the expression of SFPs. We also address open questions by performing comparative genomic analyses that failed to support the existence of many conserved SFPs shared by most dipterans and indicated that gene co-option is the most frequent mechanism accounting for the origin of Drosophila SFP-coding genes. We hope our update establishes a starting point to integrate further data and thus widen the understanding of the intricate evolution of these proteins.

The relative fitness of the de novo variants in general Lithuanian population vs. in individuals with intellectual disability

The effect of a variant on an organism is always multifaceted and can be considered from multiple perspectives-biochemical, medical, or evolutionary. However, the relationship between the effects of amino acid substitution on protein activity, human health, and an individual's evolutionary fitness is not trivial. We uncover that the general Lithuanian population is characterized by a "mirror reflection" of the de novo variant fitness effect, confirming the theory of neutrality. Meanwhile, in the group of individuals with intellectual disability, compared with the reference exome de novo variants significantly changed the composition of the amino acid. Therefore, it predicts that, both in terms of the number of amino acids and changes in their relative fitness, the structure of the proteins encoded by the studied amino acids undergo significant changes following the de novo variant, leading to possible changes in protein function associated with phenotypic traits. These results suggest that the analysis of relative fitness of exome sequences with de novo variants can predict the future phenotype. Therefore even in those cases, then only a few of all functional prediction analysis tools predict a variant as damaging, the negative relative fitness or even adaptability of the genome variant should be carefully evaluated considering both its direct function and the global background of the possible disease-associated mechanism regardless of the phenotype being studied.

Extending the Horizon of Homology Detection with Coevolution-based Structure Prediction

Traditional sequence analysis algorithms fail to identify distant homologies when they lie beyond a detection horizon. In this review, we discuss how co-evolution-based contact and distance prediction methods are pushing back this homology detection horizon, thereby yielding new functional insights and experimentally testable hypotheses. Based on correlated substitutions, these methods divine three-dimensional constraints among amino acids in protein sequences that were previously devoid of all annotated domains and repeats. The new algorithms discern hidden structure in an otherwise featureless sequence landscape. Their revelatory impact promises to be as profound as the use, by archaeologists, of ground-penetrating radar to discern long-hidden, subterranean structures. As examples of this, we describe how triplicated structures reflecting longin domains in MON1A-like proteins, or UVR-like repeats in DISC1, emerge from their predicted contact and distance maps. These methods also help to resolve structures that do not conform to a "beads-on-a-string" model of protein domains. In one such example, we describe CFAP298 whose ubiquitin-like domain was previously challenging to perceive owing to a large sequence insertion within it. More generally, the new algorithms permit an easier appreciation of domain families and folds whose evolution involved structural insertion or rearrangement. As we exemplify with α1-antitrypsin, coevolution-based predicted contacts may also yield insights into protein dynamics and conformational change. This new combination of structure prediction (using innovative co-evolution based methods) and homology inference (using more traditional sequence analysis approaches) shows great promise for bringing into view a sea of evolutionary relationships that had hitherto lain far beyond the horizon of homology detection.

Exploring Protein Space: From Hydrolase to Ligase by Substitution

The understanding of how proteins evolve to perform novel functions has long been sought by biologists. In this regard, two homologous bacterial enzymes, PafA and Dop, pose an insightful case study, as both rely on similar mechanistic properties, yet catalyze different reactions. PafA conjugates a small protein tag to target proteins, whereas Dop removes the tag by hydrolysis. Given that both enzymes present a similar fold and high sequence similarity, we sought to identify the differences in the amino acid sequence and folding responsible for each distinct activity. We tackled this question using analysis of sequence–function relationships, and identified a set of uniquely conserved residues in each enzyme. Reciprocal mutagenesis of the hydrolase, Dop, completely abolished the native activity, at the same time yielding a catalytically active ligase. Based on the available Dop and PafA crystal structures, this change of activity required a conformational change of a critical loop at the vicinity of the active site. We identified the conserved positions essential for stabilization of the alternative loop conformation, and tracked alternative mutational pathways that lead to a change in activity. Remarkably, all these pathways were combined in the evolution of PafA and Dop, despite their redundant effect on activity. Overall, we identified the residues and structural elements in PafA and Dop responsible for their activity differences. This analysis delineated, in molecular terms, the changes required for the emergence of a new catalytic function from a preexisting one.

How Does the Ribosome Fold the Proteome?

Folding of polypeptides begins during their synthesis on ribosomes. This process has evolved as a means for the cell to maintain proteostasis, by mitigating the risk of protein misfolding and aggregation. The capacity to now depict this cellular feat at increasingly higher resolution is providing insight into the mechanistic determinants that promote successful folding. Emerging from these studies is the intimate interplay between protein translation and folding, and within this the ribosome particle is the key player. Its unique structural properties provide a specialized scaffold against which nascent polypeptides can begin to form structure in a highly coordinated, co-translational manner. Here, we examine how, as a macromolecular machine, the ribosome modulates the intrinsic dynamic properties of emerging nascent polypeptide chains and guides them toward their biologically active structures.

Evolution of Protein Structure and Stability in Global Warming

This review focuses on the molecular signatures of protein structures in relation to evolution and survival in global warming. It is based on the premise that the power of evolutionary selection may lead to thermotolerant organisms that will repopulate the planet and continue life in general, but perhaps with different kinds of flora and fauna. Our focus is on molecular mechanisms, whereby known examples of thermoresistance and their physicochemical characteristics were noted. A comparison of interactions of diverse residues in proteins from thermophilic and mesophilic organisms, as well as reverse genetic studies, revealed a set of imprecise molecular signatures that pointed to major roles of hydrophobicity, solvent accessibility, disulfide bonds, hydrogen bonds, ionic and π-electron interactions, and an overall condensed packing of the higher-order structure, especially in the hydrophobic regions. Regardless of mutations, specialized protein chaperones may play a cardinal role. In evolutionary terms, thermoresistance to global warming will likely occur in stepwise mutational changes, conforming to the molecular signatures, such that each "intermediate" fits a temporary niche through punctuated equilibrium, while maintaining protein functionality. Finally, the population response of different species to global warming may vary substantially, and, as such, some may evolve while others will undergo catastrophic mass extinction.

Bovine Coronavirus: Variability, Evolution, and Dispersal Patterns of a No Longer Neglected Betacoronavirus

Bovine coronavirus (BoCV) is an important pathogen of cattle, causing severe enteric disease and playing a role in the bovine respiratory disease complex. Similar to other coronaviruses, a remarkable variability characterizes both its genome and biology. Despite their potential relevance, different aspects of the evolution of BoCV remain elusive. The present study reconstructs the history and evolution of BoCV using a phylodynamic approach based on complete genome and spike protein sequences. The results demonstrate high mutation and recombination rates affecting different parts of the viral genome. In the spike gene, this variability undergoes significant selective pressures—particularly episodic pressure—located mainly on the protein surface, suggesting an immune-induced selective pressure. The occurrence of compensatory mutations was also identified. On the contrary, no strong evidence in favor of host and/or tissue tropism affecting viral evolution has been proven. The well-known plasticity is thus ascribable to the innate broad viral tropism rather than mid- or long-term adaptation. The evaluation of the geographic spreading pattern clearly evidenced two clusters: a European cluster and an American–Asian cluster. While a relatively dense and quick migration network was identified in the former, the latter was dominated by the primary role of the United States (US) as a viral exportation source. Since the viral spreading pattern strongly mirrored the cattle trade, the need for more intense monitoring and preventive measures cannot be underestimated as well as the need to enforce the vaccination of young animals before international trade, to reduce not only the clinical impact but also the transferal and mixing of BoCV strains.

Deep phylogeny of cancer drivers and compensatory mutations

Driver mutations (DM) are the genetic impetus for most cancers. The DM are assumed to be deleterious in species evolution, being eliminated by purifying selection unless compensated by other mutations. We present deep phylogenies for 84 cancer driver genes and investigate the prevalence of 434 DM across gene-species trees. The DM are rare in species evolution, and 181 are completely absent, validating their negative fitness effect. The DM are more common in unicellular than in multicellular eukaryotes, suggesting a link between these mutations and cell proliferation control. 18 DM appear as the ancestral state in one or more major clades, including 3 among mammals. We identify within-gene, compensatory mutations for 98 DM and infer likely interactions between the DM and compensatory sites in protein structures. These findings elucidate the evolutionary status of DM and are expected to advance the understanding of the functions and evolution of oncogenes and tumor suppressors.

Rochman et al. present deep phylogenies for 84 cancer driver genes and examine the prevalence of driver mutations across gene-species trees. Their results show that driver mutations are rare in species evolution and give insight into the evolution of driver mutations and oncogenes.

Aligning functional network constraint to evolutionary outcomes

BACKGROUND

Functional constraint through genomic architecture is suggested to be an important dimension of genome evolution, but quantitative evidence for this idea is rare. In this contribution, existing evidence and discussions on genomic architecture as constraint for convergent evolution, rapid adaptation, and genic adaptation are summarized into alternative, testable hypotheses. Network architecture statistics from protein-protein interaction networks are then used to calculate differences in evolutionary outcomes on the example of genomic evolution in yeast, and the results are used to evaluate statistical support for these longstanding hypotheses.

RESULTS

A discriminant function analysis lent statistical support to classifying the yeast interactome into hub, intermediate and peripheral nodes based on network neighborhood connectivity, betweenness centrality, and average shortest path length. Quantitative support for the existence of genomic architecture as a mechanistic basis for evolutionary constraint is then revealed through utilizing these statistical parameters of the protein-protein interaction network in combination with estimators of protein evolution.

CONCLUSIONS

As functional genetic networks are becoming increasingly available, it will now be possible to evaluate functional genetic network constraint against variables describing complex phenotypes and environments, for better understanding of commonly observed deterministic patterns of evolution in non-model organisms. The hypothesis framework and methodological approach outlined herein may help to quantify the extrinsic versus intrinsic dimensions of evolutionary constraint, and result in a better understanding of how fast, effectively, or deterministically organisms adapt.

Insights Into the Role of Exposed Surface Charged Residues in the Alkali-Tolerance of GH11 Xylanase

Thermostable and alkaline- or acid-stable xylanases are more advantageous in agricultural and industrial fields. In this study, a rational structure-based design was conducted based on a thermostable GH11 xylanase TlXynA from Thermomyces lanuginosus to improved pH-tolerance. Four mutant enzymes (P1, P2, P3, and P4) and five variants (N1, N2, N3, N4, and N5) were constructed by substituting surface charged residue combinations using site-directed mutagenesis. Compared to the native enzyme, two mutants P1 and P2 showed higher acid tolerance, especially at pH 3.0, presented 50 and 40% of their maximum activity, respectively. In addition, four mutants N1, N2, N3 and N4 had higher tolerance than the native enzyme to alkaline environments (pH 7.0-9.0). At pH 9.0, the residual activities of N1, N2, N3, and N4 were 86, 78, 77, and 66%, respectively. In summary, an improved pH-tolerance design principle is being reported.

The expanding world of plant J-domain proteins

Plants maintain cellular proteostasis during different phases of growth and development despite a barrage of biotic and abiotic stressors in an ever-changing environment. This requires a collaborative effort of a cadre of molecular chaperones. Hsp70s and their obligate co-chaperones, J-domain proteins (JDPs), are arguably the most ubiquitous and formidable components of the cellular chaperone network, facilitating numerous and diverse cellular processes and allowing survival under a plethora of stressful conditions. JDPs are also among the most versatile chaperones. Compared to Hsp70s, the number of JDP-encoding genes has proliferated, suggesting the emergence of highly complex Hsp70-JDP networks, particularly in plants. Recent studies indicate that besides the increase in the number of JDP encoding genes; regulatory differences, neo- and sub-functionalization, and inter- and intra-class combinatorial interactions, is rapidly expanding the repertoire of Hsp70-JDP systems. This results in highly robust and functionally diverse chaperone networks in plants. Here, we review the current status of plant JDP research and discuss how the paradigm shift in the field can be exploited toward a better understanding of JDP function and evolution.

Machine Learning Applied to Predicting Microorganism Growth Temperatures and Enzyme Catalytic Optima

Enzymes that catalyze chemical reactions at high temperatures are used for industrial biocatalysis, applications in molecular biology, and as highly evolvable starting points for protein engineering. The optimal growth temperature (OGT) of organisms is commonly used to estimate the stability of enzymes encoded in their genomes, but the number of experimentally determined OGT values are limited, particularly for thermophilic organisms. Here, we report on the development of a machine learning model that can accurately predict OGT for bacteria, archaea, and microbial eukaryotes directly from their proteome-wide 2-mer amino acid composition. The trained model is made freely available for reuse. In a subsequent step we use OGT data in combination with amino acid composition of individual enzymes to develop a second machine learning model-for prediction of enzyme catalytic temperature optima ( T_opt). The resulting model generates enzyme T_opt estimates that are far superior to using OGT alone. Finally, we predict T_opt for 6.5 million enzymes, covering 4447 enzyme classes, and make the resulting data set available to researchers. This work enables simple and rapid identification of enzymes that are potentially functional at extreme temperatures.

The protonation state of an evolutionarily conserved histidine modulates domainswapping stability of FoxP1

Forkhead box P (FoxP) proteins are members of the versatile Fox transcription factors, which control the timing and expression of multiple genes for eukaryotic cell homeostasis. Compared to other Fox proteins, they can form domain-swapped dimers through their DNA-binding –forkhead– domains, enabling spatial reorganization of distant chromosome elements by tethering two DNA molecules together. Yet, domain swapping stability and DNA binding affinity varies between different FoxP proteins. Experimental evidence suggests that the protonation state of a histidine residue conserved in all Fox proteins is responsible for pH-dependent modulation of these interactions. Here, we explore the consequences of the protonation state of another histidine (H59), only conserved within FoxM/O/P subfamilies, on folding and dimerization of the forkhead domain of human FoxP1. Dimer dissociation kinetics and equilibrium unfolding experiments demonstrate that protonation of H59 leads to destabilization of the domain-swapped dimer due to an increase in free energy difference between the monomeric and transition states. This pH–dependence is abolished when H59 is mutated to alanine. Furthermore, anisotropy measurements and molecular dynamics evidence that H59 has a direct impact in the local stability of helix H3. Altogether, our results highlight the relevance of H59 in domain swapping and folding stability of FoxP1.

Network Analysis of Protein Adaptation: Modeling the Functional Impact of Multiple Mutations

The evolution of new biochemical activities frequently involves complex dependencies between mutations and rapid evolutionary radiation. Mutation co-occurrence and covariation have previously been used to identify compensating mutations that are the result of physical contacts and preserve protein function and fold. Here, we model pairwise functional dependencies and higher order interactions that enable evolution of new protein functions. We use a network model to find complex dependencies between mutations resulting from evolutionary trade-offs and pleiotropic effects. We present a method to construct these networks and to identify functionally interacting mutations in both extant and reconstructed ancestral sequences (Network Analysis of Protein Adaptation). The time ordering of mutations can be incorporated into the networks through phylogenetic reconstruction. We apply NAPA to three distantly homologous β-lactamase protein clusters (TEM, CTX-M-3, and OXA-51), each of which has experienced recent evolutionary radiation under substantially different selective pressures. By analyzing the network properties of each protein cluster, we identify key adaptive mutations, positive pairwise interactions, different adaptive solutions to the same selective pressure, and complex evolutionary trajectories likely to increase protein fitness. We also present evidence that incorporating information from phylogenetic reconstruction and ancestral sequence inference can reduce the number of spurious links in the network, whereas preserving overall network community structure. The analysis does not require structural or biochemical data. In contrast to function-preserving mutation dependencies, which are frequently from structural contacts, gain-of-function mutation dependencies are most commonly between residues distal in protein structure.

Structure-guided design combined with evolutionary diversity led to the discovery of the xylose-releasing exo-xylanase activity in the glycoside hydrolase family 43

Rational design is an important tool for sculpting functional and stability properties of proteins and its potential can be much magnified when combined with in vitro and natural evolutionary diversity. Herein, we report the structure-guided design of a xylose-releasing exo-β-1,4-xylanase from an inactive member of glycoside hydrolase family 43 (GH43). Structural analysis revealed a nonconserved substitution (Lys²⁴⁷ ) that results in the disruption of the hydrogen bond network that supports catalysis. The mutation of this residue to a conserved serine restored the catalytic activity and crystal structure elucidation of the mutant confirmed the recovery of the proper orientation of the catalytically relevant histidine. Interestingly, the tailored enzyme can cleave both xylooligosaccharides and xylan, releasing xylose as the main product, being the first xylose-releasing exo-β-1,4-xylanase reported in the GH43 family. This enzyme presents a unique active-site topology when compared with closely related β-xylosidases, which is the absence of a hydrophobic barrier at the positive-subsite region, allowing the accommodation of long substrates. Therefore, the combination of rational design for catalytic activation along with naturally occurring differences in the substrate binding interface led to the discovery of a novel activity within the GH43 family. In addition, these results demonstrate the importance of solvation of the β-propeller hollow for GH43 catalytic function and expand our mechanistic understanding about the diverse modes of action of GH43 members, a key and polyspecific carbohydrate-active enzyme family abundant in most plant cell-wall-degrading microorganisms.

Functional and structural profiles of GST gene family from three Populus species reveal the sequence-function decoupling of orthologous genes

A common assumption in comparative genomics is that orthologous genes are functionally more similar than paralogous genes. However, the validity of this assumption needs to be assessed using robust experimental data. We conducted tissue-specific gene expression and protein function analyses of orthologous groups within the glutathione S-transferase (GST) gene family in three closely related Populus species: Populus trichocarpa, Populus euphratica and Populus yatungensis. This study identified 21 GST orthologous groups in the three Populus species. Although the sequences of the GST orthologous groups were highly conserved, the divergence in enzymatic functions was prevalent. Through site-directed mutagenesis of orthologous proteins, this study revealed that nonsynonymous substitutions at key amino acid sites played an important role in the divergence of enzymatic functions. In particular, a single amino acid mutation (Arg39→Trp39) contributed to P. euphratica PeGSTU30 possessing high enzymatic activity via increasing the hydrophobicity of the active cavity. This study provided experimental evidence showing that orthologues belonging to the gene family have functional divergences. The nonsynonymous substitutions at a few amino acid sites resulted in functional divergence of the orthologous genes. Our findings provide new insights into the evolution of orthologous genes in closely related species.

Net Evolutionary Loss of Residue Polarity in Drosophilid Protein Cores Indicates Ongoing Optimization of Amino Acid Composition

Amino acid frequencies in proteins may not be at equilibrium. We consider two possible explanations for the nonzero net residue fluxes in drosophilid proteins. First, protein interiors may have a suboptimal residue composition and be under a selective pressure favoring stability, that is, leading to the loss of polar (and the gain of large) amino acids. One would then expect stronger net fluxes on the protein interior than at the exposed sites. Alternatively, if most of the polarity loss occurs at the exposed sites and the selective constraint on amino acid composition at such sites decreases over time, net loss of polarity may be neutral and caused by disproportionally high occurrence of polar residues at exposed, least constrained sites. We estimated net evolutionary fluxes of residue polarity and volume at sites with different solvent accessibility in conserved protein families from 12 species of Drosophila. Net loss of polarity, miniscule in magnitude, but consistent across all lineages, occurred at all sites except the most exposed ones, where net flux of polarity was close to zero or, in membrane proteins, even positive. At the intermediate solvent accessibility the net fluxes of polarity and volume were similar to neutral predictions, whereas much of the polarity loss not attributable to neutral expectations occurred at the buried sites. These observations are consistent with the hypothesis that residue composition in many proteins is structurally suboptimal and continues to evolve toward lower polarity in the protein interior, in particular in proteins with intracellular localization. The magnitude of polarity and volume changes was independent from the protein’s evolutionary age, indicating that the approach to equilibrium has been slow or that no such single equilibrium exists.

Thermophilic Proteins as Versatile Scaffolds for Protein Engineering

Literature from the past two decades has outlined the existence of a trade-off between protein stability and function. This trade-off creates a unique challenge for protein engineers who seek to introduce new functionality to proteins. These engineers must carefully balance the mutation-mediated creation and/or optimization of function with the destabilizing effect of those mutations. Subsequent research has shown that protein stability is positively correlated with "evolvability" or the ability to support mutations which bestow new functionality on the protein. Since the ultimate goal of protein engineering is to create and/or optimize a protein's function, highly stable proteins are preferred as potential scaffolds for protein engineering. This review focuses on the application potential for thermophilic proteins as scaffolds for protein engineering. The relatively high inherent thermostability of these proteins grants them a great deal of mutational robustness, making them promising scaffolds for various protein engineering applications. Comparative studies on the evolvability of thermophilic and mesophilic proteins have strongly supported the argument that thermophilic proteins are more evolvable than mesophilic proteins. These findings indicate that thermophilic proteins may represent the scaffold of choice for protein engineering in the future.

Identification and Analysis of OVATE Family Members from Genome of the Early Land Plants Provide Insights into Evolutionary History of OFP Family and Function

Mosses, liverworts, hornworts and lycophytes represent transition stages between the aquatic to terrestrial/land plants. Several morphological and adaptive novelties driven by genomic components including emergence and expansion of new or existing gene families have played a critical role during and after the transition, and contributed towards successful colonization of terrestrial ecosystems. It is crucial to decipher the evolutionary transitions and natural selection on the gene structure and function to understand the emergence of phenotypic and adaptive diversity. Plants at the "transition zone", between aquatic and terrestrial ecosystem, are also the most vulnerable because of climate change and may contain clues for successful mitigation of the challenges of climate change. Identification and comparative analyses of such genetic elements and gene families are few in mosses, liverworts, hornworts and lycophytes. Ovate family proteins (OFPs) are plant-specific transcriptional repressors and are acknowledged for their roles in important growth and developmental processes in land plants, and information about the functional aspects of OFPs in early land plants is fragmentary. As a first step towards addressing this gap, a comprehensive in silico analysis was carried out utilizing publicly available genome sequences of Marchantia polymorpha (Mp), Physcomitrella patens (Pp), Selaginella moellendorffii (Sm) and Sphagnum fallax (Sf). Our analysis led to the identification of 4 MpOFPs, 19 PpOFPs, 6 SmOFPs and 3 SfOFPs. Cross-genera analysis revealed a drastic change in the structure and physiochemical properties in OFPs suggesting functional diversification and genomic plasticity during the evolutionary course. Knowledge gained from this comparative analysis will form the framework towards deciphering and dissection of their developmental and adaptive role/s in early land plants and could provide insights into evolutionary strategies adapted by land plants.

Evolution of CYP2J19, a gene involved in colour vision and red coloration in birds: positive selection in the face of conservation and pleiotropy

BACKGROUND

Exaggerated signals, such as brilliant colours, are usually assumed to evolve through antagonistic coevolution between senders and receivers, but the underlying genetic mechanisms are rarely known. Here we explore a recently identified "redness gene", CYP2J19, that is highly interesting in this context since it encodes a carotenoid-modifying enzyme (a C4 ketolase involved in both colour signalling and colour discrimination in the red (long wavelength) spectral region.) RESULTS: A single full-length CYP2J19 was retrieved from 43 species out of 70 avian genomes examined, representing all major avian clades. In addition, CYP2J19 sequences from 13 species of weaverbirds (Ploceidae), seven of which have red C4-ketocarotenoid coloration were analysed. Despite the conserved retinal function and pleiotropy of CYP2J19, analyses indicate that the gene has been positively selected throughout the radiation of birds, including sites within functional domains described in related CYP (cytochrome P450) loci. Analyses of eight further CYP loci across 25 species show that positive selection is common in this gene family in birds. There was no evidence for a change in selection pressure on CYP2J19 following co-option for red coloration in the weaverbirds.

CONCLUSIONS

The results presented here are consistent with an ancestral conserved function of CYP2J19 in the pigmentation of red retinal oil droplets used for colour vision, and its subsequent co-option for red integumentary coloration. The cause of positive selection on CYP2J19 is unclear, but may be partly related to compensatory mutations related to selection at the adjacent gene CYP2J40.

Evolution and Function of the Populus SABATH Family Reveal That a Single Amino Acid Change Results in a Substrate Switch

Evolutionary mechanisms of substrate specificities of enzyme families remain poorly understood. Plant SABATH methyltransferases catalyze methylation of the carboxyl group of various low molecular weight metabolites. Investigation of the functional diversification of the SABATH family in plants could shed light on the evolution of substrate specificities in this enzyme family. Previous studies identified 28 SABATH genes from the Populus trichocarpa genome. In this study, we re-annotated the Populus SABATH gene family, and performed molecular evolution, gene expression and biochemical analyses of this large gene family. Twenty-eight Populus SABATH genes were divided into three classes with distinct divergences in their gene structure, expression responses to abiotic stressors and enzymatic properties of encoded proteins. Populus class I SABATH proteins converted IAA to methyl-IAA, class II SABATH proteins converted benzoic acid (BA) and salicylic acid (SA) to methyl-BA and methyl-SA, while class III SABATH proteins converted farnesoic acid (FA) to methyl-FA. For Populus class II SABATH proteins, both forward and reverse mutagenesis studies showed that a single amino acid switch between PtSABATH4 and PtSABATH24 resulted in substrate switch. Our findings provide new insights into the evolution of substrate specificities of enzyme families.

Identification of epistatic mutations and insights into the evolution of the influenza virus using a mass-based protein phylogenetic approach

A mass-based protein phylogenetic approach developed in this laboratory has been applied to study mutation trends and identify consecutive or near-consecutive mutations typically associated with positive epistasis. While epistasis is thought to occur commonly during the evolution of viruses, the extent of epistasis in influenza, and its role in the evolution of immune escape and drug resistant mutants, remains to be systematically investigated. Here putative epistatic mutations within H3 hemagglutinin in type A influenza are identified where leading parent mutations were found to predominate within reported antigenic sites of the protein. Frequent subsequent mutations resided exclusively in different antigenic regions, providing the virus with a possible immune escape mechanism, or at other remote sites that drive beneficial protein structural and functional change. The results also enable a "small steps" evolutionary model to be proposed where the more frequent consecutive, or near-consecutive, non-conservative mutations exhibited less structural, and thus functional, change. This favours the evolutionary survival of the virus over mutations associated with more substantive change that may cause or risk its own extinction.

An NLRP3 Mutation Causes Arthropathy and Osteoporosis in Humanized Mice

The NLRP3 inflammasome plays a critical role in host defense by facilitating caspase I activation and maturation of IL-1β and IL-18, whereas dysregulation of inflammasome activity results in autoinflammatory disease. Factors regulating human NLRP3 activity that contribute to the phenotypic heterogeneity of NLRP3-related diseases have largely been inferred from the study of Nlrp3 mutant mice. By generating a mouse line in which the NLRP3 locus is humanized by syntenic replacement, we show the functioning of the human NLRP3 proteins in vivo, demonstrating the ability of the human inflammasome to orchestrate immune reactions in response to innate stimuli. Humanized mice expressing disease-associated mutations develop normally but display acute sensitivity to endotoxin and develop progressive and debilitating arthritis characterized by granulocytic infiltrates, elevated cytokines, erosion of bones, and osteoporosis. This NLRP3-dependent arthritis model provides a platform for testing therapeutic reagents targeting the human inflammasome.

Regulatory network structure determines patterns of intermolecular epistasis

Most phenotypes are determined by molecular systems composed of specifically interacting molecules. However, unlike for individual components, little is known about the distributions of mutational effects of molecular systems as a whole. We ask how the distribution of mutational effects of a transcriptional regulatory system differs from the distributions of its components, by first independently, and then simultaneously, mutating a transcription factor and the associated promoter it represses. We find that the system distribution exhibits increased phenotypic variation compared to individual component distributions - an effect arising from intermolecular epistasis between the transcription factor and its DNA-binding site. In large part, this epistasis can be qualitatively attributed to the structure of the transcriptional regulatory system and could therefore be a common feature in prokaryotes. Counter-intuitively, intermolecular epistasis can alleviate the constraints of individual components, thereby increasing phenotypic variation that selection could act on and facilitating adaptive evolution.

Enzyme Efficiency but Not Thermostability Drives Cefotaxime Resistance Evolution in TEM-1 β-Lactamase

A leading intellectual challenge in evolutionary genetics is to identify the specific phenotypes that drive adaptation. Enzymes offer a particularly promising opportunity to pursue this question, because many enzymes' contributions to organismal fitness depend on a comparatively small number of experimentally accessible properties. Moreover, on first principles the demands of enzyme thermostability stand in opposition to the demands of catalytic activity. This observation, coupled with the fact that enzymes are only marginally thermostable, motivates the widely held hypothesis that mutations conferring functional improvement require compensatory mutations to restore thermostability. Here, we explicitly test this hypothesis for the first time, using four missense mutations in TEM-1 β-lactamase that jointly increase cefotaxime Minimum Inhibitory Concentration (MIC) ∼1500-fold. First, we report enzymatic efficiency (kcat/KM) and thermostability (Tm, and thence ΔG of folding) for all combinations of these mutations. Next, we fit a quantitative model that predicts MIC as a function of kcat/KM and ΔG. While kcat/KM explains ∼54% of the variance in cefotaxime MIC (∼92% after log transformation), ΔG does not improve explanatory power of the model. We also find that cefotaxime MIC rises more slowly in kcat/KM than predicted. Several explanations for these discrepancies are suggested. Finally, we demonstrate substantial sign epistasis in MIC and kcat/KM, and antagonistic pleiotropy between phenotypes, in spite of near numerical additivity in the system. Thus constraints on selectively accessible trajectories, as well as limitations in our ability to explain such constraints in terms of underlying mechanisms are observed in a comparatively "well-behaved" system.

Evolutionary Conservation and Emerging Functional Diversity of the Cytosolic Hsp70:J Protein Chaperone Network of Arabidopsis thaliana

Heat shock proteins of 70 kDa (Hsp70s) partner with structurally diverse Hsp40s (J proteins), generating distinct chaperone networks in various cellular compartments that perform myriad housekeeping and stress-associated functions in all organisms. Plants, being sessile, need to constantly maintain their cellular proteostasis in response to external environmental cues. In these situations, the Hsp70:J protein machines may play an important role in fine-tuning cellular protein quality control. Although ubiquitous, the functional specificity and complexity of the plant Hsp70:J protein network has not been studied. Here, we analyzed the J protein network in the cytosol of Arabidopsis thaliana and, using yeast genetics, show that the functional specificities of most plant J proteins in fundamental chaperone functions are conserved across long evolutionary timescales. Detailed phylogenetic and functional analysis revealed that increased number, regulatory differences, and neofunctionalization in J proteins together contribute to the emerging functional diversity and complexity in the Hsp70:J protein network in higher plants. Based on the data presented, we propose that higher plants have orchestrated their "chaperome," especially their J protein complement, according to their specialized cellular and physiological stipulations.

Ancient genes establish stress-induced mutation as a hallmark of cancer

Cancer is sometimes depicted as a reversion to single cell behavior in cells adapted to live in a multicellular assembly. If this is the case, one would expect that mutation in cancer disrupts functional mechanisms that suppress cell-level traits detrimental to multicellularity. Such mechanisms should have evolved with or after the emergence of multicellularity. This leads to two related, but distinct hypotheses: 1) Somatic mutations in cancer will occur in genes that are younger than the emergence of multicellularity (1000 million years [MY]); and 2) genes that are frequently mutated in cancer and whose mutations are functionally important for the emergence of the cancer phenotype evolved within the past 1000 million years, and thus would exhibit an age distribution that is skewed to younger genes. In order to investigate these hypotheses we estimated the evolutionary ages of all human genes and then studied the probability of mutation and their biological function in relation to their age and genomic location for both normal germline and cancer contexts. We observed that under a model of uniform random mutation across the genome, controlled for gene size, genes less than 500 MY were more frequently mutated in both cases. Paradoxically, causal genes, defined in the COSMIC Cancer Gene Census, were depleted in this age group. When we used functional enrichment analysis to explain this unexpected result we discovered that COSMIC genes with recessive disease phenotypes were enriched for DNA repair and cell cycle control. The non-mutated genes in these pathways are orthologous to those underlying stress-induced mutation in bacteria, which results in the clustering of single nucleotide variations. COSMIC genes were less common in regions where the probability of observing mutational clusters is high, although they are approximately 2-fold more likely to harbor mutational clusters compared to other human genes. Our results suggest this ancient mutational response to stress that evolved among prokaryotes was co-opted to maintain diversity in the germline and immune system, while the original phenotype is restored in cancer. Reversion to a stress-induced mutational response is a hallmark of cancer that allows for effectively searching “protected” genome space where genes causally implicated in cancer are located and underlies the high adaptive potential and concomitant therapeutic resistance that is characteristic of cancer.

Clusters of Multiple Mutations: Incidence and Molecular Mechanisms

It has been long understood that mutation distribution is not completely random across genomic space and in time. Indeed, recent surprising discoveries identified multiple simultaneous mutations occurring in tiny regions within chromosomes while the rest of the genome remains relatively mutation-free. Mechanistic elucidation of these phenomena, called mutation showers, mutation clusters, or kataegis, in parallel with findings of abundant clustered mutagenesis in cancer genomes, is ongoing. So far, the combination of factors most important for clustered mutagenesis is the induction of DNA lesions within unusually long and persistent single-strand DNA intermediates. In addition to being a fascinating phenomenon, clustered mutagenesis also became an indispensable tool for identifying a previously unrecognized major source of mutation in cancer, APOBEC cytidine deaminases. Future research on clustered mutagenesis may shed light onto important mechanistic details of genome maintenance, with potentially profound implications for human health.

Amino Acid Change in an Orchid Desaturase Enables Mimicry of the Pollinator's Sex Pheromone

Mimicry illustrates the power of selection to produce phenotypic convergence in biology [1]. A striking example is the imitation of female insects by plants that are pollinated by sexual deception of males of the same insect species [2-4]. This involves mimicry of visual, tactile, and chemical signals of females [2-7], especially their sex pheromones [8-11]. The Mediterranean orchid Ophrys exaltata employs chemical mimicry of cuticular hydrocarbons, particularly the 7-alkenes, in an insect sex pheromone to attract and elicit mating behavior in its pollinators, males of the cellophane bee Colletes cunicularius [11-13]. A difference in alkene double-bond positions is responsible for reproductive isolation between O. exaltata and closely related species, such as O. sphegodes [13-16]. We show that these 7-alkenes are likely determined by the action of the stearoyl-acyl-carrier-protein desaturase (SAD) homolog SAD5. After gene duplication, changes in subcellular localization relative to the ancestral housekeeping desaturase may have allowed proto-SAD5's reaction products to undergo further biosynthesis to both 7- and 9-alkenes. Such ancestral coproduction of two alkene classes may have led to pollinator-mediated deleterious pleiotropy. Despite possible evolutionary intermediates with reduced activity, amino acid changes at the bottom of the substrate-binding cavity have conferred enzyme specificity for 7-alkene biosynthesis by preventing the binding of longer-chained fatty acid (FA) precursors by the enzyme. This change in desaturase function enabled the orchid to perfect its chemical mimicry of pollinator sex pheromones by escape from deleterious pleiotropy, supporting a role of pleiotropy in determining the possible trajectories of adaptive evolution.

DNA polymerase ζ-dependent lesion bypass in Saccharomyces cerevisiae is accompanied by error-prone copying of long stretches of adjacent DNA

Translesion synthesis (TLS) helps cells to accomplish chromosomal replication in the presence of unrepaired DNA lesions. In eukaryotes, the bypass of most lesions involves a nucleotide insertion opposite the lesion by either a replicative or a specialized DNA polymerase, followed by extension of the resulting distorted primer terminus by DNA polymerase ζ (Polζ). The subsequent events leading to disengagement of the error-prone Polζ from the primer terminus and its replacement with an accurate replicative DNA polymerase remain largely unknown. As a first step toward understanding these events, we aimed to determine the length of DNA stretches synthesized in an error-prone manner during the Polζ-dependent lesion bypass. We developed new in vivo assays to identify the products of mutagenic TLS through a plasmid-borne tetrahydrofuran lesion and a UV-induced chromosomal lesion. We then surveyed the region downstream of the lesion site (in respect to the direction of TLS) for the presence of mutations indicative of an error-prone polymerase activity. The bypass of both lesions was associated with an approximately 300,000-fold increase in the mutation rate in the adjacent DNA segment, in comparison to the mutation rate during normal replication. The hypermutated tract extended 200 bp from the lesion in the plasmid-based assay and as far as 1 kb from the lesion in the chromosome-based assay. The mutation rate in this region was similar to the rate of errors produced by purified Polζ during copying of undamaged DNA in vitro. Further, no mutations downstream of the lesion were observed in rare TLS products recovered from Polζ-deficient cells. This led us to conclude that error-prone Polζ synthesis continues for several hundred nucleotides after the lesion bypass is completed. These results provide insight into the late steps of TLS and show that error-prone TLS tracts span a substantially larger region than previously appreciated.

Genomic instability is associated with multiple genetic diseases. Endogenous and exogenous DNA-damaging factors constitute a major source of genomic instability. Mutations occur when DNA lesions are bypassed by specialized translesion synthesis (TLS) DNA polymerases that are less accurate than the normal replicative polymerases. The discovery of the remarkable infidelity of the TLS enzymes at the turn of the century immediately suggested that their contribution to replication must be tightly restricted to sites of DNA damage to avoid excessive mutagenesis. The actual extent of error-prone synthesis that accompanies TLS in vivo has never been estimated. We describe a novel genetic approach to measure the length of DNA synthesized by TLS polymerases upon their recruitment to sites of DNA damage. We show that stretches of error-prone synthesis associated with the bypass of a single damaged nucleotide span at least 200 and sometimes up to 1,000 nucleotide-long segments, resulting in more than a 300,000-fold increase in mutagenesis in the surrounding region. We speculate that processive synthesis of long DNA stretches by error-prone polymerases could contribute to clustered mutagenesis, a phenomenon that allows for rapid genome changes without significant loss of fitness and plays an important role in tumorigenesis, the immune response and adaptation.

Break-induced replication is a source of mutation clusters underlying kataegis

Clusters of simultaneous multiple mutations can be a source of rapid change during carcinogenesis and evolution. Such mutation clusters have been recently shown to originate from DNA damage within long single-stranded DNA (ssDNA) formed at resected double-strand breaks and dysfunctional replication forks. Here, we identify double-strand break (DSB)-induced replication (BIR) as another powerful source of mutation clusters that formed in nearly half of wild-type yeast cells undergoing BIR in the presence of alkylating damage. Clustered mutations were primarily formed along the track of DNA synthesis and were frequently associated with additional breakage and rearrangements. Moreover, the base specificity, strand coordination, and strand bias of the mutation spectrum were consistent with mutations arising from damage in persistent ssDNA stretches within unconventional replication intermediates. Altogether, these features closely resemble kataegic events in cancers, suggesting that replication intermediates during BIR may be the most prominent source of mutation clusters across species.

Clustered and genome-wide transient mutagenesis in human cancers: Hypermutation without permanent mutators or loss of fitness

The gain of a selective advantage in cancer as well as the establishment of complex traits during evolution require multiple genetic alterations, but how these mutations accumulate over time is currently unclear. There is increasing evidence that a mutator phenotype perpetuates the development of many human cancers. While in some cases the increased mutation rate is the result of a genetic disruption of DNA repair and replication or environmental exposures, other evidence suggests that endogenous DNA damage induced by AID/APOBEC cytidine deaminases can result in transient localized hypermutation generating simultaneous, closely spaced (i.e. "clustered") multiple mutations. Here, we discuss mechanisms that lead to mutation cluster formation, the biological consequences of their formation in cancer and evidence suggesting that APOBEC mutagenesis can also occur genome-wide. This raises the possibility that dysregulation of these enzymes may enable rapid malignant transformation by increasing mutation rates without the loss of fitness associated with permanent mutators.