Evolutionary biochemistry: revealing the historical and physical causes of protein properties

Epistasis facilitates functional evolution in an ancient transcription factor

A protein's genetic architecture - the set of causal rules by which its sequence produces its functions - also determines its possible evolutionary trajectories. Prior research has proposed that the genetic architecture of proteins is very complex, with pervasive epistatic interactions that constrain evolution and make function difficult to predict from sequence. Most of this work has analyzed only the direct paths between two proteins of interest - excluding the vast majority of possible genotypes and evolutionary trajectories - and has considered only a single protein function, leaving unaddressed the genetic architecture of functional specificity and its impact on the evolution of new functions. Here, we develop a new method based on ordinal logistic regression to directly characterize the global genetic determinants of multiple protein functions from 20-state combinatorial deep mutational scanning (DMS) experiments. We use it to dissect the genetic architecture and evolution of a transcription factor's specificity for DNA, using data from a combinatorial DMS of an ancient steroid hormone receptor's capacity to activate transcription from two biologically relevant DNA elements. We show that the genetic architecture of DNA recognition consists of a dense set of main and pairwise effects that involve virtually every possible amino acid state in the protein-DNA interface, but higher-order epistasis plays only a tiny role. Pairwise interactions enlarge the set of functional sequences and are the primary determinants of specificity for different DNA elements. They also massively expand the number of opportunities for single-residue mutations to switch specificity from one DNA target to another. By bringing variants with different functions close together in sequence space, pairwise epistasis therefore facilitates rather than constrains the evolution of new functions.

Empowering Protein Engineering through Recombination of Beneficial Substitutions

Directed evolution stands as a seminal technology for generating novel protein functionalities, a cornerstone in biocatalysis, metabolic engineering, and synthetic biology. Today, with the development of various mutagenesis methods and advanced analytical machines, the challenge of diversity generation and high-throughput screening platforms is largely solved, and one of the remaining challenges is: how to empower the potential of single beneficial substitutions with recombination to achieve the epistatic effect. This review overviews experimental and computer-assisted recombination methods in protein engineering campaigns. In addition, integrated and machine learning-guided strategies were highlighted to discuss how these recombination approaches contribute to generating the screening library with better diversity, coverage, and size. A decision tree was finally summarized to guide the further selection of proper recombination strategies in practice, which was beneficial for accelerating protein engineering.

Theoretical Improvements in Enzyme Efficiency Associated with Noisy Rate Constants and Increased Dissipation

Previous studies have revealed the extraordinarily large catalytic efficiency of some enzymes. High catalytic proficiency is an essential accomplishment of biological evolution. Natural selection led to the increased turnover number, kcat, and enzyme efficiency, kcat/KM, of uni-uni enzymes, which convert a single substrate into a single product. We added or multiplied random noise with chosen rate constants to explore the correlation between dissipation and catalytic efficiency for ten enzymes: beta-galactosidase, glucose isomerase, β-lactamases from three bacterial strains, ketosteroid isomerase, triosephosphate isomerase, and carbonic anhydrase I, II, and T200H. Our results highlight the role of biological evolution in accelerating thermodynamic evolution. The catalytic performance of these enzymes is proportional to overall entropy production-the main parameter from irreversible thermodynamics. That parameter is also proportional to the evolutionary distance of β-lactamases PC1, RTEM, and Lac-1 when natural or artificial evolution produces the optimal or maximal possible catalytic efficiency. De novo enzyme design and attempts to speed up the rate-limiting catalytic steps may profit from the described connection between kinetics and thermodynamics.

Comparative analysis of reconstructed ancestral proteins with their extant counterparts suggests primitive life had an alkaline habitat

To understand the origin and early evolution of life it is crucial to establish characteristics of the primordial environment that facilitated the emergence and evolution of life. One important environmental factor is the pH of the primordial environment. Here, we assessed the pH-dependent thermal stabilities of previously reconstructed ancestral nucleoside diphosphate kinases and ribosomal protein uS8s. The selected proteins were likely to be present in ancient organisms such as the last common ancestor of bacteria and that of archaea. We also assessed the thermal stability of homologous proteins from extant acidophilic, neutralophilic, and alkaliphilic microorganisms as a function of pH. Our results indicate that the reconstructed ancestral proteins are more akin to those of extant alkaliphilic bacteria, which display greater stability under alkaline conditions. These findings suggest that the common ancestors of bacterial and archaeal species thrived in an alkaline environment. Moreover, we demonstrate the reconstruction method employed in this study is a valuable technique for generating alkali-tolerant proteins that can be used in a variety of biotechnological and environmental applications.

Designing a novel (R)-ω-transaminase for asymmetric synthesis of sitagliptin intermediate via motif swapping and semi-rational design

The application of (R)-ω-transaminases as biocatalysts for chiral amine synthesis has been hampered by inadequate stereoselectivity and narrow substrate spectrum. Herein, an effective evolution strategy for (R)-ω-transaminase designing for the asymmetric synthesis of sitagliptin intermediate is presented. Since natural transaminases lack activity toward bulky prositagliptin ketone, transaminase scaffolds with catalytic machinery and activity toward the truncated prositagliptin ketone were firstly screened based on substrate walking principle. A transaminase chimera was established synchronously conferring catalytic activity and (R)-selectivity toward prositagliptin ketone through motif swapping, followed by stepwise evolution. The process resulted in a "best" engineered variant MwTAM8, which exhibited 79.2-fold higher activity than the chimeric scaffold MwTAMc. Structural analysis revealed that the heightened activity is mainly due to the enlarged and adaptive substrate pocket and tunnel. The novel (R)-transaminase exhibited unsatisfied industrial operation stability, which is expected to further modify the protein to enhance its tolerance to temperature, pH, and organic solvents to meet sustainable industrial demands. This study underscores a useful evolution strategy of engineering biocatalysts to confer new properties and functions on enzymes for synthesizing high-value drug intermediates.

Evolutionary paths that link orthogonal pairs of binding proteins

Some protein binding pairs exhibit extreme specificities that functionally insulate them from homologs. Such pairs evolve mostly by accumulating single-point mutations, and mutants are selected if their affinity exceeds the threshold required for function1-4. Thus, homologous and high-specificity binding pairs bring to light an evolutionary conundrum: how does a new specificity evolve while maintaining the required affinity in each intermediate5,6? Until now, a fully functional single-mutation path that connects two orthogonal pairs has only been described where the pairs were mutationally close thus enabling experimental enumeration of all intermediates2. We present an atomistic and graph-theoretical framework for discovering low molecular strain single-mutation paths that connect two extant pairs, enabling enumeration beyond experimental capability. We apply it to two orthogonal bacterial colicin endonuclease-immunity pairs separated by 17 interface mutations7. We were not able to find a strain-free and functional path in the sequence space defined by the two extant pairs. But including mutations that bridge amino acids that cannot be exchanged through single-nucleotide mutations led us to a strain-free 19-mutation trajectory that is completely viable in vivo. Our experiments show that the specificity switch is remarkably abrupt, resulting from only one radical mutation on each partner. Furthermore, each of the critical specificity-switch mutations increases fitness, demonstrating that functional divergence could be driven by positive Darwinian selection. These results reveal how even radical functional changes in an epistatic fitness landscape may evolve.

Impact of ancestral sequence reconstruction on mechanistic and structural enzymology

Ancestral sequence reconstruction (ASR) provides insight into the changes within a protein sequence across evolution. More specifically, it can illustrate how specific amino acid changes give rise to different phenotypes within a protein family. Over the last few decades it has established itself as a powerful technique for revealing molecular common denominators that govern enzyme function. Here, we describe the strength of ASR in unveiling catalytic mechanisms and emerging phenotypes for a range of different proteins, also highlighting biotechnological applications the methodology can provide.

Infer global, predict local: Quantity-relevance trade-off in protein fitness predictions from sequence data

Predicting the effects of mutations on protein function is an important issue in evolutionary biology and biomedical applications. Computational approaches, ranging from graphical models to deep-learning architectures, can capture the statistical properties of sequence data and predict the outcome of high-throughput mutagenesis experiments probing the fitness landscape around some wild-type protein. However, how the complexity of the models and the characteristics of the data combine to determine the predictive performance remains unclear. Here, based on a theoretical analysis of the prediction error, we propose descriptors of the sequence data, characterizing their quantity and relevance relative to the model. Our theoretical framework identifies a trade-off between these two quantities, and determines the optimal subset of data for the prediction task, showing that simple models can outperform complex ones when inferred from adequately-selected sequences. We also show how repeated subsampling of the sequence data is informative about how much epistasis in the fitness landscape is not captured by the computational model. Our approach is illustrated on several protein families, as well as on in silico solvable protein models.

Marginal specificity in protein interactions constrains evolution of a paralogous family

The evolution of novel functions in biology relies heavily on gene duplication and divergence, creating large paralogous protein families. Selective pressure to avoid detrimental cross-talk often results in paralogs that exhibit exquisite specificity for their interaction partners. But how robust or sensitive is this specificity to mutation? Here, using deep mutational scanning, we demonstrate that a paralogous family of bacterial signaling proteins exhibits marginal specificity, such that many individual substitutions give rise to substantial cross-talk between normally insulated pathways. Our results indicate that sequence space is locally crowded despite overall sparseness, and we provide evidence that this crowding has constrained the evolution of bacterial signaling proteins. These findings underscore how evolution selects for "good enough" rather than optimized phenotypes, leading to restrictions on the subsequent evolution of paralogs.

A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spike

A major challenge in understanding SARS-CoV-2 evolution is interpreting the antigenic and functional effects of emerging mutations in the viral spike protein. Here, we describe a deep mutational scanning platform based on non-replicative pseudotyped lentiviruses that directly quantifies how large numbers of spike mutations impact antibody neutralization and pseudovirus infection. We apply this platform to produce libraries of the Omicron BA.1 and Delta spikes. These libraries each contain ∼7,000 distinct amino acid mutations in the context of up to ∼135,000 unique mutation combinations. We use these libraries to map escape mutations from neutralizing antibodies targeting the receptor-binding domain, N-terminal domain, and S2 subunit of spike. Overall, this work establishes a high-throughput and safe approach to measure how ∼105 combinations of mutations affect antibody neutralization and spike-mediated infection. Notably, the platform described here can be extended to the entry proteins of many other viruses.

Structural evolution of an amphibian-specific globin: A computational evolutionary biochemistry approach

Studies on the globin family are continuously revealing insights into the mechanisms of gene and protein evolution. The rise of a new globin gene type in Pelobatoidea and Neobatrachia (Amphibia:Anura) from an α-globin precursor provides the opportunity to investigate the genetic and physical mechanisms underlying the origin of new protein structural and functional properties. This amphibian-specific globin (globin A/GbA) discovered in the heart of Rana catesbeiana is a monomer. As the ancestral oligomeric state of α-globins is a homodimer, we inferred that the ancestral state was lost somewhere in the GbA lineage. Here, we combined computational molecular evolution with structural bioinformatics to determine the extent to which the loss of the homodimeric state is pervasive in the GbA clade. We also characterized the loci of GbA genes in Bufo bufo. We found two GbA clades in Neobatrachia. One was deleted in Ranidae, but retained and expanded to yield a new globin cluster in Bufonidae species. Loss of the ancestral oligomeric state seems to be pervasive in the GbA clade. However, a taxonomic sampling that includes more Pelobatoidea, as well as early Neobatrachia, lineages would be necessary to determine the oligomeric state of the last common ancestor of all GbA. The evidence presented here points out a possible loss of oligomerization in Pelobatoidea GbA as a result of amino acid substitutions that weaken the homodimeric state. In contrast, the loss of oligomerization in both Neobatrachia GbA clades was linked to independent deletions that disrupted many packing contacts at the homodimer interface.

Structure-informed microbial population genetics elucidate selective pressures that shape protein evolution

Comprehensive sampling of natural genetic diversity with metagenomics enables highly resolved insights into the interplay between ecology and evolution. However, resolving adaptive, neutral, or purifying processes of evolution from intrapopulation genomic variation remains a challenge, partly due to the sole reliance on gene sequences to interpret variants. Here, we describe an approach to analyze genetic variation in the context of predicted protein structures and apply it to a marine microbial population within the SAR11 subclade 1a.3.V, which dominates low-latitude surface oceans. Our analyses reveal a tight association between genetic variation and protein structure. In a central gene in nitrogen metabolism, we observe decreased occurrence of nonsynonymous variants from ligand-binding sites as a function of nitrate concentrations, revealing genetic targets of distinct evolutionary pressures maintained by nutrient availability. Our work yields insights into the governing principles of evolution and enables structure-aware investigations of microbial population genetics.

Ancestral Sequence Reconstruction of the Ribosomal Protein uS8 and Reduction of Amino Acid Usage to a Smaller Alphabet

Understanding the origin and early evolution of proteins is important for unveiling how the RNA world developed into an RNA-protein world. Because the composition of organic molecules in the Earth's primitive environment was plausibly not as diverse as today, the number of different amino acids used in early protein synthesis is likely to be substantially less than the current 20 proteinogenic residues. In this study, we have explored the thermal stability and RNA binding of ancestral variants of the ribosomal protein uS8 constructed from a reduced-alphabet of amino acids. First, we built a phylogenetic tree based on the amino acid sequences of uS8 from multiple extant organisms and used the tree to infer two plausible amino acid sequences corresponding to the last bacterial common ancestor of uS8. Both ancestral proteins were thermally stable and bound to an RNA fragment. By eliminating individual amino acid letters and monitoring thermal stability and RNA binding in the resulting proteins, we reduced the size of the amino acid set constituting one of the ancestral proteins, eventually finding that convergent sequences consisting of 15- or 14-amino acid alphabets still folded into stable structures that bound to the RNA fragment. Furthermore, a simplified variant reconstructed from a 13-amino-acid alphabet retained affinity for the RNA fragment, although it lost conformational stability. Collectively, RNA-binding activity may be achieved with a subset of the current 20 amino acids, raising the possibility of a simpler composition of RNA-binding proteins in the earliest stage of protein evolution.

Evolution and molecular basis of a novel allosteric property of crocodilian hemoglobin

The extraordinary breath-hold diving capacity of crocodilians has been ascribed to a unique mode of allosterically regulating hemoglobin (Hb)-oxygenation in circulating red blood cells. We investigated the origin and mechanistic basis of this novel biochemical phenomenon by performing directed mutagenesis experiments on resurrected ancestral Hbs. Comparisons of Hb function between the common ancestor of archosaurs (the group that includes crocodilians and birds) and the last common ancestor of modern crocodilians revealed that regulation of Hb-O2 affinity via allosteric binding of bicarbonate ions represents a croc-specific innovation that evolved in combination with the loss of allosteric regulation by ATP binding. Mutagenesis experiments revealed that evolution of the novel allosteric function in crocodilians and the concomitant loss of ancestral function were not mechanistically coupled and were caused by different sets of substitutions. The gain of bicarbonate sensitivity in crocodilian Hb involved the direct effect of few amino acid substitutions at key sites in combination with indirect effects of numerous other substitutions at structurally disparate sites. Such indirect interaction effects suggest that evolution of the novel protein function was conditional on neutral mutations that produced no adaptive benefit when they first arose but that contributed to a permissive background for subsequent function-altering mutations at other sites. Due to the context dependence of causative substitutions, the unique allosteric properties of crocodilian Hb cannot be easily transplanted into divergent homologs of other species.

Amino acid (acyl carrier protein) ligase-associated biosynthetic gene clusters reveal unexplored biosynthetic potential

This study aimed to evaluate the postulated cellular function of a novel family of amino acid (acyl carrier protein) ligases (AALs) in natural product biosynthesis. Here, we analyzed the manually curated, putative, aal-associated natural product biosynthetic gene clusters (NP BGCs) using two computational platforms for NP prediction, antiSMASH-BiG-SCAPE-CORASON and DeepBGC. The detected BGCs included a diversity of type I polyketide/nonribosomal peptide (PKS/NRPS) hybrid BGCs, exemplified by the guadinomine BGC, which suggested a dedicated function of AALs in the biosynthesis of rare (2S)-aminomalonyl-ACP extension units. Besides modular PKS/NRPSs and NRPSs, AAL-associated BGCs were predicted to assemble arylpolyenes, ladderane lipids, phosphonates, aminoglycosides, β-lactones, and thioamides of both nonribosomal and ribosomal origins. Additionally, we revealed a frequent association of AALs with putative, seldom observed transglutaminase-like and BtrH-like transferases of the cysteine protease superfamily, which may form larger families of ACP-dependent amide bond catalysts used in NP synthesis. Our results disclosed an exceptional chemical novelty and biosynthetic potential of the AAL-associated BGCs in NP biosynthesis. The presented in silico evidence supports the initial hypothesis and provides an important foundation for future experimental studies aimed at discovering novel pharmaceutically relevant active compounds.

Probing the origin of prion protein misfolding via reconstruction of ancestral proteins

Prion diseases are fatal neurodegenerative diseases caused by pathogenic misfolding of the prion protein, PrP. They are transmissible between hosts, and sometimes between different species, as with transmission of bovine spongiform encephalopathy to humans. Although PrP is found in a wide range of vertebrates, prion diseases are seen only in certain mammals, suggesting that infectious misfolding was a recent evolutionary development. To explore when PrP acquired the ability to misfold infectiously, we reconstructed the sequences of ancestral versions of PrP from the last common primate, primate-rodent, artiodactyl, placental, bird, and amniote. Recombinant ancestral PrPs were then tested for their ability to form β-sheet aggregates, either spontaneously or when seeded with infectious prion strains from human, cervid, or rodent species. The ability to aggregate developed after the oldest ancestor (last common amniote), and aggregation capabilities diverged along evolutionary pathways consistent with modern-day susceptibilities. Ancestral bird PrP could not be seeded with modern-day prions, just as modern-day birds are resistant to prion disease. Computational modeling of structures suggested that differences in helix 2 could account for the resistance of ancestral bird PrP to seeding. Interestingly, ancestral primate PrP could be converted by all prion seeds, including both human and cervid prions, raising the possibility that species descended from an ancestral primate have retained the susceptibility to conversion by cervid prions. More generally, the results suggest that susceptibility to prion disease emerged prior to ~100 million years ago, with placental mammals possibly being generally susceptible to disease.

A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spike

A major challenge in understanding SARS-CoV-2 evolution is interpreting the antigenic and functional effects of emerging mutations in the viral spike protein. Here we describe a new deep mutational scanning platform based on non-replicative pseudotyped lentiviruses that directly quantifies how large numbers of spike mutations impact antibody neutralization and pseudovirus infection. We demonstrate this new platform by making libraries of the Omicron BA.1 and Delta spikes. These libraries each contain ~7000 distinct amino-acid mutations in the context of up to ~135,000 unique mutation combinations. We use these libraries to map escape mutations from neutralizing antibodies targeting the receptor binding domain, N-terminal domain, and S2 subunit of spike. Overall, this work establishes a high-throughput and safe approach to measure how ~10 5 combinations of mutations affect antibody neutralization and spike-mediated infection. Notably, the platform described here can be extended to the entry proteins of many other viruses.

Intragenic compensation through the lens of deep mutational scanning

A significant fraction of mutations in proteins are deleterious and result in adverse consequences for protein function, stability, or interaction with other molecules. Intragenic compensation is a specific case of positive epistasis when a neutral missense mutation cancels effect of a deleterious mutation in the same protein. Permissive compensatory mutations facilitate protein evolution, since without them all sequences would be extremely conserved. Understanding compensatory mechanisms is an important scientific challenge at the intersection of protein biophysics and evolution. In human genetics, intragenic compensatory interactions are important since they may result in variable penetrance of pathogenic mutations or fixation of pathogenic human alleles in orthologous proteins from related species. The latter phenomenon complicates computational and clinical inference of an allele's pathogenicity. Deep mutational scanning is a relatively new technique that enables experimental studies of functional effects of thousands of mutations in proteins. We review the important aspects of the field and discuss existing limitations of current datasets. We reviewed ten published DMS datasets with quantified functional effects of single and double mutations and described rates and patterns of intragenic compensation in eight of them.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-022-01005-w.

Saturation mutagenesis of a predicted ancestral Syk-family kinase

Many tyrosine kinases cannot be expressed readily in Escherichia coli, limiting facile production of these proteins for biochemical experiments. We used ancestral sequence reconstruction to generate a spleen tyrosine kinase (Syk) variant that can be expressed in bacteria and purified in soluble form, unlike the human members of this family (Syk and zeta-chain-associated protein kinase of 70 kDa [ZAP-70]). The catalytic activity, substrate specificity, and regulation by phosphorylation of this Syk variant are similar to the corresponding properties of human Syk and ZAP-70. Taking advantage of the ability to express this novel Syk-family kinase in bacteria, we developed a two-hybrid assay that couples the growth of E. coli in the presence of an antibiotic to successful phosphorylation of a bait peptide by the kinase. Using this assay, we screened a site-saturation mutagenesis library of the kinase domain of this reconstructed Syk-family kinase. Sites of loss-of-function mutations identified in the screen correlate well with residues established previously as critical to function and/or structure in protein kinases. We also identified activating mutations in the regulatory hydrophobic spine and activation loop, which are within key motifs involved in kinase regulation. Strikingly, one mutation in an ancestral Syk-family variant increases the soluble expression of the protein by 75-fold. Thus, through ancestral sequence reconstruction followed by deep mutational scanning, we have generated Syk-family kinase variants that can be expressed in bacteria with very high yield.

Energy landscape reshaped by strain-specific mutations underlies epistasis in NS1 evolution of influenza A virus

Elucidating how individual mutations affect the protein energy landscape is crucial for understanding how proteins evolve. However, predicting mutational effects remains challenging because of epistasis—the nonadditive interactions between mutations. Here, we investigate the biophysical mechanism of strain-specific epistasis in the nonstructural protein 1 (NS1) of influenza A viruses (IAVs). We integrate structural, kinetic, thermodynamic, and conformational dynamics analyses of four NS1s of influenza strains that emerged between 1918 and 2004. Although functionally near-neutral, strain-specific NS1 mutations exhibit long-range epistatic interactions with residues at the p85β-binding interface. We reveal that strain-specific mutations reshaped the NS1 energy landscape during evolution. Using NMR spin dynamics, we find that the strain-specific mutations altered the conformational dynamics of the hidden network of tightly packed residues, underlying the evolution of long-range epistasis. This work shows how near-neutral mutations silently alter the biophysical energy landscapes, resulting in diverse background effects during molecular evolution.

Influenza A virus (IAV) nonstructural protein 1 (NS1) is a multifunctional virulence factor that interacts with several host factors such as phosphatidylinositol-3-kinase (PI3K). NS1 binds specifically to the p85β regulatory subunit of PI3K and subsequently activates PI3K signaling. Here, Kim et al. show that functionally near-neutral, strain-specific NS1 mutations lead to variations in binding kinetics to p85β exhibit long-range epistatic interactions. Applying NMR they provide evidence that the structural dynamics of the NS1 hydrophobic core have evolved over time and contributed to epistasis.

Genetic diversity loss in the Anthropocene

Anthropogenic habitat loss and climate change are reducing species' geographic ranges, increasing extinction risk and losses of species' genetic diversity. Although preserving genetic diversity is key to maintaining species' adaptability, we lack predictive tools and global estimates of genetic diversity loss across ecosystems. We introduce a mathematical framework that bridges biodiversity theory and population genetics to understand the loss of naturally occurring DNA mutations with decreasing habitat. By analyzing genomic variation of 10,095 georeferenced individuals from 20 plant and animal species, we show that genome-wide diversity follows a mutations-area relationship power law with geographic area, which can predict genetic diversity loss from local population extinctions. We estimate that more than 10% of genetic diversity may already be lost for many threatened and nonthreatened species, surpassing the United Nations' post-2020 targets for genetic preservation.

Climate change, human health, and the exposome: Utilizing OMIC technologies to navigate an era of uncertainty

Climate change is an anthropogenic phenomenon that is alarming scientists and non-scientists alike. The emission of greenhouse gases is causing the temperature of the earth to rise and this increase is accompanied by a multitude of climate change-induced environmental exposures with potential health impacts. Tracking human exposure has been a major research interest of scientists worldwide. This has led to the development of exposome studies that examine internal and external individual exposures over their lifetime and correlate them to health. The monitoring of health has also benefited from significant technological advances in the field of "omics" technologies that analyze physiological changes on the nucleic acid, protein, and metabolism levels, among others. In this review, we discuss various climate change-induced environmental exposures and their potential health implications. We also highlight the potential integration of the technological advancements in the fields of exposome tracking, climate monitoring, and omics technologies shedding light on important questions that need to be answered.

Exploiting spatial dimensions to enable parallelized continuous directed evolution

Current strategies to improve the throughput of continuous directed evolution technologies often involve complex mechanical fluid‐controlling system or robotic platforms, which limits their popularization and application in general laboratories. Inspired by our previous study on bacterial range expansion, in this study, we report a system termed SPACE for rapid and extensively parallelizable evolution of biomolecules by introducing spatial dimensions into the landmark phage‐assisted continuous evolution system. Specifically, M13 phages and chemotactic Escherichia coli cells were closely inoculated onto a semisolid agar. The phages came into contact with the expanding front of the bacterial range, and then comigrated with the bacteria. This system leverages competition over space, wherein evolutionary progress is closely associated with the production of spatial patterns, allowing the emergence of improved or new protein functions. In a prototypical problem, SPACE remarkably simplified the process and evolved the promoter recognition of T7 RNA polymerase (RNAP) to a library of 96 random sequences in parallel. These results establish SPACE as a simple, easy to implement, and massively parallelizable platform for continuous directed evolution in general laboratories.

Genetics of adaptation

The rediscovery of Mendel’s work showing that the heredity of phenotypes is controlled by discrete genes was followed by the reconciliation of Mendelian genetics with evolution by natural selection in the middle of the last century with the Modern Synthesis. In the past two decades, dramatic advances in genomic methods have facilitated the identification of the loci, genes, and even individual mutations that underlie phenotypic variants that are the putative targets of natural selection. Moreover, these methods have also changed how we can study adaptation by flipping the problem around, allowing us to first examine what loci show evidence of having been under selection, and then connecting these genetic variants to phenotypic variation. As a result, we now have an expanding list of actual genetic changes that underlie potentially adaptive phenotypic variation. Here, we synthesize how considering the effects of these adaptive loci in the context of cellular environments, genomes, organisms, and populations has provided new insights to the genetic architecture of adaptation.

Ancestrally reconstructed Von Willebrand Factor (vWF) reveals evidence for trench warfare coevolution between opossums and pit vipers

Opossums in the tribe Didelphini are resistant to pit viper venoms and are hypothesized to be coevolving with venomous snakes. Specifically, a protein involved in blood clotting (von Willebrand factor [vWF] which is targeted by snake venom C-type lectins [CTLs]) has been found to undergo rapid adaptive evolution in Didelphini. Several unique amino acid changes in vWF could explain their resistance; however, experimental evidence that these changes disrupt binding to venom CTLs was lacking. Furthermore, without explicit testing of ancestral phenotypes to reveal the mode of evolution, the assertion that this system represents an example of coevolution rather than noncoevolutionary adaptation remains unsupported. Using expressed vWF proteins and purified venom CTLs, we quantified binding affinity for vWF proteins from all resistant taxa, their venom-sensitive relatives, and their ancestors. We show that CTL-resistant vWF is present in opossums outside clade Didelphini and likely across a wider swath of opossums (family Didelphidae) than previously thought. Ancestral reconstruction and in vitro testing of vWF phenotypes in a clade of rapidly evolving opossums reveal a pattern consistent with trench warfare coevolution between opossums and their venomous snake prey.

Enhancing computational enzyme design by a maximum entropy strategy

Although computational enzyme design is of great importance, the advances utilizing physics-based approaches have been slow, and further progress is urgently needed. One promising direction is using machine learning, but such strategies have not been established as effective tools for predicting the catalytic power of enzymes. Here, we show that the statistical energy inferred from homologous sequences with the maximum entropy (MaxEnt) principle significantly correlates with enzyme catalysis and stability at the active site region and the more distant region, respectively. This finding decodes enzyme architecture and offers a connection between enzyme evolution and the physical chemistry of enzyme catalysis, and it deepens our understanding of the stability-activity trade-off hypothesis for enzymes. Overall, the strong correlations found here provide a powerful way of guiding enzyme design.

Resurrecting Enzymes by Ancestral Sequence Reconstruction

Ancestral Sequence Reconstruction (ASR) allows one to infer the sequences of extinct proteins using the phylogeny of extant proteins. It consists of disclosing the evolutionary history-i.e., the phylogeny-of a protein family of interest and then inferring the sequences of its ancestors-i.e., the nodes in the phylogeny. Assisted by gene synthesis, the selected ancestors can be resurrected in the lab and experimentally characterized. The crucial step to succeed with ASR is starting from a reliable phylogeny. At the same time, it is of the utmost importance to have a clear idea on the evolutionary history of the family under study and the events that influenced it. This allows us to implement ASR with well-defined hypotheses and to apply the appropriate experimental methods. In the last years, ASR has become popular to test hypotheses about the origin of functionalities, changes in activities, understanding physicochemical properties of proteins, among others. In this context, the aim of this chapter is to present the ASR approach applied to the reconstruction of enzymes-i.e., proteins with catalytic roles. The spirit of this contribution is to provide a basic, hands-to-work guide for biochemists and biologists who are unfamiliar with molecular phylogenetics.

Methodologies for Microbial Ancestral Sequence Reconstruction

The reconstruction of genetic material of ancestral organisms constitutes a powerful application of evolutionary biology. A fundamental step in this inference is the ancestral sequence reconstruction (ASR), which can be performed with diverse methodologies implemented in computer frameworks. However, most of these methodologies ignore evolutionary properties frequently observed in microbes, such as genetic recombination and complex selection processes, that can bias the traditional ASR. From a practical perspective, here I review methodologies for the reconstruction of ancestral DNA and protein sequences, with particular focus on microbes, and including biases, recommendations, and software implementations. I conclude that microbial ASR is a complex analysis that should be carefully performed and that there is a need for methods to infer more realistic ancestral microbial sequences.

Physics of biomolecular recognition and conformational dynamics

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

Evolutionary pathways to SARS-CoV-2 resistance are opened and closed by epistasis acting on ACE2

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infects a broader range of mammalian species than previously predicted, binding a diversity of angiotensin converting enzyme 2 (ACE2) orthologs despite extensive sequence divergence. Within this sequence degeneracy, we identify a rare sequence combination capable of conferring SARS-CoV-2 resistance. We demonstrate that this sequence was likely unattainable during human evolution due to deleterious effects on ACE2 carboxypeptidase activity, which has vasodilatory and cardioprotective functions in vivo. Across the 25 ACE2 sites implicated in viral binding, we identify 6 amino acid substitutions unique to mouse-one of the only known mammalian species resistant to SARS-CoV-2. Substituting human variants at these positions is sufficient to confer binding of the SARS-CoV-2 S protein to mouse ACE2, facilitating cellular infection. Conversely, substituting mouse variants into either human or dog ACE2 abolishes viral binding, diminishing cellular infection. However, these same substitutions decrease human ACE2 activity by 50% and are predicted as pathogenic, consistent with the extreme rarity of human polymorphisms at these sites. This trade-off can be avoided, however, depending on genetic background; if substituted simultaneously, these same mutations have no deleterious effect on dog ACE2 nor that of the rodent ancestor estimated to exist 70 million years ago. This genetic contingency (epistasis) may have therefore opened the road to resistance for some species, while making humans susceptible to viruses that use these ACE2 surfaces for binding, as does SARS-CoV-2.

Phylogenetic and Ancestral Sequence Reconstruction of SARS-CoV-2 Reveals Latent Capacity to Bind Human ACE2 Receptor

SARS-CoV-2 is a unique event, having emerged suddenly as a highly infectious viral pathogen for human populations. Previous phylogenetic analyses show its closest known evolutionary relative to be a virus detected in bats (RaTG13), with a common assumption that SARS-CoV-2 evolved from a zoonotic ancestor via recent genetic changes (likely in the Spike protein receptor-binding domain or RBD) that enabled it to infect humans. We used detailed phylogenetic analysis, ancestral sequence reconstruction, and in situ molecular dynamics simulations to examine the Spike-RBD's functional evolution, finding that the common ancestral virus with RaTG13, dating to no later than 2013, possessed high binding affinity to the human ACE2 receptor. This suggests that SARS-CoV-2 likely possessed a latent capacity to bind to human cellular targets (though this may not have been sufficient for successful infection) and emphasizes the importance of expanding efforts to catalog and monitor viruses circulating in both human and non-human populations.

Molecular basis for the evolved instability of a human G-protein coupled receptor

Membrane proteins are prone to misfolding and degradation. This is particularly true for mammalian forms of the gonadotropin-releasing hormone receptor (GnRHR). Although they function at the plasma membrane, mammalian GnRHRs accumulate within the secretory pathway. Their apparent instability is believed to have evolved through selection for attenuated GnRHR activity. Nevertheless, the molecular basis of this adaptation remains unclear. We show that adaptation coincides with a C-terminal truncation that compromises the translocon-mediated membrane integration of its seventh transmembrane domain (TM7). We also identify a series of polar residues in mammalian GnRHRs that compromise the membrane integration of TM2 and TM6. Reverting a lipid-exposed polar residue in TM6 to an ancestral hydrophobic residue restores expression with no impact on function. Evolutionary trends suggest variations in the polarity of this residue track with reproductive phenotypes. Our findings suggest that the marginal energetics of cotranslational folding can be exploited to tune membrane protein fitness.

Integral membrane proteins are prone to misfolding, especially mammalian gonadotropin-releasing hormone receptors (GnRHRs). Chamness et al. show that the evolved instability of mammalian GnRHRs stems from adaptive modifications that disrupt translocon-mediated membrane integration, suggesting that membrane protein misfolding can be exploited to tune fitness.

Evolutionary physiology at 30+: Has the promise been fulfilled?: Advances in Evolutionary Physiology: Advances in Evolutionary Physiology

Three decades ago, interactions between evolutionary biology and physiology gave rise to evolutionary physiology. This caused comparative physiologists to improve their research methods by incorporating evolutionary thinking. Simultaneously, evolutionary biologists began focusing more on physiological mechanisms that may help to explain constraints on and trade-offs during microevolutionary processes, as well as macroevolutionary patterns in physiological diversity. Here we argue that evolutionary physiology has yet to reach its full potential, and propose new avenues that may lead to unexpected advances. Viewing physiological adaptations in wild animals as potential solutions to human diseases offers enormous possibilities for biomedicine. New evidence of epigenetic modifications as mechanisms of phenotypic plasticity that regulate physiological traits may also arise in coming years, which may also represent an overlooked enhancer of adaptation via natural selection to explain physiological evolution. Synergistic interactions at these intersections and other areas will lead to a novel understanding of organismal biology.

Climbing Up and Down Binding Landscapes through Deep Mutational Scanning of Three Homologous Protein-Protein Complexes

Protein-protein interactions (PPIs) have evolved to display binding affinities that can support their function. As such, cognate and noncognate PPIs could be highly similar structurally but exhibit huge differences in binding affinities. To understand this phenomenon, we study three homologous protease-inhibitor PPIs that span 9 orders of magnitude in binding affinity. Using state-of-the-art methodology that combines protein randomization, affinity sorting, deep sequencing, and data normalization, we report quantitative binding landscapes consisting of ΔΔG_bind values for the three PPIs, gleaned from tens of thousands of single and double mutations. We show that binding landscapes of the three complexes are strikingly different and depend on the PPI evolutionary optimality. We observe different patterns of couplings between mutations for the three PPIs with negative and positive epistasis appearing most frequently at hot-spot and cold-spot positions, respectively. The evolutionary trends observed here are likely to be universal to other biological complexes in the cell.

Evolution of the folding landscape of effector caspases

Caspases are a family of cysteinyl proteases that control programmed cell death and maintain homeostasis in multicellular organisms. The caspase family is an excellent model to study protein evolution because all caspases are produced as zymogens (procaspases [PCPs]) that must be activated to gain full activity; the protein structures are conserved through hundreds of millions of years of evolution; and some allosteric features arose with the early ancestor, whereas others are more recent evolutionary events. The apoptotic caspases evolved from a common ancestor (CA) into two distinct subfamilies: monomers (initiator caspases) or dimers (effector caspases). Differences in activation mechanisms of the two subfamilies, and their oligomeric forms, play a central role in the regulation of apoptosis. Here, we examine changes in the folding landscape by characterizing human effector caspases and their CA. The results show that the effector caspases unfold by a minimum three-state equilibrium model at pH 7.5, where the native dimer is in equilibrium with a partially folded monomeric (PCP-7, CA) or dimeric (PCP-6) intermediate. In comparison, the unfolding pathway of PCP-3 contains both oligomeric forms of the intermediate. Overall, the data show that the folding landscape was first established with the CA and was retained for >650 million years. Partially folded monomeric or dimeric intermediates in the ancestral ensemble provide mechanisms for evolutionary changes that affect stability of extant caspases. The conserved folding landscape allows for the fine-tuning of enzyme stability in a species-dependent manner while retaining the overall caspase–hemoglobinase fold.

A functionally divergent intrinsically disordered region underlying the conservation of stochastic signaling

Stochastic signaling dynamics expand living cells' information processing capabilities. An increasing number of studies report that regulators encode information in their pulsatile dynamics. The evolutionary mechanisms that lead to complex signaling dynamics remain uncharacterized, perhaps because key interactions of signaling proteins are encoded in intrinsically disordered regions (IDRs), whose evolution is difficult to analyze. Here we focused on the IDR that controls the stochastic pulsing dynamics of Crz1, a transcription factor in fungi downstream of the widely conserved calcium signaling pathway. We find that Crz1 IDRs from anciently diverged fungi can all respond transiently to calcium stress; however, only Crz1 IDRs from the Saccharomyces clade support pulsatility, encode extra information, and rescue fitness in competition assays, while the Crz1 IDRs from distantly related fungi do none of the three. On the other hand, we find that Crz1 pulsing is conserved in the distantly related fungi, consistent with the evolutionary model of stabilizing selection on the signaling phenotype. Further, we show that a calcineurin docking site in a specific part of the IDRs appears to be sufficient for pulsing and show evidence for a beneficial increase in the relative calcineurin affinity of this docking site. We propose that evolutionary flexibility of functionally divergent IDRs underlies the conservation of stochastic signaling by stabilizing selection.

Evolutionary and functional lessons from human-specific amino acid substitution matrices

Human genetic variation in coding regions is fundamental to the study of protein structure and function. Most methods for interpreting missense variants consider substitution measures derived from homologous proteins across different species. In this study, we introduce human-specific amino acid (AA) substitution matrices that are based on genetic variations in the modern human population. We analyzed the frequencies of >4.8M single nucleotide variants (SNVs) at codon and AA resolution and compiled human-centric substitution matrices that are fundamentally different from classic cross-species matrices (e.g. BLOSUM, PAM). Our matrices are asymmetric, with some AA replacements showing significant directional preference. Moreover, these AA matrices are only partly predicted by nucleotide substitution rates. We further test the utility of our matrices in exposing functional signals of experimentally-validated protein annotations. A significant reduction in AA transition frequencies was observed across nine post-translational modification (PTM) types and four ion-binding sites. Our results propose a purifying selection signal in the human proteome across a diverse set of functional protein annotations and provide an empirical baseline for interpreting human genetic variation in coding regions.

Two NLR immune receptors acquired high-affinity binding to a fungal effector through convergent evolution of their integrated domain

A subset of plant NLR immune receptors carry unconventional integrated domains in addition to their canonical domain architecture. One example is rice Pik-1 that comprises an integrated heavy metal-associated (HMA) domain. Here, we reconstructed the evolutionary history of Pik-1 and its NLR partner, Pik-2, and tested hypotheses about adaptive evolution of the HMA domain. Phylogenetic analyses revealed that the HMA domain integrated into Pik-1 before Oryzinae speciation over 15 million years ago and has been under diversifying selection. Ancestral sequence reconstruction coupled with functional studies showed that two Pik-1 allelic variants independently evolved from a weakly binding ancestral state to high-affinity binding of the blast fungus effector AVR-PikD. We conclude that for most of its evolutionary history the Pik-1 HMA domain did not sense AVR-PikD, and that different Pik-1 receptors have recently evolved through distinct biochemical paths to produce similar phenotypic outcomes. These findings highlight the dynamic nature of the evolutionary mechanisms underpinning NLR adaptation to plant pathogens.

Two NLR immune receptors acquired high-affinity binding to a fungal effector through convergent evolution of their integrated domain

A subset of plant NLR immune receptors carry unconventional integrated domains in addition to their canonical domain architecture. One example is rice Pik-1 that comprises an integrated heavy metal-associated (HMA) domain. Here, we reconstructed the evolutionary history of Pik-1 and its NLR partner, Pik-2, and tested hypotheses about adaptive evolution of the HMA domain. Phylogenetic analyses revealed that the HMA domain integrated into Pik-1 before Oryzinae speciation over 15 million years ago and has been under diversifying selection. Ancestral sequence reconstruction coupled with functional studies showed that two Pik-1 allelic variants independently evolved from a weakly binding ancestral state to high-affinity binding of the blast fungus effector AVR-PikD. We conclude that for most of its evolutionary history the Pik-1 HMA domain did not sense AVR-PikD, and that different Pik-1 receptors have recently evolved through distinct biochemical paths to produce similar phenotypic outcomes. These findings highlight the dynamic nature of the evolutionary mechanisms underpinning NLR adaptation to plant pathogens.

Revenant: a database of resurrected proteins

Revenant is a database of resurrected proteins coming from extinct organisms. Currently, it contains a manually curated collection of 84 resurrected proteins derived from bibliographic data. Each protein is extensively annotated, including structural, biochemical and biophysical information. Revenant contains a browse capability designed as a timeline from where the different proteins can be accessed. The oldest Revenant entries are between 4200 and 3500 million years ago, while the younger entries are between 8.8 and 6.3 million years ago. These proteins have been resurrected using computational tools called ancestral sequence reconstruction techniques combined with wet-laboratory synthesis and expression. Resurrected proteins are commonly used, with a noticeable increase during the past years, to explore and test different evolutionary hypotheses such as protein stability, to explore the origin of new functions, to get biochemical insights into past metabolisms and to explore specificity and promiscuous behaviour of ancient proteins.

On the diversity of F420 -dependent oxidoreductases: A sequence- and structure-based classification

The F₄₂₀ deazaflavin cofactor is an intriguing molecule as it structurally resembles the canonical flavin cofactor, although behaves as a nicotinamide cofactor due to its obligate hydride-transfer reactivity and similar low redox potential. Since its discovery, numerous enzymes relying on it have been described. The known deazaflavoproteins are taxonomically restricted to Archaea and Bacteria. The biochemistry of the deazaflavoenzymes is diverse and they exhibit great structural variability. In this study a thorough sequence and structural homology evolutionary analysis was performed in order to generate an overarching classification of the F₄₂₀ -dependent oxidoreductases. Five different deazaflavoenzyme Classes (I-V) are described according to their structural folds as follows: Class I encompassing the TIM-barrel F₄₂₀ -dependent enzymes; Class II including the Rossmann fold F₄₂₀ -dependent enzymes; Class III comprising the β-roll F₄₂₀ -dependent enzymes; Class IV which exclusively gathers the SH3 barrel F₄₂₀ -dependent enzymes and Class V including the three layer ββα sandwich F₄₂₀ -dependent enzymes. This classification provides a framework for the identification and biochemical characterization of novel deazaflavoenzymes.

An Ancestry Perspective of the Evolution of PBS1 Proteins in Plants

The AVRPPHB SUSCEPTIBLE1 (PBS1) and RESISTANCE TO PSEUDOMONAS SYRINGAE 5 (RPS5) proteins are involved in signal transduction to evoke innate plant immune response. In Arabidopsis, PBS1 is cleaved by the AvrPphB (Pseudomonas phaseolicola Avirulence protein B) protease, activating RPS5 and turning in a hypersensitive response (HR). We searched for PBS1 orthologs to trace their origin and evolution. PBS1 orthologs were found in embryophytes and in other plant taxa but with lower similarity. PBS1 phylogenetic analysis indicates high divergence, suggesting that the decoy function described for Arabidopsis PBS1 might be associated with a small fraction of orthologs. Ancestral reconstruction analysis suggests an elevated diversity in the amino acid sequence within the described motifs. All the orthologs contain the conserved PBS1 kinase subdomains, whereas the cleavage motif is present in several embryophyte orthologs but absent in most other taxa. The putative resistance recognition motifs in PBS1 orthologs are highly diverse. PBS1 cleavage site motif is exposed in some 3D structure predictions, whereas it is not in others, suggesting different modes of regulation and functions in PBS1 orthologs. Our findings suggest that PBS1 originated in the lineage that gave rise to embryophytes, with the angiosperm sequences forming a separate clade from pteridophyte proteins.

Engineering the protein dynamics of an ancestral luciferase

Protein dynamics are often invoked in explanations of enzyme catalysis, but their design has proven elusive. Here we track the role of dynamics in evolution, starting from the evolvable and thermostable ancestral protein AncHLD-RLuc which catalyses both dehalogenase and luciferase reactions. Insertion-deletion (InDel) backbone mutagenesis of AncHLD-RLuc challenged the scaffold dynamics. Screening for both activities reveals InDel mutations localized in three distinct regions that lead to altered protein dynamics (based on crystallographic B-factors, hydrogen exchange, and molecular dynamics simulations). An anisotropic network model highlights the importance of the conformational flexibility of a loop-helix fragment of Renilla luciferases for ligand binding. Transplantation of this dynamic fragment leads to lower product inhibition and highly stable glow-type bioluminescence. The success of our approach suggests that a strategy comprising (i) constructing a stable and evolvable template, (ii) mapping functional regions by backbone mutagenesis, and (iii) transplantation of dynamic features, can lead to functionally innovative proteins.

Fundamentals to function: Quantitative and scalable approaches for measuring protein stability

Folding a linear chain of amino acids into a three-dimensional protein is a complex physical process that ultimately confers an impressive range of diverse functions. Although recent advances have driven significant progress in predicting three-dimensional protein structures from sequence, proteins are not static molecules. Rather, they exist as complex conformational ensembles defined by energy landscapes spanning the space of sequence and conditions. Quantitatively mapping the physical parameters that dictate these landscapes and protein stability is therefore critical to develop models that are capable of predicting how mutations alter function of proteins in disease and informing the design of proteins with desired functions. Here, we review the approaches that are used to quantify protein stability at a variety of scales, from returning multiple thermodynamic and kinetic measurements for a single protein sequence to yielding indirect insights into folding across a vast sequence space. The physical parameters derived from these approaches will provide a foundation for models that extend beyond the structural prediction to capture the complexity of conformational ensembles and, ultimately, their function.

The role of purifying selection in the origin and maintenance of complex function

Fitness contribution alone should not be the criterion of 'function' in molecular biology and genomics. Disagreement over the use of 'function' in molecular biology and genomics is still with us, almost eight years after publicity surrounding the Encyclopedia of DNA Elements project claimed that 80.4% of the human genome comprises "functional elements". Recent approaches attempt to resolve or reformulate this debate by redefining genomic 'function' in terms of current fitness contribution. In its favour, this redefinition for the genomic context is in apparent conformity with predominant experimental practices, especially in biomedical research, and with ascription of function by selective maintenance. We argue against approaches of this kind, however, on the grounds that they could be seen as non-Darwinian, and fail to properly account for the diversity of non-adaptive processes involved in the origin and maintenance of genomic complexity. We examine cases of molecular and organismal complexity that arise neutrally, showing how purifying selection maintains non-adaptive genomic complexity. Rather than lumping different sorts of genomic complexity together by defining 'function' as fitness contribution, we argue that it is best to separate the heterogeneous contributions of preaptation, exaptation and adaptation to the historical processes of origin and maintenance for complex features.

Evolution, folding, and design of TIM barrels and related proteins

Proteins are chief actors in life that perform a myriad of exquisite functions. This diversity has been enabled through the evolution and diversification of protein folds. Analysis of sequences and structures strongly suggest that numerous protein pieces have been reused as building blocks and propagated to many modern folds. This information can be traced to understand how the protein world has diversified. In this review, we discuss the latest advances in the analysis of protein evolutionary units, and we use as a model system one of the most abundant and versatile topologies, the TIM-barrel fold, to highlight the existing common principles that interconnect protein evolution, structure, folding, function, and design.

Elaboration of the Corticosteroid Synthesis Pathway in Primates through a Multistep Enzyme

Metabolic networks are complex cellular systems dependent on the interactions among, and regulation of, the enzymes in the network. Although there is great diversity of types of enzymes that make up metabolic networks, the models meant to understand the possible evolutionary outcomes following duplication neglect specifics about the enzyme, pathway context, and cellular constraints. To illuminate the mechanisms that shape the evolution of biochemical pathways, I functionally characterize the consequences of gene duplication of an enzyme family that performs multiple subsequent enzymatic reactions (a multistep enzyme) in the corticosteroid pathway in primates. The products of the corticosteroid pathway (aldosterone and cortisol) are steroid hormones that regulate metabolism and stress response in tetrapods. These steroid hormones are synthesized by a multistep enzyme Cytochrome P450 11B (CYP11B) that performs subsequent steps on different carbon atoms of the steroid derivatives. Through ancestral state reconstruction and in vitro characterization, I find that the primate ancestor of the CYP11B1 and CYP11B2 paralogs had moderate ability to synthesize both cortisol and aldosterone. Following duplication in Old World primates, the CYP11B1 homolog specialized on the production of cortisol, whereas its paralog, CYP11B2, maintained its ability to perform multiple subsequent steps as in the ancestral pathway. Unlike CYP11B1, CYP11B2 could not specialize on the production of aldosterone because it is constrained to perform earlier steps in the corticosteroid synthesis pathway to achieve the final product aldosterone. These results suggest that enzyme function, pathway context, along with tissue-specific regulation, both play a role in shaping potential outcomes of metabolic network elaboration.

Protein phylogenetics with mass spectrometry. A comparison of methods

Advances in protein mass spectrometry have provided the ability to identify and sequence proteins with unprecedented speed, sensitivity and accuracy. These benefits now offer advantages for studies of protein evolution and phylogeny avoiding the need to generate and align DNA sequences which can prove time consuming, costly and difficult in the case of large genomes and for highly diverse organisms. The methods of phylogenetic analysis using protein mass spectrometry can be classified into three categories: (1) de novo protein sequencing followed by multiple sequence alignment for classical phylogenetic reconstruction, (2) direct phylogenetic reconstruction using expressed protein mass profiles exploited in microbial biotyping applications, and (3) the construction of trees using proteolytic peptide mass map or fingerprint data. This review describes the three approaches together with the relevant tools and algorithms required to implement them. It also compares each of these alternative protein based methods alongside conventional gene sequence based phylogenetics.

Hinge-shift mechanism as a protein design principle for the evolution of β-lactamases from substrate promiscuity to specificity

TEM-1 β-lactamase degrades β-lactam antibiotics with a strong preference for penicillins. Sequence reconstruction studies indicate that it evolved from ancestral enzymes that degraded a variety of β-lactam antibiotics with moderate efficiency. This generalist to specialist conversion involved more than 100 mutational changes, but conserved fold and catalytic residues, suggesting a role for dynamics in enzyme evolution. Here, we develop a conformational dynamics computational approach to rationally mold a protein flexibility profile on the basis of a hinge-shift mechanism. By deliberately weighting and altering the conformational dynamics of a putative Precambrian β-lactamase, we engineer enzyme specificity that mimics the modern TEM-1 β-lactamase with only 21 amino acid replacements. Our conformational dynamics design thus re-enacts the evolutionary process and provides a rational allosteric approach for manipulating function while conserving the enzyme active site.