Protein Evolution Research Articles

The origin of mutational epistasis.

The interconnected processes of protein folding, mutations, epistasis, and evolution have all been the subject of extensive analysis throughout the years due to their significance for structural and evolutionary biology. The origin (molecular basis) of epistasis-the non-additive interactions between mutations-is still, nonetheless, unknown. The existence of a new perspective on protein folding, a problem that needs to be conceived as an 'analytic whole', will enable us to shed light on the origin of mutational epistasis at the simplest level-within proteins-while also uncovering the reasons why the genetic background in which they occur, a key component of molecular evolution, could foster changes in epistasis effects. Additionally, because mutations are the source of epistasis, more research is needed to determine the impact of post-translational modifications, which can potentially increase the proteome's diversity by several orders of magnitude, on mutational epistasis and protein evolvability. Finally, a protein evolution thermodynamic-based analysis that does not consider specific mutational steps or epistasis effects will be briefly discussed. Our study explores the complex processes behind the evolution of proteins upon mutations, clearing up some previously unresolved issues, and providing direction for further research.

Building rigid networks with prestress and selective pruning

Biopolymer networks from the intracellular to tissue scale display high rigidity and tensile stress while having coordinations well below the normal threshold for mechanical rigidity. The elastic filaments in these networks are often severed by enzymes in a tension-inhibited manner. The effects of such pruning on the mechanics of prestressed networks have not been studied. We show that networks pruned by a tension-inhibited method remain rigid at much lower coordinations than randomly pruned ones. These findings suggest a possible reason for the repeated evolution of tension-inhibited filament-severing proteins. Published by the American Physical Society 2024

Structure and evolution of metapolycentromeres.

Metapolycentromeres consist of multiple sequential domains of centromeric chromatin associated with a centromere-specific variant of histone H3 (CENP-A), functioning collectively as a single centromere. To date, they have been revealed in nine flowering plant, five insect and six vertebrate species. In this paper, we focus on their structure and possible mechanisms of emergence and evolution. The metapolycentromeres may vary in the number of centromeric domains and in their genetic content and epigenetic modifications. However, these variations do not seem to affect their function. The emergence of metapolycentromeres has been attributed to multiple Robertsonian translocations and segmental duplications. Conditions of genomic instability, such as interspecific hybridization and malignant neoplasms, are suggested as triggers for the de novo emergence of metapolycentromeres. Addressing the "centromere paradox" - the rapid evolution of centromeric DNA and proteins despite their conserved cellular function - we explore the centromere drive hypothesis as a plausible explanation for the dynamic evolution of centromeres in general, and in particular the emergence of metapolycentromeres and holocentromeres. Apparently, metapolycentromeres are more common across different species than it was believed until recently. Indeed, a systematic review of the available cytogenetic publications allowed us to identify 27 candidate species with metapolycentromeres. Тhe list of the already established and newly revealed candidate species thus spans 27 species of flowering plants and eight species of gymnosperm plants, five species of insects, and seven species of vertebrates. This indicates an erratic phylogenetic distribution of the species with metapolycentromeres and may suggest an independent emergence of the metapolycentromeres in the course of evolution. However, the current catalog of species with identified and likely metapolycentromeres remains too short to draw reliable conclusions about their evolution, particularly in the absence of knowledge about related species without metapolycentromeres for comparative analysis. More studies are necessary to shed light on the mechanisms of metapolycentromere formation and evolution.

A theoretical model for focal adhesion and cytoskeleton formation in non-motile cells

To function and survive cells need to be able to sense and respond to their local environment through mechanotransduction. Crucially, mechanical and biochemical perturbations initiate cell signaling cascades, which can induce responses such as growth, apoptosis, proliferation and differentiation. At the heart of this process are actomyosin stress fibres (SFs), which form part of the cell cytoskeleton, and focal adhesions (FAs), which bind this cytoskeleton to the extra-cellular matrix (ECM). The formation and maturation of these structures (connected by a positive feedback loop) is pivotal in non-motile cells, where SFs are generally of ventral type, interconnecting FAs and producing isometric tension. In this study we formulate a one-dimensional bio-chemo-mechanical continuum model to describe the coupled formation and maturation of ventral SFs and FAs. We use a set of reaction–diffusion-advection equations to describe three sets of biochemical events: the polymerisation of actin and subsequent bundling into activated SFs; the formation and maturation of cell-substrate adhesions; and the activation of signaling proteins in response to FA and SF formation. The evolution of these key proteins is coupled to a Kelvin-Voigt viscoelastic description of the cell cytoplasm and the ECM. We employ this model to understand how cells respond to external and intracellular cues in vitro and are able to reproduce experimentally observed phenomena including non-uniform cell striation and cells forming weaker SFs and FAs on softer substrates.

Human IL-22 receptor-targeted small protein antagonist suppress murine DSS-induced colitis

BackgroundHuman interleukin-22 (IL-22) is known as a “dual function” cytokine that acts as a master regulator to maintain homeostasis, structural integrity of the intestinal epithelial barrier, and shielding against bacterial pathogens. On the other hand, the overexpression of IL-22 is associated with hyper-proliferation and recruitment of pathologic effector cells, leading to tissue damage and chronic inflammation in specific diseases including inflammatory bowel disease (IBD). To study a role of IL-22-mediated signaling axis during intestinal inflammation, we generated a set of small protein blockers of IL-22R1 and verified their inhibitory potential on murine model of colitis.MethodsWe used directed evolution of proteins to identify binders of human IL-22 receptor alpha (IL-22R1), designated as ABR ligands. This approach combines the assembly of a highly complex combinatorial protein library derived from small albumin-binding domain scaffold and selection of promising protein variants using ribosome display followed by large-scale ELISA screening. The binding affinity and specificity of ABR variants were analyzed on transfected HEK293T cells by flow cytometry and LigandTracer. Inhibitory function was further verified by competition ELISA, HEK-Blue IL-22 reporter cells, and murine dextran sulfate sodium (DSS)-induced colitis.ResultsWe demonstrate that ABR specifically recognizes transgenic IL-22R1 expressed on HEK293T cells and IL-22R1 on TNFα/IFNγ-activated HaCaT cells. Moreover, some ABR binders compete with the IL-22 cytokine and function as IL-22R1 antagonists in HEK-Blue IL22 reporter cells. In a murine model of DSS-induced acute intestinal inflammation, daily intraperitoneal administration of the best IL-22R1 antagonist, ABR167, suppressed the development of clinical and histological markers of colitis including prevention of mucosal inflammation and architecture deterioration. In addition, ABR167 reduces the DSS-induced increase in mRNA transcript levels of inflammatory cytokines such as IL-1β, IL-6, IL-10, and IL-17A.ConclusionsWe developed small anti-human IL-22R1 blockers with antagonistic properties that ascertain a substantial role of IL-22-mediated signaling in the development of intestinal inflammation. The developed ABR blockers can be useful as a molecular clue for further IBD drug development.

Avian influenza A H5N1 hemagglutinin protein models have distinct structural patterns re-occurring across the 1959–2023 strains

Influenza A H5N1 hemagglutinin (HA) plays a crucial role in viral pathogenesis and changes in the HA receptor binding domain (RBD) have been attributed to alterations in viral pathogenesis. Mutations often occur within the HA which in-turn results in HA structural changes that consequently contribute to protein evolution. However, the possible occurrence of mutations that results to reversion of the HA protein (going back to an ancestral protein conformation) which in-turn creates distinct HA structural patterns across the 1959–2023 H5N1 viral evolution has never been investigated. Here, we generated and verified the quality of the HA models, identified similar HA structural patterns, and elucidated the possible variations in HA RBD structural dynamics. Our results show that there are 7 distinct structural patterns occurring among the 1959–2023 H5N1 HA models which suggests that reversion of the HA protein putatively occurs during viral evolution. Similarly, we found that the HA RBD structural dynamics vary among the 7 distinct structural patterns possibly affecting viral pathogenesis.

Emergent time scales of epistasis in protein evolution

We introduce a data-driven epistatic model of protein evolution, capable of generating evolutionary trajectories spanning very different time scales reaching from individual mutations to diverged homologs. Our in silico evolution encompasses random nucleotide mutations, insertions and deletions, and models selection using a fitness landscape, which is inferred via a generative probabilistic model for protein families. We show that the proposed framework accurately reproduces the sequence statistics of both short-time (experimental) and long-time (natural) protein evolution, suggesting applicability also to relatively data-poor intermediate evolutionary time scales, which are currently inaccessible to evolution experiments. Our model uncovers a highly collective nature of epistasis, gradually changing the fitness effect of mutations in a diverging sequence context, rather than acting via strong interactions between individual mutations. This collective nature triggers the emergence of a long evolutionary time scale, separating fast mutational processes inside a given sequence context, from the slow evolution of the context itself. The model quantitatively reproduces epistatic phenomena such as contingency and entrenchment, as well as the loss of predictability in protein evolution observed in deep mutational scanning experiments of distant homologs. It thereby deepens our understanding of the interplay between mutation and selection in shaping protein diversity and functions, allows one to statistically forecast evolution, and challenges the prevailing independent-site models of protein evolution, which are unable to capture the fundamental importance of epistasis.

Whole genome characteristics of hedgehog coronaviruses from Poland and analysis of the evolution of the Spike protein for its interspecies transmission potential

BackgroundThe hedgehogs have been recently identified as possible reservoir of Middle East respiratory syndrome coronavirus like (MERS-CoV-like). These viruses were classified as a distinct Betacoronavirus erinacei (BCoV-Eri) species within the MerBCoV-Eriirus subgenus. As coronaviruses are known for their ability to jump between different hosts, including humans, this can pose a particular threat to people in direct contact with hedgehogs, such as those working at animal asylums. Our previous studies have shown the presence of BCoV-Eri strains in animals collected in the wildlife rehabilitation centre. This study aimed to investigate the presence of CoV in subsequent hedgehogs collected from the urban area of Poland and their molecular characteristics.ResultsMonitoring for the presence of coronavirus infection in hedgehogs revealed five positive individuals. The presence of BCoV-Eri was found in a total of 20% of animals tested. Our analyses revealed no correlation between CoVs positivity and animal health conditions but a higher probability of such infection in juveniles and females. The whole genome of two Polish Hedgehog coronavirus 1 strains were sequenced and compared with available counterparts from European and Asian countries. Phylogenetic analysis showed that both CoV strains formed common cluster with other similar MerBCoV-Eriirus, but they were also found to be genetically variable and most changes in the S protein were identified. Our analysis revealed that some S protein sites of the Hedgehog coronavirus 1 strains evolved under positive selection pressure and of five such sites, three are in the S1 region while the other two in the S2 region of the Spike.ConclusionsBCoV-Eri is to some extent prevalent in wildlife asylums in Poland. Given that the S protein of BCoVs-Eri is highly variable and that some sites of this protein evolve under positive selection pressure, these strains could potentially acquire a favourable feature for cross-species transmission. Consequently, the threat to humans working in such asylums is particularly high. Adequate biosecurity safeguards, but also human awareness of such risks, are therefore essential.

Deep generative models of protein structure uncover distant relationships across a continuous fold space

Our views of fold space implicitly rest upon many assumptions that impact how we analyze, interpret and understand protein structure, function and evolution. For instance, is there an optimal granularity in viewing protein structural similarities (e.g., architecture, topology or some other level)? Similarly, the discrete/continuous dichotomy of fold space is central, but remains unresolved. Discrete views of fold space bin similar folds into distinct, non-overlapping groups; unfortunately, such binning can miss remote relationships. While hierarchical systems like CATH are indispensable resources, less heuristic and more conceptually flexible approaches could enable more nuanced explorations of fold space. Building upon an Urfold model of protein structure, here we present a deep generative modeling framework, termed DeepUrfold, for analyzing protein relationships at scale. DeepUrfold’s learned embeddings occupy high-dimensional latent spaces that can be distilled for a given protein in terms of an amalgamated representation uniting sequence, structure and biophysical properties. This approach is structure-guided, versus being purely structure-based, and DeepUrfold learns representations that, in a sense, define superfamilies. Deploying DeepUrfold with CATH reveals evolutionarily-remote relationships that evade existing methodologies, and suggests a mostly-continuous view of fold space—a view that extends beyond simple geometric similarity, towards the realm of integrated sequence ↔ structure ↔ function properties.

Metformin hydrolase is a recently evolved nickel-dependent heteromeric ureohydrolase

The anti-diabetic drug metformin is one of the most widely prescribed medicines in the world. Together with its degradation product guanylurea, it is a major pharmaceutical pollutant in wastewater treatment plants and surface waters. An operon comprising two genes of the ureohydrolase family in Pseudomonas and Aminobacter species has recently been implicated in metformin degradation. However, the corresponding proteins have not been characterized. Here we show that these genes encode a Ni2+-dependent enzyme that efficiently and specifically hydrolyzes metformin to guanylurea and dimethylamine. The active enzyme is a heteromeric complex of α- and β- subunits in which only the α-subunits contain the conserved His and Asp residues for the coordination of two Ni2+ ions in the active site. A crystal structure of metformin hydrolase reveals an α2β4 stoichiometry of the hexameric complex, which is unprecedented in the ureohydrolase family. By studying a closely related but more widely distributed enzyme, we find that the putative predecessor specifically hydrolyzes dimethylguanidine instead of metformin. Our findings establish the molecular basis for metformin hydrolysis to guanylurea as the primary pathway for metformin biodegradation and provide insight into the recent evolution of ureohydrolase family proteins in response to an anthropogenic compound.

The Relationship of Transposable Elements with Non-Coding RNAs in the Emergence of Human Proteins and Peptides

: Transposable elements are the oldest structural and functional units that were formed during the emergence of life on Earth. The most ancient properties of transposable elements are the multifunctionality of their transcription and translation products and the formation of their many variants through processing, due to which transposable elements are key evolutionary sources of long non-coding RNAs, circular RNAs, microRNAs, proteins and peptides formation. Moreover, the same type of transposon can simultaneously serve as the source of the origin of all these molecules, providing the adaptive properties of living organisms, especially complex eukaryotes, including humans. The ancient ability of transposable elements for mutual integration due to their protein products interacting with DNA and RNA molecules, as well as for mutual regulation due to the functionality of their RNA, is the basis for the origin of many proteins and non-coding RNAs characterized by the same properties. This can explain the emergence of transcription factors from transposable elements, that is, proteins capable of interacting with the structures of DNA molecules due to the presence of specific amino acid sequences derived from transposable elements. This article presents facts about the origin during the evolution of many protein and non-- coding RNA genes from transposable elements. Specific proteins and peptides translated from long non-coding RNAs, pri-microRNAs and circular RNAs are described, which reflect the origin of non-coding RNAs from transposable elements in evolution. These proteins and peptides are promising tools for the treatment of viral infections and drug-resistant tumors, since, together with non-coding RNAs, they are involved in antiviral and antitumor responses.

Novel Insights on Extracellular Electron Transfer Networks in the Desulfovibrionaceae Family: Unveiling the Potential Significance of Horizontal Gene Transfer.

Some sulfate-reducing bacteria (SRB), mainly belonging to the Desulfovibrionaceae family, have evolved the capability to conserve energy through microbial extracellular electron transfer (EET), suggesting that this process may be more widespread than previously believed. While previous evidence has shown that mobile genetic elements drive the plasticity and evolution of SRB and iron-reducing bacteria (FeRB), few have investigated the shared molecular mechanisms related to EET. To address this, we analyzed the prevalence and abundance of EET elements and how they contributed to their differentiation among 42 members of the Desulfovibrionaceae family and 23 and 59 members of Geobacteraceae and Shewanellaceae, respectively. Proteins involved in EET, such as the cytochromes PpcA and CymA, the outer membrane protein OmpJ, and the iron-sulfur cluster-binding CbcT, exhibited widespread distribution within Desulfovibrionaceae. Some of these showed modular diversification. Additional evidence revealed that horizontal gene transfer was involved in the acquiring and losing of critical genes, increasing the diversification and plasticity between the three families. The results suggest that specific EET genes were widely disseminated through horizontal transfer, where some changes reflected environmental adaptations. These findings enhance our comprehension of the evolution and distribution of proteins involved in EET processes, shedding light on their role in iron and sulfur biogeochemical cycling.

AI-Predicted Protein Deformation Encodes Energy Landscape Perturbation.

AI algorithms have proven to be excellent predictors of protein structure, but whether and how much these algorithms can capture the underlying physics remains an open question. Here, we aim to test this question using the Alphafold2 (AF) algorithm: We use AF to predict the subtle structural deformation induced by single mutations, quantified by strain, and compare with experimental datasets of corresponding perturbations in folding free energy ΔΔG. Unexpectedly, we find that physical strain alone-without any additional data or computation-correlates almost as well with ΔΔG as state-of-the-art energy-based and machine-learning predictors. This indicates that the AF-predicted structures alone encode fine details about the energy landscape. In particular, the structures encode significant information on stability, enough to estimate (de-)stabilizing effects of mutations, thus paving the way for the development of novel, structure-based stability predictors for protein design and evolution.

Generation and characterization of two acid-resistant macrocin O-methyltransferase variants with a higher enzyme activity at 30 °C from Streptomyces fradiae

Tylosin is an important macrolide antibiotic produced by Streptomyces fradiae. In the biosynthesis of tylosin, macrocin O-methyltransferase TylF catalyzes the conversion of the side-product tylosin C (macrocin) to the primary component tylosin A (C/A conversion). This conversion is the rate-limiting step in the biosynthesis of tylosin, and affects the quality of the end product. To find a high activity and environment-adapted TylF enzyme, a TylF variant pool has been constructed via protein evolution approach in our previous study (Fan et al., 2023 [41]). In this study, the TylF variants with higher C/A conversion rates were expressed in E. coli and purified. The variants TylFY139F, TylFQ138H, F232Y and TylFT36S, V54A were shown to have a higher C/A conversion rate at 30 °C than that of TylF at 38 °C. Moreover, they had a greater acid resistance and showed more adaptable to the pH change during fermentation. Further protein structural and substrate-binding affinity analyses revealed that the T36S, V54A, Q138H, Y139F, and F232Y mutations enlarged the volume of the substrate-binding pocket, thereby increasing the affinity of enzyme variants for their substrates of SAM and macrocin, and decreasing the inhibition of SAH. Three of the TylF variants were overexpressed in the industrial tylosin-producing S. fradiae strain, and the recombinant strains showed the highest C/A conversion at 30 °C without heating up to 38 °C during the last 24 h of fermentation. This is of great energy-saving significance for tylosin industrial production.

Leaf transcriptomes from C3, C3-C4 intermediate, and C4 Neurachne species give insights into C4 photosynthesis evolution.

The C4 photosynthetic pathway is hypothesized to have evolved from the ancestral C3 pathway through progressive changes in leaf anatomy and biochemistry with extant C3-C4 photosynthetic intermediate species representing phenotypes between species demonstrating full C3 and full C4 states. The Australian endemic genus Neurachne is the only known grass group that contains distinct, closely related species that carry out C3, C3-C4 intermediate, or C4 photosynthesis. To explore and understand the molecular mechanisms underlying C4 photosynthesis evolution in this genus, leaf transcriptomes were generated from two C3, three photosynthetic intermediate (proto-Kranz, C2-like, and C2), and two C4 Neurachne species. The data were used to reconstruct phylogenetic relationships in Neurachne, which confirmed two independent C4 origins in the genus. Relative transcript abundances substantiated the photosynthetic phenotypes of individual species and highlighted transcriptional investment differences between species, including between the two C4 species. The data also revealed proteins potentially involved in C4 cycle intermediate transport and identified molecular mechanisms responsible for the evolution of C4-associated proteins in the genus.

Clustering protein functional families at large scale with hierarchical approaches.

Proteins, fundamental to cellular activities, reveal their function and evolution through their structure and sequence. CATH functional families (FunFams) are coherent clusters of protein domain sequences in which the function is conserved across their members. The increasing volume and complexity of protein data enabled by large-scale repositories like MGnify or AlphaFold Database requires more powerful approaches that can scale to the size of these new resources. In this work, we introduce MARC and FRAN, two algorithms developed to build upon and address limitations of GeMMA/FunFHMMER, our original methods developed to classify proteins with related functions using a hierarchical approach. We also present CATH-eMMA, which uses embeddings or Foldseek distances to form relationship trees from distance matrices, reducing computational demands and handling various data types effectively. CATH-eMMA offers a highly robust and much faster tool for clustering protein functions on a large scale, providing a new tool for future studies in protein function and evolution.

Fast, sensitive detection of protein homologs using deep dense retrieval.

The identification of protein homologs in large databases using conventional methods, such as protein sequence comparison, often misses remote homologs. Here, we offer an ultrafast, highly sensitive method, dense homolog retriever (DHR), for detecting homologs on the basis of a protein language model and dense retrieval techniques. Its dual-encoder architecture generates different embeddings for the same protein sequence and easily locates homologs by comparing these representations. Its alignment-free nature improves speed and the protein language model incorporates rich evolutionary and structural information within DHR embeddings. DHR achieves a >10% increase in sensitivity compared to previous methods and a >56% increase in sensitivity at the superfamily level for samples that are challenging to identify using alignment-based approaches. It is up to 22 times faster than traditional methods such as PSI-BLAST and DIAMOND and up to 28,700 times faster than HMMER. The new remote homologs exclusively found by DHR are useful for revealing connections between well-characterized proteins and improving our knowledge of protein evolution, structure and function.

The ribosome lowers the entropic penalty of protein folding

Most proteins fold during biosynthesis on the ribosome1, and co-translational folding energetics, pathways and outcomes of many proteins have been found to differ considerably from those in refolding studies2–10. The origin of this folding modulation by the ribosome has remained unknown. Here we have determined atomistic structures of the unfolded state of a model protein on and off the ribosome, which reveal that the ribosome structurally expands the unfolded nascent chain and increases its solvation, resulting in its entropic destabilization relative to the peptide chain in isolation. Quantitative 19F NMR experiments confirm that this destabilization reduces the entropic penalty of folding by up to 30 kcal mol−1 and promotes formation of partially folded intermediates on the ribosome, an observation that extends to other protein domains and is obligate for some proteins to acquire their active conformation. The thermodynamic effects also contribute to the ribosome protecting the nascent chain from mutation-induced unfolding, which suggests a crucial role of the ribosome in supporting protein evolution. By correlating nascent chain structure and dynamics to their folding energetics and post-translational outcomes, our findings establish the physical basis of the distinct thermodynamics of co-translational protein folding.

Subsequent Waves of Convergent Evolution in SARS-CoV-2 Genes and Proteins.

Beginning in 2022, following widespread infection and vaccination among the global population, the SARS-CoV-2 virus mainly evolved to evade immunity derived from vaccines and past infections. This review covers the convergent evolution of structural, nonstructural, and accessory proteins in SARS-CoV-2, with a specific look at common mutations found in long-lasting infections that hint at the virus potentially reverting to an enteric sarbecovirus type.

Sequence, Structure, and Functional Space of Drosophila De Novo Proteins.

During de novo emergence, new protein coding genes emerge from previously nongenic sequences. The de novo proteins they encode are dissimilar in composition and predicted biochemical properties to conserved proteins. However, functional de novo proteins indeed exist. Both identification of functional de novo proteins and their structural characterization are experimentally laborious. To identify functional and structured de novo proteins in silico, we applied recently developed machine learning based tools and found that most de novo proteins are indeed different from conserved proteins both in their structure and sequence. However, some de novo proteins are predicted to adopt known protein folds, participate in cellular reactions, and to form biomolecular condensates. Apart from broadening our understanding of de novo protein evolution, our study also provides a large set of testable hypotheses for focused experimental studies on structure and function of de novo proteins in Drosophila.