Biology subjects

Wood, C. W.

Publications and source records attributed to Wood, C. W..

At least 19 recordsLinked to original sources

bioRxiv2026

The centromere localization domain of kinetoplastid kinetochore protein KKT2 recognizes the free N-terminus of histone H3

Kinetochores are multiprotein complexes that drive chromosome segregation in eukaryotes. Kinetoplastids, a group of early-diverging eukaryotes that lack canonical kinetochore components, have a unique set of kinetochore proteins. How their kinetochores are assembled specifically at centromeres in the absence of a centromere-specific histone H3 variant CENP-A remains unknown. Here, we demonstrate that the centromere localization (CL) domain of KKT2 has similarities to a ZZ domain. An invariant aspartate present in histone H3-binding ZZ domains is conserved in the KKT2 CL domain. Using nuclear magnetic resonance (NMR) spectroscopy and isothermal titration calorimetry (ITC), we show that Trypanosoma brucei KKT2 CL binds the N-terminus of histone H3. Strikingly, even mono-methylation of the N-terminal amino group of histone H3 abolishes the binding. Our study raises a possibility that centromere-specific kinetochore assembly in T. brucei is ensured by abundant N-terminal methylations of histone H3 in non-centromeric regions.

cell biology↗

bioRxiv2026

drFrankenstein: An Automated Pipeline for the Parameterisation of Non-Canonical Amino Acids

The incorporation of non-canonical amino acids (ncAAs) is a powerful strategy for introducing novel chemical functions into proteins. Molecular dynamics (MD) simulations are essential for understanding the structural and dynamic effects of these modifications, yet the creation of accurate force field parameters for ncAAs remains a significant bottleneck. Current parameterisation methods are often inaccurate or computationally expensive. To address this, we present drFrankenstein, an automated pipeline for generating AMBER force field parameters for ncAAs. drFrankenstein is a robust and accessible tool that streamlines the parameterisation workflow, enabling the routine use of MD simulations to study the behaviour of ncAA-containing proteins.

bioinformatics↗

bioRxiv2026

Mutualistic rhizobia harbor genetic variation for traits related to parasite infection

Nutritional mutualisms are defined by resource exchange, but growing evidence suggests that these interactions also shape resistance to parasites and pathogens. The evolutionary significance of this phenomenon is unclear, primarily because research has focused on mutualist-mediated plasticity rather than on mutualist contributions to heritable variation in the outcome of infection. To test whether nutritional mutualists harbor genetic variation for infection-related traits, we performed a quantitative genetic experiment in the nutritional mutualism between legumes and nitrogen-fixing rhizobia. We paired 10 mutualistic Sinorhizobium meliloti rhizobia strains with 20 Medicago truncatula plant genotypes in an incomplete factorial design, and experimentally infected plants with parasitic root-knot nematodes (Meloidogyne hapla). We used this design to estimate plant and rhizobia contributions to genetic variation in four infection-related traits: resistance, tolerance, virulence, and mutualism robustness to infection. Rhizobia contributed directly to genetic variation in virulence, and to parasite resistance and mutualism robustness via genotype-by-genotype interactions. Rhizobia did not contribute to genetic variation in tolerance. The effect of rhizobia on parasite resistance was partially explained by their effect on root growth. Our results raise the possibility that some nutritional mutualists play a role comparable to defensive mutualists in shaping the evolutionary potential of host defense traits. Teaser textNutritional mutualisms are everywhere. These mutualisms are defined by the exchange of resources between partners, but many have secondary effects on resistance to parasites, pathogens, or herbivores. Here, we show that a textbook nutritional mutualist (nitrogen-fixing rhizobia) harbors genetic variation for the hosts response to parasite infection. Our results imply that nutritional mutualists can impact the evolutionary potential of infection-related traits in their hosts, suggesting that these mutualisms may be overlooked drivers of defense evolution.

evolutionary biology↗

bioRxiv2025

Triplet Quenching by Active Site Cysteine Residues Improves Photostability in Fatty Acid Photodecarboxylase

Enzyme photobiocatalysis uses light to drive high-energy transformations but is limited by the rarity of photoenzymes. Fatty acid photodecarboxylase (FAP), a recently discovered photoenzyme, enables fatty acid conversion to alkanes/alkenes via excitation of an FAD cofactor, though its poor photostability and photoinactivation has hindered industrial applications. Here, we combine protein engineering approaches with biocatalytic and biophysical techniques, as well as computational chemistry, to demonstrate that additional active site cysteine residues can suppress oxygen-mediated inactivation processes that are driven by the FAD triplet-excited state. We identify a number of positions close to the FAD for cysteine residues that lead to a significant enhancement in activity as a result of an increase in the number of catalytic turnovers and improved photostability. The additional cysteine residues quench the triplet excited state of the FAD cofactor via a proposed proton-coupled electron transfer mechanism, resulting in lower levels of harmful reactive oxygen species. Our study highlights promising routes to mitigate non-productive, photoinactivation pathways in FAP and informs the rational design of new flavin-based photoenzymes.

biochemistry↗

bioRxiv2025

Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition

In this report, we summarize and analyze the 2024 Adaptyv protein design competition. Participants used computational and Machine Learning (ML) methods of their choice to design proteins that bind the Epidermal Growth Factor Receptor (EGFR), a key drug target involved in cell growth, differentiation, and cancer development. Over 1,800 designs were submitted across two rounds. Of these, 601 proteins were selected and characterized for expression and binding affinity to EGFR, with competitors both optimizing existing binders (KD = 1.21 nM) and creating de novo binders (KD = 82 nM). All selected designs were experimentally validated using Adaptyvs automated Bio-Layer Interferometry (BLI) pipeline. This competition illustrates the potential of crowdsourcing to drive creativity and innovation in protein design. However, it also exposed key challenges, such as the lack of standardized benchmarks, experimental design targets, and robust computational metrics for method comparison. We anticipate that future competitions will address these gaps and further motivate progress in computational protein design.

bioengineering↗

bioRxiv2025

Evidence for balancing selection on loci associated with host use in the genome of a generalist plant parasite

Most research on host-parasite interactions has focused on tightly coevolved species pairs, yet many parasites are generalists that infect a wide range of host taxa. Generalist parasites are subject to highly variable selection pressures across different hosts and the footprints that this heterogeneous selection leaves in the genomes of generalists have been largely unexplored. To address this knowledge gap, we studied patterns of host-associated genetic diversity in the generalist plant parasite, the northern root knot nematode Meloidogyne hapla. By leveraging whole genome amplification, we generated whole genome libraries of individual root-knot nematodes collected from three different host plant species in a spatially replicated design. Despite finding no evidence of host-associated population structure, we did observe several hundred host-associated SNPs putatively under differential host selection. Genomic regions containing these host-associated SNPs were enriched for signals of balancing selection. Additionally, host-associated SNPs were enriched for functions involved in plant pathogenesis, specifically the modification of plant cell walls. Host-associated SNPs were also found in genes with known roles in dampening host plant immune responses to infection. Together, our results suggest a model of balancing selection in which heterogeneous selection by different host taxa maintains adaptive diversity at loci involved in pathogenesis.

evolutionary biology↗

bioRxiv2025

From Atoms to Fragments: A Coarse Representation for Functional and Efficient Protein Design

MotivationAlthough deep learning has accelerated protein design, current protein representations such as sequences or full-atom structures scale non-linearly with protein length. We propose a sparse and interpretable representation for proteins, based on evolutionarily conserved fragments. Specifically, we use a curated set of 40 functional and evolutionarily conserved fragments as an alphabet to build Fragment Graphs and Fragment Sets. These fragment-based representations are both lightweight and functionally informative, capturing up to 55% more variance using fewer than [Formula] of the dimensions required by traditional methods. ResultsOn a dataset of 215 functionally diverse proteins, our approach creates more coherent functional clusters than traditional sequence- and structure-based methods, even among proteins with [≤] 30% sequence identity. Fragment-based searches of protein databases achieve accuracies comparable to traditional methods, while using 90% fewer tokens per protein. These searches execute [~]68.7x faster than RMSD-based structural methods and [~]1.64x faster than sequence-based methods, even including fragment pre-processing overhead. Additionally, we show that our representation effectively guides RFDiffusion for protein backbone generation with functional recovery rates higher than 40%. In summary, our fragment-based representation offers a scalable and interpretable alternative for the next generation of protein design tools for backbone design, sequence design, and functional similarity searches within protein structure databases. Availabilityhttps://github.com/wells-wood-research/tessera (Documentation to be made available upon acceptance)

bioinformatics↗

bioRxiv2024

drMD: Molecular Dynamics for Experimentalists

Molecular dynamics (MD) simulations can be used by protein scientists to investigate a wide array of biologically relevant properties such as the effects of mutations on a proteins structure and activity, or probing intermolecular interactions with small molecule substrates or other macromolecules. Within the world of computational structural biology, several programs have become popular for running these simulations, but each of these programs requires a significant time investment from the researcher to run even simple simulations. Even after learning how to run and analyse simulations, many elements remain a "black box." This greatly limits the accessibility of molecular dynamics simulations for non-experts. Here we present drMD, an automated pipeline for running molecular dynamics simulations using the OpenMM molecular mechanics toolkit. We have created drMD with non-experts in computational biology in mind. The drMD codebase has several functions that automatically handle routine procedures associated with running molecular dynamics simulations. This greatly reduces the expertise required to run MD simulations. We have also introduced a series of quality-of-life features to make the process of running MD simulations both easier and more pleasant. Finally, drMD explains the steps it is taking interactively and, where useful, provides relevant references so the user can learn more. All these features make drMD an effective tool for learning molecular dynamics while running publication-quality simulations. drMD is open source and can be found on GitHub: https://github.com/wells-wood-research/drMD.

bioinformatics↗

bioRxiv2024

The Protein Design Archive (PDA): insights from 40 years of protein design

The field of protein design has changed dramatically over the last 40 years, with a range of methods developing from rational design to more recent data-driven approaches. While considerable insight could be gained from analysing designed proteins, there is no single resource that brings together all the relevant data, making it difficult to identify current challenges and opportunities within the field. Here we present the Protein Design Archive, a website and database of designed proteins. Using the database, we performed systematic analysis that reveals a rapid increase in the number and complexity of designs over time and uncovers biases in their amino-acid usage and secondary structure content. Finally, sequence- and structure-based analysis demonstrates the breadth and novelty of designs within the archive. The PDA will be a valuable resource for guiding development of protein design, helping the field reach its potential. The PDA is available freely and without registration at https://pragmaticproteindesign.bio.ed.ac.uk/pda/.

bioinformatics↗

bioRxiv2024

Variation in a microbial mutualist has cascading consequences for host-parasite interactions

Strains of microbial symbionts often vary in their effect on their host. However, little is known about how the genetic variation in microbial symbiont populations impacts host interactions with other co-colonizing microbes. We investigated how different strains of nitrogen-fixing rhizobial bacteria affect their host plants response to parasitic root-knot nematodes in the legume Medicago truncatula. Using dual RNAseq of the root organs harboring rhizobia or nematodes, we identified genes from plant host, rhizobia, and nematode whose expression differed between parasite-infected and-uninfected plants, and between plants inoculated with different rhizobial strains. At the site of host-parasite interactions (in nematode galls), hundreds of host genes and few nematode genes differed in expression between host plants inoculated with different rhizobia strains. At the site of host-mutualist interactions (in rhizobia nodules), hundreds of host genes and few rhizobial genes responded to parasite infection. The vast majority of parasite-induced changes in host gene expression depended on the resident rhizobia strain. We additionally observed differences in parasite load and in some root architecture traits between plants inoculated with different rhizobia strains, showing that genetic variation in a mutualistic symbiont impacted parasite colonization. The transcriptomic and phenotypic differences we observed suggest that microbial indirect genetic effects play an underappreciated role in their hosts interactions with other co-colonizing microorganisms.

ecology↗

bioRxiv2024

Large scale analysis of predicted protein structures links model features to in vivo behaviour

Rapid advancements in protein structure prediction methods have ushered in a new era of abundant and accurate structural data, providing opportunities to analyse proteins at a scale that has not been possible before. Here we show that features derived solely from predicted structures can be used to understand in vivo protein behaviour using data-driven methods. We found that these features were predictive of in vivo protein production for a set of designed antibodies, enabling identification of high-quality designs. Following on from this result, we calculated these features for a diverse set of {approx}500,000 predicted structures, and our analysis showed systematic variation between proteins from different organisms to such an extent that the tree of life could be recapitulated from these data. Given the high degree of functional constraint around the chemistry of proteins, this result is surprising, and could have important implications for the design and engineering of novel proteins.

bioinformatics↗

bioRxiv2023

Computational Design of Periplasmic Binding Protein Biosensors Guided by Molecular Dynamics

Periplasmic binding proteins (PBPs) are bacterial proteins commonly used as scaffolds for substrate-detecting biosensors. In such biosensors, effector proteins, for example circularly permuted green fluorescent protein (cpGFP), are inserted into a PBP such that the effector proteins output changes upon PBP-substate binding. The insertion site is often determined by comparison of PBP apo/holo crystal structures, but random insertion libraries have shown that this can miss the best sites. Here, we present a PBP biosensor design method based on residue contact analysis from molecular dynamics. This computational method identifies the best previously known insertion sites in the maltose binding PBP, and suggests further previously unknown sites. We experimentally characterise cpGFP insertions at these new sites, finding they too give functional biosensors. Our method is sufficiently flexible to both suggest insertion sites compatible with a variety of effector proteins and be applied to binding proteins beyond PBPs.

synthetic biology↗

bioRxiv2023

Mutualist-Provided Resources Increase Susceptibility to Parasites

Background and AimsO_LIMutualistic microbes often increase their hosts susceptibility to parasite infection, but the mechanism underlying this pattern remains unknown. C_LIO_LIWe tested two competing hypotheses to identify the cause of this phenomenon. C_LIO_LIFirst, mutualist-provided resources could attract antagonists by making hosts more resource-rich. C_LIO_LISecond, mutualism establishment itself might increase host vulnerability to antagonists by enabling antagonists to exploit host defenses or immune systems, which are often downregulated during mutualism establishment. C_LI MethodsO_LITo test which mechanism underlies increased parasite susceptibility, we experimentally decoupled mutualism establishment and mutualist-provided resources in the legume-rhizobia mutualism. C_LIO_LIWe measured parasite load on Medicago truncatula plants infected with root-knot nematodes in a full-factorial design, in which we independently manipulated rhizobia inoculation (mutualism establishment) and nitrogen availability (mutualist-provided resources). C_LI Key ResultsO_LIIncreased nitrogen availability increased parasite infection. However, its effect was non-linear and was not explained by nitrogen assimilation into plant tissues, indicating that this effect is not driven by parasite attraction to resource-rich hosts. C_LIO_LIWe found little effect of mutualism establishment on susceptibility, as neither rhizobia inoculation nor nodulation without nitrogen fixation significantly increased parasite infection. C_LI ConclusionsO_LIOur results suggest that mutualist-provided resources are an important driver of indirect ecological costs of mutualism, although the mechanism linking mutualist-provided resources and susceptibility to infection remains unknown. C_LI

ecology↗

bioRxiv2023

Toward a trait-based framework for studying mutualism evolution: genotypic variation in benefit and cost traits in the legume-rhizobia mutualism

Mutualisms, reciprocally beneficial interaction between two or more species, are ubiquitous in nature. A common feature of mutualisms is extensive context-dependent variation in fitness outcomes. This context-dependency is hypothesized to stem from the environments mediation of the relative costs and benefits associated with mutualisms. However, traits related to the exchange of goods and services in mutualisms have received little attention in comparison to net fitness outcomes. In this study, we quantified the contribution of host and symbiont genotypes to variation in resource exchange, use, and production traits measured in the host using the model mutualism between legumes and nitrogen-fixing rhizobia. We predicted that plant genotype x rhizobia genotype (GxG) effects would be common to resource exchange traits because resource exchange is hypothesized to be governed by both interacting partners through bargaining. On the other hand, we predicted that plant genotype effects would dominate host resource use and production traits because these traits are only indirectly related to the exchange of resources. Consistent with our prediction for resource exchange traits, but not our prediction for resource use and production traits, we found that rhizobia genotype and GxG effects were the most common sources of variation in the traits that we measured. The results of this study complement the commonly observed phenomenon of GxG effects for fitness by showing that numerous mutualism traits also exhibit GxG variation. Furthermore, our results highlight the possibility that the exchange of resources as well as how partners use and produce traded resources can influence the evolution of mutualistic interactions. Our study lays the groundwork for future work to explore the relationship between resource exchange, use and production traits and fitness (i.e. selection) to test the competing hypotheses proposed to explain the maintenance of fitness variation in mutualisms.

evolutionary biology↗

bioRxiv2022

Metabolic trait means but not correlations differ among fungal endophytes isolated from the same plant species

Trait evolution depends both on the direct fitness effects of specific traits and on indirect selection arising from genetically correlated traits. Although well established in plants and animals, the role of trait correlations in microbial evolution remains a major open question. Here, we tested whether genetic correlations in a suite of metabolic traits are conserved between two sister lineages of fungal endophytes, and whether phenotypic divergence between lineages occurred in the direction of the multivariate trait combination containing the most genetic variance within lineages i.e., the genetic lines of least resistance. We found that while one lineage grew faster across nearly all substrates, lineages differed in their mean response to specific substrates and in their overall multivariate metabolic trait means. The structure of the genetic variance-covariance (G) matrix was conserved between lineages, yet to our surprise, divergence in metabolic phenotypes between lineages was nearly orthogonal to the major axis of genetic variation within lineages, indicating that divergence did not occur along the genetic lines of least resistance. Our findings suggest that the evolutionary genetics of trait correlations in microorganisms warrant further research, and highlight the extensive functional variation that exists at very fine taxonomic scales in host-associated microbial communities.

evolutionary biology↗

bioRxiv2021

Giant Starship elements mobilize accessory genes in fungal genomes

Accessory genes are variably present among members of a species and are a reservoir of adaptive functions. In bacteria, differences in gene distributions among individuals largely result from mobile elements that acquire and disperse accessory genes as cargo. In contrast, the impact of cargo-carrying elements on eukaryotic evolution remains largely unknown. Here, we show that variation in genome content within multiple fungal species is facilitated by Starships, a novel group of massive mobile elements that are 110 kb long on average, share conserved components, and carry diverse arrays of accessory genes. We identified hundreds of Starship-like regions across every major class of filamentous Ascomycetes, including 28 distinct Starships that range from 27-393 kb and last shared a common ancestor ca. 400 mya. Using new long-read assemblies of the plant pathogen Macrophomina phaseolina, we characterize 4 additional Starships whose past and ongoing activities contribute to standing variation in genome structure and content. One of these elements, Voyager, inserts into 5S rDNA and contains a candidate virulence factor whose increasing copy number has contrasting associations with pathogenic and saprophytic growth, suggesting Voyagers activity underlies an ecological trade-off. We propose that Starships are eukaryotic analogs of bacterial integrative and conjugative elements based on parallels between their conserved components and may therefore represent the first known agents of active gene transfer in eukaryotes. Our results suggest that Starships have shaped the content and structure of fungal genomes for millions of years and reveal a new concerted route for evolution throughout an entire eukaryotic phylum.

genomics↗

bioRxiv2021

DE-STRESS: A user-friendly web application for the evaluation of protein designs

De novo protein design is a rapidly growing field and there are now many interesting and useful examples of designed proteins in the literature. However, most designs could be classed as failures when characterised in the lab, usually as a result of low expression, misfolding, aggregation or lack of function. This high attrition rate makes protein design unreliable and costly. It is possible that some of these failures could be caught earlier in the design process if it were quick and easy to generate information and a set of high-quality metrics regarding designs, which could be used to make reproducible and data-driven decisions about which designs to characterise experimentally. We present DE-STRESS (DEsigned STRucture Evaluation ServiceS), a web application for evaluating structural models of designed and engineered proteins. DE-STRESS has been designed to be simple, intuitive to use and responsive. It provides a wealth of information regarding designs, as well as tools to help contextualise the results and formally describe the properties that a design requires to be fit for purpose. AvailabilityDE-STRESS is available for non-commercial use, without registration, through the following website: https://pragmaticproteindesign.bio.ed.ac.uk/de-stress/. Source code for the application is available on GitHub: https://github.com/wells-wood-research/de-stress. The data used to generate reference sets is available through a GraphQL API, with the following URL: https://pragmaticproteindesign.bio.ed.ac.uk/big-structure/graphql.

bioinformatics↗

bioRxiv2021

Generation of photocaged nanobodies for in vivo applications using genetic code expansion and computationally guided protein engineering

Nanobodies are becoming increasingly popular as tools for manipulating and visualising proteins in vivo. The ability to control nanobody/antigen interactions using light could provide precise spatiotemporal control over protein function. We develop a general approach to engineer photo-activatable nanobodies using photocaged amino acids that are introduced into the target binding interface by genetic code expansion. Guided by computational alanine scanning and molecular-dynamics simulations, we tune nanobody/target binding affinity to eliminate binding before uncaging. Upon photo-activation, binding is restored. We use this approach to generate improved photocaged variants of two anti-GFP nanobodies. These variants exhibit photo-activatable binding triggered by illumination with 365nm light. We demonstrate that the photocaged nanobodies we have created are highly robust and function in a complex cellular environment. We apply them to control subcellular protein localisation in the nematode worm C. elegans. Our approach provides a rare example of computationally designed proteins being directly applied in living animals and demonstrates the importance of accounting for in vivo effects on protein-protein interactions.

synthetic biology↗