Biology subjects

Bateman, A.

Publications and source records attributed to Bateman, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Large-scale structure prediction of DUF-containing protein-protein interactions

Motivation: Continuing advances in genome and metagenome sequencing expand the number of identified conserved protein families that remain functionally uncharacterized and contain domains of unknown function (DUFs). Functional-association resources such as STRING provide biological context, but mostly do not distinguish indirect association from physical interaction. We assessed whether AlphaFold 3 complex prediction, combined with STRING evidence and domain-level analysis of interfaces and interaction partners, can help identify and characterize DUF-containing proteins. Results: We generated four structural-prediction cohorts from STRING associations involving DUF-containing proteins and evaluated the predicted complexes using interface ipSAE, average pLDDT and buried surface area. An L2-regularized logistic regression model was trained on an initial cohort of predictions from high-confidence STRING associations to prioritize DUF-containing candidates likely to produce structurally confident AlphaFold 3 complexes. The model was then applied across all 12,535 organisms represented in STRING v12.0, followed by grouping into DUF-family and partner-architecture modules, covering 2,076 unique DUF families. The final L2-model screen contained 12,298 successfully modelled protein pairs, including 1,208 (9.82%) complexes meeting a strict-confidence criterion and 2,433 (19.78%) meeting a more liberal confidence criterion. Two examples suggest roles for DUF4130 in nucleic-acid-associated radical-SAM biology and DUF5819 in a bacterial system related to vitamin-K-dependent carboxylation. Availability and implementation: Predicted structures and associated metadata are available through Zenodo at https://doi.org/10.5281/zenodo.21875362. The model implementation and code used to generate the analyses and figures are available at https://github.com/linoriep/Proteome-scale-structure-prediction-of-DUF-containing-protein-protein-interactions.

bioinformatics↗

bioRxiv2026

Structural basis of biofilm formation mediated by the Pseudomonas aeruginosa fibrillar adhesin CdrA

Many bacteria, including the important human pathogen Pseudomonas aeruginosa, are naturally found in antibiotic-tolerant, multicellular biofilms. Cell-cell interactions within P. aeruginosa biofilms are mediated by a large fibrillar adhesin called CdrA in an extracellular polysaccharide-dependent manner. Here, we report an electron cryomicroscopy structure of the 60 kDa CdrA adhesive N-terminus, which combined with electron cryotomography of focused-ion beam milled specimens, allows us to derive a complete in situ model of the native adhesin. Our structure reveals a small adhesive domain (called ADEPT) at the distal tip of CdrA that is nearly perfectly conserved across the P. aeruginosa pangenome, with structural similarity to previously reported sugar-binding domains in multiple bacterial species. Inhibitory nanobodies targeting CdrA that reduce biofilm formation bind to epitopes in, or close to, the ADEPT on bacterial cells. Furthermore, structure-guided mutagenesis of residues within the ADEPT abolishes bacterial aggregation, and genomic deletion of the whole ADEPT leads to strong attenuation of biofilm formation. Our data forms a rational basis for future targeted inhibition of pathogenic P. aeruginosa biofilms and elucidates the mechanism of biofilm formation mediated by fibrillar adhesins that are widespread in bacteria.

microbiology↗

bioRxiv2026

Detrimental effects of advanced glycation end-products (AGEs) on a human neuromuscular junction co-culture model

The neuromuscular junction (NMJ) is a specialised synapse between motor neurons and skeletal muscle, and its progressive deterioration contributes to age-related and metabolic disease-associated declines in muscle function. Advanced glycation end-products (AGEs) accumulate in tissues during ageing, diabetes, and chronic metabolic dysfunction and have been implicated in neuromuscular degeneration, yet their effects on the intact NMJ have not previously been examined in a human model system. This study employed a fully human, serum-free, and neural growth factor-free NMJ co-culture system, combining neural progenitor cells with immortalised human myoblasts derived from an 83-year-old donor, to investigate the effects of AGE exposure on neuromuscular integrity across structural, metabolic, functional, and secretory outcomes. AGE exposure induced significant reductions in motor neuron axonal length, myotube remodelling with centralised nuclear positioning, mitochondrial membrane depolarisation, elevated mitochondrial superoxide production, mitochondrial uncoupling, and reductions in spontaneous contraction intensity and frequency. Neurotrophic and myogenic growth factor signalling was significantly downregulated in AGE-treated co-cultures. These findings identify the NMJ as a sensitive target of glycation stress and establish this fully human co-culture platform as a physiologically relevant model for investigating glycation-related neuromuscular pathology and evaluating candidate therapeutic interventions.

cell biology↗

bioRxiv2026

Folding the unfoldable 2: using AlphaFold and ESMFold to explore spurious proteins

MotivationSpurious protein sequences, resulting from gene prediction errors, theoretically should not yield folded structures. AlphaFold2 was previously shown to predict short spurious sequences with high pLDDT scores and was therefore unlikely to distinguish between real proteins and spurious proteins which are usually short. We evaluate whether newer structure prediction methods (ESMFold and AlphaFold3) similarly predict short sequences with high pLDDT or if they better discriminate between spurious and real proteins. ResultsAll three structure prediction methods (ESMFold, AlphaFold2, and AlphaFold3) predict short spurious sequences from AntiFam with unexpectedly high pLDDT scores, however the discrimination between spurious and real proteins improves beyond 100 amino acids. By analysing sequences with disparate pTM and pLDDT scores, we identified two likely spurious shadow ORFs in Swiss-Prot and one potentially non-spurious AntiFam entry. Using the structure prediction scores, we developed a Gaussian Process Model and evaluated its performance on AlphaFold DB, identifying potential spurious proteins at scale. While limited on its own, this model can increase confidence in spurious protein identification when combined with other methods. AvailabilityStructure predictions are available at https://doi.org/10.5281/zenodo.18390113. Model implementation and figure generation code are available at https://github.com/0rra/fold_unfold2.

bioinformatics↗

bioRxiv2026

Viral non-coding RNA structure annotation and API-based data retrieval with Rfam and R2DT

Rfam is a comprehensive database of non-coding RNA (ncRNA) families providing curated sequence alignments, consensus secondary structures, and covariance models for thousands of RNA families. The database is essential for identifying structured non-coding RNAs in newly sequenced genomes and understanding RNA structure-function relationships. Here we present computational protocols for automated ncRNA annotation of viral genomes, and for programmatic interaction with Rfam through its RESTful API. We showcase genome-wide RNA structure visualization from a genome sequence and from a multiple sequence alignment by generating comprehensive 2D structure diagrams using newly developed features in R2DT. We also present practical examples for retrieving family metadata, downloading alignments, accessing secondary structures, and searching user sequences from the Rfam API. These methods enable researchers in virology and RNA biology to integrate Rfam data into custom bioinformatics pipelines, comparative analyses, and machine learning workflows.

bioinformatics↗

bioRxiv2025

GOFlowLLM - Curating miRNA literature with Large Language Models and flowcharts

The exponential growth of non-coding RNA research--with over 230,000 papers published since 2000--has created an urgent knowledge management crisis in molecular biology. Despite their crucial regulatory roles, microRNAs (miRNAs) face a significant curation bottleneck, with only 1,400 articles manually curated to the Gene Ontology (GO) knowledgebase over a decade. We present GOFlowLLM, an automated curation pipeline powered by reasoning-enabled Large Language Models (LLMs) that follows established GO curation flowcharts to extract and structure miRNA-mediated gene silencing data at scale. When evaluated on existing curation, GOFlowLLM selects the correct GO term in 90% of cases. Curators also agree with 95% of the systems reasoning steps and 90% of the evidence selected. Applied to 6,996 previously uncurated articles, our system identified 2,538 new candidate GO annotations on 1,785 articles in just 58 hours--potentially doubling the available miRNA GO curation. Manual review of a subset of these annotations shows that curators agreed with the selected term in 87% of cases, the models reasoning in 92% of cases, and the extracted evidence in 93%. GOFlowLLM demonstrates how LLMs can significantly accelerate biocuration while maintaining high-quality standards by following expert-designed reasoning frameworks. The integration of reasoning traces in our system provides transparent justification for annotations that can be reviewed by human curators, addressing one of the key challenges in adopting AI for scientific curation, potentially transforming how we manage the growing corpus of scientific knowledge in molecular biology. GoFlowLLM is available on github: https://github.com/RNAcentral/GO_Flow_LLM.

bioinformatics↗

bioRxiv2025

A global survey of intramolecular isopeptide bonds

Many protein domains harbour covalent intramolecular bonds that enhance their stability and resistance to thermal, mechanical and proteolytic insults. Intramolecular isopeptide bonds represent one such covalent interaction, yet their distribution across protein domains and organisms has been largely unexplored. Here, we sought to address this by employing a large-scale prediction of intramolecular isopeptide bonds in the AlphaFold database using the structural template-based software Isopeptor. Our findings reveal an extensive phyletic distribution in surface proteins resembling fibrillar adhesins and pilins. All identified intramolecular isopeptide bonds are found in two structurally distinct folds, CnaA-like or CnaB-like, from a relatively small set of related Pfam families, including ten novel families that we predict to contain intramolecular isopeptide bonds. One CnaA-like domain of unknown function, DUF11 (renamed here to "CLIPPER") is broadly distributed in cell-surface proteins from Gram-positive bacteria, Gram-negative bacteria, and archaea, and is structurally and biophysically characterised in this work. Using X-ray crystallography, we resolve a CLIPPER domain from a Gram-negative fibrillar adhesin that contains an intramolecular isopeptide bond and further demonstrate that it imparts thermostability and resistance to proteolysis. Our findings demonstrate the extensive distribution of intramolecular isopeptide bond-containing protein domains in nature, and structurally resolve the previously cryptic CLIPPER domain.

bioinformatics↗

bioRxiv2025

Physiologic recovery of Mycobacterium tuberculosis from drug injury: A molecular study of post antibiotic effect in mice

Post-antibiotic effect (PAE) describes the delayed recovery of bacteria following antibiotic exposure. PAE is thought to underlie tuberculosis (TB) treatment forgiveness, i.e. the capacity of regimens to tolerate non-adherence. The basis of PAE in Mycobacterium tuberculosis (Mtb) remains poorly understood, partly because PAE has conventionally been measured based on change in Mtb burden in vitro rather than change in Mtb physiology in vivo. We investigated Mtb physiologic recovery in the BALB/c mouse model following sub-curative 2- and 4-week durations of the standard isoniazid, rifampin, pyrazinamide, ethambutol (HRZE) treatment. Measurement of rRNA synthesis via the RS ratio(R) and the entire transcriptome via SEARCH-TB elucidated the dynamics of physiologic recovery. Mtb burden did not increase over 28 days of drug-free post-treatment recovery, indicating prolonged PAE in vivo. The RS ratio indicated that Mtb ribosomal RNA synthesis resumed within four days of treatment interruption. However, transcriptional changes indicative of metabolic reactivation were delayed for over two weeks. Processes critical for replication, including expression of genes involved in protein and cell wall synthesis, remained suppressed throughout 28 days post-treatment. Longer treatment induced more extensive physiologic perturbation and was associated with slower and less complete recovery. Expression of processes that are typically induced by environmental stress (e.g., DosR regulon, universal stress proteins, and heat shock proteins) exhibited the reverse, decreasing during drug treatment and rising during recovery. These findings provide a new basis for understanding PAE based on drug-induced injury and physiologic recovery. Following relatively short durations of HRZE, physiologic recovery of Mtb was a slow, sequential and incomplete process in vivo. Our observation that longer treatment resulted in even slower recovery suggests that Mtb may progressively lose capacity to recover. This work establishes a tractable experimental framework for quantifying the forgiveness of new TB treatment regimens in vivo.

microbiology↗

bioRxiv2024

Isopeptor: a tool for detecting intramolecular isopeptide bonds in protein structures

MotivationIntramolecular isopeptide bonds contribute to the structural stability of proteins, and have primarily been identified in domains of bacterial fibrillar adhesins and pili. At present, there is no systematic method available to detect them in newly determined molecular structures. This can result in mis-annotations and incorrect modelling. ResultsHere, we present Isopeptor, a computational tool designed to predict the presence of intramolecular isopeptide bonds in experimentally determined structures. Isopeptor utilizes structure-guided template matching via the Jess software, combined with a logistic regression classifier that incorporates Root Mean Square Deviation (RMSD) and relative solvent accessible area (rASA) as key features. The tool demonstrates a recall of 1.0 and a precision of 0.95 when tested on a Protein Data Bank (PDB) subset of domains known to contain intramolecular isopeptide bonds that have been deposited with incorrectly modelled geometries. Isopeptors python-based implementation supports integration into bioinformatics workflows, enabling early detection and prediction of isopeptide bonds during protein structure modelling. Availability and implementationIsopeptor is implemented in python and can be accessed via the command line, through a python API or via a Google Colaboratory implementation (https://colab.research.google.com/github/FranceCosta/Isopeptor_development/blob/main/notebooks/Isopeptide_finder.ipynb). Source code is hosted on GitHub (https://github.com/FranceCosta/isopeptor) and can be installed via the python package installation manager PIP.

bioinformatics↗

bioRxiv2024

Rfam 15: RNA families database in 2025

The Rfam database, a widely-used repository of non-coding RNA (ncRNA) families, has undergone significant updates in release 15.0. This paper introduces major improvements, including the expansion of Rfamseq to 26, 106 genomes, a 76% increase, incorporating the latest UniProt reference proteomes and additional viral genomes. Sixty-five RNA families were enhanced using experimentally determined 3D structures, improving the accuracy of consensus secondary structures and annotations. R-scape covariation analysis was used to refine structural predictions in 26 families. Gene Ontology and Sequence Ontology annotations were comprehensively updated, increasing GO term coverage to 75% of families. The release adds 14 new Hepatitis C Virus RNA families and completes microRNA family synchronisation with miRBase, resulting in 1, 603 microRNA families. New data types, including FULL alignments, have been implemented. Integration with APICURON for improved curator attribution and multiple website enhancements further improve user experience. These updates significantly expand Rfams coverage and improve annotation quality, reinforcing its critical role in RNA research, genome annotation, and the development of machine learning models. Rfam is freely available at https://rfam.org. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/614430v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@9b1898org.highwire.dtl.DTLVardef@6bc030org.highwire.dtl.DTLVardef@16b789org.highwire.dtl.DTLVardef@16b8577_HPS_FORMAT_FIGEXP M_FIG Rfam has undergone a major update with the release of 15.0. We have increased the number of genomes in our sequence database Rfamseq by 75%, completed the synchronisation with miRBase and improved 65 families using 3D structures. C_FIG

genomics↗

bioRxiv2023

A novel subgroup of light-driven sodium pumps with an additional Schiff base counterion

Light-driven sodium pumps (NaRs) are unique ion-transporting microbial rhodopsins. The major group of NaRs is characterized by an NDQ motif and has two aspartic acid residues in the central region essential for sodium transport. Here we identified a new subgroup of the NDQ rhodopsins bearing an additional glutamic acid residue in the close vicinity to the retinal Schiff base. We thoroughly characterized a member of this subgroup, namely the protein ErNaR from Erythrobacter sp. HL-111 and showed that the additional glutamic acid results in almost complete loss of pH sensitivity for sodium-pumping activity, which is in contrast to previously studied NaRs. ErNaR is capable of transporting sodium efficiently even at acidic pH levels. X-ray crystallography and single particle cryo-electron microscopy reveal that the additional glutamic acid residue mediates the connection between the other two Schiff base counterions and strongly interacts with the aspartic acid of the characteristic NDQ motif. Hence, it reduces its pKa. Our findings shed light on a new subgroup of NaRs and might serve as a basis for their rational optimization for optogenetics.

biophysics↗

bioRxiv2023

What is hidden in the darkness? Deep-learning assisted large-scale protein family curation uncovers novel protein families and folds

Driven by the development and upscaling of fast genome sequencing and assembly pipelines, the number of protein-coding sequences deposited in public protein sequence databases is increasing exponentially. Recently, the dramatic success of deep learning-based approaches applied to protein structure prediction has done the same for protein structures. We are now entering a new era in protein sequence and structure annotation, with hundreds of millions of predicted protein structures made available through the AlphaFold database. These models cover most of the catalogued natural proteins, including those difficult to annotate for function or putative biological role based on standard, homology-based approaches. In this work, we quantified how much of such "dark matter" of the natural protein universe was structurally illuminated by AlphaFold2 and modelled this diversity as an interactive sequence similarity network that can be navigated at https://uniprot3d.org/atlas/AFDB90v4. In the process, we discovered multiple novel protein families by searching for novelties from sequence, structure, and semantic perspectives. We added a number of them to Pfam, and experimentally demonstrate that one of these belongs to a novel superfamily of translation-targeting toxin-antitoxin systems, TumE-TumA. This work highlights the role of large-scale, evolution-driven protein comparison efforts in combination with structural similarities, genomic context conservation, and deep-learning based function prediction tools for the identification of novel protein families, aiding not only annotation and classification efforts but also the curation and prioritisation of target proteins for experimental characterisation.

bioinformatics↗

bioRxiv2022

Expanding the repertoire of human tandem repeat RNA-binding proteins

Protein regions consisting of arrays of tandem repeats are known to bind other molecular partners, including nucleic acid molecules. Although the interactions between repeat proteins and DNA are already widely explored, studies characterising tandem repeat RNA-binding proteins are lacking. We performed a large-scale analysis of human proteins devoted to expanding the knowledge about tandem repeat proteins experimentally reported as RNA-binding molecules. This work is timely because of the release of a full set of accurate structural models for the human proteome amenable to repeat detection using structural methods. We identified 219 tandem repeat proteins that bind RNA molecules and characterised the overlap between repeat regions and RNA-binding regions as a first step towards assessing their functional relationship. Our results showed that the combination of sequence and structural methods finds more tandem repeat proteins than either method alone. We observed differences in the characteristics of regions predicted as repetitive by sequence-based or structure-based computational methods in terms of their sequence composition, their functions and their protein domains.

bioinformatics↗

bioRxiv2022

Reciprocal Best Structure Hits: Using AlphaFold models to discover distant homologues

1The conventional methods to detect homologous protein pairs use the comparison of protein sequences. But the sequences of two homologous proteins may diverge significantly and consequently may be undetectable by standard approaches. The release of the AlphaFold 2.0 software enables the prediction of highly accurate protein structures and opens many opportunities to advance our understanding of protein functions, including the detection of homologous protein structure pairs. In this proof-of-concept work, we search for the closest homologous protein pairs using the structure models of five model organisms from the AlphaFold database. We compare the results with homologous protein pairs detected by their sequence similarity and show that the structural matching approach finds a similar set of results. Additionally, we detect potential novel homologues solely with the structural matching approach, which can help to understand the function of uncharacterised proteins and make previously overlooked connections between well-characterised proteins. We also observe limitations of our implementation of the structure based approach, particularly when handling highly disordered proteins or short protein structures. Our work shows that high accuracy protein structure models can be used to discover homologous protein pairs, and we expose areas for improvement of this structural matching approach.

bioinformatics↗

bioRxiv2021

Large Scale Discovery of Microbial Fibrillar Adhesins and Identification of Novel Adhesive Domain Families

Fibrillar adhesins are bacterial cell surface proteins that mediate interactions with the environment including host cells during colonisation or other bacteria during biofilm formation. These proteins are characterised by a stalk that projects the adhesive domain closer to the binding target. Fibrillar adhesins evolve quickly and thus can be difficult to computationally identify, yet they represent an important component for understanding bacterial host interactions. To detect novel fibrillar adhesins we developed a random forest prediction approach based on common characteristics we identified for this protein class. We applied this approach to Firmicute and Actinobacterial proteomes, yielding over 6,500 confidently predicted fibrillar adhesins. To verify the approach we investigated predicted fibrillar adhesins that lacked a known adhesive domain. Based on these proteins, we identified 24 sequence clusters representing potential novel members of adhesive domain families. We used AlphaFold to verify that 15 clusters showed structural similarity to known adhesive domains such as the TED domain. Overall our study has made a significant contribution to the number of known fibrillar adhesins and has enabled us to identify novel members of adhesive domain families involved in the bacterial pathogenesis. ImportanceFibrillar adhesins are a class of bacterial cell surface proteins that enable bacteria to interact with their environment. We developed a Machine Learning approach to identify fibrillar adhesins and applied this classification approach on the Firmicutes and Actinobacteria Reference Proteomes. This method allowed us to detect a high number of novel fibrillar adhesins, and also novel members of adhesive domain families. To confirm our predictions of these potential adhesin protein domains, we predicted their structure using the AlphaFold tool.

bioinformatics↗

bioRxiv2020

Periscope Proteins are variable length regulators of bacterial cell surface interactions

Changes at the cell surface enable bacteria to survive in dynamic environments, such as diverse niches of the human host. Here, we reveal "Periscope Proteins" as a widespread mechanism of bacterial surface alteration mediated through protein length variation. Tandem arrays of highly similar folded domains can form an elongated rod-like structure; thus variation in the number of domains determines how far an N-terminal host ligand binding domain projects from the cell surface. Supported by newly-available long-read genome sequencing data, we propose this new class could contain over 50 distinct proteins, including those implicated in host colonisation and biofilm formation by human pathogens. In large multi-domain proteins, sequence divergence between adjacent domains appears to reduce inter-domain misfolding. Periscope Proteins break this "rule", suggesting their length variability plays an important role in regulating bacterial interactions with host surfaces, other bacteria and the immune system.

microbiology↗

bioRxiv2020

Discovery of Fibrillar Adhesins across Bacterial Species

BackgroundFibrillar adhesins are long multidomain proteins attached at the cell surface and composed of at least one adhesive domain and multiple tandemly repeated domains, which build an elongated stalk that projects the adhesive domain beyond the bacterial cell surface. They are an important yet understudied class of proteins that mediate interactions of bacteria with their environment. This study aims to characterize fibrillar adhesins in a wide range of bacterial phyla and to identify new fibrillar adhesin-like proteins to improve our understanding of host-bacteria interactions. ResultsBy careful search for fibrillar adhesins in the literature and by computational analysis we identified 75 stalk domains and 24 adhesive domains. Based on the presence of these domains in the UniProt Reference Proteomes database, we identified and analysed 3,388 fibrillar adhesin-like proteins across species of the most common bacterial phyla. We found that the bacterial proteomes with the highest fraction of fibrillar adhesins include several known pathogens. We further enumerate the adhesive and stalk domain combinations found in nature and demonstrate that fibrillar adhesins have complex and variable domain architectures, which differ across species. By analysing the domain architecture of fibrillar adhesins we show that in Gram positive bacteria adhesive domains are mostly positioned at the N-terminus of the protein with the cell surface anchor at the C-terminus, while their positions are more variable in Gram negative bacteria. We provide an open repository of fibrillar adhesin-like proteins and domains to facilitate downstream studies of this class of bacterial surface proteins. ConclusionThis study provides a domain-based characterization of fibrillar adhesins and demonstrates that they are widely found across the main bacterial phyla. We have discovered numerous novel fibrillar adhesins and improved the understanding of how pathogens might adhere to and subsequently invade into host cells.

microbiology↗

bioRxiv2020

Cryo-EM structures of human RNA polymerase III in its unbound and transcribing states

ABSTRACTRNA polymerase III (Pol III) synthesises tRNAs and other short, essential RNAs. Human Pol III misregulation is linked to tumour transformation, neurodegenerative and developmental disorders, and increased sensitivity to viral infections. Pol III inhibition increases longevity in different animals but also promotes intracellular bacterial growth owing to its role in the immune system. This highlights the importance to better understand human Pol III transcription on a molecular level. Here, we present cryo-EM structures at 2.8 to 3.3 Å resolution of transcribing and unbound human Pol III purified from human suspension cells that were gene-edited by CRISPR-Cas9. We observe insertion of the TFIIS-like subunit RPC10 into the polymerase funnel, providing insights into how RPC10 triggers transcription termination. Our structures also resolve elements absent from S. cerevisiae Pol III such as the winged-helix domains of RPC5 and an iron-sulphur cluster in RPC6, which tethers the heterotrimer subcomplex to the Pol III core. The cancer-associated RPC7α isoform binds the polymerase clamp, potentially interfering with Pol III inhibition by the tumour suppressor MAF1, which may explain why overexpressed RPC7α enhances tumour transformation. Finally, the human Pol III structure allows mapping of disease-related mutations and might contribute to developing inhibitors that selectively target Pol III for therapeutic interventions.Competing Interest StatementThe authors have declared no competing interest.View Full Text

molecular biology↗