Biology subjects

Graham, C. L.

Publications and source records attributed to Graham, C. L..

3 recordsLinked to original sources

bioRxiv2026

CoEVFold suite: user friendly pipelines to visually represent protein coevolution

Multiple sequence alignment (MSA) data underlies current principles in protein folding and protein-protein interaction prediction, from which large language models (LLMs) in tandem with protein datasets, can predict protein structure. However, what is missing are user-friendly tools that enable researchers to predict and demonstrate coevolution - the principal input which these MSAs infer. Here we present tools to identify and visualize coevolution, through a pipeline (CoEVFold) that uses basic direct coupling algorithms derived from GREMLIN and alignment of sequences from MMSEQs2. The pipeline generates a visual representation of coevolution for a single protein but can also represent coevolution of homomeric or heteromeric protein complexes, as well as coevolution within protein networks. The input for this pipeline can be an amino acid sequence, or user input protein structures from Alphafold their own files or the PDB database. In validation of CoEVFolds capabilities, and utilising proteins from known prokaryotic and eukaryotic model systems (Bacillus subtilis, Escherichia coli and Saccharomyces cerevisiae), as well as phage proteins, CoEVFold predicts coevolution between proteins known to interact, proteins known to oligomerise, and coevolution in proteins known to be part of a protein complex. Collectively, these suite of tools, named CoEVFold suite, have broad applicability and provide a useful toolkit to those interested in dissecting protein-protein interactions and networks. AvailabilityThe code is available online at https://colab.research.google.com/drive/1MSSvNTq7KZ4Lr0XTz89vUuK-J3xOTzwS?usp=sharing and Github. https://github.com/MishterBluesky/CoEVFold Supplementary informationSupplementary data is available via Figshare and supplementary materials.

microbiology↗

bioRxiv2026

Chemical genomics screening reveals novel functions for unannotated genes in Vibrio cholerae C6706

Vibrio cholerae, the causative agent of cholera, remains a major global health burden despite ongoing initiatives for vaccination and improved sanitation. Much of the V. cholerae life cycle occurs in aquatic environments, requiring gene functions that enable survival under diverse stresses associated with this niche and during the transition to the human host. Although numerous V. cholerae genome sequences are available, functional annotation across its pan-genome remains incomplete, and many annotated genes lack experimental validation. In this study, we employed a chemical genomics approach to profile fitness phenotypes across 104 diverse stress conditions using a library of 3,026 single-gene mutants of V. cholerae C6706, a widely used research strain. In total, we identified significant growth phenotypes for 1,518 mutants, of which 88 correspond to unannotated (hypothetical or putative) genes. Together, these data provide a comprehensive resource for exploring gene function in V. cholerae, supported by detailed quality metrics and open-access tools to facilitate community-driven discovery. AUTHOR SUMMARYAlthough many bacterial pathogens have been extensively sequenced, we still know relatively little about what many of their genes actually do. In many cases, gene functions are solely predicted by computer algorithms but have not been confirmed in the laboratory, and we can assume that some of those predictions may be incorrect. Chemical genomics -- a method that tests thousands of single-gene mutants under different stresses -- can help reveal what these genes are responsible for. Using this approach, we screened a library of Vibrio cholerae C6706 mutants under 104 different conditions. We found that more than half of the mutants showed measurable effects on growth, including many genes that were previously uncharacterized. Here, we describe our experimental pipeline, present key quality checks, and share how other researchers can use this dataset as a resource to explore V. cholerae mutant phenotypes.

systems biology↗

bioRxiv2025

Computational modelling of toroidal membranes at division and fission sites

The formation of specialised membrane architectures is fundamental to biological processes. Computational modelling of membrane structures offers a means to unravel complex molecular mechanisms that remain inaccessible through in vitro or in vivo approaches. Among these architectures, toroidal membranes, otherwise known as fusion pores or fission pores, occur during the final stages of cell division, exocytosis, endocytosis, and membrane fission; including during the phagocytic-like engulfment of bacterial endospores. Here we have designed MemTorMD, a computational simulation pipeline based on the TS2CG methodology, to enable coarse-grained modelling of free toroidal membranes with biologically-relevant dimensions. This approach allowed us to determine the lipid properties required for stable toroidal membrane formation, providing a biologically accurate simulation surface. Furthermore, we demonstrate the applicability of this approach to investigate the function of proteins that localise at toroidal membranes, and drive molecular events such as membrane fission by a prokaryotic fission protein. Collectively, our work provides insight into membrane and protein behaviour at toroidal membranes and provides a platform for the development of more complex simulations involving additional molecular components at membrane toroids present in a range of processes across life.

microbiology↗