Caenorhabditis elegans AF4/FMR2 Family Homolog affl-2 Regulates Heat-Shock-Induced Gene Expression

Reciprocal best structure hits: using AlphaFold models to discover distant homologues

Motivation

The 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.

Results

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. In addition, we detect potential novel homologs solely with the structural matching approach, which can help to understand the function of uncharacterized proteins and make previously overlooked connections between well-characterized 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.

Availability and Implementation

Information to the discovered homologous protein pairs can be found at the following URL: https://doi.org/10.17863/CAM.87873. The code can be accessed here: https://github.com/VivianMonzon/Reciprocal_Best_Structure_Hits.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Harmonizing model organism data in the Alliance of Genome Resources

The Alliance of Genome Resources (the Alliance) is a combined effort of 7 knowledgebase projects: Saccharomyces Genome Database, WormBase, FlyBase, Mouse Genome Database, the Zebrafish Information Network, Rat Genome Database, and the Gene Ontology Resource. The Alliance seeks to provide several benefits: better service to the various communities served by these projects; a harmonized view of data for all biomedical researchers, bioinformaticians, clinicians, and students; and a more sustainable infrastructure. The Alliance has harmonized cross-organism data to provide useful comparative views of gene function, gene expression, and human disease relevance. The basis of the comparative views is shared calls of orthology relationships and the use of common ontologies. The key types of data are alleles and variants, gene function based on gene ontology annotations, phenotypes, association to human disease, gene expression, protein-protein and genetic interactions, and participation in pathways. The information is presented on uniform gene pages that allow facile summarization of information about each gene in each of the 7 organisms covered (budding yeast, roundworm Caenorhabditis elegans, fruit fly, house mouse, zebrafish, brown rat, and human). The harmonized knowledge is freely available on the alliancegenome.org portal, as downloadable files, and by APIs. We expect other existing and emerging knowledge bases to join in the effort to provide the union of useful data and features that each knowledge base currently provides.

Proteomic analysis of bone marrow-derived mesenchymal stem cell extracellular vesicles from healthy donors: implications for proliferation, angiogenesis, Wnt signaling, and the basement membrane

Background

Bone marrow-derived mesenchymal stem cells (BM-MSCs) have shown therapeutic potential in various in vitro and in vivo studies in cutaneous wound healing. Furthermore, there are ubiquitous studies highlighting the pro-regenerative effects of BM-MSC extracellular vesicles (BM-MSC EVs). The similarities and differences in BM-MSC EV cargo among potential healthy donors are not well understood. Variation in EV protein cargo is important to understand, as it may be useful in identifying potential therapeutic applications in clinical trials. We hypothesized that the donors would share both important similarities and differences in cargo relating to cell proliferation, angiogenesis, Wnt signaling, and basement membrane formation—processes shown to be critical for effective cutaneous wound healing.

Methods

We harvested BM-MSC EVs from four healthy human donors who underwent strict screening for whole bone marrow donation and further Good Manufacturing Practices-grade cell culture expansion for candidate usage in clinical trials. BM-MSC EV protein cargo was determined via mass spectrometry and Proteome Discoverer software. Corresponding proteomic networks were analyzed via the UniProt Consortium and STRING consortium databases.

Results

More than 3000 proteins were identified in each of the donors, sharing > 600 proteins among all donors. Despite inter-donor variation in protein identities, there were striking similarities in numbers of proteins per biological functional category. In terms of biologic function, the proteins were most associated with transport of ions and proteins, transcription, and the cell cycle, relating to cell proliferation. The donors shared essential cargo relating to angiogenesis, Wnt signaling, and basement membrane formation—essential processes in modulating cutaneous wound repair.

Conclusions

Healthy donors of BM-MSC EVs contain important similarities and differences among protein cargo that may play important roles in their pro-regenerative functions. Further studies are needed to correlate proteomic signatures to functional outcomes in cutaneous repair.