Assembling bacterial puzzles: piecing together functions into microbial pathways.
Autor: | Chung HC; Program in Bioinformatics and Computational Biology, Iowa State University, Ames, IA 50011 , USA.; Department of Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, IA 50011, USA., Friedberg I; Department of Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, IA 50011, USA., Bromberg Y; Department of Computer Science, Emory University, Atlanta, GA 30307, USA.; Department of Biology, Emory University, Atlanta, GA 30322, USA. |
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Jazyk: | angličtina |
Zdroj: | NAR genomics and bioinformatics [NAR Genom Bioinform] 2024 Aug 24; Vol. 6 (3), pp. lqae109. Date of Electronic Publication: 2024 Aug 24 (Print Publication: 2024). |
DOI: | 10.1093/nargab/lqae109 |
Abstrakt: | Functional metagenomics enables the study of unexplored bacterial diversity, gene families, and pathways essential to microbial communities. However, discovering biological insights with these data is impeded by the scarcity of quality annotations. Here, we use a co-occurrence-based analysis of predicted microbial protein functions to uncover pathways in genomic and metagenomic biological systems. Our approach, based on phylogenetic profiles, improves the identification of functional relationships, or participation in the same biochemical pathway, between enzymes over a comparable homology-based approach. We optimized the design of our profiles to identify potential pathways using minimal data, clustered functionally related enzyme pairs into multi-enzymatic pathways, and evaluated our predictions against reference pathways in the KEGG database. We then demonstrated a novel extension of this approach to predict inter-bacterial protein interactions amongst members of a marine microbiome. Most significantly, we show our method predicts emergent biochemical pathways between known and unknown functions. Thus, our work establishes a basis for identifying the potential functional capacities of the entire metagenome, capturing previously unknown and abstract functions into discrete putative pathways. (© The Author(s) 2024. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.) |
Databáze: | MEDLINE |
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