Comparative analyses of parasites with a comprehensive database of genome-scale metabolic models.

Autor: Carey MA; Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America.; Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America., Medlock GL; Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America., Stolarczyk M; Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America.; Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America., Petri WA Jr; Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America., Guler JL; Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America.; Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America., Papin JA; Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America.; Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America.; Department of Biochemistry & Molecular Genetics, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America.
Jazyk: angličtina
Zdroj: PLoS computational biology [PLoS Comput Biol] 2022 Feb 23; Vol. 18 (2), pp. e1009870. Date of Electronic Publication: 2022 Feb 23 (Print Publication: 2022).
DOI: 10.1371/journal.pcbi.1009870
Abstrakt: Protozoan parasites cause diverse diseases with large global impacts. Research on the pathogenesis and biology of these organisms is limited by economic and experimental constraints. Accordingly, studies of one parasite are frequently extrapolated to infer knowledge about another parasite, across and within genera. Model in vitro or in vivo systems are frequently used to enhance experimental manipulability, but these systems generally use species related to, yet distinct from, the clinically relevant causal pathogen. Characterization of functional differences among parasite species is confined to post hoc or single target studies, limiting the utility of this extrapolation approach. To address this challenge and to accelerate parasitology research broadly, we present a functional comparative analysis of 192 genomes, representing every high-quality, publicly-available protozoan parasite genome including Plasmodium, Toxoplasma, Cryptosporidium, Entamoeba, Trypanosoma, Leishmania, Giardia, and other species. We generated an automated metabolic network reconstruction pipeline optimized for eukaryotic organisms. These metabolic network reconstructions serve as biochemical knowledgebases for each parasite, enabling qualitative and quantitative comparisons of metabolic behavior across parasites. We identified putative differences in gene essentiality and pathway utilization to facilitate the comparison of experimental findings and discovered that phylogeny is not the sole predictor of metabolic similarity. This knowledgebase represents the largest collection of genome-scale metabolic models for both pathogens and eukaryotes; with this resource, we can predict species-specific functions, contextualize experimental results, and optimize selection of experimental systems for fastidious species.
Competing Interests: The authors have declared that no competing interests exist.
Databáze: MEDLINE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje