In:
PLOS Computational Biology, Public Library of Science (PLoS), Vol. 18, No. 2 ( 2022-2-23), p. e1009870-
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
1553-7358
DOI:
10.1371/journal.pcbi.1009870
DOI:
10.1371/journal.pcbi.1009870.g001
DOI:
10.1371/journal.pcbi.1009870.g002
DOI:
10.1371/journal.pcbi.1009870.g003
DOI:
10.1371/journal.pcbi.1009870.g004
DOI:
10.1371/journal.pcbi.1009870.g005
DOI:
10.1371/journal.pcbi.1009870.g006
DOI:
10.1371/journal.pcbi.1009870.g007
DOI:
10.1371/journal.pcbi.1009870.t001
DOI:
10.1371/journal.pcbi.1009870.t002
DOI:
10.1371/journal.pcbi.1009870.s001
DOI:
10.1371/journal.pcbi.1009870.s002
DOI:
10.1371/journal.pcbi.1009870.s003
DOI:
10.1371/journal.pcbi.1009870.s004
DOI:
10.1371/journal.pcbi.1009870.s005
DOI:
10.1371/journal.pcbi.1009870.s006
DOI:
10.1371/journal.pcbi.1009870.s007
DOI:
10.1371/journal.pcbi.1009870.s008
DOI:
10.1371/journal.pcbi.1009870.s009
DOI:
10.1371/journal.pcbi.1009870.s010
DOI:
10.1371/journal.pcbi.1009870.s011
DOI:
10.1371/journal.pcbi.1009870.s012
DOI:
10.1371/journal.pcbi.1009870.s013
DOI:
10.1371/journal.pcbi.1009870.s014
DOI:
10.1371/journal.pcbi.1009870.s015
DOI:
10.1371/journal.pcbi.1009870.s016
DOI:
10.1371/journal.pcbi.1009870.r001
DOI:
10.1371/journal.pcbi.1009870.r002
DOI:
10.1371/journal.pcbi.1009870.r003
DOI:
10.1371/journal.pcbi.1009870.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2193340-6
Permalink