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ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species

The availability of genome sequences, annotations, and knowledge of the biochemistry underlying metabolic transformations has led to the generation of metabolic network reconstructions for a wide range of organisms in bacteria, archaea, and eukaryotes. When modeled using mathematical representations...

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Autores principales: Hanna, Eileen Marie, Zhang, Xiaokang, Eide, Marta, Fallahi, Shirin, Furmanek, Tomasz, Yadetie, Fekadu, Zielinski, Daniel Craig, Goksøyr, Anders, Jonassen, Inge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726423/
https://www.ncbi.nlm.nih.gov/pubmed/33324679
http://dx.doi.org/10.3389/fmolb.2020.591406
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author Hanna, Eileen Marie
Zhang, Xiaokang
Eide, Marta
Fallahi, Shirin
Furmanek, Tomasz
Yadetie, Fekadu
Zielinski, Daniel Craig
Goksøyr, Anders
Jonassen, Inge
author_facet Hanna, Eileen Marie
Zhang, Xiaokang
Eide, Marta
Fallahi, Shirin
Furmanek, Tomasz
Yadetie, Fekadu
Zielinski, Daniel Craig
Goksøyr, Anders
Jonassen, Inge
author_sort Hanna, Eileen Marie
collection PubMed
description The availability of genome sequences, annotations, and knowledge of the biochemistry underlying metabolic transformations has led to the generation of metabolic network reconstructions for a wide range of organisms in bacteria, archaea, and eukaryotes. When modeled using mathematical representations, a reconstruction can simulate underlying genotype-phenotype relationships. Accordingly, genome-scale metabolic models (GEMs) can be used to predict the response of organisms to genetic and environmental variations. A bottom-up reconstruction procedure typically starts by generating a draft model from existing annotation data on a target organism. For model species, this part of the process can be straightforward, due to the abundant organism-specific biochemical data. However, the process becomes complicated for non-model less-annotated species. In this paper, we present a draft liver reconstruction, ReCodLiver0.9, of Atlantic cod (Gadus morhua), a non-model teleost fish, as a practicable guide for cases with comparably few resources. Although the reconstruction is considered a draft version, we show that it already has utility in elucidating metabolic response mechanisms to environmental toxicants by mapping gene expression data of exposure experiments to the resulting model.
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spelling pubmed-77264232020-12-14 ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species Hanna, Eileen Marie Zhang, Xiaokang Eide, Marta Fallahi, Shirin Furmanek, Tomasz Yadetie, Fekadu Zielinski, Daniel Craig Goksøyr, Anders Jonassen, Inge Front Mol Biosci Molecular Biosciences The availability of genome sequences, annotations, and knowledge of the biochemistry underlying metabolic transformations has led to the generation of metabolic network reconstructions for a wide range of organisms in bacteria, archaea, and eukaryotes. When modeled using mathematical representations, a reconstruction can simulate underlying genotype-phenotype relationships. Accordingly, genome-scale metabolic models (GEMs) can be used to predict the response of organisms to genetic and environmental variations. A bottom-up reconstruction procedure typically starts by generating a draft model from existing annotation data on a target organism. For model species, this part of the process can be straightforward, due to the abundant organism-specific biochemical data. However, the process becomes complicated for non-model less-annotated species. In this paper, we present a draft liver reconstruction, ReCodLiver0.9, of Atlantic cod (Gadus morhua), a non-model teleost fish, as a practicable guide for cases with comparably few resources. Although the reconstruction is considered a draft version, we show that it already has utility in elucidating metabolic response mechanisms to environmental toxicants by mapping gene expression data of exposure experiments to the resulting model. Frontiers Media S.A. 2020-11-26 /pmc/articles/PMC7726423/ /pubmed/33324679 http://dx.doi.org/10.3389/fmolb.2020.591406 Text en Copyright © 2020 Hanna, Zhang, Eide, Fallahi, Furmanek, Yadetie, Zielinski, Goksøyr and Jonassen. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Hanna, Eileen Marie
Zhang, Xiaokang
Eide, Marta
Fallahi, Shirin
Furmanek, Tomasz
Yadetie, Fekadu
Zielinski, Daniel Craig
Goksøyr, Anders
Jonassen, Inge
ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species
title ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species
title_full ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species
title_fullStr ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species
title_full_unstemmed ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species
title_short ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species
title_sort recodliver0.9: overcoming challenges in genome-scale metabolic reconstruction of a non-model species
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726423/
https://www.ncbi.nlm.nih.gov/pubmed/33324679
http://dx.doi.org/10.3389/fmolb.2020.591406
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