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Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels
Metabolism is a highly compartmentalized process that provides building blocks for biomass generation during development, homeostasis, and wound healing, and energy to support cellular and organismal processes. In metazoans, different cells and tissues specialize in different aspects of metabolism....
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7537831/ https://www.ncbi.nlm.nih.gov/pubmed/33022146 http://dx.doi.org/10.15252/msb.20209649 |
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author | Yilmaz, Lutfu Safak Li, Xuhang Nanda, Shivani Fox, Bennett Schroeder, Frank Walhout, Albertha JM |
author_facet | Yilmaz, Lutfu Safak Li, Xuhang Nanda, Shivani Fox, Bennett Schroeder, Frank Walhout, Albertha JM |
author_sort | Yilmaz, Lutfu Safak |
collection | PubMed |
description | Metabolism is a highly compartmentalized process that provides building blocks for biomass generation during development, homeostasis, and wound healing, and energy to support cellular and organismal processes. In metazoans, different cells and tissues specialize in different aspects of metabolism. However, studying the compartmentalization of metabolism in different cell types in a whole animal and for a particular stage of life is difficult. Here, we present MEtabolic models Reconciled with Gene Expression (MERGE), a computational pipeline that we used to predict tissue‐relevant metabolic function at the network, pathway, reaction, and metabolite levels based on single‐cell RNA‐sequencing (scRNA‐seq) data from the nematode Caenorhabditis elegans. Our analysis recapitulated known tissue functions in C. elegans, captured metabolic properties that are shared with similar tissues in human, and provided predictions for novel metabolic functions. MERGE is versatile and applicable to other systems. We envision this work as a starting point for the development of metabolic network models for individual cells as scRNA‐seq continues to provide higher‐resolution gene expression data. |
format | Online Article Text |
id | pubmed-7537831 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75378312020-10-08 Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels Yilmaz, Lutfu Safak Li, Xuhang Nanda, Shivani Fox, Bennett Schroeder, Frank Walhout, Albertha JM Mol Syst Biol Articles Metabolism is a highly compartmentalized process that provides building blocks for biomass generation during development, homeostasis, and wound healing, and energy to support cellular and organismal processes. In metazoans, different cells and tissues specialize in different aspects of metabolism. However, studying the compartmentalization of metabolism in different cell types in a whole animal and for a particular stage of life is difficult. Here, we present MEtabolic models Reconciled with Gene Expression (MERGE), a computational pipeline that we used to predict tissue‐relevant metabolic function at the network, pathway, reaction, and metabolite levels based on single‐cell RNA‐sequencing (scRNA‐seq) data from the nematode Caenorhabditis elegans. Our analysis recapitulated known tissue functions in C. elegans, captured metabolic properties that are shared with similar tissues in human, and provided predictions for novel metabolic functions. MERGE is versatile and applicable to other systems. We envision this work as a starting point for the development of metabolic network models for individual cells as scRNA‐seq continues to provide higher‐resolution gene expression data. John Wiley and Sons Inc. 2020-10-06 /pmc/articles/PMC7537831/ /pubmed/33022146 http://dx.doi.org/10.15252/msb.20209649 Text en © 2020 The Authors. Published under the terms of the CC BY 4.0 license This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Yilmaz, Lutfu Safak Li, Xuhang Nanda, Shivani Fox, Bennett Schroeder, Frank Walhout, Albertha JM Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels |
title | Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels |
title_full | Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels |
title_fullStr | Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels |
title_full_unstemmed | Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels |
title_short | Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels |
title_sort | modeling tissue‐relevant caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7537831/ https://www.ncbi.nlm.nih.gov/pubmed/33022146 http://dx.doi.org/10.15252/msb.20209649 |
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