A dynamic multi-tissue model to study human metabolism

Abstract Metabolic modeling enables the study of human metabolism in healthy and in diseased conditions, e.g., the prediction of new drug targets and biomarkers for metabolic diseases. To accurately describe blood and urine metabolite dynamics, the integration of multiple metabolically active tissue...

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Autores principales:	Patricia Martins Conde, Thomas Pfau, Maria Pires Pacheco, Thomas Sauter
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/48b523ae7ac248729247a4ac599f26c2
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id	oai:doaj.org-article:48b523ae7ac248729247a4ac599f26c2
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spelling	oai:doaj.org-article:48b523ae7ac248729247a4ac599f26c22021-12-02T10:49:39ZA dynamic multi-tissue model to study human metabolism10.1038/s41540-020-00159-12056-7189https://doaj.org/article/48b523ae7ac248729247a4ac599f26c22021-01-01T00:00:00Zhttps://doi.org/10.1038/s41540-020-00159-1https://doaj.org/toc/2056-7189Abstract Metabolic modeling enables the study of human metabolism in healthy and in diseased conditions, e.g., the prediction of new drug targets and biomarkers for metabolic diseases. To accurately describe blood and urine metabolite dynamics, the integration of multiple metabolically active tissues is necessary. We developed a dynamic multi-tissue model, which recapitulates key properties of human metabolism at the molecular and physiological level based on the integration of transcriptomics data. It enables the simulation of the dynamics of intra-cellular and extra-cellular metabolites at the genome scale. The predictive capacity of the model is shown through the accurate simulation of different healthy conditions (i.e., during fasting, while consuming meals or during exercise), and the prediction of biomarkers for a set of Inborn Errors of Metabolism with a precision of 83%. This novel approach is useful to prioritize new biomarkers for many metabolic diseases, as well as for the integration of various types of personal omics data, towards the personalized analysis of blood and urine metabolites.Patricia Martins CondeThomas PfauMaria Pires PachecoThomas SauterNature PortfolioarticleBiology (General)QH301-705.5ENnpj Systems Biology and Applications, Vol 7, Iss 1, Pp 1-16 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Patricia Martins Conde Thomas Pfau Maria Pires Pacheco Thomas Sauter A dynamic multi-tissue model to study human metabolism
description	Abstract Metabolic modeling enables the study of human metabolism in healthy and in diseased conditions, e.g., the prediction of new drug targets and biomarkers for metabolic diseases. To accurately describe blood and urine metabolite dynamics, the integration of multiple metabolically active tissues is necessary. We developed a dynamic multi-tissue model, which recapitulates key properties of human metabolism at the molecular and physiological level based on the integration of transcriptomics data. It enables the simulation of the dynamics of intra-cellular and extra-cellular metabolites at the genome scale. The predictive capacity of the model is shown through the accurate simulation of different healthy conditions (i.e., during fasting, while consuming meals or during exercise), and the prediction of biomarkers for a set of Inborn Errors of Metabolism with a precision of 83%. This novel approach is useful to prioritize new biomarkers for many metabolic diseases, as well as for the integration of various types of personal omics data, towards the personalized analysis of blood and urine metabolites.
format	article
author	Patricia Martins Conde Thomas Pfau Maria Pires Pacheco Thomas Sauter
author_facet	Patricia Martins Conde Thomas Pfau Maria Pires Pacheco Thomas Sauter
author_sort	Patricia Martins Conde
title	A dynamic multi-tissue model to study human metabolism
title_short	A dynamic multi-tissue model to study human metabolism
title_full	A dynamic multi-tissue model to study human metabolism
title_fullStr	A dynamic multi-tissue model to study human metabolism
title_full_unstemmed	A dynamic multi-tissue model to study human metabolism
title_sort	dynamic multi-tissue model to study human metabolism
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/48b523ae7ac248729247a4ac599f26c2
work_keys_str_mv	AT patriciamartinsconde adynamicmultitissuemodeltostudyhumanmetabolism AT thomaspfau adynamicmultitissuemodeltostudyhumanmetabolism AT mariapirespacheco adynamicmultitissuemodeltostudyhumanmetabolism AT thomassauter adynamicmultitissuemodeltostudyhumanmetabolism AT patriciamartinsconde dynamicmultitissuemodeltostudyhumanmetabolism AT thomaspfau dynamicmultitissuemodeltostudyhumanmetabolism AT mariapirespacheco dynamicmultitissuemodeltostudyhumanmetabolism AT thomassauter dynamicmultitissuemodeltostudyhumanmetabolism
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A dynamic multi-tissue model to study human metabolism

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