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Metabolomic Analysis in Brain Research: Opportunities and Challenges

Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s). Therefore, quantifying an accurate...

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Autores principales: Vasilopoulou, Catherine G., Margarity, Marigoula, Klapa, Maria I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4878281/
https://www.ncbi.nlm.nih.gov/pubmed/27252656
http://dx.doi.org/10.3389/fphys.2016.00183
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author Vasilopoulou, Catherine G.
Margarity, Marigoula
Klapa, Maria I.
author_facet Vasilopoulou, Catherine G.
Margarity, Marigoula
Klapa, Maria I.
author_sort Vasilopoulou, Catherine G.
collection PubMed
description Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s). Therefore, quantifying an accurate metabolic network activity map under various physiological conditions is among the major objectives of systems biology in the context of many biological applications. Especially for CNS, metabolic network activity analysis can substantially enhance our knowledge about the complex structure of the mammalian brain and the mechanisms of neurological disorders, leading to the design of effective therapeutic treatments. Metabolomics has emerged as the high-throughput quantitative analysis of the concentration profile of small molecular weight metabolites, which act as reactants and products in metabolic reactions and as regulatory molecules of proteins participating in many biological processes. Thus, the metabolic profile provides a metabolic activity fingerprint, through the simultaneous analysis of tens to hundreds of molecules of pathophysiological and pharmacological interest. The application of metabolomics is at its standardization phase in general, and the challenges for paving a standardized procedure are even more pronounced in brain studies. In this review, we support the value of metabolomics in brain research. Moreover, we demonstrate the challenges of designing and setting up a reliable brain metabolomic study, which, among other parameters, has to take into consideration the sex differentiation and the complexity of brain physiology manifested in its regional variation. We finally propose ways to overcome these challenges and design a study that produces reproducible and consistent results.
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spelling pubmed-48782812016-06-01 Metabolomic Analysis in Brain Research: Opportunities and Challenges Vasilopoulou, Catherine G. Margarity, Marigoula Klapa, Maria I. Front Physiol Physiology Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s). Therefore, quantifying an accurate metabolic network activity map under various physiological conditions is among the major objectives of systems biology in the context of many biological applications. Especially for CNS, metabolic network activity analysis can substantially enhance our knowledge about the complex structure of the mammalian brain and the mechanisms of neurological disorders, leading to the design of effective therapeutic treatments. Metabolomics has emerged as the high-throughput quantitative analysis of the concentration profile of small molecular weight metabolites, which act as reactants and products in metabolic reactions and as regulatory molecules of proteins participating in many biological processes. Thus, the metabolic profile provides a metabolic activity fingerprint, through the simultaneous analysis of tens to hundreds of molecules of pathophysiological and pharmacological interest. The application of metabolomics is at its standardization phase in general, and the challenges for paving a standardized procedure are even more pronounced in brain studies. In this review, we support the value of metabolomics in brain research. Moreover, we demonstrate the challenges of designing and setting up a reliable brain metabolomic study, which, among other parameters, has to take into consideration the sex differentiation and the complexity of brain physiology manifested in its regional variation. We finally propose ways to overcome these challenges and design a study that produces reproducible and consistent results. Frontiers Media S.A. 2016-05-24 /pmc/articles/PMC4878281/ /pubmed/27252656 http://dx.doi.org/10.3389/fphys.2016.00183 Text en Copyright © 2016 Vasilopoulou, Margarity and Klapa. 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) or licensor 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 Physiology
Vasilopoulou, Catherine G.
Margarity, Marigoula
Klapa, Maria I.
Metabolomic Analysis in Brain Research: Opportunities and Challenges
title Metabolomic Analysis in Brain Research: Opportunities and Challenges
title_full Metabolomic Analysis in Brain Research: Opportunities and Challenges
title_fullStr Metabolomic Analysis in Brain Research: Opportunities and Challenges
title_full_unstemmed Metabolomic Analysis in Brain Research: Opportunities and Challenges
title_short Metabolomic Analysis in Brain Research: Opportunities and Challenges
title_sort metabolomic analysis in brain research: opportunities and challenges
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4878281/
https://www.ncbi.nlm.nih.gov/pubmed/27252656
http://dx.doi.org/10.3389/fphys.2016.00183
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