Dimitrios G Patsatzis, Efstathios-Al Tingas, Subram Mani Sarathy, Dimitris A Goussis, Renaud Blaise Jolivet
{"title":"Elucidating reaction dynamics in a model of human brain energy metabolism.","authors":"Dimitrios G Patsatzis, Efstathios-Al Tingas, Subram Mani Sarathy, Dimitris A Goussis, Renaud Blaise Jolivet","doi":"10.1371/journal.pcbi.1013504","DOIUrl":null,"url":null,"abstract":"<p><p>Energy metabolism is essential to brain function and Bioinformatics, but its study is experimentally challenging. Similarly, biologically accurate computational models are too complex for simple investigations. Here, we analyse an experimentally-calibrated multiscale model of human brain energy metabolism using Computational Singular Perturbation. This approach leads to the novel identification of functional periods during and after synaptic activation, and highlights the central reactions and metabolites controlling the system's behaviour within those periods. We identify a key role for both oxidative and glycolytic astrocytic metabolism in driving the brain's metabolic circuitry. We also identify phosphocreatine as the main endogenous energy supply to brain cells, and propose revising our view of brain energy metabolism accordingly. Our approach highlights the importance of glial cells in brain metabolism, and introduces a systematic and unbiased methodology to study the dynamics of complex biochemical networks that can be scaled, in principle, to metabolic networks of any size and complexity.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 9","pages":"e1013504"},"PeriodicalIF":3.6000,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12500149/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PLoS Computational Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1371/journal.pcbi.1013504","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/9/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Energy metabolism is essential to brain function and Bioinformatics, but its study is experimentally challenging. Similarly, biologically accurate computational models are too complex for simple investigations. Here, we analyse an experimentally-calibrated multiscale model of human brain energy metabolism using Computational Singular Perturbation. This approach leads to the novel identification of functional periods during and after synaptic activation, and highlights the central reactions and metabolites controlling the system's behaviour within those periods. We identify a key role for both oxidative and glycolytic astrocytic metabolism in driving the brain's metabolic circuitry. We also identify phosphocreatine as the main endogenous energy supply to brain cells, and propose revising our view of brain energy metabolism accordingly. Our approach highlights the importance of glial cells in brain metabolism, and introduces a systematic and unbiased methodology to study the dynamics of complex biochemical networks that can be scaled, in principle, to metabolic networks of any size and complexity.
期刊介绍:
PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery.
Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines.
Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights.
Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology.
Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.