Xi Luo, Diana C El Assal, Yanjun Liu, Samira Ranjbar, Ronan M T Fleming
{"title":"帕金森病患者多巴胺能神经元突触和非突触组分生物能量差异的约束建模。","authors":"Xi Luo, Diana C El Assal, Yanjun Liu, Samira Ranjbar, Ronan M T Fleming","doi":"10.3389/fncom.2025.1594330","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Emerging evidence suggests that different metabolic characteristics, particularly bioenergetic differences, between the synaptic terminal and soma may contribute to the selective vulnerability of dopaminergic neurons in patients with Parkinson's disease (PD).</p><p><strong>Method: </strong>To investigate the metabolic differences, we generated four thermodynamically flux-consistent metabolic models representing the synaptic and non-synaptic (somatic) components under both control and PD conditions. Differences in bioenergetic features and metabolite exchanges were analyzed between these models to explore potential mechanisms underlying the selective vulnerability of dopaminergic neurons. Bioenergetic rescue analyses were performed to identify potential therapeutic targets for mitigating observed energy failure and metabolic dysfunction in PD models.</p><p><strong>Results: </strong>All models predicted that oxidative phosphorylation plays a significant role under lower energy demand, while glycolysis predominates when energy demand exceeds mitochondrial constraints. The synaptic PD model predicted a lower mitochondrial energy contribution and higher sensitivity to Complex I inhibition compared to the non-synaptic PD model. Both PD models predicted reduced uptake of lysine and lactate, indicating coordinated metabolic processes between these components. In contrast, decreased methionine and urea uptake was exclusively predicted in the synaptic PD model, while decreased histidine and glyceric acid uptake was exclusive to the non-synaptic PD model. Furthermore, increased flux of the mitochondrial ornithine transaminase reaction (ORNTArm), which converts oxoglutaric acid and ornithine into glutamate-5-semialdehyde and glutamate, was predicted to rescue bioenergetic failure and improve metabolite exchanges for both the synaptic and non-synaptic PD models.</p><p><strong>Discussion: </strong>The predicted differences in ATP contribution between models highlight the bioenergetic differences between these neuronal components, thereby contributing to the selective vulnerability observed in PD. The observed differences in metabolite exchanges reflect distinct metabolic patterns between these neuronal components. Additionally, mitochondrial ornithine transaminase was predicted to be the potential bioenergetic rescue target for both the synaptic and non-synaptic PD models. Further research is needed to validate these dysfunction mechanisms across different components of dopaminergic neurons and to explore targeted therapeutic strategies for PD patients.</p>","PeriodicalId":12363,"journal":{"name":"Frontiers in Computational Neuroscience","volume":"19 ","pages":"1594330"},"PeriodicalIF":2.1000,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12176876/pdf/","citationCount":"0","resultStr":"{\"title\":\"Constraint-based modeling of bioenergetic differences between synaptic and non-synaptic components of dopaminergic neurons in Parkinson's disease.\",\"authors\":\"Xi Luo, Diana C El Assal, Yanjun Liu, Samira Ranjbar, Ronan M T Fleming\",\"doi\":\"10.3389/fncom.2025.1594330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Emerging evidence suggests that different metabolic characteristics, particularly bioenergetic differences, between the synaptic terminal and soma may contribute to the selective vulnerability of dopaminergic neurons in patients with Parkinson's disease (PD).</p><p><strong>Method: </strong>To investigate the metabolic differences, we generated four thermodynamically flux-consistent metabolic models representing the synaptic and non-synaptic (somatic) components under both control and PD conditions. Differences in bioenergetic features and metabolite exchanges were analyzed between these models to explore potential mechanisms underlying the selective vulnerability of dopaminergic neurons. Bioenergetic rescue analyses were performed to identify potential therapeutic targets for mitigating observed energy failure and metabolic dysfunction in PD models.</p><p><strong>Results: </strong>All models predicted that oxidative phosphorylation plays a significant role under lower energy demand, while glycolysis predominates when energy demand exceeds mitochondrial constraints. The synaptic PD model predicted a lower mitochondrial energy contribution and higher sensitivity to Complex I inhibition compared to the non-synaptic PD model. Both PD models predicted reduced uptake of lysine and lactate, indicating coordinated metabolic processes between these components. In contrast, decreased methionine and urea uptake was exclusively predicted in the synaptic PD model, while decreased histidine and glyceric acid uptake was exclusive to the non-synaptic PD model. Furthermore, increased flux of the mitochondrial ornithine transaminase reaction (ORNTArm), which converts oxoglutaric acid and ornithine into glutamate-5-semialdehyde and glutamate, was predicted to rescue bioenergetic failure and improve metabolite exchanges for both the synaptic and non-synaptic PD models.</p><p><strong>Discussion: </strong>The predicted differences in ATP contribution between models highlight the bioenergetic differences between these neuronal components, thereby contributing to the selective vulnerability observed in PD. The observed differences in metabolite exchanges reflect distinct metabolic patterns between these neuronal components. Additionally, mitochondrial ornithine transaminase was predicted to be the potential bioenergetic rescue target for both the synaptic and non-synaptic PD models. Further research is needed to validate these dysfunction mechanisms across different components of dopaminergic neurons and to explore targeted therapeutic strategies for PD patients.</p>\",\"PeriodicalId\":12363,\"journal\":{\"name\":\"Frontiers in Computational Neuroscience\",\"volume\":\"19 \",\"pages\":\"1594330\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12176876/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Computational Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3389/fncom.2025.1594330\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Computational Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fncom.2025.1594330","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
Constraint-based modeling of bioenergetic differences between synaptic and non-synaptic components of dopaminergic neurons in Parkinson's disease.
Introduction: Emerging evidence suggests that different metabolic characteristics, particularly bioenergetic differences, between the synaptic terminal and soma may contribute to the selective vulnerability of dopaminergic neurons in patients with Parkinson's disease (PD).
Method: To investigate the metabolic differences, we generated four thermodynamically flux-consistent metabolic models representing the synaptic and non-synaptic (somatic) components under both control and PD conditions. Differences in bioenergetic features and metabolite exchanges were analyzed between these models to explore potential mechanisms underlying the selective vulnerability of dopaminergic neurons. Bioenergetic rescue analyses were performed to identify potential therapeutic targets for mitigating observed energy failure and metabolic dysfunction in PD models.
Results: All models predicted that oxidative phosphorylation plays a significant role under lower energy demand, while glycolysis predominates when energy demand exceeds mitochondrial constraints. The synaptic PD model predicted a lower mitochondrial energy contribution and higher sensitivity to Complex I inhibition compared to the non-synaptic PD model. Both PD models predicted reduced uptake of lysine and lactate, indicating coordinated metabolic processes between these components. In contrast, decreased methionine and urea uptake was exclusively predicted in the synaptic PD model, while decreased histidine and glyceric acid uptake was exclusive to the non-synaptic PD model. Furthermore, increased flux of the mitochondrial ornithine transaminase reaction (ORNTArm), which converts oxoglutaric acid and ornithine into glutamate-5-semialdehyde and glutamate, was predicted to rescue bioenergetic failure and improve metabolite exchanges for both the synaptic and non-synaptic PD models.
Discussion: The predicted differences in ATP contribution between models highlight the bioenergetic differences between these neuronal components, thereby contributing to the selective vulnerability observed in PD. The observed differences in metabolite exchanges reflect distinct metabolic patterns between these neuronal components. Additionally, mitochondrial ornithine transaminase was predicted to be the potential bioenergetic rescue target for both the synaptic and non-synaptic PD models. Further research is needed to validate these dysfunction mechanisms across different components of dopaminergic neurons and to explore targeted therapeutic strategies for PD patients.
期刊介绍:
Frontiers in Computational Neuroscience is a first-tier electronic journal devoted to promoting theoretical modeling of brain function and fostering interdisciplinary interactions between theoretical and experimental neuroscience. Progress in understanding the amazing capabilities of the brain is still limited, and we believe that it will only come with deep theoretical thinking and mutually stimulating cooperation between different disciplines and approaches. We therefore invite original contributions on a wide range of topics that present the fruits of such cooperation, or provide stimuli for future alliances. We aim to provide an interactive forum for cutting-edge theoretical studies of the nervous system, and for promulgating the best theoretical research to the broader neuroscience community. Models of all styles and at all levels are welcome, from biophysically motivated realistic simulations of neurons and synapses to high-level abstract models of inference and decision making. While the journal is primarily focused on theoretically based and driven research, we welcome experimental studies that validate and test theoretical conclusions.
Also: comp neuro