Nature metabolism最新文献

{"title":"TrkB signalling regulates dopamine circuits and motor function through metabolic pathways","authors":"","doi":"10.1038/s42255-024-01154-0","DOIUrl":"https://doi.org/10.1038/s42255-024-01154-0","url":null,"abstract":"A common feature of neurodegenerative diseases is that select neuronal types are particularly sensitive to disease pathology at early stages. Altered TrkB signalling in the neuronal type most affected by Huntington’s disease increased expression of the enzyme GSTO2, leading to dopaminergic dysfunction, impaired energy metabolism, progressive degeneration and hyperkinetic symptoms.","PeriodicalId":19038,"journal":{"name":"Nature metabolism","volume":"12 1","pages":""},"PeriodicalIF":20.8,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142519515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impaired striatal glutathione–ascorbate metabolism induces transient dopamine increase and motor dysfunction","authors":"Mohd Yaseen Malik, Fei Guo, Aman Asif-Malik, Vasileios Eftychidis, Nikolaos Barkas, Elena Eliseeva, Kerstin N. Timm, Aleksandra Wolska, David Bergin, Barbara Zonta, Veronika Ratz-Wirsching, Stephan von Hörsten, Mark E. Walton, Peter J. Magill, Claus Nerlov, Liliana Minichiello","doi":"10.1038/s42255-024-01155-z","DOIUrl":"https://doi.org/10.1038/s42255-024-01155-z","url":null,"abstract":"<p>Identifying initial triggering events in neurodegenerative disorders is critical to developing preventive therapies. In Huntington’s disease (HD), hyperdopaminergia—probably triggered by the dysfunction of the most affected neurons, indirect pathway spiny projection neurons (iSPNs)—is believed to induce hyperkinesia, an early stage HD symptom. However, how this change arises and contributes to HD pathogenesis is unclear. Here, we demonstrate that genetic disruption of iSPNs function by <i>Ntrk2/Trkb</i> deletion in mice results in increased striatal dopamine and midbrain dopaminergic neurons, preceding hyperkinetic dysfunction. Transcriptomic analysis of iSPNs at the pre-symptomatic stage showed de-regulation of metabolic pathways, including upregulation of <i>Gsto2</i>, encoding glutathione S-transferase omega-2 (GSTO2). Selectively reducing <i>Gsto2</i> in iSPNs in vivo effectively prevented dopaminergic dysfunction and halted the onset and progression of hyperkinetic symptoms. This study uncovers a functional link between altered iSPN BDNF-TrkB signalling, glutathione–ascorbate metabolism and hyperdopaminergic state, underscoring the vital role of GSTO2 in maintaining dopamine balance.</p>","PeriodicalId":19038,"journal":{"name":"Nature metabolism","volume":"75 1","pages":""},"PeriodicalIF":20.8,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142519518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitation of metabolic activity from isotope tracing data using automated methodology","authors":"Shiyu Liu, Xiaojing Liu, Jason W. Locasale","doi":"10.1038/s42255-024-01144-2","DOIUrl":"https://doi.org/10.1038/s42255-024-01144-2","url":null,"abstract":"&lt;p&gt;Metabolic flux analysis (MFA) is a computational approach to deciphering labelling patterns based on machine learning principles. Differing from typical machine learning algorithms that train a model from known datasets to make predictions, the commonly used MFA algorithm trains a metabolic network with data from isotope tracing experiments and directly outputs the learned information — that is, all fluxes in the network that best fit data&lt;sup&gt;3,5&lt;/sup&gt; (Fig. 1b). However, as a machine learning algorithm, current MFA methods often lack systematic evaluation and benchmarking, a standard practice in broader machine learning and artificial intelligence applications&lt;sup&gt;6&lt;/sup&gt;. Issues such as algorithmic convergence, flux estimation accuracy and result robustness in MFA studies have been raised but remain largely unaddressed&lt;sup&gt;3&lt;/sup&gt;, limiting the effectiveness and broader adoption of these automated tools in metabolic research.&lt;/p&gt;&lt;p&gt;To advance the capabilities of MFA for complex metabolic networks and extensive isotope tracing datasets, we developed an automated analysis methodology alongside a large-scale metabolic network model. This model comprises over 100 fluxes across key pathways, including glycolysis, the tricarboxylic acid (TCA) cycle, the pentose phosphate pathway (PPP), one-carbon metabolism, and several amino acid (AA) biosynthetic pathways (Fig. 1c, Supplementary Methods). Compared to contemporary MFA tools&lt;sup&gt;7,8,9&lt;/sup&gt;, a notable feature of our methodology is the incorporation of organelle compartmentalization, facilitating accurate quantification of exchange fluxes between mitochondria and cytosol in eukaryotic cells (Fig. 1c). While other tools typically require tens of minutes to obtain a solution&lt;sup&gt;7,9&lt;/sup&gt;, our methodology can generate an optimized solution, with fluxes that accurately explain the labelling pattern from a &lt;sup&gt;13&lt;/sup&gt;C tracing experiment on cultured cell lines, within 2 s on a desktop computer&lt;sup&gt;10&lt;/sup&gt; (Supplementary Fig. 1a–d). Nonetheless, a challenge arose from the observation that these optimized solutions could diverge significantly, showing considerable variability in certain net fluxes even with similar loss values (Fig. 1d, Supplementary Fig. 1e,f).To address this problem, we developed an optimization-averaging algorithm that refines the computation process by selecting a subset of solutions with minimal loss (selected solutions) from the pool of optimized solutions and averaging them to produce a new, more stable solution set (averaged solutions) (Fig. 1e, Supplementary Methods). These solutions, along with those generated using the typical strategy used in contemporary software (Supplementary Methods, Supplementary Fig. 1c), were benchmarked using simulated &lt;sup&gt;13&lt;/sup&gt;C tracing datasets generated from a known flux vector (Supplementary Fig. 2a). The results demonstrated that, relative to the benchmark, the optimization-averaging algorithm effectively reduced flux variability and impr","PeriodicalId":19038,"journal":{"name":"Nature metabolism","volume":"5 1","pages":""},"PeriodicalIF":20.8,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142489588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Publisher Correction: Exploring pancreatic beta-cell subgroups and their connectivity.","authors":"Guy A Rutter,Anne Gresch,Luis Delgadillo Silva,Richard K P Benninger","doi":"10.1038/s42255-024-01141-5","DOIUrl":"https://doi.org/10.1038/s42255-024-01141-5","url":null,"abstract":"","PeriodicalId":19038,"journal":{"name":"Nature metabolism","volume":"14 1","pages":""},"PeriodicalIF":20.8,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142489502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Farnesyl pyrophosphate potentiates dendritic cell migration in autoimmunity through mitochondrial remodelling","authors":"Xiaomin Zhang, Yali Chen, Geng Sun, Yankang Fei, Ha Zhu, Yanfang Liu, Junyan Dan, Chunzhen Li, Xuetao Cao, Juan Liu","doi":"10.1038/s42255-024-01149-x","DOIUrl":"https://doi.org/10.1038/s42255-024-01149-x","url":null,"abstract":"<p>Cellular metabolism modulates dendritic cell (DC) maturation and activation. Migratory dendritic cells (mig-DCs) travelling from the tissues to draining lymph nodes (dLNs) are critical for instructing adaptive immune responses. However, how lipid metabolites influence mig-DCs in autoimmunity remains elusive. Here, we demonstrate that farnesyl pyrophosphate (FPP), an intermediate of the mevalonate pathway, accumulates in mig-DCs derived from mice with systemic lupus erythematosus (SLE). FPP promotes mig-DC survival and germinal centre responses in the dLNs by coordinating protein geranylgeranylation and mitochondrial remodelling. Mechanistically, FPP-dependent RhoA geranylgeranylation promotes mitochondrial fusion and oxidative respiration through mitochondrial RhoA–MFN interaction, which subsequently facilitates the resolution of endoplasmic reticulum stress in mig-DCs. Simvastatin, a chemical inhibitor of the mevalonate pathway, restores mitochondrial function in mig-DCs and ameliorates systemic pathogenesis in SLE mice. Our study reveals a critical role for FPP in dictating mig-DC survival by reprogramming mitochondrial structure and metabolism, providing new insights into the pathogenesis of DC-dependent autoimmune diseases.</p>","PeriodicalId":19038,"journal":{"name":"Nature metabolism","volume":"33 1","pages":""},"PeriodicalIF":20.8,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142448317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Farnesyl pyrophosphate modulates dendritic cell migration in lupus autoimmunity","authors":"","doi":"10.1038/s42255-024-01148-y","DOIUrl":"https://doi.org/10.1038/s42255-024-01148-y","url":null,"abstract":"Farnesyl pyrophosphate (FPP), an intermediate of cholesterol biosynthesis in the mevalonate pathway, prolongs the survival of migratory dendritic cells (mig-DCs) by remodelling mitochondrial structure and metabolism. Treating a mouse model of systemic lupus erythematosus with simvastatin (an inhibitor of this pathway) led to recovery from dysregulation in mig-DCs and ameliorated systemic autoimmune pathogenesis.","PeriodicalId":19038,"journal":{"name":"Nature metabolism","volume":"8 1 1","pages":""},"PeriodicalIF":20.8,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142448266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic architecture of oral glucose-stimulated insulin release provides biological insights into type 2 diabetes aetiology","authors":"A. L. Madsen,&nbsp;S. Bonàs-Guarch,&nbsp;S. Gheibi,&nbsp;R. Prasad,&nbsp;J. Vangipurapu,&nbsp;V. Ahuja,&nbsp;L. R. Cataldo,&nbsp;O. Dwivedi,&nbsp;G. Hatem,&nbsp;G. Atla,&nbsp;M. Guindo-Martínez,&nbsp;A. M. Jørgensen,&nbsp;A. E. Jonsson,&nbsp;I. Miguel-Escalada,&nbsp;S. Hassan,&nbsp;A. Linneberg,&nbsp;Tarunveer S. Ahluwalia,&nbsp;T. Drivsholm,&nbsp;O. Pedersen,&nbsp;T. I. A. Sørensen,&nbsp;A. Astrup,&nbsp;D. Witte,&nbsp;P. Damm,&nbsp;T. D. Clausen,&nbsp;E. Mathiesen,&nbsp;T. H. Pers,&nbsp;R. J. F. Loos,&nbsp;L. Hakaste,&nbsp;M. Fex,&nbsp;N. Grarup,&nbsp;T. Tuomi,&nbsp;M. Laakso,&nbsp;H. Mulder,&nbsp;J. Ferrer,&nbsp;T. Hansen","doi":"10.1038/s42255-024-01140-6","DOIUrl":"10.1038/s42255-024-01140-6","url":null,"abstract":"The genetics of β-cell function (BCF) offer valuable insights into the aetiology of type 2 diabetes (T2D)1,2. Previous studies have expanded the catalogue of BCF genetic associations through candidate gene studies3–7, large-scale genome-wide association studies (GWAS) of fasting BCF8,9 or functional islet studies on T2D risk variants10–14. Nonetheless, GWAS focused on BCF traits derived from oral glucose tolerance test (OGTT) data have been limited in sample size15,16 and have often overlooked the potential for related traits to capture distinct genetic features of insulin-producing β-cells17,18. We reasoned that investigating the genetic basis of multiple BCF estimates could provide a broader understanding of β-cell physiology. Here, we aggregate GWAS data of eight OGTT-based BCF traits from ~26,000 individuals of European descent, identifying 55 independent genetic associations at 44 loci. By examining the effects of BCF genetic signals on related phenotypes, we uncover diverse disease mechanisms whereby genetic regulation of BCF may influence T2D risk. Integrating BCF-GWAS data with pancreatic islet transcriptomic and epigenomic datasets reveals 92 candidate effector genes. Gene silencing in β-cell models highlights ACSL1 and FAM46C as key regulators of insulin secretion. Overall, our findings yield insights into the biology of insulin release and the molecular processes linking BCF to T2D risk, shedding light on the heterogeneity of T2D pathophysiology. In a genome-wide association study for traits related to pancreatic beta-cell function in 26,000 individuals, 55 independent associations mapping to 44 genetic loci are identified.","PeriodicalId":19038,"journal":{"name":"Nature metabolism","volume":"6 10","pages":"1897-1912"},"PeriodicalIF":18.9,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42255-024-01140-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetics brings new insight to β-cell function","authors":"Amélie Bonnefond,&nbsp;Philippe Froguel","doi":"10.1038/s42255-024-01131-7","DOIUrl":"10.1038/s42255-024-01131-7","url":null,"abstract":"A meta-analysis of genome-wide association study for eight traits related to pancreatic β-cell function, based on 26,000 individuals, identified 55 independent association signals mapping to 44 loci. This study highlighted new effectors of β-cell function.","PeriodicalId":19038,"journal":{"name":"Nature metabolism","volume":"6 10","pages":"1848-1849"},"PeriodicalIF":18.9,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Itaconate modulates mitochondria for antiviral IFN-β","authors":"Thekla Cordes, Karsten Hiller","doi":"10.1038/s42255-024-01146-0","DOIUrl":"https://doi.org/10.1038/s42255-024-01146-0","url":null,"abstract":"Itaconate is an immunomodulatory metabolite that influences the outcome of infections and inflammatory diseases. New evidence indicates that itaconate-induced inhibition of succinate dehydrogenase regulates type 1 interferon production via the release of mitochondrial RNA, linking TCA cycle modulation to antiviral interferon responses.","PeriodicalId":19038,"journal":{"name":"Nature metabolism","volume":"10 1","pages":""},"PeriodicalIF":20.8,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142440032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cytosolic acetyl-CoA synthesis shields mitochondria from stress in brown adipocytes","authors":"","doi":"10.1038/s42255-024-01152-2","DOIUrl":"https://doi.org/10.1038/s42255-024-01152-2","url":null,"abstract":"Brown adipose tissue (BAT) facilitates thermogenesis through fatty acid oxidation (FAO). Paradoxically, BAT simultaneously increases anabolic fatty acid synthesis (FAS), the reason for which is unclear. We provide evidence that thermogenic mitochondria within brown adipocytes export TCA cycle intermediates that fuel de novo lipid synthesis, in part to protect against metabolic stress.","PeriodicalId":19038,"journal":{"name":"Nature metabolism","volume":"89 1","pages":""},"PeriodicalIF":20.8,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142440355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}