Cell metabolismPub Date : 2025-12-02DOI: 10.1016/j.cmet.2025.11.001
Iyassu K. Sebhat, Monika J.M. Murphy, Shuqin Zheng, Robert J. Lovelett, Maja Engelstoft, Daniel Kosinski, Xiaodong Yang, Victoria Dunn, John Whang, Maximilian G. Lombardo, Adrian Heilbut, Giuseppe Terracina, Nicole Nicholas, Molly Leitner, Matthew J. Consolati, Bryan Chan, Gregory Poterewicz, Annemarie Vance, Jiajun Liu, Ann E. Weber, Shirly Pinto
{"title":"Gut enteroendocrine cell activation using a combination of GPR119 and GPR40 agonists results in synergistic hormone secretion in mice and humans","authors":"Iyassu K. Sebhat, Monika J.M. Murphy, Shuqin Zheng, Robert J. Lovelett, Maja Engelstoft, Daniel Kosinski, Xiaodong Yang, Victoria Dunn, John Whang, Maximilian G. Lombardo, Adrian Heilbut, Giuseppe Terracina, Nicole Nicholas, Molly Leitner, Matthew J. Consolati, Bryan Chan, Gregory Poterewicz, Annemarie Vance, Jiajun Liu, Ann E. Weber, Shirly Pinto","doi":"10.1016/j.cmet.2025.11.001","DOIUrl":"https://doi.org/10.1016/j.cmet.2025.11.001","url":null,"abstract":"A leading hypothesis for the effectiveness of bariatric surgery for weight loss is supraphysiologic activation of gut enteroendocrine cells (EECs), which results in elevated postprandial levels of satiety hormones, including glucagon-like peptide-1 (GLP-1). Here, we describe direct targeting of EECs to mimic effects of bariatric surgery. Advanced technologies were used to obtain a comprehensive understanding of EEC diversity, resulting in the identification of cells that express both satiety hormones and target receptors, including GPR40 (FFAR1) and GPR119. We developed gut-targeted agonists of these receptors, K-757 and K-833, and demonstrated synergistic hormone secretion in murine and human enteroids. The combination was efficacious in improving glucose tolerance and promoting weight loss in mice. The levels of circulating gut hormones observed in phase 1 trials exceeded levels observed in bariatric surgery, warranting further clinical investigation of these compounds for weight loss and glucose control.","PeriodicalId":9840,"journal":{"name":"Cell metabolism","volume":"18 1","pages":""},"PeriodicalIF":29.0,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145651401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cell metabolismPub Date : 2025-12-02DOI: 10.1016/j.cmet.2025.11.004
Salvatore Fabbiano, Mari-Carmen Fernández-Agüera, Beste Mutlu, Patrick Schaefer, Yongmei Sun
{"title":"Toward the next 20 years of Cell Metabolism","authors":"Salvatore Fabbiano, Mari-Carmen Fernández-Agüera, Beste Mutlu, Patrick Schaefer, Yongmei Sun","doi":"10.1016/j.cmet.2025.11.004","DOIUrl":"https://doi.org/10.1016/j.cmet.2025.11.004","url":null,"abstract":"","PeriodicalId":9840,"journal":{"name":"Cell metabolism","volume":"159 1","pages":""},"PeriodicalIF":29.0,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cell metabolismPub Date : 2025-12-01DOI: 10.1016/j.cmet.2025.10.022
Baharan Meghdadi, Wajd N. Al-Holou, Andrew J. Scott, Anjali Mittal, Ningning Liang, Palavalasa Sravya, Abhinav Achreja, Alexandra O’Brien, Kathy Do, Zhe Wu, Jiane Feng, Nathan R. Qi, Vijay Tarnal, Sriram Venneti, C. Ryan Miller, Jann N. Sarkaria, Weihua Zhou, Theodore S. Lawrence, Costas A. Lyssiotis, Daniel R. Wahl, Deepak Nagrath
{"title":"Digital twins for in vivo metabolic flux estimations in patients with brain cancer","authors":"Baharan Meghdadi, Wajd N. Al-Holou, Andrew J. Scott, Anjali Mittal, Ningning Liang, Palavalasa Sravya, Abhinav Achreja, Alexandra O’Brien, Kathy Do, Zhe Wu, Jiane Feng, Nathan R. Qi, Vijay Tarnal, Sriram Venneti, C. Ryan Miller, Jann N. Sarkaria, Weihua Zhou, Theodore S. Lawrence, Costas A. Lyssiotis, Daniel R. Wahl, Deepak Nagrath","doi":"10.1016/j.cmet.2025.10.022","DOIUrl":"https://doi.org/10.1016/j.cmet.2025.10.022","url":null,"abstract":"Recent advancements in metabolic flux estimations <em>in vivo</em> are limited to preclinical models, primarily due to challenges in tissue sampling, tumor microenvironment (TME) heterogeneity, and non-steady-state conditions. To address these limitations and enable flux estimation in human patients, we developed two machine learning-based frameworks. First, the digital twin framework (DTF) integrates first-principles stoichiometric and isotopic simulations with convolutional neural networks to estimate fluxes in patient bulk samples. Second, the single-cell metabolic flux analysis (<sup>13</sup>C-scMFA) framework combines patient single-cell RNA sequencing (scRNA-seq) data with <sup>13</sup>C-isotope tracing, allowing single-cell-level flux quantification. These studies allow quantification of metabolic activity in neoplastic glioma cells, revealing frequently elevated purine synthesis and serine uptake, compared with non-malignant cells. Our models also identify metabolic heterogeneity among patients and mice with brain cancer, in turn predicting treatment responses to metabolic inhibitors. Our frameworks advance <em>in vivo</em> metabolic flux analysis, may lead to novel metabolic therapies, and identify biomarkers for metabolism-directed therapies in patients.","PeriodicalId":9840,"journal":{"name":"Cell metabolism","volume":"123 1","pages":""},"PeriodicalIF":29.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145651402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cell metabolismPub Date : 2025-12-01DOI: 10.1016/j.cmet.2025.10.021
Claire H. Feetham, Sam Groom, Linu M. John, Berit Ostergaard Christoffersen, Valeria Collabolletta, David Lyons, Antony Adamson, Sofia Lundh, Marina Kjærgaard Gerstenberg, Mads Tang-Christensen, Kilian W. Conde-Frieboes, Anna Secher, Ann Maria Kruse Hansen, Simon M. Luckman
{"title":"Analog of prolactin-releasing peptide reduces body weight primarily through sustained fatty acid oxidation rather than hypophagia","authors":"Claire H. Feetham, Sam Groom, Linu M. John, Berit Ostergaard Christoffersen, Valeria Collabolletta, David Lyons, Antony Adamson, Sofia Lundh, Marina Kjærgaard Gerstenberg, Mads Tang-Christensen, Kilian W. Conde-Frieboes, Anna Secher, Ann Maria Kruse Hansen, Simon M. Luckman","doi":"10.1016/j.cmet.2025.10.021","DOIUrl":"https://doi.org/10.1016/j.cmet.2025.10.021","url":null,"abstract":"Prolactin-releasing peptide and its cognate receptor, G protein-coupled receptor (GPR)10, are important in the physiological regulation of body weight in both rodents and humans. Here, we describe a modified peptide, NN501, with agonist properties at both GPR10 and neuropeptide FF receptor 2 (NPFFR2), which reduces body weight when administered systemically without causing obvious aversive responses. Weight reduction is similar to that of glucagon-like peptide 1 (GLP-1) receptor agonists, but with only a modest effect on food intake, suggesting a different weight-lowering mechanism. Moreover, when treatment is discontinued, mice receiving NN501 display a more gradual weight regain and no compensatory hyperphagic response (as is observed with caloric restriction and GLP-1 receptor agonism). Instead, NN501 increases energy expenditure on treatment and has a sustained effect on fatty-acid oxidation. These results indicate that GPR10/NPFFR2 agonism produces weight loss by alternative mechanisms to GLP-1 receptor agonism, suggesting it could be a viable alternative or complementary therapy for obesity.","PeriodicalId":9840,"journal":{"name":"Cell metabolism","volume":"57 1","pages":""},"PeriodicalIF":29.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cell metabolismPub Date : 2025-11-25DOI: 10.1016/j.cmet.2025.10.016
Steven E. Pilley, Dominik Awad, Djakim Latumalea, Connie New, Edgar Esparza, Shuo Wang, Xuanyi Shi, Li Zhang, Maximilian Unfried, Jasinda H. Lee, Ernst Schmid, Ipsita Mohanty, Jenna L.E. Blum, Shivaanishaa Raventhiran, Esther Wong, Preeti R. Iyengar, Racheal Mulondo, Sriraksha Bharadwaj Kashyap, Darius Moaddeli, Peter Sajjakulnukit, Peter J. Mullen
{"title":"A metabolic atlas of mouse aging","authors":"Steven E. Pilley, Dominik Awad, Djakim Latumalea, Connie New, Edgar Esparza, Shuo Wang, Xuanyi Shi, Li Zhang, Maximilian Unfried, Jasinda H. Lee, Ernst Schmid, Ipsita Mohanty, Jenna L.E. Blum, Shivaanishaa Raventhiran, Esther Wong, Preeti R. Iyengar, Racheal Mulondo, Sriraksha Bharadwaj Kashyap, Darius Moaddeli, Peter Sajjakulnukit, Peter J. Mullen","doi":"10.1016/j.cmet.2025.10.016","DOIUrl":"https://doi.org/10.1016/j.cmet.2025.10.016","url":null,"abstract":"Humans are living longer and experiencing more age-related diseases, many of which involve metabolic dysregulation, but how metabolism changes in multiple organs during aging is not known. Answering this could reveal new mechanisms of aging and therapeutics. Here, we profile metabolic changes in 12 organs in male and female mice at 5 different ages. We also develop organ-specific metabolic aging clocks that identify metabolic drivers of aging, including alpha-ketoglutarate, previously shown to extend lifespan in mice. We also use the clocks to uncover that carglumic acid is a potential driver of aging and show that it is synthesized by human cells. Finally, we validate that hydroxyproline decreases with age in the human pancreas, emphasizing that our approach reveals insights across species. This study reveals fundamental insights into the aging process and identifies new therapeutic targets to maintain organ health.","PeriodicalId":9840,"journal":{"name":"Cell metabolism","volume":"57 1","pages":""},"PeriodicalIF":29.0,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145593511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Interindividual variability in gut microbiome mediates the efficacy of resistant starch on MASLD","authors":"Xiaoxue Long, Hui Wang, Yuwei Lu, Xiaojing Gao, Yuanyuan Xiao, Mingliang Zhang, Jingyi Guo, Jingyi Yang, Ruiqi Zhang, Qian Li, Guiyun Zhou, Ruibao Yang, Feng Chen, Qingqing Wu, Liming Sun, Chengshuang Chu, Xuexue Zhu, Zhengjun Wu, Quanlu Ren, Chunping You, Huating Li","doi":"10.1016/j.cmet.2025.10.017","DOIUrl":"https://doi.org/10.1016/j.cmet.2025.10.017","url":null,"abstract":"Our randomized, placebo-controlled trial showed resistant starch (RS), a type of prebiotic, has therapeutic effects in metabolic dysfunction-associated steatotic liver disease (MASLD). Here, we observed its heterogeneous efficacy, where 30% of participants exhibited limited benefits, which was replicated in a multi-center trial (ChiCTR2300074588). Multi-omics analysis and fecal microbiota transplantation identified baseline microbiota as a dominant contributor of response. Further population stratification and network analysis combined with <em>in vitro</em> and <em>in vivo</em> experiments revealed <em>Prevotella</em> as the key cause of low response by inhibiting RS-degrading bacteria, thereby impairing RS utilization. Conversely, <em>Bifidobacterium pseudocatenulatum RRP01</em>, a strain isolated from our cohort, restored RS degradation and improved <em>Prevotella</em>-attenuated RS response. Furthermore, we developed a predictive model integrating baseline microbial and clinical features (area under the curve [AUC] = 0.74–0.87), enabling stratification for personalized interventions. Our study indicates that gut microbiota determines the heterogeneity in RS efficacy and offers possibilities for novel microbiota-oriented precision therapeutics for MASLD.","PeriodicalId":9840,"journal":{"name":"Cell metabolism","volume":"11 1","pages":""},"PeriodicalIF":29.0,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145554810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cell metabolismPub Date : 2025-11-20DOI: 10.1016/j.cmet.2025.10.009
Masayoshi Suda, Selim Chaib, Larissa G.P. Langhi Prata, Yi Zhu, Utkarsh Tripathi, Karl H. Paul, Allyson K. Palmer, Tamar Pirtskhalava, Vagisha Kulshreshtha, Christina L. Inman, Kurt O. Johnson, Nino Giorgadze, Runqing Huang, Carolyn M. Roos, Luisa F. Leon-Sanchez, Jordan D. Miller, Thomas White, Linshan Laux, Laura J. Niedernhofer, Paul D. Robbins, James L. Kirkland
{"title":"Endothelial senescent-cell-specific clearance alleviates metabolic dysfunction in obese mice","authors":"Masayoshi Suda, Selim Chaib, Larissa G.P. Langhi Prata, Yi Zhu, Utkarsh Tripathi, Karl H. Paul, Allyson K. Palmer, Tamar Pirtskhalava, Vagisha Kulshreshtha, Christina L. Inman, Kurt O. Johnson, Nino Giorgadze, Runqing Huang, Carolyn M. Roos, Luisa F. Leon-Sanchez, Jordan D. Miller, Thomas White, Linshan Laux, Laura J. Niedernhofer, Paul D. Robbins, James L. Kirkland","doi":"10.1016/j.cmet.2025.10.009","DOIUrl":"https://doi.org/10.1016/j.cmet.2025.10.009","url":null,"abstract":"Accumulation of senescent cells is a key contributor to multiple diseases across the lifespan, including metabolic dysfunction. We previously demonstrated that elimination of senescent cells using senolytic drugs alleviates obesity-induced metabolic dysfunction. However, the contribution of senescent endothelial cells to metabolic disorders remains elusive. Hence, we crossed mice that allow selective elimination of senescent cells (<em>p16</em><sup><em>Ink4a</em></sup><em>-LOX-ATTAC</em> mice) with <em>Tie2-Cre</em> mice (<em>Tie2-Cre</em>;<em>p16</em><sup><em>Ink4a</em></sup><em>-LOX-ATTAC</em>) to enable identification and inducible, selective elimination of p16<sup>Ink4a+</sup> senescent endothelial cells. Targeted removal of senescent endothelial cells from obese <em>Tie2-Cre</em>;<em>p16</em><sup><em>Ink4a</em></sup><em>-LOX-ATTAC</em> mice attenuated the pro-inflammatory senescence-associated secretory phenotype and alleviated metabolic dysfunction. Conversely, transplanting senescent endothelial cells into lean mice caused adipose tissue inflammation and metabolic dysfunction. Consistent with these findings, the senolytic, fisetin, which targets senescent endothelial cells among other senescent cell types, reduced adipose tissue senescent endothelial cell abundance and improved glucose metabolism in obese mice or mice transplanted with senescent mouse endothelial cells. Our results indicate that specifically eliminating p16<sup>Ink4a+</sup> senescent endothelial cells is a potential therapeutic strategy for metabolic disease.","PeriodicalId":9840,"journal":{"name":"Cell metabolism","volume":"18 1","pages":""},"PeriodicalIF":29.0,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145554824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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