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• W2895956914 abstract "•Quantitative proteomics demonstrates age-related changes in islet protein abundance•Adult islets exhibit increased abundance and activity of glucose metabolic enzymes•Age-related metabolic rewiring enhances the amplifying pathway of insulin secretion Pancreatic β cell physiology changes substantially throughout life, yet the mechanisms that drive these changes are poorly understood. Here, we performed comprehensive in vivo quantitative proteomic profiling of pancreatic islets from juvenile and 1-year-old mice. The analysis revealed striking differences in abundance of enzymes controlling glucose metabolism. We show that these changes in protein abundance are associated with higher activities of glucose metabolic enzymes involved in coupling factor generation as well as increased activity of the coupling factor-dependent amplifying pathway of insulin secretion. Nutrient tracing and targeted metabolomics demonstrated accelerated accumulation of glucose-derived metabolites and coupling factors in islets from 1-year-old mice, indicating that age-related changes in glucose metabolism contribute to improved glucose-stimulated insulin secretion with age. Together, our study provides an in-depth characterization of age-related changes in the islet proteome and establishes metabolic rewiring as an important mechanism for age-associated changes in β cell function. Pancreatic β cell physiology changes substantially throughout life, yet the mechanisms that drive these changes are poorly understood. Here, we performed comprehensive in vivo quantitative proteomic profiling of pancreatic islets from juvenile and 1-year-old mice. The analysis revealed striking differences in abundance of enzymes controlling glucose metabolism. We show that these changes in protein abundance are associated with higher activities of glucose metabolic enzymes involved in coupling factor generation as well as increased activity of the coupling factor-dependent amplifying pathway of insulin secretion. Nutrient tracing and targeted metabolomics demonstrated accelerated accumulation of glucose-derived metabolites and coupling factors in islets from 1-year-old mice, indicating that age-related changes in glucose metabolism contribute to improved glucose-stimulated insulin secretion with age. Together, our study provides an in-depth characterization of age-related changes in the islet proteome and establishes metabolic rewiring as an important mechanism for age-associated changes in β cell function. It has long been recognized that islet β cells undergo changes in glucose-stimulated insulin secretion (GSIS) with age. Recent studies of rodent and human islets have shown an age-dependent increase in GSIS when juvenile islets are compared to islets during middle age or later in life (Arda et al., 2016Arda H.E. Li L. Tsai J. Torre E.A. Rosli Y. Peiris H. Spitale R.C. Dai C. Gu X. Qu K. et al.Age-Dependent Pancreatic Gene Regulation Reveals Mechanisms Governing Human β Cell Function.Cell Metab. 2016; 23: 909-920Abstract Full Text Full Text PDF PubMed Scopus (151) Google Scholar, Avrahami et al., 2015Avrahami D. Li C. Zhang J. Schug J. Avrahami R. Rao S. Stadler M.B. Burger L. Schübeler D. Glaser B. Kaestner K.H. Aging-Dependent Demethylation of Regulatory Elements Correlates with Chromatin State and Improved β Cell Function.Cell Metab. 2015; 22: 619-632Abstract Full Text Full Text PDF PubMed Scopus (133) Google Scholar, Gregg et al., 2016Gregg T. Poudel C. Schmidt B.A. Dhillon R.S. Sdao S.M. Truchan N.A. Baar E.L. Fernandez L.A. Denu J.M. Eliceiri K.W. et al.Pancreatic β-Cells From Mice Offset Age-Associated Mitochondrial Deficiency With Reduced KATP Channel Activity.Diabetes. 2016; 65: 2700-2710Crossref PubMed Scopus (46) Google Scholar). Consistent with the observed islet-intrinsic changes to GSIS, circulating insulin levels in both the fasted state and in response to a glucose challenge are higher in older animals (Avrahami et al., 2015Avrahami D. Li C. Zhang J. Schug J. Avrahami R. Rao S. Stadler M.B. Burger L. Schübeler D. Glaser B. Kaestner K.H. Aging-Dependent Demethylation of Regulatory Elements Correlates with Chromatin State and Improved β Cell Function.Cell Metab. 2015; 22: 619-632Abstract Full Text Full Text PDF PubMed Scopus (133) Google Scholar, Gregg et al., 2016Gregg T. Poudel C. Schmidt B.A. Dhillon R.S. Sdao S.M. Truchan N.A. Baar E.L. Fernandez L.A. Denu J.M. Eliceiri K.W. et al.Pancreatic β-Cells From Mice Offset Age-Associated Mitochondrial Deficiency With Reduced KATP Channel Activity.Diabetes. 2016; 65: 2700-2710Crossref PubMed Scopus (46) Google Scholar). These age-dependent functional changes may reflect both maturation and aging processes, defined as those preceding or following sexual maturity, respectively. Several mechanisms have been proposed to be responsible for the increase in GSIS with age, including increased expression of transcription factors that regulate insulin secretory genes in β cells (Arda et al., 2016Arda H.E. Li L. Tsai J. Torre E.A. Rosli Y. Peiris H. Spitale R.C. Dai C. Gu X. Qu K. et al.Age-Dependent Pancreatic Gene Regulation Reveals Mechanisms Governing Human β Cell Function.Cell Metab. 2016; 23: 909-920Abstract Full Text Full Text PDF PubMed Scopus (151) Google Scholar, Avrahami et al., 2015Avrahami D. Li C. Zhang J. Schug J. Avrahami R. Rao S. Stadler M.B. Burger L. Schübeler D. Glaser B. Kaestner K.H. Aging-Dependent Demethylation of Regulatory Elements Correlates with Chromatin State and Improved β Cell Function.Cell Metab. 2015; 22: 619-632Abstract Full Text Full Text PDF PubMed Scopus (133) Google Scholar) as well as activation of a senescence program by the cell cycle inhibitor p16Ink4a (Helman et al., 2016Helman A. Klochendler A. Azazmeh N. Gabai Y. Horwitz E. Anzi S. Swisa A. Condiotti R. Granit R.Z. Nevo Y. et al.p16(Ink4a)-induced senescence of pancreatic beta cells enhances insulin secretion.Nat. Med. 2016; 22: 412-420Crossref PubMed Scopus (184) Google Scholar). However, our current knowledge of age-associated changes in β cells is largely based on transcriptome studies, and an understanding of how age affects the abundance of proteins is lacking. Studies of the islet proteome could provide mechanistic insights into how age affects islet cell function, but these studies have been technically challenging due to the need for large protein amounts and the limited islet material that can be isolated from rodents. A further challenge of proteomic experiments is comprehensive coverage of the cell proteome, because liquid chromatography-tandem mass spectrometry (LC-MS/MS) systems used in proteomics tend to bias detection toward the most abundant proteins. Recent advances in proteomics combining stable isotope labeling of amino acids in mammals (SILAM) with multidimensional protein detection technology (MudPIT) (McClatchy et al., 2007McClatchy D.B. Dong M.Q. Wu C.C. Venable J.D. Yates 3rd, J.R. 15N metabolic labeling of mammalian tissue with slow protein turnover.J. Proteome Res. 2007; 6: 2005-2010Crossref PubMed Scopus (106) Google Scholar, Washburn et al., 2001Washburn M.P. Wolters D. Yates 3rd, J.R. Large-scale analysis of the yeast proteome by multidimensional protein identification technology.Nat. Biotechnol. 2001; 19: 242-247Crossref PubMed Scopus (4077) Google Scholar) have helped overcome these obstacles. This approach has recently provided mechanistic insight into the long-lived proteins of the aging brain (Savas et al., 2012Savas J.N. Toyama B.H. Xu T. Yates 3rd, J.R. Hetzer M.W. Extremely long-lived nuclear pore proteins in the rat brain.Science. 2012; 335: 942Crossref PubMed Scopus (215) Google Scholar). To date, age-related changes in the islet proteome have not been studied. Thus, the impact of transcriptional changes on protein abundance has yet to be broadly determined, and the contribution of posttranscriptional regulation to age-associated functional changes of pancreatic islets remains to be characterized. Insulin secretion is intimately linked to the rate of β cell glucose metabolism. Therefore, determining how β cell glucose metabolism changes throughout life could provide important insight into the mechanisms that mediate the age-associated change in GSIS. The workhorse model for metabolomic studies of β cells has been the INS1 832/13 insulinoma cell line (Alves et al., 2015Alves T.C. Pongratz R.L. Zhao X. Yarborough O. Sereda S. Shirihai O. Cline G.W. Mason G. Kibbey R.G. Integrated, Step-Wise, Mass-Isotopomeric Flux Analysis of the TCA Cycle.Cell Metab. 2015; 22: 936-947Abstract Full Text Full Text PDF PubMed Scopus (70) Google Scholar, Lorenz et al., 2013Lorenz M.A. El Azzouny M.A. Kennedy R.T. Burant C.F. Metabolome response to glucose in the β-cell line INS-1 832/13.J. Biol. Chem. 2013; 288: 10923-10935Crossref PubMed Scopus (65) Google Scholar, Mugabo et al., 2017Mugabo Y. Zhao S. Lamontagne J. Al-Mass A. Peyot M.L. Corkey B.E. Joly E. Madiraju S.R.M. Prentki M. Metabolic fate of glucose and candidate signaling and excess-fuel detoxification pathways in pancreatic β-cells.J. Biol. Chem. 2017; 292: 7407-7422Crossref PubMed Scopus (36) Google Scholar). Glucose tracing experiments and measurements of metabolite abundance during glucose stimulation have helped identify β cell characteristic patterns of glucose utilization as well as candidate metabolites involved in the regulation of GSIS (Alves et al., 2015Alves T.C. Pongratz R.L. Zhao X. Yarborough O. Sereda S. Shirihai O. Cline G.W. Mason G. Kibbey R.G. Integrated, Step-Wise, Mass-Isotopomeric Flux Analysis of the TCA Cycle.Cell Metab. 2015; 22: 936-947Abstract Full Text Full Text PDF PubMed Scopus (70) Google Scholar, Farfari et al., 2000Farfari S. Schulz V. Corkey B. Prentki M. Glucose-regulated anaplerosis and cataplerosis in pancreatic beta-cells: possible implication of a pyruvate/citrate shuttle in insulin secretion.Diabetes. 2000; 49: 718-726Crossref PubMed Scopus (221) Google Scholar, Lorenz et al., 2013Lorenz M.A. El Azzouny M.A. Kennedy R.T. Burant C.F. Metabolome response to glucose in the β-cell line INS-1 832/13.J. Biol. Chem. 2013; 288: 10923-10935Crossref PubMed Scopus (65) Google Scholar, Lu et al., 2002Lu D. Mulder H. Zhao P. Burgess S.C. Jensen M.V. Kamzolova S. Newgard C.B. Sherry A.D. 13C NMR isotopomer analysis reveals a connection between pyruvate cycling and glucose-stimulated insulin secretion (GSIS).Proc. Natl. Acad. Sci. USA. 2002; 99: 2708-2713Crossref PubMed Scopus (220) Google Scholar, Mugabo et al., 2017Mugabo Y. Zhao S. Lamontagne J. Al-Mass A. Peyot M.L. Corkey B.E. Joly E. Madiraju S.R.M. Prentki M. Metabolic fate of glucose and candidate signaling and excess-fuel detoxification pathways in pancreatic β-cells.J. Biol. Chem. 2017; 292: 7407-7422Crossref PubMed Scopus (36) Google Scholar). Nutrient tracing has also been employed in primary islets to monitor specific metabolic reactions (Adam et al., 2017Adam J. Ramracheya R. Chibalina M.V. Ternette N. Hamilton A. Tarasov A.I. Zhang Q. Rebelato E. Rorsman N.J.G. Martín-Del-Río R. et al.Fumarate Hydratase Deletion in Pancreatic β Cells Leads to Progressive Diabetes.Cell Rep. 2017; 20: 3135-3148Abstract Full Text Full Text PDF PubMed Scopus (41) Google Scholar, Li et al., 2008Li C. Nissim I. Chen P. Buettger C. Najafi H. Daikhin Y. Nissim I. Collins H.W. Yudkoff M. Stanley C.A. Matschinsky F.M. Elimination of KATP channels in mouse islets results in elevated [U-13C]glucose metabolism, glutaminolysis, and pyruvate cycling but a decreased gamma-aminobutyric acid shunt.J. Biol. Chem. 2008; 283: 17238-17249Crossref PubMed Scopus (33) Google Scholar, Wall et al., 2015Wall M.L. Pound L.D. Trenary I. O’Brien R.M. Young J.D. Novel stable isotope analyses demonstrate significant rates of glucose cycling in mouse pancreatic islets.Diabetes. 2015; 64: 2129-2137Crossref PubMed Scopus (18) Google Scholar). However, islet nutrient metabolism has not been broadly characterized, and it is unknown whether β cells regulate GSIS with age by altering glucose metabolism. In this study, we employed in vivo SILAM MS to comprehensively assess differences in islet protein levels between juvenile and adult mice. We further employed targeted metabolomics coupled with nutrient tracing in islets from juvenile and adult mice and characterized metabolic processes contributing to insulin secretion. Combined, these studies revealed hitherto unknown changes in the abundance of metabolic enzymes with age, which coincide with increased generation of glucose-derived coupling factors involved in the regulation of GSIS. Together, this study provides an in-depth characterization of age-dependent changes in the islet proteome and establishes metabolic rewiring as an important mechanism for regulating GSIS throughout life. To identify age-regulated proteins in pancreatic islets, we performed 15N SILAM MudPIT LC-MS/MS (McClatchy et al., 2007McClatchy D.B. Dong M.Q. Wu C.C. Venable J.D. Yates 3rd, J.R. 15N metabolic labeling of mammalian tissue with slow protein turnover.J. Proteome Res. 2007; 6: 2005-2010Crossref PubMed Scopus (106) Google Scholar, Washburn et al., 2001Washburn M.P. Wolters D. Yates 3rd, J.R. Large-scale analysis of the yeast proteome by multidimensional protein identification technology.Nat. Biotechnol. 2001; 19: 242-247Crossref PubMed Scopus (4077) Google Scholar). We metabolically labeled C57BL/6 mice by administering chow containing 15N-labeled amino acids to 3-week-old mice immediately after weaning for 10–11 weeks. Islets were then isolated from these mice (n = 56), pooled, and total protein lysates were mixed 1:1 with protein from 14N non-labeled islets from either 4-week-old (n = 62) or 1-year-old mice (n = 38) (Figure 1A), hereafter referred to as “juvenile” mice corresponding to the pre-pubescent stage and “adult” mice corresponding to middle age, respectively. We chose these ages to correspond to time points used in other studies assessing age-dependent changes to the β cell epigenome and transcriptome (Avrahami et al., 2015Avrahami D. Li C. Zhang J. Schug J. Avrahami R. Rao S. Stadler M.B. Burger L. Schübeler D. Glaser B. Kaestner K.H. Aging-Dependent Demethylation of Regulatory Elements Correlates with Chromatin State and Improved β Cell Function.Cell Metab. 2015; 22: 619-632Abstract Full Text Full Text PDF PubMed Scopus (133) Google Scholar) coincident with well-established differences in GSIS (Helman et al., 2016Helman A. Klochendler A. Azazmeh N. Gabai Y. Horwitz E. Anzi S. Swisa A. Condiotti R. Granit R.Z. Nevo Y. et al.p16(Ink4a)-induced senescence of pancreatic beta cells enhances insulin secretion.Nat. Med. 2016; 22: 412-420Crossref PubMed Scopus (184) Google Scholar). Proteins were proteolytically digested, loaded onto a two-dimensional column, and analyzed by multidimensional LC coupled to an electro-spray ionization tandem mass spectrometer. The mass spectrometer distinguished “heavy” 15N-labeled peptides from “light” 14N non-labeled peptides, and through subsequent protein identification and ratio-of-ratios analyses, we quantified relative protein abundance, comparing juvenile and adult islets (Park et al., 2006Park S.K. Venable J.D. Xu T. Liao L. Yates J.R. A tool for quantitative analysis of high-throughput mass spectrometry data.Mol. Cell. Proteomics. 2006; 5: S199Google Scholar). We achieved 15N enrichment of greater than 95.6% (Figure S1A). We identified 37,721 peptides (9,058 proteins) in 4-week-old islets and 38,657 peptides (9,000 proteins) in 1-year-old islets at a false discovery rate (FDR) < 1% based on the target-decoy strategy, and quantified 10,245 proteins (Table S1A; see STAR Methods). Gene Ontology (GO) analysis of all quantified proteins revealed a broad representation of proteins from multiple cellular components and association with diverse cellular functions and biological processes in a distribution similar to that of all genes (Figures S1B and S1C). This demonstrates that our quantitative proteomics approach captured a comprehensive, unbiased, and diverse set of islet proteins. To identify statistically significant differentially expressed proteins, we generated 14N 4-week-old/15N 14-week-old or 14N 1-year-old/15N 14-week-old peptide ratios to calculate a 14N 1-year-old/14N 4-week-old “ratio of ratios” (Figure 1A). We compared four biological replicates of juvenile and adult islets to calculate log2(adult/juvenile) and t test p values (Figure 1B). Consolidating isoforms, 393 uniquely named proteins were significantly enriched in 4-week-old islets and 551 proteins in 1-year-old islets, exhibiting at least a 1.2-fold change (Tables S1B and S1C). Among the proteins enriched in islets from adult mice was Urocortin 3 (Ucn3) (Table S1C), a previously identified β cell maturation marker involved in the regulation of insulin secretion (Blum et al., 2012Blum B. Hrvatin S. Schuetz C. Bonal C. Rezania A. Melton D.A. Functional beta-cell maturation is marked by an increased glucose threshold and by expression of urocortin 3.Nat. Biotechnol. 2012; 30: 261-264Crossref PubMed Scopus (249) Google Scholar, van der Meulen et al., 2015van der Meulen T. Donaldson C.J. Cáceres E. Hunter A.E. Cowing-Zitron C. Pound L.D. Adams M.W. Zembrzycki A. Grove K.L. Huising M.O. Urocortin3 mediates somatostatin-dependent negative feedback control of insulin secretion.Nat. Med. 2015; 21: 769-776Crossref PubMed Scopus (152) Google Scholar). Thus, our proteomics approach identified changes in protein abundance that are consistent with previous studies. To understand the dynamics of age-dependent regulation of the islet proteome, we performed GO annotation and Gene Set Enrichment Analysis (GSEA) of the differentially expressed proteins. Additionally, we built a network of functional categories by linking proteins via STRING interactions and assigning pathway categories to groups of proteins using Metascape (see STAR Methods) (Szklarczyk et al., 2015Szklarczyk D. Franceschini A. Wyder S. Forslund K. Heller D. Huerta-Cepas J. Simonovic M. Roth A. Santos A. Tsafou K.P. et al.STRING v10: protein-protein interaction networks, integrated over the tree of life.Nucleic Acids Res. 2015; 43: D447-D452Crossref PubMed Scopus (6709) Google Scholar, Tripathi et al., 2015Tripathi S. Pohl M.O. Zhou Y. Rodriguez-Frandsen A. Wang G. Stein D.A. Moulton H.M. DeJesus P. Che J. Mulder L.C. et al.Meta- and Orthogonal Integration of Influenza “OMICs” Data Defines a Role for UBR4 in Virus Budding.Cell Host Microbe. 2015; 18: 723-735Abstract Full Text Full Text PDF PubMed Scopus (625) Google Scholar). Proteins that decreased in abundance with age were functionally associated with RNA splicing, epigenetic regulation of gene expression, response to DNA damage, translation, and cell cycle regulation (Figures 1C, 1E and S1D; Tables S2A and S2C), which is consistent with declining β cell proliferation during this time period (Teta et al., 2005Teta M. Long S.Y. Wartschow L.M. Rankin M.M. Kushner J.A. Very slow turnover of beta-cells in aged adult mice.Diabetes. 2005; 54: 2557-2567Crossref PubMed Scopus (392) Google Scholar). Conversely, there was a striking age-dependent increase in proteins associated with the regulation of aspects of cell metabolism, including amino acid metabolism, oxidative phosphorylation, glycolysis, and fatty acid metabolism (Figures 1D, 1E and S1E; Tables S2B and S2D). Among the regulators of nutrient metabolism that increased in abundance with age were enzymes involved in glucose metabolism (e.g., Aldoa and Eno2), components of the tricarboxylic acid (TCA) cycle (e.g., Pdha1, Cs, and Fh1) and respiratory chain (e.g., Ndufv3, Cox4i1, and Atp6v1h), as well as enzymes important for fatty acid (e.g., Acaa2, Acat1, and Hadh) and amino acid metabolism (i.e., Bcat2 and Bckdhb) (Table S2B). Given the coupling of insulin secretion to β cell nutrient metabolism (Prentki et al., 2013Prentki M. Matschinsky F.M. Madiraju S.R. Metabolic signaling in fuel-induced insulin secretion.Cell Metab. 2013; 18: 162-185Abstract Full Text Full Text PDF PubMed Scopus (366) Google Scholar), this suggests that the observed increase in β cell GSIS with age (Avrahami et al., 2015Avrahami D. Li C. Zhang J. Schug J. Avrahami R. Rao S. Stadler M.B. Burger L. Schübeler D. Glaser B. Kaestner K.H. Aging-Dependent Demethylation of Regulatory Elements Correlates with Chromatin State and Improved β Cell Function.Cell Metab. 2015; 22: 619-632Abstract Full Text Full Text PDF PubMed Scopus (133) Google Scholar, Gregg et al., 2016Gregg T. Poudel C. Schmidt B.A. Dhillon R.S. Sdao S.M. Truchan N.A. Baar E.L. Fernandez L.A. Denu J.M. Eliceiri K.W. et al.Pancreatic β-Cells From Mice Offset Age-Associated Mitochondrial Deficiency With Reduced KATP Channel Activity.Diabetes. 2016; 65: 2700-2710Crossref PubMed Scopus (46) Google Scholar, Helman et al., 2016Helman A. Klochendler A. Azazmeh N. Gabai Y. Horwitz E. Anzi S. Swisa A. Condiotti R. Granit R.Z. Nevo Y. et al.p16(Ink4a)-induced senescence of pancreatic beta cells enhances insulin secretion.Nat. Med. 2016; 22: 412-420Crossref PubMed Scopus (184) Google Scholar) could be caused by age-related changes in nutrient metabolism. To determine the extent of correlation between the age-regulated islet proteome and transcriptome, we performed RNA sequencing (RNA-seq) on islets from 4-week-old and 1-year-old mice. We found 1,348 genes that increased and 1,542 genes that decreased in expression with age (≥1.2-fold change, p < 0.05; Figure 2A; Table S3). GO and GSEA analysis showed some, but incomplete, overlap between functional categories regulated at the mRNA and protein level (Figures S2A–S2D; Table S4). To assess to which extent individual mRNAs and proteins are co-regulated with age, we calculated the correlation coefficient between changes in protein and mRNA levels. Considering all 10,245 proteins quantified by in vivo proteomics (Table S1A), we found a modest correlation between age-associated regulation at the mRNA and protein level (ρ = 0.4, p = 2.2 × 10−16; Figure 2B). Of the unique proteins that changed in abundance with age, only 11.5% (109 out of 944) were also regulated at the mRNA level (Figures S2E and S2F; Table S5). GSEA of differentially expressed proteins not regulated at the mRNA level revealed involvement in RNA splicing, cell cycle, and proteasome regulation for proteins decreasing with age and oxidative phosphorylation, TCA cycle, and fatty acid metabolism for proteins increasing with age (Figure 2C; Table S6). To further validate these findings, we queried our islet proteome network against corresponding mRNA changes by building a similar mRNA category network and identifying the category nodes that overlap with the protein network (Figure 2D). This revealed that many categories, including RNA splicing, cell cycle, translation, response to insulin, and ion homeostasis, were mostly exclusive to the protein network (Figure 2E). Furthermore, several categories such as oxidative phosphorylation, glycosylation, and response to nutrient levels were enriched in the protein network with very few nodes enriched in the mRNA network. In sum, this analysis shows significant age-related changes in the abundance of proteins involved in nutrient metabolism not associated with corresponding transcriptional changes. Insulin secretion is modulated by diverse metabolic inputs (Prentki et al., 2013Prentki M. Matschinsky F.M. Madiraju S.R. Metabolic signaling in fuel-induced insulin secretion.Cell Metab. 2013; 18: 162-185Abstract Full Text Full Text PDF PubMed Scopus (366) Google Scholar). While glucose is the key stimulus for insulin secretion, the amplitude of the GSIS response is significantly augmented by metabolites derived from lipid catabolism and the TCA cycle. Having observed that TCA cycle and fatty acid metabolism enzymes are more abundant in older mice, we predicted that these metabolic pathways could contribute to the observed increase in GSIS in aged islets (Avrahami et al., 2015Avrahami D. Li C. Zhang J. Schug J. Avrahami R. Rao S. Stadler M.B. Burger L. Schübeler D. Glaser B. Kaestner K.H. Aging-Dependent Demethylation of Regulatory Elements Correlates with Chromatin State and Improved β Cell Function.Cell Metab. 2015; 22: 619-632Abstract Full Text Full Text PDF PubMed Scopus (133) Google Scholar, Gregg et al., 2016Gregg T. Poudel C. Schmidt B.A. Dhillon R.S. Sdao S.M. Truchan N.A. Baar E.L. Fernandez L.A. Denu J.M. Eliceiri K.W. et al.Pancreatic β-Cells From Mice Offset Age-Associated Mitochondrial Deficiency With Reduced KATP Channel Activity.Diabetes. 2016; 65: 2700-2710Crossref PubMed Scopus (46) Google Scholar, Helman et al., 2016Helman A. Klochendler A. Azazmeh N. Gabai Y. Horwitz E. Anzi S. Swisa A. Condiotti R. Granit R.Z. Nevo Y. et al.p16(Ink4a)-induced senescence of pancreatic beta cells enhances insulin secretion.Nat. Med. 2016; 22: 412-420Crossref PubMed Scopus (184) Google Scholar). Therefore, we measured insulin content and secretion in islets from 4-week-old and 1-year-old mice co-stimulated with glucose and nutrients contributing to lipid metabolism (palmitic acid) or the TCA cycle (leucine and glutamine). Total insulin content did not differ between islets from juvenile and adult mice (Figure S3A). Consistent with prior findings (Avrahami et al., 2015Avrahami D. Li C. Zhang J. Schug J. Avrahami R. Rao S. Stadler M.B. Burger L. Schübeler D. Glaser B. Kaestner K.H. Aging-Dependent Demethylation of Regulatory Elements Correlates with Chromatin State and Improved β Cell Function.Cell Metab. 2015; 22: 619-632Abstract Full Text Full Text PDF PubMed Scopus (133) Google Scholar, Gregg et al., 2016Gregg T. Poudel C. Schmidt B.A. Dhillon R.S. Sdao S.M. Truchan N.A. Baar E.L. Fernandez L.A. Denu J.M. Eliceiri K.W. et al.Pancreatic β-Cells From Mice Offset Age-Associated Mitochondrial Deficiency With Reduced KATP Channel Activity.Diabetes. 2016; 65: 2700-2710Crossref PubMed Scopus (46) Google Scholar, Helman et al., 2016Helman A. Klochendler A. Azazmeh N. Gabai Y. Horwitz E. Anzi S. Swisa A. Condiotti R. Granit R.Z. Nevo Y. et al.p16(Ink4a)-induced senescence of pancreatic beta cells enhances insulin secretion.Nat. Med. 2016; 22: 412-420Crossref PubMed Scopus (184) Google Scholar), islets from 1-year-old mice exhibited a more robust insulin secretory response to high glucose than islets from 4-week-old mice (Figure 3A). Co-stimulation with glucose and the amino acids leucine and glutamine potentiated GSIS, but the response was modestly reduced rather than increased in adult compared to juvenile islets (Figure 3A; 1.5-fold increase in adult versus 2.2-fold increase in juvenile compared to glucose alone). Potentiation of GSIS by the fatty acid palmitate was absent in islets from 1-year-old mice (0.8-fold in adult versus 2.6-fold in juvenile) (Figure 3A). Therefore, alterations in fatty acid and amino acid metabolism are unlikely to explain age-associated differences in GSIS. Nutrients can potentiate insulin secretion through inhibition of the ATP-sensitive K+ (KATP) channel by serving as substrates for ATP synthesis (the triggering pathway) or through production of intermediary metabolites that enhance the effect of Ca2+ on insulin secretion (the amplifying pathway). Metabolites capable of activating the amplifying pathway are termed metabolic coupling factors. To assess the ability of nutrients to enhance insulin secretion independent of KATP channel closure, we provided islets with glucose, amino acids, or fatty acids while simultaneously treating with KCl and diazoxide to stimulate Ca2+ influx and prevent further changes in membrane potential through the KATP channel (Figure 3A). Under these conditions, islets from adult mice secreted more insulin in response to glucose than islets from juvenile mice, whereas the two groups responded similarly to amino acids and palmitic acid. The more pronounced age-dependent increase in GSIS under normal conditions (4.1-fold compared to 1.3-fold) suggests that differences in the triggering pathway are more functionally impactful than differences in the amplifying pathway, though both pathways clearly contribute to age-related changes in GSIS. Similar responses of adult and juvenile islets to amino acids and palmitate during forced depolarization (measuring the amplifying pathway alone) are in contrast to age-related differences in the ability of these nutrients to potentiate insulin secretion in response to glucose (which reflects both triggering and amplifying pathways). These observations suggest there could be modest age-dependent differences in modulation of the triggering pathway of insulin secretion by these nutrients. Altogether, these results indicate that enhanced insulin secretion of adult islets reflects a specific hypersensitivity to glucose rather than a heightened response to nutrients in general. Furthermore, the increased glucose responsiveness of adult islets occurs in part through mechanisms independent of KATP channel inhibition, suggesting that changes in glucose metabolism leading to altered production of metabolic coupling factors could underlie enhanced GSIS with age. The mitochondrion is a major site for the generation of metabolic coupling factors during glucose stimulation (Prentki et al., 2013Prentki M. Matschinsky F.M. Madiraju S.R. Metabolic signaling in fuel-induced insulin secretion.Cell Metab. 2013; 18: 162-185Abstract Full Text Full Text PDF PubMed Scopus (366) Google Scholar). Given the upregulation of proteins involved in oxidative phosphorylation with age, we predicted that increased mitochondrial abundance or respiratory capacity could underlie the generation of metabolites that stimulate the amplifying pathway of insulin secretion. Thus, we investigated mitochondrial function and morphology in juvenile and adult islets. Transmission electron microscopy (TEM) of β cells did not reveal an increase in mitochondrial number or size with age (Figures 3B–3E), nor was" @default.
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• W2895956914 date "2018-12-01" @default.
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• W2895956914 title "Integrated In Vivo Quantitative Proteomics and Nutrient Tracing Reveals Age-Related Metabolic Rewiring of Pancreatic β Cell Function" @default.
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