not that comparisons

Impaired BCAA catabolism in adipose tissues promotes age-associated metabolic derangement

Liu, Z., Wu, Ok. Ok. L., Jiang, X., Xu, A. & Cheng, Ok. Ok. Y. The position of adipose tissue senescence in obesity- and ageing-related metabolic problems. Clin. Sci. 134, 315–330 (2020).

Martyniak, Ok. & Masternak, M. M. Modifications in adipose tissue mobile composition throughout weight problems and ageing as a reason for metabolic dysregulation. Exp. Gerontol. 94, 59–63 (2017).

Stout, M. B., Justice, J. N., Nicklas, B. J. & Kirkland, J. L. Physiological ageing: hyperlinks amongst adipose tissue dysfunction, diabetes, and frailty. Physiology 32, 9–19 (2017).

Sethi, J. Ok. & Vidal-Puig, A. J. Thematic overview collection: adipocyte biology. Adipose tissue operate and plasticity orchestrate dietary adaptation. J. Lipid Res. 48, 1253–1262 (2007).

Tchkonia, T. et al. Fats tissue, ageing, and mobile senescence. Growing old Cell 9, 667–684 (2010).

Palmer, A. Ok. et al. Focusing on senescent cells alleviates obesity-induced metabolic dysfunction. Growing old Cell 18, e12950 (2019).

Coppe, J. P. et al. Senescence-associated secretory phenotypes reveal cell-nonautonomous features of oncogenic RAS and the p53 tumor suppressor. PLoS Biol. 6, 2853–2868 (2008).

Coppe, J. P. et al. A human-like senescence-associated secretory phenotype is conserved in mouse cells depending on physiological oxygen. PLoS ONE 5, e9188 (2010).

Xu, M. et al. Focusing on senescent cells enhances adipogenesis and metabolic operate in previous age. eLife 4, e12997 (2015).

Han, H. S., Kwon, Y. & Koo, S. H. Position of CRTC2 in metabolic homeostasis: key regulator of whole-body vitality metabolism. Diabetes Metab. J. 44, 498–508 (2020).

Koo, S. H. et al. The CREB coactivator TORC2 is a key regulator of fasting glucose metabolism. Nature 437, 1109–1111 (2005).

Lee, M. W. et al. Regulation of hepatic gluconeogenesis by an ER-bound transcription issue, CREBH. Cell Metab. 11, 331–339 (2010).

Wang, Y., Vera, L., Fischer, W. H. & Montminy, M. The CREB coactivator CRTC2 hyperlinks hepatic ER stress and fasting gluconeogenesis. Nature 460, 534–537 (2009).

Li, Y. et al. A novel position for CRTC2 in hepatic ldl cholesterol synthesis by way of SREBP-2. Hepatology 66, 481–497 (2017).

Han, J. et al. The CREB coactivator CRTC2 controls hepatic lipid metabolism by regulating SREBP1. Nature 524, 243–246 (2015).

Han, H. S., Choi, B. H., Kim, J. S., Kang, G. & Koo, S. H. Hepatic Crtc2 controls entire physique vitality metabolism by way of a miR-34a-Fgf21 axis. Nat. Commun. 8, 1878 (2017).

Han, H. S. et al. A novel position of CRTC2 in selling nonalcoholic fatty liver illness. Mol. Metab. 55, 101402 (2022).

Lee, J. H., Wen, X., Cho, H. & Koo, S. H. CREB/CRTC2 controls GLP-1-dependent regulation of glucose homeostasis. FASEB J. 32, 1566–1578 (2018).

Blanchet, E. et al. Suggestions inhibition of CREB signaling promotes β cell dysfunction in insulin resistance. Cell Rep. 10, 1149–1157 (2015).

Music, Y. et al. CRTC3 hyperlinks catecholamine signalling to vitality steadiness. Nature 468, 933–939 (2010).

Yoon, Y. S. et al. cAMP-inducible coactivator CRTC3 attenuates brown adipose tissue thermogenesis. PNAS 115, E5289–E5297 (2018).

Mair, W. et al. Lifespan extension induced by AMPK and calcineurin is mediated by CRTC-1 and CREB. Nature 470, 404–408 (2011).

Burkewitz, Ok. et al. Neuronal CRTC-1 governs systemic mitochondrial metabolism and lifespan by way of a catecholamine sign. Cell 160, 842–855 (2015).

Kevin Flurkey, J. M. C., D.E. Harrison. in The Mouse in Biomedical Analysis Vol. III Ch. 20, 637–672 (Elsevier, 2007).

Petkevicius, Ok. et al. Accelerated phosphatidylcholine turnover in macrophages promotes adipose tissue irritation in weight problems. eLife 8, e47990 (2019).

Yoo, H., Antoniewicz, M. R., Stephanopoulos, G. & Kelleher, J. Ok. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. J. Biol. Chem. 283, 20621–20627 (2008).

Wurtz, P. et al. Metabolic signatures of insulin resistance in 7,098 younger adults. Diabetes 61, 1372–1380 (2012).

Newgard, C. B. et al. A branched-chain amino acid-related metabolic signature that differentiates overweight and lean people and contributes to insulin resistance. Cell Metab. 9, 311–326 (2009).

Newgard, C. B. Interaction between lipids and branched-chain amino acids in improvement of insulin resistance. Cell Metab. 15, 606–614 (2012).

Olson, Ok. C., Chen, G., Xu, Y., Hajnal, A. & Lynch, C. J. Alloisoleucine differentiates the branched-chain aminoacidemia of Zucker and dietary overweight rats. Weight problems 22, 1212–1215 (2014).

Zhou, M. et al. Focusing on BCAA catabolism to deal with obesity-associated insulin resistance. Diabetes 68, 1730–1746 (2019).

Solon-Biet, S. M. et al. Branched chain amino acids impression well being and lifespan not directly by way of amino acid steadiness and urge for food management. Nat. Metab. 1, 532–545 (2019).

Richardson, N. E. et al. Lifelong restriction of dietary branched-chain amino acids has sex-specific advantages for frailty and lifespan in mice. Nat. Growing old 1, 73–86 (2021).

Lackey, D. E. et al. Regulation of adipose branched-chain amino acid catabolism enzyme expression and cross-adipose amino acid flux in human weight problems. Am. J. Physiol. Endocrinol. Metab. 304, E1175–E1187 (2013).

Herman, M. A., She, P., Peroni, O. D., Lynch, C. J. & Kahn, B. B. Adipose tissue branched chain amino acid (BCAA) metabolism modulates circulating BCAA ranges. J. Biol. Chem. 285, 11348–11356 (2010).

Takashima, M. et al. Position of KLF15 in regulation of hepatic gluconeogenesis and metformin motion. Diabetes 59, 1608–1615 (2010).

Blanchard, P. G. et al. PPARγ is a significant regulator of branched-chain amino acid blood ranges and catabolism in white and brown adipose tissues. Metabolism 89, 27–38 (2018).

Herzig, S. et al. CREB controls hepatic lipid metabolism by way of nuclear hormone receptor PPAR-γ. Nature 426, 190–193 (2003).

Chen, C., Zhou, M., Ge, Y. & Wang, X. SIRT1 and ageing associated signaling pathways. Mech. Ageing Dev. 187, 111215 (2020).

Lamming, D. W. & Sabatini, D. M. A central position for mTOR in lipid homeostasis. Cell Metab. 18, 465–469 (2013).

Van Skike, C. E. et al. mTOR drives cerebrovascular, synaptic, and cognitive dysfunction in normative ageing. Growing old Cell 19, e13057 (2020).

Zhao, X. et al. Metformin protects PC12 cells and hippocampal neurons from H 2 O 2 -induced oxidative injury by way of activation of AMPK pathway. J. Cell Physiol. https://doi.org/10.1002/jcp.28337 (2019).

Satoh, A. et al. Sirt1 extends life span and delays ageing in mice by way of the regulation of Nk2 homeobox 1 within the DMH and LH. Cell Metab. 18, 416–430 (2013).

Lee, J. et al. A pathway involving farnesoid X receptor and small heterodimer accomplice positively regulates hepatic sirtuin 1 ranges by way of microRNA-34a inhibition. J. Biol. Chem. 285, 12604–12611 (2010).

Lannes, J. et al. Speedy communication: a microRNA-132/212 pathway mediates GnRH activation of FSH expression. Mol. Endocrinol. 29, 364–372 (2015).

Vasa-Nicotera, M. et al. miR-146a is modulated in human endothelial cell with ageing. Atherosclerosis 217, 326–330 (2011).

Vo, N. et al. A cAMP-response component binding protein-induced microRNA regulates neuronal morphogenesis. PNAS 102, 16426–16431 (2005).

Yoon, M. S. & Choi, C. S. The position of amino acid-induced mammalian goal of rapamycin complicated 1(mTORC1) signaling in insulin resistance. Exp. Mol. Med. 48, e201 (2016).

Herzig, S. & Shaw, R. J. AMPK: guardian of metabolism and mitochondrial homeostasis. Nat. Rev. Mol. Cell Biol. 19, 121–135 (2018).

Lumeng, C. N. et al. Growing old is related to a rise in T cells and inflammatory macrophages in visceral adipose tissue. J. Immunol. 187, 6208–6216 (2011).

Carter, S. et al. Lack of OcaB prevents age-induced fats accretion and insulin resistance by altering B-lymphocyte transition and selling vitality expenditure. Diabetes 67, 1285–1296 (2018).

Camell, C. D. et al. Growing old induces an Nlrp3 inflammasome-dependent growth of adipose B cells that impairs metabolic homeostasis. Cell Metab. 30, 1024–1039 (2019).

Bapat, S. P. et al. Depletion of fat-resident Treg cells prevents age-associated insulin resistance. Nature 528, 137–141 (2015).

Chakarov, S. et al. Two distinct interstitial macrophage populations coexist throughout tissues in particular subtissular niches. Science 363, eaau0964 (2019).

Jaitin, D. A. et al. Lipid-associated macrophages management metabolic homeostasis in a Trem2-dependent method. Cell 178, 686–698 (2019).

Hill, D. A. et al. Distinct macrophage populations direct inflammatory versus physiological modifications in adipose tissue. PNAS 115, E5096–E5105 (2018).

Pirzgalska, R. M. et al. Sympathetic neuron-associated macrophages contribute to weight problems by importing and metabolizing norepinephrine. Nat. Med. 23, 1309–1318 (2017).

Merrick, D. et al. Identification of a mesenchymal progenitor cell hierarchy in adipose tissue. Science https://doi.org/10.1126/science.aav2501 (2019).

Nahmgoong, H. et al. Distinct properties of adipose stem cell subpopulations decide fats depot-specific traits. Cell metabolism 34, 458–472 e456 (2022).

Fuster, J. J. et al. Noncanonical Wnt signaling promotes obesity-induced adipose tissue irritation and metabolic dysfunction unbiased of adipose tissue growth. Diabetes 64, 1235–1248 (2015).

Trayhurn, P. Hypoxia and adipose tissue operate and dysfunction in weight problems. Physiol. Rev. 93, 1–21 (2013).

Datta, R., Podolsky, M. J. & Atabai, Ok. Fats fibrosis: buddy or foe? JCI Perception https://doi.org/10.1172/jci.perception.122289 (2018).

Hu, L. et al. IGF1 promotes adipogenesis by a lineage bias of endogenous adipose stem/progenitor cells. Stem Cells 33, 2483–2495 (2015).

Eguchi, J. et al. Interferon regulatory components are transcriptional regulators of adipogenesis. Cell Metab. 7, 86–94 (2008).

Zhu, W., Zhao, M., Mattapally, S., Chen, S. & Zhang, J. CCND2 overexpression enhances the regenerative efficiency of human induced pluripotent stem cell-derived cardiomyocytes: remuscularization of injured ventricle. Circ. Res. 122, 88–96 (2018).

Jun, J. I. & Lau, L. F. The matricellular protein CCN1 induces fibroblast senescence andrestricts fibrosis in cutaneous wound therapeutic. Nat. Cell Biol. 12, 676–685 (2010).

Arcidiacono, B. et al. Expression of matrix metalloproteinase-11 is elevated below circumstances of insulin resistance. World J. Diabetes 8, 422–428 (2017).

Ohta, H. & Itoh, N. Roles of FGFs as adipokines in adipose tissue improvement, transforming, and metabolism. Entrance. Endocrinol. 5, 18 (2014).

Laberge, R. M. et al. MTOR regulates the pro-tumorigenic senescence-associated secretory phenotype by selling IL1A translation. Nat. Cell Biol. 17, 1049–1061 (2015).

Viola, A. & Luster, A. D. Chemokines and their receptors: drug targets in immunity and irritation. Annu. Rev. Pharmacol. Toxicol. 48, 171–197 (2008).

Yoon, Y. S. et al. Activation of the adipocyte CREB/CRTC pathway in weight problems. Commun. Biol. 4, 1214 (2021).

Tchkonia, T. et al. Elevated TNFα and CCAAT/enhancer-binding protein homologous protein with ageing predispose preadipocytes to withstand adipogenesis. Am. J. Physiol. Endocrinol. Metab. 293, E1810–E1819 (2007).

Lynch, C. J. & Adams, S. H. Branched-chain amino acids in metabolic signalling and insulin resistance. Nat. Rev. Endocrinol. 10, 723–736 (2014).

Blanchard, P. G. et al. Main involvement of mTOR within the PPARγ-induced stimulation of adipose tissue lipid uptake and fats accretion. J. Lipid Res. 53, 1117–1125 (2012).

Leibowitz, G., Cerasi, E. & Ketzinel-Gilad, M. The position of mTOR within the adaptation and failure of β-cells in kind 2 diabetes. Diabetes Obes. Metab. 10, 157–169 (2008).

Magkos, F. et al. Impact of Roux-en-Y gastric bypass and laparoscopic adjustable gastric banding on branched-chain amino acid metabolism. Diabetes 62, 2757–2761 (2013).

Choi, S. et al. Depletion of Prmt1 in adipocytes impairs glucose homeostasis in diet-induced weight problems. Diabetes 70, 1664–1678 (2021).

Lee, H. et al. Prominin-1-radixin axis controls hepatic gluconeogenesis by regulating PKA exercise. EMBO Rep. 21, e49416 (2020).

Storey, J. D. & Tibshirani, R. Statistical significance for genomewide research. PNAS 100, 9440–9445 (2003).

Younger, M. D., Wakefield, M. J., Smyth, G. Ok. & Oshlack, A. Gene Ontology evaluation for RNA-seq: accounting for choice bias. Genome Biol. 11, R14 (2010).

Ogata, H. et al. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 27, 29–34 (1999).

Luo, W. & Brouwer, C. Pathview: an R/Bioconductor package deal for pathway-based information integration and visualization. Bioinformatics 29, 1830–1831 (2013).

Zheng, G. X. et al. Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 8, 14049 (2017).

Lun, A. T. L. et al. EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing information. Genome Biol. 20, 63 (2019).

McCarthy, D. J., Campbell, Ok. R., Lun, A. T. & Wills, Q. F. Scater: pre-processing, high quality management, normalization and visualization of single-cell RNA-seq information in R. Bioinformatics 33, 1179–1186 (2017).

Lun, A. T., McCarthy, D. J. & Marioni, J. C. A step-by-step workflow for low-level evaluation of single-cell RNA-seq information with Bioconductor. F1000Res 5, 2122 (2016).

Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic information throughout totally different circumstances, applied sciences, and species. Nat. Biotechnol. 36, 411–420 (2018).

Sonntag, T. et al. Mitogenic indicators stimulate the CREB coactivator CRTC3 by way of PP2A recruitment. iScience 11, 134–145 (2019).

Fonseka, C. Y. et al. Blended-effects affiliation of single cells identifies an expanded effector CD4(+) T cell subset in rheumatoid arthritis. Sci. Transl. Med. 10, eaaq0305 (2018).

Setty, M. et al. Characterization of cell destiny chances in single-cell information with Palantir. Nat. Biotechnol. 37, 451–460 (2019).

Holland, C. H. et al. Robustness and applicability of transcription issue and pathway evaluation instruments on single-cell RNA-seq information. Genome Biol. 21, 36 (2020).

Holland, C. H., Szalai, B. & Saez-Rodriguez, J. Switch of regulatory information from human to mouse for purposeful genomics evaluation. Biochim. Biophys. Acta Gene Regul. Mech. 1863, 194431 (2020).

Schubert, M. et al. Perturbation-response genes reveal signaling footprints in most cancers gene expression. Nat. Commun. 9, 20 (2018).

Related Articles

Back to top button