RESUMO
Insulin triggers an extensive signaling cascade to coordinate adipocyte glucose metabolism. It is considered that the major role of insulin is to provide anabolic substrates by activating GLUT4-dependent glucose uptake. However, insulin stimulates phosphorylation of many metabolic proteins. To examine the implications of this on glucose metabolism, we performed dynamic tracer metabolomics in cultured adipocytes treated with insulin. Temporal analysis of metabolite concentrations and tracer labeling revealed rapid and distinct changes in glucose metabolism, favoring specific glycolytic branch points and pyruvate anaplerosis. Integrating dynamic metabolomics and phosphoproteomics data revealed that insulin-dependent phosphorylation of anabolic enzymes occurred prior to substrate accumulation. Indeed, glycogen synthesis was activated independently of glucose supply. We refer to this phenomenon as metabolic priming, whereby insulin signaling creates a demand-driven system to "pull" glucose into specific anabolic pathways. This complements the supply-driven regulation of anabolism by substrate accumulation and highlights an additional role for insulin action in adipocyte glucose metabolism.
Assuntos
Adipócitos/metabolismo , Glucose/metabolismo , Insulina/metabolismo , Metaboloma , Células 3T3 , Animais , Camundongos , Transdução de SinaisRESUMO
[This corrects the article DOI: 10.1371/journal.pone.0157763.].
RESUMO
FGF21 improves the metabolic profile of obese animals through its actions on adipocytes. To elucidate the signaling network responsible for mediating these effects, we quantified dynamic changes in the adipocyte phosphoproteome following acute exposure to FGF21. FGF21 regulated a network of 821 phosphosites on 542 proteins. A major FGF21-regulated signaling node was mTORC1/S6K. In contrast to insulin, FGF21 activated mTORC1 via MAPK rather than through the canonical PI3K/AKT pathway. Activation of mTORC1/S6K by FGF21 was surprising because this is thought to contribute to deleterious metabolic effects such as obesity and insulin resistance. Rather, mTORC1 mediated many of the beneficial actions of FGF21 in vitro, including UCP1 and FGF21 induction, increased adiponectin secretion, and enhanced glucose uptake without any adverse effects on insulin action. This study provides a global view of FGF21 signaling and suggests that mTORC1 may act to facilitate FGF21-mediated health benefits in vivo.
Assuntos
Adipócitos/efeitos dos fármacos , Adiponectina/genética , Fatores de Crescimento de Fibroblastos/farmacologia , Complexos Multiproteicos/genética , Fosfoproteínas/genética , Proteínas Quinases S6 Ribossômicas 90-kDa/genética , Serina-Treonina Quinases TOR/genética , Células 3T3-L1 , Adipócitos/citologia , Adipócitos/metabolismo , Adiponectina/agonistas , Adiponectina/metabolismo , Animais , Diferenciação Celular , Desoxiglucose/metabolismo , Fatores de Crescimento de Fibroblastos/genética , Fatores de Crescimento de Fibroblastos/metabolismo , Regulação da Expressão Gênica , Redes Reguladoras de Genes/efeitos dos fármacos , Injeções Intraperitoneais , Marcação por Isótopo , Alvo Mecanístico do Complexo 1 de Rapamicina , Camundongos , Camundongos Endogâmicos C57BL , Complexos Multiproteicos/agonistas , Complexos Multiproteicos/metabolismo , Fosfoproteínas/metabolismo , Proteoma/genética , Proteoma/metabolismo , Proteínas Proto-Oncogênicas c-akt/genética , Proteínas Proto-Oncogênicas c-akt/metabolismo , Proteínas Quinases S6 Ribossômicas 90-kDa/metabolismo , Transdução de Sinais , Sirolimo/farmacologia , Gordura Subcutânea Abdominal/citologia , Gordura Subcutânea Abdominal/efeitos dos fármacos , Gordura Subcutânea Abdominal/metabolismo , Serina-Treonina Quinases TOR/metabolismo , Proteína Desacopladora 1/agonistas , Proteína Desacopladora 1/genética , Proteína Desacopladora 1/metabolismoRESUMO
In response to stimuli, biological processes are tightly controlled by dynamic cellular signaling mechanisms. Reversible protein phosphorylation occurs on rapid time-scales (milliseconds to seconds), making it an ideal carrier of these signals. Advances in mass spectrometry-based proteomics have led to the identification of many tens of thousands of phosphorylation sites, yet for the majority of these the kinase is unknown and the underlying network topology of signaling networks therefore remains obscured. Identifying kinase substrate relationships (KSRs) is therefore an important goal in cell signaling research. Existing consensus sequence motif based prediction algorithms do not consider the biological context of KSRs, and are therefore insensitive to many other mechanisms guiding kinase-substrate recognition in cellular contexts. Here, we use temporal information to identify biologically relevant KSRs from Large-scale In Vivo Experiments (KSR-LIVE) in a data-dependent and automated fashion. First, we used available phosphorylation databases to construct a repository of existing experimentally-predicted KSRs. For each kinase in this database, we used time-resolved phosphoproteomics data to examine how its substrates changed in phosphorylation over time. Although substrates for a particular kinase clustered together, they often exhibited a different temporal pattern to the phosphorylation of the kinase. Therefore, although phosphorylation regulates kinase activity, our findings imply that substrate phosphorylation likely serve as a better proxy for kinase activity than kinase phosphorylation. KSR-LIVE can thereby infer which kinases are regulated within a biological context. Moreover, KSR-LIVE can also be used to automatically generate positive training sets for the subsequent prediction of novel KSRs using machine learning approaches. We demonstrate that this approach can distinguish between Akt and Rps6kb1, two kinases that share the same linear consensus motif, and provide evidence suggesting IRS-1 S265 as a novel Akt site. KSR-LIVE is an open-access algorithm that allows users to dissect phosphorylation signaling within a specific biological context, with the potential to be included in the standard analysis workflow for studying temporal high-throughput signal transduction data.
Assuntos
Fosfoproteínas/metabolismo , Proteínas Quinases/metabolismo , Proteômica , Análise por Conglomerados , Biologia Computacional/métodos , Bases de Dados de Proteínas , Humanos , Fosforilação , Proteômica/métodos , Reprodutibilidade dos Testes , Especificidade por Substrato , NavegadorRESUMO
The long-held view that radiation-induced biological damage must be initiated in the cell nucleus, either on or near DNA itself, is being confronted by mounting evidence to suggest otherwise. While the efficacy of cell death may be determined by radiation damage to nuclear DNA, a plethora of less deterministic biological responses has been observed when DNA is not targeted. These so-called nontargeted responses cannot be understood in the framework of DNA-centric radiobiological models; what is needed are new physically motivated models that address the damage-sensing signalling pathways triggered by the production of reactive free radicals. To this end, we have conducted a series of in silico experiments aimed at elucidating the underlying physical processes responsible for nontargeted biological responses to radiation. Our simulation studies implement new results on very low-energy electromagnetic interactions in liquid water (applicable down to nanoscales) and we also consider a realistic simulation of extranuclear microbeam irradiation of a cell. Our results support the idea that organelles with important functional roles, such as mitochondria and lysosomes, as well as membranes, are viable targets for ionizations and excitations, and their chemical composition and density are critical to determining the free radical yield and ensuing biological responses.