The selective control of glycolysis, gluconeogenesis and glycogenesis by temporal insulin patterns

Duration of Morning Hyperinsulinemia is Key to the Enhancement of Hepatic Glucose Uptake and Glycogen Storage Later in the Day

The second meal phenomenon refers to the improvement in glucose tolerance seen following a second identical meal. We previously showed that 4 hours of morning (AM) hyperinsulinemia, but not hyperglycemia, enhanced hepatic glucose uptake (HGU) and glycogen storage during an afternoon (PM) hyperinsulinemic hyperglycemic clamp (HIHG). Our current aim was to determine if the duration or pattern of morning hyperinsulinemia is important for the PM response to a HIHG clamp. To determine this, we administered the same total amount of insulin either over 2h in the first half of the morning (Ins2h-A), over 2h in the 2nd half of the morning (Ins2h-B), or over the entire 4h (Ins4h) of the morning. In the 4h PM period, all three groups had 4x basal insulin, 2x basal glycemia, and portal glucose infusion to simulate a meal. During the PM clamp, there was a marked increase in the mean hepatic glucose uptake and hepatic glycogen synthesis in the Ins4h group compared to the Ins2h-A and Ins2h-B groups, despite matched hepatic glucose and insulin loads. Thus, the longer duration (Ins4h) of mild hyperinsulinemia in the morning seems to be the key to much greater liver glucose uptake during the PM clamp.

Trans-omic analysis reveals opposite metabolic dysregulation between feeding and fasting in liver associated with obesity

Dysregulation of liver metabolism associated with obesity during feeding and fasting leads to the breakdown of metabolic homeostasis. However, the underlying mechanism remains unknown. Here, we measured multi-omics data in the liver of wild-type and leptin-deficient obese (ob/ob) mice at ad libitum feeding and constructed a differential regulatory trans-omic network of metabolic reactions. We compared the trans-omic network at feeding with that at 16 h fasting constructed in our previous study. Intermediate metabolites in glycolytic and nucleotide metabolism decreased in ob/ob mice at feeding but increased at fasting. Allosteric regulation reversely shifted between feeding and fasting, generally showing activation at feeding while inhibition at fasting in ob/ob mice. Transcriptional regulation was similar between feeding and fasting, generally showing inhibiting transcription factor regulations and activating enzyme protein regulations in ob/ob mice. The opposite metabolic dysregulation between feeding and fasting characterizes breakdown of metabolic homeostasis associated with obesity.

Cardiorespiratory fitness mediates cortisol and lactate responses to winter and summer marches

Background

The influence of homeostatically regulated physiological processes, including cardiorespiratory fitness (VO2max), on the response to physical stressors such as acclimatisation and marching, remains understudied. We aimed to investigate the effects of summer and winter acclimatisation and marching on cortisol levels and blood lactate, to gain insight into the role of these physiological processes in the stress response.

Methods

Two groups of young Europeans, classified as poor (PCF; n=9) and good physical condition (GCF; n=21), based on a VO2MAX threshold of 40 mL O2/ kg/min, underwent 2-h March (6-7 km/h) in winter (5˚C) and summer (32˚C). Commercial tests, UniCel DxI Access Cortisol assay and EKF Biosen Clinic/GP assay were used for cortisol and lactate blood measurements (morning samples and those taken immediately after marches), respectively.

Targeting the Metabolic Paradigms in Cancer and Diabetes

Dysregulated metabolic dynamics are evident in both cancer and diabetes, with metabolic alterations representing a facet of the myriad changes observed in these conditions. This review delves into the commonalities in metabolism between cancer and type 2 diabetes (T2D), focusing specifically on the contrasting roles of oxidative phosphorylation (OXPHOS) and glycolysis as primary energy-generating pathways within cells. Building on earlier research, we explore how a shift towards one pathway over the other serves as a foundational aspect in the development of cancer and T2D. Unlike previous reviews, we posit that this shift may occur in seemingly opposing yet complementary directions, akin to the Yin and Yang concept. These metabolic fluctuations reveal an intricate network of underlying defective signaling pathways, orchestrating the pathogenesis and progression of each disease. The Warburg phenomenon, characterized by the prevalence of aerobic glycolysis over minimal to no OXPHOS, emerges as the predominant metabolic phenotype in cancer. Conversely, in T2D, the prevailing metabolic paradigm has traditionally been perceived in terms of discrete irregularities rather than an OXPHOS-to-glycolysis shift. Throughout T2D pathogenesis, OXPHOS remains consistently heightened due to chronic hyperglycemia or hyperinsulinemia. In advanced insulin resistance and T2D, the metabolic landscape becomes more complex, featuring differential tissue-specific alterations that affect OXPHOS. Recent findings suggest that addressing the metabolic imbalance in both cancer and diabetes could offer an effective treatment strategy. Numerous pharmaceutical and nutritional modalities exhibiting therapeutic effects in both conditions ultimately modulate the OXPHOS-glycolysis axis. Noteworthy nutritional adjuncts, such as alpha-lipoic acid, flavonoids, and glutamine, demonstrate the ability to reprogram metabolism, exerting anti-tumor and anti-diabetic effects. Similarly, pharmacological agents like metformin exhibit therapeutic efficacy in both T2D and cancer. This review discusses the molecular mechanisms underlying these metabolic shifts and explores promising therapeutic strategies aimed at reversing the metabolic imbalance in both disease scenarios.

Hexokinase-linked glycolytic overload and unscheduled glycolysis in hyperglycemia-induced pathogenesis of insulin resistance, beta-cell glucotoxicity, and diabetic vascular complications

Hyperglycemia is a risk factor for the development of insulin resistance, beta-cell glucotoxicity, and vascular complications of diabetes. We propose the hypothesis, hexokinase-linked glycolytic overload and unscheduled glycolysis, in explanation. Hexokinases (HKs) catalyze the first step of glucose metabolism. Increased flux of glucose metabolism through glycolysis gated by HKs, when occurring without concomitant increased activity of glycolytic enzymes-unscheduled glycolysis-produces increased levels of glycolytic intermediates with overspill into effector pathways of cell dysfunction and pathogenesis. HK1 is saturated with glucose in euglycemia and, where it is the major HK, provides for basal glycolytic flux without glycolytic overload. HK2 has similar saturation characteristics, except that, in persistent hyperglycemia, it is stabilized to proteolysis by high intracellular glucose concentration, increasing HK activity and initiating glycolytic overload and unscheduled glycolysis. This drives the development of vascular complications of diabetes. Similar HK2-linked unscheduled glycolysis in skeletal muscle and adipose tissue in impaired fasting glucose drives the development of peripheral insulin resistance. Glucokinase (GCK or HK4)-linked glycolytic overload and unscheduled glycolysis occurs in persistent hyperglycemia in hepatocytes and beta-cells, contributing to hepatic insulin resistance and beta-cell glucotoxicity, leading to the development of type 2 diabetes. Downstream effector pathways of HK-linked unscheduled glycolysis are mitochondrial dysfunction and increased reactive oxygen species (ROS) formation; activation of hexosamine, protein kinase c, and dicarbonyl stress pathways; and increased Mlx/Mondo A signaling. Mitochondrial dysfunction and increased ROS was proposed as the initiator of metabolic dysfunction in hyperglycemia, but it is rather one of the multiple downstream effector pathways. Correction of HK2 dysregulation is proposed as a novel therapeutic target. Pharmacotherapy addressing it corrected insulin resistance in overweight and obese subjects in clinical trial. Overall, the damaging effects of hyperglycemia are a consequence of HK-gated increased flux of glucose metabolism without increased glycolytic enzyme activities to accommodate it.

Diet-induced glial insulin resistance impairs the clearance of neuronal debris in Drosophila brain

Obesity significantly increases the risk of developing neurodegenerative disorders, yet the precise mechanisms underlying this connection remain unclear. Defects in glial phagocytic function are a key feature of neurodegenerative disorders, as delayed clearance of neuronal debris can result in inflammation, neuronal death, and poor nervous system recovery. Mounting evidence indicates that glial function can affect feeding behavior, weight, and systemic metabolism, suggesting that diet may play a role in regulating glial function. While it is appreciated that glial cells are insulin sensitive, whether obesogenic diets can induce glial insulin resistance and thereby impair glial phagocytic function remains unknown. Here, using a Drosophila model, we show that a chronic obesogenic diet induces glial insulin resistance and impairs the clearance of neuronal debris. Specifically, obesogenic diet exposure down-regulates the basal and injury-induced expression of the glia-associated phagocytic receptor, Draper. Constitutive activation of systemic insulin release from Drosophila insulin-producing cells (IPCs) mimics the effect of diet-induced obesity on glial Draper expression. In contrast, genetically attenuating systemic insulin release from the IPCs rescues diet-induced glial insulin resistance and Draper expression. Significantly, we show that genetically stimulating phosphoinositide 3-kinase (Pi3k), a downstream effector of insulin receptor (IR) signaling, rescues high-sugar diet (HSD)-induced glial defects. Hence, we establish that obesogenic diets impair glial phagocytic function and delays the clearance of neuronal debris.

Integration of metabolic flux with hepatic glucagon signaling and gene expression profiles in the conscious dog

Glucagon rapidly and profoundly simulates hepatic glucose production (HGP), but for reasons which are unclear, this effect normally wanes after a few hours, despite sustained plasma glucagon levels. This study characterized the time course and relevance (to metabolic flux) of glucagon mediated molecular events in the livers of conscious dogs. Glucagon was either infused into the hepato-portal vein at a 6-fold basal rate in the presence of somatostatin and basal insulin, or it was maintained at a basal level in control studies. In one control group glucose remained at basal while in the other glucose was infused to match the hyperglycemia that occurred in the hyperglucagonemic group. Elevated glucagon caused a rapid (30 min) but only partially sustained increase in hepatic cAMP over 4h, a continued elevation in G6P, and activation and deactivation of glycogen phosphorylase and synthase activities, respectively. Net hepatic glycogenolysis and HGP increased rapidly, peaking at 30 min, then returned to baseline over the next 3h (although glucagons stimulatory effect on HGP was sustained relative to the hyperglycemic control group). Hepatic gluconeogenic flux did not increase due to lack of glucagon effect on substrate supply to the liver. Global gene expression profiling highlighted glucagon-regulated activation of genes involved in cellular respiration, metabolic processes, and signaling, and downregulation of genes involved in extracellular matrix assembly and development.

Diet-Induced Glial Insulin Resistance Impairs The Clearance Of Neuronal Debris

Obesity significantly increases the risk of developing neurodegenerative disorders, yet the precise mechanisms underlying this connection remain unclear. Defects in glial phagocytic function are a key feature of neurodegenerative disorders, as delayed clearance of neuronal debris can result in inflammation, neuronal death, and poor nervous system recovery. Mounting evidence indicates that glial function can affect feeding behavior, weight, and systemic metabolism, suggesting that diet may play a role in regulating glial function. While it is appreciated that glial cells are insulin sensitive, whether obesogenic diets can induce glial insulin resistance and thereby impair glial phagocytic function remains unknown. Here, using a Drosophila model, we show that a chronic obesogenic diet induces glial insulin resistance and impairs the clearance of neuronal debris. Specifically, obesogenic diet exposure downregulates the basal and injury-induced expression of the glia-associated phagocytic receptor, Draper. Constitutive activation of systemic insulin release from Drosophila Insulin-producing cells (IPCs) mimics the effect of diet-induced obesity on glial draper expression. In contrast, genetically attenuating systemic insulin release from the IPCs rescues diet-induced glial insulin resistance and draper expression. Significantly, we show that genetically stimulating Phosphoinositide 3-kinase (PI3K), a downstream effector of Insulin receptor signaling, rescues HSD-induced glial defects. Hence, we establish that obesogenic diets impair glial phagocytic function and delays the clearance of neuronal debris.

Optogenetic decoding of Akt2-regulated metabolic signaling pathways in skeletal muscle cells using transomics analysis

Insulin regulates various cellular metabolic processes by activating specific isoforms of the Akt family of kinases. Here, we elucidated metabolic pathways that are regulated in an Akt2-dependent manner. We constructed a transomics network by quantifying phosphorylated Akt substrates, metabolites, and transcripts in C2C12 skeletal muscle cells with acute, optogenetically induced activation of Akt2. We found that Akt2-specific activation predominantly affected Akt substrate phosphorylation and metabolite regulation rather than transcript regulation. The transomics network revealed that Akt2 regulated the lower glycolysis pathway and nucleotide metabolism and cooperated with Akt2-independent signaling to promote the rate-limiting steps in these processes, such as the first step of glycolysis, glucose uptake, and the activation of the pyrimidine metabolic enzyme CAD. Together, our findings reveal the mechanism of Akt2-dependent metabolic pathway regulation, paving the way for Akt2-targeting therapeutics in diabetes and metabolic disorders.

Xanthosine, a purine glycoside mediates hepatic glucose homeostasis through inhibition of gluconeogenesis and activation of glycogenesis via regulating the AMPK/ FoxO1/AKT/GSK3β signaling cascade

Type 2 Diabetes Mellitus (T2DM) is characterized by hepatic insulin resistance, which results in increased glucose production and reduced glycogen storage in the liver. There is no previous study in the literature that has explored the role of Xanthosine in hepatic insulin resistance. Moreover, mechanistic explanation for the beneficial effects of Xanthosine in lowering glucose production in diabetes is yet to be determined. This study for the first time investigated the beneficial effects of Tribulus terrestris (TT) and its active constituent, Xanthosine on gluconeogenesis and glycogenesis in Free Fatty Acid (FFA)-induced CC1 hepatocytes and streptozotocin (STZ)-induced Wistar rats. Xanthosine enhanced glucose uptake and decreased glucose production through phosphorylation of AMP-activated protein kinase (AMPK) and forkhead box transcription factor O1 (FoxO1), and downregulation of two rate limiting enzymes of gluconeogenesis, phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase (G6Pase) expression in FFA-induced CC1 cells. Xanthosine also prevented FFA-induced decreases in the phosphorylation of AKT/Protein kinase B, glycogen synthase kinase-3β (GSK3β), and increased glycogen synthase (GS) phosphorylation to increase the glycogen content in the hepatocytes. Moreover, in STZ-induced diabetic rats, oral administration of TT n-butanol fraction (TTBF) enriched with compound Xanthosine (10, 50 & 100 mg/kg body weight) improved insulin sensitivity, reduced fasting blood glucose levels, improved glucose homeostasis by reducing gluconeogenesis via AMPK/FoxO1-mediated PEPCK and G6Pase down-regulation and increasing glycogenesis via AKT/GSK3β-mediated GS activation. Overall, Xanthosine may be developed further for treating insulin resistance and hyperglycemia in T2DM.

Rate thresholds in cell signaling have functional and phenotypic consequences in non-linear time-dependent environments

All cells employ signal transduction pathways to respond to physiologically relevant extracellular cytokines, stressors, nutrient levels, hormones, morphogens, and other stimuli that vary in concentration and rate in healthy and diseased states. A central unsolved fundamental question in cell signaling is whether and how cells sense and integrate information conveyed by changes in the rate of extracellular stimuli concentrations, in addition to the absolute difference in concentration. We propose that different environmental changes over time influence cell behavior in addition to different signaling molecules or different genetic backgrounds. However, most current biomedical research focuses on acute environmental changes and does not consider how cells respond to environments that change slowly over time. As an example of such environmental change, we review cell sensitivity to environmental rate changes, including the novel mechanism of rate threshold. A rate threshold is defined as a threshold in the rate of change in the environment in which a rate value below the threshold does not activate signaling and a rate value above the threshold leads to signal activation. We reviewed p38/Hog1 osmotic stress signaling in yeast, chemotaxis and stress response in bacteria, cyclic adenosine monophosphate signaling in Amoebae, growth factors signaling in mammalian cells, morphogen dynamics during development, temporal dynamics of glucose and insulin signaling, and spatio-temproral stressors in the kidney. These reviewed examples from the literature indicate that rate thresholds are widespread and an underappreciated fundamental property of cell signaling. Finally, by studying cells in non-linear environments, we outline future directions to understand cell physiology better in normal and pathophysiological conditions.

Integration of rhythmic metabolome and transcriptome provides insights into the transmission of rhythmic fluctuations and temporal diversity of metabolism in rice

Various aspects of the organisms adapt to cyclically changing environmental conditions via transcriptional regulation. However, the role of rhythmicity in altering the global aspects of metabolism is poorly characterized. Here, we subjected four rice (Oryza sativa) varieties to a range of metabolic profiles and RNA-seq to investigate the temporal relationships of rhythm between transcription and metabolism. More than 40% of the rhythmic genes and a quarter of metabolites conservatively oscillated across four rice accessions. Compared with the metabolome, the transcriptome was more strongly regulated by rhythm; however, the rhythm of metabolites had an obvious opposite trend between day and night. Through association analysis, the time delay of rhythmic transmission from the transcript to the metabolite level was ∼4 h under long-day conditions, although the transmission was nearly synchronous for carbohydrate and nucleotide metabolism. The rhythmic accumulation of metabolites maintained highly coordinated temporal relationships in the metabolic network, whereas the correlation of some rhythmic metabolites, such as branched-chain amino acids (BCAAs), was significantly different intervariety. We further demonstrated that the cumulative diversity of BCAAs was due to the differential expression of branched-chain aminotransferase 2 at dawn. Our research reveals the flexible pattern of rice metabolic rhythm existing with conservation and diversity.

In vivo transomic analyses of glucose-responsive metabolism in skeletal muscle reveal core differences between the healthy and obese states

Metabolic regulation in skeletal muscle is essential for blood glucose homeostasis. Obesity causes insulin resistance in skeletal muscle, leading to hyperglycemia and type 2 diabetes. In this study, we performed multiomic analysis of the skeletal muscle of wild-type (WT) and leptin-deficient obese (ob/ob) mice, and constructed regulatory transomic networks for metabolism after oral glucose administration. Our network revealed that metabolic regulation by glucose-responsive metabolites had a major effect on WT mice, especially carbohydrate metabolic pathways. By contrast, in ob/ob mice, much of the metabolic regulation by glucose-responsive metabolites was lost and metabolic regulation by glucose-responsive genes was largely increased, especially in carbohydrate and lipid metabolic pathways. We present some characteristic metabolic regulatory pathways found in central carbon, branched amino acids, and ketone body metabolism. Our transomic analysis will provide insights into how skeletal muscle responds to changes in blood glucose and how it fails to respond in obesity.

Trans-omics analysis of insulin action reveals a cell growth subnetwork which co-regulates anabolic processes

Insulin signaling promotes anabolic metabolism to regulate cell growth through multi-omic interactions. To obtain a comprehensive view of the cellular responses to insulin, we constructed a trans-omic network of insulin action in Drosophila cells that involves the integration of multi-omic data sets. In this network, 14 transcription factors, including Myc, coordinately upregulate the gene expression of anabolic processes such as nucleotide synthesis, transcription, and translation, consistent with decreases in metabolites such as nucleotide triphosphates and proteinogenic amino acids required for transcription and translation. Next, as cell growth is required for cell proliferation and insulin can stimulate proliferation in a context-dependent manner, we integrated the trans-omic network with results from a CRISPR functional screen for cell proliferation. This analysis validates the role of a Myc-mediated subnetwork that coordinates the activation of genes involved in anabolic processes required for cell growth.

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A trans-omic network of insulin action in Drosophila cells was constructed

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Insulin co-regulates various anabolic processes in a time-dependent manner

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The trans-omic network and a CRISPR screen for cell proliferation were integrated

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A Myc-mediated subnetwork promoting anabolic processes is required for cell growth

Impact of Influenza A Virus Infection on Growth and Metabolism of Suspension MDCK Cells Using a Dynamic Model

Cell cultured-based influenza virus production is a viable option for vaccine manufacturing. In order to achieve a high concentration of viable cells, is requirement to have not only optimal process conditions, but also an active metabolism capable of intracellular synthesis of viral components. Experimental metabolic data collected in such processes are complex and difficult to interpret, for which mathematical models are an appropriate way to simulate and analyze the complex and dynamic interaction between the virus and its host cell. A dynamic model with 35 states was developed in this study to describe growth, metabolism, and influenza A virus production in shake flask cultivations of suspension Madin-Darby Canine Kidney (MDCK) cells. It considers cell growth (concentration of viable cells, mean cell diameters, volume of viable cells), concentrations of key metabolites both at the intracellular and extracellular level and virus titers. Using one set of parameters, the model accurately simulates the dynamics of mock-infected cells and correctly predicts the overall dynamics of virus-infected cells for up to 60 h post infection (hpi). The model clearly suggests that most changes observed after infection are related to cessation of cell growth and the subsequent transition to apoptosis and cell death. However, predictions do not cover late phases of infection, particularly for the extracellular concentrations of glutamate and ammonium after about 12 hpi. Results obtained from additional in silico studies performed indicated that amino acid degradation by extracellular enzymes resulting from cell lysis during late infection stages may contribute to this observed discrepancy.

Hexokinase-2-Linked Glycolytic Overload and Unscheduled Glycolysis-Driver of Insulin Resistance and Development of Vascular Complications of Diabetes

The recent discovery of the glucose-induced stabilization of hexokinase-2 (HK2) to proteolysis in cell dysfunction in model hyperglycemia has revealed a likely key initiating factor contributing to the development of insulin resistance and vascular complications in diabetes. Consequently, the increased flux of glucose metabolism without a change in the expression and activity of glycolytic enzymes produces a wave of increased glycolytic intermediates driving mitochondrial dysfunction and increased reactive oxygen species (ROS) formation, the activation of hexosamine and protein kinase C pathways, the increased formation of methylglyoxal-producing dicarbonyl stress, and the activation of the unfolded protein response. This is called HK2-linked glycolytic overload and unscheduled glycolysis. The conditions required to sustain this are GLUT1 and/or GLUT3 glucose uptake and the expression of HK2. A metabolic biomarker of its occurrence is the abnormally increased deposition of glycogen, which is produced by metabolic channeling when HK2 becomes detached from mitochondria. These conditions and metabolic consequences are found in the vasculature, kidneys, retina, peripheral nerves, and early-stage embryo development in diabetes and likely sustain the development of diabetic vascular complications and embryopathy. In insulin resistance, HK2-linked unscheduled glycolysis may also be established in skeletal muscle and adipose tissue. This may explain the increased glucose disposal by skeletal uptake in the fasting phase in patients with type 2 diabetes mellitus, compared to healthy controls, and the presence of insulin resistance in patients with type 1 diabetes mellitus. Importantly, glyoxalase 1 inducer—trans-resveratrol and hesperetin in combination (tRES-HESP)—corrected HK2-linked glycolytic overload and unscheduled glycolysis and reversed insulin resistance and improved vascular inflammation in overweight and obese subjects in clinical trial. Further studies are now required to evaluate tRES-HESP for the prevention and reversal of early-stage type 2 diabetes and for the treatment of the vascular complications of diabetes.

Elucidating the Glucokinase Activating Potentials of Naturally Occurring Prenylated Flavonoids: An Explicit Computational Approach

Glucokinase activators are considered as new therapeutic arsenals that bind to the allosteric activator sites of glucokinase enzymes, thereby maximizing its catalytic rate and increasing its affinity to glucose. This study was designed to identify potent glucokinase activators from prenylated flavonoids isolated from medicinal plants using molecular docking, molecular dynamics simulation, density functional theory, and ADMET analysis. Virtual screening was carried out on glucokinase enzymes using 221 naturally occurring prenylated flavonoids, followed by molecular dynamics simulation (100 ns), density functional theory (B3LYP model), and ADMET (admeSar 2 online server) studies. The result obtained from the virtual screening with the glucokinase revealed arcommunol B (−10.1 kcal/mol), kuwanon S (−9.6 kcal/mol), manuifolin H (−9.5 kcal/mol), and kuwanon F (−9.4 kcal/mol) as the top-ranked molecules. Additionally, the molecular dynamics simulation and MM/GBSA calculations showed that the hit molecules were stable at the active site of the glucokinase enzyme. Furthermore, the DFT and ADMET studies revealed the hit molecules as potential glucokinase activators and drug-like candidates. Our findings suggested further evaluation of the top-ranked prenylated flavonoids for their in vitro and in vivo glucokinase activating potentials.

Quantitative Proteomics and Phosphoproteomics Reveal TNF-α-Mediated Protein Functions in Hepatocytes

Increased secretion of proinflammatory cytokines, such as tumor necrosis factor-alpha (TNFα), is often associated with adipose tissue dysregulation, which often accompanies obesity. High levels of TNFα have been linked to the development of insulin resistance in several tissues and organs, including skeletal muscle and the liver. In this study, we examined the complex regulatory roles of TNFα in murine hepatocytes utilizing a combination of global proteomic and phosphoproteomic analyses. Our results show that TNFα promotes extensive changes not only of protein levels, but also the dynamics of their downstream phosphorylation signaling. We provide evidence that TNFα induces DNA replication and promotes G1/S transition through activation of the MAPK pathway. Our data also highlight several other novel proteins, many of which are regulated by phosphorylation and play a role in the progression and development of insulin resistance in hepatocytes.

Evaluation of Anti-Obesity Activity of an Herbal Formulation (F2) in DIO Mice Model and Validation of UPLC-DAD Method for Quality Control

Obesity is considered a chronic metabolic disorder that can be associated with multiple medical complications. Currently, there is no or limited curative therapy for obesity. This study focused on the assessment of anti-obesity activity and UPLC standardization of a polyherbal formulation (F2). An anti-obesity activity was investigated using the diet-induced obese (DIO) mice model, where obesity was developed in C57BL/6J mice by providing a high-fat diet (HFD) for five weeks without treating drugs. After the successful development of obesity, the obese mice were treated with F2 for seven weeks with continuing HFD feeding. The major obesity-related parameters such as body weight gain, food efficiency ratio, serum lipid profile, and white adipose tissue (WAT) mass were found to be significantly reduced in F2 treated obese mice. These results were supported by the down-regulation of specific adipogenic transcription factors (PPARγ, SREBP-1c, and ap2) in epididymal WAT. Histological evaluation of liver and WAT also revealed reduced fat deposition in the tissues by F2 compared to the HFD control group. The overall observations indicated that the F2 exhibited pronounced obesity-controlling activity through the inhibition of adipocyte differentiation and triglyceride accumulation in the tissues, and serum lipid depletion. In addition, F2 ameliorated obesity-induced insulin resistance. Furthermore, the UPLC-DAD method for quality control of F2 was validated and standardized using five reference compounds: astragalin, ellagic acid, fisetin, fustin, and sulfuretin.

NFAT indicates nucleocytoplasmic damped oscillation via its feedback modulator

Cell signaling and the following gene regulation are tightly regulated to keep homeostasis. NF-κB is a famous key transcription factor for inflammatory cell regulations that obtain a closed feedback loop with IκB. Similarly, we show here, NFAT is also tightly regulated via its downstream target, down syndrome critical region (DSCR)-1. In primary cultured endothelium, either shear stress or VEGF treatment revealed quick NFAT1 nuclear localization following the DSCR-1 transactivation, which in turn induced NFAT1 cytoplasm sequestration. Interestingly, both NFAT and DSCR-1 can be competitive substrates for calcineurin phosphatase and DSCR-1 is known to unstable protein, which caused NFAT1-nucleocytoplasmic damped oscillation via sustained shear stress or VEGF stimulation in endothelial cell (EC)s. To understand the molecular mechanism underlying the NFAT1 oscillation, we built a mathematical model of spatiotemporal regulation of NFAT1 combined with calcineurin and DSCR-1. Theoretically, manipulation of DSCR-1 expression in simulation predicted that DSCR-1 reduction would cause nuclear retention of dephosphorylated NFAT1 and disappearance of NFAT1 oscillation. To confirm this in ECs, DSCR-1 knockdown analysis was performed. DSCR-1 reduction indeed increased dephosphorylated NFAT1 in both the nucleus and cytoplasm, which eventually led to nuclear retention of NFAT1. Taken together, these studies suggest that DSCR-1 is a responsible critical factor for NFAT1 nucleocytoplasmic oscillation in shear stress or VEGF treated ECs. Our mathematical model successfully reproduced the experimental observations of NFAT1 dynamics. Combined mathematical and experimental approaches would provide a quantitative understanding way for the spatiotemporal NFAT1 feedback system.

TRPV1 Activation by Capsaicin Mediates Glucose Oxidation and ATP Production Independent of Insulin Signalling in Mouse Skeletal Muscle Cells

BACKGROUND

Insulin resistance (IR), a key characteristic of type 2 diabetes (T2DM), is manifested by decreased insulin-stimulated glucose transport in target tissues. Emerging research has highlighted transient receptor potential cation channel subfamily V member (TRPV1) activation by capsaicin as a potential therapeutic target for these conditions. However, there are limited data on the effects of capsaicin on cell signalling molecules involved in glucose uptake.

METHODS

C2C12 cells were cultured and differentiated to acquire the myotube phenotype. The activation status of signalling molecules involved in glucose metabolism, including 5' adenosine monophosphate-activated protein kinase (AMPK), calcium/calmodulin-dependent protein kinase 2 (CAMKK2), extracellular signal-regulated protein kinases 1 and 2 (ERK1/2), protein kinase B (AKT), and src homology phosphatase 2 (SHP2), was examined. Finally, activation of CAMKK2 and AMPK, and glucose oxidation and ATP levels were measured in capsaicin-treated cells in the presence or absence of TRPV1 antagonist (SB-452533).

RESULTS

Capsaicin activated cell signalling molecules including CAMKK2 and AMPK leading to increased glucose oxidation and ATP generation independent of insulin in the differentiated C2C12 cells. Pharmacological inhibition of TRPV1 diminished the activation of CAMKK2 and AMPK as well as glucose oxidation and ATP production. Moreover, we observed an inhibitory effect of capsaicin in the phosphorylation of ERK1/2 in the mouse myotubes.

CONCLUSION

Our data show that capsaicin-mediated stimulation of TRPV1 in differentiated C2C12 cells leads to activation of CAMKK2 and AMPK, and increased glucose oxidation which is concomitant with an elevation in intracellular ATP level. Further studies of the effect of TRPV1 channel activation by capsaicin on glucose metabolism could provide novel therapeutic utility for the management of IR and T2DM.

Effect of Caralluma tuberculata on regulation of carbohydrate metabolizing genes in alloxan-induced rats

ETHNOPHARMACOLOGICAL RELEVANCE

Caralluma tuberculata (C. tuberculata) has traditionally been used in Pakistan and other parts of the world as a folk treatment for diabetes mellitus. A few studies indicated its antihyperglycemic effect, however, the mystery remained unfolded as how did it modify the pathophysiological condition.

AIM OF STUDY

Hence, this study aimed to explore underlying mechanism(s) for its hypoglycemic activity at biochemical and molecular levels.

MATERIALS AND METHODS

Methanol extract (ME) of C. tuberculata as well as its hexane (HF) and aqueous (AF) fractions were explored for their effect on total glycogen in liver and skeletal muscle of alloxan-induced rats by spectroscopy. Moreover, the expression of genes related to hepatic carbohydrate metabolizing enzymes was quantified. At molecular level, mRNA expression of glucose transporter 2 (GLUT-2), glycogen synthase (GS), glucokinase (GK), hexokinase 1 (HK-1), pyruvate kinase (PK), glucose 6 phosphate dehydrogenase (G-6-PDH), pyruvate carboxylase (PC), phosphoenolpyruvate carboxykinase (PEPCK) and glucose 6 phosphatase (G-6-Pase) was determined by using quantitative real time polymerase chain reaction (qRT-PCR) after administration of ME (350 mg), HF(3 mg), AF (10 mg) and metformin (500 mg). The doses were administered twice daily according to per kg of body weight.

RESULTS

A significant reduction in hepatic and skeletal muscle glycogen content was exhibited. The data of qRT-PCR revealed that gene's expression of GLUT-2 was significantly decreased after treatment with ME and HF, whilst it was unaltered by AF, however, a significant decrease was observed in genes corresponding to GS, GK and HK-1 after treatment with ME. Similarly, there was a significant decrease in expression of genes corresponding to GS, GK and HK-1 following treatment with HF. Surprisingly, post-treatment with AF didn't modify the gene's expression of GS and GK, whilst it caused a profound decrease in expression of HK-1 gene. Contrarily, the expression of gene related to PK was significantly up-regulated post-administration with ME, HF and AF. The expression levels of G-6-PDH, however, remained unaltered after treatment with the experimental extract and fractions of the plant. In addition, HF and AF did not cause any modification in PEPCK, whereas ME caused a significant down-regulation of the gene. Treatment with all the extract and fractions of the plant caused a substantial decrease in the gene's expression of PC, while there was a significant increase in the expression of gene related to G-6-Pase.

CONCLUSION

The three experimental extract and fractions caused a substantial decrease in glycogen content in liver and skeletal muscle tissues. The analysis by qRT-PCR showed that glucose transport via GLUT-2 was profoundly declined by ME and HF. The expression of genes related to various metabolic pathways involved in metabolism of carbohydrate in hepatocytes revealed explicitly that the ME, HF and AF decreased the phenomena of glycogenesis and gluconeogenesis. Contrarily, all the extract and fractions of the plant activated glycogenolysis and glycolysis but did not modify the pentose phosphate shunt pathway.

Potentiation of incretin hormones and modulation of metabolic enzymes as possible mechanisms behind the insulin sensitizing effects of cabbage-metformin treatment

In our study, we treated high fructose diet-induced insulin resistance in rats with any of metformin, cabbage (80%w/w) or combined metformin and cabbage (MetCabb), and observed the activities of glycolysis and gluconeogenesis regulatory enzymes, incretin hormones and other hormones affecting glucose homeostasis. Comparisons were made with normoglycemic noninsulin resistance rats (control) and insulin-resistant untreated rats (INres). Baseline analysis showing elevated fasting blood sugar (>250 mg/dl), insulin (>25 µIU/ml) and HOMA-IR (>10) satisfied the criteria for recruitment into the insulin-resistant groups. Treatment lasted for 12 weeks. HOMA-IR values significantly (P < 0.05) decreased from 24.7 to 5.5 and 10.6 respectively with MetCabb treatment. MetCabb normalized HOMA-IR values and mean β-cell responsiveness of the INres. Cabbage and metCabb normalized the leptin levels relative to control. The mean fasting blood sugar, insulin, and c-peptide levels with MetCabb treatment reverted to control levels. We found a strong positive linear correlation between the glucagon levels (r = 0.9145) and increasing HOMA-IR values while both incretin hormones; GLP-1 and GIP negatively regressed (r = -0.8084 and -0.8488). MetCab treatment produced comparable values of GLP-1 and GIP to the control. A strong positive correlation was found between the HOMA-IR values and the PEPCK (r = 0.9065), F-1,6-BPase (r = 0.7951), and G-6-Pase (r = 0.7893). The hexokinase (r = -0.807), PFK (r = -0.9151), and PK (r = -0.7448) levels regressed as HOMA-IR values increased. The glycolytic and gluconeogenic enzymes except PEPCK reverted to control levels with MetCabb treatment. Combination of metformin and cabbage was more effective than individual treatments.

Intestinal protection by proanthocyanidins involves anti-oxidative and anti-inflammatory actions in association with an improvement of insulin sensitivity, lipid and glucose homeostasis

Recent advances have added another dimension to the complexity of cardiometabolic disorders (CMD) by directly implicating the gastrointestinal tract as a key player. In fact, multiple factors could interfere with intestinal homeostasis and elicit extra-intestinal CMD. As oxidative stress (OxS), inflammation, insulin resistance and lipid abnormalities are among the most disruptive events, the aim of the present study is to explore whether proanthocyanidins (PACs) exert protective effects against these disorders. To this end, fully differentiated intestinal Caco-2/15 cells were pre-incubated with PACs with and without the pro-oxidant and pro-inflammatory iron/ascorbate (Fe/Asc). PACs significantly reduce malondialdehyde, a biomarker of lipid peroxidation, and raise antioxidant SOD2 and GPx via the increase of NRF2/Keap1 ratio. Likewise, PACs decrease the inflammatory agents TNFα and COX2 through abrogation of NF-κB. Moreover, according to crucial biomarkers, PACs result in lipid homeostasis improvement as reflected by enhanced fatty acid β-oxidation, diminished lipogenesis, and lowered gluconeogenesis as a result of PPARα, γ and SREBP1c modulation. Since these metabolic routes are mainly regulated by insulin sensitivity, we have examined the insulin signaling pathway and found an upregulation of phosphoPI3K/Akt and downregulation of p38-MAPK expressions, indicating beneficial effects in response to PACs. Taken together, PACs display the potential to counterbalance OxS and inflammation in Fe/Asc-exposed intestinal cells, in association with an improvement of insulin sensitivity, which ameliorates lipid and glucose homeostasis.

Transomics analysis reveals allosteric and gene regulation axes for altered hepatic glucose-responsive metabolism in obesity

Impaired glucose tolerance associated with obesity causes postprandial hyperglycemia and can lead to type 2 diabetes. To study the differences in liver metabolism in healthy and obese states, we constructed and analyzed transomics glucose-responsive metabolic networks with layers for metabolites, expression data for metabolic enzyme genes, transcription factors, and insulin signaling proteins from the livers of healthy and obese mice. We integrated multiomics time course data from wild-type and leptin-deficient obese (ob/ob) mice after orally administered glucose. In wild-type mice, metabolic reactions were rapidly regulated within 10 min of oral glucose administration by glucose-responsive metabolites, which functioned as allosteric regulators and substrates of metabolic enzymes, and by Akt-induced changes in the expression of glucose-responsive genes encoding metabolic enzymes. In ob/ob mice, the majority of rapid regulation by glucose-responsive metabolites was absent. Instead, glucose administration produced slow changes in the expression of carbohydrate, lipid, and amino acid metabolic enzyme-encoding genes to alter metabolic reactions on a time scale of hours. Few regulatory events occurred in both healthy and obese mice. Thus, our transomics network analysis revealed that regulation of glucose-responsive liver metabolism is mediated through different mechanisms in healthy and obese states. Rapid changes in allosteric regulators and substrates and in gene expression dominate the healthy state, whereas slow changes in gene expression dominate the obese state.

Insulin Promotes Mitochondrial Respiration and Survival through PI3K/AKT/GSK3 Pathway in Human Embryonic Stem Cells

Insulin is an essential growth factor for the survival and self-renewal of human embryonic stem cells (hESCs). Although it is best known as the principal hormone promoting glycolysis in somatic cells, insulin's roles in hESC energy metabolism remain unclear. In this report, we demonstrate that insulin is essential to sustain hESC mitochondrial respiration that is rapidly decreased upon insulin removal. Insulin-dependent mitochondrial respiration is stem cell specific, and mainly relies on pyruvate and glutamine, while glucose suppresses excessive oxidative phosphorylation. Pharmacologic and genetic manipulations reveal that continuous insulin signal sustains mitochondrial respiration through PI3K/AKT activation and downstream GSK3 inhibition. We further show that insulin acts through GSK3 inhibition to suppress caspase activation and rescue cell survival. This study uncovers a critical role of the AKT/GSK3 pathway in the regulation of mitochondrial respiration and cell survival, highlighting insulin as an essential factor for accurate assessment of mitochondrial respiration in hESCs.

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Insulin is continuously required to sustain mitochondrial respiration in hESCs

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Insulin-dependent mitochondrial respiration is substrate specific

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GSK3 is a major regulator of insulin-dependent respiration and cell survival

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Insulin is essential for accurate assessment of mitochondrial respiration in hESCs

Nanoplastics impact the zebrafish (Danio rerio) transcriptome: Associated developmental and neurobehavioral consequences

Microplastics (MPs) are a ubiquitous pollutant detected not only in marine and freshwater bodies, but also in tap and bottled water worldwide. While MPs have been extensively studied, the toxicity of their smaller counterpart, nanoplastics (NPs), is not well documented. Despite likely large-scale human and animal exposure to NPs, the associated health risks remain unclear, especially during early developmental stages. To address this, we investigated the health impacts of exposures to both 50 and 200 nm polystyrene NPs in larval zebrafish. From 6 to 120 h post-fertilization (hpf), developing zebrafish were exposed to a range of fluorescent NPs (10-10,000 parts per billion). Dose-dependent increases in accumulation were identified in exposed larval fish, potentially coinciding with an altered behavioral response as evidenced through swimming hyperactivity. Notably, exposures did not impact mortality, hatching rate, or deformities; however, transcriptomic analysis suggests neurodegeneration and motor dysfunction at both high and low concentrations. Furthermore, results of this study suggest that NPs can accumulate in the tissues of larval zebrafish, alter their transcriptome, and affect behavior and physiology, potentially decreasing organismal fitness in contaminated ecosystems. The uniquely broad scale of this study during a critical window of development provides crucial multidimensional characterization of NP impacts on human and animal health.

A dynamic model linking cell growth to intracellular metabolism and extracellular by-product accumulation

Mathematical modeling of animal cell growth and metabolism is essential for the understanding and improvement of the production of biopharmaceuticals. Models can explain the dynamic behavior of cell growth and product formation, support the identification of the most relevant parameters for process design, and significantly reduce the number of experiments to be performed for process optimization. Few dynamic models have been established that describe both extracellular and intracellular dynamics of growth and metabolism of animal cells. In this study, a model was developed, which comprises a set of 33 ordinary differential equations to describe batch cultivations of suspension AGE1.HN.AAT cells considered for the production of α1-antitrypsin. This model combines a segregated cell growth model with a structured model of intracellular metabolism. Overall, it considers the viable cell concentration, mean cell diameter, viable cell volume, concentration of extracellular substrates, and intracellular concentrations of key metabolites from the central carbon metabolism. Furthermore, the release of metabolic by-products such as lactate and ammonium was estimated directly from the intracellular reactions. Based on the same set of parameters, this model simulates well the dynamics of four independent batch cultivations. Analysis of the simulated intracellular rates revealed at least two distinct cellular physiological states. The first physiological state was characterized by a high glycolytic rate and high lactate production. Whereas the second state was characterized by efficient adenosine triphosphate production, a low glycolytic rate, and reactions of the TCA cycle running in the reverse direction from α-ketoglutarate to citrate. Finally, we show possible applications of the model for cell line engineering and media optimization with two case studies.

Proteomic Analysis of 3T3-L1 Adipocytes Treated with Insulin and TNF-α

Insulin resistance is an indication of early stage Type 2 diabetes (T2D). Insulin resistant adipose tissues contain higher levels of insulin than the physiological level, as well as higher amounts of intracellular tumor necrosis factor-α (TNF-α) and other cytokines. However, the mechanism of insulin resistance remains poorly understood. To better understand the roles played by insulin and TNF-α in insulin resistance, we performed proteomic analysis of differentiated 3T3-L1 adipocytes treated with insulin (Ins), TNF-α (TNF), and both (Ins + TNF). Out of the 693 proteins identified, the abundances of 78 proteins were significantly different (p < 0.05). Carnitine parmitoyltransferase-2 (CPT2), acetyl CoA carboxylase 1 (ACCAC-1), ethylmalonyl CoA decarboxylase (ECHD1), and methylmalonyl CoA isomerase (MCEE), enzymes required for fatty acid β-oxidation and respiratory electron transport, and β-glucuronidase, an enzyme responsible for the breakdown of complex carbohydrates, were down-regulated in all the treatment groups, compared to the control group. In contrast, superoxide dismutase 2 (SOD2), protein disulfide isomerase (PDI), and glutathione reductase, which are the proteins responsible for cytoskeletal structure, protein folding, degradation, and oxidative stress responses, were up-regulated. This suggests higher oxidative stress in cells treated with Ins, TNF, or both. We proposed a conceptual metabolic pathway impacted by the treatments and their possible link to insulin resistance or T2D.

Dynamic modeling of signal transduction by mTOR complexes in cancer

Signal integration has a crucial role in the cell fate decision and dysregulation of the cellular signaling pathways is a primary characteristic of cancer. As a signal integrator, mTOR shows a complex dynamical behavior which determines the cell fate at different cellular processes levels, including cell cycle progression, cell survival, cell death, metabolic reprogramming, and aging. The dynamics of the complex responses to rapamycin in cancer cells have been attributed to its differential time-dependent inhibitory effects on mTORC1 and mTORC2, the two main complexes of mTOR. Two explanations were previously provided for this phenomenon: 1-Rapamycin does not inhibit mTORC2 directly, whereas it prevents mTORC2 formation by sequestering free mTOR protein (Le Chatelier's principle). 2-Components like Phosphatidic Acid (PA) further stabilize mTORC2 compared with mTORC1. To understand the mechanism by which rapamycin differentially inhibits the mTOR complexes in the cancer cells, we present a mathematical model of rapamycin mode of action based on the first explanation, i.e., Le Chatelier's principle. Translating the interactions among components of mTORC1 and mTORC2 into a mathematical model revealed the dynamics of rapamycin action in different doses and time-intervals of rapamycin treatment. This model shows that rapamycin has stronger effects on mTORC1 compared with mTORC2, simply due to its direct interaction with free mTOR and mTORC1, but not mTORC2, without the need to consider other components that might further stabilize mTORC2. Based on our results, even when mTORC2 is less stable compared with mTORC1, it can be less inhibited by rapamycin.

Hexokinase-2 Glycolytic Overload in Diabetes and Ischemia-Reperfusion Injury

Hexokinase-2 (HK2) was recently found to produce increased metabolic flux through glycolysis in hyperglycemia without concurrent transcriptional or other functional regulation. Rather, stabilization to proteolysis by increased glucose substrate binding produced unscheduled increased glucose metabolism in response to high cytosolic glucose concentration. This produces abnormal increases in glycolytic intermediates or glycolytic overload, driving cell dysfunction and vulnerability to the damaging effects of hyperglycemia in diabetes, explaining tissue-specific pathogenesis. Glycolytic overload is also activated in ischemia-reperfusion injury and cell senescence. A further key feature is HK2 displacement from mitochondria by increased glucose-6-phosphate concentration, inducing mitochondrial dysfunction and oxidative stress. This pathogenic mechanism suggested new targets for therapeutics development that gave promising outcomes in initial clinical evaluation.

Atlas of Circadian Metabolism Reveals System-wide Coordination and Communication between Clocks

Metabolic diseases are often characterized by circadian misalignment in different tissues, yet how altered coordination and communication among tissue clocks relate to specific pathogenic mechanisms remains largely unknown. Applying an integrated systems biology approach, we performed 24-hr metabolomics profiling of eight mouse tissues simultaneously. We present a temporal and spatial atlas of circadian metabolism in the context of systemic energy balance and under chronic nutrient stress (high-fat diet [HFD]). Comparative analysis reveals how the repertoires of tissue metabolism are linked and gated to specific temporal windows and how this highly specialized communication and coherence among tissue clocks is rewired by nutrient challenge. Overall, we illustrate how dynamic metabolic relationships can be reconstructed across time and space and how integration of circadian metabolomics data from multiple tissues can improve our understanding of health and disease.

Trans-omic Analysis Reveals Selective Responses to Induced and Basal Insulin across Signaling, Transcriptional, and Metabolic Networks

The concentrations of insulin selectively regulate multiple cellular functions. To understand how insulin concentrations are interpreted by cells, we constructed a trans-omic network of insulin action in FAO hepatoma cells using transcriptomic data, western blotting analysis of signaling proteins, and metabolomic data. By integrating sensitivity into the trans-omic network, we identified the selective trans-omic networks stimulated by high and low doses of insulin, denoted as induced and basal insulin signals, respectively. The induced insulin signal was selectively transmitted through the pathway involving Erk to an increase in the expression of immediate-early and upregulated genes, whereas the basal insulin signal was selectively transmitted through a pathway involving Akt and an increase of Foxo phosphorylation and a reduction of downregulated gene expression. We validated the selective trans-omic network in vivo by analysis of the insulin-clamped rat liver. This integrated analysis enabled molecular insight into how liver cells interpret physiological insulin signals to regulate cellular functions.

In Vivo Decoding Mechanisms of the Temporal Patterns of Blood Insulin by the Insulin-AKT Pathway in the Liver

Cells respond to various extracellular stimuli through a limited number of signaling pathways. One strategy to process such stimuli is to code the information into the temporal patterns of molecules. Although we showed that insulin selectively regulated molecules depending on its temporal patterns using Fao cells, the in vivo mechanism remains unknown. Here, we show how the insulin-AKT pathway processes the information encoded into the temporal patterns of blood insulin. We performed hyperinsulinemic-euglycemic clamp experiments and found that, in the liver, all temporal patterns of insulin are encoded into the insulin receptor, and downstream molecules selectively decode them through AKT. S6K selectively decodes the additional secretion information. G6Pase interprets the basal secretion information through FoxO1, while GSK3β decodes all secretion pattern information. Mathematical modeling revealed the mechanism via differences in network structures and from sensitivity and time constants. Given that almost all hormones exhibit distinct temporal patterns, temporal coding may be a general principle of system homeostasis by hormones.

Increase in hepatic and decrease in peripheral insulin clearance characterize abnormal temporal patterns of serum insulin in diabetic subjects

Insulin plays a central role in glucose homeostasis, and impairment of insulin action causes glucose intolerance and leads to type 2 diabetes mellitus (T2DM). A decrease in the transient peak and sustained increase of circulating insulin following an infusion of glucose accompany T2DM pathogenesis. However, the mechanism underlying this abnormal temporal pattern of circulating insulin concentration remains unknown. Here we show that changes in opposite direction of hepatic and peripheral insulin clearance characterize this abnormal temporal pattern of circulating insulin concentration observed in T2DM. We developed a mathematical model using a hyperglycemic and hyperinsulinemic-euglycemic clamp in 111 subjects, including healthy normoglycemic and diabetic subjects. The hepatic and peripheral insulin clearance significantly increase and decrease, respectively, from healthy to borderline type and T2DM. The increased hepatic insulin clearance reduces the amplitude of circulating insulin concentration, whereas the decreased peripheral insulin clearance changes the temporal patterns of circulating insulin concentration from transient to sustained. These results provide further insight into the pathogenesis of T2DM, and thus may contribute to develop better treatment of this condition.

Type 2 diabetes mellitus (T2DM) is one of the fastest growing public health problems, characterized by chronic hyperglycemia with the failure of glucose homeostasis. Evaluating alteration in biological functions regulating circulating glucose concentration is complicated due to the mutual relation between circulating glucose and insulin. A team led by Wataru Ogawa at Kobe University designed clinical experiments for breaking such feedback relations, and a team led by Shinya Kuroda at University of Tokyo developed mathematical models for specifically quantifying the functions from the clinical data. The estimated model parameters revealed the significant increase in hepatic and decrease in peripheral insulin clearance, which occur before and after insulin delivery into systemic circulation, respectively, from healthy to T2DM subjects. Model analysis suggested these insulin clearances centrally regulate the dynamics of circulating insulin concentration in the glucose-insulin regulatory system.

Modulation of the peripheral blood transcriptome by the ingestion of probiotic yoghurt and acidified milk in healthy, young men

The metabolic health benefits of fermented milks have already been investigated using clinical biomarkers but the development of transcriptomic analytics in blood offers an alternative approach that may help to sensitively characterise such effects. We aimed to assess the effects of probiotic yoghurt intake, compared to non-fermented, acidified milk intake, on clinical biomarkers and gene expression in peripheral blood. To this end, a randomised, crossover study was conducted in fourteen healthy, young men to test the two dairy products. For a subset of seven subjects, RNA sequencing was used to measure gene expression in blood collected during postprandial tests and after two weeks daily intake. We found that the postprandial response in insulin was different for probiotic yoghurt as compared to that of acidified milk. Moreover changes in several clinical biomarkers were associated with changes in the expression of genes representing six metabolic genesets. Assessment of the postprandial effects of each dairy product on gene expression by geneset enrichment analysis revealed significant, similar modulation of inflammatory and glycolytic genes after both probiotic yoghurt and acidified milk intake, although distinct kinetic characteristics of the modulation differentiated the dairy products. The aryl hydrocarbon receptor was a major contributor to the down-regulation of the inflammatory genesets and was also positively associated with changes in circulating insulin at 2h after yoghurt intake (p = 0.05). Daily intake of the dairy products showed little effect on the fasting blood transcriptome. Probiotic yoghurt and acidified milk appear to affect similar gene pathways during the postprandial phase but differences in the timing and the extent of this modulation may lead to different physiological consequences. The functional relevance of these differences in gene expression is supported by their associations with circulating biomarkers.

Multidimensional biochemical information processing of dynamical patterns

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Leptin Stimulates Cellular Glycolysis Through a STAT3 Dependent Mechanism in Tilapia

We assessed if leptin, a cytokine hormone known to enhance energy expenditure by promoting lipid and carbohydrate catabolism in response to physiologic stress, might directly regulate cellular glycolysis. A transcriptomic analysis of prolactin cells in the tilapia (Oreochromis mossambicus) pituitary rostral pars distalis (RPD) revealed that recombinant leptin (rtLep) differentially regulates 1,995 genes, in vitro. Machine learning algorithms and clustering analyses show leptin influences numerous cellular gene networks including metabolism; protein processing, transport, and metabolism; cell cycle and the hypoxia response. Leptin stimulates transcript abundance of the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (gapdh) in a covariate manner to the hypoxic stress gene network. Orthogonal tests confirm that rtLepA dose-dependently increases gapdh gene expression in the RPD along with transcript abundance of 6-phosphofructo-1-kinase (pfk1), the rate limiting glycolytic enzyme. Functional testing demonstrated that leptin stimulates PFK activity and glycolytic output, while Stattic (a STAT3 blocker) was sufficient to suppress these responses, indicating leptin stimulates glycolysis through a STAT3-dependent mechanism. Leptin also stimulated pfk1 gene expression and lactate production in primary hepatocyte incubations in a similar manner to those shown for the pituitary RPD. This work characterizes a critical metabolic action of leptin to directly stimulate glycolysis across tissue types in a teleost model system, and suggest that leptin may promote energy expenditure, in part, by stimulating glycolysis. These data in a teleost fish, suggest that one of leptin's ancient, highly-conserved functions among vertebrates may be stimulation of glycolysis to facilitate the energetic needs associated with various stressors.

Understanding the mTOR signaling pathway via mathematical modeling

The mechanistic target of rapamycin (mTOR) is a central regulatory pathway that integrates a variety of environmental cues to control cellular growth and homeostasis by intricate molecular feedbacks. In spite of extensive knowledge about its components, the molecular understanding of how these function together in space and time remains poor and there is a need for Systems Biology approaches to perform systematic analyses. In this work, we review the recent progress how the combined efforts of mathematical models and quantitative experiments shed new light on our understanding of the mTOR signaling pathway. In particular, we discuss the modeling concepts applied in mTOR signaling, the role of multiple feedbacks and the crosstalk mechanisms of mTOR with other signaling pathways. We also discuss the contribution of principles from information and network theory that have been successfully applied in dissecting design principles of the mTOR signaling network. We finally propose to classify the mTOR models in terms of the time scale and network complexity, and outline the importance of the classification toward the development of highly comprehensive and predictive models. WIREs Syst Biol Med 2017, 9:e1379. doi: 10.1002/wsbm.1379 For further resources related to this article, please visit the WIREs website.

Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data

In recent years, the number of large-scale metabolomics studies on various cellular processes in different organisms has increased drastically. However, it remains a major challenge to perform a systematic identification of mechanistic regulatory events that mediate the observed changes in metabolite levels, due to complex interdependencies within metabolic networks. We present the metabolic network segmentation (MNS) algorithm, a probabilistic graphical modeling approach that enables genome-scale, automated prediction of regulated metabolic reactions from differential or serial metabolomics data. The algorithm sections the metabolic network into modules of metabolites with consistent changes. Metabolic reactions that connect different modules are the most likely sites of metabolic regulation. In contrast to most state-of-the-art methods, the MNS algorithm is independent of arbitrary pathway definitions, and its probabilistic nature facilitates assessments of noisy and incomplete measurements. With serial (i.e., time-resolved) data, the MNS algorithm also indicates the sequential order of metabolic regulation. We demonstrated the power and flexibility of the MNS algorithm with three, realistic case studies with bacterial and human cells. Thus, this approach enables the identification of mechanistic regulatory events from large-scale metabolomics data, and contributes to the understanding of metabolic processes and their interplay with cellular signaling and regulation processes.

Reciprocal crosstalk between metabolism and cellular signaling pathways plays a crucial role in cellular decision-making. In recent years, this premise has motivated several metabolomics studies that aimed to gain a mechanistic understanding of metabolic phenotypes. However, due to complex interactions within metabolic networks, it remains a challenge to infer mechanisms that underlie metabolome changes. We present the metabolic network segmentation approach, a novel method that aimed to identify the sites and sequential order of metabolic regulatory events, based merely on steady state or dynamic metabolomics data. This method employs probabilistic graphical models to partition the entire metabolic network into modules with correlated metabolites. It identifies fractures between modules (i.e., reactions that connect non-correlated metabolites) as sites of regulation. We performed validation and benchmark analyses in hundreds of E. coli knockout mutants deficient in enzymes and transcription factors. Moreover, we verified the capability of our method for identifying the sequential order of metabolic regulatory events by testing it on fibroblasts exposed to oxidative stress. Our metabolic network segmentation algorithm is widely applicable, and thus, it will enhance our mechanistic understanding of metabolic phenotypes and their connections to cellular signaling and regulatory processes.

Model-based control of the temporal patterns of intracellular signaling in silico

The functions of intracellular signal transduction systems are determined by the temporal behavior of intracellular molecules and their interactions. Of the many dynamical properties of the system, the relationship between the dynamics of upstream molecules and downstream molecules is particularly important. A useful tool in understanding this relationship is a methodology to control the dynamics of intracellular molecules with an extracellular stimulus. However, this is a difficult task because the relationship between the levels of upstream molecules and those of downstream molecules is often not only stochastic, but also time-inhomogeneous, nonlinear, and not one-to-one. In this paper, we present an easy-to-implement model-based control method that makes the target downstream molecule to trace a desired time course by changing the concentration of a controllable upstream molecule. Our method uses predictions from Monte Carlo simulations of the model to decide the strength of the stimulus, while using a particle-based approach to make inferences regarding unobservable states. We applied our method to in silico control problems of insulin-dependent AKT pathway model and EGF-dependent Akt pathway model with system noise. We show that our method can robustly control the dynamics of the intracellular molecules against unknown system noise of various strengths, even in the absence of complete knowledge of the true model of the target system.

Comparative Transcriptomic Study of Muscle Provides New Insights into the Growth Superiority of a Novel Grouper Hybrid

Grouper (Epinephelus spp.) is a group of fish species with great economic importance in Asian countries. A novel hybrid grouper, generated by us and called the Hulong grouper (Hyb), has better growth performance than its parents, E. fuscoguttatus (Efu, ♀) and E. lanceolatus (Ela, ♂). We previously reported that the GH/IGF (growth hormone/insulin-like growth factor) system in the brain and liver contributed to the superior growth of the Hyb. In this study, using transcriptome sequencing (RNA-seq) and quantitative real-time PCR (qRT-PCR), we analyzed RNA expression levels of comprehensive genes in the muscle of the hybrid and its parents. Our data showed that genes involved in glycolysis and calcium signaling in addition to troponins are up-regulated in the Hyb. The results suggested that the activity of the upstream GH/IGF system in the brain and liver, along with the up-regulated glycolytic genes as well as ryanodine receptors (RyRs) and troponins related to the calcium signaling pathway in muscle, led to enhanced growth in the hybrid grouper. Muscle contraction inducing growth could be the major contributor to the growth superiority in our novel hybrid grouper, which may be a common mechanism for hybrid superiority in fishes.

Technical Challenges in Mass Spectrometry-Based Metabolomics

Metabolomics is a strategy for analysis, and quantification of the complete collection of metabolites present in biological samples. Metabolomics is an emerging area of scientific research because there are many application areas including clinical, agricultural, and medical researches for the biomarker discovery and the metabolic system analysis by employing widely targeted analysis of a few hundred preselected metabolites from 10-100 biological samples. Further improvement in technologies of mass spectrometry in terms of experimental design for larger scale analysis, computational methods for tandem mass spectrometry-based elucidation of metabolites, and specific instrumentation for advanced bioanalysis will enable more comprehensive metabolome analysis for exploring the hidden secrets of metabolism.

Selective control of up-regulated and down-regulated genes by temporal patterns and doses of insulin

Secretion of insulin transiently increases after eating, resulting in a high circulating concentration. Fasting limits insulin secretion, resulting in a low concentration of insulin in the circulation. We analyzed transcriptional responses to different temporal patterns and doses of insulin in the hepatoma FAO cells and identified 13 up-regulated and 16 down-regulated insulin-responsive genes (IRGs). The up-regulated IRGs responded more rapidly than did the down-regulated IRGs to transient stepwise or pulsatile increases in insulin concentration, whereas the down-regulated IRGs were repressed at lower concentrations of insulin than those required to stimulate the up-regulated IRGs. Mathematical modeling of the insulin response as two stages-(i) insulin signaling to transcription and (ii)transcription and mRNA stability-indicated that the first stage was the more rapid stage for the down-regulated IRGs, whereas the second stage of transcription was the more rapid stage for the up-regulated IRGs. A subset of the IRGs that were up-regulated or down-regulated in the FAO cells was similarly regulated in the livers of rats injected with a single dose of insulin. Thus, not only can cells respond to insulin but they can also interpret the intensity and pattern of signal to produce distinct transcriptional responses. These results provide insight that may be useful in treating obesity and type 2 diabetes associated with aberrant insulin production or tissue responsiveness.

Insights into the role of neuronal glucokinase

Glucokinase is a key component of the neuronal glucose-sensing mechanism and is expressed in brain regions that control a range of homeostatic processes. In this review, we detail recently identified roles for neuronal glucokinase in glucose homeostasis and counterregulatory responses to hypoglycemia and in regulating appetite. We describe clinical implications from these advances in our knowledge, especially for developing novel treatments for diabetes and obesity. Further research required to extend our knowledge and help our efforts to tackle the diabetes and obesity epidemics is suggested.

Glucose Homeostatic Law: Insulin Clearance Predicts the Progression of Glucose Intolerance in Humans

Homeostatic control of blood glucose is regulated by a complex feedback loop between glucose and insulin, of which failure leads to diabetes mellitus. However, physiological and pathological nature of the feedback loop is not fully understood. We made a mathematical model of the feedback loop between glucose and insulin using time course of blood glucose and insulin during consecutive hyperglycemic and hyperinsulinemic-euglycemic clamps in 113 subjects with variety of glucose tolerance including normal glucose tolerance (NGT), impaired glucose tolerance (IGT) and type 2 diabetes mellitus (T2DM). We analyzed the correlation of the parameters in the model with the progression of glucose intolerance and the conserved relationship between parameters. The model parameters of insulin sensitivity and insulin secretion significantly declined from NGT to IGT, and from IGT to T2DM, respectively, consistent with previous clinical observations. Importantly, insulin clearance, an insulin degradation rate, significantly declined from NGT, IGT to T2DM along the progression of glucose intolerance in the mathematical model. Insulin clearance was positively correlated with a product of insulin sensitivity and secretion assessed by the clamp analysis or determined with the mathematical model. Insulin clearance was correlated negatively with postprandial glucose at 2h after oral glucose tolerance test. We also inferred a square-law between the rate constant of insulin clearance and a product of rate constants of insulin sensitivity and secretion in the model, which is also conserved among NGT, IGT and T2DM subjects. Insulin clearance shows a conserved relationship with the capacity of glucose disposal among the NGT, IGT and T2DM subjects. The decrease of insulin clearance predicts the progression of glucose intolerance.

Diabetes and its link with cancer: providing the fuel and spark to launch an aggressive growth regime

Diabetes is a disease involving metabolic derangements in multiple organs. While the spectrum of diabetic complications has been known for years, recent evidence suggests that diabetes could also contribute to the initiation and propagation of certain cancers. The mechanism(s) underlying this relationship are not completely resolved but likely involve changes in hormone and nutrient levels, as well as activation of inflammatory and stress-related pathways. Interestingly, some of the drugs used clinically to treat diabetes also appear to have antitumour effects, further highlighting the interaction between these two conditions. In this contribution we review recent literature on this emerging relationship and explore the potential mechanisms that may promote cancer in diabetic patients.

Glycolysis is governed by growth regime and simple enzyme regulation in adherent MDCK cells

Due to its vital importance in the supply of cellular pathways with energy and precursors, glycolysis has been studied for several decades regarding its capacity and regulation. For a systems-level understanding of the Madin-Darby canine kidney (MDCK) cell metabolism, we couple a segregated cell growth model published earlier with a structured model of glycolysis, which is based on relatively simple kinetics for enzymatic reactions of glycolysis, to explain the pathway dynamics under various cultivation conditions. The structured model takes into account in vitro enzyme activities, and links glycolysis with pentose phosphate pathway and glycogenesis. Using a single parameterization, metabolite pool dynamics during cell cultivation, glucose limitation and glucose pulse experiments can be consistently reproduced by considering the cultivation history of the cells. Growth phase-dependent glucose uptake together with cell-specific volume changes generate high intracellular metabolite pools and flux rates to satisfy the cellular demand during growth. Under glucose limitation, the coordinated control of glycolytic enzymes re-adjusts the glycolytic flux to prevent the depletion of glycolytic intermediates. Finally, the model's predictive power supports the design of more efficient bioprocesses.

Glycolysis generates biomass precursors and energy from sugars and is therefore a key element in the metabolism of mammalian cells. Changes in its activity greatly affect cellular function which is often recognized as metabolic disease but also as opportunity for the design of efficient bioprocesses. Metabolic research discovered that continuously growing mammalian cells often exhibit a high glycolytic activity but also delivered seemingly endless facets in the pathway operation. The latter call for a systems-level understanding regarding capacity and regulation for a broad range of cultivation conditions. In this work, we couple a cell growth model to a simple kinetic description of glycolysis to consistently explain intracellular metabolite pool dynamics of the Madin-Darby canine kidney cell line over a variety of experiments and time scales while considering the growth status and cultivation history of the cells. We argue that the many different dynamics in glycolysis result from an interplay between a growth-dependent sugar uptake together with simple intrinsic enzyme regulation.

Reconstruction of insulin signal flow from phosphoproteome and metabolome data

Cellular homeostasis is regulated by signals through multiple molecular networks that include protein phosphorylation and metabolites. However, where and when the signal flows through a network and regulates homeostasis has not been explored. We have developed a reconstruction method for the signal flow based on time-course phosphoproteome and metabolome data, using multiple databases, and have applied it to acute action of insulin, an important hormone for metabolic homeostasis. An insulin signal flows through a network, through signaling pathways that involve 13 protein kinases, 26 phosphorylated metabolic enzymes, and 35 allosteric effectors, resulting in quantitative changes in 44 metabolites. Analysis of the network reveals that insulin induces phosphorylation and activation of liver-type phosphofructokinase 1, thereby controlling a key reaction in glycolysis. We thus provide a versatile method of reconstruction of signal flow through the network using phosphoproteome and metabolome data.