Mathematical Models of the Effect of Glucagon on Glycemia in Individuals With Type 2 Diabetes Treated With Dapagliflozin

Context

Sodium-glucose cotransporter 2 (SGLT2) inhibitors lower blood glucose levels by promoting urinary glucose excretion, but their overall effects on hormonal and metabolic status remain unclear.

Objective

We here investigated the roles of insulin and glucagon in the regulation of glycemia in individuals treated with an SGLT2 inhibitor using mathematical model analysis.

Methods

Hyperinsulinemic-euglycemic clamp and oral glucose tolerance tests were performed in 68 individuals with type 2 diabetes treated with the SGLT2 inhibitor dapagliflozin. Data previously obtained from such tests in 120 subjects with various levels of glucose tolerance and not treated with an SGLT2 inhibitor were examined as a control. Mathematical models of the feedback loops connecting glucose and insulin (GI model) or glucose, insulin, and glucagon (GIG model) were generated.

Results

Analysis with the GI model revealed that the disposition index/clearance, which is defined as the product of insulin sensitivity and insulin secretion divided by the square of insulin clearance and represents the glucose-handling ability of insulin, was significantly correlated with glycemia in subjects not taking an SGLT2 inhibitor but not in those taking dapagliflozin. Analysis with the GIG model revealed that a metric defined as the product of glucagon sensitivity and glucagon secretion divided by glucagon clearance (designated production index/clearance) was significantly correlated with blood glucose level in subjects treated with dapagliflozin.

Conclusion

Treatment with an SGLT2 inhibitor alters the relation between insulin effect and blood glucose concentration, and glucagon effect may account for variation in glycemia among individuals treated with such drugs.

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.

High-Performance Genetically Encoded Green Fluorescent Biosensors for Intracellular l-Lactate

l-Lactate is a monocarboxylate produced during the process of cellular glycolysis and has long generally been considered a waste product. However, studies in recent decades have provided new perspectives on the physiological roles of l-lactate as a major energy substrate and a signaling molecule. To enable further investigations of the physiological roles of l-lactate, we have developed a series of high-performance (ΔF/F = 15 to 30 in vitro), intensiometric, genetically encoded green fluorescent protein (GFP)-based intracellular l-lactate biosensors with a range of affinities. We evaluated these biosensors in cultured cells and demonstrated their application in an ex vivo preparation of Drosophila brain tissue. Using these biosensors, we were able to detect glycolytic oscillations, which we analyzed and mathematically modeled.

DI/cle, a Measure Consisting of Insulin Sensitivity, Secretion, and Clearance, Captures Diabetic States

CONTEXT

Insulin clearance is implicated in regulation of glucose homeostasis independently of insulin sensitivity and insulin secretion.

OBJECTIVE

To understand the relation between blood glucose and insulin sensitivity, secretion, and clearance.

METHODS

We performed a hyperglycemic clamp, a hyperinsulinemic-euglycemic clamp, and an oral glucose tolerance test (OGTT) in 47, 16, and 49 subjects with normal glucose tolerance (NGT), impaired glucose tolerance (IGT), and type 2 diabetes mellitus (T2DM), respectively. Mathematical analyses were retrospectively performed on this dataset.

RESULTS

The disposition index (DI), defined as the product of insulin sensitivity and secretion, showed a weak correlation with blood glucose levels, especially in IGT (r = 0.04; 95% CI, -0.63 to 0.44). However, an equation relating DI, insulin clearance, and blood glucose levels was well conserved regardless of the extent of glucose intolerance. As a measure of the effect of insulin, we developed an index, designated disposition index/clearance, (DI/cle) that is based on this equation and corresponds to DI divided by the square of insulin clearance. DI/cle was not impaired in IGT compared with NGT, possibly as a result of a decrease in insulin clearance in response to a reduction in DI, whereas it was impaired in T2DM relative to IGT. Moreover, DI/cle estimated from a hyperinsulinemic-euglycemic clamp, OGTT, or a fasting blood test were significantly correlated with that estimated from 2 clamp tests (r = 0.52; 95% CI, 0.37 to 0.64, r = 0.43; 95% CI, 0.24 to 0.58, r = 0.54; 95% CI, 0.38 to 0.68, respectively).

CONCLUSION

DI/cle can serve as a new indicator for the trajectory of changes in glucose tolerance.

DNA hypomethylation characterizes genes encoding tissue-dominant functional proteins in liver and skeletal muscle

Each tissue has a dominant set of functional proteins required to mediate tissue-specific functions. Epigenetic modifications, transcription, and translational efficiency control tissue-dominant protein production. However, the coordination of these regulatory mechanisms to achieve such tissue-specific protein production remains unclear. Here, we analyzed the DNA methylome, transcriptome, and proteome in mouse liver and skeletal muscle. We found that DNA hypomethylation at promoter regions is globally associated with liver-dominant or skeletal muscle-dominant functional protein production within each tissue, as well as with genes encoding proteins involved in ubiquitous functions in both tissues. Thus, genes encoding liver-dominant proteins, such as those involved in glycolysis or gluconeogenesis, the urea cycle, complement and coagulation systems, enzymes of tryptophan metabolism, and cytochrome P450-related metabolism, were hypomethylated in the liver, whereas those encoding-skeletal muscle-dominant proteins, such as those involved in sarcomere organization, were hypomethylated in the skeletal muscle. Thus, DNA hypomethylation characterizes genes encoding tissue-dominant functional proteins.

Comparison of hepatic responses to glucose perturbation between healthy and obese mice based on the edge type of network structures

Interactions between various molecular species in biological phenomena give rise to numerous networks. The investigation of these networks, including their statistical and biochemical interactions, supports a deeper understanding of biological phenomena. The clustering of nodes associated with molecular species and enrichment analysis is frequently applied to examine the biological significance of such network structures. However, these methods focus on delineating the function of a node. As such, in-depth investigations of the edges, which are the connections between the nodes, are rarely explored. In the current study, we aimed to investigate the functions of the edges rather than the nodes. To accomplish this, for each network, we categorized the edges and defined the edge type based on their biological annotations. Subsequently, we used the edge type to compare the network structures of the metabolome and transcriptome in the livers of healthy (wild-type) and obese (ob/ob) mice following oral glucose administration (OGTT). The findings demonstrate that the edge type can facilitate the characterization of the state of a network structure, thereby reducing the information available through datasets containing the OGTT response in the metabolome and transcriptome.

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.

Features extracted using tensor decomposition reflect the biological features of the temporal patterns of human blood multimodal metabolome

High-throughput omics technologies have enabled the profiling of entire biological systems. For the biological interpretation of such omics data, two analyses, hypothesis- and data-driven analyses including tensor decomposition, have been used. Both analyses have their own advantages and disadvantages and are mutually complementary; however, a direct comparison of these two analyses for omics data is poorly examined.We applied tensor decomposition (TD) to a dataset representing changes in the concentrations of 562 blood molecules at 14 time points in 20 healthy human subjects after ingestion of 75 g oral glucose. We characterized each molecule by individual dependence (constant or variable) and time dependence (later peak or early peak). Three of the four features extracted by TD were characterized by our previous hypothesis-driven study, indicating that TD can extract some of the same features obtained by hypothesis-driven analysis in a non-biased manner. In contrast to the years taken for our previous hypothesis-driven analysis, the data-driven analysis in this study took days, indicating that TD can extract biological features in a non-biased manner without the time-consuming process of hypothesis generation.

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.

AB0157 EFFICACY AND SAFETY OF FILGOTINIB IN ACTIVE RHEUMATOID ARTHRITIS PATIENTS WITH INADEQUATE RESPONSE TO METHOTREXATE: COMPARATIVE STUDY WITH FILGOTINIB AND TOCILIZUMAB EXAMINED BY CLINICAL INDEX AS WELL AS MUSCULOSKELETAL ULTRASOUND ASSESSMENT (TRANSFORM STUDY): STUDY PROTOCOL

Background

The administration of Janus kinase (JAK) inhibitors as well as biological disease-modifying anti-rheumatic drugs has dramatically improved even the clinical outcomes in rheumatoid arthritis (RA) patients with inadequate response to methotrexate (MTX). The dysregulation of JAK- signal transducer and activator of transcription (STAT) pathways via overproduction of cytokines, such as interleukin-6 (IL-6) is involved in the pathogenesis of RA (1). Filgotinib, a preferential JAK1 inhibitor, is effective in suppressing disease activity and preventing the progression of joint destruction due to inhibition of the JAK-STAT pathway. IL-6 inhibitors such as tocilizumab also inhibit the JAK-STAT pathways due to inhibition of IL-6 signaling. Thus, it should be desirable to investigate whether the effectiveness of filgotinib monotherapy is non-inferior to those of tocilizumab monotherapy in RA patients with inadequate response to MTX. In addition, it is important to accurately evaluate disease activity at the joint level by using musculoskeletal ultrasound (MSUS) and clinical disease activity indices, including subjective parameters (2).

Objectives

This study’s principal objective is to evaluate the effects of filgotinib monotherapy is non-inferior to those of tocilizumab monotherapy in RA patients with inadequate response to MTX. In addition, we will evaluate changes in patients’ parameters, including clinical disease activity indices, MSUS scores, serum biomarkers, patient-reported outcome (PRO), and modified total Sharp score (mTSS) after the administration of filgotinib or tocilizumab. Herein, we describe the study protocol for this study.

Methods

This study is an interventional, multicenter, randomized, open-label, parallel-group and non-inferiority clinical trial with a 52-week follow-up. In total, 400 RA patients with at least moderate disease activity during treatment with MTX will be included. Patients will be randomized in a 1:1 ratio to administration of filgotinib 200mg/day monotherapy or subcutaneous tocilizumab 162mg/biweekly monotherapy switched from MTX (Figure 1). We will evaluate disease activity by measuring clinical disease activity indices and by using MSUS. The primary endpoint is the proportion of patients who achieve an American College of Rheumatology 50 response at week 12. Important secondary endpoints are the changes from the baseline of the MSUS scores, PRO, and mTSS. We will also comprehensively analyze the serum levels of multiple biomarkers such as cytokines and chemokines.

Figure 1.

Results

Although the study results cannot be shown because the research entry is in progress, they are expected to show the non-inferiority of filgotinib monotherapy to tocilizumab monotherapy in RA patients with inadequate response to MTX.

Conclusion

The strength of this study is its prospective evaluation of therapeutic efficacy using not only clinical disease activity indices but also MSUS, which accurately and objectively evaluate disease activity at the joint level among patients drawn from multiple centers with a standardized evaluation by MSUS. In addition, we will evaluate the effectiveness of both drugs by integrating multilateral assessments, i.e., clinical disease activity indices, MSUS findings, and serum biomarkers.

References

[1]Gadina M, Le MT, Schwartz DM, Silvennoinen O, Nakayamada S, Yamaoka K, et al. Janus kinases to jakinibs: from basic insights to clinical practice. Rheumatology (Oxford). 2019;58(Suppl 1):i4-i16.

[2]Colebatch AN, Edwards CJ, Ostergaard M, van der Heijde D, Balint PV, D’Agostino MA, et al. EULAR recommendations for the use of imaging of the joints in the clinical management of rheumatoid arthritis. Ann Rheum Dis. 2013;72(6):804-14.

Disclosure of Interests

Toshimasa Shimizu: None declared, Shin-ya Kawashiri: None declared, Shimpei Morimoto: None declared, Yurika Kawazoe: None declared, Shohei Kuroda: None declared, Rina Kawasaki: None declared, Yasuko Ito: None declared, Shuntaro Sato: None declared, Hiroshi Yamamoto: None declared, Atsushi Kawakami Grant/research support from: Gilead Sciences, Inc.

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

Multi-omics-based label-free metabolic flux inference reveals obesity-associated dysregulatory mechanisms in liver glucose metabolism

Glucose homeostasis is maintained by modulation of metabolic flux. Enzymes and metabolites regulate the involved metabolic pathways. Dysregulation of glucose homeostasis is a pathological event in obesity. Analyzing metabolic pathways and the mechanisms contributing to obesity-associated dysregulation in vivo is challenging. Here, we introduce OMELET: Omics-Based Metabolic Flux Estimation without Labeling for Extended Trans-omic Analysis. OMELET uses metabolomic, proteomic, and transcriptomic data to identify relative changes in metabolic flux, and to calculate contributions of metabolites, enzymes, and transcripts to the changes in metabolic flux. By evaluating the livers of fasting ob/ob mice, we found that increased metabolic flux through gluconeogenesis resulted primarily from increased transcripts, whereas that through the pyruvate cycle resulted from both increased transcripts and changes in substrates of metabolic enzymes. With OMELET, we identified mechanisms underlying the obesity-associated dysregulation of metabolic flux in the liver.

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We developed OMELET to infer metabolic flux from label-free multi-omic data

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Contributions of metabolites, enzymes, and transcripts for flux were inferred

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Gluconeogenic flux increased in fasting ob/ob mice by increased transcripts

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Increased pyruvate cycle fluxes were led by increased transcripts and substrates

An extensive and dynamic trans-omic network illustrating prominent regulatory mechanisms in response to insulin in the liver

An effective combination of multi-omic datasets can enhance our understanding of complex biological phenomena. To build a context-dependent network with multiple omic layers, i.e., a trans-omic network, we perform phosphoproteomics, transcriptomics, proteomics, and metabolomics of murine liver for 4 h after insulin administration and integrate the resulting time series. Structural characteristics and dynamic nature of the network are analyzed to elucidate the impact of insulin. Early and prominent changes in protein phosphorylation and persistent and asynchronous changes in mRNA and protein levels through non-transcriptional mechanisms indicate enhanced crosstalk between phosphorylation-mediated signaling and protein expression regulation. Metabolic response shows different temporal regulation with transient increases at early time points across categories and enhanced response in the amino acid and nucleotide categories at later time points as a result of process convergence. This extensive and dynamic view of the trans-omic network elucidates prominent regulatory mechanisms that drive insulin responses through intricate interlayer coordination.

P–572 Purifying selection for aneuploidy cells in mosaicism embryo at post-implantation stage

Study question

Why low ratio mosaicism embryos develop to normal karyotype babies?

Summary answer

Our in vitro implantation assay clarified purifying selection for aneuploid cells in post implantation embryos.

What is known already

There are some reports about healthy live birth after transfer of mosaic embryos, which was reported for the first time from Italy in 2015. It is also reported that the abnormal cell is screened with the mouse in the embryo development, and only a normal cell contributes to the development. But it has not been examined in human.

Study design, size, duration

To clarify the change of aneuploid cells and mitochondrial activity in human embryo, we biopsied several parts from one blastocyst and examined karyotype. After in vitro implantation assay for biopsied embryos, we compared the karyotype of biopsy sample with that of cultured cell mass.

Participants/materials, setting, methods

Under the ethical review of Yokohama City University and informed consent with patients, we collected human surplus blastocysts those are donated after successful clinical treatment or discarded because of poor development grade. We biopsied multiple parts from one blastocyst and cultured the biopsied embryos, and extracted whole DNA from the biopsy samples and cultured embryos. Karyotyping by next generation sequencing were performed.

Main results and the role of chance

We analyzed 34 samples from 11 embryos, including 25 biopsy sample from 11 embryos and 9 cell mass from 7 cultured embryos. In the karyotype tracking results, even though biopsy sample analysis before the culture were uniformed aneuploid or chromosome mosaic, the developing embryo cell mass had normal karyotype. In one embryo as an example, among the three biopsied extra trophectoderm samples from that, two of them were mosaic, and one of them had uniformed chromosome 21 trisomy and chromosome 16 mosaic monosomy. But the embryo formed multiple cell mass in implantation assay. We examined karyotype of three cell mass, and the result from all were normal karyotype. We suggested that the chromosome aberration cells were screened in the human embryo development, and when the function was not carried out the embryo stopped the development.

Limitations, reasons for caution

Because of small number of samples available, we need more samples for a more accurate evaluation. Furthermore, we cannot evaluate the absolute mechanism that cells with chromosome aberration decreases.

Wider implications of the findings: Conventional PGT-A techniques are based on uniformed embryos developing hypothesized past time. As showed in some clinical reports, PGT-A can reduce of spontaneous abortion and chance of embryo transfer. Thinking about aneuploid cell purifying system in embryo development, effectiveness of PGT-A should be more questionable for infertility treatment.

Trial registration number

A200326004

Single-Cell Information Analysis Reveals That Skeletal Muscles Incorporate Cell-to-Cell Variability as Information Not Noise

Cell-to-cell variability in signal transduction in biological systems is often considered noise. However, intercellular variation (i.e., cell-to-cell variability) has the potential to enable individual cells to encode different information. Here, we show that intercellular variation increases information transmission of skeletal muscle. We analyze the responses of multiple cultured myotubes or isolated skeletal muscle fibers as a multiple-cell channel composed of single-cell channels. We find that the multiple-cell channel, which incorporates intercellular variation as information, not noise, transmitted more information in the presence of intercellular variation than in the absence according to the "response diversity effect," increasing in the gradualness of dose response by summing the cell-to-cell variable dose responses. We quantify the information transmission of human facial muscle contraction during intraoperative neurophysiological monitoring and find that information transmission of muscle contraction is comparable to that of a multiple-cell channel. Thus, our data indicate that intercellular variation can increase the information capacity of tissues.

Trans-omic analysis reveals obesity-associated dysregulation of inter-organ metabolic cycles between the liver and skeletal muscle

Systemic metabolic homeostasis is regulated by inter-organ metabolic cycles involving multiple organs. Obesity impairs inter-organ metabolic cycles, resulting in metabolic diseases. The systemic landscape of dysregulated inter-organ metabolic cycles in obesity has yet to be explored. Here, we measured the transcriptome, proteome, and metabolome in the liver and skeletal muscle and the metabolome in blood of fasted wild-type and leptin-deficient obese (ob/ob) mice, identifying components with differential abundance and differential regulation in ob/ob mice. By constructing and evaluating the trans-omic network controlling the differences in metabolic reactions between fasted wild-type and ob/ob mice, we provided potential mechanisms of the obesity-associated dysfunctions of metabolic cycles between liver and skeletal muscle involving glucose-alanine, glucose-lactate, and ketone bodies. Our study revealed obesity-associated systemic pathological mechanisms of dysfunction of inter-organ metabolic cycles.

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Multi-omic data in liver and skeletal muscle of WT and ob/ob mice were measured

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We developed the trans-omic network of differentially regulated metabolic reactions

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Dysregulation of inter-organ metabolic cycles associated with obesity was revealed

Fat Induces Glucose Metabolism in Nontransformed Liver Cells and Promotes Liver Tumorigenesis

Hepatic fat accumulation is associated with diabetes and hepatocellular carcinoma (HCC). Here, we characterize the metabolic response that high-fat availability elicits in livers before disease development. After a short term on a high-fat diet (HFD), otherwise healthy mice showed elevated hepatic glucose uptake and increased glucose contribution to serine and pyruvate carboxylase activity compared with control diet (CD) mice. This glucose phenotype occurred independently from transcriptional or proteomic programming, which identifies increased peroxisomal and lipid metabolism pathways. HFD-fed mice exhibited increased lactate production when challenged with glucose. Consistently, administration of an oral glucose bolus to healthy individuals revealed a correlation between waist circumference and lactate secretion in a human cohort. In vitro, palmitate exposure stimulated production of reactive oxygen species and subsequent glucose uptake and lactate secretion in hepatocytes and liver cancer cells. Furthermore, HFD enhanced the formation of HCC compared with CD in mice exposed to a hepatic carcinogen. Regardless of the dietary background, all murine tumors showed similar alterations in glucose metabolism to those identified in fat exposed nontransformed mouse livers, however, particular lipid species were elevated in HFD tumor and nontumor-bearing HFD liver tissue. These findings suggest that fat can induce glucose-mediated metabolic changes in nontransformed liver cells similar to those found in HCC. SIGNIFICANCE: With obesity-induced hepatocellular carcinoma on a rising trend, this study shows in normal, nontransformed livers that fat induces glucose metabolism similar to an oncogenic transformation.

Erratum: Dynamic 13C Flux Analysis Captures the Reorganization of Adipocyte Glucose Metabolism in Response to Insulin

[This corrects the article DOI: 10.1016/j.isci.2020.100855.].

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.

Kinetic Trans-omic Analysis Reveals Key Regulatory Mechanisms for Insulin-Regulated Glucose Metabolism in Adipocytes

Insulin regulates glucose metabolism through thousands of regulatory mechanisms; however, which regulatory mechanisms are keys to control glucose metabolism remains unknown. Here, we performed kinetic trans-omic analysis by integrating isotope-tracing glucose flux and phosphoproteomic data from insulin-stimulated adipocytes and built a kinetic mathematical model to identify key allosteric regulatory and phosphorylation events for enzymes. We identified nine reactions regulated by allosteric effectors and one by enzyme phosphorylation and determined the regulatory mechanisms for three of these reactions. Insulin stimulated glycolysis by promoting Glut4 activity by enhancing phosphorylation of AS160 at S595, stimulated fatty acid synthesis by promoting Acly activity through allosteric activation by glucose 6-phosphate or fructose 6-phosphate, and stimulated glutamate synthesis by alleviating allosteric inhibition of Gls by glutamate. Most of glycolytic reactions were regulated by amounts of substrates and products. Thus, phosphorylation or allosteric modulator-based regulation of only a few key enzymes was sufficient to change insulin-induced metabolism.

Trans-omic Analysis Reveals ROS-Dependent Pentose Phosphate Pathway Activation after High-Frequency Electrical Stimulation in C2C12 Myotubes

Skeletal muscle adaptation is mediated by cooperative regulation of metabolism, signal transduction, and gene expression. However, the global regulatory mechanism remains unclear. To address this issue, we performed electrical pulse stimulation (EPS) in differentiated C2C12 myotubes at low and high frequency, carried out metabolome and transcriptome analyses, and investigated phosphorylation status of signaling molecules. EPS triggered extensive and specific changes in metabolites, signaling phosphorylation, and gene expression during and after EPS in a frequency-dependent manner. We constructed trans-omic network by integrating these data and found selective activation of the pentose phosphate pathway including metabolites, upstream signaling molecules, and gene expression of metabolic enzymes after high-frequency EPS. We experimentally validated that activation of these molecules after high-frequency EPS was dependent on reactive oxygen species (ROS). Thus, the trans-omic analysis revealed ROS-dependent activation in signal transduction, metabolome, and transcriptome after high-frequency EPS in C2C12 myotubes, shedding light on possible mechanisms of muscle adaptation.

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We performed electrical pulse stimulation in differentiated C2C12 myotubes

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We constructed trans-omic network after high-frequency electrical pulse stimulation

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Trans-omic network integrates metabolome, transcriptome, and signaling molecules

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We identified ROS-dependent pentose phosphate pathway activation

Dynamic 13C Flux Analysis Captures the Reorganization of Adipocyte Glucose Metabolism in Response to Insulin

Cellular metabolism is dynamic, but quantifying non-steady metabolic fluxes by stable isotope tracers presents unique computational challenges. Here, we developed an efficient 13C-tracer dynamic metabolic flux analysis (13C-DMFA) framework for modeling central carbon fluxes that vary over time. We used B-splines to generalize the flux parameterization system and to improve the stability of the optimization algorithm. As proof of concept, we investigated how 3T3-L1 cultured adipocytes acutely metabolize glucose in response to insulin. Insulin rapidly stimulates glucose uptake, but intracellular pathways responded with differing speeds and magnitudes. Fluxes in lower glycolysis increased faster than those in upper glycolysis. Glycolysis fluxes rose disproportionally larger and faster than the tricarboxylic acid cycle, with lactate a primary glucose end product. The uncovered array of flux dynamics suggests that glucose catabolism is additionally regulated beyond uptake to help shunt glucose into appropriate pathways. This work demonstrates the value of using dynamic intracellular fluxes to understand metabolic function and pathway regulation.

P6154Association between n-3 and n-6 polyunsaturated fatty acids and plaque vulnerability by optical coherence tomography in acute myocardial infarction patients

Background

The values of n-3 and n-6 polyunsaturated fatty acids (PUFAs) like low eicosapentaenoic acid (EPA) /arachidonic acid (AA) ratio are known to be associated with cardiovascular events, however their relationship with coronary plaque vulnerability in acute myocardial infarction (AMI) is not revealed.

Purpose

We evaluated the relationship between n-3 and n-6 PUFAs and coronary plaque vulnerability assessed by optical coherence tomography (OCT) in AMI patients.

Methods

We investigated 79 AMI lesions (51 ST elevated myocardial infarction (STEMI) lesions and 28 non-STEMI lesions) that had undergone emergency percutaneous coronary intervention using OCT. Coronary plaque characteristics by OCT were compared with n-3 and n-6 PUFAs values which were measured on admission.

Results

Of all AMI lesions (n=79), 43 thin-cap fibroatheroma (TCFA) and 35 plaque rapture (PR) were detected by OCT. Lesions with TCFA had no significant relationship with n-3 and n-6 PUFAs values, whereas lesion with PR had significantly lower EPA values than those without (55.8±29.5 vs 74.3±37.1 μg/ml, p=0.018). Median low-density lipoprotein (LDL) cholesterol value was 117 (98–137) mg/dl and sub-analysis in patients who had lower LDL cholesterol values than median (n=39) revealed that EPA values were significantly lower in lesions with TCFA (56.3±30.9 vs 85.3±47.7 μg/ml, p=0.03). In STEMI patients, the values of EPA and EPA/AA ratio were significantly lower in lesions with TCFA (EPA: 55.5±22.8 vs 80.8±46.1 μg/ml, p=0.01; EPA/AA ratio: 0.34±0.16 vs 0.50±0.36, p=0.03). STEMI patients who had lower LDL cholesterol values <114 mg/dl of median (n=26), the values of EPA, EPA/AA ratio, and EPA+ docosahexaenoic acid (DHA) /AA ratio were significantly lower in lesions with TCFA (EPA: 51.4±20.7 vs 93.1±53.0 μg/ml, p=0.01; EPA/AA ratio: 0.37±0.16 vs 0.67±0.41, p=0.01; EPA+DHA/AA ratio: 1.13±0.41 vs 1.63±0.76, p=0.04). In STEMI patients with lower LDL cholesterol values, EPA/AA ratio positively correlated with fibrous cap thickness (Spearman, ρ=0.35, p=0.08). The cutoff value of EPA/AA ratio predicting the existence of TCFA was 0.52 (area under the curve 0.78, sensitivity 93.8%, specificity 70.0%, p=0.02).

Conclusion

This study demonstrated that n-3 and n-6 PUFAs values were associated with coronary plaque vulnerability by OCT in AMI patients, especially in STEMI. These results suggest that n-3 and n-6 PUFAs may be residual risk markers of severe acute cardiovascular events in patients with low LDL cholesterol values.

Robustness against additional noise in cellular information transmission

Fluctuations in intracellular reactions (intrinsic noise) reduce the information transmitted from an extracellular input to a cellular response. However, recent studies have demonstrated that the decrease in the transmitted information with respect to extracellular input fluctuations (extrinsic noise) is smaller when the intrinsic noise is larger. Therefore, it has been suggested that robustness against extrinsic noise increases with the level of the intrinsic noise. We call this phenomenon intrinsic noise-induced robustness (INIR). As previous studies on this phenomenon have focused on complex biochemical reactions, the relation between INIR and the input-output of a system is unclear. Moreover, the mechanism of INIR remains elusive. In this paper, we address these questions by analyzing simple models. We first analyze a model in which the input-output relation is linear. We show that the robustness against extrinsic noise increases with the intrinsic noise, confirming the INIR phenomenon. Moreover, the robustness against the extrinsic noise is more strongly dependent on the intrinsic noise when the variance of the intrinsic noise is larger than that of the input distribution. Next, we analyze a threshold model in which the output depends on whether the input exceeds the threshold. When the threshold is equal to the mean of the input, INIR is realized, but when the threshold is much larger than the mean, the threshold model exhibits stochastic resonance, and INIR is not always apparent. The robustness against extrinsic noise and the transmitted information can be traded off against one another in the linear model and the threshold model without stochastic resonance, whereas they can be simultaneously increased in the threshold model with stochastic resonance.

Logical design of oral glucose ingestion pattern minimizing blood glucose in humans

Excessive increase in blood glucose level after eating increases the risk of macroangiopathy, and a method for not increasing the postprandial blood glucose level is desired. However, a logical design method of the dietary ingestion pattern controlling the postprandial blood glucose level has not yet been established. We constructed a mathematical model of blood glucose control by oral glucose ingestion in three healthy human subjects, and predicted that intermittent ingestion 30 min apart was the optimal glucose ingestion patterns that minimized the peak value of blood glucose level. We confirmed with subjects that this intermittent pattern consistently decreased the peak value of blood glucose level. We also predicted insulin minimization pattern, and found that the intermittent ingestion 30 min apart was optimal, which is similar to that of glucose minimization pattern. Taken together, these results suggest that the glucose minimization is achieved by suppressing the peak value of insulin concentration, rather than by enhancing insulin concentration. This approach could be applied to design optimal dietary ingestion patterns.

Metabolism-Centric Trans-Omics

Two recent studies in Cell and Science demonstrate the reconstruction of global mechanistic networks and identification of regulatory principles from multi-omics data.

NMDAR-Mediated Ca2+ Increase Shows Robust Information Transfer in Dendritic Spines

A dendritic spine is a small structure on the dendrites of a neuron that processes input timing information from other neurons. Tens of thousands of spines are present on a neuron. Why are spines so small and many? We addressed this issue by using the stochastic simulation model of N-methyl-D-aspartate receptor (NMDAR)-mediated Ca²⁺ increase. NMDAR-mediated Ca²⁺ increase codes the input timing information between prespiking and postspiking. We examined how much the input timing information is encoded by Ca²⁺ increase against presynaptic fluctuation. We found that the input timing information encoded in the cell volume (10³μm³) largely decreases against the presynaptic fluctuation, whereas that in the spine volume (10^-1μm³) slightly decreases. Therefore, the input timing information encoded in the spine volume is more robust against presynaptic fluctuation than that in the cell volume. We further examined the mechanism of the robust information transfer in the spine volume. We demonstrated that the condition for the robustness is that the stochastic NMDAR-mediated Ca²⁺ increase (intrinsic noise) becomes much larger than the presynaptic fluctuation (extrinsic noise). When the presynaptic fluctuation is large, the condition is satisfied in the spine volume but not in the cell volume. Moreover, we compared the input timing information encoded in many small spines with that encoded in a single large spine. We found that the input timing information encoded in many small spines are larger than that in a single large spine when presynaptic fluctuation is large because of their robustness. Thus, robustness is a functional reason why dendritic spines are so small and many.

A case of under-dosing after raltegravir formulation change in an elderly patient treated for HIV

Our case was a 70-year-old male (height: 168 cm, weight: 74.3 kg) with polypharmacy (total 15 drugs including 10 tablets) who was treated for HIV infection. His dosing schedule of raltegravir was changed from BID (a 400 mg tablet, twice) to QD (2x600 mg tablet, once). After a month, we found that he miss-took raltegravir for 1x600 mg tablet at once. His HIV-1 RNA increased from undetectable levels to < 20 copies per mL. Pharmaceutical companies should therefore carefully consider swallowing difficulties in old patients, such as by reformulating medications so that only one dosing is required per day and decreasing the size of tablets to 7-8 mm in diameter or orally distinguish tablet.

Reconstruction of global regulatory network from signaling to cellular functions using phosphoproteomic data

Cellular signaling regulates various cellular functions via protein phosphorylation. Phosphoproteomic data potentially include information for a global regulatory network from signaling to cellular functions, but a procedure to reconstruct this network using such data has yet to be established. In this paper, we provide a procedure to reconstruct a global regulatory network from signaling to cellular functions from phosphoproteomic data by integrating prior knowledge of cellular functions and inference of the kinase-substrate relationships (KSRs). We used phosphoproteomic data from insulin-stimulated Fao hepatoma cells and identified protein phosphorylation regulated by insulin specifically over-represented in cellular functions in the KEGG database. We inferred kinases for protein phosphorylation by KSRs, and connected the kinases in the insulin signaling layer to the phosphorylated proteins in the cellular functions, revealing that the insulin signal is selectively transmitted via the Pi3k-Akt and Erk signaling pathways to cellular adhesions and RNA maturation, respectively. Thus, we provide a method to reconstruct global regulatory network from signaling to cellular functions based on phosphoproteomic data.

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.

Automatic Quantitative Segmentation of Myotubes Reveals Single-cell Dynamics of S6 Kinase Activation

Automatic cell segmentation is a powerful method for quantifying signaling dynamics at single-cell resolution in live cell fluorescence imaging. Segmentation methods for mononuclear and round shape cells have been developed extensively. However, a segmentation method for elongated polynuclear cells, such as differentiated C2C12 myotubes, has yet to be developed. In addition, myotubes are surrounded by undifferentiated reserve cells, making it difficult to identify background regions and subsequent quantification. Here we developed an automatic quantitative segmentation method for myotubes using watershed segmentation of summed binary images and a two-component Gaussian mixture model. We used time-lapse fluorescence images of differentiated C2C12 cells stably expressing Eevee-S6K, a fluorescence resonance energy transfer (FRET) biosensor of S6 kinase (S6K). Summation of binary images enhanced the contrast between myotubes and reserve cells, permitting detection of a myotube and a myotube center. Using a myotube center instead of a nucleus, individual myotubes could be detected automatically by watershed segmentation. In addition, a background correction using the two-component Gaussian mixture model permitted automatic signal intensity quantification in individual myotubes. Thus, we provide an automatic quantitative segmentation method by combining automatic myotube detection and background correction. Furthermore, this method allowed us to quantify S6K activity in individual myotubes, demonstrating that some of the temporal properties of S6K activity such as peak time and half-life of adaptation show different dose-dependent changes of insulin between cell population and individuals.Key words: time lapse images, cell segmentation, fluorescence resonance energy transfer, C2C12, myotube.

Dynamic Metabolomics Reveals that Insulin Primes the Adipocyte for Glucose Metabolism

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.

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.

A case of a rare variant of Klinefelter syndrome, 47,XY,i(X)(q10)

Klinefelter syndrome is a condition in which a male patient has one Y chromosome and one or more extra X chromosomes. It is the most common sex chromosome disorder. Klinefelter syndrome is distinguished by many clinical features, such as infertility, high gonadotropin and low testosterone levels, increased height, and sparse body and facial hair. We report the case of a 32-year-old man who visited our hospital complaining of male infertility. Semen analysis showed azoospermia, and chromosomal analysis revealed a 47,XY,i(X)(q10) karyotype, which is a rare variant of Klinefelter syndrome. No spermatozoon was found on microdissection testicular sperm extraction, and the testis biopsy histology showed only Sertoli cells and hyalinised seminiferous tubules. 47,XY, i(X)(q10) has an additional isochromosome made of the long arm of the X chromosome, which shares some features of classical Klinefelter syndrome in many aspects, but patients are usually shorter than average height and have normal intelligence. In addition, to the best of our knowledge, no successful sperm extractions from 47,XY, i(X)(q10) patients were reported in the literature. The reports of patients who have undergone microdissection testicular sperm extraction are very rare. Further reports and studies of this chromosomal abnormality are needed.

Digoxin Transport by Renal Proximal Tubule Cells is Enhanced by Adhesive Synthetic RGD Peptide

Introduction

The dialyzer apparatus has been widely used as an artificial kidney in medical treatment. However, side effects such as amyloidosis have occurred during long-term treatment. Therefore, we focused on developing a hybrid artificial kidney with a filtration and reabsorption apparatus, but it was found that cells spread extensively and it is difficult to maintain a uniform monolayer with a regular cell shape on a collagen-coated substrate. The purpose of this study was to improve cell adhesion, uniform stable monolayer formation and active transport function by immobilization of arginine-glycine-aspartic acid (RGD) on the culture substratum.

Materials and Methods

Polycarbonate semipermeable membranes were coated with collagen, fibronectin, laminin and synthetic polypeptide, including RGD (Pronectin F). Cell adhesion and digoxin transport were estimated using a renal proximal tubule cell line that overexpressed the P-glycoprotein gene.

Results and Discussion

Under initial and confluent conditions, immobilized cell density in Pronectin F-coated wells was higher than that under other conditions. Transepithelial electrical resistance and digoxin transport activity on Pronectin F-coated membranes were the highest of all conditions. This might have been caused by uniform cell morphology and high cell density.

System identification of signaling dependent gene expression with different time-scale data

Cells decode information of signaling activation at a scale of tens of minutes by downstream gene expression with a scale of hours to days, leading to cell fate decisions such as cell differentiation. However, no system identification method with such different time scales exists. Here we used compressed sensing technology and developed a system identification method using data of different time scales by recovering signals of missing time points. We measured phosphorylation of ERK and CREB, immediate early gene expression products, and mRNAs of decoder genes for neurite elongation in PC12 cell differentiation and performed system identification, revealing the input-output relationships between signaling and gene expression with sensitivity such as graded or switch-like response and with time delay and gain, representing signal transfer efficiency. We predicted and validated the identified system using pharmacological perturbation. Thus, we provide a versatile method for system identification using data with different time scales.

Small-Volume Effect Enables Robust, Sensitive, and Efficient Information Transfer in the Spine

Why is the spine of a neuron so small that it can contain only small numbers of molecules and reactions inevitably become stochastic? We previously showed that, despite such noisy conditions, the spine exhibits robust, sensitive, and efficient features of information transfer using the probability of Ca²⁺ increase; however, the mechanisms are unknown. In this study, we show that the small volume effect enables robust, sensitive, and efficient information transfer in the spine volume, but not in the cell volume. In the spine volume, the intrinsic noise in reactions becomes larger than the extrinsic noise of input, resulting in robust information transfer despite input fluctuation. In the spine volume, stochasticity makes the Ca²⁺ increase occur with a lower intensity of input, causing higher sensitivity to lower intensity of input. The volume-dependency of information transfer increases its efficiency in the spine volume. Thus, we propose that the small-volume effect is the functional reason why the spine has to be so small.