Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Authorship：Last author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Scientific Reports  

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.

DOI： 10.1038/s41598-023-31547-2

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1038/s41598-022-17964-9

Language：English   Publishing type：Research paper (scientific journal)  

DOI： DOI: 10.1038/s41540-022-00213-0

Language：English   Publishing type：Research paper (scientific journal)  

DOI： doi.org/10.1016/j.isci.2022.103787

Language：Others   Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.isci.2021.102217

Language：English   Publishing type：Research paper (scientific journal)  

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.

DOI： 10.1126/scisignal.aaz1236

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1016

Language：English  

DOI： 10.1007/s12551-020-00643-2

Language：English   Publishing type：Research paper (scientific journal)  

The thymic function to produce self-protective and self-tolerant T cells is chiefly mediated by cortical thymic epithelial cells (cTECs) and medullary TECs (mTECs). Recent studies including single-cell transcriptomic analyses have highlighted a rich diversity in functional mTEC subpopulations. Because of their limited cellularity, however, the biochemical characterization of TECs, including the proteomic profiling of cTECs and mTECs, has remained unestablished. Utilizing genetically modified mice that carry enlarged but functional thymuses, here we show a combination of proteomic and transcriptomic profiles for cTECs and mTECs, which identified signature molecules that characterize a developmental and functional contrast between cTECs and mTECs. Our results reveal a highly specific impact of the thymoproteasome on proteasome subunit composition in cTECs and provide an integrated trans-omics platform for further exploration of thymus biology.

DOI： 10.1016/j.celrep.2019.10.079

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1038/s41540-019-0108-1.

Language：English   Publishing type：Research paper (scientific journal)  

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.

DOI： 10.1111/gtc.12655

Language：English   Publishing type：Research paper (scientific journal)  

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.

DOI： 10.1016/j.isci.2018.07.022

Language：English   Publishing type：Research paper (scientific journal)  

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.

DOI： 10.1016/j.cels.2018.05.013

Authorship：Last author   Language：English   Publishing type：Research paper (other academic)  

Recent advances in measurement technology have enabled us to measure various omic layers, such as genome, transcriptome, proteome, and metabolome layers. The demand for data analysis to determine the network structure of the interaction between molecular species is increasing. The Gaussian graphical model is one method of estimating the network structure. However, biological omics data sets tend to include missing values, which is conventionally handled by preprocessing. We propose a novel method by which to estimate the network structure together with missing values by combining a sparse graphical model and matrix factorization. The proposed method was validated by artificial data sets and was applied to a signal transduction data set as a test run.

DOI： 10.23919/FRUCT.2017.8250201

Language：English   Publishing type：Research paper (scientific journal)  

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.

DOI： 10.1038/s41540-018-0051-6

Language：English   Publishing type：Research paper (scientific journal)  

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.

DOI： 10.1371/journal.pcbi.1005913

Language：English   Publishing type：Research paper (scientific journal)  

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.

DOI： 10.1126/scisignal.aaf3739

Language：English  

We propose 'trans-omic' analysis for reconstructing global biochemical networks across multiple omic layers by use of both multi-omic measurements and computational data integration. We introduce technologies for connecting multi-omic data based on prior knowledge of biochemical interactions and characterize a biochemical trans-omic network by concepts of a static and dynamic nature. We introduce case studies of metabolism-centric trans-omic studies to show how to reconstruct a biochemical trans-omic network by connecting multi-omic data and how to analyze it in terms of the static and dynamic nature. We propose a trans-ome-wide association study (trans-OWAS) connecting phenotypes with trans-omic networks that reflect both genetic and environmental factors, which can characterize several complex lifestyle diseases as breakdowns in the trans-omic system.

DOI： 10.1016/j.tibtech.2015.12.013

Language：English   Publishing type：Research paper (scientific journal)  

Epithelial cell plasticity is controlled by extracellular cues, but the underlying mechanisms remain to be fully understood. Epidermal growth factor (EGF) and amphiregulin (AREG) are high-and low-affinity ligands for EGF receptor (EGFR), respectively. EGFR signaling is known to promote epithelial-mesenchymal transition (EMT) by the activation of ERK and the induction of an EMT transcription factor, ZEB1. Here, we demonstrate that ligand-switching between EGF and AREG at equivalent molarity reversibly interconverts epithelial and mesenchymal-like states of EGFR signal-dependent mammary epithelial cells. The EGF- and AREG-cultured cells also differ in their epithelial characteristics, including the expression of cell surface markers, the mode of migration and the ability for acinus-formation. The ligand-switching between EGF and AREG temporally alters strength of the shared EGFR-ERK signaling. This alteration inverts relative expression levels of ZEB1 and its antagonizing microRNAs, miR-205 and miR-200c, those are critical determinants of the epithelial phenotype. Further, AREG-induced EGFR accumulation on the plasma membrane compensates for the weak association between AREG and EGFR. The EGFR dynamics enables AREG to support proliferation as efficiently as EGF at equivalent molarity and to maintain epithelial characteristics. Our findings reveal a role of EGFR ligands-generated signal strength in the regulation of mammary epithelial cell plasticity.

DOI： 10.1038/srep20209

Language：English   Publishing type：Research paper (scientific journal)  

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.

DOI： 10.1371/journal.pone.0143880

Language：English   Publishing type：Research paper (scientific journal)  

The dynamic activity of the serine/threonine kinase Akt is crucial for the regulation of diverse cellular functions, but the precise spatiotemporal control of its activity remains a critical issue. Herein, we present a photo-activatable Akt (PA-Akt) system based on a light-inducible protein interaction module of Arabidopsis thaliana cryptochrome2 (CRY2) and CIB1. Akt fused to CRY2phr, which is a minimal light sensitive domain of CRY2 (CRY2-Akt), is reversibly activated by light illumination in several minutes within a physiological dynamic range and specifically regulates downstream molecules and inducible biological functions. We have generated a computational model of CRY2-Akt activation that allows us to use PA-Akt to control the activity quantitatively. The system provides evidence that the temporal patterns of Akt activity are crucial for generating one of the downstream functions of the Akt-FoxO pathway; the expression of a key gene involved in muscle atrophy (Atrogin-1). The use of an optical module with computational modeling represents a general framework for interrogating the temporal dynamics of biomolecules by predictive manipulation of optogenetic modules.

DOI： 10.1038/srep14589

Authorship：Lead author,　Corresponding author   Language：English  

During recent years, it has become clearer that temporal patterns of stimuli and molecules are important in the regulation of cellular functions. For example, many hormones show distinct temporal patterns in vivo, which are important for homeostasis. One of the unique characteristics of cellular signaling pathways is that a common signaling pathway can selectively regulate multiple cellular functions depending on their temporal patterns. Therefore, one of the major advances in understanding the "pathogenic dysregulation of signaling" is to reveal the temporal coding mechanisms of signaling pathways related to pathogenesis. A systems biological approach combining experiments and computational analysis is necessary to address this issue. In this chapter, we will introduce the concept that the insulin- dependent AKT pathway uses temporal patterns multiplexing for selective regulation of signaling molecules and metabolites, which depend on their network structures and kinetics, using rat hepatoma Fao cells. These results represent a huge step forward in our understanding of insulin actions and type II diabetes mellitus .

DOI： 10.1007/978-4-431-55561-2_7

Language：English   Publishing type：Research paper (scientific journal)  

Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multipleoutputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.

DOI： 10.1371/journal.pone.0072780

Language：English   Publishing type：Research paper (scientific journal)  

Robust transmission of information despite the presence of variation is a fundamental problem in cellular functions. However, the capability and characteristics of information transmission in signaling pathways remain poorly understood. We describe robustness and compensation of information transmission of signaling pathways at the cell population level. We calculated the mutual information transmitted through signaling pathways for the growth factor-mediated gene expression. Growth factors appeared to carry only information sufficient for a binary decision. Information transmission was generally more robust than average signal intensity despite pharmacological perturbations, and compensation of information transmission occurred. Information transmission to the biological output of neurite extension appeared robust. Cells may use information entropy as information so that messages can be robustly transmitted despite variation in molecular activities among individual cells.

DOI： 10.1126/science.1234511

Language：English   Publishing type：Research paper (scientific journal)  

Insulin governs systemic glucose metabolism, including glycolysis, gluconeogenesis and glycogenesis, through temporal change and absolute concentration. However, how insulin-signalling pathway selectively regulates glycolysis, gluconeogenesis and glycogenesis remains to be elucidated. To address this issue, we experimentally measured metabolites in glucose metabolism in response to insulin. Step stimulation of insulin induced transient response of glycolysis and glycogenesis, and sustained response of gluconeogenesis and extracellular glucose concentration (GLC(ex)). Based on the experimental results, we constructed a simple computational model that characterises response of insulin-signalling-dependent glucose metabolism. The model revealed that the network motifs of glycolysis and glycogenesis pathways constitute a feedforward (FF) with substrate depletion and incoherent feedforward loop (iFFL), respectively, enabling glycolysis and glycogenesis responsive to temporal changes of insulin rather than its absolute concentration. In contrast, the network motifs of gluconeogenesis pathway constituted a FF inhibition, enabling gluconeogenesis responsive to absolute concentration of insulin regardless of its temporal patterns. GLC(ex) was regulated by gluconeogenesis and glycolysis. These results demonstrate the selective control mechanism of glucose metabolism by temporal patterns of insulin.

DOI： 10.1038/msb.2013.19

Language：English   Publishing type：Research paper (scientific journal)  

In cellular signal transduction, the information in an external stimulus is encoded in temporal patterns in the activities of signaling molecules
for example, pulses of a stimulus may produce an increasing response or may produce pulsatile responses in the signaling molecules. Here, we show how the Akt pathway, which is involved in cell growth, specifically transmits temporal information contained in upstream signals to downstream effectors. We modeled the epidermal growth factor (EGF)-dependent Akt pathway in PC12 cells on the basis of experimental results. We obtained counterintuitive results indicating that the sizes of the peak amplitudes of receptor and downstream effector phosphorylation were decoupled
weak, sustained EGF receptor (EGFR) phosphorylation, rather than strong, transient phosphorylation, strongly induced phosphorylation of the ribosomal protein S6, a molecule downstream of Akt. Using frequency response analysis, we found that a three-component Akt pathway exhibited the property of a low-pass filter and that this property could explain decoupling of the peak amplitudes of receptor phosphorylation and that of downstream effectors. Furthermore, we found that lapatinib, an EGFR inhibitor used as an anticancer drug, converted strong, transient Akt phosphorylation into weak, sustained Akt phosphorylation, and, because of the low-pass filter characteristics of the Akt pathway, this led to stronger S6 phosphorylation than occurred in the absence of the inhibitor. Thus, an EGFR inhibitor can potentially act as a downstream activator of some effectors. Copyright 2008 by the American Association for the Advancement of Science
all rights reserved.

DOI： 10.1126/scisignal.2000810

Language：English   Publishing type：Research paper (scientific journal)  

In cellular signal transduction, the information in an external stimulus is encoded in temporal patterns in the activities of signaling molecules; for example, pulses of a stimulus may produce an increasing response or may produce pulsatile responses in the signaling molecules. Here, we show how the Akt pathway, which is involved in cell growth, specifically transmits temporal information contained in upstream signals to downstream effectors. We modeled the epidermal growth factor (EGF)-dependent Akt pathway in PC12 cells on the basis of experimental results. We obtained counterintuitive results indicating that the sizes of the peak amplitudes of receptor and downstream effector phosphorylation were decoupled; weak, sustained EGF receptor (EGFR) phosphorylation, rather than strong, transient phosphorylation, strongly induced phosphorylation of the ribosomal protein S6, a molecule downstream of Akt. Using frequency response analysis, we found that a three-component Akt pathway exhibited the property of a low-pass filter and that this property could explain decoupling of the peak amplitudes of receptor phosphorylation and that of downstream effectors. Furthermore, we found that lapatinib, an EGFR inhibitor used as an anticancer drug, converted strong, transient Akt phosphorylation into weak, sustained Akt phosphorylation, and, because of the low-pass filter characteristics of the Akt pathway, this led to stronger S6 phosphorylation than occurred in the absence of the inhibitor. Thus, an EGFR inhibitor can potentially act as a downstream activator of some effectors.

DOI： 10.1126/scisignal.2000810

Language：English   Publishing type：Research paper (scientific journal)  

Background: Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling.
Methodology/Principal Findings: We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells.
Conclusions/Significance: The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.

DOI： 10.1371/journal.pone.0009955

Language：English   Publishing type：Research paper (scientific journal)  

Background: Continuous NGF stimulation induces PC12 cell differentiation. However, why continuous NGF stimulation is required for differentiation is unclear. In this study, we investigated the underlying mechanisms of the timing-dependent requirement of NGF action for cell differentiation.
Methodology/Principal Findings: To address the timing-dependency of the NGF action, we performed a discontinuous stimulation assay consisting of a first transient stimulation followed by an interval and then a second sustained stimulation and quantified the neurite extension level. Consequently, we observed a timing-dependent action of NGF on cell differentiation, and discontinuous NGF stimulation similarly induced differentiation. The first stimulation did not induce neurite extension, whereas the second stimulation induced fast neurite extension; therefore, the first stimulation is likely required as a prerequisite condition. These observations indicate that the action of NGF can be divided into two processes: an initial stimulation-driven latent process and a second stimulation-driven extension process. The latent process appears to require the activities of ERK and transcription, but not PI3K, whereas the extension-process requires the activities of ERK and PI3K, but not transcription. We also found that during the first stimulation, the activity of NGF can be replaced by PACAP, but not by insulin, EGF, bFGF or forskolin; during the second stimulation, however, the activity of NGF cannot be replaced by any of these stimulants. These findings allowed us to identify potential genes specifically involved in the latent process, rather than in other processes, using a microarray.
Conclusions/Significance: These results demonstrate that NGF induces the differentiation of PC12 cells via mechanically distinct processes: an ERK-driven and transcription-dependent latent process, and an ERK- and PI3K-driven and transcription-independent extension process.

DOI： 10.1371/journal.pone.0009011

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Amino acid-starved yeast activates the eIF2a kinase Gcn2p to suppress general translation and to selectively derepress the transcription factor Gcn4p, which induces various biosynthetic genes to elicit general amino acid control (GAAC). Well-fed yeast activates the target of rapamycin (TOR) to stimulate translation via the eIF4F complex. A crosstalk was demonstrated between the pathways for GAAC and TOR signaling: the TOR-specific inhibitor rapamycin activates Gcn2p. Here we demonstrate that, upon TOR-inactivation, the putative TOR-regulated eIF4E-associated protein Eap1p likely functions downstream of Gcn2p to attenuate GCN4 translation via a mechanism independent of eIF4E-binding, thereby constituting another interface between the two pathways. 2005 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

DOI： 10.1016/j.febslet.2004.03.043

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

BMH1 and BMH2 encode Saccharomyces cerevisiae 14-3-3 homologues whose exact functions have remained unclear. The present work compares the transcriptomic and proteomic profiles of the wild type and a BMH1/2-deficient S. cerevisiae mutant (bmhDelta) using DNA microarrays and two-dimensional polyacrylamide gel electrophoresis. It is reported here that, although the global patterns of gene and protein expression are very similar between the two types of yeast cells, a subset of genes and proteins (a total of 220 genes) is significantly induced or reduced in the absence of Bmh1/2p. These genes include approximately 60 elements that could be linked to the reported phenotypes of the bmhDelta mutant (e.g., accumulation of glycogen and hypersensitivity to environmental stress) and/or could be the potential downstream targets of interacting partners of Bmh1/2p such as Msn2p and Rtg3p. Importantly, > 30% of the identified genes (71 genes) were found to be associated with carbon (C) and nitrogen (N) metabolism and transport, thereby suggesting that Bmh1/2p may play a major role in the regulation of C/N-responsive cellular processes. This study presents the first comprehensive overview of the genes and proteins that are affected by the depletion of Bmh1/2p and extends the scope of knowledge of the regulatory roles of Bmh1/2p in S. cerevisiae.

DOI： 10.1021/bi03542li

Language：Others  

Rapamycin-induced translational derepression of GCN4 mRNA involves a novel mechanism for activation of the eIF2α kinase GCN2.

DOI： 10.1074/jbc.C300133200

Language：English   Publishing type：Research paper (scientific journal)  

Language：English  

Comprehensive analysis of protein-protein interactions is a challenging endeavor of functional proteomics and has been best explored in the budding yeast. The yeast protein interactome analysis was achieved first by using the yeast two-hybrid system in a proteome-wide scale and next by large-scale mass spectrometric analysis of affinity-purified protein complexes. While these interaction data have led to a number of novel findings and the emergence of a single huge network containing thousands of proteins, they suffer many false signals and fall short of grasping the entire interactome. Thus, continuous efforts are necessary in both bioinformatics and experimentation to fully exploit these data and to proceed another step forward to the goal. Computational tools to integrate existing biological knowledge buried in literature and various functional genomic data with the interactome data are required for biological interpretation of the huge protein interaction network. Novel experimental methods have to be developed to detect weak, transient interactions involving low abundance proteins as well as to obtain clues to the biological role for each interaction. Since the yeast two-hybrid system can be used for the mapping of the interaction domains and the isolation of interaction-defective mutants, it would serve as a technical basis for the latter purpose, thereby playing another important role in the next phase of protein interactome research.

DOI： 10.1074/mcp.R200005-MCP200

Language：English   Publishing type：Research paper (scientific journal)  

Budding yeast GCN1 binds the GI domain to activate the eIF2 alpha kinase GCN2
When starved for a single amino acid, the budding yeast Saccharomyces cerevisiae activates the eukaryotic initiation factor 2 alpha (eIF2 alpha) kinase GCN2 in a GCN1-dependent manner. Phosphorylated eIF2 alpha inhibits general translation but selectively derepresses the synthesis of the transcription factor GCN4, which leads to coordinated induction of genes involved in biosynthesis of various amino acids, a phenomenon called general control response. We recently demonstrated that this response requires binding of GCN1 to the GI domain occurring at the N terminus of GCN2 (Kubota, H,, Sakaki, Y., and Ito, T. (2000) J. Biol. Chem. 275, 20243-20246), Here we provide the first evidence for the involvement of GCN1-GCN2 interaction in activation of GCN2 per se. We identified a C-terminal segment of GCN1 sufficient to bind the GI domain and used a novel dual bait two-hybrid method to identify mutations rendering GCN1 incapable of interacting with GCN2, The yeast bearing such an allele, gcn1-F2291L, fails to display derepression of GCN4 translation and hence general control response, as does a GI domain mutant, gcn2-Y74A,, defective in association with GCN1. Furthermore, we demonstrated that phosphorylation of eIF2 alpha is impaired in both mutants. Since GCN2 is the sole eIF2 alpha kinase in yeast, these findings indicate a critical role of GCN1-GCN2 interaction in activation of the kinase in vivo.

DOI： 10.1074/jbc.M011793200

Language：English   Publishing type：Research paper (scientific journal)  

GI domain-mediated association of the eukaryotic initiation factor 2 alpha kinase GCN2 with its activator GCN1 is required for general amino acid control in budding yeast
In response to the starvation of a single amino acid, the budding yeast Saccharomyces cerevisiae activates numerous genes involved in various amino acid biosynthetic pathways, all of which are under the control of transcription factor GCN4. This general amino acid control response is based on de-repressed translation of GCN4 mRNA, which is induced by the activation of the eIF2 alpha kinase, GCN2. Although it is known that in vivo activation of GCN2 requires GCN1, the mode of GCN1 action remains to be elucidated at the molecular level. Here, we show that GCN2 interacts with GCN1 via the GI domain, a novel protein-binding module that occurs at the N terminus; mutations to conserved residues of this domain abolish its binding to GCN1. Furthermore, the yeast cells with GCN2 defective in interaction with GCN1 fail to display general control response. A similar phenotype is observed in cells overexpressing the GI domain of GCN2 or its target region on GCN1, Thus, GI domain-mediated association of GCN2 to GCN1 is required for general amino acid control. This finding provides the first insight into the molecular mechanism for the activation of GCN2 by GCN1.

DOI： 10.1074/jbc.C000262200

Language：Japanese   Book type：General book, introductory book for general audience

Language：Japanese   Book type：Scholarly book

Language：English   Book type：Scholarly book

Event date： 2015.9

Language：English   Presentation type：Symposium, workshop panel (public)  

Venue：Fukuoka   Country：Japan  

Event date： 2024.4

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Country：Japan  

Event date： 2024.4

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Venue：東京   Country：Japan  

Event date： 2023.6

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Venue：on line   Country：Japan  

Event date： 2022.11

Language：English   Presentation type：Symposium, workshop panel (public)  

Venue：on line   Country：Japan  

Event date： 2022.11

Language：English   Presentation type：Symposium, workshop panel (public)  

Venue：on line   Country：Japan  

Event date： 2022.3

Language：English   Presentation type：Symposium, workshop panel (public)  

Venue：Taipei, Taiwan (hybrid with online)   Country：Japan  

Event date： 2021.6

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Venue：on line   Country：Japan  

Event date： 2021.3

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Venue：on line   Country：Japan  

Event date： 2020.10

Language：English   Presentation type：Symposium, workshop panel (public)  

Venue：on line   Country：Japan  

Event date： 2020.10

Language：English   Presentation type：Symposium, workshop panel (public)  

Venue：on line   Country：Japan  

Event date： 2019.12

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Venue：福岡   Country：Japan  

Event date： 2019.11

Language：English  

Venue：沖縄   Country：Japan  

Event date： 2019.9

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Country：Japan  

Event date： 2019.9

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：埼玉   Country：Japan  

Event date： 2019.6

Language：Japanese   Presentation type：Oral presentation (invited, special)  

Venue：宮崎   Country：Japan  

Event date： 2019.2

Language：English   Presentation type：Symposium, workshop panel (public)  

Venue：東京   Country：Japan  

Event date： 2019.2

Language：English   Presentation type：Symposium, workshop panel (public)  

Venue：東京   Country：Japan  

Event date： 2018.8 - 2018.9

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：大津   Country：Japan  

Event date： 2016.3

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Venue：東京   Country：Japan  

Event date： 2015.11

Language：English   Presentation type：Symposium, workshop panel (public)  

Venue：Fukuoka   Country：Japan  

Event date： 2015.1

Language：English   Presentation type：Symposium, workshop panel (public)  

Venue：東京大学医科学研究所   Country：Japan  

Cellular responses are regulated by signals that are transmitted in multiple omic layers (trans-omic layers), such as epigenome, transcriptome, proteome and metabolome. Therefore, a new top-down approach combined with multiple omic layers will be necessary for understanding of the entire picture of the cellular responses. We call this strategy as “trans-omic analysis”. Since molecular interactions among trans-omic layers are mutually connected, it is almost impossible to reconstruct trans-omic network from the data with different conditions. Therefore, tans-omic analysis requires global, multiple omic measurements under the same experimental condition (1). In this study, we measured time course data from the metabolome and phosphoproteome of acute insulin action (<60 minutes) under the same experimental condition in Fao cells, which consisted of 304 metabolites and 7,277 phosphorylated residues on 3,458 proteins (2). We subsequently developed a new method to integrate multi omic data using multiple databases. We found that an insulin signal flows through a network that is consistent with 44 changed metabolites which are the targets of acute insulin action, 26 phosphorylated responsible metabolic enzymes which potentially regulate the amount of changed metabolites, and 13 protein kinases which potentially phosphorylate phosphorylated responsible metabolic enzymes (fig). Moreover, 35 metabolites out of 44 changed metabolites were identified as allosteric effectors which potentially regulate the activity of responsible metabolic enzymes. We then, focused on the conversion of fructose-1-phosphate to fructose-1,6-bisphospate which is one of the important steps of glycogenesis pathway, and constructed a kinetic model of it. As results of analysis, we found that a novel phosphorylation site and some allosteric effectors are important for the regulation.

Language：Japanese   Presentation type：Symposium, workshop panel (public)  

Venue：筑波   Country：Japan  

生物は限られた少数の分子によって制御されるのではなく、DNA（ゲノム）やRNA（トランスクリプトーム）、タンパク質（プロテオーム）、代謝物（メタボローム）など、複数のオミクス階層にまたがるネットワークによって制御されている。つまり、細胞（生物）の理解には複数のオミクス階層を「統合」し、「理解」する必要がある（トランスオミクス解析）。一方で、近年の網羅的計測技術の進歩により、各階層において高精度の網羅的データが取得できるようになってきた。つまり、ようやくトランスオミクス解析が行える環境が整ってきたと考えられる。我々は、主にリン酸化シグナルによって代謝が調節されると考えられる短時間（1時間）のインスリン応答に注目し、同一条件で刺激した細胞からリン酸化プロテオー
ム（九大、中山・松本先生）とメタボローム（慶応、曽我先生）を測定して頂き、トランスオミクス解析を行った。実験データと3 つのデータベース（KEGG, NetPhorest,BRENDA）を用いることで、主観を排除した解析を行い、インスリンの入力から代謝制御までのネットワークを推定することに成功した。トランスオミクス解析で予測された新規の代謝制御に注目して検証実験を行ったところ、リン酸化によって制御された代謝酵素による、新規の代謝調節経路を見出した。この結果、本手法が十分な予測精度を持つことが示された。今後、このようなトランスオミクス解析
が、複数のオミクス解析のアプリケーションになることを期待する。

Language：English   Presentation type：Symposium, workshop panel (public)  

Venue：横浜   Country：Japan  

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：愛媛   Country：Japan  

実験とコンピュータ解析を合わせたシステム生物学により、直観や経験では分からなかった生物の特性が明らかになってきています。現在我々は、システム生物学的アプローチを用いてインスリン作用の研究を行っています。インスリンはリン酸化や遺伝子発現、代謝などの「階層」を介して細胞の応答を制御しています。また、血中インスリンの時間パターンはいくつかのパターンからなることが知られており、生体のホメオスタシスに重要であることが知られています。我々は、「階層」をまたぐ全体像を明らかにするトップダウンと、時間パターンに注目した作用メカニズムを明らかにするボトムアップのアプローチを用いて研究を行っています。本講演では、これらの2つの研究を中心に、我々が現在行っているいくつかの研究内容についてご紹介したいと思います。

Language：Japanese  

Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)  

Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)  

Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)  

Language：English  

During recent years, it has become clearer that temporal patterns of stimuli and molecules are important in the regulation of cellular functions. For example, many hormones show distinct temporal patterns in vivo, which are important for homeostasis. One of the unique characteristics of cellular signaling pathways is that a common signaling pathway can selectively regulate multiple cellular functions depending on their temporal patterns. Therefore, one of the major advances in understanding the "pathogenic dysregulation of signaling" is to reveal the temporal coding mechanisms of signaling pathways related to pathogenesis. A systems biological approach combining experiments and computational analysis is necessary to address this issue. In this chapter, we will introduce the concept that the insulin- dependent AKT pathway uses temporal patterns multiplexing for selective regulation of signaling molecules and metabolites, which depend on their network structures and kinetics, using rat hepatoma Fao cells. These results represent a huge step forward in our understanding of insulin actions and type II diabetes mellitus .

DOI： 10.1007/978-4-431-55561-2_7

Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)  

Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)  

Type：Competition, symposium, etc. 

Number of participants：100

Type：Peer review 

Number of peer-reviewed articles in foreign language journals：3

Type：Competition, symposium, etc. 

Type：Peer review 

Number of peer-reviewed articles in foreign language journals：3

Type：Peer review 

Number of peer-reviewed articles in foreign language journals：1

Type：Competition, symposium, etc.