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.

One of the unique characteristics of cellular signaling pathways is that a common signaling pathway can selectively regulate multiple cellular functions of a hormone; however, this selective downstream control through a common signaling pathway is poorly understood. Here we show that the insulin-dependent AKT pathway uses temporal patterns multiplexing for selective regulation of downstream molecules. Pulse and sustained insulin stimulations were simultaneously encoded into transient and sustained AKT phosphorylation, respectively. The downstream molecules, including ribosomal protein S6 kinase (S6K), glucose-6-phosphatase (G6Pase), and glycogen synthase kinase-3β (GSK3β) selectively decoded transient, sustained, and both transient and sustained AKT phosphorylation, respectively. Selective downstream decoding is mediated by the molecules' network structures and kinetics. Our results demonstrate that the AKT pathway can multiplex distinct patterns of blood insulin, such as pulse-like additional and sustained-like basal secretions, and the downstream molecules selectively decode secretion patterns of insulin.

TheBiophysical Society of Japan General IncorporatedAssociation this theory however is that the nucleated reaction mechamsm by which amyloid lormaL]on ig be]ieved to oscur results in a very lovv number LonLenti dtion of early aggregates which are rap]dly extended to ioiin amy]o]d t]br]]s This sMiation means that the Loncentrauon of early aggregates ig iery low at the time when they aTL supposedTy it theu most toxic Here we adol]t a novel exph"t simulataon gtrategy to examine a kinetTe iegLme invoTvLng nucleated growth conibined wth fibHl fragmentAtion unde-xhJLh this sTtuat]on can be ieveised so as to produLe a high nurnber concentration et small on path-ay toxic aggregates Dependent upon the rate of fragmentation the time scale ior generation ot toxic ear]y aggregdtes may be LoupTed uncoupled or digaggociated from thc tirne gcale for the dppedranLe of amylotd fibnls As such we designate the rnodel as subtle Furthermore the model presents itself ag a bmchernical s-itch transitronmg bet"een modcg oi amyloid induLed Lell death dependent upon eTther specific amyloid toxicity or non specific solid mass mduced tissue damage vvhcn thL rLaLting mLdium has a gpatial Lonstrain on the miLrosLopic level such as the intraeellu]Ar environment tractal kinetiLs oeLur ab a resutt of the hLterogeneDub distnbution of the reaLtantb For the Ldbe of batLh redctions fractal k]netiLs gives a time dependent reaLt]on rate Loeffitient whiLh is d constant in cldssictilkrneucs In this study we investigate howu the enzymc icaLLiong trangrtg bet"een the clasgical and frac{al kinetics by the effect of mo]eeular erowd]ng Lattice Monte Carlo rnethod was used te calculate the M]chaels Mcnten typc LnLyrne reaLtions and the moletulac crowding was exprebsed as an obstructing random cluster on the cakulatmg tattiLe Analysis based on the t"o dimenstonal lattlce whlch assumes an entyme rcaction over thc plasma membrane sho"s thit as the obgtac]L densitieynaLAses the rLaction iate Loetfiuent beLomeb time dependent Thc iLgults indiLate that thL fiaLta] kmetiLs o"urs in enzyme reactson under molccularaowdmgLffLct 3P237 fieeItnthSEetitmsfihi[:lk#Y62tsffcakl:fott6AS-Pattern foimatien Jn a couple of dendritie paths correlated-ith a history of signa] propagaUon Ikuko Motoike (1) {ri) PRSTO JST TCems Kvoto Vniv) Tn hving s)stems the branchmg structuies are observed widely m open systems in neurong bleod vessels lung tubes ot shme molds tiees baLtellal Lelenies and so on In these branehing structurcs branching paths olten dclorm dcpending on a htstoiy of tsignal propdgation on branches In ordei to grasp a signal processing function with characteristic geometncal paths I adopted the system ]n whiLh path formation dynarnics correlates with signal piopagation In this btudy the model mvokeb the brallLh geneiation dynamics and the signal propagatien dynarmLs whLrc an intuaLtion bLtwLen two dynamics roughty obeys the law of increasing returns As the former dynarnics I have proposed a simplL discrLtiied LLtlultr iutematDn (CA) model for the branchmg pattern formation...

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

Highlights d Enlarged thymus in K5D1 mice produces immunocompetent and self-tolerant T cells d Enlarged thymus in K5D1 mice enables proteomic analysis of cTECs and mTECs d Trans-omics profiles identify signature molecules that characterize cTECs and mTECs d b5t deficiency specifically affects proteasomal subunit composition in cTECs

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.

Oral glucose ingestion induces systemic changes of many blood metabolites related not only to glucose, but also other metabolites such as amino acids and lipids through many blood hormones. However, the detailed temporal changes in the concentrations of comprehensive metabolites and hormones over a long time by oral glucose ingestion are uncharacterized. We measured 83 metabolites and 7 hormones in 20 healthy human subjects in response to glucose ingestion. We characterized temporal patterns of blood molecules by four features: (i) the decomposability into “amplitude” and “rate” components, (ii) the similarity of temporal patterns among individuals, (iii) the relation of molecules over time among individuals, and (iv) the similarity of temporal patterns among molecules. Glucose and glucose metabolism-related hormones indicated a rapid increase, and citrulline and lipids, which indicated a rapid decrease, returned to fasting levels faster than amino acids. Compared to glucose metabolism-related molecules and lipids, amino acids showed similar temporal patterns among individuals. The four features of temporal patterns of blood molecules by oral glucose ingestion characterize the differences among individuals and among molecules.

Summary 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.