Literature DB >> 25131207

Reconstruction of insulin signal flow from phosphoproteome and metabolome data.

Katsuyuki Yugi1, Hiroyuki Kubota2, Yu Toyoshima1, Rei Noguchi3, Kentaro Kawata1, Yasunori Komori1, Shinsuke Uda4, Katsuyuki Kunida1, Yoko Tomizawa1, Yosuke Funato5, Hiroaki Miki5, Masaki Matsumoto6, Keiichi I Nakayama6, Kasumi Kashikura7, Keiko Endo7, Kazutaka Ikeda7, Tomoyoshi Soga7, Shinya Kuroda8.   

Abstract

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.
Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

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Year:  2014        PMID: 25131207     DOI: 10.1016/j.celrep.2014.07.021

Source DB:  PubMed          Journal:  Cell Rep            Impact factor:   9.423


  22 in total

1.  Technical Challenges in Mass Spectrometry-Based Metabolomics.

Authors:  Fumio Matsuda
Journal:  Mass Spectrom (Tokyo)       Date:  2016-11-25

2.  Biophysics at Kyushu University.

Authors:  Ryo Akiyama; Masahiko Annaka; Daisuke Kohda; Hiroyuki Kubota; Yusuke Maeda; Nobuaki Matsumori; Daisuke Mizuno; Norio Yoshida
Journal:  Biophys Rev       Date:  2020-02-17

3.  Next-Generation Genome-Scale Models Incorporating Multilevel 'Omics Data: From Yeast to Human.

Authors:  Tunahan Çakır; Emel Kökrek; Gülben Avşar; Ecehan Abdik; Pınar Pir
Journal:  Methods Mol Biol       Date:  2019

4.  Distinct signalling properties of insulin receptor substrate (IRS)-1 and IRS-2 in mediating insulin/IGF-1 action.

Authors:  Atefeh Rabiee; Marcus Krüger; Jacob Ardenkjær-Larsen; C Ronald Kahn; Brice Emanuelli
Journal:  Cell Signal       Date:  2018-03-14       Impact factor: 4.315

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

Authors:  Akira Terakawa; Yanhui Hu; Toshiya Kokaji; Katsuyuki Yugi; Keigo Morita; Satoshi Ohno; Yifei Pan; Yunfan Bai; Andrey A Parkhitko; Xiaochun Ni; John M Asara; Martha L Bulyk; Norbert Perrimon; Shinya Kuroda
Journal:  iScience       Date:  2022-04-08

6.  A rule-based model of insulin signalling pathway.

Authors:  Barbara Di Camillo; Azzurra Carlon; Federica Eduati; Gianna Maria Toffolo
Journal:  BMC Syst Biol       Date:  2016-06-01

Review 7.  Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data.

Authors:  Kansuporn Sriyudthsak; Fumihide Shiraishi; Masami Yokota Hirai
Journal:  Front Mol Biosci       Date:  2016-05-03

8.  Phosphoprotein network analysis of white adipose tissues unveils deregulated pathways in response to high-fat diet.

Authors:  Asfa Alli Shaik; Beiying Qiu; Sheena Wee; Hyungwon Choi; Jayantha Gunaratne; Vinay Tergaonkar
Journal:  Sci Rep       Date:  2016-05-16       Impact factor: 4.379

Review 9.  Metabolic modeling with Big Data and the gut microbiome.

Authors:  Jaeyun Sung; Vanessa Hale; Annette C Merkel; Pan-Jun Kim; Nicholas Chia
Journal:  Appl Transl Genom       Date:  2016-02-05

10.  Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery.

Authors:  Daisuke Saigusa; Yasunobu Okamura; Ikuko N Motoike; Yasutake Katoh; Yasuhiro Kurosawa; Reina Saijyo; Seizo Koshiba; Jun Yasuda; Hozumi Motohashi; Junichi Sugawara; Osamu Tanabe; Kengo Kinoshita; Masayuki Yamamoto
Journal:  PLoS One       Date:  2016-08-31       Impact factor: 3.240

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