Literature DB >> 26280412

High-throughput phosphoproteomics reveals in vivo insulin signaling dynamics.

Sean J Humphrey1, S Babak Azimifar1, Matthias Mann1.   

Abstract

Mass spectrometry has enabled the study of cellular signaling on a systems-wide scale, through the quantification of post-translational modifications, such as protein phosphorylation. Here we describe EasyPhos, a scalable phosphoproteomics platform that now allows rapid quantification of hundreds of phosphoproteomes in diverse cells and tissues at a depth of >10,000 sites. We apply this technology to generate time-resolved maps of insulin signaling in the mouse liver. Our results reveal that insulin affects ~10% of the liver phosphoproteome and that many known functional phosphorylation sites, and an even larger number of unknown sites, are modified at very early time points (<15 s after insulin delivery). Our kinetic data suggest that the flow of signaling information from the cell surface to the nucleus can occur on very rapid timescales of less than 1 min in vivo. EasyPhos facilitates high-throughput phosphoproteomics studies, which should improve our understanding of dynamic cell signaling networks and how they are regulated and dysregulated in disease.

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Year:  2015        PMID: 26280412     DOI: 10.1038/nbt.3327

Source DB:  PubMed          Journal:  Nat Biotechnol        ISSN: 1087-0156            Impact factor:   54.908


  31 in total

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Authors:  Judit Villén; Sean A Beausoleil; Scott A Gerber; Steven P Gygi
Journal:  Proc Natl Acad Sci U S A       Date:  2007-01-22       Impact factor: 11.205

2.  Phosphorylation and regulation of Akt/PKB by the rictor-mTOR complex.

Authors:  D D Sarbassov; David A Guertin; Siraj M Ali; David M Sabatini
Journal:  Science       Date:  2005-02-18       Impact factor: 47.728

3.  A cell-signaling network temporally resolves specific versus promiscuous phosphorylation.

Authors:  Evgeny Kanshin; Louis-Philippe Bergeron-Sandoval; S Sinan Isik; Pierre Thibault; Stephen W Michnick
Journal:  Cell Rep       Date:  2015-02-19       Impact factor: 9.423

4.  Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs.

Authors:  Janine Mok; Philip M Kim; Hugo Y K Lam; Stacy Piccirillo; Xiuqiong Zhou; Grace R Jeschke; Douglas L Sheridan; Sirlester A Parker; Ved Desai; Miri Jwa; Elisabetta Cameroni; Hengyao Niu; Matthew Good; Attila Remenyi; Jia-Lin Nianhan Ma; Yi-Jun Sheu; Holly E Sassi; Richelle Sopko; Clarence S M Chan; Claudio De Virgilio; Nancy M Hollingsworth; Wendell A Lim; David F Stern; Bruce Stillman; Brenda J Andrews; Mark B Gerstein; Michael Snyder; Benjamin E Turk
Journal:  Sci Signal       Date:  2010-02-16       Impact factor: 8.192

5.  Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.

Authors:  Jesper V Olsen; Blagoy Blagoev; Florian Gnad; Boris Macek; Chanchal Kumar; Peter Mortensen; Matthias Mann
Journal:  Cell       Date:  2006-11-03       Impact factor: 41.582

6.  Functional characterization of cancer-associated Gab1 mutations.

Authors:  C Ortiz-Padilla; D Gallego-Ortega; B C Browne; F Hochgräfe; C E Caldon; R J Lyons; D R Croucher; D Rickwood; C J Ormandy; T Brummer; R J Daly
Journal:  Oncogene       Date:  2012-07-02       Impact factor: 9.867

7.  Differential 14-3-3 affinity capture reveals new downstream targets of phosphatidylinositol 3-kinase signaling.

Authors:  Fanny Dubois; Franck Vandermoere; Aurélie Gernez; Jane Murphy; Rachel Toth; Shuai Chen; Kathryn M Geraghty; Nick A Morrice; Carol MacKintosh
Journal:  Mol Cell Proteomics       Date:  2009-08-01       Impact factor: 5.911

8.  Phosphoproteomic analyses reveal novel cross-modulation mechanisms between two signaling pathways in yeast.

Authors:  Stefania Vaga; Marti Bernardo-Faura; Thomas Cokelaer; Alessio Maiolica; Christopher A Barnes; Ludovic C Gillet; Björn Hegemann; Frank van Drogen; Hoda Sharifian; Edda Klipp; Matthias Peter; Julio Saez-Rodriguez; Ruedi Aebersold
Journal:  Mol Syst Biol       Date:  2014-12-09       Impact factor: 11.429

Review 9.  Status of large-scale analysis of post-translational modifications by mass spectrometry.

Authors:  Jesper V Olsen; Matthias Mann
Journal:  Mol Cell Proteomics       Date:  2013-11-01       Impact factor: 5.911

10.  Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ.

Authors:  Jürgen Cox; Marco Y Hein; Christian A Luber; Igor Paron; Nagarjuna Nagaraj; Matthias Mann
Journal:  Mol Cell Proteomics       Date:  2014-06-17       Impact factor: 5.911

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  155 in total

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Authors:  Sachin Khurana; Michael J Coffey; Alan John; Alessandro D Uboldi; My-Hang Huynh; Rebecca J Stewart; Vern B Carruthers; Christopher J Tonkin; Ethan D Goddard-Borger; Nichollas E Scott
Journal:  J Biol Chem       Date:  2018-12-04       Impact factor: 5.157

2.  Positive-unlabeled ensemble learning for kinase substrate prediction from dynamic phosphoproteomics data.

Authors:  Pengyi Yang; Sean J Humphrey; David E James; Yee Hwa Yang; Raja Jothi
Journal:  Bioinformatics       Date:  2015-09-22       Impact factor: 6.937

Review 3.  A Biologist's Field Guide to Multiplexed Quantitative Proteomics.

Authors:  Corey E Bakalarski; Donald S Kirkpatrick
Journal:  Mol Cell Proteomics       Date:  2016-02-12       Impact factor: 5.911

4.  Highly reproducible improved label-free quantitative analysis of cellular phosphoproteome by optimization of LC-MS/MS gradient and analytical column construction.

Authors:  Nagib Ahsan; Judson Belmont; Zhuo Chen; James G Clifton; Arthur R Salomon
Journal:  J Proteomics       Date:  2017-06-17       Impact factor: 4.044

5.  Machine Learning of Global Phosphoproteomic Profiles Enables Discrimination of Direct versus Indirect Kinase Substrates.

Authors:  Evgeny Kanshin; Sébastien Giguère; Cheng Jing; Mike Tyers; Pierre Thibault
Journal:  Mol Cell Proteomics       Date:  2017-03-06       Impact factor: 5.911

6.  Afadin is a scaffold protein repressing insulin action via HDAC6 in adipose tissue.

Authors:  Morten Lundh; Patricia Ss Petersen; Marie S Isidor; Dolly Nm Kazoka-Sørensen; Kaja Plucińska; Farnaz Shamsi; Cathrine Ørskov; Marco Tozzi; Erin L Brown; Emil Andersen; Tao Ma; Ulrich Müller; Romain Barrès; Viggo B Kristiansen; Zachary Gerhart-Hines; Yu-Hua Tseng; Brice Emanuelli
Journal:  EMBO Rep       Date:  2019-07-02       Impact factor: 8.807

7.  The bacterial arginine glycosyltransferase effector NleB preferentially modifies Fas-associated death domain protein (FADD).

Authors:  Nichollas E Scott; Cristina Giogha; Georgina L Pollock; Catherine L Kennedy; Andrew I Webb; Nicholas A Williamson; Jaclyn S Pearson; Elizabeth L Hartland
Journal:  J Biol Chem       Date:  2017-08-31       Impact factor: 5.157

8.  Highly Multiplexed Quantitative Mass Spectrometry Analysis of Ubiquitylomes.

Authors:  Christopher M Rose; Marta Isasa; Alban Ordureau; Miguel A Prado; Sean A Beausoleil; Mark P Jedrychowski; Daniel J Finley; J Wade Harper; Steven P Gygi
Journal:  Cell Syst       Date:  2016-09-22       Impact factor: 10.304

9.  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

10.  An Integrative Analysis of the InR/PI3K/Akt Network Identifies the Dynamic Response to Insulin Signaling.

Authors:  Arunachalam Vinayagam; Meghana M Kulkarni; Richelle Sopko; Xiaoyun Sun; Yanhui Hu; Ankita Nand; Christians Villalta; Ahmadali Moghimi; Xuemei Yang; Stephanie E Mohr; Pengyu Hong; John M Asara; Norbert Perrimon
Journal:  Cell Rep       Date:  2016-09-13       Impact factor: 9.423

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