Literature DB >> 19949701

Use of a label-free quantitative platform based on MS/MS average TIC to calculate dynamics of protein complexes in insulin signaling.

Xuemei Yang1, Adam Friedman, Shailender Nagpal, Norbert Perrimon, John M Asara.   

Abstract

A label-free quantification strategy including the development of in-house software (NakedQuant) to calculate the average TIC across all spectral counts in tandem affinity purification (TAP)-tagging liquid chromatography-mass spectrometry MS/MS (LC/MS/MS) experiments was applied to a large-scale study of protein complexes in the MAPK portion of the insulin signaling pathway from Drosophila cells. Dynamics were calculated under basal and stimulating conditions as fold changes. These experiments were performed in the context of a core service model with the user performing the TAP immunoprecipitation and the MS core performing the MS and informatics stops. The MS strategy showed excellent coverage of known components in addition to potentially novel interactions.

Entities:  

Keywords:  LC/MS/MS; average TIC; networks; protein–protein interaction; proteomics; quantification; signal transduction; spectral counting

Mesh:

Substances:

Year:  2009        PMID: 19949701      PMCID: PMC2777340     

Source DB:  PubMed          Journal:  J Biomol Tech        ISSN: 1524-0215


  3 in total

1.  A label-free quantification method by MS/MS TIC compared to SILAC and spectral counting in a proteomics screen.

Authors:  John M Asara; Heather R Christofk; Lisa M Freimark; Lewis C Cantley
Journal:  Proteomics       Date:  2008-03       Impact factor: 3.984

2.  Functional organization of the yeast proteome by systematic analysis of protein complexes.

Authors:  Anne-Claude Gavin; Markus Bösche; Roland Krause; Paola Grandi; Martina Marzioch; Andreas Bauer; Jörg Schultz; Jens M Rick; Anne-Marie Michon; Cristina-Maria Cruciat; Marita Remor; Christian Höfert; Malgorzata Schelder; Miro Brajenovic; Heinz Ruffner; Alejandro Merino; Karin Klein; Manuela Hudak; David Dickson; Tatjana Rudi; Volker Gnau; Angela Bauch; Sonja Bastuck; Bettina Huhse; Christina Leutwein; Marie-Anne Heurtier; Richard R Copley; Angela Edelmann; Erich Querfurth; Vladimir Rybin; Gerard Drewes; Manfred Raida; Tewis Bouwmeester; Peer Bork; Bertrand Seraphin; Bernhard Kuster; Gitte Neubauer; Giulio Superti-Furga
Journal:  Nature       Date:  2002-01-10       Impact factor: 49.962

3.  A functional RNAi screen for regulators of receptor tyrosine kinase and ERK signalling.

Authors:  Adam Friedman; Norbert Perrimon
Journal:  Nature       Date:  2006-11-01       Impact factor: 49.962

  3 in total
  5 in total

1.  Phosphoinositide 3-kinase pathway activation in phosphate and tensin homolog (PTEN)-deficient prostate cancer cells is independent of receptor tyrosine kinases and mediated by the p110beta and p110delta catalytic subunits.

Authors:  Xinnong Jiang; Sen Chen; John M Asara; Steven P Balk
Journal:  J Biol Chem       Date:  2010-03-15       Impact factor: 5.157

2.  Using tandem mass spectrometry in targeted mode to identify activators of class IA PI3K in cancer.

Authors:  Xuemei Yang; Alexa B Turke; Jie Qi; Youngchul Song; Brent N Rexer; Todd W Miller; Pasi A Jänne; Carlos L Arteaga; Lewis C Cantley; Jeffrey A Engelman; John M Asara
Journal:  Cancer Res       Date:  2011-07-20       Impact factor: 12.701

3.  Label-free proteomic identification of endogenous, insulin-stimulated interaction partners of insulin receptor substrate-1.

Authors:  Thangiah Geetha; Paul Langlais; Moulun Luo; Rebekka Mapes; Natalie Lefort; Shu-Chuan Chen; Lawrence J Mandarino; Zhengping Yi
Journal:  J Am Soc Mass Spectrom       Date:  2011-01-29       Impact factor: 3.109

4.  A Cross-Species Study of PI3K Protein-Protein Interactions Reveals the Direct Interaction of P85 and SHP2.

Authors:  Susanne B Breitkopf; Xuemei Yang; Michael J Begley; Meghana Kulkarni; Yu-Hsin Chiu; Alexa B Turke; Jessica Lauriol; Min Yuan; Jie Qi; Jeffrey A Engelman; Pengyu Hong; Maria I Kontaridis; Lewis C Cantley; Norbert Perrimon; John M Asara
Journal:  Sci Rep       Date:  2016-02-03       Impact factor: 4.379

5.  Serial-omics characterization of equine urine.

Authors:  Min Yuan; Susanne B Breitkopf; John M Asara
Journal:  PLoS One       Date:  2017-10-13       Impact factor: 3.240

  5 in total

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