Literature DB >> 18550893

Comparative phosphoproteomics of zebrafish Fyn/Yes morpholino knockdown embryos.

Simone Lemeer1, Chris Jopling, Joost Gouw, Shabaz Mohammed, Albert J R Heck, Monique Slijper, Jeroen den Hertog.   

Abstract

The coordinated movement of cells is indispensable for normal vertebrate gastrulation. Several important players and signaling pathways have been identified in convergence and extension (CE) cell movements during gastrulation, including non-canonical Wnt signaling. Fyn and Yes, members of the Src family of kinases, are key regulators of CE movements as well. Here we investigated signaling pathways in early development by comparison of the phosphoproteome of wild type zebrafish embryos with Fyn/Yes knockdown embryos that display specific CE cell movement defects. For quantitation we used differential stable isotope labeling by reductive amination of peptides. Equal amounts of labeled peptides from wild type and Fyn/Yes knockdown embryos were mixed and analyzed by on-line reversed phase TiO(2)-reversed phase LC-MS/MS. Phosphorylated and non-phosphorylated peptides were quantified, and significant changes in protein expression and/or phosphorylation were detected. We identified 348 phosphoproteins of which 69 showed a decrease in phosphorylation in Fyn/Yes knockdown embryos and 72 showed an increase in phosphorylation. Among these phosphoproteins were known regulators of cell movements, including Adducin and PDLIM5. Our results indicate that quantitative phosphoproteomics combined with morpholino-mediated knockdowns can be used to identify novel signaling pathways that act in zebrafish development in vivo.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18550893     DOI: 10.1074/mcp.M800081-MCP200

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  16 in total

1.  Autophosphorylation and ATM activation: additional sites add to the complexity.

Authors:  Sergei V Kozlov; Mark E Graham; Burkhard Jakob; Frank Tobias; Amanda W Kijas; Marcel Tanuji; Philip Chen; Phillip J Robinson; Gisela Taucher-Scholz; Keiji Suzuki; Sairai So; David Chen; Martin F Lavin
Journal:  J Biol Chem       Date:  2010-12-13       Impact factor: 5.157

2.  Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics.

Authors:  Paul J Boersema; Reinout Raijmakers; Simone Lemeer; Shabaz Mohammed; Albert J R Heck
Journal:  Nat Protoc       Date:  2009       Impact factor: 13.491

3.  In-depth qualitative and quantitative profiling of tyrosine phosphorylation using a combination of phosphopeptide immunoaffinity purification and stable isotope dimethyl labeling.

Authors:  Paul J Boersema; Leong Yan Foong; Vanessa M Y Ding; Simone Lemeer; Bas van Breukelen; Robin Philp; Jos Boekhorst; Berend Snel; Jeroen den Hertog; Andre B H Choo; Albert J R Heck
Journal:  Mol Cell Proteomics       Date:  2009-09-21       Impact factor: 5.911

4.  Quantitative proteomics by metabolic labeling of model organisms.

Authors:  Joost W Gouw; Jeroen Krijgsveld; Albert J R Heck
Journal:  Mol Cell Proteomics       Date:  2009-11-19       Impact factor: 5.911

Review 5.  Stable isotope dimethyl labelling for quantitative proteomics and beyond.

Authors:  Jue-Liang Hsu; Shu-Hui Chen
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2016-10-28       Impact factor: 4.226

6.  Proteomics of Xenopus development.

Authors:  Liangliang Sun; Matthew M Champion; Paul W Huber; Norman J Dovichi
Journal:  Mol Hum Reprod       Date:  2015-09-22       Impact factor: 4.025

7.  N,N-dimethyl leucines as novel isobaric tandem mass tags for quantitative proteomics and peptidomics.

Authors:  Feng Xiang; Hui Ye; Ruibing Chen; Qiang Fu; Lingjun Li
Journal:  Anal Chem       Date:  2010-04-01       Impact factor: 6.986

8.  Establishment of Dimethyl Labeling-based Quantitative Acetylproteomics in Arabidopsis.

Authors:  Shichang Liu; Fengchao Yu; Zhu Yang; Tingliang Wang; Hairong Xiong; Caren Chang; Weichuan Yu; Ning Li
Journal:  Mol Cell Proteomics       Date:  2018-02-13       Impact factor: 5.911

Review 9.  Systematizing serendipity for cardiovascular drug discovery.

Authors:  Peter J Schlueter; Randall T Peterson
Journal:  Circulation       Date:  2009-07-21       Impact factor: 29.690

10.  Protein-protein interaction network of the marine microalga Tetraselmis subcordiformis: prediction and application for starch metabolism analysis.

Authors:  Chaofan Ji; Xupeng Cao; Changhong Yao; Song Xue; Zhilong Xiu
Journal:  J Ind Microbiol Biotechnol       Date:  2014-05-31       Impact factor: 3.346

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.