Following is a description of a recently published research paper recommended by a scientist involved in integrated biology. The recommender, Mark Duncan, is director of the University of Colorado Cancer Center Proteomics Core at the University of Colorado Health Sciences Center in
For a complete list of this month's recommended papers, read Genome Technology, a GenomeWeb News sister publication.
"Temporal analysis of phosphotyrosine-dependent signaling networks by quantitative proteomics," Blagoy Blagoev, Shao-En Ong, Irina Kratchmarova, and Matthias Mann. Nature Biotechnology. 2004; 22 (9): 1139-1145.
"The authors, from the University of Southern Denmark, say they have 'developed a mass spectrometric method that converts temporal changes to differences in peptide isotopic abundance' in order to better understand the dynamics of the phosphotyrosine-based signaling that takes place in early growth factor stimulation, according to the abstract.
"To do this, they metabolically encoded the proteomes of several cell populations 'with different stable isotopic forms of arginine' and then stimulated each population with epidermal growth factor for varying time periods. After quantifying the arginine-containing peptides and combining two experiments for more profiles, 'we identified 81 signaling proteins, including virtually all known epidermal growth factor receptor substrates, 31 novel effectors, and the time course of their activation upon epidermal growth factor stimulation,' the authors state. They contend that these activation profiles will prove critical to a systems biology approach to modeling signaling networks.
"According to recommender Mark Duncan, 'The work is thoughtful, thorough, and elegant, but most importantly, it demonstrates some of the potential of proteomics methods when skillful and expertly implemented. Techniques such as immunoprecipitation, Western blotting, stable isotope label incorporation, and qualitative and quantitative LC-tandem mass spectrometry are combined to deliver some high-quality hypothesis-generating data. It is a very fine piece of work.'"