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.”
Professor of Medicine
Director, University of Colorado Cancer Center Proteomics Core
University of Colorado Health Sciences Center
In silico simulation of biological network dynamics
Lukasz Salwinski and David Eisenberg.
Nature Biotechnology. 2004; 22 (9): 1017-1019.
In this paper, the authors present an approach to simulating biological networks using field programmable gate arrays, whose parallel architecture allows for more realistic simulation of the reaction steps in biological networks, according to the paper’s abstract. They say that in the past such large-scale simulations have been limited both by data availability and by the vast computational demands for the stochastic algorithms needed to model the networks. “With the rise of various ‘omics’ approaches, the limitation of experimental data is being lifted, but the computational demands remain staggering for simulating networks of thousands of reactions involving thousands of reactants,” the authors note. “The problem stems from the sequential nature of microprocessor architecture and the highly parallel nature of biological systems, with the result that simulation times become prohibitively long.” The authors say using FPGAs can improve simulation rates by “at least an order of magnitude” over what conventional microprocessors can achieve.
Research Assistant Professor
Life Sciences Institute
University of Michigan
Transcriptional regulatory code of a eukaryotic genome
Christopher Harbison, Benjamin Gordon, Tong Ihn Lee, Nicola Rinaldi, Kenzie MacIsaac, Timothy Danford, Nancy Hannett, Jean-Bosco Tagne, David Reynolds, Jane Yoo, Ezra Jennings, Julia Zeitlinger, Dmitry Pokholok, Manolis Kellis, Alex Rolfe, Ken Takusagawa, Eric Lander, David Gifford, Ernest Fraenkel, and Richard Young.
Nature. 2004; 431 (02 Sept): 99-104.
The authors report having used the sequence elements bound by regulators in certain circumstances and conserved among yeast strains to construct a map of the transcriptional regulatory code of yeast. They note that comparative genomics has been used to find potential cis-regulatory sequences in the yeast genome based on phylogenetic conservation, but that such studies remain inconclusive as to whether and when transcriptional regulators occupy the discovered binding sites. The paper includes discussion of “the organization of regulatory elements in promoters and the environment-dependent use of these elements by regulators,” according to the abstract. Authors add that “environment-specific use of regulatory elements predicts mechanistic models for the function of a large population of yeast’s transcriptional regulators.”
Dick McCombie recommends this paper for being one of the first real looks at genome-wide regulation of transcription and transcription-factor binding in a eukaryotic organism.
Cold Spring Harbor Laboratory
Peer Review is a forum for scientists to recommend noteworthy recent papers. If you have a recommendation, e-mail it to John MacNeil at [email protected]