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      Phosphoproteomics: new insights into cellular signaling

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      Author(s): 1 , , 1
      Publication date (Electronic):
      Journal: Genome Biology
      Publisher: BioMed Central

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          Abstract

          This article presents a brief review of phosphoproteomics with an emphasis on the biological insights into signaling networks that have been derived so far.

          Abstract

          Developments in the field of phosphoproteomics have been fueled by the need simultaneously to monitor many different phosphoproteins within the signaling networks that coordinate responses to changes in the cellular environment. This article presents a brief review of phosphoproteomics with an emphasis on the biological insights that have been derived so far.

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          Quantitative analysis of complex protein mixtures using isotope-coded affinity tags.

          S P Gygi, B Rist, S Gerber … (1999)
          We describe an approach for the accurate quantification and concurrent sequence identification of the individual proteins within complex mixtures. The method is based on a class of new chemical reagents termed isotope-coded affinity tags (ICATs) and tandem mass spectrometry. Using this strategy, we compared protein expression in the yeast Saccharomyces cerevisiae, using either ethanol or galactose as a carbon source. The measured differences in protein expression correlated with known yeast metabolic function under glucose-repressed conditions. The method is redundant if multiple cysteinyl residues are present, and the relative quantification is highly accurate because it is based on stable isotope dilution techniques. The ICAT approach should provide a widely applicable means to compare quantitatively global protein expression in cells and tissues.
          Article 0 comments Cited 470 times – based on 0 reviews     Review now
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            Causal protein-signaling networks derived from multiparameter single-cell data.

            Karen Sachs, Omar Perez, Dana Pe'er … (2005)
            Machine learning was applied for the automated derivation of causal influences in cellular signaling networks. This derivation relied on the simultaneous measurement of multiple phosphorylated protein and phospholipid components in thousands of individual primary human immune system cells. Perturbing these cells with molecular interventions drove the ordering of connections between pathway components, wherein Bayesian network computational methods automatically elucidated most of the traditionally reported signaling relationships and predicted novel interpathway network causalities, which we verified experimentally. Reconstruction of network models from physiologically relevant primary single cells might be applied to understanding native-state tissue signaling biology, complex drug actions, and dysfunctional signaling in diseased cells.
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              Evolution of protein kinase signaling from yeast to man.

              Gerard Manning, Gregory Plowman, Tony Hunter … (2002)
              Protein phosphorylation controls many cellular processes, especially those involved in intercellular communication and coordination of complex functions. To explore the evolution of protein phosphorylation, we compared the protein kinase complements ('kinomes') of budding yeast, worm and fly, with known human kinases. We classify kinases into putative orthologous groups with conserved functions and discuss kinase families and pathways that are unique, expanded or lost in each lineage. Fly and human share several kinase families involved in immunity, neurobiology, cell cycle and morphogenesis that are absent from worm, suggesting that these functions might have evolved after the divergence of nematodes from the main metazoan lineage.
              Article 0 comments Cited 283 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Genome Biol
                Title: Genome Biology
                Publisher: BioMed Central (London )
                ISSN (Print): 1465-6906
                ISSN (Electronic): 1465-6914
                Publication date (Print): 2005
                Publication date (Electronic): 17 August 2005
                Volume: 6
                Issue: 9
                Page: 230
                Affiliations
                [1 ]Department of Pharmacology and the Alliance for Cellular Signaling, University of Texas Southwestern Medical Center, Dallas, TX 75390-9041, USA
                Article
                Publisher ID: gb-2005-6-9-230
                DOI: 10.1186/gb-2005-6-9-230
                PMC ID: 1242200
                PubMed ID: 16168091
                SO-VID: 7cdf5b5f-f644-45a8-8584-a547d963f3e9
                Copyright © Copyright © 2005 BioMed Central Ltd
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                Subject: Review

                ScienceOpen disciplines: Genetics
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                ScienceOpen disciplines: Genetics

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