Literature DB >> 26893027

A Novel Systems-Biology Algorithm for the Analysis of Coordinated Protein Responses Using Quantitative Proteomics.

Fernando García-Marqués1, Marco Trevisan-Herraz1, Sara Martínez-Martínez1, Emilio Camafeita1, Inmaculada Jorge1, Juan Antonio Lopez1, Nerea Méndez-Barbero1, Simón Méndez-Ferrer1, Miguel Angel Del Pozo1, Borja Ibáñez1, Vicente Andrés1, Francisco Sánchez-Madrid1, Juan Miguel Redondo1, Elena Bonzon-Kulichenko2, Jesús Vázquez2.   

Abstract

The coordinated behavior of proteins is central to systems biology. However, the underlying mechanisms are poorly known and methods to analyze coordination by conventional quantitative proteomics are still lacking. We present the Systems Biology Triangle (SBT), a new algorithm that allows the study of protein coordination by pairwise quantitative proteomics. The Systems Biology Triangle detected statistically significant coordination in diverse biological models of very different nature and subjected to different kinds of perturbations. The Systems Biology Triangle also revealed with unprecedented molecular detail an array of coordinated, early protein responses in vascular smooth muscle cells treated at different times with angiotensin-II. These responses included activation of protein synthesis, folding, turnover, and muscle contraction - consistent with a differentiated phenotype-as well as the induction of migration and the repression of cell proliferation and secretion. Remarkably, the majority of the altered functional categories were protein complexes, interaction networks, or metabolic pathways. These changes could not be detected by other algorithms widely used by the proteomics community, and the vast majority of proteins involved have not been described before to be regulated by AngII. The unique capabilities of The Systems Biology Triangle to detect functional protein alterations produced by the coordinated action of proteins in pairwise quantitative proteomics experiments make this algorithm an attractive choice for the biological interpretation of results on a routine basis.
© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

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Year:  2016        PMID: 26893027      PMCID: PMC4858952          DOI: 10.1074/mcp.M115.055905

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


  123 in total

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