The key components to the molecular understanding of the pathophysiology of various forms of heart failure involve global and/or large-scale identifications of proteins, their patterns of expression, posttranslational modifications, and functional characterization. Particularly, proteins involved in the induction of cardiac (mal)adaptive hypertrophic growth, interstitial fibrosis, and contractile dysfunction are of interest. In general, with the accumulation of vast amounts of DNA sequences in databases, researchers have become aware that merely having complete sequences of genomes and transcriptional changes for thousands of genes simultaneously will not be sufficient to elucidate, in molecular terms, the etiology and pathophysiology of cardiovascular disease. In the last decade, a new technology called proteomics has become available that allows biological and (patho)physiological questions to be approached exclusively from the protein perspective. Proteomics may enable us to map the entire complement of proteins expressed by the heart at any time and condition. This approach creates the unique possibility to identify, by differential analysis, protein alterations associated with the etiology of heart disease and its progression, outcome, and response to therapy. To illustrate the true power of proteomics, most of the currently available methodologies are first reviewed, including their limitations. This review also deals with the current status and the perspectives of proteomics applications in research on heart failure in general. Furthermore, examples of our recent data on global protein profiling of the pressure-overloaded rat right ventricle and of endothelin-1-stimulated cultures of neonatal rat cardiac myocytes are provided. The last section is devoted to the continuous advances in proteomic technologies, including protein separation methods, mass spectrometric instrumentation, computational analysis, and bioinformatic tools, together with integrative databases.

Recent developments in proteomics.Implications for the study of cardiac hypertrophy and failure

AGNETTI, GIULIO;GUARNIERI, CARLO;CALDARERA, CLAUDIO MARCELLO;
2006

Abstract

The key components to the molecular understanding of the pathophysiology of various forms of heart failure involve global and/or large-scale identifications of proteins, their patterns of expression, posttranslational modifications, and functional characterization. Particularly, proteins involved in the induction of cardiac (mal)adaptive hypertrophic growth, interstitial fibrosis, and contractile dysfunction are of interest. In general, with the accumulation of vast amounts of DNA sequences in databases, researchers have become aware that merely having complete sequences of genomes and transcriptional changes for thousands of genes simultaneously will not be sufficient to elucidate, in molecular terms, the etiology and pathophysiology of cardiovascular disease. In the last decade, a new technology called proteomics has become available that allows biological and (patho)physiological questions to be approached exclusively from the protein perspective. Proteomics may enable us to map the entire complement of proteins expressed by the heart at any time and condition. This approach creates the unique possibility to identify, by differential analysis, protein alterations associated with the etiology of heart disease and its progression, outcome, and response to therapy. To illustrate the true power of proteomics, most of the currently available methodologies are first reviewed, including their limitations. This review also deals with the current status and the perspectives of proteomics applications in research on heart failure in general. Furthermore, examples of our recent data on global protein profiling of the pressure-overloaded rat right ventricle and of endothelin-1-stimulated cultures of neonatal rat cardiac myocytes are provided. The last section is devoted to the continuous advances in proteomic technologies, including protein separation methods, mass spectrometric instrumentation, computational analysis, and bioinformatic tools, together with integrative databases.
2006
M.J.Faber;G.Agnetti;K.Bezstarosti;I.M.Lankhuizen; M.Dalinghaus;C.Guarnieri;C.M.Caldarera;W.A.Heilbing; J.M.J.Lamers
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/27244
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