Proteomics in nutrition research: principles, technologies and applications

Abstract

The global profiling of the whole protein complement of the genome expressed in a particular cell or organ, or in plasma or serum, makes it possible to identify biomarkers that respond to alterations in diet or to treatment, and that may have predictive value for the modelling of biological processes. Proteomics has not yet been applied on a large scale in nutritional studies, yet it has advantages over transcriptome profiling techniques in that it directly assesses the entities that carry out the biological functions. The present review summarizes the different approaches in proteomics research, with special emphasis on the current technical ‘workhorses’: two-dimensional (2D)-PAGE with immobilized pH gradients and protein identification by MS. Using a work-flow approach, we provide information and advice on sample handling and preparation, protein solubilization and pre-fractionation, protein separation by 2D-PAGE, detection and quantification via computer-assisted analysis of gels, and protein identification and characterization techniques by means of MS. Examples from nutritional studies employing proteomics are provided to demonstrate not only the advantages but also the limitations of current proteome analysis platforms.

Variation in protein levels obtained from human blood cells and biofluids for platelet, peripheral blood mononuclear cell, plasma, urine and saliva proteomics

“…Proteomics is emerging as a valuable tool in nutritional and clinical research [6,8,13,21,23,24,27]. Proteome analysis from easily-accessible human body fluids and blood cells can identify thousands of proteins, which may provide valuable new biomarkers for health and disease progression and enable discovery of mechanisms of action of food components [24].…”

Dietary fatty acids affecting hepatic metabolism and atherosclerosis – mechanisms unravelled using a proteomics approach

“…In particular the combination of proteomics data with physiological parameters, using correlation analysis as a statistical tool, will help to understand how dietary components regulate several metabolic processes (de Roos et al, 2005a;de Roos et al, 2005b;Arbones-Mainar et al, 2007;Milner, 2007). Current proteomics approaches in nutrition research mainly include the use of protein separation, visualisation and identification by 2D gel electrophoresis combined with mass spectrometry (Fuchs et al, 2005). Despite its limited ability to detect regulation of low abundant proteins, this approach has already provided valuable insights in the effects of several dietary interventions on (relatively abundant) proteins involved in the regulation of glucose and fatty acid metabolism, oxidative stress, and the redox regulation.…”

“…The multiple components of the proteome can be analysed by mass spectrometry (MS) after an evaporation of peptides and protein by electrospray ionisation (ESI) or matrix-assisted laser desorption ionisation (MALDI) technologies . Classical two-dimensional (2D) gel electrophoresis, where proteins are separated according to charge and molecular weight, coupled with protein spot analysis by mass spectrometry, is still the most widely used technical approach in proteomics to identify changes in individual proteins of tissues, cells and biofluids upon nutritional intervention Fuchs et al, 2005). While this method is one of the most labourintensive of the several types of 2D separation methods available, it actually yields a physical separation of intact polypeptides from each other, providing information about molecular weight and iso-electric point.…”

Harnessing Nutrigenomics: Development of web-based communication, databases, resources, and tools

“…NuGO already has begun this process with ongoing meetings and discussions among European scientists at different institutions. This effort has generated three best practices papers in transcriptomics (Garosi et al, 2005), metabolomics , and proteomics (Fuchs et al, 2005). These papers and recommendations focus on the technologies of each discipline rather than experimental designs for human, laboratory animal, cell culture experiments, or for pre-and post-experiment biocomputation methods.…”