2D-electrophoresis and multiplex immunoassay proteomic analysis of different body fluids and cellular components reveal known and novel markers for extended ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-12

AUTHORS

Freek G Bouwman, Baukje de Roos, Isabel Rubio-Aliaga, L Katie Crosley, Susan J Duthie, Claus Mayer, Graham Horgan, Abigael C Polley, Carolin Heim, Susan LM Coort, Chris T Evelo, Francis Mulholland, Ian T Johnson, Ruan M Elliott, Hannelore Daniel, Edwin CM Mariman

ABSTRACT

BACKGROUND: Proteomic technologies applied for profiling human biofluids and blood cells are considered to reveal new biomarkers of exposure or provide insights into novel mechanisms of adaptation. METHODS: Both a non-targeted (classical 2D-electrophoresis combined with mass spectrometry) as well as a targeted proteomic approach (multiplex immunoassay) were applied to investigate how fasting for 36 h, as compared to 12 h, affects the proteome of platelets, peripheral blood mononuclear cells (PBMC), plasma, urine and saliva collected from ten healthy volunteers. RESULTS: Between-subject variability was highest in the plasma proteome and lowest in the PBMC proteome. Random Forests analysis performed on the entire dataset revealed that changes in the level of the RhoGDI2 protein in PBMC and plasma ApoA4 levels were the two most obvious biomarkers of an extended fasting. Random Forests (RF) analysis of the multiplex immunoassay data revealed leptin and MMP-3 as biomarkers for extended fasting. However, high between-subject variability may have masked the extended fasting effects in the proteome of the biofluids and blood cells. CONCLUSIONS: Identification of significantly changed proteins in biofluids and blood cells using a non-targeted approach, together with the outcome of targeted analysis revealed both known and novel markers for a 36 h fasting period, including the cellular proteins RhoGDI2 and CLIC1, and plasma proteins ApoA4, leptin and MMP-3. The PBMC proteome exhibited the lowest between-subject variability and therefore these cells appear to represent the best biosamples for biomarker discovery in human nutrigenomics. More... »

PAGES

24

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1755-8794-4-24

DOI

http://dx.doi.org/10.1186/1755-8794-4-24

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1000609852

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/21439033


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