Literature DB >> 18489134

Proteomic methodological recommendations for studies involving human plasma, platelets, and peripheral blood mononuclear cells.

Baukje de Roos1, Susan J Duthie, Abigael C J Polley, Francis Mulholland, Freek G Bouwman, Carolin Heim, Garry J Rucklidge, Ian T Johnson, Edwin C Mariman, Hannelore Daniel, Ruan M Elliott.   

Abstract

This study was designed to develop, optimize and validate protocols for blood processing prior to proteomic analysis of plasma, platelets and peripheral blood mononuclear cells (PBMC) and to determine analytical variation of a single sample of depleted plasma, platelet and PBMC proteins within and between four laboratories each using their own standard operating protocols for 2D gel electrophoresis. Plasma depleted either using the Beckman Coulter IgY-12 proteome partitioning kit or the Amersham albumin and IgG depletion columns gave good quality gels, but reproducibility appeared better with the single-use immuno-affinity column. The use of the Millipore Filter Device for protein concentration gave a 16% ( p < 0.005) higher recovery of protein in flow-through sample compared with acetone precipitation. The use of OptiPrep gave the lowest level of platelet contamination (1:0.8) during the isolation of PBMC from blood. Several proteins (among which are alpha-tropomyosin, fibrinogen and coagulation factor XIII A) were identified that may be used as biomarkers of platelet contamination in future studies. When identifying preselected spots, at least three out of the four centers found similar identities for 10 out of the 10 plasma proteins, 8 out of the 10 platelet proteins and 8 out of the 10 PBMC proteins. The discrepancy in spot identifications has been described before and may be explained by the mis-selection of spots due to laboratory-to-laboratory variation in gel formats, low scores on the peptide analysis leading to no or only tentative identifications, or incomplete resolution of different proteins in what appears as a single abundant spot. The average within-laboratory coefficient of variation (CV) for each of the matched spots after automatic matching using either PDQuest or ProteomWeaver software ranged between 18 and 69% for depleted plasma proteins, between 21 and 55% for platelet proteins, and between 22 and 38% for PBMC proteins. Subsequent manual matching improved the CV with on average between 1 and 16%. The average between laboratory CV for each of the matched spots after automatic matching ranged between 4 and 54% for depleted plasma proteins, between 5 and 60% for platelet proteins, and between 18 and 70% for PBMC proteins. This variation must be considered when designing sufficiently powered studies that use proteomics tools for biomarker discovery. The use of tricine in the running buffer for the second dimension appears to enhance the resolution of proteins especially in the high molecular weight range.

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Year:  2008        PMID: 18489134     DOI: 10.1021/pr700714x

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  22 in total

Review 1.  Proteomic approaches to predict bioavailability of fatty acids and their influence on cancer and chronic disease prevention.

Authors:  Baukje de Roos; Donato F Romagnolo
Journal:  J Nutr       Date:  2012-05-30       Impact factor: 4.798

2.  Selectivity of monolithic supports under overloading conditions and their use for separation of human plasma and isolation of low abundance proteins.

Authors:  Marija Brgles; James Clifton; Robert Walsh; Feilei Huang; Marijana Rucevic; Lulu Cao; Douglas Hixson; Egbert Müller; Dj Josic
Journal:  J Chromatogr A       Date:  2010-12-03       Impact factor: 4.759

Review 3.  Long-chain n-3 polyunsaturated fatty acids: new insights into mechanisms relating to inflammation and coronary heart disease.

Authors:  Baukje de Roos; Yiannis Mavrommatis; Ingeborg A Brouwer
Journal:  Br J Pharmacol       Date:  2009-05-05       Impact factor: 8.739

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

Authors:  L Katie Crosley; Susan J Duthie; Abigael C Polley; Freek G Bouwman; Carolin Heim; Francis Mulholland; Graham Horgan; Ian T Johnson; Edwin C Mariman; Ruan M Elliott; Hannelore Daniel; Baukje de Roos
Journal:  Genes Nutr       Date:  2009-04-29       Impact factor: 5.523

5.  A comparative protein analysis of lung cancer, along with three controls using a multidimensional proteomic approach.

Authors:  Mahwish Saleem; Syed K Raza; Syed G Musharraf
Journal:  Exp Biol Med (Maywood)       Date:  2019-01

6.  Anti-platelet effects of olive oil extract: in vitro functional and proteomic studies.

Authors:  Baukje de Roos; Xuguang Zhang; Guillermo Rodriguez Gutierrez; Sharon Wood; Garry J Rucklidge; Martin D Reid; Gary J Duncan; Louise L Cantlay; Garry G Duthie; Niamh O'Kennedy
Journal:  Eur J Nutr       Date:  2011-01-01       Impact factor: 5.614

7.  Transcriptome analysis of peripheral blood mononuclear cells in human subjects following a 36 h fast provides evidence of effects on genes regulating inflammation, apoptosis and energy metabolism.

Authors:  R M Elliott; B de Roos; S J Duthie; F G Bouwman; I Rubio-Aliaga; L K Crosley; C Mayer; A C Polley; C Heim; S L Coort; C T Evelo; F Mulholland; H Daniel; E C Mariman; I T Johnson
Journal:  Genes Nutr       Date:  2014-09-27       Impact factor: 5.523

8.  Dual-color proteomic profiling of complex samples with a microarray of 810 cancer-related antibodies.

Authors:  Christoph Schröder; Anette Jacob; Sarah Tonack; Tomasz P Radon; Martin Sill; Manuela Zucknick; Sven Rüffer; Eithne Costello; John P Neoptolemos; Tatjana Crnogorac-Jurcevic; Andrea Bauer; Kurt Fellenberg; Jörg D Hoheisel
Journal:  Mol Cell Proteomics       Date:  2010-02-16       Impact factor: 5.911

9.  Trichloroacetic acid-induced protein precipitation involves the reversible association of a stable partially structured intermediate.

Authors:  Dakshinamurthy Rajalingam; Charles Loftis; Jiashou J Xu; Thallapuranam Krishnaswamy S Kumar
Journal:  Protein Sci       Date:  2009-05       Impact factor: 6.725

Review 10.  Proteomic and metabolic prediction of response to therapy in gastrointestinal cancers.

Authors:  Ken Herrmann; Axel Walch; Benjamin Balluff; Marc Tänzer; Heinz Höfler; Bernd J Krause; Markus Schwaiger; Helmut Friess; Roland M Schmid; Matthias P A Ebert
Journal:  Nat Clin Pract Gastroenterol Hepatol       Date:  2009-03
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