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.
Fasting is one of the simplest metabolic challenges that can be performed in humans. We here report for the first time a comprehensive analysis of the human ''fasting metabolome'' obtained from analysis of plasma and urine samples in a small cohort of healthy volunteers, using nuclear magnetic resonance (NMR), gas chromatography-and liquid chromatography-mass spectrometry (GC-MS and LC-MS). Intra-and inter-individual variation of metabolites was on measurement of four overnight fasting samples collected from each volunteer over a four week period. One additional sample per volunteer was collected following a prolonged fasting period of 36 h. Amongst a total of 377 quantified entities in plasma around 44% were shown to change significantly in concentration when volunteers extended fasting from 12 to 36 h. In addition to known markers (plasma free fatty acids, glycerol, ketone bodies) that reflect changes in the body's fuel management under fasting conditions a wide range of ''new'' entities such as a-aminobutyrate as well as other amino and keto acids were identified as fasting markers. Based on multiple correlations amongst the metabolites and selected hormones in plasma such as leptin or insulinlike-growth-factor-1 (IGF-1), a robust metabolic network with coherent regulation of a wide range of metabolites could be identified. The metabolomics approach described here demonstrates the plasticity of human metabolism and identifies new and robust markers of the fasting state.
Blood cells and biofluid proteomics are emerging as a valuable tool to assess effects of interventions on health and disease. This study is aimed to assess the amount and variability of proteins from platelets, peripheral blood mononuclear cells (PBMC), plasma, urine and saliva from ten healthy volunteers for proteomics analysis, and whether protein yield is affected by prolonged fasting. Volunteers provided blood, saliva and morning urine samples once a week for 4 weeks after an overnight fast. Volunteers were fasted for a further 24 h after the fourth sampling before providing their final samples. Each 10 mL whole blood provided 400-1,500 lg protein from platelets, and 100-600 lg from PBMC. 30 lL plasma depleted of albumin and IgG provided 350-650 lg protein. A sample of morning urine provided 0.9-8.6 mg protein/dL, and a sample of saliva provided 70-950 lg protein/mL. None of these yields were influenced by the degree of fasting (overnight or 36 h). In conclusion, in contrast to the yields from plasma, platelets and PBMC, the protein yields of urine and saliva samples were highly variable within and between subjects. Certain disease conditions may cause higher or lower PBMC counts and thus protein yields, or increased urinary protein levels.
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