alexa Evaluation of reproducibility of protein identification results after multidimensional human serum protein separation.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Proteomics & Bioinformatics

Author(s): Stalder D, Haeberli A, Heller M

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Abstract We developed a gel- and label-free proteomics platform for comparative studies of human serum. The method involves the depletion of the six most abundant proteins, protein fractionation by Off-Gel IEF and RP-HPLC, followed by tryptic digestion, LC-MS/MS, protein identification, and relative quantification using probabilistic peptide match score summation (PMSS). We evaluated performance and reproducibility of the complete platform and the individual dimensions, by using chromatograms of the RP-HPLC runs, PMSS based abundance scores and abundance distributions as objective endpoints. We were interested if a relationship exists between the quantity ratio and the PMSS score ratio. The complete analysis was performed four times with two sets of serum samples containing different concentrations of spiked bovine beta-lactoglobulin (0.1 and 0.3\%, w/w). The two concentrations resulted in significantly differing PMSS scores when compared to the variability in PMSS scores of all other protein identifications. We identified 196 proteins, of which 116 were identified four times in corresponding fractions whereof 73 qualified for relative quantification. Finally, we characterized the PMSS based protein abundance distributions with respect to the two dimensions of fractionation and discussed some interesting patterns representing discrete isoforms. We conclude that combination of Off-Gel electrophoresis (OGE) and HPLC is a reproducible protein fractionation technique, that PMSS is applicable for relative quantification, that the number of quantifiable proteins is always smaller than the number of identified proteins and that reproducibility of protein identifications should supplement probabilistic acceptance criteria. This article was published in Proteomics and referenced in Journal of Proteomics & Bioinformatics

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