Reproducibility of Quantitative Proteomic Analyses of Complex Biological Mixtures by Multidimensional Protein Identification Technology

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Abstract
If quantitative proteomic technologies are to be of widespread use to the biological community, the reproducibility of each method must be investigated and determined. We have analyzed the reproducibility of complex quantitative proteomic analyses of metabolically labeled S. cerevisiae analyzed via multidimensional protein identification technology (MudPIT). Three independent cell growths of S. cerevisiae grown in rich and minimal media and independent MudPIT analyses of each were compared and contrasted. Quantitative MudPIT was found to be intra- and interexperimentally reproducible at both the peptide and protein levels. Proteins of potential low abundance were detected, identified, and quantified by identical peptides from three independent samples. In addition, when multiple peptides were matched to a protein, the relative abundance of each peptide was in agreement across the three samples. Despite the reproducibility, errors in the experimental determination of protein expression levels occurred, but the impact of the variation was minimized by replicate experiments. Last, quantitative MudPIT analyses will likely be improved by increasing the number of peptide hits per protein in a given analysis, which will provide for greater intraexperimental reproducibility.