Application of Capture-Recapture Models to Estimation of Protein Count in MudPIT Experiments

摘要

MudPIT is an automated shotgun proteomics approach that enhances the separation of peptides for sequencing by mass spectrometry analysis. We here adapt a mathematical model from ecology, namely, the capture-recapture model with a closed population and time-varying and heterogeneous individual probabilities of capture, to model the number of peptide identifications across the various cycles of a typical MudPIT experiment. In the absence of any prior information on abundance levels, the model can be used to estimate the total number of proteins in the experimental sample. We apply the model to a recent MudPIT-based experiment to estimate the total number of rat lung endothelial cell surface proteins. The model provides some practical guidelines for planning MudPIT experiments.