title: Differential proteomics via probabilistic peptide identification scores.
abstract: Relative quantitation is key to enable differential proteomics and hence answer biological questions by comparing samples. Classical approaches involve stable isotope labeling with/without spiked standards. Although stable isotopes may lead to precise results, their application is not straightforward. In Proteomics, 2004, 4, 2333-2351, we proposed an approach where we summed peptide identification scores to derive a semiquantitative abundance indicator. In this study, we combine such an indicator with a statistical test to detect differentially expressed proteins. We demonstrate the effectiveness of this method by using mixtures of purified proteins and human plasma spiked with proteins at low-nanomolar concentrations. The impact of the number of repeated experiments is discussed, and we show that the statistical test we use performs well with two to three repetitions, whereas a classical t-test would require at least four repetitions to achieve the same performance. Typically, 2.5-5-fold changes are detected with 90-95% confidence in human plasma. The method is finally characterized by deriving estimates of its false positive and negative rates. This new characterization is valid for a wider class of methods such as spectrum sampling (Liu, H.; Sadygov, R. G.; Yates, J. R. III. Anal. Chem. 2004, 76, 4193-4201).
authors.affiliation: GeneProt Inc.. 2 Pré-de-la-Fontaine, case postale 125, CH-1217 Meyrin 2, Geneva, Switzerland. Jacques.Collinge@geneprot.com
authors.forename: Jacques
authors.initials: J
authors.lastname: Colinge
authors.forename: Diego
authors.initials: D
authors.lastname: Chiappe
authors.forename: Sophie
authors.initials: S
authors.lastname: Lagache
authors.forename: Marc
authors.initials: M
authors.lastname: Moniatte
authors.forename: Lydie
authors.initials: L
authors.lastname: Bougueleret
mesh_terms: D000818:Animals; D019992:Databases as Topic; D006801:Humans; D020738:Leptin / Q000097:blood; D015233:Models, Statistical; D009211:Myoglobin / Q000032:analysis; D010455:Peptides / Q000097:blood*; D010949:Plasma / Q000737:chemistry*; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results
chemical_list: D020738:Leptin; D009211:Myoglobin; D010455:Peptides