title: Benchmarking stable isotope labeling based quantitative proteomics.
abstract: Several quantitative mass spectrometry based technologies have recently evolved to interrogate the complexity, interconnectivity and dynamic nature of proteomes. Currently, the most popular methods use either metabolic or chemical isotope labeling with MS based quantification or chemical labeling using isobaric tags with MS/MS based quantification. Here, we assess the performance of three of the most popular approaches through systematic independent large scale quantitative proteomics experiments, comparing SILAC, dimethyl and TMT labeling strategies. Although all three methods have their strengths and weaknesses, our data indicate that all three can reach a similar depth in number of identified proteins using a classical (MS2 based) shotgun approach. TMT quantification using only MS2 is heavily affected by co-isolation leading to compromised precision and accuracy. This issue may be partly resolved by using an MS3 based acquisition; however, at the cost of a significant reduction in number of proteins quantified. Interestingly, SILAC and chemical labeling with MS based quantification produce almost indistinguishable results, independent of which database search algorithm used.
authors.affiliation: Biomolecular Mass Spectrometry and Proteomics, Utrecht Institute for Pharmaceutical Sciences and Bijvoet Center for Biomolecular Research, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands.
authors.forename: A F Maarten
authors.initials: AF
authors.lastname: Altelaar
authors.forename: Christian K
authors.initials: CK
authors.lastname: Frese
authors.forename: Christian
authors.initials: C
authors.lastname: Preisinger
authors.forename: Marco L
authors.initials: ML
authors.lastname: Hennrich
authors.forename: Andree W
authors.initials: AW
authors.lastname: Schram
authors.forename: H Th Marc
authors.initials: HT
authors.lastname: Timmers
authors.forename: Albert J R
authors.initials: AJ
authors.lastname: Heck
authors.forename: Shabaz
authors.initials: S
authors.lastname: Mohammed
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D006367:HeLa Cells; D006801:Humans; D007553:Isotope Labeling / Q000379:methods*; D013058:Mass Spectrometry / Q000379:methods; D020543:Proteome / Q000378:metabolism*; D040901:Proteomics / Q000379:methods*
chemical_list: D020543:Proteome
keywords: AGC; AP-MS; Affinity Purification based Mass Spectrometry; Automatic Gain Control; CID; Collision induced dissociation; Dimethyl labeling; FDR; False Discovery Rate; HCD; Higher energy C-trap dissociation; Isobaric Tag for Relative and Absolute Quantification; Isobaric labeling; MS/MS; NCE; Normalized Collision Energy; PSMs; Peptide to Spectrum Matches; Quantitation; SCX; SILAC; Stable Isotope Labeling by Amino acids in Cell culture; Strong Cation Exchange; TMT; Tandem Mass Spectrometry; Tandem Mass Tag; iTRAQ