Assessment of current mass spectrometric workflows for the quantification of low abundant proteins and phosphorylation sites
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 3293437
Author(s) Bauer, Manuel; Ahrné, Erik; Baron, Anna P; Glatter, Timo; Fava, Luca L; Santamaria, Anna; Nigg, Erich A; Schmidt, Alexander
Author(s) at UniBasel Nigg, Erich
Ahrné, Erik
Baron, Anna
Schmidt, Alexander
Year 2015
Title Assessment of current mass spectrometric workflows for the quantification of low abundant proteins and phosphorylation sites
Journal Data in brief
Volume 5
Pages / Article-Number 297-304
Abstract The data described here provide a systematic performance evaluation of popular data-dependent (DDA) and independent (DIA) mass spectrometric (MS) workflows currently used in quantitative proteomics. We assessed the limits of identification, quantification and detection for each method by analyzing a dilution series of 20 unmodified and 10 phosphorylated synthetic heavy labeled reference peptides, respectively, covering six orders of magnitude in peptide concentration with and without a complex human cell digest background. We found that all methods performed very similarly in the absence of background proteins, however, when analyzing whole cell lysates, targeted methods were at least 5-10 times more sensitive than directed or DDA methods. In particular, higher stage fragmentation (MS3) of the neutral loss peak using a linear ion trap increased dynamic quantification range of some phosphopeptides up to 100-fold. We illustrate the power of this targeted MS3 approach for phosphopeptide monitoring by successfully quantifying 9 phosphorylation sites of the kinetochore and spindle assembly checkpoint component Mad1 over different cell cycle states from non-enriched pull-down samples. The data are associated to the research article 'Evaluation of data-dependent and data-independent mass spectrometric workflows for sensitive quantification of proteins and phosphorylation sites׳ (Bauer et al., 2014) [1]. The mass spectrometry and the analysis dataset have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD000964.
Publisher Elsevier
ISSN/ISBN 2352-3409
edoc-URL http://edoc.unibas.ch/39733/
Full Text on edoc No
Digital Object Identifier DOI 10.1016/j.dib.2015.08.015
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/26550600
ISI-Number MEDLINE:26550600
Document type (ISI) Journal Article
 
   

MCSS v5.8 PRO. 0.683 sec, queries - 0.000 sec ©Universität Basel  |  Impressum   |    
14/08/2020