Journal
MOLECULAR & CELLULAR PROTEOMICS
Volume 19, Issue 1, Pages 181-197Publisher
ELSEVIER
DOI: 10.1074/mcp.RA119.001714
Keywords
Mass Spectrometry; Quantification; Label-free quantification; Bioinformatics software; Target identification; data-independent acquisition (DIA); peptide identification; proteomics; spectral library
Categories
Funding
- FoRUM Program of Ruhr University Bochum [F871-2016]
- de.NBI project of the Bundesministerium fur Bildung und Forschung (BMBF), PURE (Protein Unit for Research in Europe), a project of North Rhine-Westphalia, Germany [FKZ 031 A 534A]
- European Union H2020 project NISCI [681094]
- Internal Security Fund (ISF)
- European Union
Ask authors/readers for more resources
The impact of different approaches for spectral library generation used by DIA was analyzed on identification and quantification level using a gold standard spike-in data set. We included approaches using repetitive measurements of the original samples as well as methods applying peptide and protein pre-fractionation before library generation. The comparisons show, that prefractionation generally increases the number of identified peptides and protein groups, whereas the ground truth quantification ratios could be well approximated using libraries generated by repetitive measurements. Currently data-dependent acquisition (DDA) is the method of choice for mass spectrometry-based proteomics discovery experiments, but data-independent acquisition (DIA) is steadily becoming more important. One of the most important requirements to perform a DIA analysis is the availability of suitable spectral libraries for peptide identification and quantification. Several studies were performed addressing the evaluation of spectral library performance for protein identification in DIA measurements. But so far only few experiments estimate the effect of these libraries on the quantitative level. In this work we created a gold standard spike-in sample set with known contents and ratios of proteins in a complex protein matrix that allowed a detailed comparison of DIA quantification data obtained with different spectral library approaches. We used in-house generated sample-specific spectral libraries created using varying sample preparation approaches and repeated DDA measurement. In addition, two different search engines were tested for protein identification from DDA data and subsequent library generation. In total, eight different spectral libraries were generated, and the quantification results compared with a library free method, as well as a default DDA analysis. Not only the number of identifications on peptide and protein level in the spectral libraries and the corresponding DIA analysis results was inspected, but also the number of expected and identified differentially abundant protein groups and their ratios. We found, that while libraries of prefractionated samples were generally larger, there was no significant increase in DIA identifications compared with repetitive non-fractionated measurements. Furthermore, we show that the accuracy of the quantification is strongly dependent on the applied spectral library and whether the quantification is based on peptide or protein level. Overall, the reproducibility and accuracy of DIA quantification is superior to DDA in all applied approaches. Data has been deposited to the ProteomeXchange repository with identifiers PXD012986, PXD012987, PXD012988 and PXD014956.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available