Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline

By B. Schilling, Matthew J. Rardin, Brendan MacLean, A. Zawadzka, Barbara E Frewen, Michael P. Cusack, Dylan J. Sorensen, Michael S. Bereman, Enxuan Jing, Christine C. Wu and 4 more. Molecular & Cellular Proteomics, 2012

419 citations recorded by the source corpus.

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/2d088171d52255d50090858af0737dac9a1d5e46

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Citations in the corpus

SIRT5 regulates the mitochondrial lysine succinylome and metabolic networks (2013, positive): “In the present study, we generated antibodies for the specific enrichment of succinyl-lysine-containing peptides and applied a label-free quantitative proteomic method called MS1 filtering (Schilling et al., 2012) to characterize the mitochondrial succinylome in a metabolically active and highly aer”
The Skyline Ecosystem: Informatics for Quantitative Mass Spectrometry Proteomics (2017, methodology): “For DDA analyses, an MS1 filtering approach through the external tool MS1Probe (Schilling et al. 2012) enables high throughput statistical quantification of peptide analytes.”