Abstract
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.
Highlights
Mass spectrometry has rapidly evolved into a high throughput methodology for identifying differentially expressed proteins or post-translational modifications
Stable isotope labeling by amino acids in cell culture or SILAC1 is typically used in cell culture experiments [3], this approach has been recently adapted for studies in animals [4, 5]
Label-free quantitative methods are better suited for proteomic experiments where SILAC labeling is not possible or where postmetabolic isobaric labeling approaches may result in substantial inefficiencies
Summary
Mass spectrometry has rapidly evolved into a high throughput methodology for identifying differentially expressed proteins or post-translational modifications (for review, see Ref. 1). To test the utility of Skyline MS1 filtering for label-free quantitative proteomics, we have carried out comparative experiments to examine the ability to process data from several instrument types, including QqTOF and LTQ FT-ICR mass spectrometers, and obtained appropriate linear and quantitative response curves for multiple peptides Once these performance metrics were established, we carried out a set of experiments that targeted two important PTMs, phosphorylation and N--acetylation, that would provide a more rigorous evaluation of the performance and robustness of Skyline MS1 filtering, especially in peptide-centric workflows where quantitation methods are lacking. These experiments were carried out with samples of increasing complexity and workflow design, consisting of peptide affinity enrichment steps that targeted PTMs changes in breast cancer cell lines and mitochondria isolated from transgenic mouse models
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