Dataset Information

Label-free quantification in ion-mobility enhanced data-independent acquisition proteomics

ABSTRACT: Data-dependent acquisition (DDA) methods are a well-established tool for proteome analysis and have greatly expedited the field of shotgun proteomics. However, their serial and stochastic nature restricts their reproducibility and limits the detectable dynamic range to the peptides that ionize best. Unbiased data-independent acquisition (DIA) strategies strive to overcome this limitation and have gained increased popularity over recent years. The integration of ion-mobility separation (IMS) into DIA workflows provides an additional dimension of separation and increases the achievable analytical depth of DIA approaches. Here we provide a detailed protocol for a label-free quantitative proteomics workflow based on ion-mobility enhanced DIA, which uses drift time specific collision energies to improve precursor fragmentation efficiency. The protocol comprises a detailed description of all major steps including sample preparation, LC-IMS-MS analysis, and data processing. Our protocol can handle proteome samples of any complexity and enables a highly reproducible and accurate label-free quantitation of up to 5,600 proteins across multiple runs in complete cellular lysates. Depending on the number of samples to be analysed, the protocol takes a minimum of three days to complete from proteolytic digest to data evaluation.

INSTRUMENT(S): Synapt G2-S HDMS

ORGANISM(S): Homo Sapiens (human) Escherichia Coli Saccharomyces Cerevisiae (strain Lalvin Ec1118 / Prise De Mousse) (baker's Yeast)

TISSUE(S): Tissues

SUBMITTER: Ute Distler

LAB HEAD: Stefan Tenzer

PROVIDER: PXD002393 | Pride | 2016-03-29

REPOSITORIES: Pride

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Publications

Label-free quantification in ion mobility-enhanced data-independent acquisition proteomics.

Distler Ute U Kuharev Jörg J Navarro Pedro P Tenzer Stefan S

Nature protocols 20160324 4

Unbiased data-independent acquisition (DIA) strategies have gained increased popularity in the field of quantitative proteomics. The integration of ion mobility separation (IMS) into DIA workflows provides an additional dimension of separation to liquid chromatography-mass spectrometry (LC-MS), and it increases the achievable analytical depth of DIA approaches. Here we provide a detailed protocol for a label-free quantitative proteomics workflow based on ion mobility-enhanced DIA, which synchron ...[more]

PMID: 27010757

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Project description:Data independent acquisition (DIA or DIA/SWATH ) mass spectrometry has emerged as a primary measurement strategy in the field of quantitative proteomics. diaPASEF is a recent adaptation that leverages trapped ion mobility spectrometry (TIMS) to improve selectivity and increase sensitivity. The complex fragmentation spectra generated by co-isolation of peptides in DIA mode are most typically analyzed with reference to prior knowledge in the form of spectral libraries. The best established method for generating libraries uses data dependent acquisition (DDA) mode, or DIA mode if appropriately deconvoluted, often including offline fractionation to increase depth of coverage,to create spectral libraries. More recently strategies for spectral library generation based on gas phase fractionation (GPF), where a representative sample is injected serially using narrow window DIA methods designed to cover different slices of the precursor space, have been introduced and performed comparably to deep offline fractionation-based libraries for DIA data analysis. Here, we investigated whether an analogous GPF-based library building approach that accounts for the ion mobility (IM) dimension is useful for the analysis of diaPASEF data and can remove the need for offline fractionation. To enable a rapid library development approach for diaPASEF we designed a GPF acquisition scheme covering the majority of multiply charged precursors in the m/z vs 1/K0 space requiring 7 injections of a representative sample and compared this with libraries generated by direct deconvolution-based analysis of diaPASEF data or by deep offline fractionation and ddaPASEF. . We found that the GPF based library outperformed library generation by direct deconvolution of the diaPASEF data, and performed comparably to deep offline fractionation libraries, when analysing diaPASEF data acquired from 200ng of commercial HeLa digest. With the ion mobility integrated GPF scheme we establish a pragmatic approach to rapid and comprehensive library generation for the analysis of diaPASEF data.

Dataset Information

Label-free quantification in ion-mobility enhanced data-independent acquisition proteomics

Publications

Label-free quantification in ion mobility-enhanced data-independent acquisition proteomics.

Similar Datasets

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