Dataset Information

Considerations for peptide and protein error rate control in large-scale targeted DIA analyses

ABSTRACT: Liquid chromatography coupled to tandem mass spectrometry has become the main method for high-throughput identification and quantification of peptides and the inferred proteins. Discovery proteomics commonly employs data-dependent acquisition in combination with spectrum-centric analysis. The accumulation of data generated from thousands of samples by this method has approached saturation coverage of different proteomes. Recently, as a result of technological advances, methods based on data acquisition strategies compatible with peptide-centric scoring have also reached similar proteome coverage in individual runs, and scalability. This is exemplified by SWATH-MS, which combines data-independent acquisition (DIA) with targeted data extraction of groups of transitions uniquely detecting a peptide. As the data matrices generated by these experiments continue to grow with respect to both the number of peptides identified per sample and the number of samples analyzed per study, challenges for error rate control have emerged. Here, we discuss the adaptation of statistical concepts developed for discovery proteomics based on spectrum-centric scoring to large-scale DIA experiments analyzed with peptide-centric scoring strategies, and provide some guidance on their application. We propose that, in order to increase the quality and reproducibility of published proteomic results, well-established confidence criteria should be reported at each level as we progress from spectral evidence to identified or detected peptides and inferred proteins. These confidence criteria should equally be applied to proteomic analyses based on spectrum- and peptide-centric scoring strategies.

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Permanent Cell Line Cell, Cell Culture

SUBMITTER: Isabell Bludau

LAB HEAD: Ruedi Aebersold

PROVIDER: PXD004884 | Pride | 2017-08-03

REPOSITORIES: Pride

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Publications

Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses.

Rosenberger George G Bludau Isabell I Schmitt Uwe U Heusel Moritz M Hunter Christie L CL Liu Yansheng Y MacCoss Michael J MJ MacLean Brendan X BX Nesvizhskii Alexey I AI Pedrioli Patrick G A PGA Reiter Lukas L Röst Hannes L HL Tate Stephen S Ting Ying S YS Collins Ben C BC Aebersold Ruedi R

Nature methods 20170821 9

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the main method for high-throughput identification and quantification of peptides and inferred proteins. Within this field, data-independent acquisition (DIA) combined with peptide-centric scoring, as exemplified by the technique SWATH-MS, has emerged as a scalable method to achieve deep and consistent proteome coverage across large-scale data sets. We demonstrate that statistical concepts developed for discovery proteomics ...[more]

PMID: 28825704

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Project description:It has become increasingly clear that biological functions depend not only on the identity and quantity, but also the correct interplay among the biomolecules that constitute the cell. Importantly, proteins as the key effectors in the cell dynamically organize into complexes. This study describes a workflow to interrogate the role of dynamic proteome organization in biological functions. Specifically, we here characterize the proteome of the HeLa CCL2 cell line in interphase and mitosis, including the measurement of the protein complex assembly state with the goal to screen for functional proteome rearrangement. We employ an optimized SEC-SWATH-MS workflow to profile protein elution along size exclusion chromatographic fractionations of mild proteome extracts. Largely maintaining the integrity of protein association into complexes, the method captures the proteomes contextual state via the measure of protein appearance at distinct molecular weight. Quantitatively accurate readout of polypeptide elution profiles is achieved by bottom-up DIA/SWATH mass spectrometry, facilitating sensitive detection of quantitatively context-re-wiring proteins. The study quantitatively profiles 5044 proteins across 390 SWATH-MS maps. Statistical analysis pinpoints several hundred proteins with significantly altered cellular context indicated by altered quantitative elution behavior across distinct apparent molecular weight ranges measured in SEC. The results are validated by the reconciliation of established cell biology such as CDK1 recruitment by cyclin B1 and the mitotic disassembly of nuclear pore complexes as presented in the accompanying manuscript. The high quality chromatographic data further delineate distinct cellular assemblies such as a novel mitotic intermediate of nuclear pore complex disassembly that was validated by orthogonal methods. The study sheds light on altered proteome state in the pivotal process of cell division at systems scale. In contrast to typical quantitative approaches to study the proteome, SEC-SWATH-MS captures the biophysical context state of proteins that is often associated with protein function. Thus, the data may well support the discovery and validation of novel aspects and effectors of modular proteome function along cell cycle progression. Our workflow and study build the capacity to investigate biological systems including their higher order organization on the level of proteins and in a systems-wide fashion which will help to elucidate how biochemical functions, responses and phenotypes are generated within a cell.

Dataset Information

Considerations for peptide and protein error rate control in large-scale targeted DIA analyses

Publications

Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses.

Similar Datasets

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