Literature DB >> 28188537

Automated SWATH Data Analysis Using Targeted Extraction of Ion Chromatograms.

Hannes L Röst1,2, Ruedi Aebersold3,4, Olga T Schubert5,6.   

Abstract

Targeted mass spectrometry comprises a set of methods able to quantify protein analytes in complex mixtures with high accuracy and sensitivity. These methods, e.g., Selected Reaction Monitoring (SRM) and SWATH MS, use specific mass spectrometric coordinates (assays) for reproducible detection and quantification of proteins. In this protocol, we describe how to analyze, in a targeted manner, data from a SWATH MS experiment aimed at monitoring thousands of proteins reproducibly over many samples. We present a standard SWATH MS analysis workflow, including manual data analysis for quality control (based on Skyline) as well as automated data analysis with appropriate control of error rates (based on the OpenSWATH workflow). We also discuss considerations to ensure maximal coverage, reproducibility, and quantitative accuracy.

Keywords:  DIA; Data-independent acquisition; OpenSWATH; SWATH; SWATH MS; SWATH acquisition; Skyline; TRIC aligner; Targeted proteomics; pyProphet

Mesh:

Substances:

Year:  2017        PMID: 28188537     DOI: 10.1007/978-1-4939-6747-6_20

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  13 in total

1.  Application of SWATH Proteomics to Mouse Biology.

Authors:  Yibo Wu; Evan G Williams; Ruedi Aebersold
Journal:  Curr Protoc Mouse Biol       Date:  2017-06-19

2.  SWATH-MS Protocols in Human Diseases.

Authors:  Maria Del Pilar Chantada-Vázquez; María García Vence; Antonio Serna; Cristina Núñez; Susana B Bravo
Journal:  Methods Mol Biol       Date:  2021

3.  The autoimmune signature of hyperinflammatory multisystem inflammatory syndrome in children.

Authors:  Rebecca A Porritt; Aleksandra Binek; Lisa Paschold; Magali Noval Rivas; Angela McArdle; Lael M Yonker; Galit Alter; Harsha K Chandnani; Merrick Lopez; Alessio Fasano; Jennifer E Van Eyk; Mascha Binder; Moshe Arditi
Journal:  J Clin Invest       Date:  2021-10-15       Impact factor: 14.808

4.  Identifying Cell-Type-Specific Metabolic Signatures Using Transcriptome and Proteome Analyses.

Authors:  Nadja Gebert; Shahadat Rahman; Caroline A Lewis; Alessandro Ori; Chia-Wei Cheng
Journal:  Curr Protoc       Date:  2021-09

5.  Identification of Putative Early Atherosclerosis Biomarkers by Unsupervised Deconvolution of Heterogeneous Vascular Proteomes.

Authors:  Sarah J Parker; Lulu Chen; Weston Spivia; Georgia Saylor; Chunhong Mao; Vidya Venkatraman; Ronald J Holewinski; Mitra Mastali; Rakhi Pandey; Grace Athas; Guoqiang Yu; Qin Fu; Dana Troxlair; Richard Vander Heide; David Herrington; Jennifer E Van Eyk; Yue Wang
Journal:  J Proteome Res       Date:  2020-04-07       Impact factor: 4.466

Review 6.  Expanding the Use of Spectral Libraries in Proteomics.

Authors:  Eric W Deutsch; Yasset Perez-Riverol; Robert J Chalkley; Mathias Wilhelm; Stephen Tate; Timo Sachsenberg; Mathias Walzer; Lukas Käll; Bernard Delanghe; Sebastian Böcker; Emma L Schymanski; Paul Wilmes; Viktoria Dorfer; Bernhard Kuster; Pieter-Jan Volders; Nico Jehmlich; Johannes P C Vissers; Dennis W Wolan; Ana Y Wang; Luis Mendoza; Jim Shofstahl; Andrew W Dowsey; Johannes Griss; Reza M Salek; Steffen Neumann; Pierre-Alain Binz; Henry Lam; Juan Antonio Vizcaíno; Nuno Bandeira; Hannes Röst
Journal:  J Proteome Res       Date:  2018-10-11       Impact factor: 4.466

7.  TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.

Authors:  Hannes L Röst; Yansheng Liu; Giuseppe D'Agostino; Matteo Zanella; Pedro Navarro; George Rosenberger; Ben C Collins; Ludovic Gillet; Giuseppe Testa; Lars Malmström; Ruedi Aebersold
Journal:  Nat Methods       Date:  2016-08-01       Impact factor: 28.547

8.  Development of a Gill Assay Library for Ecological Proteomics of Threespine Sticklebacks (Gasterosteus aculeatus).

Authors:  Johnathon Li; Bryn Levitan; Silvia Gomez-Jimenez; Dietmar Kültz
Journal:  Mol Cell Proteomics       Date:  2018-08-09       Impact factor: 5.911

9.  A comprehensive spectral assay library to quantify the Escherichia coli proteome by DIA/SWATH-MS.

Authors:  Mukul K Midha; Ulrike Kusebauch; David Shteynberg; Charu Kapil; Samuel L Bader; Panga Jaipal Reddy; David S Campbell; Nitin S Baliga; Robert L Moritz
Journal:  Sci Data       Date:  2020-11-12       Impact factor: 6.444

10.  Generation of a murine SWATH-MS spectral library to quantify more than 11,000 proteins.

Authors:  Chuan-Qi Zhong; Jianfeng Wu; Xingfeng Qiu; Xi Chen; Changchuan Xie; Jiahuai Han
Journal:  Sci Data       Date:  2020-03-26       Impact factor: 6.444

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