Literature DB >> 32690956

Complex-centric proteome profiling by SEC-SWATH-MS for the parallel detection of hundreds of protein complexes.

Isabell Bludau1,2, Moritz Heusel1,3, Max Frank1,4, George Rosenberger1,5, Robin Hafen1, Amir Banaei-Esfahani1, Audrey van Drogen1, Ben C Collins1,6, Matthias Gstaiger7, Ruedi Aebersold8,9.   

Abstract

Most catalytic, structural and regulatory functions of the cell are carried out by functional modules, typically complexes containing or consisting of proteins. The composition and abundance of these complexes and the quantitative distribution of specific proteins across different modules are therefore of major significance in basic and translational biology. However, detection and quantification of protein complexes on a proteome-wide scale is technically challenging. We have recently extended the targeted proteomics rationale to the level of native protein complex analysis (complex-centric proteome profiling). The complex-centric workflow described herein consists of size exclusion chromatography (SEC) to fractionate native protein complexes, data-independent acquisition mass spectrometry to precisely quantify the proteins in each SEC fraction based on a set of proteotypic peptides and targeted, complex-centric analysis where prior information from generic protein interaction maps is used to detect and quantify protein complexes with high selectivity and statistical error control via the computational framework CCprofiler (https://github.com/CCprofiler/CCprofiler). Complex-centric proteome profiling captures most proteins in complex-assembled state and reveals their organization into hundreds of complexes and complex variants observable in a given cellular state. The protocol is applicable to cultured cells and can potentially also be adapted to primary tissue and does not require any genetic engineering of the respective sample sources. At present, it requires ~8 d of wet-laboratory work, 15 d of mass spectrometry measurement time and 7 d of computational analysis.

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Year:  2020        PMID: 32690956     DOI: 10.1038/s41596-020-0332-6

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  51 in total

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Authors:  Marco Y Hein; Nina C Hubner; Ina Poser; Jürgen Cox; Nagarjuna Nagaraj; Yusuke Toyoda; Igor A Gak; Ina Weisswange; Jörg Mansfeld; Frank Buchholz; Anthony A Hyman; Matthias Mann
Journal:  Cell       Date:  2015-10-22       Impact factor: 41.582

2.  Toward chromatographic analysis of interacting protein networks.

Authors:  Xiuping Liu; Wen-chu Yang; Qiang Gao; Fred Regnier
Journal:  J Chromatogr A       Date:  2008-01-18       Impact factor: 4.759

3.  The BioPlex Network: A Systematic Exploration of the Human Interactome.

Authors:  Edward L Huttlin; Lily Ting; Raphael J Bruckner; Fana Gebreab; Melanie P Gygi; John Szpyt; Stanley Tam; Gabriela Zarraga; Greg Colby; Kurt Baltier; Rui Dong; Virginia Guarani; Laura Pontano Vaites; Alban Ordureau; Ramin Rad; Brian K Erickson; Martin Wühr; Joel Chick; Bo Zhai; Deepak Kolippakkam; Julian Mintseris; Robert A Obar; Tim Harris; Spyros Artavanis-Tsakonas; Mathew E Sowa; Pietro De Camilli; Joao A Paulo; J Wade Harper; Steven P Gygi
Journal:  Cell       Date:  2015-07-16       Impact factor: 41.582

4.  A "tagless" strategy for identification of stable protein complexes genome-wide by multidimensional orthogonal chromatographic separation and iTRAQ reagent tracking.

Authors:  Ming Dong; Lee Lisheng Yang; Katherine Williams; Susan J Fisher; Steven C Hall; Mark D Biggin; Jian Jin; H Ewa Witkowska
Journal:  J Proteome Res       Date:  2008-03-13       Impact factor: 4.466

5.  A promiscuous biotin ligase fusion protein identifies proximal and interacting proteins in mammalian cells.

Authors:  Kyle J Roux; Dae In Kim; Manfred Raida; Brian Burke
Journal:  J Cell Biol       Date:  2012-03-12       Impact factor: 10.539

6.  A high-throughput approach for measuring temporal changes in the interactome.

Authors:  Anders R Kristensen; Joerg Gsponer; Leonard J Foster
Journal:  Nat Methods       Date:  2012-08-05       Impact factor: 28.547

7.  Characterization of native protein complexes and protein isoform variation using size-fractionation-based quantitative proteomics.

Authors:  Kathryn J Kirkwood; Yasmeen Ahmad; Mark Larance; Angus I Lamond
Journal:  Mol Cell Proteomics       Date:  2013-09-16       Impact factor: 5.911

8.  Global Membrane Protein Interactome Analysis using In vivo Crosslinking and Mass Spectrometry-based Protein Correlation Profiling.

Authors:  Mark Larance; Kathryn J Kirkwood; Michele Tinti; Alejandro Brenes Murillo; Michael A J Ferguson; Angus I Lamond
Journal:  Mol Cell Proteomics       Date:  2016-04-25       Impact factor: 5.911

9.  Architecture of the human interactome defines protein communities and disease networks.

Authors:  Edward L Huttlin; Raphael J Bruckner; Joao A Paulo; Joe R Cannon; Lily Ting; Kurt Baltier; Greg Colby; Fana Gebreab; Melanie P Gygi; Hannah Parzen; John Szpyt; Stanley Tam; Gabriela Zarraga; Laura Pontano-Vaites; Sharan Swarup; Anne E White; Devin K Schweppe; Ramin Rad; Brian K Erickson; Robert A Obar; K G Guruharsha; Kejie Li; Spyros Artavanis-Tsakonas; Steven P Gygi; J Wade Harper
Journal:  Nature       Date:  2017-05-17       Impact factor: 49.962

10.  Panorama of ancient metazoan macromolecular complexes.

Authors:  Cuihong Wan; Blake Borgeson; Sadhna Phanse; Fan Tu; Kevin Drew; Greg Clark; Xuejian Xiong; Olga Kagan; Julian Kwan; Alexandr Bezginov; Kyle Chessman; Swati Pal; Graham Cromar; Ophelia Papoulas; Zuyao Ni; Daniel R Boutz; Snejana Stoilova; Pierre C Havugimana; Xinghua Guo; Ramy H Malty; Mihail Sarov; Jack Greenblatt; Mohan Babu; W Brent Derry; Elisabeth R Tillier; John B Wallingford; John Parkinson; Edward M Marcotte; Andrew Emili
Journal:  Nature       Date:  2015-09-07       Impact factor: 49.962

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Review 6.  Complexome Profiling-Exploring Mitochondrial Protein Complexes in Health and Disease.

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Authors:  Saiful Effendi Syafruddin; M Aiman Mohtar; Teck Yew Low; Adaikkalam Vellaichamy; Nisa Syakila A Rahman; Yuh-Fen Pung; Chris Soon Heng Tan
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