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System-Wide Profiling of Protein Complexes Via Size Exclusion Chromatography–Mass Spectrometry (SEC–MS)

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Shotgun Proteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2259))

Abstract

In living cells, most proteins are organized in stable or transient functional assemblies, protein complexes, which control a multitude of vital cellular processes such as cell cycle progression, metabolism, and signal transduction. Over several decades, specific protein complexes have been analyzed by structural biology methods, initially X-ray crystallography and more recently single particle cryoEM. In parallel, mass spectrometry (MS)-based methods including in vitro affinity-purification coupled to MS or in vivo protein proximity-dependent labeling methods have proven particularly effective to detect complexes, thus nominating new assemblies for structural analysis. Those approaches, however, are either of limited in throughput or require specifically engineered protein systems.

In this chapter, we present protocols for a workflow that supports the parallel analysis of multiple complexes from the same biological sample with respect to abundance, subunit composition, and stoichiometry. It consists of the separation of native complexes by size-exclusion chromatography (SEC) and the subsequent mass spectrometric analysis of the proteins in consecutive SEC fractions. In particular, we describe (1) optimized conditions to achieve native protein complex separation by SEC, (2) the preparation of the SEC fractions for MS analysis, (3) the acquisition of the MS data at high throughput via SWATH/DIA (data-independent analysis) mass spectrometry and short chromatographic gradients, and (4) a set of bioinformatic tools for the targeted analysis of protein complexes. Altogether, the parallel measurement of a high number of complexes from a single biological sample results in unprecedented system-level insights into the remodeling of cellular protein complexes in response to perturbations of a broad range of cellular systems.

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Acknowledgments

Contributions: AF, FF, and FU conceived and designed the project. MV and FF prepared and conducted the showcase experiment. AF and FF analyzed the showcase example. AF, FF, FU, and CM wrote the manuscript. BC, LG, MG, and RA supervised, reviewed, and edited the manuscript. MG and RA provided funding and resources to support the project. Fig. 1 was created with BioRender.com.

Declaration of Interests: The authors declare no conflict of interest.

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Author notes

  1. * Andrea Fossati, Fabian Frommelt, Federico Uliana contributed equally to this work.

Authors and Affiliations

  1. Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zürich, Switzerland

    Andrea Fossati, Fabian Frommelt, Federico Uliana, Claudia Martelli, Matej Vizovisek, Ludovic Gillet, Matthias Gstaiger & Ruedi Aebersold

  2. School of Biological Sciences, Queen’s University of Belfast, Belfast, UK

    Ben Collins

  3. Faculty of Science, University of Zurich, Zurich, Switzerland

    Ruedi Aebersold

Authors
  1. Andrea Fossati
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  2. Fabian Frommelt
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  3. Federico Uliana
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  4. Claudia Martelli
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  5. Matej Vizovisek
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  6. Ludovic Gillet
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  7. Ben Collins
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  8. Matthias Gstaiger
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  9. Ruedi Aebersold
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Corresponding author

Correspondence to Ruedi Aebersold .

Editor information

Editors and Affiliations

  1. Department of Food Technology, Institute of Marine Research (IIM), Spanish National Research Council (CSIC), Vigo, Spain

    Mónica Carrera

  2. Department of Food Technology, Institute of Marine Research (IIM), Spanish National Research Council (CSIC), Vigo, Spain

    Jesús Mateos

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Fossati, A. et al. (2021). System-Wide Profiling of Protein Complexes Via Size Exclusion Chromatography–Mass Spectrometry (SEC–MS). In: Carrera, M., Mateos, J. (eds) Shotgun Proteomics. Methods in Molecular Biology, vol 2259. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1178-4_18

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  • DOI: https://doi.org/10.1007/978-1-0716-1178-4_18

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1177-7

  • Online ISBN: 978-1-0716-1178-4

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