A quantitative mapping approach to identify direct interactions within complexomes Article Swipe
Philipp Trepte
,
Christopher Secker
,
Soon Gang Choi
,
Julien Olivet
,
Eduardo Silva Ramos
,
Patricia Cassonnet
,
Sabrina Golusik
,
Martina Zenkner
,
Stephanie Beetz
,
Marcel Sperling
,
Yang Wang
,
Tong Hao
,
Kerstin Spirohn
,
Jean‐Claude Twizere
,
Michael A. Calderwood
,
David E. Hill
,
Yves Jacob
,
Marc Vidal
,
Erich E. Wanker
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1101/2021.08.25.457734
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1101/2021.08.25.457734
Complementary methods are required to fully characterize all protein complexes, or the complexome, of a cell. Affinity purification coupled to mass-spectrometry (AP-MS) can identify the composition of complexes at proteome-scale. However, information on direct contacts between subunits is often lacking. In contrast, solving the 3D structure of protein complexes can provide this information, but structural biology techniques are not yet scalable for systematic, proteome-wide efforts. Here, we optimally combine two orthogonal high-throughput binary interaction assays, LuTHy and N2H, and demonstrate that their quantitative readouts can be used to differentiate direct interactions from indirect associations within multiprotein complexes. We also show that LuTHy allows accurate distance measurements between proteins in live cells and apply these findings to study the impact of the polyglutamine expansion mutation on the structurally unresolved N-terminal domain of Huntingtin. Thus, we present a new framework based on quantitative interaction assays to complement structural biology and AP-MS techniques, which should help to provide first-approximation contact maps of multiprotein complexes at proteome-scale. Graphical Abstract
Related Topics
Concepts
Computational biology
Proteome
Protein–protein interaction
Multiprotein complex
Complement (music)
Structural biology
Systems biology
Biology
Chemistry
Cell biology
Bioinformatics
Biochemistry
Complementation
Gene
Phenotype
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2021.08.25.457734
- https://www.biorxiv.org/content/biorxiv/early/2021/08/26/2021.08.25.457734.full.pdf
- OA Status
- green
- Cited By
- 3
- References
- 56
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3194558227
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3194558227Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2021.08.25.457734Digital Object Identifier
- Title
-
A quantitative mapping approach to identify direct interactions within complexomesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-08-26Full publication date if available
- Authors
-
Philipp Trepte, Christopher Secker, Soon Gang Choi, Julien Olivet, Eduardo Silva Ramos, Patricia Cassonnet, Sabrina Golusik, Martina Zenkner, Stephanie Beetz, Marcel Sperling, Yang Wang, Tong Hao, Kerstin Spirohn, Jean‐Claude Twizere, Michael A. Calderwood, David E. Hill, Yves Jacob, Marc Vidal, Erich E. WankerList of authors in order
- Landing page
-
https://doi.org/10.1101/2021.08.25.457734Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2021/08/26/2021.08.25.457734.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2021/08/26/2021.08.25.457734.full.pdfDirect OA link when available
- Concepts
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Computational biology, Proteome, Protein–protein interaction, Multiprotein complex, Complement (music), Structural biology, Systems biology, Biology, Chemistry, Cell biology, Bioinformatics, Biochemistry, Complementation, Gene, PhenotypeTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1, 2023: 1, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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56Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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