dc.contributor.author
Stockhammer, Alexander
dc.contributor.author
Spalt, Carissa
dc.contributor.author
Klemt, Antonia
dc.contributor.author
Benz, Laila S.
dc.contributor.author
Harel, Shelly
dc.contributor.author
Natalia, Vini
dc.contributor.author
Wiench, Lukas
dc.contributor.author
Freund, Christian
dc.contributor.author
Kuropka, Benno
dc.contributor.author
Bottanelli, Francesca
dc.date.accessioned
2024-09-16T08:56:14Z
dc.date.available
2024-09-16T08:56:14Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/44328
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-44040
dc.description.abstract
In recent years, proximity labeling has established itself as an unbiased and powerful approach to map the interactome of specific proteins. While physiological expression of labeling enzymes is beneficial for the mapping of interactors, generation of the desired cell lines remains time-consuming and challenging. Using our established pipeline for rapid generation of C- and N-terminal CRISPR-Cas9 knock-ins (KIs) based on antibiotic selection, we were able to compare the performance of commonly used labeling enzymes when endogenously expressed. Endogenous tagging of the µ subunit of the AP-1 complex with TurboID allowed identification of known interactors and cargo proteins that simple overexpression of a labeling enzyme fusion protein could not reveal. We used the KI-strategy to compare the interactome of the different adaptor protein (AP) complexes and clathrin and were able to assemble lists of potential interactors and cargo proteins that are specific for each sorting pathway. Our approach greatly simplifies the execution of proximity labeling experiments for proteins in their native cellular environment and allows going from CRISPR transfection to mass spectrometry analysis and interactome data in just over a month.
en
dc.format.extent
16 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
Gene editing
en
dc.subject
Membrane trafficking
en
dc.subject.ddc
500 Naturwissenschaften und Mathematik::540 Chemie::540 Chemie und zugeordnete Wissenschaften
dc.title
When less is more – A fast TurboID KI approach for high sensitivity endogenous interactome mapping
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
jcs261952
dcterms.bibliographicCitation.doi
10.1242/jcs.261952
dcterms.bibliographicCitation.journaltitle
Journal of Cell Science
dcterms.bibliographicCitation.number
16
dcterms.bibliographicCitation.volume
137
dcterms.bibliographicCitation.url
https://doi.org/10.1242/jcs.261952
refubium.affiliation
Biologie, Chemie, Pharmazie
refubium.affiliation.other
Institut für Chemie und Biochemie
refubium.funding
The Company of Biologists
refubium.note.author
Die Publikation wurde aus Open Access Publikationsgeldern der Freien Universität Berlin gefördert.
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
1477-9137