Published June 27, 2022 | Version v1
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Rapid and specific degradation of endogenous proteins in mouse models using auxin-inducible degrons

  • 1. University of Edinburgh

Description

Auxin-inducible degrons are a chemical genetic tool for targeted protein degradation and are widely used to study protein function in cultured mammalian cells. Here we develop CRISPR-engineered mouse lines that enable rapid and highly specific degradation of tagged endogenous proteins in vivo. Most but not all cell types are competent for degradation. By combining ligand titrations with genetic crosses to generate animals with different allelic combinations, we show that degradation kinetics depend upon the dose of the tagged protein, ligand, and the E3 ligase substrate receptor TIR1. Rapid degradation of condensin I and condensin II – two essential regulators of mitotic chromosome structure - revealed that both complexes are individually required for cell division in precursor lymphocytes, but not in their differentiated peripheral lymphocyte derivatives. This generalisable approach provides unprecedented temporal control over the dose of endogenous proteins in mouse models, with implications for studying essential biological pathways and modeling drug activity in mammalian tissues.

Notes

Flow Cytometry data analysis was conducted using FlowJo software (Treestar). Flowing software is a free alternative: http://www.flowingsoftware.com/.

3D imaging datasets datasets were visualised and analysed for fluorescence intensity using Imaris V9.5 (Bitplane, Oxford Instruments, UK). FIJI/ImageJ is an open source alternative.

2D imaging datasets were analysed using QuPath 0.3.0, which is open source.

Funding provided by: Medical Research Council
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000265
Award Number:

Funding provided by: Wellcome Trust
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100010269
Award Number:

Funding provided by: Canadian Institutes of Health Research
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000024
Award Number:

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Related works

Is cited by
10.1101/2022.01.13.476100 (DOI)