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Duplex Labeling and Manipulation of Neuronal Proteins Using Sequential CRISPR/Cas9 Gene Editing
Wouter J Droogers1, Jelmer Willems1, Harold D MacGillavry2
1Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University, 3584 CH, Utrecht, The Netherlands.
Eneuro
|July 19, 2022
Summary
We developed Conditional Activation of Knock-in Expression (CAKE), a CRISPR/Cas9 method for precise multiplex protein labeling in neurons. CAKE overcomes crosstalk, enabling accurate visualization and manipulation of endogenous proteins to study neuronal function.
Area of Science:
- Neuroscience
- Molecular Biology
- Genetics
Background:
- CRISPR/Cas9 knock-in methods allow endogenous protein labeling for studying spatiotemporal distribution.
- Multiplexing knock-in events in neurons is challenging due to crosstalk between editing events.
Purpose of the Study:
- To develop an efficient, flexible, and accurate method for multiplex genome editing in rat neurons.
- To overcome crosstalk limitations in CRISPR/Cas9 multiplexing for neuronal protein labeling.
Main Methods:
- Conditional Activation of Knock-in Expression (CAKE) utilizes sequential, recombinase-driven guide RNA expression.
- CAKE controls the timing of genomic integration for each donor sequence to minimize crosstalk.
- Super-resolution microscopy and inducible dimerization modules were employed.
Main Results:
- CAKE enables efficient and accurate multiplex genome editing in rat neurons.
- The method successfully co-labeled various endogenous neuronal proteins, including cytoskeletal proteins, synaptic scaffolds, ion channels, and receptor subunits.
- Synaptic protein co-organization was found to depend on synapse size, and receptor dynamics were acutely controlled.
Conclusions:
- CAKE is a versatile method for multiplex protein labeling, detection, localization, and manipulation of endogenous proteins in neurons.
- The developed strategy provides new biological insights into neuronal function and protein organization.
- CAKE facilitates accurate duplex endogenous protein labeling and manipulation for addressing complex biological questions.
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