Sleeping ORANGE: A CRISPR-Transposase Hybrid Approach to Boost Endogenous Protein Tagging Efficiency

Abstract Background Investigating the subcellular distribution of proteins is crucial for understanding complex cell behaviours and disease mechanisms. Fluorescence microscopy is a key tool for visualising protein localisation. However, its application is often hindered by the lack of high-quality antibodies, and the common approach to overexpress recombinant fusion constructs tagged with fluorescent proteins can introduce artefacts. Endogenous protein tagging, where the sequence for a tag (typically a peptide or fluorescent protein) is integrated into the native genetic sequence encoding a protein of interest, can be used to overcome these limitations, enabling proteins to be visualised without the need for antibodies against the target protein and avoiding complications associated with recombinant protein overexpression. ORANGE (Open Resource for the Application of Neuronal Genome Editing) is a CRISPR-Cas9-based endogenous protein tagging technique which relies on homology-independent targeted integration (HITI)-mediated gene editing. Utilising HITI as the DNA repair pathway of choice gives ORANGE the advantage of being less error-prone than classical homology-directed repair (HDR)-based endogenous protein tagging techniques and additionally, means it can be used in post-mitotic cells. Results We applied the ORANGE system to tag three proteins, CYFIP1, JAKMIP1, and STAT3, and confirmed that the expressed fusion proteins demonstrate expected subcellular localisations through fluorescence microscopy. Unexpectedly, the efficiency of ORANGE editing was less than 1% in HEK293 cells, despite high transfection efficiency. To improve the editing efficiency associated with ORANGE, we combined the ORANGE method with an established Sleeping Beauty transposase/CRISPR-Cas9 fusion technique, which has been shown to enhance HITI-mediated gene editing. Using this new method, which we term Sleeping ORANGE, we successfully tagged CYFIP1 with the fluorescent protein mNeonGreen. Importantly, through fluorescence microscopy and flow cytometry, we demonstrate that Sleeping ORANGE increased gene-editing efficiency by approximately 4- to 6-fold compared to the original ORANGE technique. Conclusions We have developed a method to improve the editing efficiency associated with the ORANGE technique, and with further research to ensure that the fluorescent tags are correctly inserted into their target gene without off-target effects, the Sleeping ORANGE technique may form a valuable tool for researchers to use to better study protein subcellular localisation and dynamics.