A tetracycline-inducible Split TurboID system for specific biotinylation and identification of nuclear proteins from HEK293T cells.

Background/aim: To overcome the limitations of conventional organelle isolation methods including low purity, low yield, sample degradation, scalability and the need for multiple centrifugation steps, an improved nuclear protein enrichment approach was developed using the modified Split TurboID biotin ligase enzyme.

Materials and methods: A construct was created in which the N-terminal domain of TurboID, fused to the FK506-binding protein (FKBP) was targeted to the nucleus. This construct was incorporated into a tetracycline-inducible gene expression vector. Similarly, the C-terminal domain of TurboID was fused to the rapamycin-binding domain of mTOR (FRB) and directed to the nucleus. This construct was introduced into a constitutive expression vector. A HEK-293T-TetR+ cell line, stably expressing both fusion proteins, was created. Activation of the N-terminal domain was achieved by tetracycline induction while an active Split-TurboID was formed within the nucleus only after the introduction of rapamycin into the culture medium which facilitated the formation of the FKBP-Rapamycin-FRB complex.

Results: The cells expressed N- and C-termini of Split-TurboID and produced an active biotin ligase enzyme in the nucleus, as demonstrated by Western blot and immunofluorescence microscopy analyses. The active enzyme biotinylated both residential nuclear proteins and the proteins that transiently interact with the nucleus. Enrichment and identification of the biotinylated proteins showed that 1518 proteins were identified, of which 78.4% were localized to or colocalized with the nucleus. Comparison with unenriched samples confirmed higher confidence in identification of resident nuclear proteins. Cross-referencing with the Human Protein Atlas highlighted the limitations of current databases, 820 proteins match known nuclear proteins and 698 have not been previously annotated.

Conclusion: Split-TurboID-based approach effectively minimized background noise arising from nonspecific labeling or imperfect localization and provided an appreciable level of specificity resulting identification of both residential and transiently interacting nuclear proteins.