The Split-Ubiquitin Based Membrane Yeast Two-Hybrid (MYTH) for detecting protein-protein interaction
Reference: https://app.jove.com/v/1698/split-ubi...
The Split-Ubiquitin Based Membrane Yeast Two-Hybrid (MYTH) System is an exceptionally effective tool utilized for the identification of protein-protein interactions. This system employs the concept of splitting the ubiquitin protein into two fragments, the N-terminal half (Nub) and the C-terminal half (Cub), which are then fused to the proteins of interest. When these proteins interact, the two fragments of ubiquitin are brought into close proximity, allowing for their reconstitution and subsequent activation of a reporter gene.
The Split-Ubiquitin MYTH System offers several advantages over other protein-protein interaction assays. Firstly, it allows for the detection of interactions that occur at the membrane, which is particularly important for studying integral membrane proteins and their interactions with other proteins or ligands. This is achieved by fusing the Nub fragment to a membrane protein and the Cub fragment to a cytoplasmic protein, enabling the detection of interactions that occur across the membrane.
Furthermore, the Split-Ubiquitin MYTH System is highly sensitive and specific, as it relies on the reconstitution of ubiquitin fragments, which is a highly specific process. This ensures that only true protein-protein interactions are detected, minimizing false positives. Additionally, the activation of a reporter gene provides a quantitative readout of the interaction strength, allowing for the comparison of different interactions and the identification of weak or transient interactions.
The Split-Ubiquitin MYTH System has been successfully applied to study a wide range of biological processes and disease mechanisms. For example, it has been used to identify protein interactions involved in signal transduction pathways, protein trafficking, and protein degradation. By understanding the intricate network of protein interactions within cells, researchers can gain valuable insights into the underlying mechanisms of various biological processes and diseases.