Protein methylation,mainly on lysine and arginine, is the smallest post-translational modification but can modulate protein properties such as structure, function and stability. Dysregulatedprotein methylation can initiate abnormal biochemistry, leading to disease. Methyltransferases have been found to be dysregulated in various cancers including colorectal cancer (CRC). However, very little is known regarding the impact this has on specific cancers because the methylated targets are not fully known, particularly when the methyltransferase domain is mutated.

Since EHMT2 is one of the 5 most dysregulated lysine methyltransferases in CRC (as well as various other cancers) it is an important research target. It catalyses the addition of methylation via the Su(var)3-9, Enhancer-of-zeste and Trithorax (SET) domain, composed of 130- to 140-amino acids, flanked by two cysteine-rich regions called the pre-SET and post-SET domains. These 3 essential domains only cover residues 972-1180 of the massive EHMT2 protein. The aim of this project was to use a yeast two-hybrid set up to isolate interactors of EHMT2 using only the 3 catalytic domains and then validate which of the isolated interactors were dysregulated in CRC.

A clone spanning the pre-SET, SET and post-SET domains of EHMT2 was generated and used to create a bait fusion protein for the isolation of interactors from a protein coding library through mating in a yeast-two hybrid system. Following the determination of the interaction strength of the isolated interactions using a CPRG assay, a number of successful strong interactors were sequenced. The differential expression of the isolated EHMT2 interactors is now being investigated in CRC spheroids, since 3D cell culture better mimics in-vivo protein expression patterns.

Once this model is fully validated, specific misense mutation especially those listed as "likely pathogenic" within the catalytic region of EHMT2 can be mutated in the bait construct to understand their impact on target interactions. This workflow is also being extended to methyltransferases of other families such as methyltransferase-like (METTL) enzymes. The data generated will be a useful guide for future diagnostic and prognostic testing of different CRC sub-types, particularly prior to chemotherapy administration or to determine the metastatic potential of tumours, especially in cases where the methyltransferase is dysregulated due to mutation of the catalytic domain.