Wet-Lab Validation of Computationally-Generated Mutations
Initially, as a proof of concept, we will use the cystatin-C biomarker employed in Adeniran et al., 2018. This way, we have a baseline directed evolution experiment to compare our pipeline to and preliminary data on intermediate ligands and mutated receptors.
In order to test the efficacy of our computational pipeline, we induced targeted mutations in the yeast through the use of oligos containing our point mutations. Primers were designed to surround the STE2 gene and the NotI restriction site in pRS406 was used to insert specific fragments. Using PCR and primer overlap, Gibson Assembly was used to stitch together the oligo fragments containing specific mutations. Due to the principles of chemical kinetics, the yield of Gibson Assembly drops exponentially as the number of fragments grows. Hence, in order to ensure that our pipeline would continually work even with a large number of targeted mutations, we explored other methods of assembly.
In the spirit of accelerating protein engineering in our pipeline, we chose to use in-yeast assembly as it cuts down on a dramatic portion of normal mutagenesis protocols. This allows for cheaper, less-resource intensive protein engineering while still retaining a relatively high success rate. mVenus YFP gene introduced downstream of the pFUS1 promoter. The promotor itself is downstream in STE2 induction pathway. Successful induction of a-factor/cystatin-c results in mVenus YFP production. Generated optical readout can be used to track and quantify induction across the wildtype and mutant yeast.
We then induced two different point mutations in the STE2 in yeast. Both mutations were affecting binding residues in the active site of the protein. Four yeast strains were tested, one was a STE2 knockout variant that did not express the protein, one was wildtype, and the other two had unique mutations. With the assembly protocol accomplished, we had successfully implemented computationally generated mutations in our target organism.
Fluorescent Microscopy as Proof of Concept Success
Next, we conducted microscopy assays across the four different yeast groups using three experimental conditions: water and DMSO as a control, alpha-factor, and cystatin-c. The results from the fluorescent microscopy assays as below:
Our project streamlines the process of designing receptors to recognize disease biomarkers. These receptors are naturally used to detect a molecule important to the cell’s function. When that molecule binds to the receptor, it causes a downstream signal that can be displayed as a fluorescent readout. These results demonstrate a slightly decreased affinity for alpha-factor in ste2 mut1 and mut2 while maintaining fluorescence for cystatin detection. The very minor change in fluorescence can be explained by the fact that there is only one active site mutation in both mut1 and mut2. This indicates that our targeted mutagenesis protocol is affecting the functionality of the ste2 protein in one of our desired directions. Hence, we were able to show that our computational pipeline was accurately identifying binding residues and also correctly predicting residue changes that would increase the protein's binding affinity to a target ligand. As such, this pipeline will be able to be used with other active sites on different proteins and is generalizable across target peptide ligands. Furthermore, the pipeline is easily translatable to wet-lab microbiology assembly protocols and has a high experimental yield as well.