Engineering Success | RS_United_China

Design:

We first amplified the COMT gene sequence, constructed the overexpression vector, and transformed the night disk into transgenic poplars by the leaf disk method. The endogenous melatonin content of transgenic poplars was measured, and the difference of melatonin between transgenic plants and wild-type plants was compared.

Build:

a )PtoCOMT was cloned successfully

Specific primers, enzymes and cDNA were reacted in PCR to obtain gene fragments ligated to the pEASY vector. The sequencing results showed that we successfully cloned PtoCOMT. And the length of this gene is 1098bp.

Figure 1. (a) Electrophoregram of PtoCOMT. (b) PtoCOMT gene sequence.

b)Construction of expression vector and genetic transformation in populus

The gene was successfully attached to the PBI121 vector by seamless cloning technology. The recombinant PBI121-PtoCOMT-GFP vector was transformed into Agrobacterium tumefaciens and then transformed by leaf disc method. And transgenic plants were obtained.

Figure 2. (a) PBI121-PtoCOMT vector diagram. (b) Wild-type populus and transgenic populus.

Test:

Over-expression on endogenous melatonin contents in populus

To ascertain the direct involvement of PtoCOMT in melatonin biosynthesis, transgenic populus with overexpression of PtoCOMT were generated. We used Melatonin ELISA Kit to detect melatonin in wild-type and transgenic plants. A standard curve needs to be constructed based on the standards in the kit at concentrations of 0,1,2,4,8,16 pg/ml. The contents of melatonin in transgenic populus increased by 1.5-fold compared to that in wild-type populus. Therefore, we found that COMT was not efficient in catalyzing the synthesis of melatonin, so we wanted to develop a method to improve the synthesis efficiency.

Figure 3. Melatonin content in wild-type and transgenic populus

design and test:

Bioinformatics modification of PtoCOMT to improve the efficiency of melatonin synthesis

We identified positive selection sites of PtoCOMT by bioinformatics analysis. These sites were then mutated to construct a mutant library. The results showed that mutations at positions 48, 49, 89, 92 position have high degree of significance. And we used alphafold to predict protein structure and it turns out that the structure does change at these sites. So we sort of figured out a way to design proteins.

Table 1. Positive selection sites calculated by bioinformatics.

Figure 4. Protein structure before and after mutation at 48, 49, 89, 92.