![](https://parts.igem.org/images/partbypart/icon_composite.png)
Part:BBa_K4122027
SP-PETase-His-Spycatcher-T+SP-MHETase-cMyc-Snoopcatcher-T + SP- V5-CBM -ST-ST-SNT-781
This part is compose of 3 parts:
P-SP-PETase-His-Spycatcher-T
+ SP-MHETase-cMyc-Snoopcatcher-T
+ SP-CBM-V5-ST-ST-SNT-7813 (ST:SNT=2:1)
Optimize PETase and MHETase surface display Ratios-Final optimized system
We started with a ratio of snooptag: spytag=1:3. In order to obtain better catalytic effect, we optimized its proportion and successfully constructed scaffolds with different proportions.
![](https://static.igem.wiki/teams/4122/wiki/parts/14-successful-construction-of-different-scaffolds-ratios.png)
Fig.1 Successful construction of different scaffolds ratios.(BBa_K4122025, BBa_K4122027
We tested the effect of different ratios by HPLC, and found that the ratio of 2:1 performed the best among all the groups.
We started with a ratio of snooptag: spytag=1:3. In order to obtain better catalytic effect, we optimized its proportion and successfully constructed scaffolds with different proportions.
![](https://static.igem.wiki/teams/4122/wiki/parts/15-hplc-analysis-of-degraded-pet-with-displaying-petases-and-mhetase-different-ratios.png)
Fig.2 HPLC analysis of degraded PET with displaying PETases and MHETase (different ratios).
The results of degraded PET film further confirmed the results.
![](https://static.igem.wiki/teams/4122/wiki/parts/16-degradation-of-pet-film-with-the-strain-s-f-m-is-2-1.png)
Fig.3 Degradation of PET film with the strainS-F:M=2:1.
References
[1] Wei Zheng, Chengxin Zhang, Yang Li, Robin Pearce, Eric W. Bell, Yang Zhang. Folding non-homology proteins by coupling deep-learning contact maps with I-TASSER assembly simulations. Cell Reports Methods, 1: 100014 (2021).
[2] Chengxin Zhang, Peter L. Freddolino, and Yang Zhang. COFACTOR: improved protein function prediction by combining structure, sequence and protein-protein interaction information. Nucleic Acids Research, 45: W291-299 (2017).
[3] Jianyi Yang, Yang Zhang. I-TASSER server: new development for protein structure and function predictions, Nucleic Acids Research, 43: W174-W181, 2015.
[4] Lu, Hongyuan, et al. "Machine learning-aided engineering of hydrolases for PET depolymerization." Nature 604.7907 (2022): 662-667.
Sequence and FeaturesNone |