Proof of concept
Overview
Our goal is to construct the strain that are better at degrading plastics. Based on last year's project, we chose to develop a self-assembled multi-enzyme display system of Candida tropicalis, where both enzymes work together to improve degradation efficiency. At the same time, we kept optimizing our system to ensure a higher enzyme activity and plastic degradation ability. In our project, we showed the process from zero to one, but also from 1 to 100, and of course we will go from 100 to higher level.
Zero to One-------Successful construction of co-display system One to One hundred--------Optimization of surface display system
Part 1 Construction of the co-display system
1.1 Successful construction of SpyTag-SpyCatcher and SnoopTag-SnoopCatcher system
GFP and RFP were used to indicate the successful construction of Spycatcher/Spytag and Snoopcatcher/Snooptag systems. We initially tried two catcher types with a ratio of 1:3.
1.2 Validation of Molecular modeling
When replacing RFP and GFP with MHETase and PETase, we did not observe immunofluorescence with secondary antibodies that should theoretically bind specifically to the V5 tag. Through modeling, we figured out that the problem was caused by V5 tag being embedded. After altering the V5 tag’s location, we predicted the model again using I-TASSER to ensure its feasibility. In response to this question, we moved the V5 tag forward in the sequence and the prediction model was showed in Figure 4. Therefore, we changed the position of V5 tag to successfully improve the condition.
Part 2 (Improvement) Optimization of scaffold for surface display
To improve PET plastic degradation efficiency, we imitated cellulosome and controlled the ratio and display sequence of PETase and MHETase enzymes.
Step 1: Optimize the scaffold by exchanging tag and catcher to reduce the molecular mass of the proteins. Notes: Tag is much smaller than catcher.
Step 2: Optimize PETase and MHETase surface display Ratios
Step3: Fast-PETase with higher enzyme activity were used rather than wild-type PETase
2.1 Successful trial on exchanging the position of tag and catcher
The tags have a shorter sequence than the catchers, which allows the anchor protein to display tags with less effort. When immunofluorescence is found, it is evident that the new scaffold has been built successfully.
Finally, we built the scaffolds with tags and V5 Tag in the front——SP-CBM-V5-ST-ST-SNT-ST-7813.
2.2 Higher degradation efficiency was achieved with newly reported Fast-PETase
According to the latest report, we have synthesized Fast-PETase. The results showed that the activity of Fast-PETase is indeed higher than that of wild-type PETase.
We also measured the effectiveness of FAST-PETase more directly by testing its effect with degrading PET powder. Specifically, we took the following steps. First, we collected an appropriate amount of cultivated strains and washed it three times with 50 mM glycine-NaOH (pH 9.0-10) buffer. Second, the bacteria were incubated with 1 mL buffer containing 50 mM glycine-NaOH (pH 9.0) and 10 mg PET powder at 30℃ with a shaking speed of 900 r /min. Third, the reaction was terminated by diluting the aqueous solution with 18 mM phosphate buffer (pH 2.5) containing 10% (v/v) DMSO followed by heat treatment (85°C, 10 min). Fourth, the supernatant obtained by centrifugation (15,000 × g, 10 min) was analyzed by HPLC. The result shown in the figure below reflect a significantly larger concentration of degraded PET, MHET with FAST-PETase than wild PETase, consistent under different OD codition,
2.3 Optimizing PETase and MHETase surface display Ratios helped to achieve higher degradation efficiency
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.
We tested the effect of different ratios by HPLC, and found that the ratio of 2:1 performed the best among all the groups.
The results of degraded PET film further confirmed the results.
References
- Lu, Hongyuan et al. “Machine learning-aided engineering of hydrolases for PET depolymerization.” Nature vol. 604,7907 (2022): 662-667. doi:10.1038/s41586-022-04599-z
- Yang, Jianyi et al. “The I-TASSER Suite: protein structure and function prediction.” Nature methods vol. 12,1 (2015): 7-8. doi:10.1038/nmeth.3213
- Zheng, Wei et al. “I-TASSER gateway: A protein structure and function prediction server powered by XSEDE.” Future generations computer systems : FGCS vol. 99 (2019): 73-85. doi:10.1016/j.future.2019.04.011
- Tam, Benjamin et al. “Combining Ramachandran plot and molecular dynamics simulation for structural-based variant classification: Using TP53 variants as model.” Computational and structural biotechnology journal vol. 18 4033-4039. 2 Dec. 2020, doi:10.1016/j.csbj.2020.11.041
- Gopalakrishnan, K et al. “Ramachandran plot on the web (2.0).” Protein and peptide letters vol. 14,7 (2007): 669-71. doi:10.2174/092986607781483912