Composite

Part:BBa_K5175031:Design

Designed by: Xihong Zeng   Group: iGEM24_HUST-China   (2024-10-01)
Revision as of 08:58, 2 October 2024 by Yuhanzou (Talk | contribs)


T7 promoter-lac operator-pelB-MHETase-G4S-FAST-PETase-T7 terminator


Assembly Compatibility:
  • 10
    INCOMPATIBLE WITH RFC[10]
    Illegal PstI site found at 826
    Illegal PstI site found at 1169
  • 12
    INCOMPATIBLE WITH RFC[12]
    Illegal NheI site found at 2820
    Illegal PstI site found at 826
    Illegal PstI site found at 1169
  • 21
    INCOMPATIBLE WITH RFC[21]
    Illegal BamHI site found at 709
    Illegal XhoI site found at 1967
  • 23
    INCOMPATIBLE WITH RFC[23]
    Illegal PstI site found at 826
    Illegal PstI site found at 1169
  • 25
    INCOMPATIBLE WITH RFC[25]
    Illegal PstI site found at 826
    Illegal PstI site found at 1169
    Illegal NgoMIV site found at 166
    Illegal NgoMIV site found at 508
    Illegal NgoMIV site found at 896
    Illegal NgoMIV site found at 1259
  • 1000
    COMPATIBLE WITH RFC[1000]


Design Notes

It is a composite component consisting of the T7 promoter, T7 terminator, target genes tphA2, tphA3, tphA1. It is responsible for degrading PET polymers into monomers TPA and EG.

FAST-PETase is a machine-learning obtained PETase with properties suitable for in situ PET degradation at mild temperatures and moderate pH conditions.However, the main product of PETase degradation of PET is MHET, and the MHET intermediate tends to bind tightly to PET degrading enzyme in a non-catalytic pose, which leads to the inhibition of PET degrading enzyme. Therefore, an efficient MHET hydrolase is needed to degrade the intermediate product in time to further depolymerise MHET into its monomers TPA and EG.In the process of constructing a dual enzyme system, we used bioinformatics to simulate the molecular docking of the linker connecting the two enzymes, and after simulation prediction, we chose the G4S flexible peptide as the linker of FAST-PETase and MHETase, and constructed the two into a dual enzyme system.


Source

Ideonella sakaiensis

References

[4] LU H, DIAZ D J, CZARNECKI N J, et al. Machine learning-aided engineering of hydrolases for PET depolymerization [J]. Nature, 2022, 604(7907): 662-7.

[5] ZHANG J, WANG H, LUO Z, et al. Computational design of highly efficient thermostable MHET hydrolases and dual enzyme system for PET recycling [J]. Communications Biology, 2023, 6(1): 1135.

[6] ZHANG Y, HESS H. Toward Rational Design of High-efficiency Enzyme Cascades [J]. ACS Catalysis, 2017, 7(9): 6018-27.