Coding
BIND bear

Part:BBa_K5436124:Design

Designed by: Ayaka Sasaki, Shota Yamamoto, Yuto Toriyama, Hanna Watanabe, Ryojun Hayashizaki   Group: iGEM24_Waseda-Tokyo   (2024-09-28)


Optimized RBS for BIND-System+BIND-bearPETase+6xHisTag


Assembly Compatibility:
  • 10
    INCOMPATIBLE WITH RFC[10]
    Illegal PstI site found at 395
  • 12
    INCOMPATIBLE WITH RFC[12]
    Illegal PstI site found at 395
    Illegal NotI site found at 550
  • 21
    INCOMPATIBLE WITH RFC[21]
    Illegal BamHI site found at 478
  • 23
    INCOMPATIBLE WITH RFC[23]
    Illegal PstI site found at 395
  • 25
    INCOMPATIBLE WITH RFC[25]
    Illegal PstI site found at 395
    Illegal NgoMIV site found at 622
  • 1000
    COMPATIBLE WITH RFC[1000]

Design Notes

Fig. 4. Components of Optimized RBS for BIND-System+BIND-bearPETase+6xHisTag

I. Optimized RBS for BIND-System (Waseda-Tokyo2024, BBa_K5436005)
This RBS is designed to efficiently drive the BIND-System. In some existing BioBricks, inappropriate RBS strength can either overload E. coli with excessive expression or result in no expression. We've designed an RBS to optimize the amount of CsgA displayed on E. coli’s surface as components of Curli Fibers, which will support future iGEMers using the BIND-System.
II. csgA-taa(Waseda-Tokyo2024, BBa_K5436006)
CsgA-taa is a modified version of BBa_K1583000 from iGEM15_TU_Delft, with the stop codon removed, enabling the expression of the desired protein in a fused state after the Curli Fiber formation factor CsgA.
III. BamHI_Linker (Waseda-Tokyo2024, BBa_K5436020)
This uses the BamHI recognition site, which consists of 6 nucleotides, directly as a linker. The BamHI recognition site encodes glycine and serine, which are commonly used amino acids in linker sequences.
IV. bearPETase (Waseda-Tokyo2024, BBa_K5436015)
BearPETase was rationally designed by Waseda-Tokyo 2024 to enhance its enzymatic activity. As shown below, we confirmed that its enzymatic activity surpassed that of existing variants. The existing PETase variants include depoPETase and duraPETase, and combining both was expected to improve enzymatic activity. Based on that consideration, we created 81 combinations, excluding the overlapping mutations Q119Y and Q119R, and generated 3D structures using AlphaFold 2, selecting those with stable structures.
V. 6x HisTag (Waseda-Tokyo2024, BBa_K5436021)
It is useful in protein purification and also beneficial for Western blotting, where anti-His Tag antibodies are used as primary antibodies.

ʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔʕ•ᴥ•ʔ ʕ•ᴥ•ʔʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔ ʕ•ᴥ•ʔ

Designing RBS for BIND-System

The "Optimized RBS for BIND-System (BBa_K5436005)" included in this part was carefully designed by the RBS Calculator from Salis Lab[5], rather than reusing an existing RBS. Existing RBS used in previous CsgA overexpression experiments did not meet our criteria. The RBS included in the pRha + CsgA (BBa_K1583100) developed by iGEM15_TU_Delft had a transcriptional rate of 40.80, which was insufficient for the expression levels we required. On the other hand, the transcriptional rate of the RBS in Rec-PhoA/CsgA (Addgene #170787)[6] was approximately 700, and it appeared to meet our requirements. Referring to that order of magnitude, we newly designed an RBS for BIND-PETase (WT) with a transcriptional rate of 800 using the RBS Calculator.

As mentioned later, this optimized RBS was sufficient to induce the expression of BIND-bearPETase.

Fig. 5. Optimized RBS for BIND-System generated with Transcriptional Rate set to 800

References

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  3. L Shi et al.(2023) Complete Depolymerization of PET Wastes by an Evolved PET Hydrolase from Directed Evolution. Angewandte Chemie International Edition 62(14) doi: 10.1002/anie.202218390 ↩︎

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  7. V Pirillo et al.(2023) Analytical methods for the investigation of enzyme-catalyzed degradation of polyethylene terephthalate. The FEBS Jour. 288(16) 4730-4745. doi.org/10.1111/febs.15850. ↩︎

  8. Pirillo, V., Pollegioni, L., & Molla, G. (2021). Analytical methods for the investigation of enzyme‐catalyzed degradation of polyethylene terephthalate. The FEBS Journal, 288(16), 4730–4745. doi: 10.1111/febs.15850 ↩︎

  9. F Kawai et al. (2022) Efficient depolymerization of polyethylene terephthalate (PET) and polyethylene furanoate by engineered PET hydrolase Cut190. AMB Expr 12(134) doi: 10.1186/s13568-022-01474-y ↩︎

  10. Oleg T. et al. (2010), AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading, Computational Chemistry, Vol. 31, Issue 2, 455-461, https://doi.org/10.1002/jcc.21334 ↩︎

  11. Smith S. et al. (2020),Assessing multiple score functions in Rosetta for drug discovery, PLoS One.15(10): e0240450.https://doi.org/10.1371/journal.pone.0240450 ↩︎

  12. Schymkowitz, J., Borg, J., Stricher, F., Nys, R., Rousseau, F., & Serrano, L. (2005). The FoldX web server: an online force field. Nucleic Acids Research, 33(Web Server), W382–W388. https://doi.org/10.1093/nar/gki387. ↩︎

  13. B. Guo et al. (2022). Conformational Selection in Biocatalytic Plastic Degradation by PETase. ACS Catal. 2022, 12, 6, 3397–3409 https://doi.org/10.1021/acscatal.1c05548 ↩︎

  14. The PyMOL Molecular Graphics System, Version 3.0.3 Schrödinger, LLC, http://www.pymol.org/pymol ↩︎