Coding

Part:BBa_K5151016

Designed by: Chan, Yu-Wen   Group: iGEM24_NYCU-Formosa   (2024-08-29)

Protein G Introduction

Early detection of diseases is crucial. To achieve this, we can target disease biomarkers for testing to assist in early diagnosis. Currently, clinical tests for disease biomarkers, such as ELISA, RIA, and mass spectrometry, though widely used, tend to require longer detection times. Many have developed biosensors and rapid diagnostic tools (RDT). However, challenges still exist in detecting disease biomarkers, mainly due to the complexity of samples and the insufficient sensitivity and specificity of detection technologies.
To address these issues, our team has proposed a new strategy this year, utilizing a pre-trained Natural Language Processing (NLP) model to identify potential biomarkers for diseases[1]. Through this approach, we aim to overcome the current bottlenecks in detection technologies and provide a more efficient and cost-effective pathway for early diagnosis and timely treatment of diseases. This not only helps to shorten diagnostic times but also improves diagnostic accuracy and patient treatment outcomes.
In terms of experimental design, we plan to use the Lpp-OmpA-GS linker to display specific proteins on the cell membrane for further functional testing. To validate the feasibility of this strategy, we introduced Protein G as an additional validation tool to help confirm the stability and versatility of the Lpp-OmpA-GS linker system in expressing various functional proteins. Protein G, a cell-wall protein derived from group G Streptococci, binds a greater variety of antibodies and has a high affinity for immunoglobulin G (IgG), which is used as a target in cancer and inflammation[2]. In our project, we use the Lpp-OmpA-GS linker to display protein G on the membrane. Then, through ELISA experiments, we can confirm whether the protein G expressed on the membrane is correctly folded and functional.


Reference

[1] Available at: https://2024.igem.wiki/nycu-formosa/model
[2] Rodriguez, E., & Bolaños, R. (2006). Use of capillary electrophoresis with laser-induced fluorescence detection for the analysis of urinary carboxylic acids. Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences, 842(1-2), 11–19. Available at: https://www.sciencedirect.com/science/article/pii/S1570023206006908?ref=pdf_download&fr=RR-2&rr=8c943f9fdc8d4a24

Sequence and Features


Assembly Compatibility:
  • 10
    COMPATIBLE WITH RFC[10]
  • 12
    COMPATIBLE WITH RFC[12]
  • 21
    COMPATIBLE WITH RFC[21]
  • 23
    COMPATIBLE WITH RFC[23]
  • 25
    INCOMPATIBLE WITH RFC[25]
    Illegal NgoMIV site found at 408
  • 1000
    COMPATIBLE WITH RFC[1000]


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Categories
Parameters
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