Our team leverages advanced synthetic biology technologies to transform scientific advancements into commercially viable products with strong market prospects. The initiative aligns with global trends and has received robust support from the Chinese government, promoting goals such as carbon neutrality and bioeconomic development.

With cutting-edge technology and governmental support, our team effectively meets market demands through a professional approach, sound financial planning, and a commitment to social value, showcasing significant commercial potential and social impact.

·Our team designed and characterized parts based on the formate assimilation pathway, enabling TD80 to utilize formate.

·Building on the existing research on P34HB conducted in our laboratory, we decided to optimize the screening pressure and design additional relevant parts to improve the molar ratio of 4HB.

·Based on the work of team iGEM06_Berkeley and iGEM09_Imperial College London,we have lowered the leakage of the thermosensitive bio-switch in Halomonas TD and at the same time improved the fold change by replacing the promoter of ci857.

·Based on the work of team iGEM09_Imperial College London, we mutated the regulatory protein CI857 and obtained several mutants that showed different level of controlling the expression of report gene in Halomonas TD.

·Based on the work of iGEM21_LINKS_China,we introduced dynamic control of thermalsensitive bio-switch into the synthesis of tyrian purple and successfully raised the production of it.

·Our team designed a locus screening program equipped with an easy-to-use graphical user interface. This program can efficiently and quickly screen highly transcribed active loci on the genome.

·Our team has developed a GO-term-based ec-GEM called Motrol. Motrol simulates reactions occurring within cells and incorporates enzyme partitioning constraints along with continuous feeding fermentation control logic. By running this model, we can predict the cell's state under different substrate concentrations. Additionally, it enables the reverse prediction of the required substrate concentration range based on the desired cell state, facilitating continuous feeding in fermentation control. This method has the potential to enhance the success rate of fermentation scaling.