Project: SolHMetal:Application of new biofilm in industrial water treatment
Track:Environment,Undergrad
Team wiki delivery: https://2022.igem.wiki/xjtlu-china/
Web Page for Modeling part: https://2022.igem.wiki/xjtlu-china/model.html
Team promotion video: https://video.igem.org/w/jKHWKW82h13X16vyKK5NwQ
Final Presentaion for judging session : https://video.igem.org/w/21f2ecf1-08e1-4e65-a983-cb30f832b809
Results: GOLD MEDAL; BEST ENVIRONMENT PROJECT NOMINATION
International Genetically Engineered Machine (iGEM) competition is a worldwide synthetic biology competition which emphasize on the Design-Build-Test-Learn engineering success and interdisplinary research, inluding Biology,Mathematics,Computer Science and Engineering,etc.The field of synthetic biology, still in its early stages, has largely been driven by experimental expertise, and much of its success can be attributed to the skill of the researchers in specific domains of biology. There has been a concerted effort to assemble repositories of standardized components; however, creating and integrating synthetic components remains an ad hoc process. Inspired by these challenges, the field has seen a proliferation of efforts to create computer-aided design tools addressing synthetic biology's specific design needs, many drawing on prior expertise from the Model work.
The Model session falls into four diverse but complementary categories, which assist wet lab work and overall insightful optimization of our biofilm system for industrial water purification and heavy metal absorption. We have achieved full-system simulations ranging from molecules to pathways, to populational bacterium working limit, and finally to the mathematical hydrodynamic simulation of the utilized device.
Part1: Molecular Dynamic Model: Computational frameworks of Autodock and Gromacs are developed and implemented to prove the binding sites and affinity of our absorption system.View guide
Part2: Cellular Model: Deterministic models of ideal IPTG concentration alter tac promoter activity and heavy metal binding affinity fitting are implemented using ordinary differential equations based on literature and experimental measurement.
Part3: Populational Survival Model: A network of relationships between heavy metal ion concentrations and the corresponding survival parameters was established to predict the working limit of E. coli in the actual wastewater environment, guiding practical operations.
Part4: Device System Model: With binding affinity from the fitting of experimental data, we create a system model based on the real device to simulate the output concentration of metal ions, meeting the precise threshold for absorption.