On the early morning of October 27th, Beijing time, the International Genetically Engineered Machine Competition (iGEM) — a top-tier event in the field of synthetic biology for 2024 — concluded at the Paris Convention Centre in France. Over 400 elite teams from prestigious universities worldwide, including MIT, Harvard, Oxford, Tsinghua University, Peking University, and Shanghai Jiao Tong University (SJTU), participated in the competition. After intense competition, SJTU's representative teams, SJTU-BioX-Shanghai with the project "XPCures" and SJTU-Software with the project "HEATMAP," successfully retained their gold awards, once again showcasing the talent of SJTU students on the international stage!

This year, the SJTU-BioX-Shanghai team focused on health and disease treatment. Xeroderma pigmentosum (XP) is an autosomal recessive genetic disorder reported in nearly all racial groups across continents. Patients are highly sensitive to ultraviolet radiation B (UV-B), with sun-exposed areas prone to blisters, epidermal hyperplasia, and tumors. Two-thirds of patients die before age 20, and there is currently no cure for XP. The team members focused on the most common type, Xeroderma pigmentosum complementation group C (XPC), which is caused by mutations in the XPC gene leading to abnormal DNA repair proteins and inability to repair UV-B-induced DNA damage. Inspired by a UV-responsive system in plants, the team decided to design a novel UV-responsive gene switch to achieve controlled expression of the XPC gene in patients, converting pathogenic UV-B into therapeutic UV-B.

The team combined this UV-responsive system from plants with transcriptional regulatory elements to develop a novel therapy based on optogenetics and gene therapy, while also constructing a negative feedback regulatory mechanism. The system can be delivered to skin basal layer cells via an adeno-associated virus delivery system using microneedles for transdermal delivery to achieve replacement therapy.

After validating the effectiveness of the plant-derived UV-responsive system in mammalian cells, the team conducted functional tests on the system in human keratinocytes. They found that keratinocytes lacking the XPC gene underwent massive apoptosis after UV-B exposure, while the survival rate of XPC-deficient cells transfected with the system approached normal levels, strongly demonstrating the effectiveness of the UV-responsive gene switch system. This system plays a crucial role in repairing UV-induced DNA damage, providing new insights for future XP treatment.

Meanwhile, the team actively engaged with stakeholders from various sectors, continually optimizing the project based on their feedback to make XPCures safer and more effective in meeting patient needs. Additionally, SJTU-BioX-Shanghai envisioned the future path for XPCures from basic research to medical products, detailing steps such as patent application, preclinical trials, clinical trials, investigator-initiated clinical studies, and market entry. By interviewing practitioners from governments and hospital ethics committees, the team gained insights into special policies and safety and ethical considerations for rare disease gene therapy development. In advancing the project, the team members gradually painted a picture of the social situation of the rare disease patient community, appealing to all sectors of society to pay attention to this group, fully demonstrating humanistic care for patients with rare diseases.

Meanwhile, the team actively engaged with stakeholders from various sectors, continually optimizing the project based on their feedback to make XPCures safer and more effective in meeting patient needs. Additionally, SJTU-BioX-Shanghai envisioned the future path for XPCures from basic research to medical products, detailing steps such as patent application, preclinical trials, clinical trials, investigator-initiated clinical studies, and market entry. By interviewing practitioners from governments and hospital ethics committees, the team gained insights into special policies and safety and ethical considerations for rare disease gene therapy development. In advancing the project, the team members gradually painted a picture of the social situation of the rare disease patient community, appealing to all sectors of society to pay attention to this group, fully demonstrating humanistic care for patients with rare diseases.

In recent years, pests have caused 40% crop losses and $70 billion in economic losses, leading to an increasing demand for pesticides. However, traditional pesticides are often difficult to degrade and highly toxic. This year, the SJTU-Software team focused on spinosad, a harmless, natural, and highly effective biological pesticide. Spinosad rapidly paralyzes and kills pests, with an insecticidal speed comparable to chemical pesticides but higher safety and a broader spectrum of action. However, low productivity, numerous by-products, and complex extraction processes make it expensive and difficult to promote.

After rounds of comprehensive research, the team found that the optimal temperatures for most enzymes do not match the actual fermentation temperatures, leading to low enzyme activity during production. Moreover, the existing methods for determining optimal temperatures are complex, resulting in missing data for most enzymes and difficulties in optimizing metabolic pathways.

Therefore, the team's project, "HEATMAP: Harmonizing Enzymatic Activity and Temperature in Metabolic Pathways," uses an AI model named HEATMAP-AI to predict the optimal temperatures of enzymes and establishes the etcGEM model to simulate the metabolic pathway for spinosad production in Saccharopolyspora spinosa. By combining these two models, the team identifies key enzymes limiting reaction rates in the production process. These enzymes are then further directed to evolve, making their optimal temperatures closer to reaction temperatures, thereby improving spinosad purity, unit production, reducing costs, and expanding market influence.

The deep learning model HEATMAP-AI developed by the team has higher accuracy than existing models, and the team continuously improves the model's prediction accuracy through wet experiment validation during iterative learning. To benefit more users with this model, the team developed the optimal temperature prediction platform HEATMAP, which allows users to obtain predicted optimal temperatures for any enzyme protein sequence by inputting it and download all enzyme sequences and optimal temperature information from the website.

Currently, the team has established contact and cooperation with several companies. In the future, the team will continue to maintain the model, optimize the project, and serve more people, assisting researchers in different fields to conduct research and contribute to the construction of actinomycete chassis organisms.

In addition, the team has done exceptional work in social research and social practice. To ensure project feasibility, team members consulted on global environmental and agricultural issues with the United Nations, highlighting the urgency and necessity of pest control. The team visited over 20 experts in the field to discuss the project content, visited enterprises to understand practical problems in the actual production process, and gradually optimized the project content through in-depth cooperation with Qilu Pharmaceutical, a spinosad producer, to jointly promote project implementation and landing. Furthermore, the team noticed bioethical issues in the field of synthetic biology, joining industry experts and Mengniu Dairy, a listed company in the synthetic biology products sector, to convene the "AI and Biosafety & Bioethics Roundtable Forum" with all iGEM teams in the Software & AI track in China, jointly compiling a white paper to promote the implementation of bioethics-related policies.

Meanwhile, the team conducted extensive science popularization efforts to promote the dissemination of synthetic biology knowledge. Through preliminary questionnaires targeting different age groups, the team categorized and carried out science popularization and publicity activities based on their understanding of synthetic biology knowledge, achieving good results.

The SJTU-Software team is led by Professor Chaochun Wei and associate researcher Yue Zhang, with valuable advice from Professors Linquan Bai, Haifeng Chen, Yan Feng, and Hongzhong Lu during the project advancement, and computing resources provided by the school's supercomputing center. The team consists of 17 undergraduates, captained by Xinyu Qian from the School of Life Sciences and Biotechnology. Team members also include Yuhang Cheng, Yuan Yuan, Ming Gao, Yibo Peng, Aifei Jiang, Jinliang Hua, Suning Wang from the School of Life Sciences and Biotechnology; Zhuohao Tang, Dian Zhang from Zhiyuan College; Zhiwei Yu from the School of Pharmacy; Minying Wang from the School of Biomedical Engineering; Siyu Chen from the School of Medicine; Chaokai Xu, Qihao Huang, Mingjian Yuan from the School of Design; and Yidan Zhang from the School of Media and Communication. The 2023 SJTU-Software team captain Junjie Zhu and the 2022 SJTU-Software team captain Jialu Wei served as technical advisors.