Synthetic Biology Team
Chief Principal Investigators (PIs):Weiren Huang, Yuchen Liu
Core Team Members:Wei Chen, Zhichao Li
Research Focus and Directions:
Synthetic biology, a rapidly emerging interdisciplinary field, has been recognized by many countries as a strategic and disruptive technology area with the potential to lead to the third biotechnology revolution, following the discoveries of the "DNA double helix" and the "Human Genome Project". In medicine, artificial gene circuits introduced into living cells or organisms can actively sense disease-related signals and express or release therapeutic drugs, reconstructing homeostasis to correct disease-induced dysfunction. Utilizing the CRISPR-Cas9 system to construct "AND gate" gene circuits enables precise and specific identification of tumor cells, reprogramming complex intracellular signaling systems and cell fates. The construction of gene circuits like "CRISPRreader" with high AAV virus loading efficiency and therapeutic potential, as well as the development of efficient, safe, and high-load delivery systems, aims to revolutionize disease treatment.
The team is actively pursuing the following research directions:
Innovative Treatments Based on Remodeling the Tumor Microenvironment:By analyzing the systematic changes of diseased cells and their microenvironments using artificial intelligence (AI) and machine learning, the team deciphers the multi-level, multi-target network of disease progression. They apply an engineering design concept for systematic intervention in diseased cells, remodeling the disease microenvironment. Gene circuits integrated with chassis cell systems intelligently recognize changes in the internal and external cellular environments, reconstructing the fate of chassis cells to mediate microenvironment remodeling and improve cellular functional behavior for efficient disease treatment.
The main goal is to design a systematic targeting system for personalized tumor diagnosis and treatment. The primary outcomes include technical reports and patents on AI system design for microenvironment remodeling.
Precision Drug Screening for Tumors:The team has established an organoid culture system derived from various tumor tissues, including kidney cancer, bladder cancer, upper urinary tract urothelial carcinoma, nasopharyngeal carcinoma, lung cancer, liver cancer, colon cancer, breast cancer, and thyroid cancer. By comparing morphology, conducting multi-omics analyses, and detecting tumor markers, they have developed a tumor organoid culture system encompassing multiple cancer types and constructed a living organoid sample library from clinical samples. Integrating organoid culture with chip automation technology, they aim to build an automated, chip-controlled organoid library for patients, creating a standardized, automated, and high-throughput organoid culture technology platform. Organoid chips serve as preclinical models to predict individual drug responses, providing effective recommendations for personalized medication and supporting the realization of personalized tumor treatment.
The main goal is to develop multi-cancer tumor organoid culture methods and high-throughput drug screening chips. The primary results include major technical reports, patents, and product registration certificates for organoid culture and high-throughput drug screening.
Tumor Neoantigen Screening and Application Platform Based on AI "Test Learning":Utilizing a self-developed HLA-peptide binding prediction algorithm, combined with whole exome sequencing and other omics technologies, the team employs AI and machine learning to screen tumor neoantigens and obtain neoantigen-specific TCR information. They further build a specific HLA-presenting cell library and TCR gene virus library for Chinese individuals using automated high-throughput biological facilities, developing tumor vaccines and an immune cell therapy platform based on tumor neoantigens for personalized precision treatment of malignant tumors.
The main goal is to establish a precision treatment platform for tumors based on neoantigens and an AI-based tumor neoantigen screening system. The primary outcomes include key technical reports, patents, and product registration certificates for the tumor neoantigen screening system.
