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Understanding bacterial cell cycle using synthetic biology

Multiplication is a fundamental requirement for all life forms. The doubling time of bacterial cells varies in different growth environments, ranging from approximately 20 minutes to several hours. The cell size, the amount of DNA content, the initiation time point of DNA replication, and the rate of DNA replication vary with the doubling time. In this project, we will combine synthetic biology with single-cell level analysis, such as microscopy and flow cytometry, and population-level analysis, including biochemistry, transcriptomics, and proteomics. Quantitative observations and analysis will elucidate the interconnections between bacterial cell growth, DNA replication, and cell division and reveal the underlying regulatory mechanisms at the molecular level.

Cancer therapy with synthetic bacteria

Existing cancer treatments, such as radiotherapy, chemotherapy, surgery, and targeted drugs, are not effective enough for mid- to late-stage cancers, especially recurrent and metastatic cancers. Cancer patients suffer from short survival periods, severe pain due to treatment, and high medical costs. Therefore, the development of more effective therapies for cancer is an urgent need. Microbial therapy aims to recognize and treat tumors by equipping microorganisms such as bacteria and viruses with various therapeutic modules. In this project, we use synthetic biology to engineer bacteria to develop novel therapies that can target a broad range of solid tumors and effectively inhibit cancer metastasis and recurrence.

Synthetic pattern formation

Pattern formation refers to the generation of regular spatial structures and plays essential roles in the development of organisms and ecosystems. Reconstructing biological patterns with synthetic biology allows us to simplify and control the systems, providing a new tool and research paradigm for studying pattern formation. The design and construction of biosystems with spatial patterns also provides the possibility of synthetic biomaterials, tissues, and organs with controllable spatial structures. The aim of this project is to elucidate the design principle of pattern formation. In this project, we will develop mathematical models to systematically investigate the system topologies that allow pattern formation during the range expansion of bacteria. Based on the quantitative predictions of modeling, we will design gene circuits and engineer synthetic bacterial strains.