Abstract
Transcriptional circuits play major roles in regulating T cell differentiation and response. Manipulating transcriptional machinery has been used to enhance T cell function in cell therapies, mainly via reinvigorating exhausted T cells towards effectors. In these studies, we have established a binary cell fate decision model between “partially functional survival” exhausted T cell fate and “hyperactive terminal” effector T cell fate and defined transcriptional immune checkpoint Fli1 as a safeguard to restrain effector proliferation and promote exhausted T cell progenitors. However, switching the cell fate from exhausted T cells to effectors will result in the reduction of cell durability during chronic antigen exposure and inflammation. Thus, we proposed new strategies about engineering cis-regulatory elements of effector associated genes. We first established orthogonal validation strategies of molecular and deep learning methods in tuning single bases in effector-associated genes and find key transcriptional circuits GATA3-TAL1 in regulating CD69 expression, and furthermore we developed in situ directed evolution system called Helicase-Assisted Continuous Editing (HACE) to process positional saturated single base mutagenesis on effector-gene enhancers and find multiple regulatory pathways towards effector-genes. Last, we performed generative model with prime editing screen and establish a strategy of generate de novo enhancer elements that drive gene expression in a context-specific manner，and further designed new DNA language model and molecular tools for dissecting native element functions in immune gene co-regulation patterns. Overall, by tuning transcriptional circuits, we can achieve the functional alteration of T cell fate and effector gene expression, which potentially lead to novel designs of context-specific T cell response circuits and contributes to microenvironmental precision-medicine.
Profile
陈则宇，北京大学基础医学院助理教授，研究员，博士生导师。2013年本科毕业于北京大学生命科学学院；2013年至2014年于耶鲁大学免疫系Richard A. Flavell实验室任科研助理；2014年至2020年于宾夕法尼亚大学免疫系E.John Wherry实验室攻读博士研究生并获得博士学位；2020年至2025年于哈佛大学医学院/博德研究所Bradley E. Bernstein实验室从事博士后研究工作，2025年4月入职北京大学基础医学院。
陈则宇共发表论文三十余篇，其中以一作/共同一作在Cell, Science, Immunity, Cell Genomics, Nature Reviews Immunology等期刊上发表论文6篇，总引用9600+，H-index 31，共6篇论文入选ESI高被引论文系列，并获批两项国际专利。
陈则宇实验室目前聚焦于T细胞转录调控的遗传编码解析及其工程化研究，拟开发和利用新型分子生物学和计算生物学工具，包括新型单碱基编辑系统，哺乳动物原位定向进化系统，基因组大语言模型模拟突变，生成式人工智能等，目标在原代T细胞上探究如下两个方向：1）解析基因组上碱基突变对于免疫基因调控功能的预测，进而理解人类遗传多态性如何影响人类免疫健康；2）突破自然进化基因组的调控瓶颈，建立生成式T细胞转录环路体系，进而实现病理微环境特异性的精准医疗。