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6月13日美国哈佛大学Ting Lu博士的学术报告通知2011-06-10
作者:管理员 来源:本站原创 时间:2012-4-27
题目:Emergent Pattern Formation in a Synthetic Bacterial Population
时间:6月13日(周一)19:00-20:30
地点:生科大楼245报告厅
     联系人:高海春   haichung@zju.edu.cn
 
                                                  
2011年6月10日
报告人简历:
     Lu 博士已被伊利诺伊大学香槟分校生物工程系聘为助理教授。在博士期间,在PNAS, Syst Biol等期刊发表多篇论文;在MIT和Harvard U.开展博士后研究期间,跟随合成生物学大师Ron Weiss 和抗生素机理研究大师James Collins ,目前已有两篇文章被Nature和Science 接受。欢迎科研人员和研究生朋友踊跃参加!有意在Lu博士研究方向深造的本科生和研究生请在讲座后直接接触。
 
 
报告摘要: Synthetic biology is an emerging field that integrates biology, engineering, and physical sciences with broad applications in systems biology as well as real-world concerns. In this talk, I will use our recently engineered patterning system as an example to illustrate how synthetic biology can be employed to tackle important biological questions. A fundamental challenge in developmental biology is to understand how global spatial patterns emerge from local interactions in a population of isogenic cells. Using a synthetic biology approach, we constructed a two-signal bacterial patterning system where one signal serves as an activator and the other as an inhibitor. An initially homogenous lawn of our engineered bacteria spontaneously produces Turing-like patterns with a spatial scale much larger than that of a single cell. Our experiments further suggest that the emergent patterns originate from a collective intercellular decision-making process rather than from initial spatial heterogeneity, population growth, or random cell-fate decisions of individual cells. To achieve a quantitative understanding of the patterning mechanism, we developed a stochastic spatiotemporal mathematical model producing simulations that correlate well with our experimental patterns and also allow us to examine the importance of gene expression noise in pattern formation. This synthetic system reveals design principles of biological patterning organisms, provides a platform for studying general features of cellular fate determination in developmental biology, and can be useful for programmed control over tissue development.
 

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