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Associate 2012-13

Sheng Zhong

Bioengineering

Systems Biology of Cell Decision-making

After a cell begins life as a fertilized egg, it will divide into two cells, and then divide into four cells, and so on. Very soon the developing life form will have to make decisions: for example, which cells shall make the heart and which cells the skin? Understanding the biological principles of this cell decision-making is one of the great mysteries of life and represents a fundamental challenge in biology: How does a single cell give rise to a complex, multicellular organism?

During his Center appointment, Professor Zhong proposes to develop new ideas in this area. He will follow a systems biology approach to create and combine quantitative models, computational tools, and genomic technologies to study the molecular interactions as a whole. The project is high-risk and highly interdisciplinary, involving research components in bioengineering, statistics, molecular and cellular biology, computer science, and animal sciences.

Professor Zhong’s group has identified two major challenges to overcome. First, at the earliest stages of cell differentiation, how to distinguish among (a) cells sharing the same fate but involved in varying molecular activities not associated with cell fate, (b) cells of different types, or predisposition to certain types, and (c) technical noises from the measurements themselves. Second, because it is impossible to determine which cell was divided from which cell, how to associate time-course molecular data with each cell’s lineage.

To address the first challenge, the group will use a “bottom up” approach to model gene expression from the single-cell level to homogeneous cell groups and mixtures of cell groups. The goal is to tease apart the causes and effects of cell differentiation from gene expression. For the second challenge, they will barcode individual cells with fluorescent protein genes to trace cell division and test cell-fate determination at the two-cell stage. The information and predictive models resulting from this project will be directly relevant to understanding and preventing birth defects and prenatal deaths in humans.