Personal History: A Theorist&aposs Mind Trained to Investigate Fundamental Biological Questions

　　Amazed by the generality of physics and curious about the nature of the beautiful universe it describes, I started to read translated popular western science books when I was 16, including A Bri History of Time and The Emperor&apossNew Mind. Although the books are abstract and abstruse, I enjoyed trying to understand them with every bit of my rationale and imagination. However, the book that has affected my life the most is not about physics, it is The Medusaand the Snail: More Notes of a Biology Watcher by Lewis Thomas. While reading it I realized that biology is not just a descriptive science but is underpinned by fundamental questions as well. The issues Thomas raised, from super-organism for social insects to mind as connected neurons, all shared the phenomenon of emergence. I wondered if there are universal laws of emergence.

　　With success in the College Entrance Exam, I chose to further my study in the interdisciplinary program in Yuanpei College of Peking University, which has a reputation as the best undergraduate program in China, planning to prepare myself for academic exploration of my teenage interests. Knowing that the answers to my interests can only be found at the interface of system theory and biology, I chose to specialize in Biological Sciences and take all the core courses of the mathematical department. I extended my curriculum to 5 years,not only to complete the mathematics courses, but also to learn more about physics and computer science.

　　I was confused by the great gaps between math and biology, until I entered the Center for Theoretical Biology of Peking University and got live experience of research. There, I joined the research group led by Prof. xx She, aleading scientist in complex system theory. I first participated in research on recognition of translation initiation sites (TIS), work reported in two published papers on which I was a co-author. I then started an independent project to investigate the unexpected transcription signals near the TISs that we found in the previous project. I first confirmed these signals to be indicators of "leaderless" translation initiation mechanisms and then designed a mot if finding algorithm specifically tailored to recognize them. The result was exciting: the leaderless TISs existed in significant number of genomes, distributed in nearly every phylum of Bacteria and Archaea, which contradicts the contemporary viewpoint of leaderless translation initiation. These are part of the results in a first-authored paper I&aposm currently preparing.

　　However, as a biology major, I&aposm more interested in what really happens in living organisms. So I turned to systems and synthetic biology, where quantitat live techniques and biological insights can be combined. At the end of 2006, as the leader, I initiated and organized the first iGEM (international Genetically Engineered Machine competition) team of Peking University. Inspired by the amorphous computing project of the MIT CSAI laboratory, I set out to design a hop count device with the goal of genetically identical bacterial cells developing into different but cooperating phenotypes, as in multi-cellular organisms. This device was proposed to be able to transmit itself as a signal between cells, record the times of itself being transferred and use that number on direct neighboring cells to express different genes. With my rigorous training in molecular biology, I was able to use a design in which the conjugation system was manipulated to delete a DNA fragment containing arbitrary genetic elements after each consecutive conjugation event. The genetic elements contained in the lost elements can be used to control downstream gene expression. My teammates and I spent the whole summer doing experiments to implement my design and proved its feasibility with extensive testing.I proposed a conceptual framework to combined this project and another related project. They won us the Grand Prize of iGEM 2007.

　　Academic interest: Inter-cellular Communication, Cooperation: A higher hierarchy for biological complexityI noticed in the systems biology literature that much fort has been invested in modeling systems, such as transcription regulatory or metabolic networks, in which cells are viewed as bags of enzymes. However, real biology does better than that. The major part of the bio-diversity is multi-cellular organisms. Even single cell bacteria form specific patterns and may have division of labor when facing complex environment. Cooperation is crucial and is ubiquitous in nature. It creates levels of complexity above that of the cell and may be an intermediate state in the evolution to multicellularity.

　　When we consider that populations of cells can begin to differentiate into patterns in which they can cooperate, interesting questions arise. What&aposs the mechanism for pattern formation? Here is one real example: When cyanobacteria cells develop into nitrogen-fixing heterocysts, a fixed spacing between heterocysts emerges. Is it a Turing Pattern? After reading papers on the molecular mechanism, I suggest that it is. The key components for the network are a non-diffusing positively auto-regulated master transcription factor for heterocyst development: hetR, and a transported peptide (patS) which is positively regulated by the hetR while inhibiting hetR expression in the neighboring cells. These resemble the slow diffusing activator and the fast diffusing inhibitor in Turing’s reaction-diffusion model for pattern formation. While it would be an interesting project to test the idea, there are even more exciting questions.

　　The evolution of cooperation has been a difficult issue for biologists ever since Darwin. How does cooperation evolve in a selfish world? There are now many papers discussing the possible mechanisms and strategies in a game theory perspective. I&aposd like to combine this evolutionary view with systems biology approaches to address a series of related questions: How do cells utilize noise in gene expression to generate individuality? How are different phenotypes selected into cooperating strategies? Are the cooperation patterns like the cyanobacteria example mentioned above well-tuned by natural selection or just a self-organizing phenomenon? With the quantitative and empirical tools that current systems biology provides, these questions and the assumptions behindthem can be well tested in several model systems including cyanobacteria, Bacillus subtilis and Caenorhabditis elegans embryo development.

　　I would like to consider these questions in a theoretical framework. All the information necessary for developing such patterns is encoded in a single genome. The information in the genome can be divided into two components corresponding to two hierarchies of bio-complexity, one for intra-cellular structureand regulation, the other for inter-cellular communication and patterns. Non-clustering non-cooperating single celled organisms only have the former hierarchy. What are the advantages of having another hierarchy? How and under what conditions does evolution move up to a new hierarchy of natural selection?How and under what conditions does information in the genome start to accumulate at another level? These topics could occupy my attention for a lifetime.

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