Successful completion of the Human Genome Project has led to the realization that effective models for predicting cellular behavior must take into account the dynamic network interactions that mediate gene regulation. Since behavior arising from these complex interactions is difficult to predict with qualitative reasoning, there is a need for experimentally validated computational modeling approaches that can be used to understand the complexities of gene regulation. Such model approaches will be invaluable in the generation of logically consistent hypotheses and will provide a framework for the systematic comparison of data across multiple experiments. The design and construction of de novo synthetic gene ``circuits'' provides a natural framework for reducing the complexity of gene regulatory networks. This approach combines tools from nonlinear dynamics and statistical physics with the extensive array of techniques in traditional molecular biology. The power of this approach is that it can be used to study simplified systems in order to gain insight into the modular components of gene regulation. Our research is directed towards the construction and utilization of gene circuits for dissecting, analyzing, and controlling the dynamical interactions involved in gene regulation. We have two general goals in pursuing this research:

To develop a quantitative computational framework for understanding the dynamics of gene regulatory networks. The ability to design synthetic gene circuits offers the exciting prospect of extracting carefully chosen subsystems from natural organisms and focusing both modeling and experimental efforts on determining the subsystems' behavior in isolation. Our approach is to assemble increasingly complete models of the behavior of natural systems through the coupling of small modules, while maintaining at each stage the ability to test models in a tractable experimental system.

To develop cellular control schemes for potential therapeutic applications. Engineered gene circuits represent a first step towards logical cellular control, whereby biological processes can be manipulated or monitored at the DNA level. Such control may have a significant impact on post-genomic biotechnology. From the construction of simple switches or oscillators, one can envision the design of genetic code, or software, capable of performing increasingly elaborate functions.

In order to accomplish these goals, we adopt a highly multidisciplinary approach which entails the integration of computational modeling and molecular biology, along with the development of novel experimental assays utilizing microscopy and microfabrication techniques. Computational modeling is used both in the development of "design criteria" for genetic circuits and in the generation of hypotheses for naturally-occurring regulatory modules. We develop novel computational approaches which can be systematically tested against experimental data and modified if necessary. Standard tools from molecular biology are utilized both to build novel synthetic gene networks and to modify naturally-occurring regulatory modules. These networks are constructed and modified in accordance with computational modeling predictions and are used to validate or refute model assumptions. Lastly, in order to quantitatively compare model and experiment, new experimental assays are needed. Here we develop new technologies that allow for single-cell dynamical measurements over a large population of cells.

Facilities

The overall goal of the Systems Biodynamics lab is to use computational models to accurately predict the behavior of genetic regulatory experiments. Our wet laboratory (1000 sq. ft.) and computational laboratory (500 sq. ft.), as well as the Molecular Biotechnology Core (1600 sq ft), are housed in the Powell-Focht Bioengineering Hall at UCSD. Experiments are conducted in Escherichia coli, Saccharomyces cerevisiae, Neurospora, and mammalian Hela cells. The design and implementation of these experiments is typically carried out by UCSD Bioengineering undergraduate and graduate students. Modeling is conducted in our computational laboratory, which currently houses eight graduate students and two postdocs, and consists of approximately 15 high-end pentium machines running windows or linux. For projects requiring more extensive computational resources, we utilize the San Diego Supercomputer Center (SDSC), which is housed at UCSD. This Center is one of two nationally funded Centers for computational science, and has pioneered the birth of the Bioinformatics era with its strong emphasis on computational biology. In addition, the SDSC houses the Protein Data Bank, the Biology Workbench, and a host of other high-end computing resources for the national community.

Core Facility

The SBL manages a molecular biotechnology core facility located at PFBH 344 . Access to the core is organized by each participating laboratory. Training for specialized equipment is available. For questions, please contact biotech AT bioeng.ucsd.edu.