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Our group focuses on the development and analysis of networks that represent cells as complex systems. By incorporating different types of biological data, such as gene expression profiles, proteomics studies, and genome annotations, these networks account for various cellular components and their interactions. Because cellular functions rely on the coordinated activity of multiple gene products, understanding the interrelatedness and connectivity of these elements is essential. Networks must therefore include the interactions between DNA, transcripts, proteins, and other molecular components. The research group has begun to tackle the challenge of incorporating both transcriptional and kinetic regulatory information into their models. The modeling of transcriptional regulation has included studying regulatory network structure and how it further influences and constrains a cell's metabolic function. Functional analysis and representation of genomes and their characteristics represent the most interesting and exciting challenges now facing bioengineering. The work undertaken by the Systems Biology Research Group is attempting to meet these challenges by laying the foundation for fully integrated single-cell models.
systemsbiology.ucsd.edu
Regulatory interactions identified via chromatin immunoprecipitation (ChIP) in Escherichia coli represent a first step toward extending our knowledge of the underlying E. coli transcriptional regulatory network. In many cases, the direct interaction between transcription factor and target gene may stem from regulation through unidentified cellular components such as other transcription factors or proteins. In an effort to discriminate between these indirect effects and direct regulatory interactions, we are performing genome-wide location analysis. Typical ChIP experiments require an antibody for the isolation of target chromatin complex from cell extract. Although specific antibodies could be generated and used for each transcription factor, it is cost-prohibitive and tedious in large-scale experiments. Therefore, the PCR-based tandem epitope tagging method described here is the method that led to a versatile genetic strategy enabling rapid and effective immune-activity generation of the target proteins against commercial antibodies. The significance of the method is that it lays the foundation for obtaining the high-throughput experimental data necessary for the systematic analysis of transcriptional regulatory networks.
PCR-based tandem epitope tagging system for Escherichia coli genome engineering, p. 67.
