"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)."
University of North Carolina at Charlotte has been awarded a grant to develop software and a database resource for characterizing cis-regulatory binding sites in sequenced bacteria. Biological functions of a bacterial cell are carried out by the products of genes (proteins and RNAs) in the cell, but when, where, how much and how fast these proteins and RNAs should be expressed under different physiological and environmental conditions are mainly controlled by the interactions between specific transcription factor proteins and the cis-regulatory binding sites in the upstream regions of the genes on the chromosome. A better understanding of prokaryotes in general has great significance in global ecological control, efficient agriculture, better medicine and health, and renewable energy production. However, our general understanding of cis-regulatory systems in most sequenced bacterial genomes is very limited due to the lack of efficient and accurate experimental and computational methods for their characterization. The research team of this project will develop:
1) A new tool for more accurate prediction of operons in bacteria, since operons are the basic transcription units in bacteria and knowing operon structures in a genome can facilitate its cis-regulatory binding site prediction. 2) An efficient and accurate tool for genome-wide prediction of cis-regulatory binding sites in bacteria. 3) A database system to store the predicted operons and cis-regulatory binding sites in all sequenced bacteria genomes.
In addition, the results of these prediction tools will be verified and further refined through experimental validation of a large portion of the predicted novel cis-regulatory sites in E. coli K12. These software, database and experimental procedures will be freely available to the public, thus researchers can 1) directly apply the software to their genomes of interest; 2) use the database for target selection, experimental design and testing hypotheses when characterizing cis-regulatory systems in certain genomes; and 3) use the experimental procedures to verify the predicted cis-regulatory binding sites, and at the same time, identify the cognate transcription factors. Therefore, these tools and database will fundamentally change the way that biologists study cis-regulatory systems in bacteria. This project will also provide a unique educational platform to train the next generation of computational biologists, as one postdoctoral fellow, three PhD graduates, and various numbers of undergraduates and high school students will be trained in the project. Traditionally underrepresented minority and/or female students will be particularly encouraged to participate in the project. Furthermore, the algorithms and results generated from this project will be incorporated into the principle investigator?s newly developed courses at the University of North Carolina at Charlotte. More information about the project can be found at http://gleclubs.uncc.edu/pbs and information about the research team can be found at http://sulab.uncc.edu.
