Agricultural Microbes Genome 2 Conference

Workshop: Bioinformatics
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BIOINFORMATICS AND THE ANALYSIS OF BACTERIAL METABOLISM

Department of Chemical Engineering, University of Delaware, Newark DE 19716

Biology is going through a period of fundamental change. The complete genome sequence for an increasing number of organisms is available. We will soon have the complete "parts catalogue" for many organisms. The next challenge is to search for the "blueprints" that underlie the various operations in the cell. Such an endeavor calls for the use of systems analysis of cellular processes based on the physicochemical properties of the gene products.

The need for systems based approaches to study physiological characteristics is two fold. First, the majority of cellular functions are multigenic in nature. To analyze, interpret, and ultimately predict cellular functions we must consider the interactions among the participating gene products. This will inevitably involve the methods of systems science to decipher this complex relation. Secondly, biological data is being produced at a rate that outweighs the ability experimentally examine the data. Thus, an experimental program based on the in silico predictions would be streamlined to address the most important questions.

The future success of many areas of biological study will depend greatly upon the ability to capitalize on the wealth of genetic and biochemical information currently being generated from the field of genomics. The engineering analysis of genome information will play a key role in these developments. This talk will illustrate how the metabolic characteristics of annotated small genomes can be analyzed using flux analysis and metabolic pathway analysis. The predictive and exploratory capability of the method will be discussed and highlighted by a few illustrative examples. The results presented will find applications in the pharmaceutical industry, such as bioprocess design, metabolic engineering, and drug target identification. Additionally, emphasis will be placed on the concept of utilizing genome information to gain an understanding of cellular physiology.