Experimental and Computational Systems Analysis of Stress Responses in Lactococcus

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

The goal of this research is to provide a deeper understanding of the responses of Lactococcus lactis to fluctuations in its environment and to alterations in its genomic and metabolic make-up. Cross-disciplinary investigations of genomic and metabolic control in this bacterium will combine experimental studies using noninvasive in vivo nuclear magnetic resonance techniques with mathematical, statistical and computational modeling. Novel computational and statistical methods of genome inference, metabolic analysis, and model construction will be developed from experimental time series data. Analytical methods for understanding the bacterium's control of glycolysis will be extended to include noisy or incomplete data, and toward predictions with respect to multi-level control and regulation under untested experimental conditions. This project will result in a detailed understanding of sugar and energy metabolism in L. lactis and generate hypotheses about the underlying design and operating principles of physiological control tasks. These will have relevance beyond this particular organism and advance our understanding of fundamental mechanisms that are central to the evolution of life. The broader impact of the project includes the multi-faceted involvement in systems biological research of students with diverse backgrounds. First, the research will serve as a teaching and training tool for students and postdocs who are intrigued by the multi-disciplinary nature of systems biology. Second, the research is part of a test bed for an innovative cognitive study of the learning processes that must be mastered by any newcomer to the complex field of systems biology. Third, the research constitutes an emerging comprehensive case study for a graduate program in integrative systems biology that is being developed at Georgia Tech for students with different scientific backgrounds. This proposal is co-funded by the Cellular Systems Cluster in the Division of Molecular and Cellular Biosciences and the Physiological and Structural Systems Cluster in the Division of Integrative Organismal Systems.