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.
The project just completed is a paradigm for analyses in the young field of systems biology and included a combination of experimental, bioinformatics, and computational modeling approaches. The overriding goal was a deeper understanding of a comparatively simple—yet difficult to comprehend—regulatory system that coordinates the metabolic responses of the bacterium Lactococcus lactis to starvation and acid stress. The particular focus of the analysis was the glycolytic pathway. On the experimental side, we characterized changes in glucose metabolism occurring under acid stress conditions and performed a directed evolution strategy, which led to significantly increased acid tolerance, up to a pH of 4.1. Our bioinformatics studies led to the proposal of genes affected by acid stress and candidate genes for a lactate transporter. As a result of our modeling studies, we now have an integrative mathematical model of glycolysis in L. lactis that, with a single set of parameters, fits available time course data better than any previous models. The model captures the full, complex dynamics of the pathway and reveals strategies with which the organism responds to starvation. We found that these strategies critically depend on the environmental milieu and, in particular, the presence or absence of oxygen. We had previously characterized this response under oxygen conditions. Here we studied an anaerobic milieu and found that if the glucose supply wanes, the subsequent metabolites, G6P and FBP, decrease in concentration, which reduces the synthesis of PEP. At the same time, the pyruvate kinase reaction is essentially shut down by the decreasing G6P and FBP activation, thereby leading to an overall accumulation of PEP. This accumulation inhibits the lactate dehydrogenase step, which stops the recycling of NAD+. As a consequence, FBP can no longer be degraded toward PEP, and the pathway dynamics comes to a halt. When this happens, a residual amount of FBP is retained. This residual amount is critical for restarting the pathway for a time when glucose becomes available again. To obtain these results, we developed several new computational techniques for smoothing data, estimating appropriate parameter values, identifying the format of processes within the system, and accounting for stochastic effects. The studies involved students of all levels of higher education. A highlight for the students was the organization of an international conference on the topic of systems and synthetic biology, where they helped in all aspects, from planning and inviting speakers to execution and participation. They also enjoyed serving as ambassadors for international visitors. During the funding period, the PI published an introductory text on systems biology which, according to the publisher, is already being used as a recommended or required text in about eighty courses around the world. All investigators gave presentations and used materials from the project in teaching and mentoring.
