Overview

The goal of the research in my laboratory is to understand fundamental paradigms that govern metabolic network design. We use a bacterial model system and emphasize a biochemical genetic approach that utilizes in vivo analyses to inform the design of in vitro experiments. Currently the research in the lab is focused on two general goals.

1) Understanding the Rid system of endogenous metabolite stress.

My laboratory recently identified a new stress system that is conserved across all domains. We showed that enamine metabolites, which are necessary intermediates in some PLP-dependent reactions, are able to damage cellular components. The RidA protein family (previously YjgF/YER057c/UK114) is responsible for deaminating the enamines to generate stable keto acid products. These findings have opened an exciting new field of study in the lab. Immediate questions include; which enzymes generate enamine stressors? Which enzymes are targets of the damage? What is the specificity of RidA homologs? What are the biochemical consequences of lacking RidA in various organisms? This project has not only defined a new stress and cellular response to it, but has implications for our understanding of the composition and characteristics of the cellular milieu.

ridA 

2) Exploring metabolic integration and redundancy

By virtue of the selective pressure exerted through millions of years of evolution, a living cell is likely to be the most well tuned and complex system in existence. The research in the laboratory uses classical approaches and emerging technologies to better understand the molecular details of metabolic processes and identify the mechanisms used to integrate these processes into a productive physiology. In our study of metabolic integration, we use a well-characterized biosynthetic pathway as a “nucleation point” from which to build and expand a model system. Our strategy has been to utilize genetic techniques to identify metabolic connections to this central pathway and thus build a defined network that we can then dissect on the molecular level. Recent addition of collaborators with metabolomics and mathematic modeling expertise has invigorated these studies, which have been the long term interest of the lab. Moving forward we will test the predictions from metabolomics data and mathematic models of metabolism with in vivo genetic biochemical approaches. 

robustness 

Mentoring Philosophy

My laboratory consistently has a strong and vibrant group of students that enjoy thinking about science and developing problem solving skills. We emphasize the development of models and the design of experiments to test them. Graduate and undergraduate students form the critical component of the lab community, which over time has also included, high school students, post-doctoral fellows and technicians. The laboratory emphasizes “big picture” thinking and thrives on complex questions that require one to integrate multiple variables and delve into the literature to recall the basics of metabolism, into which new data must be incorporated. Students from my laboratory have strong training in classical and molecular genetics particularly as applied to metabolic questions. They also utilize standard biochemical and molecular biological approaches. The direction of the research ensures that students will become familiar with the global metabolomics and mathematic modeling approaches used in Systems Biology. I strive to train students to think beyond linear pathways to appreciate the integrated nature of metabolism and the inherent chemistry that governs cellular processes.