Dr. Allen’s research interests include the analysis of metabolic networks in plants by combined experimental and computational methods. These investigations give insight to plant metabolism, important for designing crops to meet future nutritional and chemical feedstock needs. Doug received his Ph.D. in Engineering from Purdue University, has previously worked for the Archer Daniels Midland Company and the Great Lakes Bioenergy Research Center at Michigan State University, and joined the Danforth Center in the capacity of Research Computational Biologist with the USDA in 2010.
RESEARCH TEAM |
My lab is dedicated to understanding the metabolic networks of oilseed plants to enhance biomass composition.
Plant seeds represent an important supply of food, feed and fiber for humans and animals and are the world’s cheapest source of protein, oil and carbohydrates. Recently, the pressures to develop “green” solutions to our resource needs has led to intensified crop research as plants can also be grown as energy or industrial chemical feed stocks. The oil obtained from plants serves as an energetically dense form of biomass and can be readily processed into biodiesel or used for generation of polymers, plastics, surfactants, detergents and adhesives; that are currently petroleum-based. Therefore we are interested in oilseeds, such as soybean, that can provide the oils necessary to supplant some of our non-renewable dependencies.
Among the greatest challenges associated with increased oil production in seeds and other plant tissues is improving our understanding of the metabolism that governs storage reserve composition (i.e protein, oil and carbohydrate). Our work is focused on developing quantitative biochemical descriptions of the carbon, nitrogen, redox and energy flows necessary to generate these reserves in oilseeds. Studies of the response of the cell to genetic or environmental perturbations will lead to a more “systems level” understanding of plants and aid our fundamental understanding of cellular metabolism that in turn guides transgenic work.
Specifically, we employ systems level techniques such as metabolic flux analysis that integrate computational model building with experimental data obtained from isotopic labeling investigations. Experiments involve culturing plant tissues and measuring biomass composition as well as analyzing the redistribution of labeled carbon (13C/14C) or hydrogen (2H) atoms using a combination of GC/MS, NMR, GC/FID, scintillation counting and other biochemical techniques as necessary. The distribution of label in final storage reserves is a direct result of the fluxes through different biochemical pathways. Therefore these label measurements can be used within the context of a “retrobiosynthetic approach” to establish fluxes from models of central metabolism. Together, the experiments and models describe metabolic network activity and cellular response to environmental and/or genotypical perturbations.
Technologies available for license: