Multi-scale Metabolic Modeling Research
Metabolic models of metabolism are mathematical, network-based, and large-scale representations of the set of chemical reactions for which various types of evidence exists. These models are generally reconstructed from publicly available data, or in collaboration with in vivo researchers, and their reconstruction and analysis is often accomplished using freely available programming languages and packages, or programmable computational methods. Many such models account for all reactions supported by their annotated genome, in which case they are said to be genome-scale models (GSM). GSMs span many levels of complexity ranging from purely stoichiometric to metabolic networks accounting for protein synthesis (resource analysis models) to kinetic models of metabolism. Metabolic models have been applied to a wide range of applications including bioengineering (their most typical application), investigation of metabolism, and medical applications. Examples of metabolic investigation include resolution of basic metabolic questions such as atypical energy sources, metabolic reprogramming under stress, exploring understudied pathways, multi-scale elucidation of regulation, and drug repurposing. My proposed research plan leverages the breadth of systems that can be modeled, model types, model applications, the development of new modeling techniques, and publicly available yet underleveraged datasets, along with potential collaborations within WSU and the PNNL to develop a broad program of research addressing key challenges including improved plant tolerance to heat and drought stresses, drug repurposing, and designing cyanobacteria as CO2 to biochemical platforms. These proposed applications highlight only a fraction of the breadth of modeling applications, and our lab is actively searching for collaborative in vivo and in vitro researchers with which to work to use modeling techniques to answer fundamental research questions.
Collaboration and Involvement
Multi-scale metabolic modeling is naturally collaborative and brings together a wide variety of skills and knowledges to achieve research goals. Therefore, our lab group brings together undergraduate researchers at all stages of their education, graduate students, and collaborators across a broad range of field to address some of the most pressing challenges at the intersections of metabolism, health, enzymology, and plant science. Metabolic models are excellent at elucidating fundamentals of metabolic systems which may be difficult or expensive to measure, as well as hypothesizing genetic interventions and experiments to improve or elucidate phenotype. As an example of what metabolic modeling can contribute to other research areas, here are some examples of research I have participated in (as primary researcher or in a supervisory/mentoring role):
Borrowing from economics, I investigated the shadow price of protective pigment (melanin, carotenoid) production in the fungus Exophiala dermatitidis. Additionally investigated melanogenesis pathway compared to humans as a potential model system.
Constructed a four tissue seven stage lifecycle model of Arabidopsis thaliana for plant lifecycle modeling.
Investigated metabolic adaptations of Zea mays root tissue to nitrogen starvation.
Investigated pyrophosphate metabolism in Clostridium thermocellum to attempt to identify its primary source and
Construction of a three tissue diurnal model of Populus tricocarpa under control and drought conditions. Comparison of metabolism was used to hypothesize genetic interventions improving biomass yield under drought conditions.
Current projects in the Schroeder Lab include:
Investigating the interrelations between fatty acid metabolism, reactive oxygen species, circadian rhythms, and seizures (using mice as the test system)
Reconstructing a multi-tissue model of the energy crop Sorghum bicolor (Sorghum) to investigate and redesign photorespiration, produce aromatic chemicals (in cell culture), and investigate ideotypes for high-density planting.
Engineering filamentous nitrogen-fixing bacteria to produce common fertilizers (like urea) to replace the energy- and material- intensive Bosch-Meiser process
The quality of a model is dependent on the quality of the data used in its construction. Often, the most valuable measurements for constructing models are measurements which are seen as simple, for example: growth rate and rate of uptake of the limiting nutrient. Because of this, communication with researchers before data collection can be key to quality model development.
Researchers who are interested in bringing metabolic modeling into their work are encouraged to contact the PI (Wheaton Schroeder, wheaton.schroeder@wsu.edu) to discuss potential research collaboration.