CBIOMES Project: Thermodynamically Constrained Metabolic Networks for Ocean Modeling
Predicting how marine chemistry and biology will respond to global change is a pressing issue for society. This project will develop new modeling techniques for predicting such changes using ideas derived from physics in the subdiscipline of thermodynamics that concerns how energy moves in a system. Recent advancements in thermodynamics indicate that systems will internally organize so as to maximize the flow and dissipation of energy. For example, the temperature difference that develops between the ocean and atmosphere over the summer drives the formation of hurricanes (the organized structures), the presence of which hastens dissipation of the temperature difference. This project utilizes this fundamental property but extends it to microbial communities, such as bacteria and phytoplankton, which form the base of the ocean food web and strongly influence ocean chemistry. Based on information on how biology utilizes solar and chemical energy to construct itself from carbon, nitrogen, phosphorus and other elements in the environment, the model can predict how metabolic functions, such as photosynthesis or nitrogen fixation from the atmosphere, are expressed over time and space within the ocean.
Joe Vallino’s initial research started in chemical engineering in an emerging field that is now known as systems biology; in particular he was one of the founding investigators in developing and applying flux balance analysis for metabolic engineering objectives. Over the last two decades he has extended systems biology approaches for understanding biogeochemistry orchestrated by microbial communities using a distributed metabolic network as a framework to interpret and model functional gene expression in microbial communities. He currently employs control theory, computational science and non-equilibrium thermodynamics to predict functional gene expression governing mass and energy flow in microbial communities. New theories and computational algorithms are tested using a combination of microcosm experiments and field-based observations and data assimilation. Joe Vallino received his Ph.D. at MIT, and then broadened his research focus to natural microbial communities as a Mellon postdoctoral scholar at the Scripps Institution of Oceanography and a Lakian postdoctoral scholar at the Marine Biological Laboratory. He is currently a senior scientist at MBL.