Research
Genome-scale models of cellular processes
Although detailed models of cellular processes have been constructed in the past, research in this area has attained a new dimension in the last few years due to the development of novel high-throughput experimental techniques for both sensing and manipulating cellular processes at a molecular level. As an example, both steady state genome scale models and smaller dynamic models of metabolism of several industrially important organisms including Escherichia coli have been developed in the past. More recently, such models have been developed for a metal reducing bacteria (Geobacter sulfurreducens) with applications in bioelectricity and bioremediation and have been used to rationally engineer the metabolism for improved electricity generation. However, further research is required to extend such models of metabolism to represent the inherent dynamics of biological systems and to account for the increased complexity in multi-cellular organisms and microbial communities.
Optimization and control of biological processes
Biological systems span several orders of magnitude in time scales (e.g., enzymatic reactions that take place in seconds-minutes, protein synthesis which takes a few minutes, cellular growth which takes a few hours, and finally, evolution at the organism levels which can take many days to years). Similarly, these systems are spread across and interact at multiple length scales from a few nanometers in an intracellular environment to several meters in the case of microbial communities in ground water and oceans.
Several engineering disciplines (e.g., mechanical, electrical, & chemical) routinely use quantitative models for design and optimization of processes of interest. However, such rational approach to design and optimization has been possible in the life science only recently due to the lack of predictive large-scale models of biological processes in the past. Research activities in our group include the design of dynamic model-driven engineering strategies for biological process optimization and control across different length and time scales (i.e., from microscopic (intracellular) processes to macroscopic (bioreactor) processes).
Applications can include metabolic engineering (e.g., increasing the rate of electrical current in microbial fuel cells, designing dynamic gene manipulation strategies for increased product yields), biomedical engineering (drug design and dosage), bioreactor control and optimization (designing optimal substrate and inducer feeding strategies), and bioremediation (determining the spatiotemporal substrate addition strategies to effectively stimulate microbial activity).
Application: Models of Microbial Communities for Improving Bioremediation
In the environment, microbes rarely exist in isolation and almost always function together as a part of an overall community. These microbes can also communicate within these environments by synthesizing and spreading small organic compounds, a phenomenon known as quorum sensing. Understanding of how these communications and the individual function of species have evolved together can be valuable for reverse engineering these aspects for improved practical applications. An example of these applications is in the area of bioremediation.
Bioremediation of toxic heavy metals and chlorinated compounds is catalyzed by anaerobic microbial communities such as Geobacteraceae and Dehalococcoides spp. These remediation processes result from the reduction of these toxic compounds due to electron transfer by the anaerobic organisms. The electron transfer rate is directly related to respiration and the metabolic processes in the cell and consequently, it is critical to understand metabolism in these organisms for the efficient design of strategies for bioremediation of heavy metals and chlorinated compounds. Our group in collaboration with the Environmental Biotechnology Center at the University of Massachusetts directed by Prof. Lovley has pioneered the analysis of metabolism in such dissimilatory metal reducing bacteria and are actively working on analyzing the metabolism of Dehalococcoides spp in collaboration with Prof. Elizabeth Edwards.
Application: Model-based Engineering for Microbial Fuel Cells
In addition to the bioremediation of toxic metals, Geobacteraceae members can also transfer electrons onto an electrode in a microbial fuel cell environment. Although the coulombic efficiency of this process is high, the rates of electron transfer is low. Hence, approaches for understanding the metabolic processes in a microbial fuel cell and redesign of metabolism is required for increasing the rate of electron transfer. We have utilized metabolic models for engineering the metabolism in this bacteria to increase the rate of respiration as way of increasing the electron transfer onto the electrodes. Research in this area is performed in collaboration with Environmental Biotechnology Center and is funded by the Department of Energy's Genomics:GtL Initiative.