The LLNL Biofuels Scientific Focus Area (SFA) is focused on the community systems biology of microbial consortia that are closely associated with bioenergy-relevant plants and algae, with the ultimate goal of developing predictive models. Photosynthetic algal and plant systems have the unrivaled advantage of converting solar energy and CO2 into useful organic molecules. Their growth and efficiency are largely shaped and assisted by their surrounding “microbiome”—the groups of microorganisms that dwell in and around plants and algae and live off photosynthate, exopolymers, or exudates. The biogeochemical outcomes of these interactions—how specific taxonomic combinations affect energy and nutrient cycling pathways and are shaped by various environmental stressors—are fundamental concerns in the fields of microbial ecology and bioenergy production.
We seek to understand and predict ecological, biophysical, and biochemical dynamics of multi-taxa communities, as well as the metabolite fluxes that regulate trophic interactions. In our research, we focus on microscale interactions between bacteria and algae in the phycosphere (the surface of algal cells) and between soil bacteria, fungi, and plant roots in the rhizosphere as model systems. Our approach emphasizes microbial ecology, organismal interactions, quantitative isotope tracing of elemental exchanges, and effects of environmental regulation, using techniques that exploit unique LLNL capabilities to measure the microscale impacts of single cells on system scale processes.
August 16, 2019
Katie Harding, a University of California at Santa Cruz graduate student conducting research at LLNL with SFA team members, won the best poster award at LLNL’s summer poster symposium for summer interns.
SFA team member Ty Samo presented his SFA-funded research at the Applied Environmental Microbiology GRC in South Hadley, MA this July.
In a recent special Research Topic in Frontiers in Microbiology, we published the results of pairing isotope tracing with NanoSIMS analysis to resolve activity to the single taxon level (using Chip-SIP) to examine the role of light in bacterial processing of algal organic matter.