Modeling metabolic exchange between microalgae and bacteria to test mechanisms of bacteria-mediated biomass enhancement
ORAL
Abstract
Experiments have demonstrated that the rate of biomass production in laboratory batch cultures of the green algae Chlamydomonas reinhardtii is increased when it is co-cultured with the bacterium Arthrobacter strain P2b compared to when cultured on its own. The algal/bacterial co-culture shows an up to 2.4 times higher chlorophyll concentration compared to the axenic culture. This suggests a mutualistic interaction between the two organisms potentially mediated by metabolite exchange. Here we report the results of in silico investigations of the metabolic interaction between these two organisms with the aim of elucidating the underpinnings for this phenomenon. We have created the first genome-scale, constraint-based model (GSM) of strain P2b and used it to examine robustness of the organism’s metabolism to genomic and environmental perturbations. Additionally, we have also discovered a pathway for phytohormone production in P2b and have used the model to study the effect on the rest of its metabolism. Finally, by pairing the P2b model with a well-curated GSM of C. reinhardtii, and using in silico analysis methods like dynamic FBA and multi-objective flux analysis, we have begun to examine interactions between C. reinhardtii and P2b.
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Presenters
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Marc Griesemer
Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory
Authors
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Marc Griesemer
Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory
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Miriam Windler
Civil and Environmental Engineering, Stanford University
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Jeff Kimbrel
Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory
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Patrik D'haeseleer
Global Security Computing Applications Division, Lawrence Livermore National Laboratory
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Alfred Spormann
Civil and Environmental Engineering, Stanford University
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Xavier Mayali
Nuclear and Chemical Division, Lawrence Livermore National Laboratory
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Ali Navid
Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory