Xu, X., Department of Microbiology, Key Lab of Microbiology for Agricultural Environment, Ministry of Agriculture, College of Life Sciences, Nanjing Agricultural University, Nanjing, 210095, China, Newe Ya’ar Research Center, Agricultural Research Organization, P.O. Box 1021, Ramat Yishay, 30095, Israel; Liu, X., Department of Microbiology, Key Lab of Microbiology for Agricultural Environment, Ministry of Agriculture, College of Life Sciences, Nanjing Agricultural University, Nanjing, 210095, China; Chen, C., Department of Microbiology, Key Lab of Microbiology for Agricultural Environment, Ministry of Agriculture, College of Life Sciences, Nanjing Agricultural University, Nanjing, 210095, China; Hu, S., Department of Microbiology, Key Lab of Microbiology for Agricultural Environment, Ministry of Agriculture, College of Life Sciences, Nanjing Agricultural University, Nanjing, 210095, China; Gat, D., Department of Environmental Hydrology and Microbiology, The Zuckerberg Institute for Water Research, Ben-Gurion University of the Negev, Sede-Boqer Campus, Sede-Boqer, 8499000, Israel; Porob, S., Department of Environmental Hydrology and Microbiology, The Zuckerberg Institute for Water Research, Ben-Gurion University of the Negev, Sede-Boqer Campus, Sede-Boqer, 8499000, Israel; Ronen, Z., Department of Environmental Hydrology and Microbiology, The Zuckerberg Institute for Water Research, Ben-Gurion University of the Negev, Sede-Boqer Campus, Sede-Boqer, 8499000, Israel; Jiang, J., Department of Microbiology, Key Lab of Microbiology for Agricultural Environment, Ministry of Agriculture, College of Life Sciences, Nanjing Agricultural University, Nanjing, 210095, China;
Microbial communities play a vital role in biogeochemical cycles, allowing the biodegradation of a wide range of pollutants. The composition of the community and the interactions between its members affect degradation rate and determine the identity of the final products. Here, we demonstrate the application of sequencing technologies and metabolic modeling approaches towards enhancing biodegradation of atrazine—a herbicide causing environmental pollution. Treatment of agriculture soil with atrazine is shown to induce significant changes in community structure and functional performances. Genome-scale metabolic models were constructed for Arthrobacter, the atrazine degrader, and four other non-atrazine degrading species whose relative abundance in soil was changed following exposure to the herbicide. By modeling community function we show that consortia including the direct degrader and non-degrader differentially abundant species perform better than Arthrobacter alone. Simulations predict that growth/degradation enhancement is derived by metabolic exchanges between community members. Based on simulations we designed endogenous consortia optimized for enhanced degradation whose performances were validated in vitro and biostimulation strategies that were tested in pot experiments. Overall, our analysis demonstrates that understanding community function in its wider context, beyond the single direct degrader perspective, promotes the design of biostimulation strategies. © 2018, International Society for Microbial Ecology.
Xu, X., Department of Microbiology, Key Lab of Microbiology for Agricultural Environment, Ministry of Agriculture, College of Life Sciences, Nanjing Agricultural University, Nanjing, 210095, China, Newe Ya’ar Research Center, Agricultural Research Organization, P.O. Box 1021, Ramat Yishay, 30095, Israel; Liu, X., Department of Microbiology, Key Lab of Microbiology for Agricultural Environment, Ministry of Agriculture, College of Life Sciences, Nanjing Agricultural University, Nanjing, 210095, China; Chen, C., Department of Microbiology, Key Lab of Microbiology for Agricultural Environment, Ministry of Agriculture, College of Life Sciences, Nanjing Agricultural University, Nanjing, 210095, China; Hu, S., Department of Microbiology, Key Lab of Microbiology for Agricultural Environment, Ministry of Agriculture, College of Life Sciences, Nanjing Agricultural University, Nanjing, 210095, China; Gat, D., Department of Environmental Hydrology and Microbiology, The Zuckerberg Institute for Water Research, Ben-Gurion University of the Negev, Sede-Boqer Campus, Sede-Boqer, 8499000, Israel; Porob, S., Department of Environmental Hydrology and Microbiology, The Zuckerberg Institute for Water Research, Ben-Gurion University of the Negev, Sede-Boqer Campus, Sede-Boqer, 8499000, Israel; Ronen, Z., Department of Environmental Hydrology and Microbiology, The Zuckerberg Institute for Water Research, Ben-Gurion University of the Negev, Sede-Boqer Campus, Sede-Boqer, 8499000, Israel; Jiang, J., Department of Microbiology, Key Lab of Microbiology for Agricultural Environment, Ministry of Agriculture, College of Life Sciences, Nanjing Agricultural University, Nanjing, 210095, China;
Microbial communities play a vital role in biogeochemical cycles, allowing the biodegradation of a wide range of pollutants. The composition of the community and the interactions between its members affect degradation rate and determine the identity of the final products. Here, we demonstrate the application of sequencing technologies and metabolic modeling approaches towards enhancing biodegradation of atrazine—a herbicide causing environmental pollution. Treatment of agriculture soil with atrazine is shown to induce significant changes in community structure and functional performances. Genome-scale metabolic models were constructed for Arthrobacter, the atrazine degrader, and four other non-atrazine degrading species whose relative abundance in soil was changed following exposure to the herbicide. By modeling community function we show that consortia including the direct degrader and non-degrader differentially abundant species perform better than Arthrobacter alone. Simulations predict that growth/degradation enhancement is derived by metabolic exchanges between community members. Based on simulations we designed endogenous consortia optimized for enhanced degradation whose performances were validated in vitro and biostimulation strategies that were tested in pot experiments. Overall, our analysis demonstrates that understanding community function in its wider context, beyond the single direct degrader perspective, promotes the design of biostimulation strategies. © 2018, International Society for Microbial Ecology.