Scientists in Trent Northen’s groups in Environmental Genomics and Systems Biology (EGSB) and Metabolomics Technology at the DOE Joint Genome Institute (JGI) have published detailed video protocols for creating fabricated ecosystems, or EcoFABs, in the Journal of Visualized Experiments (JOVE). These laboratory-scale controlled habitats, constructed using widely available 3D printing technologies, enable mechanistic studies of plant-microbe interactions within specific environmental conditions. The published protocols serve as a starting point for other researchers, ideally helping to create standardized experimental systems for investigating plant-microbe interactions. The video component of this article can be found here.
Plants Really Do Feed Their Friends
Researchers at Berkeley Lab and UC Berkeley have discovered that as plants develop, they craft their root microbiome, favoring microbes that consume very specific metabolites. Their study could help scientists identify ways to enhance the soil microbiome for improved carbon storage and plant productivity.
Digging Deep: Harnessing the Power of Soil Microbes for More Sustainable Farming
How will the farms of the future feed a projected 9.8 billion people by 2050? Berkeley Lab’s “smart farm” project marries microbiology and machine learning in an effort to reduce the need for chemical fertilizers and enhance soil carbon uptake, thus improving the long-term viability of the land while increasing crop yields.
Environmental Genomics and Systems Biology Division’s Ben Brown and Haruko Wainwright of the Earth and Environmental Sciences Area are working with the University of Arkansas and Glennoe Farms on the “AR1K Smart Farm” project. This project brings together molecular biology, biogeochemistry, environmental sensing technologies, and machine learning in an effort to revolutionize agriculture and create sustainable farming practices that benefit both the environment and farms. Read the Berkeley Lab News Center feature story.
New Machine Learning Method Sees the Forests and the Trees
While it may be the era of supercomputers and big data, without smart methods to mine all that data, it’s only so much digital detritus. Now researchers at Berkeley Lab and UC Berkeley have come up with a novel machine learning method that enables scientists to derive insights from systems of previously intractable complexity in record time.
Impact of Environmental Changes on Microbes in Arctic Soils
As the Arctic continues to warm at about twice the rate of the rest of the world, scientists expect its frozen soils—known as permafrost—to thaw, activating microbes capable of decomposing soil and releasing carbons and other nutrients to the atmosphere and water. Berkeley Lab scientists in the Earth and Environmental Systems Area (EESA), led by microbial ecologist Neslihan Taş, set out to learn more about how Arctic soil microbes can contribute to greenhouse gas emissions under a warming climate. Taş’s research team collaborated with Susannah Tringe, Deputy for User Programs at the Joint Genome Institute (JGI), to conduct their study, funded by the Department of Energy’s Office of Biological and Environmental Research (BER). The results were published in Nature Communications.
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