EGSB News

The projects of 13 Biosciences Area scientists and engineers received funding through the FY18 Laboratory Directed Research and Development (LDRD) program. These projects span a diverse array of topics and approaches including the study of microbiomes in relation to patterns of mutualism, crop productivity, and gut health; synthetic biology for engineering biosurfactant production and energy conversion pathways; and the application of technologies such as machine learning, high-resolution optical microscopy, and single-cell transcriptomics. Together, these efforts account for 18.75 percent of the $20 million allocated. Lab-wide, 74 projects were selected from a field of 215.

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.

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.

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.

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.