A collaboration among experts at the Molecular Foundry, the Joint BioEnergy Institute (JBEI), and the Advanced Light Source has shown that the starting ingredients in an infinitely recyclable plastic known as poly(diketoenamine), or PDK, can be successfully made by microbes. The new approach shows that renewable, recyclable plastics are not only possible, but also outperform those from petrochemicals.
A Roadmap for Gene Regulation in Plants
A team of researchers from the Joint BioEnergy Institute’s (JBEI) Feedstocks Division has, for the first time, developed a genome-scale way to map the regulatory role of transcription factors, the proteins that play a key role in gene expression and determining a plant’s physiological traits. Their work reveals unprecedented insights into gene regulatory networks and identifies a new library of DNA parts that can be used to optimize genetic engineering efforts in plants.
Dylan Chivian, Microbial Explorer
Dylan Chivian’s upbringing motivated him to help humanity and the natural world. Now a microbial scientist and coding engineer with the Department of Energy Systems Biology Knowledgebase (KBase), he’s building software tools that aim to share microbial genomic information and promote collaboration across the broader scientific community.
Tiny Microbes Could Brew Big Benefits for Green Biomanufacturing
A research team led by Jay Keasling, Senior Faculty Scientist in the Biological Systems and Engineering and CEO of the Joint BioEnergy Institute (JBEI), has engineered bacteria to produce new-to-nature carbon products that could provide a powerful route to sustainable biochemicals.
How Technoeconomic Analyses Pave the Way to a Low-Carbon Future
Scientists in the Biosciences Area at Berkeley Lab are answering key questions about emerging technologies with technoeconomic analysis, a data-driven way to predict the best routes to decarbonization. Technoeconomic analysis uses computer models to evaluate the cost implications and potential environmental impacts of emerging technologies. This type of predictive analysis can be used to support decision-making by researchers, industry stakeholders, regulators, and policy-makers.
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