An imaging technique pioneered by Berkeley Lab is helping reveal the best antibodies to test for in rapid and reliable COVID-19 detection. Although current tests such as polymerase chain reaction (PCR) are highly accurate, these samples must be sent to an accredited lab for testing, causing a longer wait time for results. Michal Hammel, a research scientist in the Molecular Biophysics and Integrated Bioimaging Division, and Curtis D. Hodge led a study that could help get reliable, self-administered tests with instant results on the market.
In a study appearing in Nature Plants, researchers from UC Davis, UC Berkeley, and Berkeley Lab report the discovery and characterization of a previously undescribed lineage of form I rubisco – one that the researchers suspect diverged from form I rubisco prior to the evolution of cyanobacteria. The novel lineage, called form I’ rubisco, gives researchers new insights into the structural evolution of form I rubisco, potentially providing clues as to how this enzyme changed the planet.
The work was led by Patrick Shih, a UC Davis assistant professor and the director of Plant Biosystems Design at the Joint BioEnergy Institute (JBEI), and Doug Banda, a postdoctoral scholar in his lab.
A group of researchers at Washington University School of Medicine have used the capabilities available at the Advanced Light Source’s SIBYLS beamline to gain insight into an enzyme that functions in blood clotting. ADAMTS13, which stands for a disintegrin and metalloproteinase with thrombospondin-1 repeats, member 13, is a multi-domain protease enzyme whose catalytic mechanism involves a metal. It is the only known protein to regulate the adhesive function of von Willebrand factor (VWF), a blood clotting protein involved in hemostasis.
Bioscientists at the Advanced Light Source (ALS) at Berkeley Lab lent their expertise to a project led by scientists at the University of Washington to design proteins in the lab that zip together like DNA. The technique could enable the design of protein nanomachines to help diagnose and treat disease, allow for more precise engineering of cells, and perform a variety of other tasks.
CASP is the Critical Assessment of Protein Structure Predictions, a biannual “competition” to determine which prediction algorithm generates the most accurate model. There are several categories in which models will be assessed, including accuracy, topology, and biological relevance. The SIBYLS beamline is participating to provide small-angle X-ray scattering (SAXS) data for––and judging for the first time––the “data-assisted” category. This CASP competition should lead to improvement in predicting protein-protein interfaces and complex structures.