Biosciences News

The Vilcek Foundation has honored Markita del Carpio Landry, faculty scientist in Molecular Biophysics and Integrated Bioimaging and assistant professor at UC Berkeley, with the 2022 Vilcek Prize for Creative Promise in Biomedical Science. Landry’s work centers on understanding aberrations in neurotransmitter signaling—a fundamental component in psychiatric disorders such as depression, and schizophrenia, and neurodegenerative disorders such as Alzheimer disease. She has also led work that has elucidated transport phenomena in plants, which has applications in agricultural biotechnology with regard to the development of food and medicine.

A team of scientists, including Joint BioEnergy Institute (JBEI) researchers, studying the biochemistry of plant cell walls have identified an enzyme that could turn woody poplar trees into a source for producing a major industrial chemical. The research, recently published in Nature Plants, could lead to a new sustainable pathway for making “p-hydroxybenzoic acid,” a chemical building block currently derived from fossil fuels, in plant biomass.

Einstein’s theory of general relativity, which describes gravity as a curvature of space-time, explains a multitude of gravitational phenomena, but that theory falls apart within the tiniest of volumes.

Researchers at Berkeley Lab and the National Institute of Standards and Technology (NIST) proposed an experiment that may settle the persistent question: Is gravity truly a quantum force? They recently described their work in the journal Physical Review X Quantum.

Scientists who specialize in studying the atom-by-atom choreography of enzymes have revealed new insights into the function of isopenicillin N synthase, an enzyme needed to produce some of the world’s most critical antibiotics.

For structural biologists who study proteins, predicting their shape offers a key to understanding their function and accelerating treatments for diseases like cancer and COVID-19. The current approaches to accurately mapping that shape have their limitations, but by applying powerful machine learning methods to the large library of protein structures it is now possible to predict a protein’s shape from its gene sequence.