Chemotherapy and radiation treatments can be life-saving for patients with cancer, but they have harsh side effects that can been felt and seen throughout the body. There can also be unseen consequences: These important treatments can mutate DNA and damage chromosomes in patients’ cancerous and noncancerous cells alike. When this occurs in a germline cell (eggs in women and sperm in men), it can lead to serious fetal and birth defects in a resulting pregnancy. In a study published in PLOS One, a team led by Biological Systems and Engineering (BSE) Division senior scientist Andrew Wyrobek reported success adapting an established cellular DNA analysis technique called fluorescence in situ hybridization (FISH) to probe sperm DNA for a wide variety of chromosomal defects simultaneously.More »
The protein CheY plays a role in relaying sensory signals from chemoreceptors to the rotary motor at the base of the tail-like appendage, or flagellum, that protrudes from the cell body of certain bacteria and eukaryotic cells. It has been studied as a model for dissecting the mechanism of allostery—the process by which the binding of biological macromolecules (mainly proteins) at one location regulates activity at another, often distant, functional site. When it is transiently phosphorylated in response to chemotactic cues, CheY’s binding affinity for a flagellar motor switch protein called FliM is enhanced. CheY binding to FliM changes the direction of flagellar rotation from counterclockwise to clockwise.
Using X-ray footprinting with mass spectroscopy (XFMS), a team led by Shahid Khan, a senior scientist with the Molecular Biology Consortium, established that CheY changes shape when it tethers to the motor, and further parsed the contribution of phosphorylation to this shape change. The results of the XFMS experiments validated atomistic molecular dynamics (MD) predictions of the architecture of the allosteric communication network, marking the first time that XFMS has been used to validate protein dynamics simulations at single-residue resolution sampled over the complete protein.More »
The American Association for the Advancement of Science (AAAS), which was founded in 1848 and is the world’s largest general scientific society, announced that 489 of its members—among them nine scientists at Berkeley Lab—have been named Fellows. This lifetime honor, which follows a nomination and review process, recognizes scientists, engineers, and innovators for their distinguished achievements toward the advancement or applications of science.
The three newly named Fellows from the Biosciences Area are: Sanjay Kumar, a faculty scientist in the Biological Systems and Engineering (BSE) Division; Mary Maxon, the Associate Laboratory Director for the Biosciences Area; and Len Pennacchio, a senior scientist in the Environmental Genomics and Systems Biology (EGSB) Division and the Deputy of Genomic Technologies at the DOE Joint Genome Institute (JGI).More »
This spring, Mina Bissell, distinguished senior scientist in the Biological Systems and Engineering (BSE) Division, was awarded the 2020 Canada Gairdner International Award for Biomedical Research. Due to the ongoing coronavirus pandemic, the Gairdner Foundation held their annual Laureate Lectures and Gala Celebration—normally hosted in Toronto, Ontario, Canada—virtually this year. Bissell presented her talk, entitled “Why Don’t We Get More Cancer?”, about a signaling pathway she and her research group discovered that doesn’t get turned off in cancer and leads to uncontrolled growth. She received her medal surrounded by family at home in Berkeley, and spoke about the power of empathy.
Engineering biological systems to specification–for example, designing a microbe to produce a cancer-fighting agent–requires a detailed mechanistic understanding of how all the parts of a cell work. Typically, this knowledge is acquired through years of painstaking work and a fair amount of trial and error. But Berkeley Lab scientists have created an Automated Recommendation Tool (ART) that adapts machine learning algorithms to the needs of synthetic biology to guide development systematically. With a limited set of training data, the algorithms are able to predict how changes in a cell’s DNA or biochemistry will affect its behavior, then make recommendations for the next engineering cycle along with probabilistic predictions for attaining the desired goal. The work was led by Hector Garcia Martin, a researcher in Berkeley Lab’s Biological Systems and Engineering (BSE) Division and Tijana Radivojevic, a BSE data scientist. In a pair of papers recently published in the journal Nature Communications, they presented the algorithm and demonstrated its capabilities.
Read more in the Berkeley Lab News Center.