EGSB News

University of California San Francisco (UCSF), UC Davis, and Lawrence Berkeley National Laboratory (Berkeley Lab) have formed a Tri-Institutional Partnership in Microbiome Research (TrIP Microbiome) to catalyze and fund novel, bold, and potentially transformative collaborative microbiome research projects. A unique aspect of the partnership is its data-driven focus and data infrastructure, brought through the participation of the Berkeley Lab-led National Microbiome Data Collaborative (NMDC). The NMDC is working with TrIP Microbiome researchers to catalyze experimental co-design between biologists and computational scientists, adoption of data management best practices, and open science to enable cross-study comparison and machine learning.

The Encyclopedia of DNA Elements (ENCODE) collaboration was launched 17 years ago by the National Human Genome Research Institute with the goal of developing the tools and expertise needed to shed light on the 98% of our genome that does not code for proteins. Now in its final year, ENCODE has made huge advances thanks to the combined scientific and technological prowess of several hundred researchers at dozens of institutions. Leading the project for Berkeley Lab are Diane Dickel, Len Pennacchio, and Axel Visel, co-PIs of the Mammalian Functional Genomics Laboratory in Biosciences’ Environmental Genomics and Systems Biology (EGSB) Division. They are co-authors on 4 of the 15 new ENCODE papers published this week as part of a special collection in Nature.

Under a special project launched in May, a Berkeley Lab–led team of computing and bioinformatics experts is developing a platform that consolidates disparate COVID-19 data sources and uses the unified library to make predictions—about potential drug targets, for example.

Lysine is an important amino acid that must be supplied in our diets, as our bodies can’t produce lysine on their own. Most cereal grains have low levels of lysine, and scientists have worked to breed crops with higher lysine levels. 

However, the biochemical processes that break down lysine in plants weren’t fully understood. New Joint BioEnergy Institute (JBEI) research, published in Nature Communications, reveals this last missing step of lysine catabolism. 

A cross-disciplinary team of Berkeley Lab scientists with expertise in climate modeling, data analytics, machine learning, and geospatial analytics is launching a project to determine if the novel coronavirus might be seasonal. The team will apply machine-learning methods to a plethora of health and environmental datasets, combined with high-resolution climate models and seasonal forecasts.