JBIMS fosters collaboration and synergy across UC Berkeley and Berkeley Lab, combining strengths in Theory, Technology, Model Systems and Data Science to promote microbiome-based solutions for the health of our community, our ecosystems and our planet.
Integrative Microbiome Science for Discovery, Prediction and Translation:
Microbiome Theory
Coordinating across disciplines to advance and evaluate theories from ecology, evolution, biophysics and thermodynamics to understand and predict microbiome structure and function.
Technology for Microbiomes
Developing and integrating diverse technologies to observe and manipulate microbiomes and their interactions with their environments or hosts.
Data Science for Microbiomes
Building a community of microbiome researchers that promote data science best practices for reproducible and reusable datasets, and develop innovative science to uncover causal mechanisms in microbiomes.
Microbiome Model Systems
Developing and promoting the use of reproducible model systems for the study of microbiomes across scales of complexity.
News & Events
COBRA improves viral MAGs
Drs. LinXing Chen and Jill Banfield (IGI and EPS departments at UC Berkeley) unveiled Contig Overlap Based Re-Assembly (COBRA), a bioinformatic tool that resolves viral MAG assembly breakpoints. They tested the tool using >200 published freshwater metagenomes and found that COBRA vastly improved our ability to generate circular genome assemblies from 34% to 70%.
Published February 6, 2024 in Natural Microbiology.
Created by LinXing Chen.
The Swiss Army Knife of post-fire Paraburkholderia: rhamnolipid methyl esters
Mira Liu and members of the noteworthy Traxler Lab (PMB Department, UC Berkeley) found that multiple Paraburkholderia spp. isolated from burned soils produce unusual rhamnolipid surfactants. Upon further experimentation, they found that these molecules may serve multiple functions: they can inhibit other post-fire bacteria and fungi, aid in bacterial motility, and potentially solubilize hydrocarbons found in char. Published February 5, 2024 in ISME.
From Liu et al. (2024)
Predicting rhizosphere microbiome dynamics
Dr. Gianna Marschmann and members of LBNL’s Ecology Department used genome-inferred models of microbial traits and energy budgets to successfully predict metabolic strategies of plant-associated microbes. In doing so, their models highlighted important life history traits and trade-offs, which provide useful insights for improving microbial components of global biogeochemical models. Published February 5, 2024 in Nature Microbiology
From Marschmann et al. (2024)
Harnessing fermentation in sulfate-reducing bioreactors
Fermentative microbes are often undesirable in sulfate-reducing bioreactors used for the bioremediation of acid mine drainage, due to their competition for organic substrates with sulfate reducers. Drs. Tomas Hessler and Jill Banfield along with collaborators from the University of Cape Town find bioreactor and metagenomic evidence that H2 generated by fermenters may greatly benefit sulfate reducers in the reactors and propose this syntrophy could be harnessed in the future. Published February 1, 2024 in Environmental Science and Technology.
From Hessler et al. (2024)
Community Spotlights
Read More
Read More
Read More