The EcoFAB initiative will create a new center for world-class ecological research. Led by EGSB, EcoFAB will involve close collaborations with researchers at the DOE Joint Genome Institute and in the Earth and Environmental Sciences Area. A cross-functional team of biologists, geologists, and ecologists from Berkeley Lab will provide critical new insights into ecosystem processes through the creation of controlled model ecosystems in which microorganisms and host responses can be monitored in response to additional or changing variables.
EcoPODs are enclosed environments of several meters cubed that allow direct and intensive monitoring and manipulation of replicated plant-soil-microbe-atmosphere interactions over the complete plant life cycle that are being developed at EGSB. These “pilot-scale” ecosystems are designed to bridge the gap between small, lab-scale experiments that are not large enough to mimic the environment and field-scale experiments that cannot be carefully controlled. The goal is to develop cross-disciplinary partnerships that will use the EcoPODs to develop testable ecosystem models in topics that include carbon cycling and secure biosystems design. (Photo Credit: UGT)
Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA)
The mission of ENIGMA is to support the development of laboratory and computational tools that link the molecular functions within individual microbes to the integrated activities of microbial communities as they interact with their environment.
DOE Systems Biology Knowledgebase (KBase)
KBase is an open platform for comparative functional genomics and systems biology for microbes, plants and their communities, and for sharing results and methods with other scientists. Berkeley Lab is the lead institution in a partnership comprised of Argonne, Brookhaven, and Oak Ridge National Laboratories.
Gene Ontology Knowledgebase
The Gene Ontology (GO) knowledgebase is the world’s largest source of information on gene functions. Both human-readable and machine-readable, this knowledge is foundational for computational analysis of large-scale molecular biology and genetics experiments in biomedical research. GO is a multi-PI collaboration among Berkeley Lab, the University of Southern California, Stanford University, and the California Institute of Technology, in addition to a very broad consortium.
Microbial Community Analysis and Functional Evaluation in Soils (mCAFES)
mCAFES is a collaborative, coordinated and integrated, mission-driven program to interrogate the function of soil microbiomes with critical implications for carbon cycling and sequestration, nutrient availability and plant productivity in natural and managed ecosystems. The project targets molecular mechanisms governing carbon and nutrient transformation in soil, with a focus on microbial metabolic networks.
The Monarch Initiative is an integrative data and analytic platform connecting phenotypes to genotypes across species, bridging basic and applied research with semantics-based analysis. Berkeley Lab co-leads this project with the University of Colorado and the Jackson Laboratory.
National Microbiome Data Collaborative (NMDC)
The National Microbiome Data Collaborative (NMDC) was launched in 2019 as a pilot initiative that seeks to address fundamental roadblocks in microbiome data science and gaps in transdisciplinary collaboration. NMDC is a multi-national laboratory partnership led by Berkeley Lab. Its two strategic priorities — infrastructure and engagement — and future activities support the long-term vision of empowering the research community to more effectively harness microbiome data.
The OpenMSI project allows broad use of mass spectrometry imaging (MSI) to researchers by providing a web-based gateway for management and storage of MSI data, the visualization of the hyper-dimensional contents of the data, and the statistical analysis. OpenMSI uses the advanced, high-performance compute resources of the National Energy Research Scientific Computing Center (NERSC) to make advanced mass spectrometry imaging accessible.