Laboratory Research & Development
At Pacific Northwest National Laboratory (PNNL), we conduct both public and private research. Sources of public funds for biology research include but are not limited to:
- U.S. Department of Energy (DOE)
- National Institutes of Health (NIH)
- Department of Homeland Security (DHS)
- Environmental Protection Agency (EPA).
PNNL uses its private funds to support Initiatives and Grand Challenges. Initiatives are designed to explore innovative ideas and to strengthen or create technical capabilities that support DOE missions. Grand Challenges are complex, large-scale scientific and engineering problems with broad scientific and environmental or economic impact whose solution can be advanced by applying high-performance scientific techniques and resources. Grand Challenge collaborative teams are made up of a large number of individuals from multiple institutions, including universities, other laboratories, and industry, that use multiple facilities within the Environmental Molecular Sciences Laboratory (EMSL).
Biomolecular Systems Initiative
The Biomolecular Systems Initiative (BSI) research team is providing PNNL with the capabilities and infrastructure necessary to use a quantitative and predictive approach to answer biological questions. Our efforts address both the experimental and computational aspects of the biological sciences with a focus on managing, integrating, and analyzing high-throughput genomics, proteomics, and metabonomics data. Research conducted as part of the BSI seeks to answer fundamental biology questions as well as has practical applications such as identification of biomarkers for early detection and treatment of diseases, environmental remediation, and biothreat detection. As part of the BSI, PNNL staff are studying interrogative cell signaling, microbial biofilm activity and behavior, spatial and temporal proteomics, and bioanalytics.
Environmental Biomarkers Initiative
Scientists contributing to the Environmental Biomarkers Initiative (EBI) will decode the biomolecular signatures associated with toxic insults to specific biological systems and use those signatures to predict detrimental changes in complex systems. Our goal is to transform the way we assess and manage environmental systems, moving from what has been predominantly an observational approach to a more accurate, predictive approach. We will accomplish this goal through the discovery and implementation of environmental biomarkers. Significant challenges exist to make this shift, one of which is the development of tools and methods to discover a suite of biomolecules constituting a biosignature. Another challenge is the integration and interpretation of multiple, comprehensive genomic, proteomic and metabonomic data sets resulting from these tools. Solving such challenges will lead to the discovery and validation of biomarkers, the development of field-deployable sensors to assess the status of an organism or ecosystem, and the development of predictive models using the resulting data. Success will come as our ability to recognize early warning signs of ecosystem and human health-related stress and damage improves. Current focus areas include: Predicting Ecosystem Change and Damage, Nanomaterials Impact on Respiratory Health, and Response to Zoonotic Agents.
Data-Intensive Computing Initiative
Systems Biology at PNNL is benefiting from the Data-Intensive Computing Initiative. PNNL is leveraging traditional research and development in computing sciences and applying new computational technologies and techniques to manage, model, and analyze petascale data and information. Our mission is to provide the intellectual leadership in the architecture and design of next-generation computing hardware and software, develop the computational facilities necessary to advance the research, and help client and partner institutions employ DI Computing techniques. Our goal is to build multidisciplinary, collaborative programs that integrate domain science problems with computational tools, and as PNNL establishes itself as a national leader in DI Computing, to stimulate a paradigm shift in computing toward data-centered modeling and facilitate the next frontier—predictive science
Grand Challenges
PNNL supports Computational Grand Challenge projects as well as EMSL Grand Challenge projects. Computational researchers apply our tools to a variety of biological problems, including enzymatic reactions, DNA damage, and proteomic analysis. Members of the EMSL Biogeochemistry Grand Challenge team study how organisms exchange energy and electron flux with mineral matter in soils, sediments, and subsurface materials. The goal of the EMSL Membrane Biology Grand Challenge is to use a systems approach to understand the network of genes and proteins that govern the structure and function of membranes and their components responsible for photosynthesis and nitrogen fixation in cyanobacteria.
