Science Focus Area: National Renewable Energy Laboratory
- Principal Investigator: Michael Guarnieri1
- Laboratory Research Manager: Adam Bratis1
- Co-Investigators: Jeffrey Linger1, Jianping Yu1, Wei Xiong1, Karsten Zengler2, Yo Suzuki3, Katie Arnolds1
- Participating Institutions: 1National Renewable Energy Laboratory, 2University of California-San Diego, 3J. Craig Venter Institute
Genetically modified organisms (GMOs) have emerged as an integral component of a sustainable bioeconomy, with an array of applications in agriculture and bioenergy. However, the rapid development of GMOs and associated synthetic biology approaches raises a number of biosecurity concerns related to GMO environmental escape, their detection, and impact upon native ecosystems. Establishing a secure bioeconomy requires novel biocontainment strategies informed by a fundamental understanding of systems-level governing mechanisms. The Integrative Modeling and Genome-Scale Engineering for Biosystems Security (IMAGINE BioSecurity) team seeks to achieve predictive control of engineered systems to enable secure biosystems design. The team integrates core capabilities in synthetic and applied systems biology to develop a high-throughput platform for the design, generation, and analysis of biocontainment strategies in industrially relevant and next-generation, genetically modified bacteria and yeasts. IMAGINE leverages the National Renewable Energy Laboratory’s metabolic engineering and multiscale omics capabilities in industrial microbial hosts and its unique pilot-scale deployment capacity to expand the U.S. Department of Energy’s knowledgebase into deployment-relevant systems. These capabilities are complemented by expertise in synthetic genomics (J. Craig Venter Institute) and genome-scale and community metabolic modeling (University of California, San Diego) to enable predictive design strategies for next-generation microbial production platforms. The IMAGINE BioSecurity Science Focus Area is establishing an extensive library of biocontainment modules and strains, a testing platform, and a systems knowledgebase. These outputs will lay the foundation for predictive computational design of biocontainment strategies with enhanced stability and resilience in diverse microbial hosts, while maintaining maximal fitness and bioproductivity of the engineered microbial strains. Combined, these efforts will reduce the risk associated with deployment of engineered biosystems and ultimately enable a secure bioeconomy.