Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

2024 Abstracts

IMAGINE BioSecurity: Genome-Scale Engineering and High-Throughput Screening to Establish Secure Biosystems Design


Michael T. Guarnieri1* ([email protected]), Natalie Lamb1, Ayako Murao2, Jacob Sebesta1, Bin Yang1, Kathleen L. Arnolds1, Wei Xiong1, Jianping Yu1, Clifford Louime3, Karsten Zengler4, Jeffrey G. Linger1, Yo Suzuki2


1National Renewable Energy Laboratory; 2J. Craig Venter Institute; 3University of Puerto Rico–Rio Piedras; 4University of California–San Diego



The Integrative Modeling and Genome-scale Engineering for Biosystems Security (IMAGINE BioSecurity) Science Focus Area (SFA) project seeks to establish a predictive framework for secure biosystems design. To this end, the IMAGINE 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 emerging, next-generation microbes.


Microbial biocatalysts and bio-derived products have emerged as an integral component of a sustainable bioeconomy, with an array of applications in agriculture and bioenergy. However, the rapid development of genetically engineered microbes and associated synthetic biology approaches raises several biosecurity concerns related to microbial environmental escape, detection, and impact upon native ecosystems (Arnolds et al 2021; Arnolds et al 2024). To establish a secure bioeconomy, novel biocontainment strategies that do not compromise laboratory performance are needed. To this end, the Integrative Modeling and Genome-scale Engineering for Biosystems Security SFA Team (IMAGINE BioSecurity) was established to accomplish the overarching goal of achieving predictive control of engineered systems to enable secure biosystems design. The IMAGINE Team is developing an array of passive and active synthetic biocontainment strategies in a series of non-model, industrial, and/or next-generation microbial hosts to serve as chassis for secure biosystems design.

To facilitate the analysis of combinatorial constructs in the target organisms, a method termed combinatorial genetics en masse (CombiGEM; Wong et al 2016; Hernandez Hernandez et al 2023) for generating combinatorial genotypes en masse and tracking them in mixed populations using DNA barcodes and next-generation sequencing was implemented. Combinatorial biocontainment strategies are being developed and evaluated for the capacity to reduce GMO escape frequency in laboratory and environmental simulation settings. Additional efforts to target synthetic carbon, nitrogen, and phosphorus storage auxotrophies are under development (Sebesta et al 2022; Sebesta et al 2024).  In parallel, researchers have initiated assessment of the metabolic burden associated with implementation of these strategies, with the goal of maximizing biocontainment while maintaining optimal microbial fitness in deployment settings. Engineered strains are experimentally analyzed via growth, escape frequency, and bioproductivity using high-throughput screening in laboratory and environmental mesocosm settings. Strains are concurrently subjected to fitness and escape frequency screening assays to assess the effect of genetic safeguards on strain fitness and biocontainment efficacy.

Systems level analyses of these microbial biocatalysts in the absence and presence of biocontainment constraints will elucidate principles that: (1) govern effective biocontainment and laboratory performance; and (2) drive biological systems in their natural environments. These learnings will establish an extensive library of biocontainment modules and strains, testing platform, and systems knowledgebase, and lay the foundation for predictive design of biocontainment strategies with enhanced stability and resilience in diverse microbial hosts. Combined, these efforts will reduce the risk associated with deployment of GMOs, ultimately accelerating a secure bioeconomy.


Arnolds, K. L., et al. 2021. “Biotechnology for Secure Biocontainment Designs in an Emerging Bioeconomy,” Current Opinion in Biotechnology 71, 25–31.

Arnolds, K. L., et al. 2024. “Risk Assessment of Industrial Microbes Using a Terrestrial Mesocosm Platform,” Microbial Ecology 87(1), 12.

Hernandez Hernandez, D., et al. 2023. “Improved Combinatorial Assembly and Barcode Sequencing for Gene-Sized DNA Constructs,” ACS Synthetic Biology 12(9), 2778–82.

Sebesta, J., et al. 2022. “Biocontainment of Genetically Engineered Algae,” Frontiers in Plant Science 13, 839446

Sebesta, J., et al. 2024. “Polyphosphate Kinase Deletion Increases Laboratory Productivity in Cyanobacteria,” Frontiers in Plant Science 15, 1342496.

Wong, A. S. L., et al. 2016. “Multiplexed Barcoded CRISPR-Cas9 Screening Enabled by CombiGEM,” Proceedings of the National Academy of Sciences, U.S. 113, 2544–49.

Funding Information

This research was supported by the DOE Office of Science, BER Program, GSP, Secure Biosystems Design Science Focus Area | IMAGINE BioSecurity: Integrative Modeling and Genome-scale Engineering for Biosystems Security, under contract number DE-AC36-08GO28308.