IMAGINE BioSecurity: Genome-Scale Engineering and Modeling for Secure Biosystems Design
Jianping Yu1, Ayako Murao2, Jacob Sebesta1, Bin Yang1, Chao Wu1, Diana Hernandez Hernandez2, Melissa Amezola2, Lin Ding2, Gabriella Li1, Kathleen L. Arnolds1, Rodrigo Santibanez3, Juan D. Tibocha-Bonilla3, Karsten Zengler3, Wei Xiong1, Jeffrey G. Linger1, Yo Suzuki2* (YSuzuki@jcvi.org), and Michael T. Guarnieri1
1National Renewable Energy Laboratory; 2J. Craig Venter Institute; and 3University of California–San Diego
The Integrative Modeling and Genome-scale Engineering for Biosystems Security (IMAGINE BioSecurity) Science Focus Area project seeks to establish an understanding of the behavior of engineered microbes in controlled versus environmental conditions to predictively devise new strategies for responding to biological escape. 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.
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 several biosecurity concerns related to environmental escape of GMOs, detection thereof, and impact upon native ecosystems. To establish a secure bioeconomy, novel biocontainment strategies—informed by a fundamental understanding of systems level governing mechanisms—are needed. To this end, the IMAGINE Team is developing an array of passive and active synthetic biocontainment strategies to effectively minimize laboratory escape frequency while concurrently maintaining maximal laboratory performance. Researchers have selected a series of non-model, industrial, and/or next-generation microbial hosts to serve as chassis for secure biosystems design, including Pseudomonas putida, Synechocystis sp. PCC6803, Clostridium ljungdahlii, Mycoplasma mycoides, and Saccharomyces cerevisiae.
To facilitate the analysis of combinatorial constructs in the target organisms, a method termed combinatorial genetics en masse (CombiGEM; Wong et al. 2016) 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. 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. Researchers have also initiated the assessment of the robustness and fitness of the engineered microbes via computational robustness and genome-scale metabolic modeling to understand the underlying mechanisms that govern the efficacy of biocontainment and metabolic fitness.
Systems level analyses of these hosts in the absence and presence of biocontainment constraints will elucidate principles that (i) govern effective biocontainment and laboratory performance and (ii) 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 forwarding a secure bioeconomy.
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.
Arnolds, K. L., et al. 2021. “Biotechnology for Secure Biocontainment Designs in an Emerging Bioeconomy.” Current Opinion in Biotechnology 71, 25–31.
This research was supported by the DOE Office of Science, Office of Biological and Environmental Research (BER), Genomic Science program, Secure Biosystems Design Science Focus Area | IMAGINE BioSecurity: Integrative Modeling and Genome-scale Engineering for Biosystems Security, under contract number DE-AC36-08GO28308.