Safe and effective synthetic biology

Synthetic biology and occupational risk

Synthetic biology is an emerging interdisciplinary field of biotechnology that involves applying the principles of engineering and chemical design to biological systems. Biosafety professionals have done an excellent job in addressing research laboratory safety as synthetic biology and gene editing have emerged from the larger field of biotechnology. Despite these efforts, risks posed by synthetic biology are of increasing concern as research procedures scale up to industrial processes in the larger bioeconomy. A greater number and variety of workers will be exposed to commercial synthetic biology risks in the future, including risks to a variety of workers from the use of lentiviral vectors as gene transfer devices. There is a need to review and enhance current protection measures in the field of synthetic biology, whether in experimental laboratories where new advances are being researched, in health care settings where treatments using viral vectors as gene delivery systems are increasingly being used, or in the industrial bioeconomy. Enhanced worker protection measures should include increased injury and illness surveillance of the synthetic biology workforce; proactive risk assessment and management of synthetic biology products; research on the relative effectiveness of extrinsic and intrinsic biocontainment methods; specific safety guidance for synthetic biology industrial processes; determination of appropriate medical mitigation measures for lentiviral vector exposure incidents; and greater awareness and involvement in synthetic biology safety by the general occupational safety and health community as well as by government occupational safety and health research and regulatory agencies.

Identification of line-specific strategies for improving carotenoid production in synthetic maize through data-driven mathematical modeling

Plant synthetic biology is still in its infancy. However, synthetic biology approaches have been used to manipulate and improve the nutritional and health value of staple food crops such as rice, potato and maize. With current technologies, production yields of the synthetic nutrients are a result of trial and error, and systematic rational strategies to optimize those yields are still lacking. Here, we present a workflow that combines gene expression and quantitative metabolomics with mathematical modeling to identify strategies for increasing production yields of nutritionally important carotenoids in the seed endosperm synthesized through alternative biosynthetic pathways in synthetic lines of white maize, which is normally devoid of carotenoids. Quantitative metabolomics and gene expression data are used to create and fit parameters of mathematical models that are specific to four independent maize lines. Sensitivity analysis and simulation of each model is used to predict which gene activities should be further engineered in order to increase production yields for carotenoid accumulation in each line. Some of these predictions (e.g. increasing Zmlycb/Gllycb will increase accumulated β-carotenes) are valid across the four maize lines and consistent with experimental observations in other systems. Other predictions are line specific. The workflow is adaptable to any other biological system for which appropriate quantitative information is available. Furthermore, we validate some of the predictions using experimental data from additional synthetic maize lines for which no models were developed.