New high-throughput screening technologies to improve cannabinoid production in yeast. - SUMMARY
Natural products derived from plants have played crucial roles in the treatments of many diseases
throughout history. However, scarce natural sources and complex chemical synthesis have limited research
and development and increased costs on these products. An example of this is the non-psychoactive
cannabinoids found in cannabis plants. There are over 70 low-abundant cannabinoids that are known to be
safe and have beneficial effects ranging from bone growth to neuroprotection. Yet agricultural production of
these cannabinoids is not environmentally or economically sustainable. Thus, their therapeutic potentials
are unfortunately limited by their availabilities for research and commercial production. Alternative
biosynthetic production routes in S. cerevisiae are being investigated to increase accessibility to these high
potential therapeutics. Further, massive libraries of yeast mutants are being generated for the purpose of
identifying cellular pathways that enhance cannabinoid biosynthesis. However, a major bottleneck in this
biosynthetic approach is the lack of high-throughput screening technology that can screen these massive
libraries efficiently. Current analytically methods are low-throughput, expensive, cumbersome, and complex.
Another problem is that these methods do not enable individual mutant cells to be screened for key
metabolite production, which is widely recognized as a limiting problem in metabolic engineering. Single-cell
isolation techniques have been explored as high-throughput means to quickly identify and separate
metabolically and physiologically favorably mutants for further strain evolution. Therefore, fluorescent
sensors that can inform on the intracellular concentrations of valuable metabolites in living cells and enable
high-throughput cell sorting would be highly useful tools for any industrial production of natural products. In
this application, we will use our fluorescent aptamer technology to develop genetically encoded sensors that
can active fluorescence upon binding to target cannabinoid metabolites. These sensors can then be
expressed in yeast to monitor cannabinoid production levels in real-time and used in flow cytometry-based
screening applications. Taken together, the experiments in this application provide the foundation for a
novel approach that can be widely used to improve industrial production of natural products by allowing
culture conditions or genetically modified organisms with improved production characteristics to be rapidly
identified.
