Screening microbially produced Δ9-tetrahydrocannabinol using a yeast biosensor workflow

William M. Shaw, Yunfeng Zhang, Xinyu Lu, Ahmad S. Khalil, Graham Ladds, Xiaozhou Luo and Tom Ellis ()
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William M. Shaw: Boston University
Yunfeng Zhang: Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
Xinyu Lu: Imperial College London
Ahmad S. Khalil: Boston University
Graham Ladds: University of Cambridge
Xiaozhou Luo: Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
Tom Ellis: Imperial College London

Nature Communications, 2022, vol. 13, issue 1, 1-10

Abstract: Abstract Microbial production of cannabinoids promises to provide a consistent, cheaper, and more sustainable supply of these important therapeutic molecules. However, scaling production to compete with traditional plant-based sources is challenging. Our ability to make strain variants greatly exceeds our capacity to screen and identify high producers, creating a bottleneck in metabolic engineering efforts. Here, we present a yeast-based biosensor for detecting microbially produced Δ9-tetrahydrocannabinol (THC) to increase throughput and lower the cost of screening. We port five human cannabinoid G protein-coupled receptors (GPCRs) into yeast, showing the cannabinoid type 2 receptor, CB2R, can couple to the yeast pheromone response pathway and report on the concentration of a variety of cannabinoids over a wide dynamic and operational range. We demonstrate that our cannabinoid biosensor can detect THC from microbial cell culture and use this as a tool for measuring relative production yields from a library of Δ9-tetrahydrocannabinol acid synthase (THCAS) mutants.

Date: 2022
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DOI: 10.1038/s41467-022-33207-x

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