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Related Experiment Video

Updated: Aug 28, 2025

Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae
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Screening microbially produced Δ9-tetrahydrocannabinol using a yeast biosensor workflow.

William M Shaw1,2,3,4, Yunfeng Zhang5, Xinyu Lu3,4

  • 1Biological Design Center, Boston University, Boston, MA, 02215, USA.

Nature Communications
|September 20, 2022
PubMed
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Scientists developed a novel yeast biosensor to detect microbially produced tetrahydrocannabinol (THC). This tool accelerates the screening of high-yield strains, overcoming a key metabolic engineering bottleneck for sustainable cannabinoid production.

Area of Science:

  • Synthetic Biology
  • Metabolic Engineering
  • Biotechnology

Background:

  • Microbial production offers a sustainable, cost-effective alternative to plant-derived cannabinoids.
  • Scaling up microbial cannabinoid production is hindered by inefficient screening methods for high-producing strains.
  • Metabolic engineering efforts are bottlenecked by the slow identification of optimal microbial variants.

Purpose of the Study:

  • To develop a high-throughput yeast-based biosensor for detecting microbially produced Δ9-tetrahydrocannabinol (THC).
  • To enable faster and more cost-effective screening of microbial strains for cannabinoid production.
  • To facilitate metabolic engineering advancements in the sustainable production of therapeutic cannabinoids.

Main Methods:

  • Engineered yeast strains expressing human cannabinoid G protein-coupled receptors (GPCRs).

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  • Utilized the yeast pheromone response pathway for signal transduction from CB2R.
  • Developed a biosensor assay to quantify cannabinoids in microbial cell cultures.
  • Applied the biosensor to screen a library of Δ9-tetrahydrocannabinol acid synthase (THCAS) mutants.
  • Main Results:

    • Successfully ported five human cannabinoid GPCRs into yeast.
    • Demonstrated that CB2R couples to the yeast pheromone response pathway.
    • The biosensor accurately reports cannabinoid concentrations over a wide dynamic range.
    • Validated the biosensor's ability to detect THC in microbial cultures and measure relative yields of THCAS mutants.

    Conclusions:

    • A novel yeast biosensor for detecting microbially produced THC has been established.
    • This biosensor significantly enhances screening throughput for metabolic engineering.
    • The developed tool supports the advancement of sustainable and scalable microbial cannabinoid production.