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Screening microbially produced Δ(9)-tetrahydrocannabinol using a yeast biosensor workflow
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 ca...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9489785/ https://www.ncbi.nlm.nih.gov/pubmed/36127350 http://dx.doi.org/10.1038/s41467-022-33207-x |
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author | Shaw, William M. Zhang, Yunfeng Lu, Xinyu Khalil, Ahmad S. Ladds, Graham Luo, Xiaozhou Ellis, Tom |
author_facet | Shaw, William M. Zhang, Yunfeng Lu, Xinyu Khalil, Ahmad S. Ladds, Graham Luo, Xiaozhou Ellis, Tom |
author_sort | Shaw, William M. |
collection | PubMed |
description | 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 Δ(9)-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 Δ(9)-tetrahydrocannabinol acid synthase (THCAS) mutants. |
format | Online Article Text |
id | pubmed-9489785 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94897852022-09-22 Screening microbially produced Δ(9)-tetrahydrocannabinol using a yeast biosensor workflow Shaw, William M. Zhang, Yunfeng Lu, Xinyu Khalil, Ahmad S. Ladds, Graham Luo, Xiaozhou Ellis, Tom Nat Commun Article 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 Δ(9)-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 Δ(9)-tetrahydrocannabinol acid synthase (THCAS) mutants. Nature Publishing Group UK 2022-09-20 /pmc/articles/PMC9489785/ /pubmed/36127350 http://dx.doi.org/10.1038/s41467-022-33207-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Shaw, William M. Zhang, Yunfeng Lu, Xinyu Khalil, Ahmad S. Ladds, Graham Luo, Xiaozhou Ellis, Tom Screening microbially produced Δ(9)-tetrahydrocannabinol using a yeast biosensor workflow |
title | Screening microbially produced Δ(9)-tetrahydrocannabinol using a yeast biosensor workflow |
title_full | Screening microbially produced Δ(9)-tetrahydrocannabinol using a yeast biosensor workflow |
title_fullStr | Screening microbially produced Δ(9)-tetrahydrocannabinol using a yeast biosensor workflow |
title_full_unstemmed | Screening microbially produced Δ(9)-tetrahydrocannabinol using a yeast biosensor workflow |
title_short | Screening microbially produced Δ(9)-tetrahydrocannabinol using a yeast biosensor workflow |
title_sort | screening microbially produced δ(9)-tetrahydrocannabinol using a yeast biosensor workflow |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9489785/ https://www.ncbi.nlm.nih.gov/pubmed/36127350 http://dx.doi.org/10.1038/s41467-022-33207-x |
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