The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
A microbial biomanufacturing platform for natural and semisynthetic opioids
Open accessAbstract
Opiates and related molecules are medically essential, but their production via field cultivation of opium poppy Papaver somniferum leads to supply inefficiencies and insecurity. As an alternative production strategy, we developed baker's yeast Saccharomyces cerevisiae as a microbial host for the transformation of opiates. Yeast strains engineered to express heterologous genes from P. somniferum and bacterium Pseudomonas putida M10 convert thebaine to codeine, morphine, hydromorphone, hydrocodone, and oxycodone. A new biosynthetic branch to neopine and neomorphine was discovered, which diverted pathway flux from morphine and other target products. Strain titer and specificity was optimized by titrating gene copy number, enhancing cosubstrate supply, applying a spatial engineering strategy, and performing high-density fermentation, resulting in total opioid titers up to 131 mg/L. This work is an important step toward total biosynthesis of valuable benzylisoquinoline alkaloid drug molecules and demonstrates the potential for developing a sustainable and secure yeast biomanufacturing platform for opioids.
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Production of the antimalarial drug precursor artemisinic acid in engineered yeast
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Delebecque, C. J., Lindner, A. B., Silver, P. A., & Aldaye, F. A. (2011) · Science · doi:10.1126/science.1206938 · Cited by 633
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International Narcotics Control Board
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Synthetic biology strategies for microbial biosynthesis of plant natural products
Cravens, A., Payne, J., & Smolke, C. D. (2019) · Nature Communications · doi:10.1038/s41467-019-09848-w · Cited by 438
Self-citationExtending the application of biocatalysis to meet the challenges of drug development
Devine, P. N., Howard, R. M., Kumar, R., Thompson, M. P., Truppo, M. D., & Turner, N. J. (2018) · Nature Reviews Chemistry · doi:10.1038/s41570-018-0055-1 · Cited by 426
Courbet, A., Endy, D., Renard, E., Molina, F., & Bonnet, J. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aaa3601 · Cited by 266
Biosensor and machine learning-aided engineering of an amaryllidaceae enzyme
d’Oelsnitz, S., Diaz, D. J., Kim, W., Acosta, D. J., Dangerfield, T. L., Schechter, M. W., Minus, M. B., Howard, J. R., Do, H., Loy, J. M., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-46356-y · Cited by 58
Metadata
- Authors
- Thodey, K., Galanie, S., & Smolke, C. D.
- Venue
- Nature Chemical Biology
- Published
- 2014-08-24
- Volume
- 10
- Issue
- 10
- Pages
- 837-844
- ISSN
- 1552-4450 (ISSN-L)
- 1552-4469
- OpenAlex
- W1977550796
- Cited by
- 273
- References
- 29
- FWCI
- 12.41
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
