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Cited by 487

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Improving fatty acids production by engineering dynamic pathway regulation and metabolic control

Open access
Xu, Peng, Li, Lingyun, Zhang, Fuming, Stephanopoulos, Gregory, Koffas, Mattheos·2014·Proceedings of the National Academy of Sciences

Abstract

Significance: One important synthetic chemistry reaction endowed by nature is the decarboxylative carbon condensation reaction using malonyl-CoA as carbon donor. Previous metabolic engineering efforts centered on the malonyl-CoA–dependent pathway have resulted in the production of many value-added compounds. Here we mimicked the native biological systems and used a dynamic regulatory network to optimize production titers and yield. The naturally existing transcriptional regulator FapR was rewired to dynamically control gene expressions involved in the supply and consumption of malonyl-CoA. Applying this metabolic control allowed the engineered cell to dynamically regulate pathway expression and compensated the metabolic activity of critical enzymes. The synthetic malonyl-CoA switch engineered in this study opens up new venues for dynamic pathway optimization and efficient production of malonyl-CoA–derived compounds.

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Metadata

Authors
Xu, P., Li, L., Zhang, F., Stephanopoulos, G., & Koffas, M.
Venue
Proceedings of the National Academy of Sciences
Published
2014-07-21
Volume
111
Issue
31
Pages
11299-11304
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2161782059
Cited by
487
References
3
FWCI
18.62
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Improving fatty acids production by engineering dynamic pathway regulation and metabolic control. https://app.cochat.ai/papers/10.1073/pnas.1406401111
The paper
Xu, P., Li, L., Zhang, F., Stephanopoulos, G., & Koffas, M. (2014). Improving fatty acids production by engineering dynamic pathway regulation and metabolic control. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1406401111

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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.