The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
A synthetic biochemistry platform for cell free production of monoterpenes from glucose
Open accessAbstract
Cell-free systems designed to perform complex chemical conversions of biomass to biofuels or commodity chemicals are emerging as promising alternatives to the metabolic engineering of living cells. Here we design a system comprises 27 enzymes for the conversion of glucose into monoterpenes that generates both NAD(P)H and ATP in a modified glucose breakdown module and utilizes both cofactors for building terpenes. Different monoterpenes are produced in our system by changing the terpene synthase enzyme. The system is stable for the production of limonene, pinene and sabinene, and can operate continuously for at least 5 days from a single addition of glucose. We obtain conversion yields >95% and titres >15 g l−1. The titres are an order of magnitude over cellular toxicity limits and thus difficult to achieve using cell-based systems. Overall, these results highlight the potential of synthetic biochemistry approaches for producing bio-based chemicals.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
COPASI—a COmplex PAthway SImulator
Hoops, S., Sahle, S., Gauges, R., Lee, C., Pahle, J., Simus, N., Singhal, M., Xu, L., Mendes, P., & Kummer, U. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl485 · Cited by 2,618
Metabolic costs of terpenoid accumulation in higher plants
Gershenzon, J. (1994) · Journal of Chemical Ecology · doi:10.1007/bf02059810 · Cited by 522
Natural products as biofuels and bio-based chemicals: fatty acids and isoprenoids
Beller, H. R., Lee, T. S., & Katz, L. (2015) · Natural Product Reports · doi:10.1039/c5np00068h · Cited by 153
Cited by
Cell-free chemoenzymatic starch synthesis from carbon dioxide
Cai, T., Sun, H., Qiao, J., Zhu, L., Zhang, F., Zhang, J., Tang, Z., Wei, X., Yang, J., Yuan, Q., et al. (2021) · Science · doi:10.1126/science.abh4049 · Cited by 632
Multienzyme Cascade Reactions—Status and Recent Advances
Sperl, J. M., & Sieber, V. (2018) · ACS Catalysis · doi:10.1021/acscatal.7b03440 · Cited by 363
Metadata
- Authors
- Korman, T. P., Opgenorth, P. H., & Bowie, J. U.
- Venue
- Nature Communications
- Published
- 2017-05-24
- Volume
- 8
- Issue
- 1
- Pages
- 15526-15526
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W2618238633
- Cited by
- 230
- References
- 3
- FWCI
- 8.93
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
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.
