Systems engineering of Escherichia coli for n-butane production
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
---|---|
Pages (from-to) | 98-107 |
Journal / Publication | Metabolic Engineering |
Volume | 74 |
Online published | 13 Oct 2022 |
Publication status | Published - Nov 2022 |
Externally published | Yes |
Link(s)
Abstract
Rising concerns about climate change and sustainable energy have attracted efforts towards developing environmentally friendly alternatives to fossil fuels. Biosynthesis of n-butane, a highly desirable petro-chemical, fuel additive and diluent in the oil industry, remains a challenge. In this work, we first engineered enzymes Tes, Car and AD in the termination module to improve the selectivity of n-butane biosynthesis, and ancestral reconstruction and a synthetic RBS significantly improved the AD abundance. Next, we did ribosome binding site (RBS) calculation to identify potential metabolic bottlenecks, and then mitigated the bottleneck with RBS engineering and precursor propionyl-CoA addition. Furthermore, we employed a model-assisted strain design and a nonrepetitive extra-long sgRNA arrays (ELSAs) and quorum sensing assisted CRISPRi to facilitate a dynamic two-stage fermentation. Through systems engineering, n-butane production was increased by 168-fold from 0.04 to 6.74 mg/L. Finally, the maximum n-butane production from acetate was predicted using parsimonious flux balance analysis (pFBA), and we achieved n-butane production from acetate produced by electrocatalytic CO reduction. Our findings pave the way for selectively producing n-butane from renewable carbon source.
Research Area(s)
- Electrocatalytic reduction, Enzyme engineering, Metabolic engineering, Model-assisted design, n-Butane
Citation Format(s)
Systems engineering of Escherichia coli for n-butane production. / Liu, Yilan; Khusnutdinova, Anna; Chen, Jinjin et al.
In: Metabolic Engineering, Vol. 74, 11.2022, p. 98-107.
In: Metabolic Engineering, Vol. 74, 11.2022, p. 98-107.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review