Coupling feedback genetic circuits with growth phenotype for dynamic population control and intelligent bioproduction
| dc.contributor.author | Lv, Yongkun | |
| dc.contributor.author | Qian, Shuai | |
| dc.contributor.author | Du, Guocheng | |
| dc.contributor.author | Chen, Jian | |
| dc.contributor.author | Zhou, Jingwen | |
| dc.contributor.author | Xu, Peng | |
| dc.date.accessioned | 2019-04-22T17:38:47Z | |
| dc.date.available | 2019-04-22T17:38:47Z | |
| dc.date.issued | 2019-03-30 | |
| dc.description.abstract | Metabolic engineering entails target modification of cell metabolism to maximize cell's production potential. Due to the complexity of cell metabolism, feedback genetic circuits have emerged as basic tools to combat metabolic heterogeneity, enhance microbial cooperation as well as boost cell's productivity. This is generally achieved by applying social reward-punishment rules to eliminate cheaters and reward winners in a mixed cell population. With metabolite-responsive transcriptional factors to rewire gene expression, metabolic engineers are well-positioned to integrate feedback genetic circuits with growth fitness and achieve dynamic population control. Towards this goal, we argue that feedback genetic circuits and microbial interactions will be a golden mine for future metabolic engineering. We will summarize the design principles of engineering burden-driven feedback control to combat metabolic stress, implementing population quality control to eliminate cheater cell, applying product addiction to reward productive cell, as well as layering dual dynamic regulation to decouple cell growth from product formation. Collectively, these strategies will be useful to improve community-level cellular performance. Encoding such decision-marking functions and reprogramming cellular logics at population level will enable metabolic engineers to deliver robust cell factories and pave the way for intelligent bioproduction. We envision that various cellular regulation mechanisms and genetic/metabolic circuits could be exploited to achieve self-adaptive or autonomous metabolic function for diverse biotechnological and medical applications. Applying these design rules may offer us a genetic solution beyond bioprocess engineering strategies to further improve the cost-competitiveness of industrial fermentation. | en_US |
| dc.description.sponsorship | This work was supported by the Cellular & Biochem Engineering Program of the National Science Foundation under grant no.1805139. The authors would also like to acknowledge the Department of Chemical, Biochemical and Environmental Engineering at University of Maryland Baltimore County for funding support. YL would like to thank the China Scholarship Council for funding support. | en_US |
| dc.description.uri | https://www.sciencedirect.com/science/article/pii/S109671761930028X | en_US |
| dc.format.extent | 8 pages | en_US |
| dc.genre | journal articles postprints | en_US |
| dc.identifier | doi:10.13016/m2uuev-5gur | |
| dc.identifier.citation | Yongkun Lv , Shuai Qian , Guocheng Du , Jian Chen , Jingwen Zhou , Peng Xu, Coupling feedback genetic circuits with growth phenotype for dynamic population control and intelligent bioproduction, Metabolic Engineering , Volume 54, July 2019, Pages 109-116, https://doi.org/10.1016/j.ymben.2019.03.009 | en_US |
| dc.identifier.uri | https://doi.org/10.1016/j.ymben.2019.03.009 | |
| dc.identifier.uri | http://hdl.handle.net/11603/13482 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Elsevier B.V. | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Chemical, Biochemical & Environmental Engineering Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.rights | Access to this item will begin on July 30, 2020. | * |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
| dc.subject | genetic circuits | en_US |
| dc.subject | metabolic engineering | en_US |
| dc.subject | dynamic population control | en_US |
| dc.subject | growth fitness | en_US |
| dc.subject | synthetic biology | en_US |
| dc.title | Coupling feedback genetic circuits with growth phenotype for dynamic population control and intelligent bioproduction | en_US |
| dc.type | Text | en_US |