{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,14]],"date-time":"2025-12-14T05:26:01Z","timestamp":1765689961918,"version":"3.48.0"},"reference-count":47,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:00:00Z","timestamp":1765497600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62376288"],"award-info":[{"award-number":["62376288"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["2022HWYQ10"],"award-info":[{"award-number":["2022HWYQ10"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004761","name":"Provincial Natural Science Foundation of Hunan","doi-asserted-by":"crossref","award":["2024JJ5441"],"award-info":[{"award-number":["2024JJ5441"]}],"id":[{"id":"10.13039\/501100004761","id-type":"DOI","asserted-by":"crossref"}]},{"name":"High Performance Computing Center of Central South University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Bilevel modelling has been widely applied for the identification of genetic perturbations in metabolic engineering. However, most current approaches are based on a biased assumption that mutant strains always grow optimally. In addition, they are developed based on production rates, which may not meet yield requirements imposed on a production strain. This paper propose to design strains via multiobjective bilevel models that account for the tradeoff between cell growth and metabolic adjustments from the wild type strain. The proposed modelling frameworks can be used to identify design strategies that maximise rates and\/or yields of target products, termed rate-based and yield-based modelling, respectively. We demonstrate, through in silico production of important chemicals in Escherichia coli, that our modelling approaches can generate growth-coupled designs in terms of rate and\/or yield, and yield-based modelling identifies design strategies consistent with existing experimental studies as well as suggesting novel designs, thereby holding great promise for selecting targets for high-performance strain design. An important finding from this work that a growth rate coupled design is not necessarily growth yield coupled and vice versa suggests that growth-coupled designs should be analysed in both rate and yield spaces to determine their theoretical feasibility.<\/jats:p>","DOI":"10.3390\/a18120786","type":"journal-article","created":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T11:13:33Z","timestamp":1765538013000},"page":"786","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Bilevel Modelling of Metabolic Networks for Computational Strain Design"],"prefix":"10.3390","volume":"18","author":[{"given":"Beichen","family":"Wang","sequence":"first","affiliation":[{"name":"School of Automation, Central South University, Changsha 410083, China"}]},{"given":"Shouyong","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha 410083, China"}]},{"given":"Shibo","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha 410083, China"}]},{"given":"Jichun","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.copbio.2017.06.007","article-title":"Recent advances in systems metabolic engineering tools and strategies","volume":"47","author":"Chae","year":"2017","journal-title":"Curr. 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