Anita L. Ziegler , Marc-Daniel Stumm , Tim Prömper , Thomas Steimann , Jørgen Magnus , Alexander Mitsos
{"title":"微生物与生物反应器同步设计","authors":"Anita L. Ziegler , Marc-Daniel Stumm , Tim Prömper , Thomas Steimann , Jørgen Magnus , Alexander Mitsos","doi":"10.1016/j.compchemeng.2025.109388","DOIUrl":null,"url":null,"abstract":"<div><div>When developing a biotechnological process, the microorganism is first designed, e.g., using metabolic engineering. Then, the optimum fermentation parameters are determined on a laboratory scale, and lastly, they are transferred to the bioreactor scale. However, this step-by-step approach is costly and time-consuming and may result in suboptimal configurations. Herein, we present the bilevel optimization formulation <em>SimulKnockReactor</em>, which connects bioreactor design with microbial strain design, an extension of our previous formulation, SimulKnock (Ziegler et al., 2024). At the upper (bioreactor) level, we minimize investment and operation costs for agitation, aeration, and pH control by determining the size and operating conditions of a continuous stirred-tank reactor—without selecting specific devices like the stirrer type. The lower (cellular) level is based on flux balance analysis and implements optimal reaction knockouts predicted by the upper level. Our results with a core and a genome-scale metabolic model of <em>Escherichia coli</em> show that the substrate is the largest cost factor. Our simultaneous approach outperforms a sequential approach using OptKnock. Namely, the knockouts proposed by OptKnock cannot guarantee the required production capacity in all cases considered. SimulKnockReactor, on the other hand, provides solutions in all cases considered, highlighting the advantage of combining cellular and bioreactor levels. This work is a further step towards a fully integrated bioprocess design.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"204 ","pages":"Article 109388"},"PeriodicalIF":3.9000,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Simultaneous design of microbe and bioreactor\",\"authors\":\"Anita L. Ziegler , Marc-Daniel Stumm , Tim Prömper , Thomas Steimann , Jørgen Magnus , Alexander Mitsos\",\"doi\":\"10.1016/j.compchemeng.2025.109388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>When developing a biotechnological process, the microorganism is first designed, e.g., using metabolic engineering. Then, the optimum fermentation parameters are determined on a laboratory scale, and lastly, they are transferred to the bioreactor scale. However, this step-by-step approach is costly and time-consuming and may result in suboptimal configurations. Herein, we present the bilevel optimization formulation <em>SimulKnockReactor</em>, which connects bioreactor design with microbial strain design, an extension of our previous formulation, SimulKnock (Ziegler et al., 2024). At the upper (bioreactor) level, we minimize investment and operation costs for agitation, aeration, and pH control by determining the size and operating conditions of a continuous stirred-tank reactor—without selecting specific devices like the stirrer type. The lower (cellular) level is based on flux balance analysis and implements optimal reaction knockouts predicted by the upper level. Our results with a core and a genome-scale metabolic model of <em>Escherichia coli</em> show that the substrate is the largest cost factor. Our simultaneous approach outperforms a sequential approach using OptKnock. Namely, the knockouts proposed by OptKnock cannot guarantee the required production capacity in all cases considered. SimulKnockReactor, on the other hand, provides solutions in all cases considered, highlighting the advantage of combining cellular and bioreactor levels. This work is a further step towards a fully integrated bioprocess design.</div></div>\",\"PeriodicalId\":286,\"journal\":{\"name\":\"Computers & Chemical Engineering\",\"volume\":\"204 \",\"pages\":\"Article 109388\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Chemical Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0098135425003916\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Chemical Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0098135425003916","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
When developing a biotechnological process, the microorganism is first designed, e.g., using metabolic engineering. Then, the optimum fermentation parameters are determined on a laboratory scale, and lastly, they are transferred to the bioreactor scale. However, this step-by-step approach is costly and time-consuming and may result in suboptimal configurations. Herein, we present the bilevel optimization formulation SimulKnockReactor, which connects bioreactor design with microbial strain design, an extension of our previous formulation, SimulKnock (Ziegler et al., 2024). At the upper (bioreactor) level, we minimize investment and operation costs for agitation, aeration, and pH control by determining the size and operating conditions of a continuous stirred-tank reactor—without selecting specific devices like the stirrer type. The lower (cellular) level is based on flux balance analysis and implements optimal reaction knockouts predicted by the upper level. Our results with a core and a genome-scale metabolic model of Escherichia coli show that the substrate is the largest cost factor. Our simultaneous approach outperforms a sequential approach using OptKnock. Namely, the knockouts proposed by OptKnock cannot guarantee the required production capacity in all cases considered. SimulKnockReactor, on the other hand, provides solutions in all cases considered, highlighting the advantage of combining cellular and bioreactor levels. This work is a further step towards a fully integrated bioprocess design.
期刊介绍:
Computers & Chemical Engineering is primarily a journal of record for new developments in the application of computing and systems technology to chemical engineering problems.