Vittoria Martinelli, Davide Fiore, Davide Salzano, Mario di Bernardo
{"title":"多细胞PID控制对生物过程的鲁棒调节。","authors":"Vittoria Martinelli, Davide Fiore, Davide Salzano, Mario di Bernardo","doi":"10.1098/rsif.2024.0583","DOIUrl":null,"url":null,"abstract":"<p><p>This article presents the first implementation of a proportional-integral-derivative (PID) biomolecular controller within a consortium of different cell populations, aimed at robust regulation of biological processes. By leveraging the modularity and cooperative dynamics of multiple engineered cell populations, we develop a comprehensive <i>in silico</i> analysis of the performance and robustness of P, PD, PI and PID control architectures. Our theoretical findings, validated through <i>in silico</i> experiments using the BSim agent-based simulation platform for bacterial populations, demonstrate the robustness and effectiveness of our multicellular PID control strategy. This innovative approach addresses critical limitations in current control methods, offering significant potential for applications in metabolic engineering, therapeutic contexts and industrial biotechnology. Future work will focus on experimental validation <i>in vivo</i> and further refinement of the control models.</p>","PeriodicalId":17488,"journal":{"name":"Journal of The Royal Society Interface","volume":"22 222","pages":"20240583"},"PeriodicalIF":3.7000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11775662/pdf/","citationCount":"0","resultStr":"{\"title\":\"Multicellular PID control for robust regulation of biological processes.\",\"authors\":\"Vittoria Martinelli, Davide Fiore, Davide Salzano, Mario di Bernardo\",\"doi\":\"10.1098/rsif.2024.0583\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This article presents the first implementation of a proportional-integral-derivative (PID) biomolecular controller within a consortium of different cell populations, aimed at robust regulation of biological processes. By leveraging the modularity and cooperative dynamics of multiple engineered cell populations, we develop a comprehensive <i>in silico</i> analysis of the performance and robustness of P, PD, PI and PID control architectures. Our theoretical findings, validated through <i>in silico</i> experiments using the BSim agent-based simulation platform for bacterial populations, demonstrate the robustness and effectiveness of our multicellular PID control strategy. This innovative approach addresses critical limitations in current control methods, offering significant potential for applications in metabolic engineering, therapeutic contexts and industrial biotechnology. Future work will focus on experimental validation <i>in vivo</i> and further refinement of the control models.</p>\",\"PeriodicalId\":17488,\"journal\":{\"name\":\"Journal of The Royal Society Interface\",\"volume\":\"22 222\",\"pages\":\"20240583\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11775662/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of The Royal Society Interface\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1098/rsif.2024.0583\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/29 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of The Royal Society Interface","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1098/rsif.2024.0583","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/29 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Multicellular PID control for robust regulation of biological processes.
This article presents the first implementation of a proportional-integral-derivative (PID) biomolecular controller within a consortium of different cell populations, aimed at robust regulation of biological processes. By leveraging the modularity and cooperative dynamics of multiple engineered cell populations, we develop a comprehensive in silico analysis of the performance and robustness of P, PD, PI and PID control architectures. Our theoretical findings, validated through in silico experiments using the BSim agent-based simulation platform for bacterial populations, demonstrate the robustness and effectiveness of our multicellular PID control strategy. This innovative approach addresses critical limitations in current control methods, offering significant potential for applications in metabolic engineering, therapeutic contexts and industrial biotechnology. Future work will focus on experimental validation in vivo and further refinement of the control models.
期刊介绍:
J. R. Soc. Interface welcomes articles of high quality research at the interface of the physical and life sciences. It provides a high-quality forum to publish rapidly and interact across this boundary in two main ways: J. R. Soc. Interface publishes research applying chemistry, engineering, materials science, mathematics and physics to the biological and medical sciences; it also highlights discoveries in the life sciences of relevance to the physical sciences. Both sides of the interface are considered equally and it is one of the only journals to cover this exciting new territory. J. R. Soc. Interface welcomes contributions on a diverse range of topics, including but not limited to; biocomplexity, bioengineering, bioinformatics, biomaterials, biomechanics, bionanoscience, biophysics, chemical biology, computer science (as applied to the life sciences), medical physics, synthetic biology, systems biology, theoretical biology and tissue engineering.