{"id":72,"date":"2017-12-15T15:30:13","date_gmt":"2017-12-15T14:30:13","guid":{"rendered":"https:\/\/project.inria.fr\/iplcosy\/?page_id=72"},"modified":"2021-11-12T16:03:40","modified_gmt":"2021-11-12T15:03:40","slug":"research","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/iplcosy\/research\/","title":{"rendered":"Research"},"content":{"rendered":"<p><\/p>\n<h4>The concept<\/h4>\n<p>Automated control of synthetic microbial communities:<\/p>\n<p><a href=\"https:\/\/project.inria.fr\/iplcosy\/files\/2019\/02\/ThePicture.png\"><img loading=\"lazy\" decoding=\"async\" class=\"size-medium wp-image-117 alignleft\" src=\"https:\/\/project.inria.fr\/iplcosy\/files\/2019\/02\/ThePicture-300x225.png\" alt=\"\" width=\"300\" height=\"225\" srcset=\"https:\/\/project.inria.fr\/iplcosy\/files\/2019\/02\/ThePicture-300x225.png 300w, https:\/\/project.inria.fr\/iplcosy\/files\/2019\/02\/ThePicture-768x577.png 768w, https:\/\/project.inria.fr\/iplcosy\/files\/2019\/02\/ThePicture-1024x769.png 1024w, https:\/\/project.inria.fr\/iplcosy\/files\/2019\/02\/ThePicture-150x113.png 150w, https:\/\/project.inria.fr\/iplcosy\/files\/2019\/02\/ThePicture.png 1056w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a>Engineering of biochemical circuits ensuring controlled single-cell response to actuation inputs<\/p>\n<p>Mathematical modelling of dynamics of cellluar sub-populations and community interactions<\/p>\n<p>Definition of community-level optimal control goals<\/p>\n<p>Model-based estimation and optimal control algorithms<\/p>\n<p>Computer-based automated control of bioreactor system<\/p>\n<p>&nbsp;<\/p>\n<h4>Achievement highlights<\/h4>\n<ul>\n<li>Design, synthesis, characterization and control of a light-tunable differentiation system for bioproduction in yeast<\/li>\n<li>Design, synthesis and characterization of a consortium of <em>E. coli<\/em> bacteria for cooperative protein production<\/li>\n<li>New methods and results on the mathematical and numerical analysis of the microbial communities<\/li>\n<li>Design and theoretical analysis of real-time estimation and control methods for stabilization of biomasses\/bioproduction performance<\/li>\n<li>Deployment of three platforms for the automated execution of monitoring and control experiments with microbial communities<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h4>Publications<\/h4>\n<p>In preparation\/submitted:<\/p>\n<ul>\n<li>C. Martinez, E. Cinquemani, H. de Jong, J.-L. Gouz\u00e9, &#8220;Coexistence and optimization of a synthetic microbial community&#8221;<\/li>\n<li>A. dos Reis de Souza, D. Efimov, A. Polyakov, J.-L. Gouz\u00e9, E. Cinquemani, &#8220;State observation in microbial consortia: a case study on a synthetic producer-cleaner consortium&#8221;<\/li>\n<li>A. Pavlou, E.Cinquemani, J.Geiselmann, H. de Jong, \u201cProtein-specific maturation models are necessary to obtain unbiased estimates of promoter activity\u201d<\/li>\n<\/ul>\n<p>In press:<\/p>\n<ul>\n<li>A. dos Reis de Souza, D. Efimov, T. Ra\u00efssi, X. Ping, &#8220;Robust output feedback model predictive control for constrained linear systems via interval observers&#8221;, <em>Automatica<\/em><\/li>\n<li>A. Yabo, J.-B. Caillau, J.-L. Gouz\u00e9, H. de Jong, F. Mairet, &#8220;Dynamical analysis and optimization of a generalized resource allocation model of microbial growth&#8221;, <em>SIADS<\/em>.<br \/>\nhttps:\/\/hal.inria.fr\/hal-03251044\/file\/maintenance.pdf<\/li>\n<li>A. Yabo, J.-B. Caillau, J.-L. Gouz\u00e9, &#8220;Hierarchical MPC applied to bacterial resource allocation and metabolite synthesis&#8221;, <em>Proceedings of CDC 2021<\/em>. https:\/\/hal.archives-ouvertes.fr\/hal-03189960\/file\/CDC2021.pdf<\/li>\n<\/ul>\n<p>2021:<\/p>\n<ul>\n<li>A. Marguet, E. Cinquemani, &#8220;Identification of stochastic gene expression models over lineage trees&#8221;, <em>Proceedings of the 19th IFAC sympusium on System Identification<\/em> (SysId), Padova\/online, July 13-16<\/li>\n<li>D. Lunz, G. Batt, J. Ruess, J. F. Bonnans, &#8220;Beyond the chemical master equation: stochastic chemical kinetics coupled with auxiliary processes&#8221;, <em>PLoS Computational Biology<\/em>. https:\/\/doi.org\/10.1371\/journal.pcbi.1009214<\/li>\n<li>D. Lunz, &#8220;On rapid oscillations driving biological processes at disparate timescales&#8221;, <em>Physical Biology<\/em>, 18(3):036002<\/li>\n<li>D. Lunz, &#8220;On continuum approximations of discrete-state Markov processes of large system size&#8221;,<em> Multiscale Modeling and Simulation<\/em>, SIAM, 19(1):294-319<\/li>\n<li>Z. R. Fox, S. Fletcher, A. Fraisse, C. Aditya, S. Sosa-Carrillo, S. Gilles, F. Bertaux, J. Ruess, G. Batt, &#8220;MicroMator: Open and Flexible Software for Reactive Microscopy&#8221;, <em>bioRxiv<\/em>. https:\/\/doi.org\/10.1101\/2021.03.12.435206<\/li>\n<li>C. Aditya, F. Bertaux, G. Batt, J. Ruess, &#8220;A light tunable differentiation system for the creation and control of consortia in yeast&#8221;, <em>Nature Communications<\/em>, 12:5829.<\/li>\n<li>F.Bertaux, J.Ruess, G.Batt, \u201cExternal control of microbial populations for bioproduction: A modeling and optimization viewpoint\u201d. <em>Current Opinion in Systems Biology<\/em>, 28:100394<\/li>\n<li>C.Aditya, F.Bertaux, G.Batt, J.Ruess, \u201cUsing single-cell models to predict the functionality of synthetic circuits at the population scale\u201d, <em>bioRxiv<\/em> 2021.08.03.454887. https:\/\/doi.org\/10.1101\/2021.08.03.454887<\/li>\n<li>C. Mart\u00ednez, J.-L. Gouz\u00e9, &#8220;Global dynamics of the chemostat with overflow metabolism&#8221;, <em>Journal of Mathematical Biology<\/em>, 82:3<\/li>\n<li>A. dos Reis de Souza, D. Efimov, T. Ra\u00efssi, &#8220;Robust output feedback MPC for LPV systems using interval observers&#8221;, <em>IEEE Transactions on Automatic Control<\/em><\/li>\n<li>D. Lunz, G. Batt, J. Ruess, &#8220;To quarantine, or not to quarantine: A theoretical framework for disease control via contact tracing&#8221;, <em>Epidemics<\/em>, 34:100428. https:\/\/doi.org\/10.1016\/j.epidem.2020.100428<\/li>\n<\/ul>\n<p>2020:<\/p>\n<ul>\n<li>F. Bertaux, S. Sosa-Carrillo, A. Fraisse, C. Aditya, M. Furstenheim, G. Batt, &#8220;Enhancing bioreactor arrays for automated measurements and reactive control with ReacSight&#8221;, <em>bioRxiv<\/em>, https:\/\/doi.org\/10.1101\/2020.12.27.424467<\/li>\n<li>A. dos Reis de Souza, J.-L. Gouz\u00e9, D. Efimov, A. Polyakov, &#8220;Robust adaptive estimation in the competitive chemostat&#8221;, <em>Computers and Chemical Engineering,<\/em> 142:107030, 2020<\/li>\n<li><span class=\"highwire-cite-metadata-doi highwire-cite-metadata\">D. Lunz, G. Batt, J. Ruess, J.F. Bonnans, &#8220;Beyond the chemical master equation: stochastic chemical kinetics coupled with auxiliary processes&#8221;, Hal, 2020.\u00a0https:\/\/hal.inria.fr\/hal-02991103\/<\/span><\/li>\n<li>A.G. Yabo, J.-L. Gouz\u00e9, &#8220;Optimizing bacterial resource allocation: metabolite production in continuous bioreactors&#8221;,\u00a0<em>Proceedings of the 21th IFAC World Congress<\/em>, 2020<\/li>\n<li>E. Cinquemani, \u201cInference of the statistics of a modulated promoter process from population snapshot gene expression data\u201d, <em>Proceedings of the 21th IFAC World Congress<\/em>, 2020<\/li>\n<li>A. dos Reis de Souza, D. Efimov, A. Polyakov, J.-L. Gouz\u00e9,\u00a0 &#8220;Observer-Based Robust Control of a Continuous Bioreactor with Heterogeneous Community&#8221;, <em>Proceedings of the 21th IFAC World Congress<\/em>, 2020<\/li>\n<li>A.G. Yabo, J.-B. Caillau, J.-L. Gouz\u00e9, &#8220;Optimal bacterial resource allocation: metabolite production in continuous bioreactors&#8221;, <em>Mathematical Biosciences and Engineering<\/em>,\u00a017(6): 7074-7100, 2020<\/li>\n<li>M. Mauri, J.-L. Gouz\u00e9, H. de Jong, E. Cinquemani, &#8220;Enhanced production of heterologous proteins by a synthetic microbial community: Conditions and trade-offs&#8221;, <em>PLoS Computational Biology, <\/em>16(4):e1007795, 2020<em><br \/>\n<\/em><\/li>\n<li>A. dos Reis de Souza, D. Efimov, A. Polyakov, J.-L. Gouz\u00e9, &#8220;Robust stabilization of competing species in the chemostat&#8221;, <em>Journal of Process Control, 87:138-146, 2020<\/em><\/li>\n<\/ul>\n<p>2019:<\/p>\n<ul>\n<li>A. Yabo, J.-B. Caillau, J.-L. Gouz\u00e9, &#8220;Singular regimes for the maximization of metabolite production&#8221;,\u00a0<i> <em>Proceedings of the\u00a0 <\/em>58th IEEE Conference on Decision and Control (CDC)<\/i>, 2019<\/li>\n<li>A. dos Reis de Souza, D. Efimov, A. Polyakov, J.-L. Gouz\u00e9, &#8220;On adaptive estimation of bacterial growth in the competitive chemostat&#8221;, <em>Proceedings of the 11th IFAC Symposium on Nonlinear Systems Control (NOLCOS)<\/em>, 2019<\/li>\n<li>A. dos Reis de Souza, D. Efimov, A. Polyakov, J.-L. Gouz\u00e9, &#8220;Robust control of a competitive environment in the chemostat using discontinuous control laws&#8221;, <em>Proceedings of the <\/em><em>58th IEEE Conference on Decision and Control (CDC)<\/em>, 2019<\/li>\n<li>A. Marguet, M. Lavielle, E. Cinquemani, &#8220;Inheritance and variability of kinetic gene expression parameters in microbial cells: Modelling and inference from lineage tree data&#8221;.<em> Bioinformatics<\/em> (Proceedings of ISMB\/ECCB), 35(14):i586\u2013i595, 2019<\/li>\n<li>E. Cinquemani, F. Mairet, I. Yegorov, H. de Jong, J.-L. Gouz\u00e9, &#8220;Optimal control of bacterial growth for metabolite production: The role of timing and costs of control&#8221;, <em>Proceedings of the 17th European Control Conference (ECC)<\/em>, 2019<\/li>\n<li>E. Weill, V. Andreani, C. Aditya, P. Martinon, J. Ruess, G. Batt, J.F. Bonnans, &#8220;Optimal control of an artificial microbial differentiation system for protein bioproduction&#8221;, <em>Proceedings of the 17th European Control Conference (ECC)<\/em>, 2019<\/li>\n<li>E. Cinquemani, &#8220;Stochastic reaction networks with input processes: Analysis and application to gene expression inference&#8221;, <em>Automatica<\/em>, 101:150-156, 2019<\/li>\n<\/ul>\n<p>2018:<\/p>\n<ul>\n<li>E. Cinquemani, &#8220;Identifiability and Reconstruction of Biochemical Reaction Networks from Population Snapshot Data\u201d, <em>Processes<\/em> (Special Issue on Computational Synthetic Biology), 6(9):136, 2018<\/li>\n<\/ul>\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/iplcosy\/research\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":1309,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":"","_members_access_role":[],"_members_access_error":""},"class_list":["post-72","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/iplcosy\/wp-json\/wp\/v2\/pages\/72","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/iplcosy\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/iplcosy\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/iplcosy\/wp-json\/wp\/v2\/users\/1309"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/iplcosy\/wp-json\/wp\/v2\/comments?post=72"}],"version-history":[{"count":26,"href":"https:\/\/project.inria.fr\/iplcosy\/wp-json\/wp\/v2\/pages\/72\/revisions"}],"predecessor-version":[{"id":173,"href":"https:\/\/project.inria.fr\/iplcosy\/wp-json\/wp\/v2\/pages\/72\/revisions\/173"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/iplcosy\/wp-json\/wp\/v2\/media?parent=72"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}