BioModelsapplication/xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL8262229752?filename=MODEL8262229752.pdfhttps://www.ebi.ac.uk/biomodels/model/download/MODEL8262229752?filename=MODEL8262229752-biopax3.owlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL8262229752?filename=MODEL8262229752-biopax2.owlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL8262229752?filename=MODEL8262229752_url.xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL8262229752?filename=MODEL8262229752_urn.xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL8262229752?filename=MODEL8262229752.scihttps://www.ebi.ac.uk/biomodels/model/download/MODEL8262229752?filename=MODEL8262229752.pnghttps://www.ebi.ac.uk/biomodels/model/download/MODEL8262229752?filename=MODEL8262229752.xpphttps://www.ebi.ac.uk/biomodels/model/download/MODEL8262229752?filename=MODEL8262229752.mhttps://www.ebi.ac.uk/biomodels/model/download/MODEL8262229752?filename=MODEL8262229752.vcmlprimaryOK200Molecular Systems BiologyNon-curatedordinary differential equation modelL2V1https://www.ebi.ac.uk/biomodels/MODEL826222975217170762falseBioModelsSBMLModelsMODEL8262229752 url.xml2006MODEL8262229752Jun Li, Liang Wang, Yoshifumi Hashimoto, Chen-Yu Tsao, Thomas K Wood, James J Valdes, Evanghelos Zafiriou, William E BentleyJun Li17170762, Quorum sensing (QS) is an important determinant of bacterial phenotype. Many cell functions are regulated by intricate and multimodal QS signal transduction processes. The LuxS/AI-2 QS system is highly conserved among Eubacteria and AI-2 is reported as a 'universal' signal molecule. To understand the hierarchical organization of AI-2 circuitry, a comprehensive approach incorporating stochastic simulations was developed. We investigated the synthesis, uptake, and regulation of AI-2, developed testable hypotheses, and made several discoveries: (1) the mRNA transcript and protein levels of AI-2 synthases, Pfs and LuxS, do not contribute to the dramatically increased level of AI-2 found when cells are grown in the presence of glucose; (2) a concomitant increase in metabolic flux through this synthesis pathway in the presence of glucose only partially accounts for this difference. We predict that 'high-flux' alternative pathways or additional biological steps are involved in AI-2 synthesis; and (3) experimental results validate this hypothesis. This work demonstrates the utility of linking cell physiology with systems-based stochastic models that can be assembled de novo with partial knowledge of biochemical pathways.. null, 2. Center for Biosystems Research, University of Maryland Biotechnology Institute, College Park, Maryland, MD, USA.msbforum@embo.orgNature Publishing GroupQuorum sensing (QS) is an important determinant of bacterial phenotype. Many cell functions are regulated by intricate and multimodal QS signal transduction processes. The LuxS/AI-2 QS system is highly conserved among Eubacteria and AI-2 is reported as a 'universal' signal molecule. To understand the hierarchical organization of AI-2 circuitry, a comprehensive approach incorporating stochastic simulations was developed. We investigated the synthesis, uptake, and regulation of AI-2, developed testable hypotheses, and made several discoveries: (1) the mRNA transcript and protein levels of AI-2 synthases, Pfs and LuxS, do not contribute to the dramatically increased level of AI-2 found when cells are grown in the presence of glucose; (2) a concomitant increase in metabolic flux through this synthesis pathway in the presence of glucose only partially accounts for this difference. We predict that 'high-flux' alternative pathways or additional biological steps are involved in AI-2 synthesis; and (3) experimental results validate this hypothesis. This work demonstrates the utility of linking cell physiology with systems-based stochastic models that can be assembled de novo with partial knowledge of biochemical pathways.A stochastic model of Escherichia coli AI-2 quorum signal circuit reveals alternative synthesis pathways.Li Jun J, Wang Liang L, Hashimoto Yoshifumi Y, Tsao Chen-Yu CY, Wood Thomas K TK, Valdes James J JJ, Zafiriou Evanghelos E, Bentley William E WEfalseMODEL8262229752_url.xml This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92. 2018-07-092005-01-012007-03-12MODEL826222975217170762MODEL8262229752GO:0009372562