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MIT Jamboree 2007
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Talk Outline Background System design Novel reporter system Established modelling techniques Cutting-edge modelling
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MIT Jamboree 2007 Phenolic compounds Polycyclic aromatic hydrocarbons (PAH) BTEX compounds The Problem
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MIT Jamboree 2007 1: Design modular sensor construct 2: Create the construct 3: Test the system 4: Development into a machine 5: Model and predict outcomes! Objectives
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MIT Jamboree 2007 Why a Biosensor? Lab-based monitoring Skilled workforce Expensive!
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MIT Jamboree 2007 operator / promoterreporter gene() XylR toluene What is a Biosensor? Biosensors include a transcriptional activator coupled to a reporter Luciferase gene luciferase luciferin luminescence
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MIT Jamboree 2007 Our Construct Design Responsive promoter Double terminator BBa_B0015 RBS BBa_J61101 Reporter gene Constitutive promoter Transcriptional activator Double terminator BBa_B0015 RBS
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MIT Jamboree 2007 1: Design modular sensor construct –Switch on reporter in presence of pollutants 2: Create the construct 3: Test the system 4: Development into a machine 5: Model and predict outcomes! Objectives
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MIT Jamboree 2007 Phenolic compounds Polycyclic aromatic hydrocarbons (PAH) BTEX compounds Our Solution DmpR - phenols DntR - PAHs XylR - toluene
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MIT Jamboree 2007 Responsive promoter RBS BBa_J61101 Double terminator BBa_B0015 Reporter gene Constitutive promoter Transcriptional activator Double terminator BBa_B0015 RBS LacZ GFP Luciferase DmpR - phenols DntR - PAHs XylR - toluene Our Construct Design
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MIT Jamboree 2007 1: Design modular sensor construct –Switch on reporter in presence of pollutants 2: Create the construct –Use 3 different sensors to express luciferase or LacZ 3: Test the system 4: Development into a machine 5: Model and predict outcomes! Objectives
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MIT Jamboree 2007 Testing The System XylR - inducible luciferase DntR - inducible LacZ [PAH metabolite] ( M)
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MIT Jamboree 2007 1: Design sensor/reporter construct –Switch on reporter in presence of pollutants 2: Create the construct –Use 3 different sensors to express luciferase or LacZ 3: Test the system –PAH-metabolite and xylene sensors successful 4: Development into a machine 5: Model and predict outcomes! Objectives
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MIT Jamboree 2007 Unique Reporter System Conventional biosensors use conventional reporter genes –e.g. LacZ, GFP, luciferase… Lengthy and expensive procedures Need a novel idea!
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MIT Jamboree 2007 Microbial Fuel Cells Clean, renewable & autonomous Electrons from metabolism harvested at anode Versatile, long-lasting, varied carbon sources Advantage over conventional power sources
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MIT Jamboree 2007 Microbial Fuel Cells
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MIT Jamboree 2007 Pyocyanin From pathogenic Pseudomonas aeruginosa
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MIT Jamboree 2007 Phz genes – 7 gene operon, pseudomonad specific PhzM and PhzS – P. aeruginosa specific Pyocyanin
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MIT Jamboree 2007 Our Constructs Constitutive promoter Inducible transcription factor Double terminator RBS Target promoter PhzM coding region RBS PhzS coding region Double terminator RBS
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MIT Jamboree 2007 + - Pollutant Microbial Fuel Cell Electrical Output xylR RBS Term. PrPr PuPu phz genes Term. PYOCYANIN RBS
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MIT Jamboree 2007 1: Design sensor/reporter construct –Switch on reporter in presence of pollutants 2: Create the construct –Use 3 different sensors to express luciferase or LacZ 3: Test the system –PAH-metabolite and xylene sensors successful 4: Development into a machine –Use Pseudomonas aeruginosa to power a fuel cell which generates a remote signal sent to base station 5: Model and predict outcomes! Objectives
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MIT Jamboree 2007 Wetlab - Drylab
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MIT Jamboree 2007 Computational Modelling of the Biosensor Aims Guide biologists for the better design of synthetic networks Use different computational approaches to model and analyze the systems o Simple biosensor o Positive feedback within the biosensor Test and Validate the hypothesis proposed by the biologists
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MIT Jamboree 2007 The Model 24 PhzMPhzS PCA Intermediate compound PYO TF + S TF|S tf phzM phzS TF|S mRNA PhzM mRNA PhzS mRNA TF Merge transcription and translation Merge phzM with phzS (Parsons 2007) TF: Dntr or Xylr S: signal TF|S: complex
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MIT Jamboree 2007 The Model 25 tf TF + S TF|S phzMS PhzMS PCA PYO TF|S PYO TF: Dntr or Xylr S: signal TF|S: complex Merge transcription and translation Merge phzM with phzS (Parsons 2007)
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MIT Jamboree 2007 Feedback Loop tf TF + S TF|S phzMS PhzMS PCA PYO TF|S PYO TF: Dntr or Xylr S: signal TF|S: complex tf
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MIT Jamboree 2007 Modelling framework
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MIT Jamboree 2007 Modelling framework
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MIT Jamboree 2007 Qualitative Petri-Net Modelling & Analysis Graphical representation--Snoopy Qualitative analysis Charlie –T invariants (cyclic behavior in pink) –P invariants –(constant amount of output) Quantitative Analysis by continuous Petri Net –ODE Simulation
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MIT Jamboree 2007 Modelling framework
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MIT Jamboree 2007 Parameters 31 Literature search Experts knowledge
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MIT Jamboree 2007 Ordinary Differential Equations 32 Available! Created in
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MIT Jamboree 2007 Parameters 33 Literature search Experts knowledge
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MIT Jamboree 2007 Model Parameter Refinement 34 Modified MPSA
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MIT Jamboree 2007 Modelling framework
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MIT Jamboree 2007 Advantages and disadvantages of stochastic modelling Living systems are intrinsically stochastic due to low numbers of molecules that participate in reactions Gives a better prediction of the model on a cellular level Allows random variation in one or more inputs over time Slow simulation time
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MIT Jamboree 2007 Chemical Master Equations A set of linear, autonomous ODEs, one ODE for each possible state of the system. The system may be written: Ф TF - production of TF TF Ф - degradation of TF TF+S TFS - association of TFS TFS TF+S - dissociation of TFS TFS Ф - degradation of TFS Ф PhzMS - production of PhzMS PhzMS Ф - degradation of PhzMS PhzMS PYO - production of pyocyanin PYO Ф - degradation of pyocyanin
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MIT Jamboree 2007 Propensity Functions
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MIT Jamboree 2007
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Simulink Modelling Environment
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MIT Jamboree 2007 In the end… Our Contributions: –standard SBML models of the systems –new biobricks with mathematical description –Practical comparison of modelling apporaches – qualitative, continuous, stochastic, based on sound theoretical framework –Tools to support synthetic biology (Code available) : Minicap: multi-parametric sensitivity analysis of dynamic systems Simulink environment
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MIT Jamboree 2007 1: Design sensor/reporter construct –Switch on reporter in presence of pollutants 2: Create the construct –Use 3 different sensors to express luciferase or LacZ 3: Test the system –PAH-metabolite and xylene sensors successful 4: Development into a machine –Use Pseudomonas aeruginosa to power a fuel cell which generates a remote signal sent to base station 5: Model and predict outcomes! Objectives
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MIT Jamboree 2007 Our Constructs So Far… Native promoter XylR Double Terminator BBa_B0015 Native RBS XylR responsive promoter Double Terminator BBa_B0015 RBS BBa_J61101 Renilla Luciferase BBa_J52008 IRESXylR responsive promoter RBS Renilla Luciferase BBa_J52008 Double Terminator BBa_B0015 IRESXylR
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MIT Jamboree 2007 Registry Contributions
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MIT Jamboree 2007 Instructors David Forehand David Gilbert Gary Gray Xu Gu Raya Khanin David Leader Susan Rosser Emma Travis Gabriela Kalna Students Toby Friend Rachael Fulton Christine Harkness Mai-Britt Jensen Karolis Kidykas Martina Marbà Lynsey McLeay Christine Merrick Maija Paakkunainen Scott Ramsay Maciej Trybiło
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MIT Jamboree 2007 Thank You!
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