Difference between revisions of "Team:Heidelberg/Model"

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         Successful in vivo directed evolution by PREDCEL and PACE requires the thorough consideration of experimental parameters, e.g. phage propagation times, culture dilution rates and inducer/inhibitor concentrations. We employed extensive ODE-based and stochastic modeling to identify the most sensitive parameters and adapt our experiments accordingly. First, we calibrated our models using phage propagation experiments from our wet lab complemented with literature data. Simulations showed that the phage titer is highly sensitive to culture dilution rates. We simulated batch times and transfer volumes for PREDCEL and corresponding flow rates for PACE to determine optimized conditions for gene pool selection while avoiding phage washout. We also estimated phage titer monitoring intervals for cost/labor efficient QC as well as inducer/inhibitor concentrations required to express the required mutagenic polymerases. Finally, provide a web-based, fully interactive modeling platform, not only extensively employed by our wet lab, but highly informs future iGEM teams building on our work.
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         Successful <i>in vivo</i> directed evolution by PREDCEL and PACE requires the thorough consideration of experimental parameters, e.g. phage propagation times, culture dilution rates and inducer/inhibitor concentrations. We employed extensive ODE-based and stochastic modeling to identify the most sensitive parameters and adapt our experiments accordingly. First, we calibrated our models using phage propagation experiments from our wet lab complemented with literature data. Simulations showed that the phage titer is highly sensitive to culture dilution rates. We simulated batch times and transfer volumes for PREDCEL and corresponding flow rates for PACE to determine optimized conditions for gene pool selection while avoiding phage washout. We also estimated phage titer monitoring intervals for cost and labor efficient QC/monitoring as well as inducer/inhibitor concentrations required to express the required mutagenic polymerases. Finally, we provide a web-based, fully interactive modeling platform that not only informed our wet lab experiments, but enables future iGEM teams to efficiently build on our work.
 
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                 {{Heidelberg/panelelement|Mutation Rate Estimation|https://static.igem.org/mediawiki/2017/a/ab/T--Heidelberg--2017_mutation_rate_estimation-logo.png|https://2017.igem.org/Team:Heidelberg/Model/Mutation|
 
                 {{Heidelberg/panelelement|Mutation Rate Estimation|https://static.igem.org/mediawiki/2017/a/ab/T--Heidelberg--2017_mutation_rate_estimation-logo.png|https://2017.igem.org/Team:Heidelberg/Model/Mutation|
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                 {{#tag:html|Estimate the number of mutated sequences in a PREDCEL or PACE experiment at a given point in time to check for the covered sequence space and to save time and mony when sequencing.</p><a href="https://2017.igem.org/Team:Heidelberg/Model/Mutation_Rate_Estimation" class="card-button">Analytic Model</a><p>}}|Interactive Webtool
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                 {{#tag:html|Estimate the number of mutated sequences in a PREDCEL or PACE experiment at a given point in time to check for the covered sequence space and to save time and money when sequencing.</p><a href="https://2017.igem.org/Team:Heidelberg/Model/Mutation_Rate_Estimation" class="card-button">Analytic Model</a><p>}}|Interactive Webtool
 
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                 {{Heidelberg/panelelement|Medium Consumption|https://static.igem.org/mediawiki/2017/1/13/T--Heidelberg--2017_medium_consumption-logo.png|https://2017.igem.org/Team:Heidelberg/Model/Medium|
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                 {{#tag:html|Calculate the amount of medium needed for a PACE experiment, see how medium consumption can be reduced when experimental parameters are optimised.</p><a href="https://2017.igem.org/Team:Heidelberg/Model/Medium_Consumption" class="card-button">Analytic Model</a><p>}}|Interactive Webtool}}
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                 {{#tag:html|Calculate the amount of medium needed for a PACE experiment, see how medium consumption can be reduced when experimental parameters are optimized.</p><a href="https://2017.igem.org/Team:Heidelberg/Model/Medium_Consumption" class="card-button">Analytic Model</a><p>}}|Interactive Webtool}}
 
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Revision as of 19:51, 31 October 2017


Modeling
Overview
Successful in vivo directed evolution by PREDCEL and PACE requires the thorough consideration of experimental parameters, e.g. phage propagation times, culture dilution rates and inducer/inhibitor concentrations. We employed extensive ODE-based and stochastic modeling to identify the most sensitive parameters and adapt our experiments accordingly. First, we calibrated our models using phage propagation experiments from our wet lab complemented with literature data. Simulations showed that the phage titer is highly sensitive to culture dilution rates. We simulated batch times and transfer volumes for PREDCEL and corresponding flow rates for PACE to determine optimized conditions for gene pool selection while avoiding phage washout. We also estimated phage titer monitoring intervals for cost and labor efficient QC/monitoring as well as inducer/inhibitor concentrations required to express the required mutagenic polymerases. Finally, we provide a web-based, fully interactive modeling platform that not only informed our wet lab experiments, but enables future iGEM teams to efficiently build on our work.
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Phage titer

Simulations of phage and E. coli titer support both PREDCEL and PACE by helping to choose a set of experimental parameters that is both efficient in terms of directed evolution and in terms of usability.

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Interactive Webtools

Use the interactive tools to simulate the conditions you are interested in and explore how the combined experimental parameters influence experimental outcomes.

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Mutagenesis Induction

Model the glucose and arabinose concentration to make sure mutagenesis plasmids are sufficiently induced to get optimal mutagenesis conditions for both PREDCEL and PACE.

Analytic Model

Glucose Tool

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Lagoon Contamination

Check if lagoons are vulnerable to contamination by microorganisms under given experimental conditions.

Analytic Model

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Mutation Rate Estimation

Estimate the number of mutated sequences in a PREDCEL or PACE experiment at a given point in time to check for the covered sequence space and to save time and money when sequencing.

Analytic Model

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Medium Consumption

Calculate the amount of medium needed for a PACE experiment, see how medium consumption can be reduced when experimental parameters are optimized.

Analytic Model

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