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+ | <p>Tune our bacteria so that it activates the synthesis of Azurin only in the right conditions: High cell density AND High lactate</p> | ||
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<h1>OVERVIEW</h1> | <h1>OVERVIEW</h1> | ||
<p>As discussed in the <a href="https://2017.igem.org/Team:ETH_Zurich/Description">description of our project</a> one main issue of anti-cancer treatments is specificity: deleterious effects induced by these treatments should only target tumor cells, and leave healthy cells unaffected. To avoid such so called “off-target” effects, our synthetic bacterial system comprises of two sensing capabilities: sensing of lactate, and of bacterial cell density (via quorum sensing). Because <i>E. coli</i> Nissle should only form colonies in tumors, which are also areas where the ambient lactate concentration is higher than in healthy tissues, we believe that our dual sensing circuit will help minimize off-target synthesis of azurin.</p> | <p>As discussed in the <a href="https://2017.igem.org/Team:ETH_Zurich/Description">description of our project</a> one main issue of anti-cancer treatments is specificity: deleterious effects induced by these treatments should only target tumor cells, and leave healthy cells unaffected. To avoid such so called “off-target” effects, our synthetic bacterial system comprises of two sensing capabilities: sensing of lactate, and of bacterial cell density (via quorum sensing). Because <i>E. coli</i> Nissle should only form colonies in tumors, which are also areas where the ambient lactate concentration is higher than in healthy tissues, we believe that our dual sensing circuit will help minimize off-target synthesis of azurin.</p> | ||
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<p>After we gave preliminary guidelines for the first design of our plasmids based on our parameter space search and previously characterized iGEM BioBrick, we explored which experiments could give us the important parameters of our system. Once determined and conducted in the wet lab, we fitted the obtained data to characterize the behavior of our current system.</p> | <p>After we gave preliminary guidelines for the first design of our plasmids based on our parameter space search and previously characterized iGEM BioBrick, we explored which experiments could give us the important parameters of our system. Once determined and conducted in the wet lab, we fitted the obtained data to characterize the behavior of our current system.</p> | ||
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Revision as of 12:08, 27 October 2017
![CATE logo](https://static.igem.org/mediawiki/2017/d/d6/T--ETH_Zurich--LogoMinimal.png)
Environment Sensing
GOAL
Tune our bacteria so that it activates the synthesis of Azurin only in the right conditions: High cell density AND High lactate
OVERVIEW
As discussed in the description of our project one main issue of anti-cancer treatments is specificity: deleterious effects induced by these treatments should only target tumor cells, and leave healthy cells unaffected. To avoid such so called “off-target” effects, our synthetic bacterial system comprises of two sensing capabilities: sensing of lactate, and of bacterial cell density (via quorum sensing). Because E. coli Nissle should only form colonies in tumors, which are also areas where the ambient lactate concentration is higher than in healthy tissues, we believe that our dual sensing circuit will help minimize off-target synthesis of azurin.
Our gene design implements the double sensing of cell density and lactate (see FIGURE). We have modeled it to predict its behavior in both in vivo and in vitro situations, depending on the relevant gene-expression dynamics.
Our in vivo model, which integrates parameters estimated from the literature regarding tumor colonization of E. coli Nissle, enabled us to characterize the parameter space where our system would meet both the specificity and azurin output requirements that we preliminarily set thanks to our azurin toxicity assays (LINK TO EXPERIMENT).
After we gave preliminary guidelines for the first design of our plasmids based on our parameter space search and previously characterized iGEM BioBrick, we explored which experiments could give us the important parameters of our system. Once determined and conducted in the wet lab, we fitted the obtained data to characterize the behavior of our current system.