Difference between revisions of "Team:UofUppsala"

 
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                 <h1 class="text-title animate__animated animate__fadeInUp animate__delay-4s">NANOFLEX</h1>
 
                 <h1 class="text-title animate__animated animate__fadeInUp animate__delay-4s">NANOFLEX</h1>
                 <h2 class="text-subtitle  animate__animated animate__fadeInUp animate__delay-5s">Your specific and modular biosensor</h2>
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                 <h2 class="text-subtitle  animate__animated animate__fadeInUp animate__delay-5s">Our detection device for your analyte of choice</h2>
 
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<h3>Our project...</h3>
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<br class="title-br">
<p>...aims to create a cellular biosensor adaptable to detect your analytes of choice. Its design contains a sensory module, where nanobodies interact with the targets, activating the signal amplification module, which will result in an output signal visible to the naked eye. Placing this system in an easy-to-use format, we intend to offer a standardized, flexible and accessible detection system. Read more <a href="https://2020.igem.org/Team:UofUppsala/Description">here</a>.</p>
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<h1 style="text-align:center">NANOFLEX: Standardized, Flexible and Accessible Cellular Biosensor </h1>
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<h3 style="text-align:center">Best New Application Project of iGEM 2020</h3><hr>
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<p>NANOFLEX is a cellular biosensor adaptable to detect your analyte of choice and generate a colorimetric output, visible by the naked eye. The First Generation of NANOFLEX achieves this through using modified DNA binding domains (DBDs) fused to nanobodies that bind specifically to an analyte of choice, binding  a specific promoter, pCadBA, which induces a reporter gene. The proof of concept of the First Generation of NANOFLEX uses anti-caffeine nanobody and mRFP1 as the reporter gene, showing the system's sensitivity at low concentrations of analyte in both analytically clean and crude samples. This was also reassured by a stochastic model predicting the same pattern for the signal in different caffeine concentrations.</p>
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<p>The Next Generation of NANOFLEX focuses on improving the signal by amplifying it and removing the background noise. Signal amplification and noise reduction modules employ Q&beta; viral replicase and T7 RNA polymerase systems respectively. A switch towards an enzymatic reporter, &beta;-galactosidase, is explored for faster and stronger signals as well.</p>
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<p>Further focus lays on enabling detection of larger analytes that cannot cross the membrane of our biosensor cell <i>Escherichia coli</i> (<i>E. coli</i>), for example proteins. Firstly, the avenue of outer cell wall deficient <i>E. coli</i> was explored. Secondly, modified NarX-NarL, two-component system from <i>E. coli</i>, fused to nanobodies was explored as the system is rewired for a gram positive host, <i>Bacillus subtilis</i>. This will allow detection in the extracellular media, as this organism only has a single membrane.</p>
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<p>Protein detection was explored in several ways. A guideline on creating new nanobodies was compiled and a Molecular Dynamics (MD) pipeline was created in order to study nanobody affinity in silico. We explored detection of HSP16.3 protein, a biomarker for tuberculosis, as a potential application of NANOFLEX. An anti-HSP16.3 nanobody was run through the MD pipeline and practical implementation information was gathered via interviews with experts in the field.</p>
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<p>NANOFLEX's potential lays within an easy-to-use format of a cellular biosensor. In order to envision potential distribution, a prototype of a distribution kit was developed and biosensing was tested after lyophilization. Read more <a href="https://2020.igem.org/Team:UofUppsala/Description">here</a>.</p>
 
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     <h5 class="card-title text-center">In the Lab</h5>
 
     <h5 class="card-title text-center">In the Lab</h5>
     <p class="card-text">Parallelly to the development of our sensor,  a lot of effort this year went to the “Development of Type IIS cloning standard”, which allows a higher degree of modularity for NANOFLEX.</p>
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     <p class="card-text">In parallel to the development of our sensor,  a lot of effort this year went to the “Development of Type IIS cloning Standard”, which allows a higher degree of modularity for NANOFLEX.</p>
 
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   <a href="https://2020.igem.org/Team:UofUppsala/Results" class="card-footer text-center"> Read more </a>
 
   <a href="https://2020.igem.org/Team:UofUppsala/Results" class="card-footer text-center"> Read more </a>
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     <h5 class="card-title text-center">Computational modelling</h5>
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     <h5 class="card-title text-center">Computational Modelling</h5>
 
     <p class="card-text">Our modelling approach is two-fold, a python based stochastic model for expression of detection proteins and a molecular dynamics pipeline for modifying the nanobody component of our sensor.</p>
 
     <p class="card-text">Our modelling approach is two-fold, a python based stochastic model for expression of detection proteins and a molecular dynamics pipeline for modifying the nanobody component of our sensor.</p>
 
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Latest revision as of 21:41, 17 December 2020


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NANOFLEX

Our detection device for your analyte of choice


NANOFLEX: Standardized, Flexible and Accessible Cellular Biosensor

Best New Application Project of iGEM 2020


NANOFLEX is a cellular biosensor adaptable to detect your analyte of choice and generate a colorimetric output, visible by the naked eye. The First Generation of NANOFLEX achieves this through using modified DNA binding domains (DBDs) fused to nanobodies that bind specifically to an analyte of choice, binding a specific promoter, pCadBA, which induces a reporter gene. The proof of concept of the First Generation of NANOFLEX uses anti-caffeine nanobody and mRFP1 as the reporter gene, showing the system's sensitivity at low concentrations of analyte in both analytically clean and crude samples. This was also reassured by a stochastic model predicting the same pattern for the signal in different caffeine concentrations.

The Next Generation of NANOFLEX focuses on improving the signal by amplifying it and removing the background noise. Signal amplification and noise reduction modules employ Qβ viral replicase and T7 RNA polymerase systems respectively. A switch towards an enzymatic reporter, β-galactosidase, is explored for faster and stronger signals as well.

Further focus lays on enabling detection of larger analytes that cannot cross the membrane of our biosensor cell Escherichia coli (E. coli), for example proteins. Firstly, the avenue of outer cell wall deficient E. coli was explored. Secondly, modified NarX-NarL, two-component system from E. coli, fused to nanobodies was explored as the system is rewired for a gram positive host, Bacillus subtilis. This will allow detection in the extracellular media, as this organism only has a single membrane.

Protein detection was explored in several ways. A guideline on creating new nanobodies was compiled and a Molecular Dynamics (MD) pipeline was created in order to study nanobody affinity in silico. We explored detection of HSP16.3 protein, a biomarker for tuberculosis, as a potential application of NANOFLEX. An anti-HSP16.3 nanobody was run through the MD pipeline and practical implementation information was gathered via interviews with experts in the field.

NANOFLEX's potential lays within an easy-to-use format of a cellular biosensor. In order to envision potential distribution, a prototype of a distribution kit was developed and biosensing was tested after lyophilization. Read more here.

Card image cap
In the Lab

In parallel to the development of our sensor, a lot of effort this year went to the “Development of Type IIS cloning Standard”, which allows a higher degree of modularity for NANOFLEX.

Read more
Card image cap
Computational Modelling

Our modelling approach is two-fold, a python based stochastic model for expression of detection proteins and a molecular dynamics pipeline for modifying the nanobody component of our sensor.

Read more
Card image cap
Outreach

Informed decision-making is the motto of our project. From early on, we have been contacting experts and professors for their inputs. We have also organized education and collaborations programs directed to the iGEM community, but also to the general public.

Read more
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Team

We are the team of Uppsala University (Sweden) for the complicated year of 2020. With different education backgrounds and from all over the world, we are 25 students that decided to enrol in the iGEM adventure.

Read more