Difference between revisions of "Template:Team:Utrecht/MainBody"

 
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<script id="page-home" type="text/template"><!--
 
<script id="page-home" type="text/template"><!--
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<div style="position: absolute;top: 0;right: -250px;width: 200px;text-align: center;border: 1px solid gold;padding: 10px;border-radius: 10px;box-sizing: border-box;background: #ffedb8;">
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<div style="
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    font-weight: bold;
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    border-bottom: 1px solid #ffd700;
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padding-bottom: 15px;
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    margin-bottom: 15px;
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">Awards</div>
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<img width="100" src="https://static.igem.org/mediawiki/2017/thumb/a/a2/UU_gold_medal.png/240px-UU_gold_medal.png"><br><div style="font-size: 15px;color: #c48b00; border-bottom: 1px solid #ffd700; padding-bottom: 15px; margin-top: 5px;">Gold medal</div>
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<div style="margin-top: 15px; margin-bottom: 10px; font-size: 15px;color: #c48b00;"><b>Nominated</b><br />Best integrated human practices</div>
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</div>
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<div class="page-heading">The OUTCASST two-component system</div>
 
<div class="page-heading">The OUTCASST two-component system</div>
−
This year, Utrecht University participates in the iGEM for the first time.  
+
This year is the debut year for the Utrecht University iGEM team. Our team has developed an easy to use and cheap DNA detection kit for disease diagnosis in areas of the world where advanced diagnostic technologies are not available. We call our system ‘OUTCASST’, which stands for ‘Out-of-cell Crispr-Activated Sequence-specific Signal Transducer’.
−
We aim to create a cheap DNA detection kit for disease diagnosis that is easy to use and does not rely on complicated sequencing technologies.  
+
−
We call our system ‘OUTCASST’, which stands for ‘Out-of-cell Crispr-Activated Sequence-specific Signal Transducer’.
+
 
 
 
<br />
 
<br />
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<h2 class="subhead" id="subhead-2">The problem</h2>
 
<h2 class="subhead" id="subhead-2">The problem</h2>
 
Disease diagnosis is of great importance for healthcare.  
 
Disease diagnosis is of great importance for healthcare.  
−
In developing countries, diagnoses are often based on limited information, even though accurate disease determination based on pathogen specific DNA is possible through sequencing technologies. These technologies, however, require specialised equipment and expertise that simply is not available everywhere.  
+
In developing countries, diagnoses are often based on limited information, even though accurate disease determination based on pathogen specific DNA is possible through sequencing technologies. These technologies, however, require specialised equipment and expertise that simply is not available in developing parts of the world.  
−
With the OUTCASST two-component system and detection kit, we hope to alleviate this problem.
+
The OUTCASST two-component system and detection kit was designed to alleviate this problem.
  
 
<center>
 
<center>
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<div id="popover-1" style="display: none;">
 
<div id="popover-1" style="display: none;">
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Binding of components with search-specific gRNA sequences.
+
First, guide RNA (gRNA) needs to be added, which is complementary to the DNA sequence you want to detect.
 
<br>
 
<br>
 
<br>
 
<br>
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<div id="popover-2" style="display: none;">
 
<div id="popover-2" style="display: none;">
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DNA sample fragment binds to one of the components.
+
dCas9 and dCpf1 will bind their corresponding gRNA.
 
<br>
 
<br>
 
<br>
 
<br>
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<div id="popover-3" style="display: none;">
 
<div id="popover-3" style="display: none;">
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Fragment binding with both components induces co-localization.
+
DNA from the sample that matches the gRNA will first bind to one of the proteins.
 
<br>
 
<br>
 
<br>
 
<br>
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<div id="popover-4" style="display: none;">
 
<div id="popover-4" style="display: none;">
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Protease cleaves, transcription factor is released from complex.
+
Once the DNA fragment binds the other protein, the system will co-localize. This allows the protease to release the transcription factor from the complex, resulting in an intracellular signal.
 
<br>
 
<br>
 
<br>
 
<br>
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<h2 class="subhead" id="subhead-3">The system</h2>
 
<h2 class="subhead" id="subhead-3">The system</h2>
−
The OUTCASST two-component system consists of two proteins that span the membrane.  
+
The OUTCASST two-component system consists of two synthetic receptors that span the membrane.  
 
One of the proteins has a Cas9 protein attached as an extracellular domain, the other has a Cpf1 protein attached.  
 
One of the proteins has a Cas9 protein attached as an extracellular domain, the other has a Cpf1 protein attached.  
 
Both proteins can be given a guide RNA that makes them bind to a specific, user-chosen, complementary sequence.  
 
Both proteins can be given a guide RNA that makes them bind to a specific, user-chosen, complementary sequence.  
−
When both proteins bind a single DNA fragment from a sample, possibly containing pathogen DNA, they co-localize, so that a protease releases a transcription factor which then induces an intracellular reporter mechanism, resulting in a stained or fluorescent cell.
+
When both proteins bind a single DNA fragment from a sample, possibly containing pathogen DNA, they co-localize, so that a protease releases a transcription factor which then induces an intracellular reporter mechanism such as a luminescent or fluorescent signal.
 +
<br><br>
 +
A final product would include the use of so-called anhydrobiotic insect <i>Polypedilum vanderplanki</i> cells, which can be air-dried, allowing them to be stored for prolonged periods of time at room temperature. The OUTCASST system is cheap to produce, store and ship, and requires nothing more then a simple microscope as a readout.
 
 
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<script type="text/javascript" language="JavaScript">
 
<script type="text/javascript" language="JavaScript">
 
function tut_goto(step)
 
function tut_goto(step)
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{
 
{
 
jQuery("#link-" + i).removeClass("selected");
 
jQuery("#link-" + i).removeClass("selected");
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jQuery("#link-" + i).removeClass("pulsing");
 
jQuery("#popover-" + i).dxPopover("hide");
 
jQuery("#popover-" + i).dxPopover("hide");
 
jQuery("#figure-" + i).fadeOut("5");
 
jQuery("#figure-" + i).fadeOut("5");
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{
 
{
 
jQuery("#link-" + i).removeClass("selected");
 
jQuery("#link-" + i).removeClass("selected");
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jQuery("#link-" + i).removeClass("pulsing");
 
jQuery("#popover-" + i).dxPopover("hide");
 
jQuery("#popover-" + i).dxPopover("hide");
 
jQuery("#figure-" + i).fadeOut("5");
 
jQuery("#figure-" + i).fadeOut("5");
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var title;
 
var title;
 
 
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if(i == 1)
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/*if(i == 1)
 
title = "Guide RNA";
 
title = "Guide RNA";
 
else if(i == 2)
 
else if(i == 2)
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else if(i == 3)
 
else if(i == 3)
 
title = "Signal transduction";
 
title = "Signal transduction";
 +
else if(i == 4)
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title = "Signal transduction";*/
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 +
if(i == 1)
 +
title = "Start";
 +
else if(i == 2)
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title = "gRNA binding";
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else if(i == 3)
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title = "DNA binding";
 
else if(i == 4)
 
else if(i == 4)
 
title = "Signal transduction";
 
title = "Signal transduction";
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<br><br>
 
<br><br>
 
Additionally, together with team Wageningen_UR a final experiment was done to verify that the protein in the medium was indeed secreted instead of due to involuntary cell lysis (see <a onclick="return change_page('collaborations', 1)" href="collaborations">Collaborations</a>).  
 
Additionally, together with team Wageningen_UR a final experiment was done to verify that the protein in the medium was indeed secreted instead of due to involuntary cell lysis (see <a onclick="return change_page('collaborations', 1)" href="collaborations">Collaborations</a>).  
−
This experiment was done in duplo, by members from both team Wageningen_UR and team Utrecht, individually, to provide independent verification of the result. This final experiment was done according to a collaboration protocol that was shared with the Wageningen_UR team [Experimental\Protocols\Wiki ready\Experimental\Protocols\Wiki ready.pdf].
+
This experiment was done in duplo, by members from both team Wageningen_UR and team Utrecht, individually, to provide independent verification of the result. This final experiment was done according to a collaboration protocol that was shared with the Wageningen_UR team <a target=_BLANK href="https://static.igem.org/mediawiki/2017/4/40/UuProtocolCollaborationWageningen.pdf" class="pdf pdf-inline"></a>.
 
<br><br>
 
<br><br>
 
<b>Endonuclease activity assay</b>
 
<b>Endonuclease activity assay</b>
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<br><br>
 
<br><br>
 
By comparing the two figures, we can now see that the probability of cleavage for the slow cleaver is much smaller than that of the fast cleaver in the timespan that the transient complex persists. Of course, the concentration of the substrate-mediated complex decreases over time, so the total cleavage decreases when it cleaves later. To investigate how much the transient and substrate-mediated complex contribute to signal development for both Protease Chain variants, we define:
 
By comparing the two figures, we can now see that the probability of cleavage for the slow cleaver is much smaller than that of the fast cleaver in the timespan that the transient complex persists. Of course, the concentration of the substrate-mediated complex decreases over time, so the total cleavage decreases when it cleaves later. To investigate how much the transient and substrate-mediated complex contribute to signal development for both Protease Chain variants, we define:
−
<br><br>
+
 
−
S'(t) = p_c (t)⋅C(t)⋅(1-∫_0^t p_c  dt)
+
<center><img height="75" src="https://static.igem.org/mediawiki/2017/b/b5/UuModelingEquation1.png"></center>
−
<br><br>
+
 
 
Wherein S’ is the increase in signal, given by the probability of cleavage (p<sub>c</sub>) for the remaining uncleaved complex. The remaining uncleaved complex is given by the remaining complex fraction (C) and how likely it is that it has not already been cleaved (one minus the integral of p<sub>c</sub> from 0 until that timepoint).
 
Wherein S’ is the increase in signal, given by the probability of cleavage (p<sub>c</sub>) for the remaining uncleaved complex. The remaining uncleaved complex is given by the remaining complex fraction (C) and how likely it is that it has not already been cleaved (one minus the integral of p<sub>c</sub> from 0 until that timepoint).
 
<br><br>
 
<br><br>
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<br><br>
 
<br><br>
 
From these relations, it is already clear that there can only be a stable signal potential, i.e. a stable fraction of the target chains remains uncleaved, when the production of target chain outweighs the decay and cleavage of it, whilst the acquisition of cleaved target chain is balanced by its decay, such that the following conditions apply:
 
From these relations, it is already clear that there can only be a stable signal potential, i.e. a stable fraction of the target chains remains uncleaved, when the production of target chain outweighs the decay and cleavage of it, whilst the acquisition of cleaved target chain is balanced by its decay, such that the following conditions apply:
−
<br><br>
+
<center><img height="50" src="https://static.igem.org/mediawiki/2017/9/91/UuModelingEquation2.png"></center>
−
p_T=d ([T]+[T:S]+[T:S:P])+k_5 [T:S:P]
+
<center><img height="45" src="https://static.igem.org/mediawiki/2017/e/e0/UuModelingEquation3.png"></center>
−
<br><br>
+
−
k_5 [T:S:P]=d([T_c]+[T_c:S]+[T_c:S:P])
+
−
<br><br>
+
 
Which together forms:
 
Which together forms:
−
<br><br>
+
<br>
−
p_T=d ([T]+[T:S]+[T:S:P]+[T_c]+[T_c:S]+[T_c:S:P])
+
<center><img height="45" src="https://static.igem.org/mediawiki/2017/9/90/UuModelingEquation4.png"></center>
−
<br><br>
+
<br>
 
However, the concentrations of the intermediary complexes is dependent on the concentration and hence production of protease chain P. We know that, at equilibrium concentrations, the following must hold:
 
However, the concentrations of the intermediary complexes is dependent on the concentration and hence production of protease chain P. We know that, at equilibrium concentrations, the following must hold:
 
<br><br>
 
<br><br>
−
p_P=d([P]+[P:S]+[T:S:P]+[T_c:S:P])
+
<center><img height="45" src="https://static.igem.org/mediawiki/2017/4/4b/UuModelingEquation5.png"></center>
−
<br><br>
+
<br>
 
By combining these equations, we can get an expression for T depending on the production, decay and complex concentrations:
 
By combining these equations, we can get an expression for T depending on the production, decay and complex concentrations:
 
<br><br>
 
<br><br>
−
[T]=p_T/p_P ([P]+[P:S]+(p_T/p_P -1)([T:S:P]+[T_c:S:P])-([T:S]+[T_c]+[T_c:S])
+
<center><img height="50" src="https://static.igem.org/mediawiki/2017/b/b9/UuModelingEquation6.png"></center>
−
<br><br>
+
<br>
 
By assuming that the DNA binding dynamics of the system occur at much faster timescales than protein production and decay, we can assume that the substrate binding of the protease and target chains is at steady state, yielding the following expressions:
 
By assuming that the DNA binding dynamics of the system occur at much faster timescales than protein production and decay, we can assume that the substrate binding of the protease and target chains is at steady state, yielding the following expressions:
 
<br><br>
 
<br><br>
−
[T:S] = (k_1  [S] [T] + k_4  [T:S:P])/(d + k_2  + k_3  [P])
+
<center><img height="75" src="https://static.igem.org/mediawiki/2017/0/0d/UuModelingEquation7.png"></center>
 +
<center><img height="75" src="https://static.igem.org/mediawiki/2017/1/19/UuModelingEquation8.png"></center>
 +
<center><img height="75" src="https://static.igem.org/mediawiki/2017/e/ee/UuModelingEquation9.png"></center>
 +
<br>
 +
We could then substitute these three concentrations for their expressions in the expression of the target chain concentration. Making further quasi steady state assumptions on the formation of the pre-cleavage and post-cleavage complexes reduces the expression by two more dependencies. This was done in mathematica notebook, found <a target=_BLANK href="https://static.igem.org/mediawiki/2017/2/21/UuModelingQSSAWorkouts.txt" class="url_external">here</a>.
 
<br><br>
 
<br><br>
−
[T_c:S] =  (k_1  [S] [T_c] + k_4  [T_c:S:P])/(d + k_2  + k_3  [P])
+
 
 +
The resulting expression shows that the concentration of target chain depends on: 1) The concentrations of its production relative to the production of the protease chain. 2) The concentration of protease chain. 3) The concentration of substrate. 4) How much cleaved target chain is available to trap said substrate.
 
<br><br>
 
<br><br>
−
[P:S]=(k_3  [P] [S] + k_2  [T_c:S:P] + k_2  [T:S:P])/(d + k_4  + k_1 ([T] + [Tc]))
+
The fraction of the total target chain that is cleaved is a saturation function that depends on substrate and protease chain concentrations with respect to how quickly the function's saturation point is attained. We can minimize the cleaved target chain fraction, and the occurrence of substrate trapping with it, by simply having a target chain amount that is much larger than that of the substrate.
 
<br><br>
 
<br><br>
−
We could then substitute these three concentrations for their expressions in the expression of the target chain concentration. Making further quasi steady state assumptions on the formation of the pre-cleavage and post-cleavage complexes reduces the expression by two more dependencies. This was done in mathematica notebook, found <a target=_BLANK href="https://static.igem.org/mediawiki/2017/2/21/UuModelingQSSAWorkouts.txt" class="url_external">here</a>.
+
In short, the more substrate there is available per target chain, the less signal per substrate molecule we can get as ineffectual target chain concentration increases.  
 
<br><br>
 
<br><br>
−
[INSERT WILL FOLLOW]
+
The equations suggest that there is a theoretical optimum for the production rates of both chains, relative to the substrate concentration in the system. Due to time constraints, the expression for this optimum could not be given. The methods given in the mathematica script provided here should be able to reach this solution, given enough time. The meaning of such an optimum, however, is questionable. As the substrate concentrations in our toolkit may differ greatly depending on severity of infection and chance, optimization through growth-rates would need to be different per sample. In conclusion, the only effective optimization of protein productions is to make sure that the protein concentrations greatly exceed the sample concentration of DNA sequence we wish to detect.
  
 
<br><br>
 
<br><br>
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<div style="position: absolute; bottom: 5px; left: 5px; right: 5px; color: white; font-size: 13px; line-height: 100%;">
 
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Marit de Wit<br>
 
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<span style="font-style: italic;">Doctors without borders</span>
 
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</div>
 
 
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<div class="page-heading">Integrated human practices: design of OUTCASST</div>
 
<div class="page-heading">Integrated human practices: design of OUTCASST</div>
 
Altogether, we gathered information from many different fields and perspectives. All of these views helped us to optimize our design to use OUTCASST as a tool for diagnosing Chagas disease. Since we want our tool to be easy to use in the field and rural areas, there are different aspects that should be taken into account. Robustness and resistance of the toolkit to temperature fluctuations and humidity are chief among these. In addition, it is important not to rely on material and storage containers such as fridges or freezers (Marit de Wit, Doctors without borders).  
 
Altogether, we gathered information from many different fields and perspectives. All of these views helped us to optimize our design to use OUTCASST as a tool for diagnosing Chagas disease. Since we want our tool to be easy to use in the field and rural areas, there are different aspects that should be taken into account. Robustness and resistance of the toolkit to temperature fluctuations and humidity are chief among these. In addition, it is important not to rely on material and storage containers such as fridges or freezers (Marit de Wit, Doctors without borders).  
 
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The OUTCASST toolkit consists of dried cells in a closed off compartment, two medium compartments (green) and a lysis and reset buffer compartment (purple).
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First, the seal on one of the medium compartments is broken so medium goes onto the cells. The cells will now be rejuvenated and allowed to acclimatize in 12 hours.
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After 12 hours, a patient's sample can be added to the test kit. The sample will enter the filtering compartment, which contains chemicals that bind all sorts of unwanted chemicals.
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The seal on the lysis buffer compartment is broken. The lysis buffer causes any intact cells to burst, releasing their DNA and internal contents. Unwanted cell debris is bound by the filter molecules, coated to the inside of the filtering compartment.
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The seal on the reset buffer compartment is broken. Reset buffer, sample and lysis buffer mingle, neutralizing each other and resulting in an isotonic mixture that will not harm the sensor cells.
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The second medium pocket is used to resuspend the gRNA. We kept the gRNA dry until now to prevent degradation of this sensitive chemical.
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The dissolved gRNA is released onto the sensor cells. The protein chains on the surface of these cells can now bind with the gRNA, making the sensor cells specific for DNA that is complementary to the gRNA they were provided with.
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The seal to the waste compartment is broken. As this compartment was under a slight vacuum, a part of the medium is sucked away from the cells, making room for the sample.
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The seal to the waste compartment is closed again and so are the seals to the medium pockets. The lysed and filtered sample, containing the patient's DNA, is now brought to the cells. If the right DNA sequence is present, the cells will detect it and give an output signal.
 +
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The tool should be cheap to produce and easy to use. To achieve this goal, the tool needs to have a closed box design wherein only the blood sample has to be added and a simple protocol can be followed to perform the test (Jet Bliek and Ruud van den Bogaard, Academical Medical Center Amsterdam: clinical genetics). Disposal of the system also needs to be considered (collaboration RIVM National Insitute for Public Health and the Environment).
 
The tool should be cheap to produce and easy to use. To achieve this goal, the tool needs to have a closed box design wherein only the blood sample has to be added and a simple protocol can be followed to perform the test (Jet Bliek and Ruud van den Bogaard, Academical Medical Center Amsterdam: clinical genetics). Disposal of the system also needs to be considered (collaboration RIVM National Insitute for Public Health and the Environment).
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Science can have an impact on the world in many ways. With our project, we are not only trying to make a difference by creating a diagnostic tool, but by reaching out to the public we hope to make science accessible for everyone as well. We tried to achieve this by collaborating with ‘de Kennis van Nu’, a platform of the Dutch national public broadcasting corporation that brings different scientific themes to the general public in an understandable way. They aim to make science accessible to everyone, old and young, and encourage everyone to be curious and bring out the scientist in themselves!  
+
Science impacts the world in many ways. With our project, we are not only aiming to make a difference by creating a diagnostic tool, but also to reach out to the public to create awareness and make science accessible for everyone. We collaborated with ‘de Kennis van Nu’, a well-known national TV program and internet platform that brings different scientific themes to the general public in an understandable way. They aim to make science accessible to everyone, old and young, and encourage everyone to be curious and bring out the scientist in themselves!  
 
On their platform, we explain the formation of Utrecht’s very first team, our design and how we are trying to solve healthcare problems.  
 
On their platform, we explain the formation of Utrecht’s very first team, our design and how we are trying to solve healthcare problems.  
 
Through our whole iGEM experience, they follow us from lab bench to Boston. Their special about our team can be found <a target=_BLANK href="https://dekennisvannu.nl/site/special/iGEM-2017-studenten-ontwerpen-nieuw-leven/111#!/" class="url_external">here</a>.
 
Through our whole iGEM experience, they follow us from lab bench to Boston. Their special about our team can be found <a target=_BLANK href="https://dekennisvannu.nl/site/special/iGEM-2017-studenten-ontwerpen-nieuw-leven/111#!/" class="url_external">here</a>.
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Latest revision as of 00:24, 15 December 2017

<!DOCTYPE html>

  • Home
  • Experimental
  • Human practices
  • Team & Sponsors
Cas9 & Cpf1 secretion
and activity
Comparison of endonuclease activity for Cas9 and Cpf1 that has been produced in, and excreted by, HEK293 cells.
MESA two-component system replication
Details on the MESA two-component system, explanation of its relation to our design and the results of its reproduction.
OUTCASST system production
Detailed explanation of the OUTCASST mechanism, experimental progress and technical prospects.
Modeling and
mathematics
Ordinary differential equations, cellular automaton and an object based model for optimal linker-length estimation.
InterLab study participation
Results and details of our measurements for the iGEM 2017 InterLab Study.
Stakeholders & opinions
Interviews and dialogues with stakeholders, potential users, third parties and experts relating to pathogen detection or DNA-based diagnostics.
Risks & safety-issues
Implications and design considerations relating to safety in the usage and implementation of OUTCASST as a diagnostics tool.
Design & integration
OUTCASST toolkit and product design with factors such as bio-safety and user-friendliness taken into account.
Outreach
Videos we made for the dutch public, together with 'de Kennis van Nu'.
Meet our team
About us, our interests and roles in the team and our supervisors.
Sponsors
A listing of our sponsors, how they assisted us and our gratitude for their assistance.
Collaborations
Read about our exchanges with other iGEM teams and government agencies.
Achievements
A short description of all that we have achieved during our participation in the iGEM.
Attributions
A thank-you for everyone that assited us, both in and outside the lab.
Intro
The problem
The system