Difference between revisions of "Team:Munich/Hardware"

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We need to find an equation to choose an optimal resistor <i>R<sub>ref</sub></i> . We want a maximum change of <i>U<sub>LDR</sub></i> for a certain detection range of <i>R<sub>LDR</sub></i>. Therefore <a href="#equation5">equation 5</a> is solved for <i>U<sub>LDR</sub></i> giving
 
We need to find an equation to choose an optimal resistor <i>R<sub>ref</sub></i> . We want a maximum change of <i>U<sub>LDR</sub></i> for a certain detection range of <i>R<sub>LDR</sub></i>. Therefore <a href="#equation5">equation 5</a> is solved for <i>U<sub>LDR</sub></i> giving
 
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<div class="equationDiv"><img class="largeEquation" src="https://static.igem.org/mediawiki/2017/3/3f/T--Munich--Hardware_equation6.png"><span>(6)</span></div>
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<p>
 
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The change ∆<i>U<sub>LDR</sub></i> of <i>U<sub>LDR</sub></i> between a maximum value <i>R<sub>max</sub></i> and a minimum value <i>R<sub>min</sub></i> of <i>R<sub>LDR</sub></i> is
 
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<p>
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We wanted to start our project by showing that Cas13a's collateral activity could be used to detect the presence of specific RNA. For this, we used the RNAse alert system, as done in a recent publication<sup><a class="myLink" href="#ref_11">11</a></sup>, to detect RNA digestion. In this assay, the presence of RNAse-like activity is detected by an increase in green fluorescence. Our experiments yielded a convincing proof-of-principle which we went on to model. Moreover, CascAID can be used to detect a wide spectrum of pathogens, as our experiments with gram-positive and viral targets suggested. As we wanted to make CascAID available for everyone, we focused on building an inexpensive fluorescence detector to measure the presence of the target. Our detector “Lightbringer” was designed to be able to detect the fluorescence produced by the fluorescein in the Rnase alert system<sup><a class="myLink" href="#ref_12">12</a></sup>, but we theorize that changing the filters allows detection of other fluorophores. In addition, we experimented with freeze-drying on paper to make CascAID durable and easily portable.
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<div class="equationDiv"><img class="largeEquation" src="https://static.igem.org/mediawiki/2017/9/9b/T--Munich--Hardware_equation7.png"><span>(7)</span></div>
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<p>
<img src="https://static.igem.org/mediawiki/2017/7/7f/T--Munich--Description_Cas13a_Readout_Comparision.svg">
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which has a maximum for
<p>Cas13a can be used to detect specific RNA sequences</p>
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<td align=center valign=center colspan=2>
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<a href="http://www.uni-muenchen.de/studium/lehre_at_lmu/index.html"><img src="https://static.igem.org/mediawiki/2017/9/9a/T--Munich--Logo_LehreLMU.gif" width="200"></a>
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<p>Picture of the Thermocycler</p>
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<td align=center valign=center colspan=4>
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<p>
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For RNA extraction from the samples we tested three methods: extraction with silica beads, extraction with silica membrane and heat lysis. We custom-built an affordable thermocycler for signal amplification by RT-PCR to improve the detection limit. We explored recombinase polymerase amplification (RPA), an isothermal amplification procedure, to use over more conventional PCR methods as its simplicity makes it the more attractive option.
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We expect an <i>R<sub>max</sub></i> of approximately 2 and an <i>R<sub>min</sub></i> of approximately 1 MΩ. By using <a href="#equation8">equation 8</a> as a guideline we choose <i>R<sub>ref</sub></i> to be 1.5 .
 
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<tr><td colspan=6 align=center valign=center>
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<h3>Colorimetric read-outs</h3>
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<p>
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To couple CascAID with an easy read-out method we explored three colorimetric read-outs:
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</p>
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<p> 
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<b>AeBlue</b>: The RNA strand in a specially designed RNA/DNA dimer is cut by Cas13a's collateral
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activity. After digestion, the interaction between the two strands is too weak to hold the dimer and it
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decays. We can then use the DNA-strand as template to translate the chromoprotein <a href="http://parts.igem.org/Part:BBa_K864401">aeBlue</a>.
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<td colspan=4 align=center valign=center>
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<img src="https://static.igem.org/mediawiki/2017/9/90/T--Munich--Description_aeBlue.svg">
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<p>Diagram of aeBlue</p>
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<p> 
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<b>Intein-Extein</b>: By binding TEV-protease with a RNA-linker we can use Cas13a's collateral activity
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to regulate the protease's diffusion and use it to cleave a TEV tag separating the intein regions of a
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modified chromophore. After the first cleavage, the intein segment excises itself<sup><a class="myLink" href="#13">13</a></sup>, bringing together the
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halves of the chromophore. Only then is the chromophore functional and produces the colorimetric
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read-out.
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</p>
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<td colspan=4 align=center valign=center>
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<a href="http://www.uni-muenchen.de/studium/lehre_at_lmu/index.html"><img src="https://static.igem.org/mediawiki/2017/9/9a/T--Munich--Logo_LehreLMU.gif" width="200"></a>
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<p>Diagram of Intein-Extein</p>
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<p> 
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<b>Gold nanoparticles</b>: Gold nanoparticles coated with short DNA sequences are held closely
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together by a complementary linker RNA, which makes the solution intense blue<sup><a class="myLink" href="#14">14</a></sup>. Activated Cas13a cuts
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the linker RNA, causing the nanoparticles to diffuse away from each other. This increase in distance
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causes a color change to intense red.
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</p>
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<td colspan=4 align=center valign=center>
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<img src="https://static.igem.org/mediawiki/2017/b/b3/T--Munich--Description_Goldnanoparticles.svg">
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<p>Gold nanoparticles</p>
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</td>
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<h3>Software</h3>
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<p> 
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To help facilitate the design of crRNA, the sequences that give CascAID its specificity, we developed a
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software tool that checks crRNA for unwanted secondary structures. This gives valuable insight on
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whether the sequence is suited to use with Cas13a or whether some modifications are needed.
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Together with Team Delft's software tool which designs the corresponding crRNA based on the target,
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we collaborated to develop a powerful tool that suggests crRNA sequences and checks their usability
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</p>
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<h3>References</h3>
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<p>
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    <ol style="text-align: left">
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      <li id="ref_1">Cohen, Limor, and David R. Walt. "Single-Molecule Arrays for Protein and Nucleic Acid Analysis." Annual Review of Analytical Chemistry 0 (2017).</li>
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      <li id="ref_2">Nakano, Michihiko, et al. "Single-molecule PCR using water-in-oil emulsion." Journal of biotechnology 102.2 (2003): 117-124.</li>
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      <li id="ref_3">Taniguchi, Yuichi, et al. "Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells." science 329.5991 (2010): 533-538.</li>
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      <li id="ref_4">Rissin, David M., et al. "Single-molecule enzyme-linked immunosorbent assay detects serum proteins at subfemtomolar concentrations." Nature biotechnology 28.6 (2010): 595-599.</li>
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      <li id="ref_5">Pardee, Keith, et al. "Rapid, low-cost detection of Zika virus using programmable biomolecular components." Cell 165.5 (2016): 1255-1266.</li>
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      <li id="ref_6">Slomovic, Shimyn, Keith Pardee, and James J. Collins. "Synthetic biology devices for in vitro and in vivo diagnostics." Proceedings of the National Academy of Sciences 112.47 (2015): 14429-14435.</li>
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      <li id="ref_7">Tang, Ruihua, et al. "A fully disposable and integrated paper-based device for nucleic acid extraction, amplification and detection." Lab on a Chip 17.7 (2017): 1270-1279.</li>
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      <li id="ref_8">Vashist, Sandeep Kumar, et al. "Emerging technologies for next-generation point-of-care testing." Trends in biotechnology 33.11 (2015): 692-705.</li>
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      <li id="ref_9">Gubala, Vladimir, et al. "Point of care diagnostics: status and future." Analytical chemistry 84.2 (2011): 487-515.</li>
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      <li id="ref_10">Abudayyeh, Omar O., et al. "C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector." Science 353.6299 (2016): aaf5573.</li>
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      <li id="ref_11">Gootenberg, Jonathan S., et al. "Nucleic acid detection with CRISPR-Cas13a/C2c2." Science (2017): eaam9321.</li>
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      <li id="ref_12">https://www.idtdna.com/pages/docs/technical-reports/in_vitro_nuclease_detectionD325FDB69855.pdf (retrieved: 13.10.17)</li>
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      <li id="ref_13"> Anraku, Yasuhiro, Ryuta Mizutani, and Yoshinori Satow. "Protein splicing: its discovery and structural insight into novel chemical mechanisms." IUBMB life 57.8 (2005): 563-574.</li>
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      <li id="ref_14">Link, Stephan, and Mostafa A. El-Sayed. "Size and temperature dependence of the plasmon absorption of colloidal gold nanoparticles." The Journal of Physical Chemistry B 103.21 (1999): 4212-4217.</li>
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    </ol>
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Revision as of 09:56, 19 October 2017


Hardware

Our pathogen detection approach relies on Cas13a digesting RNA. A common way of monitoring RNase activityis using commercially available RNaseAlert consisting of a fluorescent RNA beacon. This is impractical for in-fieldapplications because commercial fluorescence detectors are expensive and inconveniently large. We therefore makeour pathogen detection system fit for in-field applications by developing a cheap and handy fluorescence detector. Al-though many previous iGEM teams constructed fluorescence detectors, we could not find any that had a high enoughsensitivity or the ability to measure fluorescence quantitatively. We therefore constructed a detector matching ourrequirements and compared it to others in a cost vs sensitivity diagram.

Our detector is paper-based and can detect fluorescein concentrations down to 200 nM. The detector is able to automatically measure fluorescence in units of equivalent fluorescein concentrations. It fits in a pipette box and costs less than 15 $. We were able to measure a time trace of Cas13a digesting RNaseAlert with our detector. For comparison we also measured a positive control containing RNase A and a negative control containing only RNaseAlert. The data are displayed in the figure bellow.

The time traces show an enzymatic reaction taking place on filter paper. This proves that our detector is sensitive enough and meets our requirements. However the detector is not limited to our specific application but can be used for the detection of any fluorescence signal in biological or chemical systems. We therefore think that our detector can benefit other iGEM teams and research groups that want to make fluorescence based detection fit for in-field applications.

Overall Design

Light from a blue LED is filtered by a blue filter foil and excites fluorophores on a filter paper. The excitation light is blocked by an orange filter foil while the emission light from the fluoroscopes passes through the orange filter foil and illuminates a light dependent resistor (LDR). The LDR changes its resistance corresponding to the intensity of the fluorescence light.Finally an Arduino Nano measures the resistance via a voltage divider and calculates the fluorophore concentration. The two figures bellow show this overall design and the operational detector.

Components

Micro Controller

We used an Arduino Nano for automatized data collection. This micro controller has analog pins that can measure voltages from 0 to 5 V and gives an integer from 0 to 1023 as output. The micro controller is connected via an USB port with a computer or smart-phone where the data can be processed further.

Light dependent resistor (LDR)

For the detection of fluorescence light we used a light depending resistor (LDR). A LDR decreases its resistance RLDR with increasing light intensity I. The dependence of the resistance RLDR on the light intensity I is

(1)

where γ is a parameter depending on the type of resistor being used and can even differ for LDRs with the same type designation.

Equation 1 is motivated from the equation

(2)

which is given in the data sheet of the LDR. The denominator is the decadic logarithm of the fraction of two light intensities of 100 Lx and 10 Lx. R10 and R100 are the corresponding resistances at these light intensities. The used resistor with the type designation GL5516 NT00183 has a parameter γ of 0.8.

The response of a LDR depends on the wavelength λ of the incoming light. The data sheet provides information on the relative response normalized to the maximal response. The relative response is maximum for a wavelength of 540 nm and is therefore appropriate for detection of green fluorophores.

Circuit for resistance measurements

A voltage divider as shown in the figure bellow is the simplest way to measure resistance.

Applying Kirchhoff’s laws we get

(3)

and

(4)

RLDR and ULDR are the resistance and voltage drop at the LDR. Rref and Uref are the resistance and voltage drop at a reference resistor. U0 is the supply voltage which we choose to be 5V. This gives

(5)

an equation to calculate RLDR from ULDR, which can be measured with the micro controller.

We need to find an equation to choose an optimal resistor Rref . We want a maximum change of ULDR for a certain detection range of RLDR. Therefore equation 5 is solved for ULDR giving

(6)

The change ∆ULDR of ULDR between a maximum value Rmax and a minimum value Rmin of RLDR is

(7)

which has a maximum for

We expect an Rmax of approximately 2 MΩ and an Rmin of approximately 1 MΩ. By using equation 8 as a guideline we choose Rref to be 1.5 MΩ.