Difference between revisions of "Team:Uppsala/InterLab"

 
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                 <li class="toclevel tocsection"><a href="#Project_Description" class="scroll"> <span id="whereYouAre"> Project Description  </span> </a>
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                 <li class="toclevel tocsection"><a href="#Project_Description" class="scroll"> <span id="whereYouAre"> InterLab </span> </a>
 
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                             <li class="toclevel nav-item active"><a href="#top" class="nav-link scroll"> Overview </a></li>
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                             <li class="toclevel nav-item active"><a href="#Pur" class="nav-link scroll"> Purpose</a></li>
                             <li class="toclevel nav-item"><a href="#Problem" class="nav-link scroll">  Problem  </a></li>
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                             <li class="toclevel nav-item"><a href="#Inter" class="nav-link scroll">  InterLab Study 2018</a></li>
                             <li class="toclevel nav-item"><a href="#Solution" class="nav-link scroll">  Solution </a></li>
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                             <li class="toclevel nav-item"><a href="#Mat" class="nav-link scroll">  Materials and Methods </a></li>
                             <li class="toclevel nav-item"><a href="#References" class="nav-link scroll"> References </a></li>
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                             <li class="toclevel nav-item"><a href="#Exp" class="nav-link scroll"> Our Experience with the InterLab</a></li>
 
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  <h1>Purpose</h1>
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  <h1 style="margin-top: 0px;" id="Pur">Purpose</h1>
  
 
   <p>Synthetic biology is an emerging and constantly developing field which holds great promise to solve major problems humanity is facing today in terms of biology related medicine. In order to make use of this potential it is very important to reduce measurement variability and ensure there are standards in the field. To contribute towards this, our team has taken part in the iGEM interlab study, which has the noble goal of identifying and correcting the sources of systematic variability in synthetic biology measurement.<br><br>  
 
   <p>Synthetic biology is an emerging and constantly developing field which holds great promise to solve major problems humanity is facing today in terms of biology related medicine. In order to make use of this potential it is very important to reduce measurement variability and ensure there are standards in the field. To contribute towards this, our team has taken part in the iGEM interlab study, which has the noble goal of identifying and correcting the sources of systematic variability in synthetic biology measurement.<br><br>  
  
iGEM has in previous interlab studies showed that it is possible to reduce the variability in measurements between labs by measuring GFP expression in absolute fluorescence units which are calibrated against a known concentration of a chromoprotein. However, there is still a large source of variability in such measurements depending on the number of cells in the sample. By dividing the total fluorescence by the number of cells we can determine the mean expression level of GFP per cell. Usually, computing the optical density (OD) of the sample gets you an approximation of the number of cells present. OD measurements are however subject to high variability between labs due to spectrophotometer calibrations and is therefore not a precise approximation method. By instead using the direct method of cell count in each sample, one can remove this source of variability in measurements.  
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iGEM has in previous interlab studies showed that it is possible to reduce the variability in measurements between labs by measuring GFP expression in absolute fluorescence units which are calibrated against a known concentration of a fluorescent protein. However, there is still a large source of variability in such measurements depending on the number of cells in the sample. By dividing the total fluorescence by the number of cells we can determine the mean expression level of GFP per cell. Usually, computing the optical density (OD) of the sample gets you an approximation of the number of cells present. OD measurements are however subject to high variability between labs due to spectrophotometer calibrations and is therefore not a precise approximation method. By instead using the direct method of cell count in each sample, one can remove this source of variability in measurements.  
 
</p>
 
</p>
  
  <h1>InterLab Study 2018</h1>
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  <h1 id="Inter">InterLab Study 2018</h1>
  
 
<p>By comparing how much the following methods agree with each other we can investigate if by using one approach or both, can help to reduce the variability in measurements between different labs. </p>
 
<p>By comparing how much the following methods agree with each other we can investigate if by using one approach or both, can help to reduce the variability in measurements between different labs. </p>
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  <h2>Conversion Between Absorbance of Cells to Absorbance of a Known Concentration of Beads</h2>
 
  <h2>Conversion Between Absorbance of Cells to Absorbance of a Known Concentration of Beads</h2>
  
   <p>By measuring the scattered light from a known concentration of silica beads that are roughly the same size and shape as a normal  <i>E.coli</i> cells we converted each lab’s absorbance measurement into a standard “equivalent concentration of beads” measurement</p>
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   <p>By measuring the scattered light from a known concentration of silica beads that are roughly the same size and shape as a normal  <i>E.coli</i> cells we converted each lab's absorbance measurement into a standard “equivalent concentration of beads” measurement.</p>
  
 
  <h2>Counting Colony-Forming Units (CFUs) from the Sample</h2>
 
  <h2>Counting Colony-Forming Units (CFUs) from the Sample</h2>
  
   <p>By spreading a known concentration of cells in liquid media on a plate to see how many colonies grow, we can determine the cell concentration of the sample as a whole since each colony should grow from one single cell. We determined the number of CFUs in negative and positive control samples to compute a conversion factor from absorbance to CFU. </p>
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   <p>By spreading a known concentration of cells in liquid media on a plate to see how many colonies that grow, we can determine the cell concentration of the sample as a whole since each colony should grow from one single cell. We determined the number of CFUs in negative and positive control samples to compute a conversion factor from absorbance to CFU. </p>
  
  
  <h1>Material and Methods</h1>
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  <h1 id="Mat">Material and Methods</h1>
  
 
  <h2>Conversion Between Absorbance of Cells to Absorbance of a Known Concentration of Beads</h2>
 
  <h2>Conversion Between Absorbance of Cells to Absorbance of a Known Concentration of Beads</h2>
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                            <p><strong>Figure 1:</strong> Fluorescein standard curve based on measured values of fluorescein in serial dilution. Fluorescence intensity was measured with TECAN infinite M200. </p>
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                                <p><strong>Figure 1.</strong> Fluorescein standard curve based on measured values of fluorescein in serial dilution. Fluorescence intensity was measured with TECAN infinite M200. </p>
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                                <p><strong>Figure 2.</strong> Particle standard curve based on measured absorbance of serial diluted samples of silica beads at a wavelength of 600.  
 
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                            <p><strong>Figure 2:</strong> Particle standard curve based on measured absorbance of serial diluted samples of silica beads at a wavelength of 600.  
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                                 <p><strong>Figure 3:</strong> Transformation plates containing plasmids with different inserts, from the upper right to lower left: Test Device 4, Colony 2; Test Device 3, Colony 2; Test Device 1, Colony 2; Test Device 2, Colony 2.</p>
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                                 <p><strong>Figure 3.</strong> Transformation plates containing plasmids with different inserts, from the upper right to lower left: Test Device 4, Colony 2; Test Device 3, Colony 2; Test Device 1, Colony 2; Test Device 2, Colony 2.</p>
 
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                                 <p><strong>Figure 4:</strong> Transformation plates containing plasmids with different inserts, from the right to left: Test Device 5, Colony 2; Test Device 6, Colony 2. </p>  
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                                 <p><strong>Figure 4.</strong> Transformation plates containing plasmids with different inserts, from the right to left: Test Device 5, Colony 2; Test Device 6, Colony 2. </p>  
 
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<br><p> All plates were placed under a UV-light to confirm expression of GFP before picking colonies for inoculation. Fluorescent expression can be clearly distinguished from the expected cell culture, see <strong>figure 3</strong> and <strong>figure 4</strong>.</p>
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<br><p> All plates were placed under a UV-light (312 nm) to confirm expression of GFP before picking colonies for inoculation. Fluorescent expression can be clearly distinguished from the expected cell culture, see figure 3 and figure 4.</p>
  
  
 
<h2>Method for Counting Colony-Forming Units (CFUs) from the Sample</h2>  
 
<h2>Method for Counting Colony-Forming Units (CFUs) from the Sample</h2>  
  
<p>To determine the CFU count, we counted colonies from two positive control (<a  href="http://parts.igem.org/Part:BBa_I20270"><strong>BBa_I20270</strong></a>) plates and two negative control (<a  href="http://parts.igem.org/Part:BBa_R0040"><strong>BBa_R0040</strong></a>) plates. The OD values of the liquid cultures of the four samples were measured and diluted in triplicates to OD = 0.1 in 1 mL of LB + Cam media. Each diluted sample was further diluted in series where samples with dilution factor 8 x 10<sup>-3</sup>, 8 x 10<sup>-4</sup> and 8 x 10<sup>-5</sup> was plated on LB + Cam plates.<br><br>  
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<p>To determine the CFU count, we counted colonies from two positive control (<a  href="http://parts.igem.org/Part:BBa_I20270"><strong>BBa_I20270</strong></a>) plates and two negative control (<a  href="http://parts.igem.org/Part:BBa_R0040"><strong>BBa_R0040</strong></a>) plates. The OD values of the liquid cultures of the four samples were measured and diluted in triplicates to OD = 0.1 in 1 mL of LB + Cam media. Each diluted sample was further diluted in series where samples with dilution factor 8 x 10<sup>-3</sup>, 8 x 10<sup>-4</sup> and 8 x 10<sup>-5</sup> were streaked on LB + Cam plates.<br><br>  
  
After Incubation at 37°C for 17 hours the colonies on the plates were counted. Based on the assumption that 1 bacterial cell gives rise to 1 colony, CFU per 1 mL of an OD = 0.1 was calculated by the formula:  
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After incubation at 37°C for 17 hours the colonies on the plates were counted. Based on the assumption that 1 bacterial cell gives rise to 1 colony, CFU per 1 mL of an OD = 0.1 was calculated by the formula:  
 
  #colonies x Final Dilution Factor = CFU/mL</p>
 
  #colonies x Final Dilution Factor = CFU/mL</p>
  
  
<h1>Our Experience with the InterLab Study</h1>
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<h1 id="Exp">Our Experience with the InterLab Study</h1>
  
 
<p>The interlab is an excellent opportunity to practice cell transformations and streaking of plates. It was also very useful for us since we became more familiar with the iGEM kit plates and how to use the DNA provided in the starting kit. In addition we learned a lot from using the plate reader and the different calibrations, we gathered experience that became useful in other parts of our project.<br><br>  
 
<p>The interlab is an excellent opportunity to practice cell transformations and streaking of plates. It was also very useful for us since we became more familiar with the iGEM kit plates and how to use the DNA provided in the starting kit. In addition we learned a lot from using the plate reader and the different calibrations, we gathered experience that became useful in other parts of our project.<br><br>  

Latest revision as of 14:18, 3 December 2018