Difference between revisions of "Team:DTU-Denmark/Design Measurement"

 
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<img src="https://static.igem.org/mediawiki/2019/9/99/T--DTU-Denmark--designmeasurement.svg" title="Illustrates a rack of test tubes with liquid of different colors" style="margin-top:75px;max-width:70%;margin-right:auto; margin-left:auto;display: block;
 
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<h2>Measurement Design</h2>
 
<h2>Measurement Design</h2>
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<h2>Measuring promoters</h2>
 
<h2>Measuring promoters</h2>
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<h2>Choice of fluorescent protein</h2>
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<p>For testing the synthetic promoters, the red fluorescent protein <a href=”http://parts.igem.org/Part:BBa_J06504” target=”_blank”>mCherry</a> was chosen as the fluorescent reporter. mCherry was used for a number of reasons, including:
 +
<ol>
 +
<li>mCherry has been proven to work both in <i>E.coli</i> and filamentous fungi. This enables our test device to be used for screening for correct insertion of synthetic promoters in <i>E.coli</i>, as the expression of mCherry can be seen with the naked eye.</li>
 +
<li>Compared to mRFP such as [part number for J04450], the maturation time is short, which is beneficial when analysing the promoter dynamics.[2] </li>
 +
<li>Compared to mRFP, mCherry does not have a peak in absorbance around 500 nm. For mRFP, this peak means that it would absorb part of the signal from GFP, thus obscuring the result if we are to introduce a double fluorescence calibration system as described in <a href=”https://2019.igem.org/Team:DTU-Denmark/Design_Plasmid#FutureDesign” target=”_blank”>Future design</a> and the figure below. </li>
 +
<li>Fluorescence standards such as TexasRed are easy to obtain, and have a nice overlap in spectra with mCherry. Furthermore, the iGEM measurement committee has also <a href=”https://2019.igem.org/Measurement/Resources#fluor_proteins”>recommended the use of TexasRed</a> as a chemical standard for mCherry.</li>
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</ol>
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<figure>
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<img style="padding:28px;width:100%" src="https://static.igem.org/mediawiki/2019/c/c1/T--DTU-Denmark--NewDesignDataRFP.svg" alt="The figure shows three curves visualising the exitation levels for mRFP1, mCherry EX, and moxGFP EM. mRFP1 and mCherry EX mostly overlap but while mCherry EX only peaks around 580 nm, mRFP additionally peaks around 500nm which overlaps with the moxGFP EM peak." class=""/>
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<figcaption>Standard curves to interpolate our fluorescence data into a known concentration of a fluorescence standard is easily obtained using TexasRed (Sulforhodamine 101) [3]</figcaption>
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<h2>A secondary fluorescent protein: moxGFP</h2>
 +
<p>Plans were made to incorporate a second fluorescent reporter in our test design in order to create an internal standard for promoter tests. For this internal standard, we needed a fluorescent reporter that would have an emission/excitation spectrum that did not overlap with that of our red fluorescent protein of choice, mCherry. Though our initial design planned to use eGFP as a reporter for the internal standard, we eventually found a new GFP variant suiting our needs but it was not yet present in the Parts Registry. The moxGFP variant of GFP has increased redox stability, faster maturation time, and is monomeric [4], qualities we are interested in having, in order to minimize sources of error when expressing the protein in a variety of organisms. </p>
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<figure>
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<img src="https://static.igem.org/mediawiki/parts/5/52/T--DTU-Denmark--mCherry_no_tag.png" style="width: 100%; padding: 15px;" >
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<figcaption> This figure shows that secretion tag (<a href="http://parts.igem.org/Part:BBa_K3046019" target="_blank">BBa_K3046019</a>) attached to mCherry (<a href="http://parts.igem.org/Part:BBa_J06504" target="_blank">J06504</a>) is predicted to be transported out of the cell by DeepLoc-1.0.
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<h2>Comming soon</h2>
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<h2>Protein secretion</h2>
<p>Text will also be comming soon</a>.
+
<p>As previously mentioned, there are advantages associated with using β-glucuronidase (GUS) as a reporter, such as it being secreted into the extracellular environment, something that can ease protein purification and assaying of promoter activity. As we are using a fluorescent protein we do not have this advantage, but this can be mediated by adding a secretion tag to our mCherry part. We hypothesize that this would enable our mCherry protein to be secreted into the extracellular environment.
 +
<br><br>
 +
The secretion tag was identified via a query on UniProt.org, targeting proteins from <i>A. niger</i> with a signal peptide annotation. A list of signal peptides was produced by identifying enzymes commonly secreted in large quantities by <i>A. niger</i>, and their signal peptide sequences were attached to the N-terminal end of an mCherry peptide sequence. These fusion sequences were subsequently analyzed with SignalP-5.0[5] and DeepLoc.[6] The SignalP-5.0 algorithm predicts the presence of signal peptides in the query peptides and suggests the position for their respective cleavage sites. In addition, it scores the likelihood of cleavage from the suggested cleavage site. The DeepLoc algorithm predicts the subcellular localization of the query peptide in a eukaryotic cell and it can therefore be used to score the likelihood of secretion.
 +
Combined, these bioinformatic tools revealed that the GlaA signal peptide is the most efficient in terms of targeting mCherry to the secretory pathway and thus secreting the protein to the extracellular environment as seen in the figures below.
 +
</a>.
  
 
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<img src="https://static.igem.org/mediawiki/2019/d/d8/T--DTU-Denmark--commingsoon.png" class="safetyfirstimg"/>
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<figure>
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<img src="https://static.igem.org/mediawiki/parts/5/52/T--DTU-Denmark--mCherry_no_tag.png" style="width: 100%; padding: 15px;" >
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<figcaption> This figure shows that secretion tag (<a href="http://parts.igem.org/Part:BBa_K3046019" target="_blank">BBa_K3046019</a>) attached to mCherry (<a href="http://parts.igem.org/Part:BBa_J06504" target="_blank">J06504</a>) is predicted to be transported out of the cell by DeepLoc-1.0.
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<h2>coming soon</h2>
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<h2>Choice of strain</h2>
<p>more text coming soon</p>
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<p>For the entirety of the project, we have been using two specific <i>Aspergillus niger</i> ATCC 1015 strains, the first of which is NIG96 (ATCC1015; <i>pyrG1</i>, <i>kusAΔ</i>). This specific strain offers two desirable qualities; first, the strain is auxotrophic for uridine, we can use the <i>pyrG</i> gene as our marker to select for successful transformations, and second, the <i>kusA</i> deletion greatly improves the efficiency of gene insertions into the genome. [7,8]
 +
<br><br>
 +
We have also been using a protease deficient version of the NIG96 strain that contains an inactivated <i>prtT</i> transcription factor. [9] This strain therefore lacks many of the endogenous proteases normally secreted by <i>A. niger</i>, and will hopefully prevent much of the unwanted digestion of our fluorescent protein which would result in a more accurate reading of our fluorescent protein.
 +
 
 +
</p>
  
  
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<h2>Normalizing data for growth</h2>
 +
<p>When cultivating biological samples in different scales, we need some way of standardizing the data in order to be able to compare results between experiments. The first method used to achieve this is using a Bradford assay to measure the total protein concentration in the biomass samples. This was done along with the fluorescence measurements for the purified proteins in order to obtain a standardized quantity of fluorescence per protein. This allows us to compare the different samples, even if one fungus grows faster than the others, if different amounts of spores were used for inoculation, or some other minor factor that would obfuscate the underlying relative promoter expression.<br>
 +
 
 +
We have also measured the growth of our fungi in multiple different ways for each of the three scales, in which we have been cultivating our fungal cultures. In the Biolector, we had continuous measurements of “Light Scattering Units”, which can give an estimate of biomass. Next, in the shake flasks we did not have direct access to biomass measurements and thus, we resorted to determining the amount of residual glucose in the media in order to correlate it to biomass growth. Lastly, in the bioreactor, we had access to analysis of the off-gas, thus giving us a measurement of respiration, which is correlated with growth.
 +
<br><br>
 +
Combining all of the above allows for understanding in greater detail how our promoters work and it also enables us to compare different promoters across different experiments, which is of utmost importance when characterizing new parts.
  
<h2>Comming soon</h2>
 
<p>Text will also be comming soon</a>.
 
  
 
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Sources here will also come soon</p>
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[1] K. Ozeki, A. Kanda, M. Hamachi, and Y. Nunokawa, “Construction of a promoter probe vector autonomously maintained in aspergillus and characterization of promoter regions derived from A. niger and A. oryzae Genomes,” Biosci. Biotechnol. Biochem., vol. 60, no. 3, pp. 383–389, 1996.
 +
<br>
 +
[2] E. Balleza, J. M. Kim, and P. Cluzel, “Systematic characterization of maturation time of fluorescent proteins in living cells,” Nat Methods, vol. 15, no. 1, pp. 47–51, 2018.
 +
<br>
 +
[3] T. J. Lambert, “FPbase: a community-editable fluorescent protein database,” Nat. Methods, vol. 16, no. 4, pp. 277–278, 2019.
 +
<br>
 +
[4] L. M. Constantini et al., “A palette of fluorescent proteins optimized for diverse cellular environments,” Nat Commun, vol. 6, no. 1, p. 8670, 2015.
 +
<br>
 +
[5] http://www.cbs.dtu.dk/services/SignalP/, last accessed 20th October 2019
 +
<br>
 +
[6] http://www.cbs.dtu.dk/services/DeepLoc-1.0/index.php, last accessed 20th October 2019
 +
<br>
 +
[7] C. S. Nødvig et al., “Efficient oligo nucleotide mediated CRISPR-Cas9 gene editing in Aspergilli,” Fungal Genet. Biol., vol. 115, no. September 2017, pp. 78–89, 2018.
 +
<br>
 +
[8] V. Meyer et al., “Highly efficient gene targeting in the Aspergillus niger kusA mutant,” J. Biotechnol., vol. 128, no. 4, pp. 770–775, 2007.
 +
<br>
 +
[9] P. J. Punt, F. H. J. Schuren, J. Lehmbeck, T. Christensen, C. Hjort, and C. A. M. J. J. van den Hondel, “Characterization of the Aspergillus niger prtT, a unique regulator of extracellular protease encoding genes,” Fungal Genet. Biol., vol. 45, no. 12, pp. 1591–1599, 2008.
 +
</p>
  
 
   </div>
 
   </div>

Latest revision as of 03:59, 22 October 2019

Measurement Design

A lot of considerations have gone into how to reliably measure the performance of our promoters. This page provides an overview of this.

Measuring promoters

A lot of considerations have gone into how to reliably measure the performance of our promoters. We decided that the primary method of measuring expression from our promoters would be fluorescence reading as we wanted to test the promoters in three different scales: Microplate scale (1-1.5 mL cultures), shake flask scale (200 mL cultures), and bioreactor scale (1 L cultures), also described on the Demonstrate page.

Using a fluorescent reporter

By using a fluorescent reporter gene to measure promoter output, we were able to use a micro bioreactor (BioLector®, M2Plabs) for our microplate scale experiments. The BioLector is able to continuously measure cell density and fluorescence while cell cultures are growing, thus giving us data with a good enough temporal resolution to analyze the dynamics of the different LEAP promoters. Additionally, expressing a fluorescent protein that produces a relatively stable signal is a big advantage compared to having the signal heavily influenced by external factors such as temperature when purifying enzymes for subsequent assays. This is especially important when working with larger experiments, since the frequent measurements we did would have been impractical to carry out with a less stable protein if we were to get the time resolution required for detailed analysis.

We did consider using expression of enzymes such as β-glucuronidase to test our synthetic promoters, since these are known to be secreted by A. niger. β-glucuronidase has also been used in previous studies on promoter activity in A. niger[1], but despite these advantages for the enzyme, we decided the benefits from using fluorescent proteins to get continuous measurements from the BioLector would be greater than the slight disadvantages posed by not having the fluorescent proteins exported from the cells.

Choice of fluorescent protein

For testing the synthetic promoters, the red fluorescent protein mCherry was chosen as the fluorescent reporter. mCherry was used for a number of reasons, including:

  1. mCherry has been proven to work both in E.coli and filamentous fungi. This enables our test device to be used for screening for correct insertion of synthetic promoters in E.coli, as the expression of mCherry can be seen with the naked eye.
  2. Compared to mRFP such as [part number for J04450], the maturation time is short, which is beneficial when analysing the promoter dynamics.[2]
  3. Compared to mRFP, mCherry does not have a peak in absorbance around 500 nm. For mRFP, this peak means that it would absorb part of the signal from GFP, thus obscuring the result if we are to introduce a double fluorescence calibration system as described in Future design and the figure below.
  4. Fluorescence standards such as TexasRed are easy to obtain, and have a nice overlap in spectra with mCherry. Furthermore, the iGEM measurement committee has also recommended the use of TexasRed as a chemical standard for mCherry.
The figure shows three curves visualising the exitation levels for mRFP1, mCherry EX, and moxGFP EM. mRFP1 and mCherry EX mostly overlap but while mCherry EX only peaks around 580 nm, mRFP additionally peaks around 500nm which overlaps with the moxGFP EM peak.
Standard curves to interpolate our fluorescence data into a known concentration of a fluorescence standard is easily obtained using TexasRed (Sulforhodamine 101) [3]

A secondary fluorescent protein: moxGFP

Plans were made to incorporate a second fluorescent reporter in our test design in order to create an internal standard for promoter tests. For this internal standard, we needed a fluorescent reporter that would have an emission/excitation spectrum that did not overlap with that of our red fluorescent protein of choice, mCherry. Though our initial design planned to use eGFP as a reporter for the internal standard, we eventually found a new GFP variant suiting our needs but it was not yet present in the Parts Registry. The moxGFP variant of GFP has increased redox stability, faster maturation time, and is monomeric [4], qualities we are interested in having, in order to minimize sources of error when expressing the protein in a variety of organisms.

This figure shows that secretion tag (BBa_K3046019) attached to mCherry (J06504) is predicted to be transported out of the cell by DeepLoc-1.0.

Protein secretion

As previously mentioned, there are advantages associated with using β-glucuronidase (GUS) as a reporter, such as it being secreted into the extracellular environment, something that can ease protein purification and assaying of promoter activity. As we are using a fluorescent protein we do not have this advantage, but this can be mediated by adding a secretion tag to our mCherry part. We hypothesize that this would enable our mCherry protein to be secreted into the extracellular environment.

The secretion tag was identified via a query on UniProt.org, targeting proteins from A. niger with a signal peptide annotation. A list of signal peptides was produced by identifying enzymes commonly secreted in large quantities by A. niger, and their signal peptide sequences were attached to the N-terminal end of an mCherry peptide sequence. These fusion sequences were subsequently analyzed with SignalP-5.0[5] and DeepLoc.[6] The SignalP-5.0 algorithm predicts the presence of signal peptides in the query peptides and suggests the position for their respective cleavage sites. In addition, it scores the likelihood of cleavage from the suggested cleavage site. The DeepLoc algorithm predicts the subcellular localization of the query peptide in a eukaryotic cell and it can therefore be used to score the likelihood of secretion. Combined, these bioinformatic tools revealed that the GlaA signal peptide is the most efficient in terms of targeting mCherry to the secretory pathway and thus secreting the protein to the extracellular environment as seen in the figures below. .

This figure shows that secretion tag (BBa_K3046019) attached to mCherry (J06504) is predicted to be transported out of the cell by DeepLoc-1.0.

Choice of strain

For the entirety of the project, we have been using two specific Aspergillus niger ATCC 1015 strains, the first of which is NIG96 (ATCC1015; pyrG1, kusAΔ). This specific strain offers two desirable qualities; first, the strain is auxotrophic for uridine, we can use the pyrG gene as our marker to select for successful transformations, and second, the kusA deletion greatly improves the efficiency of gene insertions into the genome. [7,8]

We have also been using a protease deficient version of the NIG96 strain that contains an inactivated prtT transcription factor. [9] This strain therefore lacks many of the endogenous proteases normally secreted by A. niger, and will hopefully prevent much of the unwanted digestion of our fluorescent protein which would result in a more accurate reading of our fluorescent protein.

Normalizing data for growth

When cultivating biological samples in different scales, we need some way of standardizing the data in order to be able to compare results between experiments. The first method used to achieve this is using a Bradford assay to measure the total protein concentration in the biomass samples. This was done along with the fluorescence measurements for the purified proteins in order to obtain a standardized quantity of fluorescence per protein. This allows us to compare the different samples, even if one fungus grows faster than the others, if different amounts of spores were used for inoculation, or some other minor factor that would obfuscate the underlying relative promoter expression.
We have also measured the growth of our fungi in multiple different ways for each of the three scales, in which we have been cultivating our fungal cultures. In the Biolector, we had continuous measurements of “Light Scattering Units”, which can give an estimate of biomass. Next, in the shake flasks we did not have direct access to biomass measurements and thus, we resorted to determining the amount of residual glucose in the media in order to correlate it to biomass growth. Lastly, in the bioreactor, we had access to analysis of the off-gas, thus giving us a measurement of respiration, which is correlated with growth.

Combining all of the above allows for understanding in greater detail how our promoters work and it also enables us to compare different promoters across different experiments, which is of utmost importance when characterizing new parts.



[1] K. Ozeki, A. Kanda, M. Hamachi, and Y. Nunokawa, “Construction of a promoter probe vector autonomously maintained in aspergillus and characterization of promoter regions derived from A. niger and A. oryzae Genomes,” Biosci. Biotechnol. Biochem., vol. 60, no. 3, pp. 383–389, 1996.
[2] E. Balleza, J. M. Kim, and P. Cluzel, “Systematic characterization of maturation time of fluorescent proteins in living cells,” Nat Methods, vol. 15, no. 1, pp. 47–51, 2018.
[3] T. J. Lambert, “FPbase: a community-editable fluorescent protein database,” Nat. Methods, vol. 16, no. 4, pp. 277–278, 2019.
[4] L. M. Constantini et al., “A palette of fluorescent proteins optimized for diverse cellular environments,” Nat Commun, vol. 6, no. 1, p. 8670, 2015.
[5] http://www.cbs.dtu.dk/services/SignalP/, last accessed 20th October 2019
[6] http://www.cbs.dtu.dk/services/DeepLoc-1.0/index.php, last accessed 20th October 2019
[7] C. S. Nødvig et al., “Efficient oligo nucleotide mediated CRISPR-Cas9 gene editing in Aspergilli,” Fungal Genet. Biol., vol. 115, no. September 2017, pp. 78–89, 2018.
[8] V. Meyer et al., “Highly efficient gene targeting in the Aspergillus niger kusA mutant,” J. Biotechnol., vol. 128, no. 4, pp. 770–775, 2007.
[9] P. J. Punt, F. H. J. Schuren, J. Lehmbeck, T. Christensen, C. Hjort, and C. A. M. J. J. van den Hondel, “Characterization of the Aspergillus niger prtT, a unique regulator of extracellular protease encoding genes,” Fungal Genet. Biol., vol. 45, no. 12, pp. 1591–1599, 2008.

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