Difference between revisions of "Team:Paris Bettencourt/Project/Microbiology"

 
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<div id=topheader> </div>
  
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<!--h1 class="red">Microbiology Group: The Search for Anthocyanin Degradation in Nature </h1-->
  
  <div id="page">
 
    <div style="width:1100px;margin:0 auto;">
 
      <img src="https://static.igem.org/mediawiki/2013/3/3a/PB_logoParis.gif" width="122px" style="position:absolute;top:40px;right:30px;"/>
 
    </div>
 
    <img src="https://static.igem.org/mediawiki/2013/c/c7/PB_targettitle.png" style="margin-bottom:15px"/>
 
    <div class="overbox">
 
      <div class="bkgr">
 
<h2>Background</h2>
 
<p>SirA is an essential gene in latent tuberculosis infections</p>
 
      </div>
 
      <div class="results">
 
<h2>Results</h2>
 
<ul>
 
          <li>Produced an <i>E. coli</i> strain which relies upon mycobacterial sirA, fprA and fdxA genes to survive in M9 minimal media</li>
 
          <li>Demonstrated that <i>E. coli</i> can survive with mycobacterial sulfite reduction pathway with Flux Balance Analysis</li>
 
<li>Realized in sillico modeling and identified experimentally a potential anti-TB activity of Pyridoxine at high doses.</li>
 
          <li>Performed  a high throughput drug screening and identified 10 new potential anti-TB drug candidates.</li>
 
  
</ul>
+
<!----------------------- BEGIN SUMMARY BOXES-------------------------> 
<p></p>
+
 
      </div>
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<div class="projtile1">
       <div class="biocriks">
+
    <h2 class="red" style="text-align:center;">Goals</h2>
<h2>BioBricks</h2>
+
    <ul>
<ol>
+
        <li>To screen soil samples from around the world for microbes that naturally degrade anthocyanin.</li>
          <li><a href="http://parts.igem.org/Part:BBa_K1137000">BBa_K1137000 (SirA)</a></li>
+
        <li>To identify enzymes linked to the most efficient anthocyanin eaters.</li>
          <li><a href="http://parts.igem.org/Part:BBa_K1137001">BBa_K1137001 (FprA)</a></li>  
+
    </ul>
          <li><a href="http://parts.igem.org/Part:BBa_K1137002">BBa_K1137002 (FdxA)</a></li>
+
</div>
</ol>
+
 
      </div>
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      <div style="clear: both;"></div>
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<div style="clear: both;"></div>
      <div class="aims">
+
 
<h2>Aims</h2>
+
<div class="projtile3">
<p>To perform a drug screen targeted at the sirA gene from mycobacteria</p>
+
       <h2 class="red" style="text-align:center;">Results</h2>
      </div>
+
      <ul>
      <a href="#Introduction">
+
            <li>We collected species from all around the world through iGEM collaborations.
<div class="hlink">
+
            <li>186 bacteria were tested for degradation of quercetin.
  <h2>Skip to Introduction</h2>
+
            <li>174 bacteria were identified by 16s rRNA sequencing.
 +
            <li>4 promising species were selected for whole genome sequencing.
 +
            <li>Candidate enzymes were identified from genome sequence, and passed to the enzyme group.</li>
 +
 
 +
      </ul>
 +
</div>
 +
 
 +
<div style="clear: both;"></div>
 +
 
 +
<div class="projtile4">
 +
    <h2 class="red" style="text-align:center;">Methods</h2>
 +
    <ul>
 +
        <li>Microbe cultivation
 +
        <li>Anthocyanin purification
 +
        <li>Anthocyanin & quercetin measurement
 +
        <li>16S rRNA sequencing
 +
        <li>Whole genome sequencing
 +
        <li>Phylogenetic analysis
 +
    </ul>
 +
</div>
 +
 
 +
<div style="clear: both;"></div>
 +
 
 +
<!----------------------- END SUMMARY BOXES------------------------->   
 +
 
 +
<div id=subheader>
 +
<div id="input">
 +
<h2 class="red">Abstract</h2>
 +
<p>
 +
<b>Anthocyanins, the key pigments found in red wine, are abundant in grapes, berries, flowers and many plants. Like all naturally ocurring metabolites, they eventually biodegrade and re-enter the carbon cycle. In this project, we search nature for enzymatic pathways that can break down anthocyanins into simpler, unpigmented molecules. We reasoned that microbes living in the soil near vineyards were likely to catabolize and consume anthocyanin. Therefore we collected soil samples from 10 vinyards around France, Europe and the world, notably with the help of our fellow iGEM teams. In total we isolated 186 strains through selective and non-selective plating on different media. All of the strains were identified by 16s rRNA sequencing, then characterized for their ability to degrade quercetin, a compound structurally similar to anthocyanin. By phylogenetic analysis, we were able to connect quercetin degradation to specific bacterial phyla and genus including <i>Micrococcus</i>, <i>Pseudomonas</i>, <i>Lysinibacillus</i> and <i>Oerskovia</i>. The most effective strains were further characterized by whole genome sequencing to identify enzymes linked to natural quercetin degradation. By bioprospecting with the help of the worldwide iGEM community, we were able to find the best stain fighting enzymes that nature has to offer.</b>
 +
</p>
 +
 
 +
<h2 class="red"> Motivation and Background</h2>
 +
<h3>Bioprospecting and Bioremediation</h3>
 +
 
 +
<p>
 +
Bioprospecting is the process of searching nature for genetic information that can be adapted in useful or profitable ways. In recent years, bioprospecting efforts have focused on the search for small molecule pharmaceuticals and other bioactive compounds (Müller, 2016). Bioremediation is the use of living organisms to remove environmental toxins from contaminated areas. Microbes in particular are well known for their ability to degrade organic pollutants like petroleum, pesticides and phenolic compounds. Bioremediation has always been a popular topic in iGEM, producing many notable projects with diverse organisms and applications.</p>
 +
 
 +
 
 +
<p>
 +
<br>Anthocyanin is not harmful, but in the context of a stain it is unwanted and so could be considered a target for bioremediation. Therefore a mechanism to degrade anthocyanin could be revealed with a classic bioremediation strategy :
 +
<ol>
 +
<li>Select organisms from a contaminated environment, where enzymatic decontamination may have naturally evolved.</li>
 +
<li>Isolate pure strains and measure their activity.</li>
 +
<li>Connect the activity to specific pathways using molecular genetics.</li>
 +
</ol>
 +
</p>
 +
 
 +
<h3>Anthocyanidin and quercetin</h3>
 +
<p>
 +
In these experiments, we use quercetin as a chemical proxy for anthocyanins. Naturally occurring anthocyanidins are chemically diverse derivatives of a a core flavylium cation. Plant sources of anthocyanidin carry a range of anthocyanidin pigments substituted at any of up to seven positions, with the relative concentrations contributing to a characteristic color.
 +
Pure anthocyanidins, like malvidin, are expensive (120 EUR for 1 mg) and do not necessarily represent the full chemical diversity of a natural wine stain. Therefore, in this work we use quercetin, a flavonol, as a structural proxy. Quercetin is cheap (40 EUR for 10 g), stable, and can be quantified by absorbance at 315 nm. In follow up experiments, microbes are tested on real wine and on bulk anthocyanins that we extract directly from grape skins.
 +
</p>
 +
 
 +
<div id="figurebox">
 +
<div style="text-align:center;">
 +
<img src="https://static.igem.org/mediawiki/2016/2/29/Paris_Bettencourt-Malvidin_and_Quercetin_chemical_structure.png" alt="Quercetin strains degradation" style="height:600px;">
 +
<p>
 +
<b>Figure 1</b> Structure and absorbance of malvidin, the most abundant anthocyanidin in wine, and quercetin, a flavonol.<p>
 +
All flavonoids are structured as two phenyl rings and a heterocyclic ring. Anthocyanin itself is structured as a chromane ring with an aromatic ring on C2. Cyanindin and malvidin comprise 90% of the anthocyanins found in nature. These chemicals differ only in their cyclic B groups, and the chromane ring is well conserved in most flavonoids. Therefore, we theorized that the chromane ring itself presented an ideal target for degradation.<br>
 +
Based on these criteria, we chose the flavanol quercetin as our anthocyanin substitute. This molecule differs from anthocyanins only in the presence of a carbonyl group. Additionally, quercetin is present in wine, and contributes to its color. Thus, even in the case where enzymes are isolated that break down quercetin and not anthocyanin, the possibility exists of reducing the color or intensity of wine stains.<br>
 +
Finally, co-pigmentation chemical interactions occur between anthocyanin and quercetin, increasing wine color stability, mainly through π-π stacking between their phenolic cycles. Thus, it leads to the possibility that quercetin degradation could also impact anthocyanin stability.
 +
</p>
 +
 
 +
</p>
 +
</div>
 +
</div>
 +
 
 +
 
 +
 
 +
 
 +
<h2 class="red">Results</h2>
 +
<h3>Anthocyanin Extraction and analysis</h3>
 +
<p>Anthocyanins were extracted from <i>Vinis vitifera</i> fruits. It skin was separated from the rest of the fruit and macerated overnight in an ethanol solution with 1% chloridric acid. After maceration, the solution was passed through with a paper filter to eliminate solid material and evaporated at 37°C at 150 rpm. We confirmed the presence of anthocyanin with HPLC and, colour variation with pH.</p>
 +
 
 +
<h3>Collection of the soil samples</h3>
 +
 
 +
<p>Soil samples were collected from France, Spain, Croatia, Namibia and Australia. Samples from the Paris region were collected by members of our team. Other samples were sent by friends, family members, and collaborating iGEM teams. Soil samples were declared to French customs authorities with a <a href = "https://static.igem.org/mediawiki/2016/b/b7/Paris_Bettencourt_Facture_Proforma.pdf">Facture Proforma</a>, printed out by the sample donor and included in the shipment.
 +
 
 +
<br>Upon arrival, samples were washed gently with phosphate-buffered saline (PBS) solution, then left to stand, allowing large particles to settle. The resulting eluate was diluted further with PBS then used directly as a source of soil microbes.
 +
</p>
 +
 
 +
<div id="figurebox">
 +
<table border="1">
 +
<tr>
 +
<th>Country</th>
 +
<th>Location</th>
 +
<th>Collector</th>
 +
</tr>
 +
 
 +
<tr>
 +
<td>France</td>
 +
<td>Clos Monmartre Vineyard, Paris</td>
 +
<td>Our Team</td>
 +
</tr>
 +
 
 +
<tr>
 +
<td>France</td>
 +
<td>Cochin Port Royal, Paris</td>
 +
<td>Our team</td>
 +
</tr>
 +
 
 +
<tr>
 +
<td>France</td>
 +
<td>Vaucluse region’s vineyard</td>
 +
<td>INSA-Lyon iGEM team</td>
 +
</tr>
 +
 
 +
<tr>
 +
<td>Spain</td>
 +
<td>Barcelona</td>
 +
<td>UPF-CRG Barcelona iGEM team</td>
 +
</tr>
 +
 
 +
<tr>
 +
<td>Spain</td>
 +
<td>Utiel Requena</td>
 +
<td>UPV Valencia iGEM team</td>
 +
</tr>
 +
 
 +
<tr>
 +
<td>Australia</td>
 +
<td>Hunter Valley</td>
 +
<td>UNSW</td>
 +
</tr>
 +
 
 +
<tr>
 +
<td>Australia</td>
 +
<td>Sydney</td>
 +
<td>Macquarie 2016 iGEM team</td>
 +
</tr>
 +
 
 +
<tr>
 +
<td>Namibia</td>
 +
<td>Etosha National Park</td>
 +
<td>Our team</td>
 +
</tr>
 +
 
 +
<tr>
 +
<td>Algeria</td>
 +
<td>Alger</td>
 +
<td>Our team</td>
 +
</tr>
 +
 
 +
<tr>
 +
<td>Croatia</td>
 +
<td>Kricke</td>
 +
<td>Our team</td>
 +
</tr>
 +
 
 +
<tr>
 +
<td>Israel</td>
 +
<td>Jerusalem</td>
 +
<td>Our team</td>
 +
</tr>
 +
</table>
 +
 
 +
<div style="float:right; margin-bottom:10px;margin-top: -500px; ">
 +
<img src="https://static.igem.org/mediawiki/2016/f/f8/Paris_Bettencourt-File_Sample_World_microbio.jpg"alt="world_Microbiome" style="width:450px;">
 +
<p>
 +
</p>
 +
 
 +
<p>
 +
<b>Figure 2</b> Location of soil samples<br>collected or obtained by the team.
 +
</div>
 +
 
 +
</div>
 +
 
 +
<h3>Preparation of the microbe library</h3>
 +
<p>
 +
For safety and to avoid environmental contamination, microbial isolation was performed in a fume hood in a BSL 2 facility. More safety information in provided on our safety page.
 +
 
 +
<br>Microbes were isolated from soil samples using either selective or nonselective plating. For the selective plating, M9 agar was supplemented with either quercetin alone or quercetin with glucose to enrich for microbes with the ability to metabolize quercetin.
 +
 
 +
<br>The resulting culture was incubated at 30 C for 48 hours, then re-streaked to eliminate potential contamination.
 +
 
 +
<br>To maximize library diversity, we preferentially chose colonies with unique morphologies. After isolation, we performed colony PCR with universal 16s rRNA primers (see methods). Sequencing the resulting PCR products allowed us to identify the strains and position them within the greater bacterial taxonomy.
 +
 
 +
</p>
 +
 
 +
 
 +
 
 +
 
 +
 
 +
<h3>Quercetin degradation assay</h3>
 +
 +
<p>
 +
Each of the 189 isolated strains was innoculated into M9 quercitin medium in triplicate and incubated at 37 C for 6 days. At the end of the period, quercitin concentration was measured by absorbance.<br><br>
 +
 +
 
 +
Of 186 strains tested, 50 produced quercetin levels significantly lower than controls (Figures 3 and 4). 20 strains degraded more than 50% of quercetin and 2 strains degraded more than 80%.<br>
 +
Both selective and nonselective plating methods were able to produce quercetin-degrading strains. 4 of the 5 strains showing the most quercetin degradation were obtained by selective plating. <br>However, 40 of the 50 strains showing significant degradation were obtained by nonselective plating.
 +
<br><br>
 +
 
 +
 
 +
<br></p>
 +
<div id="figurebox">
 +
<div style="text-align:center;">
 +
<img src="https://static.igem.org/mediawiki/2016/1/1f/Paris_Bettencourt-File_Quercetin_.jpg" alt="Quercetin strains degradation" style="width:900px;">
 +
<p>
 +
<b> Figure 3</b> Quercetin degradation by 186 microbes collected from global soil samples. Single colonies were inoculated in M9 minimal medium and grown for 6 days. Quercetin was measured by absorbance. Strains to the extreme left of the figure represent the highest-degrading strains. Red bars represent strains isolated from selective media and blue from non selective media.
 +
<br>
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<br>
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</div>
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 +
<div id="figurebox">
 +
    <img src="https://static.igem.org/mediawiki/2016/b/be/Paris_Bettencourt-File_Quercetin_degradation_kinetic.jpg" alt="Quercetin degradation detail" style="width:900px; " >
 +
 
 +
<p style="text-align: left;">
 +
            <b> Figure 4</b> Quercetin degradation detail. The top-performing strains included those isolated from both selective and nonselective media. Strains marked with an asterisk were selected for further investigation. Red bars represent strains isolated from selective media and blue from non selective media.
 +
        </p>
 +
</div>
 +
<p>
 +
Working with M9 quercetin plates can be challenging. The bright green color of the plates makes colony visualization difficult. <br>Indeed, only fungal mycelia were visible due to a white halo resulting from quercetin degradation. However, working with liquid media allows the control of residual sample carbon source contamination through sample dilution.<br> Additionally, we were concerned agar in plates could be used as a carbon source.
 +
<br><br>8 top-performing strains were selected for detailed valication in a time-course assay, and all were able to degrade quercitin significantly better than E. coli negative controls. <br>We observed a 50% degradation over 6 days in the best case.</p>
 +
 
 +
<div id="figurebox">
 +
    <img src="https://static.igem.org/mediawiki/2016/b/b7/Paris_Bettencourt-File_Quercetin_degradation_totalstrains.jpg" alt="Quercetin degradation detail" style="width:450px; " >
 +
 
 +
<p style="text-align: left;">
 +
<div style="text-align:center;">
 +
            <b> Figure 5</b> Kinetics of quercetin degradation by 8 promising strains. This experiment had two negative controls, one with no bacteria (black line) and one with non-quercetin degrading <i>E. coli</i>. <i>Pseudomonas putita</i> was included as a positive control. Four strains, shown in bold, degraded quercetin at a higher rate than our <i>P. putida</i> control.
 +
        </p>
 +
</div>
 +
</div>
 +
 
 +
 
 +
<h3>Phylogenetic analysis of quercetin degradation</h3>
 +
<p>
 +
Using the 16s rRNA sequences, we constructed a global phylogeny of all the assayed strains (Figure 6). <br>Quercitin-degrading activity was concentrated among the Pseudomonas genus, where most of the strains were positive.<br> However many diverse species were able to significantly degrade quercitin, suggesting that the phenotype may be highly variable in evolution.<br>
 +
 +
 
 +
</p>
 +
<div id="figurebox">
 +
<img src="https://static.igem.org/mediawiki/2016/d/dc/Paris_Bettencourt-Phylogenetic_Tree.jpg" alt="Quercetin degradation detail" style="width:950px;" >
 +
<p>
 +
<b> Figure 6: Phylogenetic Tree of isolated strains. </b>
 +
We constructed a phylogenetic tree of all isolated bacterial strains. Strain taxonomic classification is indicated by the color key to the left of the figure. Strains that demonstrated high quercetin degradation are marked with an asterisk. Those strains marked with a large star were selected for whole genome sequencing to look for common anthocyanin-degrading genes.
 +
 
 +
</p>  
 +
</div>  
 +
<div style="clear: both">
 +
</div>
 +
 
 +
 
 +
<h3>Mining genomes for quercetin-degrading enzymes</h3>
 +
 
 +
<p>
 +
 
 +
Four of our top-degrading strains, representing diverse phylogentic lineages, were selected for whole genome sequencing. <br>As of the wiki freeze, the genome sequences were not complete. So, as a proxy, we obtained complete genome sequences of their nearest relatives in GenBank.<br> BLAST searches against the genomes revealed the presence of several candidate quercitin-degrading enzymes, including laccase and XylE.
 +
<br>
 +
<br>
 +
The results of these genomic analysis were passed to the enzyme group, where these enzymes form the basis of our synthetic stain fighting product.
 +
</p>
 +
<div id="figurebox">
 +
<img src="https://static.igem.org/mediawiki/2016/3/37/Paris_Bettencourt-Genome_Table.jpg" alt="Genome Table" style="width:900px;" >
 +
<p>
 +
<b> Figure 7: Genome table.</b> Genome sequences were analyzed for the presence of potential anthocyanin degrading enzymes as identified in the Enzymes Project. The genes of at least one of the six candidates were identified for each of the sequenced strains. The number of + signs indicated represent the number of gene copies in the bacterial genome.
 +
</b>
 +
</p>
 +
</div>  
 +
<div style="clear: both">
 +
</div>
 +
 
 +
 
 +
 
 +
<br>
 +
</p>
 +
 
 +
 
 +
<br><br>
 +
 
 +
 
 +
 
 +
<h2 class=”red”>Methods</h2>
 +
 +
<h3>Anthocyanin extraction</h3>
 +
<p>
 +
<i>Vinis vitifera</i> grapes were our source for anthocyanin extraction. <br> Grapes were peeled and the skins were collected, washed and soaked overnight in ethanol with 1% HCl.<br> By trial and error, we determined that 2.5 mL of this solution per 1 g of skins was the best compromise between efficiency and the quantity of solvent used.<br> The solution was filtered with Whatman paper, with the filtrate collected, and the solvent evaporated at 37°C for several hours.<br> The dry extract was resuspended in water (10 mL for 1g of grape skin).<br>
 +
</p>
 +
 
 +
<h3>Anthocyanin quantification by differential absorbance</h3>
 +
<p>
 +
Following Lee et al. (2005), we prepared one buffer at pH 1 (0.025M potassium chloride) and a second at pH 4.5 (sodium acetate, 0.4M).<br>
 +
100 µL of the anthocyanin solution was mixed with 900µL of each buffers and the color was allowed to develop over 20 minutes.<br> Absorbance measurements were obtained at 510 nm and 700 nm for each solution.<br> Anthocyanin concentration was determined as a function of the four absorbance measurements, using an established formula (Lee et al., 2005).<br>
 +
</p>
 +
<h3>Protein quantification with Bradford assays</h3>
 +
<p>
 +
A stock solution of Bovine Serum Albumin (BSA) was prepared in water at 1 mg/mL.<br> 100 μL of standard dilutions of BSA solution were mixed with 1 mL of Bradford Reagent and mixed by vortexing.<br> Absorbance was measured at 595 nm. Experimental samples were treated similarly and compared to the BSA standard curve to determine concentration.<br>
 +
</p>
 +
<h3>Carbohydrate quantification with Fehling Reaction</h3>
 +
<p>
 +
200µL of Fehling's A solution, 200µL of Fehling's solution B and 200µL of our carbohydrate solution into sodium acetate buffer (20µL of solution and 180 µL of buffer).<br> The Fehling reaction is measured as the loss of absorbance at 650nm relative to a blank solution without carbohydrate.<br> Quantification was achieved by comparison to a standard curve of glucose prepared at 1g/L to 5g/L.
 +
</p>
 +
   
 +
<h3>Bacteria plating on selective and non-selective media</h3>
 +
<p>1 g of soil samples were suspended in 5 mL Phosphate Buffered Saline (PBS) then left to stand allowing large particles to settle.<br> The soil suspension was serially diluted to obtain a suitable density of microbes (typically 1:1000) then 200 µL was plated on standard Petri dishes with M9 agar with 1 g/L quercetin for selection.<br> Non-selective plating was performed on a range of rich media including FTO agar (Curry, 1976), Mossel agar (Mossel, 1967), standard LB, standard TSA and standard M9 glucose.<br>
 +
</p>
 +
 
 +
<h3>Protocol for growth assay in Quercetin M9 liquid media</h3>
 +
<p>Following the protocol of Dantas <i>et al.</i> 2012, all step were performed in liquid media to control soil carbon source contamination.<br> We suspended soil samples in 5 ml M9 with 1g/L quercetin at pH 7 in 50 ml Falcon tubes with 500µL of overnight culture of strains isolated from selective or non-selective plates.<br><br>
 +
All cultures were made in triplicate at 30°C with shaking at 150 rpm for several days. As quercetin is not soluble at pH=7, shaking important to avoid precipitation.<br></p>
 +
<h3> Quercetin absorbance measurement </h3>
 +
<p>Quercetin absorbance was measured at two time points for histogram construction: at 0 days to ensure quercetin sample concentration consistent with the controls, and at 6 days to evaluate quercetin degradation.<br> M9-quercetin and <i>Pseudomonas putida</i>K2440 samples were included as negative and positive controls, respectively.<br><br>
 +
Prior to absorbance measurement, Quercetin was solubilized by diluting samples 10 fold in 0.5M NaOH, centrifuged to remove cell material, and further diluted 100X for measurement at 315 nm in a Tecan plate reader.<br></p>
 +
<h3>PCR for 16s characterization, sequencing interpretation and phylogenetic tree construction.</h3>
 +
<p>To identify bacterial strains, 16S rRNA sequences were amplified through colony PCR, column purified, and Sanger sequenced by GATC.<br> The resulting sequences were submitted for BLAST comparison at ncbi.gov.<br> Alignments were performed using the Ribosomal Database Project Aligner tool (https://rdp.cme.msu.edu/),<br> and a phylogenetic tree was constructed using Geneious software with the following parameters: we used Neighbor-Joining tree building with Jukes Cantor as the genetic distance model, with a 93% similarity cost matrix for the alignment with free end gaps.<br> The tree was then exported and improved using the online Tree of Life software (http://www.tolweb.org/tree/).</p>
 +
 
 +
<h3>PCR for genome sequencing.</h3>
 +
 
 +
<p>We isolated bacterial DNA using the DNeasy Blood and Tissue Kit from Qiagen.<br> We submitted four strains to GATC for whole genome sequencing: NS.4 (<i>Lysinibacillus</i>), S.48 (<i>Stenothrophomonas maltophilia</i>), S.33 (<i>Oerskovia Paurometabola</i>), NS.33 (<i>Microccocus Luteus</i>) according to their sample preparation specifications.<br></p>
 +
 
 +
<h2 class=”red”>Attributions</h2>
 +
<p>This project was done by Antoine Villa Antoine Poirot and Sébastien Gaultier. Anthocyanin data was obtained by Ibrahim Haouchine. <br> Thanks to our advisors Jake and Jason for all their help with the figures.<br> We would like to thank Philippe Morand from the microbiology lab of Cochin for his advice.</p>
 +
<img src="https://static.igem.org/mediawiki/2016/d/de/Paris_Bettencourt-sebstatic.jpeg" width="200px"/><img src="https://static.igem.org/mediawiki/2016/6/6c/Paris_Bettencourt-Antoinepstatic.jpeg" width="200px"/><img src="https://static.igem.org/mediawiki/2016/f/f6/Paris_Bettencourt-AntoineVstatic.jpeg" width="200px"/><img src="https://static.igem.org/mediawiki/2016/b/b3/Paris_Bettencourt-Ibrastatic.jpeg" width="200px"/> <br>
 +
 
 +
<h2 class=”red”>References</h2>
 +
<ul>
 +
<li>Kanekar, P. P., Sarnaik, S. S., & Kelkar, A. S. (1998). Bioremediation of phenol by alkaliphilic bacteria isolated from alkaline lake of Lonar, India. <i>Journal of applied microbiology</i>, 85(S1).</li>
 +
<li>Dantas, G., Sommer, M. O., Oluwasegun, R. D., & Church, G. M. (2008). Bacteria subsisting on antibiotics. <i>Science</i>, 320(5872), 100-103.</li>
 +
<li>Lee, J., Durst, R. W., & Wrolstad, R. E. (2005). Determination of total monomeric anthocyanin pigment content of fruit juices, beverages, natural colorants, and wines by the pH differential method: collaborative study. <i>Journal of AOAC international</i>, 88(5), 1269-1278.</li>
 +
<li>Curry, J. C., & Borovian, G. E. (1976). Selective medium for distinguishing micrococci from staphylococci in the clinical laboratory. <i>Journal of clinical microbiology</i>, 4(5), 455.</lI>
 +
<li>Pillai, B. V., & Swarup, S. (2002). Elucidation of the flavonoid catabolism pathway in Pseudomonas putida PML2 by comparative metabolic profiling. <i>Applied and environmental microbiology</i>, 68(1), 143-151.</li>
 +
<li>Herrmann, H., Janke, D., Krejsa, S., & Kunze, I. (1987). Involvement of the plasmid pPGH1 in the phenol degradation of Pseudomonas putida strain H. <i>FEMS microbiology letters</i>, 43(2), 133-137.</li>
 +
</ul>
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<div style="margin-top:20px; margin-bottom:20px">
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<a href="https://2016.igem.org/Team:Paris_Bettencourt/Project/Assay" title="Assay">
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<div id="pspanel" class="subpanel2"  onmouseover="chgtrans(this)">
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  <img class="narrowimg" src="https://static.igem.org/mediawiki/2016/b/b9/Paris_Bettencourt-Assay_Button2.png" width="150px" height="250px"/>
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    <center><img src="https://static.igem.org/mediawiki/2016/e/e8/Paris_Bettencourt-Logo_Assay.png" style="height:60px;"/></center>
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    <div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div>
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    Assay
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       <a href="#Model">
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       <a href="https://2016.igem.org/Team:Paris_Bettencourt/Project/Microbiology" title="Microbiology">
<div class="hlink">
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<div id="dspanel" class="subpanel2">
  <h2>Skip to Modeling</h2>
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  <img class="narrowimg" src="https://static.igem.org/mediawiki/2016/e/e0/Paris_Bettencourt-Microbiology_Button2.png" width="150px" height="250px"/>
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    <center><img src="https://static.igem.org/mediawiki/2016/f/f8/Paris_Bettencourt-Logo_Microbiology.png" style="height:60px;"/></center>
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    <div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div>
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    Microbiology
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       <a href="#Design">
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       <a href="https://2016.igem.org/Team:Paris_Bettencourt/Project/Enzyme" title="Enzyme">
<div class="hlink">
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<div id="tcpanel" class="subpanel2">
  <h2>Skip to Design</h2>
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  <img class="narrowimg" src="https://static.igem.org/mediawiki/2016/d/d0/Paris_Bettencourt-Enzyme_Button2.png" width="150px" height="250px"/>
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    <center><img src="https://static.igem.org/mediawiki/2016/9/9d/Paris_Bettencourt-Logo_Enzyme.png" style="height:60px;"/></center>
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  Enzyme
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       <a href="#Results">  
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       <a href="https://2016.igem.org/Team:Paris_Bettencourt/Project/Binding" title="Binding domains">
<div class="hlink" style="margin-right:0px">
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<div id="thpanel" class="subpanel2">     
  <h2>Skip to Results</h2>
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  <img class="narrowimg" src="https://static.igem.org/mediawiki/2016/6/68/Paris_Bettencourt-Binding_Button2.png" width="150px" height="250px"/>
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  <div class="titlebox">
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    <center><img src="https://static.igem.org/mediawiki/2016/4/44/Paris_Bettencourt-Logo_Binding.png" style="height:60px;"/></center>
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    <div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div>
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    Binding
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  </div>
 
</div>
 
</div>
 
       </a>
 
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    <a href="https://2016.igem.org/Team:Paris_Bettencourt/Project/Indigo" title="Indigo">
    </div>
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<div id="thpanel" class="subpanel2">    
    <div id="Introduction"></div>
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  <img class="narrowimg" src="https://static.igem.org/mediawiki/2016/7/75/Paris_Bettencourt-Indigo_Button2.png" width="150px" height="250px"/>
    <h2>Introduction</h2>
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  <div class="titlebox">
    <div class="leftparagraph">
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    <center><img src="https://static.igem.org/mediawiki/2016/f/f0/Paris_Bettencourt-Logo_Indigo.png" style="height:60px;"/></center>
      <p> &nbsp;&nbsp;
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    <div style="width:60%;margin-left:20%;margin-bottom:10px;"><hr></div>
SirA is essential for <i>M. tuberculosis</i> persistence phenotype as sulfur containing amino acids are particularly sensitive to oxidative stress within the macrophage and must regularly be replaced <a href="#Reference">(Pinto <i>et al</i> 2007)</a>. Currently, there are no drug candidates that are known to specifically inhibit SirA and conventional drug screens involve do not provide information regarding the mechanism of drug action nor do compounds that inhibit exponential growth necessarily have an effect on persistent TB. We designed a working drug screen assay to specifically target the mycobacterial sulfite reductase protein SirA. To this end we cloned Ito <i>E. coli </i><span style="font-style: normal;">the sulfite reduction pathway</span> of <i>M. smegmatis</i>, a non-pathogenic mycobacterial relative of <i>M. Tuberculosis</i>. Our model overcomes the problem of long doubling time of <i>M. tuberculosis</i>. Specific inhibition of the sulfite reduction pathway is scored by comparing a drug screen of our <i>E. coli</i> construct <i>vs.</i> wild-type. Any drug candidates that have activity against both the wild-type <i>E. coli</i> and our construct are non-specific inhibitors of <i>E. coli</i> growth. However, any drug candidates that inhibit only the growth of our <i>E. coli </i>construct will be <span style="font-style: normal;">SirA</span><i> </i><span style="font-style: normal;">pathway specific.</span>
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    Indigo
      </p>
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  </div>
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</div>
    <div class="rightparagraph">
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       </a>
      <a href="https://static.igem.org/mediawiki/2013/4/4f/PS_Drug_Scheme.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/4/4f/PS_Drug_Scheme.png" width="535px"/></a>
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  <a href="https://2016.igem.org/Team:Paris_Bettencourt/Model" title="Model">
      <p><b>Figure 1: Overview of Targeted Drug Screen Design</b></p>
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<div id="thpanel" class="subpanel2">    
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  <img class="narrowimg" src="https://static.igem.org/mediawiki/2016/9/96/Paris_Bettencourt-Model_Button2.png" width="150px" height="250px"/>
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    <center><img src="https://static.igem.org/mediawiki/2016/2/21/Paris_Bettencourt-Model_Icon.png" style="height:60px;"/></center>
    <h2>Flux Balance Analysis of Sulfite Reduction Pathway</h2>
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    <div style="width:60%;margin-left:20%;margin-bottom:10px;"><hr></div>
    <div class="leftparagraph">
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    Model
       <p>&nbsp;&nbsp;
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  </div>
We used an <i>E. coli</i> model (iJR904) obtained from the <a href="http://bigg.ucsd.edu/bigg/main.pl">BiGG database</a> as a starting model to obtain wild-type growth rate (f = 0.9129 divisions/hour). We then deleted the reaction ‘SULR’ which encodes for the sulphite reduction pathway involving cysI and obtained a f=  -8e-13=0 divisions/hour indicating that the sulphite reduction pathway is essential for growth. Finally we introduced two new reactions for sirA and fprA and a new species fdxA. We found that growth with the mycobacteria pathway reverts the growth phenotype back to wild-type levels (f = 0.9105 divisions/hour).  We then wanted to expand our model to find new pathways that we could utilize for a targeted drug screen approach.  We wrote a matlab script that finds all the essential reactions in <i>M. tuberculosis</i> and all the essential reactions in <i>E. coli</i>, and then tries to complement the essential reactions in the <i>E. coli</i> model with the essential reactions from <i>M. tuberculosis</i>. The model identified <a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Target/FBA">100 metabolic reactions</a> that we could target.  Additionally, due to the modular nature of the model, it can be used to find target-able metabolic reactions in any SBML file.  The Matlab scripts can be found <a href="https://2013.igem.org/File:TargetFBA.zip">here</a> and requires <a href="http://opencobra.sourceforge.net/openCOBRA/Welcome.html">Cobra Toolbox 2.0</a> to function.  Please visit the FBA page for a detailed list of <a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Target/FBA">results</a>.
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</div>
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</div>
    <div class="rightparagraph">
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</div>
      <center><a href="https://static.igem.org/mediawiki/2013/7/76/PS_FBA.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/7/76/PS_FBA.png" width="267.5px"/></a></center>
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      <p><b>Figure 2: Biomass Flux through <i>E. coli</i> and mycoSIR E. coli</b><div style="font-size: 90%">Flux balance analysis was run using Cobra Toolbox 2.0 on <i>E. coli</i> sbml model iJR904 with and without SULR reaction.  Additionally an <i>E. coli</i> sbml model was built with the SULR reaction replaced with a reaction representing the mycobacterial SirA reaction and FprA reaction, as well as ferredoxin FdxA as an additional species.  The Biomass flux is restored to 99.75% of the wild-type level with the synthetic mycobacterial system.</div></p>
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    <h2>Structural Analysis of SirA</h2>
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    <div class="leftparagraph">
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<p class=definition><br>
      <p>&nbsp;&nbsp;
+
  </p>
Superimposing the structures of <i>M.tuberculosis</i> SirA and <i>E.coli </i> CysI reveals high homology, in particular of the active sites. Both proteins have the same symmetry (psuedo 2 fold) indicative of a common evolutionary origin. Our analysis highlighted important conserved residues, involved in substrate binding to be Arg97, Arg130, Arg166, Lys207. These positively charged residues are conserved in the sulphite/nitrite reductase family. In addition, 4 Cys residues are conserved for iron-sulphur binding. </p>
+
      <p>The most profound structural differences between the two enzymes are found in the ferredoxin binding site and SirA's most C terminal residues and several surface loop regions due to deletions or insertions. A stark difference is a covalent bond formed between Cys161 (thiolate) and Tyr69 (C carbon atom) found adjacent to the redox center (Cu ions) in SirA. The covalently bound residues act as a secondary cofactor in tyrosyl radical stabilization. </p>
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    </div>
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    <div class="rightparagraph">
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      <center><a href="https://static.igem.org/mediawiki/2013/5/52/Purplecys_SirA-1.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/5/52/Purplecys_SirA-1.png" width="267.5px"/></a></center>
+
      <p><b>Figure 3: The superimposed 3D protein structures of SirA and CysI.</b><div style="font-size: 90%"> 303 amino acids are involved in superimposition with an rsmd of 1.41Å. All domains and loops of CysI are coloured purple, whilst SirA is coloured according to structural similarity with CysI: Red indicates poor alignment whilst blue indicates good alignment.</div></p>
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    </div>
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    <h2>Identification of potential drug target binding sites</h2>
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    <div class="leftparagraph">
+
      <p>&nbsp;&nbsp;
+
Our structural analysis provided the basis for our drug target prediction. Using Chembl and swiss pdb, we have shown a predicted drug target site. Our calculation gives strong favour for a drug to be effective at this site. The calculation reflects the suitability of small molecules to the binding site under the Lipinski's Rule of 5.</p>
+
      <p>The drug target is located at the interface of the three domains. This binding pocket exhibits a dense hydrophobic region. Our analysis targets 48 amino acids of SirA within 6Å of a modelled small drug molecule. Of these residues, only 6 amino acids are charged: His409, Asp453, Asp474, His500, Asp504 and Arg541.
+
      </p>
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    </div>
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    <div class="rightparagraph">
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      <center><a href="https://static.igem.org/mediawiki/2013/5/59/Drug_target_withoutAA.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/5/59/Drug_target_withoutAA.png" width="267.5px"/></a></center>
+
      <p><b>Figure 4 Drug target locations in SirA </b><div style="font-size: 90%">A domain located in SirA, identified as a drug target through Chembl analysis.</div></p>
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    <h2>Structure based pharmacophore modelling of mycobacterial Fpra</h2>
+
    <div class="leftparagraph">
+
      <p>&nbsp;&nbsp;
+
Using LigandScount 3.1, we searched over 8100 drug compounds from the BindingDB and Chembl databases for drugs targetting mycobacterial Fpra. Our search revealed Riboflavin (Vitamin B2) and Pyridoxine to be drug targets for Fpra. We used NADP interacting with the active site as the model of the pharmacore. Results showed pyridoxin to be a competitive inhibitor to NADP. Pyridoxin is a synthetic compound currently available as a prescribed drug. </p>
+
      <p>Chembl analysis of Pyridoxine (vitamin B6) show that it's properties fulfill Lipinski's criteria of being an orally active drug in humans. These properties state that any small drug molecule must have:  no more than 5 H bond donors, no more 10 H bond acceptors (N or O atoms), mol mass of less than 500 dalts and octanol-water partition coefficient log P of no greater than 5).</p>
+
      <p>We have shown the proposed properties of Pyridoxine's interaction with Fpra as a competitive inhibitor to NADP at Fpra's active site. The key amino acids at the active site are Ala205, GLN204 and Thr208. GLN204 and Ala205 act as hydrogen bond acceptors whilst Thr208 interacts with a H via van der waals forces. Pyridoxin is a smaller, more lipid soluble molecule than NADP, thus more fitting to Lipinski's criteria. </p>
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    </div>
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    <div class="rightparagraph">
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      <center><a href="https://static.igem.org/mediawiki/2013/4/42/PB_Fnr_ribbons3.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/4/42/PB_Fnr_ribbons3.png" width="100%"/></a></center>
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      <p><b>Figure 5: </b><div style="font-size: 90%">Our 3D model shows the structure of FNR where negative residues are coloured in blue, positive residues in red and NAD in purple (ball and stick representation). The key amino acids at the active site are Glu211, Gly 366, Arg 110, Arg 199, Arg 200 and Asn155. Glu211 acts as a hydrogen acceptor whilst the latter four residues act as hydrogen donors.</div></p>
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      <center><a href="https://static.igem.org/mediawiki/2013/0/0a/PB_picture16.15.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/0/0a/PB_picture16.15.png" width="100%"/></a></center>
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      <p><b>Figure 6:</b></b><div style="font-size: 90%"> The interaction of Pyridoxine to its active site residues.</div> </p>
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    <div id="Design"></div>
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    <h2>Synthetic Mycobacteria Pathway</h2>
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    <div class="leftparagraph">
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      <p> &nbsp;&nbsp;
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We designed a synthetic <i>M.smegmatis-</i> derived sulfite reduction pathway containing sirA - the sulfite reductase, and two supporting genes that are required for its function in <i>E.coli</i>: fdxA and fprA. FdxA is a mycobacterial Ferredoxin cofactor which is oxidised by SirA during the sulfite reduction reaction and FprA is a Ferredoxin-NADPH reductase use replenish the reduced Fdx pool. The genes' sequences were taken from previous work describing their expression <a href="#Reference">(Pinto <i>et al</i> 2007)</a> in <i>E.coli</i> for purification and in vitro characterization; we removed restriction sites and codon optimized for expression in <i>E. coli</i>. The genes were then cloned into two Duet expression vectors, one containing sirA and one containing the supporting genesand were transformed into our knock-out mutant strains of <i>E. coli</i>. Data on Growth curves can be found <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook#target_Monday_30th_September.html">here</a>.
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      <a href="https://static.igem.org/mediawiki/2013/8/84/TB_drug_FinalSmeg.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/8/84/TB_drug_FinalSmeg.png" width="535px"/></a>
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      <p><b>Figure 7: Growth curves of <i>E. coli</i> mycoSIR</b> <div style="font-size: 90%">BL21 (DE3) ΔcysI containing the MycoSIR pathway (MycoSIR <i>E. coli</i>) were grown in liquid minimal media containing Various concentration of IPTG. (A) Replicates of each strain were measured for absorbance in a spectrophotometer every 10 minutes for 14 hours. Growth was observed for the WT BL21 <i>E. coli</i>, (blue), and the MycoSIR <i>E. coli</i> (red). No growth was detected for uninduced MycoSIR <i>E. coli</i> (purple) or for the BL21 (DE3) ΔcysI that did not contain the synthetic pathway (Orange) . (B) Mean Final ODs of all replicates, measured after 14 hours of growth. Growth was detected in zmSIR <i>E. coli</i> and WT BL21 but not in uninduced zmSIR strain.</div></p>
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    <h2>Creation of Knock out Mutants</h2>
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    <div class="leftparagraph">
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      <p>&nbsp;&nbsp;
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We prepared two strains of <i>E. coli</i> which have the sulfite reduction pathway deleted: BL21 (DE3) <i>ΔCysI Δfpr ΔydbK</i> and BL21 (AI) <i>ΔCysI</i>. CysI is responsible for sulfite reduction in <i>E. coli</i>, while <i>fpr and ydbK</i> are two non-essential genes that consume ferredoxin. These two genes are deleted, as sulfite reduction in mycobacteria is ferredoxin dependent in comparison to<i> E. coli</i> in which it is NADPH dependant. These genes were also removed to ensure that they do not interfere with our system.
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    <div class="rightparagraph">
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    <h2>Synthetic Corn Pathway</h2>
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    <div class="leftparagraph">
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      <p>&nbsp;&nbsp;
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Additionally we prototyped the system with a reconstruction of a sulphite reduction pathway previously designed and published by the silver group <a href="#Reference">(2011 Barstow et al)</a>. In place of CysI, a corn (Zea mays) derived sulfite reductase (zmSIR) was used. Two additional genes were included: Spinach ferredoxin (soFD),  and  corn derived ferredoxin NADP+ reductase (zmFNR). These genes, respectively, are required for production of the ferredoxin cofactor and the NADP+ ferredoxin reductase and are required for sulfite reductase (zmSIR) to function within <i>E. coli</i>.
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      <a href="https://static.igem.org/mediawiki/2013/a/a2/PB_final_Corn.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/a/a2/PB_final_Corn.png" width="535px"/></a>
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      <p><b>Figure 8:</b> Growth curves of <i>E. coli</i> maizeSIR<div style="font-size: 90%"> BL21 (DE3) ΔcysI containing the MaizeSIR pathway (MaizeSIR <i>E. coli</i>) were grown in liquid minimal media containing Various concentration of IPTG. (A) Replicates of each strain were measured for absorbance in a spectrophotometer every 10 minutes for 14 hours. Growth was observed for the WT BL21 <i>E. coli</i>, (blue), and the MaizeSIR <i>E. coli</i> (red). No growth was detected for uninduced MaizeSIR <i>E. coli</i> (purple) or for the BL21 (DE3) ΔcysI that did not contain the synthetic pathway (Orange) . (B) Mean Final ODs of all replicates, measured after 14 hours of growth. Growth was detected in zmSIR <i>E. coli</i> and WT BL21 but not in uninduced zmSIR strain.</div></p>
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    <div id="Results"></div>
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    <h2>Results</h2>
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    <div class="leftparagraph">
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      <p>&nbsp;&nbsp;
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Upon successful cloning of the three genes into our <i>E. coli</i> deletion strain, we continued to confirm that all three genes are required for growth on minimal media. Our two synthetic pathways were found to rescue growth on a sulfurless amino acid supplemented minimal media.  We hope that this technique of using synthetic biology to overcome problems faced in naturally occurring systems will be both a large boon to the pursuit of finding novel drug candidates in <i>M. tuberculosis</i> and more broadly as this technique can be used for high-throughput screening of any pathway that can be constructed to be essential for growth in <i>E. coli</i>.
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      </p>
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      </br>
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      <p><b>Figure 9:</b> Growth of zmSIR <i>E. coli</i> on minimal media. <div style="font-size: 90%">BL21 (DE3) ΔcysI cells transformed with 1, 2 and 3 genes of the 3-gene zmSIR synthetic pathway were grown for 24 hours on minimal media supplemented with 25 uM IPTG (see methods), along with a WT BL21 (DE3) serving as a negative control, and an untransformed BL21 (DE3) ΔcysI, as negative control. Rescue of growth required all genes of the synthetic pathway (SIR, FNR and FD). </div></p>
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      <a href="https://static.igem.org/mediawiki/2013/8/85/PS_D_Figure1_plate.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/8/85/PS_D_Figure1_plate.png" width="535px"/></a>
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    <h2>Z-score</h2>
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     <div class="leftparagraph">
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      <p>&nbsp;&nbsp;
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The Z-score is a statistical measurement aimed at assessing the "hit effect" in a drug screen high throughput screening. It is a commonly used measurement that shows how well did the drug effect the growth of the assay strain and how significant is the decrease in growth.</p>
+
      <p>
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To calculate the Z-score we used our experimental <i>E. coli</i> strain BL21 (AI) ΔcysI that carries all three genes of the synthetic pathway (sirA, fprA, fdxA). We grew it in the M9 minimal media supplemented with amino acid sulfur dropout powder, in a 96 well plate.  Four of the wells were "spiked" with antibiotics (Amp, Gent, Kan, and Spect). </p>
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    </div>
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    <div class="rightparagraph">
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      <p>&nbsp;&nbsp;
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This served as a simulation of the drug screen without the actual drug library. Only the drug screen controls are used: growth in M9 as a negative control (no drugs) and growth in M9 + antibiotics as a positive control (a sure hit). We then compared the distribution of the growth (OD) in the negative control with the distribution of growth (OD) in the positive control. The Z-score shows the distance of the negative control mean from the positive control mean in negative control standard deviation units.</p>
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      <p><b>Our Z-score is: -10.2.</b></p>
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    <h2>Z-factor</h2>
 
    <div class="leftparagraph">
 
      <p>&nbsp;&nbsp;
 
Z-factor is a measurement complementary to the Z-score. It measures the assay's quality based on the same data  extracted from the same experiment made for the Z-score. This calculation gives an estimation of how far the negative controls are from the positive controls. It is a comparison of the two distributions which assumes that both distributions are normal and calculate how far 99% of the data points of each distribution are from each other.</p>
 
     
 
    </div>
 
    <div class="rightparagraph">
 
      <p>&nbsp;&nbsp;
 
Z-factor is given on a scale from 0 to 1. Scores between 0.5 and 1 show that the assay is good and will enable testing in High throughput screens.</p>
 
      <p><b>Our Z-factor score is 0.58.</b></p>
 
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    <h2> MycoSir growth assays reveal the potential anti TB activity of Pyridoxine </h2>
 
  
    <div class="leftparagraph">
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      <p>&nbsp;&nbsp;Motivated by the results of our computational analysis, we attemped to use MycoSIR <i>E. coli</i> to assay the activity of pyridoxine, our candidate FprA inhibitor and a potential anti-TB compound. Briefly, we added both pyridoxine and a control compound, riboflavin, to growing cultures of both WT <i>E. coli</i> and MycoSIR <i>E. coli</i>. In all cases, cells were grown in minimal media, where our previous  work demonstrates that the MycoSIR pathway is essential for viability.
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      <p>&nbsp;&nbsp;Our growth assays indicate that pyridoxine, at high doses, specifically inhibits the growth of MycoSIR <i>E. coli</i> and therefore acts specifically on the mycobacterial sulfur pathway. While the observed affinity is low, it could in principle be expanded through derivitivizaion and further screening.
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These results indicate that our MycoSIR <i>E. coli</i> are a practical tool for measuring drug activities. We have ordered several small drug libraries to assay with our strain, and we look forward to finding more candidate anti-TB drugs!</p>
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    <div class="leftparagraph">     
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      <center><a href="https://static.igem.org/mediawiki/2013/d/d5/PB_RiboflavinData.png"><img width="80%" src="https://static.igem.org/mediawiki/2013/d/d5/PB_RiboflavinData.png"/></a></center>
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      <p><b>Figure 10:</b>Riboflavin has no effect on the growth of WT or synthetic MycoSIR <i>E. coli.</i><div style="font-size: 90%"></div> The indicated quantities of riboflavin were dissolved in water and added to cultures of WT or MycoSIR <i>E. coli</i> in 4 biological replicates. No significant growth effects were observed. </p>
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    <div class="rightparagraph">
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      <center><a href="https://static.igem.org/mediawiki/2013/8/86/PyridoxineData.png"><img width="80%" src="https://static.igem.org/mediawiki/2013/8/86/PyridoxineData.png"></a></center>
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      <p><b>Figure 11:</b> MycoSIR <i>E. coli</i> growth assays reveal a potential anti-TB acitivity of pyridoxine at high doses. <div style="font-size: 90%"> The indicated quantities of pyridoxine were dissolved in water and added to cultures of WT or MycoSIR <i>E. coli</i> in 4 biological replicates. Both strains were grown in defined minimal media, where MycoSIR <i>E. coli</i> require our synthetic pathway for growth. Low pyridoxine doses had no detectable effects. However, a very high dose of pyridoxine (10 mg/mL) substantially inhibited the growth of MycoSIR <i>E. coli</i> yet showed no effect on WT growth.  This suggests pyridoxine  specifically inhibits the activity of the Mycobacterial SirA pathway.  Derivativization or other methods could be used to further enhance the affinity and specificity of this compound.</div> </p>
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<h2>High throughput screening : 10 new potential drug candidates</h2>
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    <div class="leftparagraph">
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      <p>&nbsp;&nbsp;
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Using MycoSirA we performed a high throughput drug screening. We screened two libraries from the NIH, Diversity Set IV and Natural Product Set II. <br>
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Good drug candidates are the ones in which wild type <i> E. Coli </i> grow well but not <i> MycoSirA </i>. We found 10 compound which ODs  differ clearly from the general distribution (Fig 12). Their Z-Score are all higher than 3. Those ten compounds are potential new drug candidates.<br>
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Among those 10 potential drug candidates, six share structural similarities. Those structural similarities are also shared with pyrodoxine.
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      </p>
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    </div>
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    <div class="rightparagraph">
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      <a href="https://static.igem.org/mediawiki/2013/a/a2/PB_final_Corn.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/c/c2/Capture_d%E2%80%99%C3%A9cran_2013-11-07_%C3%A0_13.48.14.png" width="535px"/></a>
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      <p><b>Figure 12</b> High throughput drug screening performed on the library "NIH Diversity Set IV". <b> A.  </b>Scatter plot ; in red, compounds that differ from the general distribution : low growth for MycoSiRA, normal growth for E; Coli <b> B.  </b> OD Ratios of all the tested compound and the best candidates..</div></p>
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    <div id="Reference"></div>
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    <h2>Literature</h2>
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    <div class="leftparagraph">
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      <ul>
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<li>Global Alliance for TB Drug Development, Tuberculosis. Scientific blueprint for tuberculosis drug development, Tuberculosis (Edinb) 81 Suppl 1, 1–52 (2001).</li>
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<li>World Health Organization, Global Tuberculosis Report 2012 (2012).</li>
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<li>K. Raman, K. Yeturu, N. Chandra, targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis, BMC Syst Biol 2, 109 (2008).</li>
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<li>R. Pinto, J. S. Harrison, T. Hsu, W. R. Jacobs, T. S. Leyh, Sulfite Reduction in Mycobacteria, Journal of Bacteriology 189, 6714–6722 (2007).</li>
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<li>B. Barstow C. M. Agapakis, P. M. Boyle, G. Grandl, P. A. Silver, E. H. Wintermute, A synthetic system links FeFe-hydrogenases to essential E. coli sulfur metabolism, J Biol Eng 5, 7 (2011).</li>
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      </ul>
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    </div>
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    <div class="rightparagraph">
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      <ul>
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<li>Schellenberger J, Que R, Fleming RMT, Thiele I, Orth JD, Feist AM, Zielinski DC, Bordbar A, Lewis NE, Rahmanian S, Kang J, Hyduke DR, Palsson BØ. 2011 Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nature Protocols 6:1290-1307.</li>
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<li>Schellenberger, J., Park, J. O., Conrad, T. C., and Palsson, B. Ø., BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions, BMC Bioinformatics, 11:213, (2010).</li>
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<li>S. G. Franzblau et al., Comprehensive analysis of methods used for the evaluation of compounds against Mycobacterium tuberculosis, Tuberculosis 92, 453–488 (2012).</li>
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<li>D. J. Payne, M. N. Gwynn, D. J. Holmes, D. L. Pompliano, Drugs for bad bugs: confronting the challenges of antibacterial discovery, Nat Rev Drug Discov 6, 29–40 (2006).</li>
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<li>M. Nakayama, T. Akashi, T. Hase, Plant sulfite reductase: molecular structure, catalytic function and interaction with ferredoxin, J. Inorg. Biochem. 82, 27–32 (2000).</li>
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    <h2>Attributions</h2>
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      <ul>
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<li>Strains NEBTurbo, BL21 (DE3) KO20, BL21 AI were provided by INSERM U1001.</li>
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<li>Plasmids pET Duet, pACYC Duet, pACYC zmSIR, pACYC soFD zmSIR, pCDF FNR were provided by INSERM U1001.</li>
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      </ul>
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    </div>
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      <ul>
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<li>Genes msSirA, msFprA, msFdxA were synthesized by IDT.</li>
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<li>Project was designed by Idonnya Aghoghogbe, Yonatan Zegman, Matthew Deyell and Edwin Wintermute.  All experiments and modelling were performed by Idonnya Aghoghogbe, Yonatan Zegman, Matthew Deyell. </li>
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Latest revision as of 03:51, 20 October 2016


Goals

  • To screen soil samples from around the world for microbes that naturally degrade anthocyanin.
  • To identify enzymes linked to the most efficient anthocyanin eaters.

Results

  • We collected species from all around the world through iGEM collaborations.
  • 186 bacteria were tested for degradation of quercetin.
  • 174 bacteria were identified by 16s rRNA sequencing.
  • 4 promising species were selected for whole genome sequencing.
  • Candidate enzymes were identified from genome sequence, and passed to the enzyme group.

Methods

  • Microbe cultivation
  • Anthocyanin purification
  • Anthocyanin & quercetin measurement
  • 16S rRNA sequencing
  • Whole genome sequencing
  • Phylogenetic analysis

Abstract

Anthocyanins, the key pigments found in red wine, are abundant in grapes, berries, flowers and many plants. Like all naturally ocurring metabolites, they eventually biodegrade and re-enter the carbon cycle. In this project, we search nature for enzymatic pathways that can break down anthocyanins into simpler, unpigmented molecules. We reasoned that microbes living in the soil near vineyards were likely to catabolize and consume anthocyanin. Therefore we collected soil samples from 10 vinyards around France, Europe and the world, notably with the help of our fellow iGEM teams. In total we isolated 186 strains through selective and non-selective plating on different media. All of the strains were identified by 16s rRNA sequencing, then characterized for their ability to degrade quercetin, a compound structurally similar to anthocyanin. By phylogenetic analysis, we were able to connect quercetin degradation to specific bacterial phyla and genus including Micrococcus, Pseudomonas, Lysinibacillus and Oerskovia. The most effective strains were further characterized by whole genome sequencing to identify enzymes linked to natural quercetin degradation. By bioprospecting with the help of the worldwide iGEM community, we were able to find the best stain fighting enzymes that nature has to offer.

Motivation and Background

Bioprospecting and Bioremediation

Bioprospecting is the process of searching nature for genetic information that can be adapted in useful or profitable ways. In recent years, bioprospecting efforts have focused on the search for small molecule pharmaceuticals and other bioactive compounds (Müller, 2016). Bioremediation is the use of living organisms to remove environmental toxins from contaminated areas. Microbes in particular are well known for their ability to degrade organic pollutants like petroleum, pesticides and phenolic compounds. Bioremediation has always been a popular topic in iGEM, producing many notable projects with diverse organisms and applications.


Anthocyanin is not harmful, but in the context of a stain it is unwanted and so could be considered a target for bioremediation. Therefore a mechanism to degrade anthocyanin could be revealed with a classic bioremediation strategy :

  1. Select organisms from a contaminated environment, where enzymatic decontamination may have naturally evolved.
  2. Isolate pure strains and measure their activity.
  3. Connect the activity to specific pathways using molecular genetics.

Anthocyanidin and quercetin

In these experiments, we use quercetin as a chemical proxy for anthocyanins. Naturally occurring anthocyanidins are chemically diverse derivatives of a a core flavylium cation. Plant sources of anthocyanidin carry a range of anthocyanidin pigments substituted at any of up to seven positions, with the relative concentrations contributing to a characteristic color. Pure anthocyanidins, like malvidin, are expensive (120 EUR for 1 mg) and do not necessarily represent the full chemical diversity of a natural wine stain. Therefore, in this work we use quercetin, a flavonol, as a structural proxy. Quercetin is cheap (40 EUR for 10 g), stable, and can be quantified by absorbance at 315 nm. In follow up experiments, microbes are tested on real wine and on bulk anthocyanins that we extract directly from grape skins.

Quercetin strains degradation

Figure 1 Structure and absorbance of malvidin, the most abundant anthocyanidin in wine, and quercetin, a flavonol.

All flavonoids are structured as two phenyl rings and a heterocyclic ring. Anthocyanin itself is structured as a chromane ring with an aromatic ring on C2. Cyanindin and malvidin comprise 90% of the anthocyanins found in nature. These chemicals differ only in their cyclic B groups, and the chromane ring is well conserved in most flavonoids. Therefore, we theorized that the chromane ring itself presented an ideal target for degradation.
Based on these criteria, we chose the flavanol quercetin as our anthocyanin substitute. This molecule differs from anthocyanins only in the presence of a carbonyl group. Additionally, quercetin is present in wine, and contributes to its color. Thus, even in the case where enzymes are isolated that break down quercetin and not anthocyanin, the possibility exists of reducing the color or intensity of wine stains.
Finally, co-pigmentation chemical interactions occur between anthocyanin and quercetin, increasing wine color stability, mainly through π-π stacking between their phenolic cycles. Thus, it leads to the possibility that quercetin degradation could also impact anthocyanin stability.

Results

Anthocyanin Extraction and analysis

Anthocyanins were extracted from Vinis vitifera fruits. It skin was separated from the rest of the fruit and macerated overnight in an ethanol solution with 1% chloridric acid. After maceration, the solution was passed through with a paper filter to eliminate solid material and evaporated at 37°C at 150 rpm. We confirmed the presence of anthocyanin with HPLC and, colour variation with pH.

Collection of the soil samples

Soil samples were collected from France, Spain, Croatia, Namibia and Australia. Samples from the Paris region were collected by members of our team. Other samples were sent by friends, family members, and collaborating iGEM teams. Soil samples were declared to French customs authorities with a Facture Proforma, printed out by the sample donor and included in the shipment.
Upon arrival, samples were washed gently with phosphate-buffered saline (PBS) solution, then left to stand, allowing large particles to settle. The resulting eluate was diluted further with PBS then used directly as a source of soil microbes.

Country Location Collector
France Clos Monmartre Vineyard, Paris Our Team
France Cochin Port Royal, Paris Our team
France Vaucluse region’s vineyard INSA-Lyon iGEM team
Spain Barcelona UPF-CRG Barcelona iGEM team
Spain Utiel Requena UPV Valencia iGEM team
Australia Hunter Valley UNSW
Australia Sydney Macquarie 2016 iGEM team
Namibia Etosha National Park Our team
Algeria Alger Our team
Croatia Kricke Our team
Israel Jerusalem Our team
world_Microbiome

Figure 2 Location of soil samples
collected or obtained by the team.

Preparation of the microbe library

For safety and to avoid environmental contamination, microbial isolation was performed in a fume hood in a BSL 2 facility. More safety information in provided on our safety page.
Microbes were isolated from soil samples using either selective or nonselective plating. For the selective plating, M9 agar was supplemented with either quercetin alone or quercetin with glucose to enrich for microbes with the ability to metabolize quercetin.
The resulting culture was incubated at 30 C for 48 hours, then re-streaked to eliminate potential contamination.
To maximize library diversity, we preferentially chose colonies with unique morphologies. After isolation, we performed colony PCR with universal 16s rRNA primers (see methods). Sequencing the resulting PCR products allowed us to identify the strains and position them within the greater bacterial taxonomy.

Quercetin degradation assay

Each of the 189 isolated strains was innoculated into M9 quercitin medium in triplicate and incubated at 37 C for 6 days. At the end of the period, quercitin concentration was measured by absorbance.

Of 186 strains tested, 50 produced quercetin levels significantly lower than controls (Figures 3 and 4). 20 strains degraded more than 50% of quercetin and 2 strains degraded more than 80%.
Both selective and nonselective plating methods were able to produce quercetin-degrading strains. 4 of the 5 strains showing the most quercetin degradation were obtained by selective plating.
However, 40 of the 50 strains showing significant degradation were obtained by nonselective plating.


Quercetin strains degradation

Figure 3 Quercetin degradation by 186 microbes collected from global soil samples. Single colonies were inoculated in M9 minimal medium and grown for 6 days. Quercetin was measured by absorbance. Strains to the extreme left of the figure represent the highest-degrading strains. Red bars represent strains isolated from selective media and blue from non selective media.

Quercetin degradation detail

Figure 4 Quercetin degradation detail. The top-performing strains included those isolated from both selective and nonselective media. Strains marked with an asterisk were selected for further investigation. Red bars represent strains isolated from selective media and blue from non selective media.

Working with M9 quercetin plates can be challenging. The bright green color of the plates makes colony visualization difficult.
Indeed, only fungal mycelia were visible due to a white halo resulting from quercetin degradation. However, working with liquid media allows the control of residual sample carbon source contamination through sample dilution.
Additionally, we were concerned agar in plates could be used as a carbon source.

8 top-performing strains were selected for detailed valication in a time-course assay, and all were able to degrade quercitin significantly better than E. coli negative controls.
We observed a 50% degradation over 6 days in the best case.

Quercetin degradation detail

Figure 5 Kinetics of quercetin degradation by 8 promising strains. This experiment had two negative controls, one with no bacteria (black line) and one with non-quercetin degrading E. coli. Pseudomonas putita was included as a positive control. Four strains, shown in bold, degraded quercetin at a higher rate than our P. putida control.

Phylogenetic analysis of quercetin degradation

Using the 16s rRNA sequences, we constructed a global phylogeny of all the assayed strains (Figure 6).
Quercitin-degrading activity was concentrated among the Pseudomonas genus, where most of the strains were positive.
However many diverse species were able to significantly degrade quercitin, suggesting that the phenotype may be highly variable in evolution.

Quercetin degradation detail

Figure 6: Phylogenetic Tree of isolated strains. We constructed a phylogenetic tree of all isolated bacterial strains. Strain taxonomic classification is indicated by the color key to the left of the figure. Strains that demonstrated high quercetin degradation are marked with an asterisk. Those strains marked with a large star were selected for whole genome sequencing to look for common anthocyanin-degrading genes.

Mining genomes for quercetin-degrading enzymes

Four of our top-degrading strains, representing diverse phylogentic lineages, were selected for whole genome sequencing.
As of the wiki freeze, the genome sequences were not complete. So, as a proxy, we obtained complete genome sequences of their nearest relatives in GenBank.
BLAST searches against the genomes revealed the presence of several candidate quercitin-degrading enzymes, including laccase and XylE.

The results of these genomic analysis were passed to the enzyme group, where these enzymes form the basis of our synthetic stain fighting product.

Genome Table

Figure 7: Genome table. Genome sequences were analyzed for the presence of potential anthocyanin degrading enzymes as identified in the Enzymes Project. The genes of at least one of the six candidates were identified for each of the sequenced strains. The number of + signs indicated represent the number of gene copies in the bacterial genome.




Methods

Anthocyanin extraction

Vinis vitifera grapes were our source for anthocyanin extraction.
Grapes were peeled and the skins were collected, washed and soaked overnight in ethanol with 1% HCl.
By trial and error, we determined that 2.5 mL of this solution per 1 g of skins was the best compromise between efficiency and the quantity of solvent used.
The solution was filtered with Whatman paper, with the filtrate collected, and the solvent evaporated at 37°C for several hours.
The dry extract was resuspended in water (10 mL for 1g of grape skin).

Anthocyanin quantification by differential absorbance

Following Lee et al. (2005), we prepared one buffer at pH 1 (0.025M potassium chloride) and a second at pH 4.5 (sodium acetate, 0.4M).
100 µL of the anthocyanin solution was mixed with 900µL of each buffers and the color was allowed to develop over 20 minutes.
Absorbance measurements were obtained at 510 nm and 700 nm for each solution.
Anthocyanin concentration was determined as a function of the four absorbance measurements, using an established formula (Lee et al., 2005).

Protein quantification with Bradford assays

A stock solution of Bovine Serum Albumin (BSA) was prepared in water at 1 mg/mL.
100 μL of standard dilutions of BSA solution were mixed with 1 mL of Bradford Reagent and mixed by vortexing.
Absorbance was measured at 595 nm. Experimental samples were treated similarly and compared to the BSA standard curve to determine concentration.

Carbohydrate quantification with Fehling Reaction

200µL of Fehling's A solution, 200µL of Fehling's solution B and 200µL of our carbohydrate solution into sodium acetate buffer (20µL of solution and 180 µL of buffer).
The Fehling reaction is measured as the loss of absorbance at 650nm relative to a blank solution without carbohydrate.
Quantification was achieved by comparison to a standard curve of glucose prepared at 1g/L to 5g/L.

Bacteria plating on selective and non-selective media

1 g of soil samples were suspended in 5 mL Phosphate Buffered Saline (PBS) then left to stand allowing large particles to settle.
The soil suspension was serially diluted to obtain a suitable density of microbes (typically 1:1000) then 200 µL was plated on standard Petri dishes with M9 agar with 1 g/L quercetin for selection.
Non-selective plating was performed on a range of rich media including FTO agar (Curry, 1976), Mossel agar (Mossel, 1967), standard LB, standard TSA and standard M9 glucose.

Protocol for growth assay in Quercetin M9 liquid media

Following the protocol of Dantas et al. 2012, all step were performed in liquid media to control soil carbon source contamination.
We suspended soil samples in 5 ml M9 with 1g/L quercetin at pH 7 in 50 ml Falcon tubes with 500µL of overnight culture of strains isolated from selective or non-selective plates.

All cultures were made in triplicate at 30°C with shaking at 150 rpm for several days. As quercetin is not soluble at pH=7, shaking important to avoid precipitation.

Quercetin absorbance measurement

Quercetin absorbance was measured at two time points for histogram construction: at 0 days to ensure quercetin sample concentration consistent with the controls, and at 6 days to evaluate quercetin degradation.
M9-quercetin and Pseudomonas putidaK2440 samples were included as negative and positive controls, respectively.

Prior to absorbance measurement, Quercetin was solubilized by diluting samples 10 fold in 0.5M NaOH, centrifuged to remove cell material, and further diluted 100X for measurement at 315 nm in a Tecan plate reader.

PCR for 16s characterization, sequencing interpretation and phylogenetic tree construction.

To identify bacterial strains, 16S rRNA sequences were amplified through colony PCR, column purified, and Sanger sequenced by GATC.
The resulting sequences were submitted for BLAST comparison at ncbi.gov.
Alignments were performed using the Ribosomal Database Project Aligner tool (https://rdp.cme.msu.edu/),
and a phylogenetic tree was constructed using Geneious software with the following parameters: we used Neighbor-Joining tree building with Jukes Cantor as the genetic distance model, with a 93% similarity cost matrix for the alignment with free end gaps.
The tree was then exported and improved using the online Tree of Life software (http://www.tolweb.org/tree/).

PCR for genome sequencing.

We isolated bacterial DNA using the DNeasy Blood and Tissue Kit from Qiagen.
We submitted four strains to GATC for whole genome sequencing: NS.4 (Lysinibacillus), S.48 (Stenothrophomonas maltophilia), S.33 (Oerskovia Paurometabola), NS.33 (Microccocus Luteus) according to their sample preparation specifications.

Attributions

This project was done by Antoine Villa Antoine Poirot and Sébastien Gaultier. Anthocyanin data was obtained by Ibrahim Haouchine.
Thanks to our advisors Jake and Jason for all their help with the figures.
We would like to thank Philippe Morand from the microbiology lab of Cochin for his advice.


References

  • Kanekar, P. P., Sarnaik, S. S., & Kelkar, A. S. (1998). Bioremediation of phenol by alkaliphilic bacteria isolated from alkaline lake of Lonar, India. Journal of applied microbiology, 85(S1).
  • Dantas, G., Sommer, M. O., Oluwasegun, R. D., & Church, G. M. (2008). Bacteria subsisting on antibiotics. Science, 320(5872), 100-103.
  • Lee, J., Durst, R. W., & Wrolstad, R. E. (2005). Determination of total monomeric anthocyanin pigment content of fruit juices, beverages, natural colorants, and wines by the pH differential method: collaborative study. Journal of AOAC international, 88(5), 1269-1278.
  • Curry, J. C., & Borovian, G. E. (1976). Selective medium for distinguishing micrococci from staphylococci in the clinical laboratory. Journal of clinical microbiology, 4(5), 455.
  • Pillai, B. V., & Swarup, S. (2002). Elucidation of the flavonoid catabolism pathway in Pseudomonas putida PML2 by comparative metabolic profiling. Applied and environmental microbiology, 68(1), 143-151.
  • Herrmann, H., Janke, D., Krejsa, S., & Kunze, I. (1987). Involvement of the plasmid pPGH1 in the phenol degradation of Pseudomonas putida strain H. FEMS microbiology letters, 43(2), 133-137.


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