− | }</style><h2>Project - Design - now Proof of concept</h2><p>We aimed to create a fast and easy to use test for the detection of pathogens and plant stress proteins that are expressed after pathogen infections, that is also applicable directly in-field. We decided to go for a <strong>sandwich lateral flow assay</strong> (LFA), but with a twist. Instead of using antibodies that are predominantly used, we use aptamers for target binding <a href="https://2021.igem.org/Team:Duesseldorf/selex">Link to SELEX</a> and gold nanoparticles as our visible output<a href="#citation1">1</a>. <strong>Gold nanoparticles</strong> (AuNPs) in their stabilized form are red and are therefore suitable for an easy read out. Aptamers are single-stranded DNA fragments, generated through the <strong>SELEX</strong> process, that can bind to their target with high specificity. LFAs are not new in the field of detection and are commonly used within medical diagnostics<a href="#citation2">2</a>. The most commonly known examples are pregnancy tests and COVID-19 antigen tests. Nanoparticles themselves were already used in the 19th century and from then on only developed further<a href="#citation2">2</a>. In the medical field, gold nanoparticles are also used as nano-platforms for antibodies and as an easy delivery method for drugs into cells<a href="#citation2">2</a>.</p><p><em>What sets us apart from the already existing methods?</em></p><p>We are using existing parts and bring them together in a new way and with a new field of application: pathogen detection and differentiation. Currently, pathogens can only be differentiated by trained experts, or in special labs, but this takes a lot of time. Additionally both methods can only be used at later stages of infection when symptoms are clearly visible so the plants are already damaged.</p><p>[small sketch?]<br/>For this sandwich LFA, a leaf is taken from the plant that needs to be tested for one or more pathogens. This leaf is ground up and mixed with a suitable buffer that is fitting for the chosen target. It is added to the test device by dripping it onto the sample application pad. If the pathogen or stress protein of interest is present in the sample, it will bind to the aptamer-1 that is part of the AuNP-aptamer-conjugates. The suspension, including the AuNP-aptamer-conjugates and the bound target, flow through the test strip. When they pass the test line, the target will also bind to aptamer-2. Since aptamer-2 is anchored to the test line with a streptavidin-biotin bond, the target serves as a linker between the test line and the gold-nanoparticles. In case this linker is present, a red signal can be observed at the test line. The last line on a LFA is always the control line, which in our case contains a poly-A-tag, which is linked to the membrane with a streptavidin-biotin bond. In a working LFA the control line should always turn red because the complementary poly-T-sequence is part of the AuNP-aptamer-conjugates and binds to the poly-A-tag. If the control line is not red, the test is faulty and not reliable anymore<a href="#citation3">3</a>.</p><p>We first established the protocols needed for our test with known aptamers for thrombin to be able to implement our newly generated aptamers later on<a href="#citation4">4</a>. In addition to this we also researched and selected potential pathogen-induced protein candidates to use in the SELEX process to generate aptamers for our test. These were: F6'H1, FMO1, PAD3, PR1 and UGT74F2. They are all genes from <em>Arabidopsis thaliana</em> and homologs can be found in other plant families. For us, they were only potential candidates for the SELEX process that we ended up not using for now. F6'H1 or 2-oxoglutarate (OG)- and Fe(II)-dependent dioxygenase, is required for H2O2 induced programmed cell death, which is part of the plant's stress response to pathogens. It is also involved in the scopoletin synthesis. Scopoletin is a coumarin derivative. It also is involved in the response to iron ion starvation<a href="#citation5">5</a><a href="#citation6">6</a>. FMO1, Flavin-dependent monooxygenase 1, can confer a salicylic acid-dependent resistance to virulent pathogens. It catalyzes the hydroxylation of pipecolic acid to N-hydroxypipecolic acid, which acts as a long distance signal and induced systemic aquired resistance<a href="#citation7">7</a>. PAD3, phytoalexin deficient 3, is a Cytochrome P450 enzyme that catalyzes the conversion of dihydrocamalexic acid to camalexin<a href="#citation8">8</a>. PR1, pathogenesis-related gene 1, is induced as a response to a variety of pathogens and can function as a molecular marker for SAR (systemic acquired resistance) response<a href="#citation9">9</a>. UGT74F2, UDP-glycosyltransferase 74F2 binds specifically to the molecular chaperone HSP90 and is suggested to play a role in Resistance protein folding<a href="#citation10">10</a>.</p><p><em>Further information can be found here: PROTEAM.</em></p><h2>Conservation of proteins in different plants</h2><p>To get an overview if the selected proteins could be potential targets in multiple plants, we made a sequence comparison via BLAST. The amino acid sequences from Arabidopsis thaliana were run through BLAST on Phytozome<a href="#citation11">11</a> then aligned by Ebi's Clustal Omega multiple sequence alignment tool<a href="#citation12">12</a> and the phylogenetic trees were made with Phylogeny<a href="#citation13">13</a>. Phylogenetic trees for F6'H1, FMO1, PAD3, PR1, UGT74F2 paralogs in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to e.g. 0.5 = 50% difference in compared protein sequences.</p><div class="image"><img alt="Phylogenetic trees for F6'H1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 40% difference in compared protein sequences." src="https://static.igem.org/mediawiki/2021/f/fa/T--Duesseldorf--img--F6%27H1.png" style="width: 100%"/><p>Figure 1: Phylogenetic trees for F6'H1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 40% difference in compared protein sequences.</p></div><div class="image"><img alt="Phylogenetic trees for FMO1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 50% difference in compared protein sequences." src="https://static.igem.org/mediawiki/2021/8/8b/T--Duesseldorf--img--FMO1.png" style="width: 100%"/><p>Figure 2: Phylogenetic trees for FMO1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 50% difference in compared protein sequences.</p></div><div class="image"><img alt="Phylogenetic trees for PAD3 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 30% difference in compared protein sequences." src="https://static.igem.org/mediawiki/2021/c/cb/T--Duesseldorf--img--PAD3.png" style="width: 100%"/><p>Figure 3: Phylogenetic trees for PAD3 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 30% difference in compared protein sequences.</p></div><div class="image"><img alt="Phylogenetic trees for PR1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 20% difference in compared protein sequences." src="https://static.igem.org/mediawiki/2021/4/44/T--Duesseldorf--img--PR1.png" style="width: 100%"/><p>Figure 4: Phylogenetic trees for PR1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 20% difference in compared protein sequences.</p></div><div class="image"><img alt="Phylogenetic trees for UGT74F2 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 50% difference in compared protein sequences." src="https://static.igem.org/mediawiki/2021/e/ec/T--Duesseldorf--img--UDP.png" style="width: 100%"/><p>Figure 5: Phylogenetic trees for UGT74F2 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 50% difference in compared protein sequences.</p></div><div class="card"><p>As expected, the sequences from <em>Brassica oleracea capitata</em> for all selected proteins were the most similar ones to the ones from <em>Arabidopsis thaliana</em>. They are both part of the <em>Brassicaceae</em> family and are therefore more closely related than the other plants. The sequences of <em>Physcomitrella patens</em> were always the most distant ones. Several of the plants have promising sequence similarities, which could imply that these proteins have similar structures and surfaces. The next step would be to test out if the aptamers created for the <em>Arabidopsis thaliana</em> proteins can bind to conserved proteins from other families as well.</p><h2>LFA - Lateral flow test</h2></div><div class="card"><h3>Sample application pad</h3><p>The first part of the LFA consists of a nitrocellulose membrane (CFSP173000 Sigma Aldrich). Here the sample is applied as suspension in a suitable buffer. The sample can be a protein in the defense response of the plant or the pathogen itself, the only requirement is that during the SELEX process at least two fitting aptamers (aptamer-1 and aptamer-2) are found for the target protein or pathogen<a href="#citation3">3</a>.</p></div><div class="card"><h3>Conjugate pad</h3><p>The glass-fiber membrane (GFDX083000 Sigma Aldrich) connects the sample application pad and the test-membrane and contains the AuNP-aptamer conjugates. To test our design and to get used to working with LFAs, we used already published thrombin aptamers. The thiolated aptamer-1 is our primary aptamer (aptamer-1: 5'-SH-(CH2)6- AAA AAA AAA AAA AAA GGT TGG TGT GGT TGG-3')<a href="#citation4">4</a>.</p></div><div class="card"><h4>Gold nanoparticles</h4><p>Gold nanoparticles can be synthesized or bought in various sizes. If they are synthesized, HAuCl4 is the main content<a href="#citation3">3</a>. Our gold nanoparticles were ordered and had a diameter of around 15, an OD of 1, were citrate buffered and had a maximum absorbance at 510-525 nm (777137-25ML Sigma Aldrich).</p></div><div class="card"><h4>AuNP-aptamer-1-conjugates</h4><p>AuNP-aptamer-conjugates are aptamers bound to gold nanoparticles through a coordinated bond between the AuNP-surface and thiol groups linked to the aptamers <a href="#citation15">15</a>. The thiol groups have to be activated in order to be able to bind to the AuNPs. This activation can be achieved by adding Dithiothreitol (DTT) and Triethylamine (TEA), DTT reduces the thiol-modified aptamers which activates them and enables them to bind to the AuNPs<a href="#citation16">16</a>. TEA is often used as an alkaline solvent or to bind released acids<a href="#citation17">17</a>. DTT is then extracted with ethyl acetate which forms an organic phase that can be pipetted away. The aqueous phase with the activated aptamers is retained and then added to the AuNPs. Incubating them together causes them to form conjugates. In the end these are gold nanoparticles functionalized with thiolated aptamers.</p></div><div class="card"><h3>Test-membrane:</h3><p>As already mentioned, the following part is a nitrocellulose membrane (CFSP173000 Sigma Aldrich) with two or more lines. The test line or lines, lie closest to the sample application pad. They are formed by streptavidin-biotin-aptamer conjugates bound to the nitrocellulose membrane. Streptavidin and Biotin have one of the highest intermolecular bonds, making them particularly useful for such binding applications<a href="#citation3">3</a>. The control line consists of a Poly-T-biotin-streptavidin conjugate (Sequence: 5'-TTTTTTTTTTTTTTT-BiotinTEG-3')<a href="#citation4">4</a>. The test line, or capture probe, consists of the second aptamer that is biotinylated (aptamer-2: 5'-biotin-AGT CCG TGG TAG GGC AGG TTG GGG TGA CT-3') <a href="#citation4">4</a>. Both were added to the nitrocellulose membrane which was cut into strips that had a size of about 6 cm x 0,5 cm.</p></div><div class="card"><h3>Absorption pad:</h3><p>At the end of the test strip another nitrocellulose membrane (CFSP173000 Sigma Aldrich) is located, to absorb the excess fluid<a href="#citation3">3</a>.</p></div><div class="card"><h3>AuNP-conjugate preparation</h3><p>What worked for us in the end, was to orientate ourselves at the protocol from Yi. Peng et al.<a href="#citation18">18</a>. We heated 100 µM aptamer-1 to 90°C and let them cool down, before we further used them. According to Peng et al. this should help the structure of the aptamers to stay flexible. This is important in order for the aptamers to bind to their target. 99 µl heated aptamers were then used and mixed with a spatula tip SDS and allowed to react for 30 min. at room temperature. We used the SDS as an alternative to TCEP as they are both reducing agents and should help to disrupt the unwanted disulfide bonds between the thiolated aptamers. From this mixture, 10 µl were taken and added to 60 µl AuNPs. This was then again allowed to react for 16 h at room temperature<a href="#citation18">18</a>.</p></div><div class="card"><h3>Streptavidin-Biotin-DNA preparation</h3><p>For our Streptavidin-Biotin-DNA preparation followed the protocol of L. Wang et al. (2011)<a href="#citation19">20</a>: The Streptavidin (Streptomyces avidinii<a href="#citation4">4</a>) is dissolved in 0.01 mM PBS (1mg/ml). 5 µl of the Streptavidin solution gets mixed with 35 µl 5 µM DNA solution (here, aptamer-1 was used) and left at 4 °C for 2h. 60 µl of 0.01 mM PBS is added and the solution is centrifuged at 12.000 rpm with a centrifugal filter (cutoff 30,000) for 5 min to remove the excess DNA. The only alteration we made to this protocol was to spin at 12.000 rpm instead of 6.000 rpm<a href="#citation20">21</a>. The solution gets washed twice with 100 µl 0.01 mM PBS and resuspended in 40 µl of 0.01 mM PBS. It can be stored in the freezer for later use.</p></div><div class="card"><h3>Test assembly</h3><p>Despite minor problems due to the lack of devices for building a reproducible test, we managed to build a prototype of the detection strip. During this assembly process we found out that the thickness of the nitrocellulose membrane (CFSP173000 Sigma Aldrich) is important. With the original thickness of the purchased membrane we had no success in getting proper flow through. We then divided the membrane in half and had a successful flow through. Single parts of the test were not sticking together as expected, so we used lab tape to hold our test-prototype together. We further faced the problem that the AuNPs did not flow through or lost their color after they dried on the glass fiber membrane. We suspect that maybe the concentration of the AuNP-conjugates was not high enough or that during the drying process they require special treatment to prevent them from aggregating<a href="#citation3">3</a>.</p></div><div class="image"><img alt="Our Test-prototype, with the sample application pad, the conjugate pad, the test-membrane, one testline and an absorption pad." src="https://static.igem.org/mediawiki/2021/6/68/T--Duesseldorf--img--teststripe.png" style="width: 100%"/><p>Figure 6: Our Test-prototype, with the sample application pad, the conjugate pad, the test-membrane, one testline and an absorption pad.</p></div><p>TEST How to read results of an LFA (with pictures): positive: two lines negative: one line (only control line) unreliable/invalid no line or more lines than those who were made</p><p><em>The results of our test have plenty of possible applications that can be found here: Link to IMPLEMENTATION.</em></p></article><article id="references"><h2>References</h2><ol><li id="citation1"><p class="author">Zhao, S., Wang, S., Zhang, S., Liu, J., & Dong, Y. (2018).</p><cite>State of the art: Lateral flow assay (LFA) biosensor for on-site rapid detection.</cite><p><span class="journalTitle">Chinese Chemical Letters</span> <span class="journalInfo">29(11), 1567-1577.</span></p><a class="in-text" href="https://doi.org/10.1016/j.cclet.2017.12.008" rel="noopener" target="_blank">CrossRef</a><a class="in-text" href="https://scholar.google.com/scholar?q=State of the art: Lateral flow assay (LFA) biosensor for on-site rapid detection." rel="noopener" target="_blank">Google Scholar</a><a class="in-text" href="#intext1">Back to text</a></li><li id="citation2"><p class="author">Das, M., Shim, K. H., An, S. S. A., & Yi, D. K. (2011).</p><cite>Review on gold nanoparticles and their applications.</cite><p><span class="journalTitle">Toxicology and Environmental Health Sciences</span> <span class="journalInfo">3(4), 193-205.</span></p><a class="in-text" href="https://doi.org/10.1007/s13530-011-0109-y" rel="noopener" target="_blank">CrossRef</a><a class="in-text" href="https://scholar.google.com/scholar?q=Review on gold nanoparticles and their applications." rel="noopener" target="_blank">Google Scholar</a><a class="in-text" href="#intext2">Back to text</a></li><li id="citation3"><p class="author">Xu, H., Mao, X., Zeng, Q., Wang, S., Kawde, A.-N., & Liu, G. (2008).</p><cite>Aptamer-Functionalized Gold Nanoparticles as Probes in a Dry-Reagent Strip Biosensor for Protein Analysis.</cite><p><span class="journalTitle">Analytical Chemistry</span> <span class="journalInfo">81(2), 669-675.</span></p><a class="in-text" href="https://doi.org/10.1021/ac8020592" rel="noopener" target="_blank">CrossRef</a><a class="in-text" href="https://scholar.google.com/scholar?q=Aptamer-Functionalized Gold Nanoparticles as Probes in a Dry-Reagent Strip Biosensor for Protein Analysis." rel="noopener" target="_blank">Google Scholar</a><a class="in-text" href="#intext3">Back to text</a></li><li id="citation4"><p class="author">Xu, H., Mao, X., Zeng, Q., Wang, S., Kawde, A.-N., & Liu, G. (2008).</p><cite>Aptamer-Functionalized Gold Nanoparticles as Probes in a Dry-Reagent Strip Biosensor for Protein Analysis.</cite><p><span class="journalTitle">Analytical Chemistry</span> <span class="journalInfo">81(2), 669-675.</span></p><a class="in-text" href="https://doi.org/10.1021/ac8020592" rel="noopener" target="_blank">CrossRef</a><a class="in-text" href="https://scholar.google.com/scholar?q=Aptamer-Functionalized Gold Nanoparticles as Probes in a Dry-Reagent Strip Biosensor for Protein Analysis." rel="noopener" target="_blank">Google Scholar</a><a class="in-text" href="#intext4">Back to text</a></li><li id="citation5"><p class="author">Kai, K., Mizutani, M., Kawamura, N., Yamamoto, R., Tamai, M., Yamaguchi, H., ... & Shimizu, B. (2008).</p><cite>Scopoletin is biosynthesized viaortho-hydroxylation of feruloyl CoA by a 2-oxoglutarate-dependent dioxygenase inArabidopsis thaliana.</cite><p><span class="journalTitle">The Plant Journal</span> <span class="journalInfo">55(6), 989-999.</span></p><a class="in-text" href="https://doi.org/10.1111/j.1365-313X.2008.03568.x" rel="noopener" target="_blank">CrossRef</a><a class="in-text" href="https://scholar.google.com/scholar?q=Scopoletin is biosynthesized viaortho-hydroxylation of feruloyl CoA by a 2-oxoglutarate-dependent dioxygenase inArabidopsis thaliana." rel="noopener" target="_blank">Google Scholar</a><a class="in-text" href="#intext5">Back to text</a></li><li id="citation6"><p class="author">Gechev, T., Minkov, I., & Hille, J. (2005).</p><cite>Hydrogen Peroxide-induced Cell Death in Arabidopsis: Transcriptional and Mutant Analysis Reveals a Role of an Oxoglutarate-dependent Dioxygenase Gene in the Cell Death Process.</cite><p><span class="journalTitle">IUBMB Life (International Union of Biochemistry and Molecular Biology: Life)</span> <span class="journalInfo">57(3), 181-188.</span></p><a class="in-text" href="https://doi.org/10.1080/15216540500090793" rel="noopener" target="_blank">CrossRef</a><a class="in-text" href="https://scholar.google.com/scholar?q=Hydrogen Peroxide-induced Cell Death in Arabidopsis: Transcriptional and Mutant Analysis Reveals a Role of an Oxoglutarate-dependent Dioxygenase Gene in the Cell Death Process." rel="noopener" target="_blank">Google Scholar</a><a class="in-text" href="#intext6">Back to text</a></li><li id="citation7"><p class="author">Hartmann, M., Zeier, T., Bernsdorff, F., Reichel-Deland, V., Kim, D., Hohmann, M., ... & Zeier, J. (2018).</p><cite>Flavin Monooxygenase-Generated N-Hydroxypipecolic Acid Is a Critical Element of Plant Systemic Immunity.</cite><p><span class="journalTitle">Cell</span> <span class="journalInfo">173(2), 456-469.e16.</span></p><a class="in-text" href="https://doi.org/10.1016/j.cell.2018.02.049" rel="noopener" target="_blank">CrossRef</a><a class="in-text" href="https://scholar.google.com/scholar?q=Flavin Monooxygenase-Generated N-Hydroxypipecolic Acid Is a Critical Element of Plant Systemic Immunity." rel="noopener" target="_blank">Google Scholar</a><a class="in-text" href="#intext7">Back to text</a></li><li id="citation8"><p class="author">B ttcher, C., Chapman, A., Fellermeier, F., Choudhary, M., Scheel, D., & Glawischnig, E. (2014).</p><cite>The Biosynthetic Pathway of Indole-3-Carbaldehyde and Indole-3-Carboxylic Acid Derivatives in Arabidopsis .</cite><p><span class="journalTitle">Plant Physiology</span> <span class="journalInfo">165(2), 841-853.</span></p><a class="in-text" href="https://doi.org/10.1104/pp.114.235630" rel="noopener" target="_blank">CrossRef</a><a class="in-text" href="https://scholar.google.com/scholar?q=The Biosynthetic Pathway of Indole-3-Carbaldehyde and Indole-3-Carboxylic Acid Derivatives in Arabidopsis
| + | }</style><h2>Project - Design - now Proof of concept</h2><p>We aimed to create a fast and easy to use test for the detection of pathogens and plant stress proteins that are expressed after pathogen infections, that is also applicable directly in-field. We decided to go for a <strong>sandwich lateral flow assay</strong> (LFA), but with a twist. Instead of using antibodies that are predominantly used, we use aptamers for target binding <a href="https://2021.igem.org/Team:Duesseldorf/selex">Link to SELEX</a> and gold nanoparticles as our visible output<a href="#citation1">1</a>. <strong>Gold nanoparticles</strong> (AuNPs) in their stabilized form are red and are therefore suitable for an easy read out. Aptamers are single-stranded DNA fragments, generated through the <strong>SELEX</strong> process, that can bind to their target with high specificity. LFAs are not new in the field of detection and are commonly used within medical diagnostics<a href="#citation2">2</a>. The most commonly known examples are pregnancy tests and COVID-19 antigen tests. Nanoparticles themselves were already used in the 19th century and from then on only developed further<a href="#citation2">2</a>. In the medical field, gold nanoparticles are also used as nano-platforms for antibodies and as an easy delivery method for drugs into cells<a href="#citation2">2</a>.</p><p><em>What sets us apart from the already existing methods?</em></p><p>We are using existing parts and bring them together in a new way and with a new field of application: pathogen detection and differentiation. Currently, pathogens can only be differentiated by trained experts, or in special labs, but this takes a lot of time. Additionally both methods can only be used at later stages of infection when symptoms are clearly visible so the plants are already damaged.</p><p>[small sketch?]<br/>For this sandwich LFA, a leaf is taken from the plant that needs to be tested for one or more pathogens. This leaf is ground up and mixed with a suitable buffer that is fitting for the chosen target. It is added to the test device by dripping it onto the sample application pad. If the pathogen or stress protein of interest is present in the sample, it will bind to the aptamer-1 that is part of the AuNP-aptamer-conjugates. The suspension, including the AuNP-aptamer-conjugates and the bound target, flow through the test strip. When they pass the test line, the target will also bind to aptamer-2. Since aptamer-2 is anchored to the test line with a streptavidin-biotin bond, the target serves as a linker between the test line and the gold-nanoparticles. In case this linker is present, a red signal can be observed at the test line. The last line on a LFA is always the control line, which in our case contains a poly-A-tag, which is linked to the membrane with a streptavidin-biotin bond. In a working LFA the control line should always turn red because the complementary poly-T-sequence is part of the AuNP-aptamer-conjugates and binds to the poly-A-tag. If the control line is not red, the test is faulty and not reliable anymore<a href="#citation3">3</a>.</p><p>We first established the protocols needed for our test with known aptamers for thrombin to be able to implement our newly generated aptamers later on<a href="#citation4">4</a>. In addition to this we also researched and selected potential pathogen-induced protein candidates to use in the SELEX process to generate aptamers for our test. These were: F6'H1, FMO1, PAD3, PR1 and UGT74F2. They are all genes from <em>Arabidopsis thaliana</em> and homologs can be found in other plant families. For us, they were only potential candidates for the SELEX process that we ended up not using for now. F6'H1 or 2-oxoglutarate (OG)- and Fe(II)-dependent dioxygenase, is required for H2O2 induced programmed cell death, which is part of the plant's stress response to pathogens. It is also involved in the scopoletin synthesis. Scopoletin is a coumarin derivative. It also is involved in the response to iron ion starvation<a href="#citation5">5</a><a href="#citation6">6</a>. FMO1, Flavin-dependent monooxygenase 1, can confer a salicylic acid-dependent resistance to virulent pathogens. It catalyzes the hydroxylation of pipecolic acid to N-hydroxypipecolic acid, which acts as a long distance signal and induced systemic aquired resistance<a href="#citation7">7</a>. PAD3, phytoalexin deficient 3, is a Cytochrome P450 enzyme that catalyzes the conversion of dihydrocamalexic acid to camalexin<a href="#citation8">8</a>. PR1, pathogenesis-related gene 1, is induced as a response to a variety of pathogens and can function as a molecular marker for SAR (systemic acquired resistance) response<a href="#citation9">9</a>. UGT74F2, UDP-glycosyltransferase 74F2 binds specifically to the molecular chaperone HSP90 and is suggested to play a role in Resistance protein folding<a href="#citation10">10</a>.</p><p><em>Further information can be found here: PROTEAM.</em></p><h2>Conservation of proteins in different plants</h2><p>To get an overview if the selected proteins could be potential targets in multiple plants, we made a sequence comparison via BLAST. The amino acid sequences from Arabidopsis thaliana were run through BLAST on Phytozome<a href="#citation11">11</a> then aligned by Ebi's Clustal Omega multiple sequence alignment tool<a href="#citation12">12</a> and the phylogenetic trees were made with Phylogeny<a href="#citation13">13</a>. Phylogenetic trees for F6'H1, FMO1, PAD3, PR1, UGT74F2 paralogs in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to e.g. 0.5 = 50% difference in compared protein sequences.</p><div class="image"><img alt="Phylogenetic trees for F6'H1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 40% difference in compared protein sequences." src="https://static.igem.org/mediawiki/2021/f/fa/T--Duesseldorf--img--F6%27H1.png" style="width: 100%"/><p>Figure 1: Phylogenetic trees for F6'H1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 40% difference in compared protein sequences.</p></div><div class="image"><img alt="Phylogenetic trees for FMO1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 50% difference in compared protein sequences." src="https://static.igem.org/mediawiki/2021/8/8b/T--Duesseldorf--img--FMO1.png" style="width: 100%"/><p>Figure 2: Phylogenetic trees for FMO1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 50% difference in compared protein sequences.</p></div><div class="image"><img alt="Phylogenetic trees for PAD3 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 30% difference in compared protein sequences." src="https://static.igem.org/mediawiki/2021/c/cb/T--Duesseldorf--img--PAD3.png" style="width: 100%"/><p>Figure 3: Phylogenetic trees for PAD3 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 30% difference in compared protein sequences.</p></div><div class="image"><img alt="Phylogenetic trees for PR1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 20% difference in compared protein sequences." src="https://static.igem.org/mediawiki/2021/4/44/T--Duesseldorf--img--PR1.png" style="width: 100%"/><p>Figure 4: Phylogenetic trees for PR1 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 20% difference in compared protein sequences.</p></div><div class="image"><img alt="Phylogenetic trees for UGT74F2 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 50% difference in compared protein sequences." src="https://static.igem.org/mediawiki/2021/e/ec/T--Duesseldorf--img--UDP.png" style="width: 100%"/><p>Figure 5: Phylogenetic trees for UGT74F2 paralog in Arabidopsis thaliana (TAIR10), Zea mays PH207 v1.1, Solanum tuberosum v4.03, Brassica oleracea capitata v1.0, Physcomitrella patens v3.3, Glycine max Wm82.a2.v1 with branch support values shown in reds. The scale on the bottom represents the branch length equivalent to 50% difference in compared protein sequences.</p></div><p>As expected, the sequences from <em>Brassica oleracea capitata</em> for all selected proteins were the most similar ones to the ones from <em>Arabidopsis thaliana</em>. They are both part of the <em>Brassicaceae</em> family and are therefore more closely related than the other plants. The sequences of <em>Physcomitrella patens</em> were always the most distant ones. Several of the plants have promising sequence similarities, which could imply that these proteins have similar structures and surfaces. The next step would be to test out if the aptamers created for the <em>Arabidopsis thaliana</em> proteins can bind to conserved proteins from other families as well.</p><h2>LFA - Lateral flow test</h2><div class="card"><h3>Sample application pad</h3><p>The first part of the LFA consists of a nitrocellulose membrane (CFSP173000 Sigma Aldrich). Here the sample is applied as suspension in a suitable buffer. The sample can be a protein in the defense response of the plant or the pathogen itself, the only requirement is that during the SELEX process at least two fitting aptamers (aptamer-1 and aptamer-2) are found for the target protein or pathogen<a href="#citation3">3</a>.</p></div><div class="card"><h3>Conjugate pad</h3><p>The glass-fiber membrane (GFDX083000 Sigma Aldrich) connects the sample application pad and the test-membrane and contains the AuNP-aptamer conjugates. To test our design and to get used to working with LFAs, we used already published thrombin aptamers. The thiolated aptamer-1 is our primary aptamer (aptamer-1: 5'-SH-(CH2)6- AAA AAA AAA AAA AAA GGT TGG TGT GGT TGG-3')<a href="#citation4">4</a>.</p></div><div class="card"><h4>Gold nanoparticles</h4><p>Gold nanoparticles can be synthesized or bought in various sizes. If they are synthesized, HAuCl4 is the main content<a href="#citation3">3</a>. Our gold nanoparticles were ordered and had a diameter of around 15, an OD of 1, were citrate buffered and had a maximum absorbance at 510-525 nm (777137-25ML Sigma Aldrich).</p></div><div class="card"><h4>AuNP-aptamer-1-conjugates</h4><p>AuNP-aptamer-conjugates are aptamers bound to gold nanoparticles through a coordinated bond between the AuNP-surface and thiol groups linked to the aptamers <a href="#citation15">15</a>. The thiol groups have to be activated in order to be able to bind to the AuNPs. This activation can be achieved by adding Dithiothreitol (DTT) and Triethylamine (TEA), DTT reduces the thiol-modified aptamers which activates them and enables them to bind to the AuNPs<a href="#citation16">16</a>. TEA is often used as an alkaline solvent or to bind released acids<a href="#citation17">17</a>. DTT is then extracted with ethyl acetate which forms an organic phase that can be pipetted away. The aqueous phase with the activated aptamers is retained and then added to the AuNPs. Incubating them together causes them to form conjugates. In the end these are gold nanoparticles functionalized with thiolated aptamers.</p></div><div class="card"><h3>Test-membrane:</h3><p>As already mentioned, the following part is a nitrocellulose membrane (CFSP173000 Sigma Aldrich) with two or more lines. The test line or lines, lie closest to the sample application pad. They are formed by streptavidin-biotin-aptamer conjugates bound to the nitrocellulose membrane. Streptavidin and Biotin have one of the highest intermolecular bonds, making them particularly useful for such binding applications<a href="#citation3">3</a>. The control line consists of a Poly-T-biotin-streptavidin conjugate (Sequence: 5'-TTTTTTTTTTTTTTT-BiotinTEG-3')<a href="#citation4">4</a>. The test line, or capture probe, consists of the second aptamer that is biotinylated (aptamer-2: 5'-biotin-AGT CCG TGG TAG GGC AGG TTG GGG TGA CT-3') <a href="#citation4">4</a>. Both were added to the nitrocellulose membrane which was cut into strips that had a size of about 6 cm x 0,5 cm.</p></div><div class="card"><h3>Absorption pad:</h3><p>At the end of the test strip another nitrocellulose membrane (CFSP173000 Sigma Aldrich) is located, to absorb the excess fluid<a href="#citation3">3</a>.</p></div><div class="card"><h3>AuNP-conjugate preparation</h3><p>What worked for us in the end, was to orientate ourselves at the protocol from Yi. Peng et al.<a href="#citation18">18</a>. We heated 100 µM aptamer-1 to 90°C and let them cool down, before we further used them. According to Peng et al. this should help the structure of the aptamers to stay flexible. This is important in order for the aptamers to bind to their target. 99 µl heated aptamers were then used and mixed with a spatula tip SDS and allowed to react for 30 min. at room temperature. We used the SDS as an alternative to TCEP as they are both reducing agents and should help to disrupt the unwanted disulfide bonds between the thiolated aptamers. From this mixture, 10 µl were taken and added to 60 µl AuNPs. This was then again allowed to react for 16 h at room temperature<a href="#citation18">18</a>.</p></div><div class="card"><h3>Streptavidin-Biotin-DNA preparation</h3><p>For our Streptavidin-Biotin-DNA preparation followed the protocol of L. Wang et al. (2011)<a href="#citation19">20</a>: The Streptavidin (Streptomyces avidinii<a href="#citation4">4</a>) is dissolved in 0.01 mM PBS (1mg/ml). 5 µl of the Streptavidin solution gets mixed with 35 µl 5 µM DNA solution (here, aptamer-1 was used) and left at 4 °C for 2h. 60 µl of 0.01 mM PBS is added and the solution is centrifuged at 12.000 rpm with a centrifugal filter (cutoff 30,000) for 5 min to remove the excess DNA. The only alteration we made to this protocol was to spin at 12.000 rpm instead of 6.000 rpm<a href="#citation20">21</a>. The solution gets washed twice with 100 µl 0.01 mM PBS and resuspended in 40 µl of 0.01 mM PBS. It can be stored in the freezer for later use.</p></div><div class="card"><h3>Test assembly</h3><p>Despite minor problems due to the lack of devices for building a reproducible test, we managed to build a prototype of the detection strip. During this assembly process we found out that the thickness of the nitrocellulose membrane (CFSP173000 Sigma Aldrich) is important. With the original thickness of the purchased membrane we had no success in getting proper flow through. We then divided the membrane in half and had a successful flow through. Single parts of the test were not sticking together as expected, so we used lab tape to hold our test-prototype together. We further faced the problem that the AuNPs did not flow through or lost their color after they dried on the glass fiber membrane. We suspect that maybe the concentration of the AuNP-conjugates was not high enough or that during the drying process they require special treatment to prevent them from aggregating<a href="#citation3">3</a>.</p></div><div class="imageWrapper"><style>.imageWrapper img{ |
| + | }</style><div class="image"><img alt="Our Test-prototype, with the sample application pad, the conjugate pad, the test-membrane, one testline and an absorption pad." src="https://static.igem.org/mediawiki/2021/6/68/T--Duesseldorf--img--teststripe.png" style="width: 100%"/><p>Figure 6: Our Test-prototype, with the sample application pad, the conjugate pad, the test-membrane, one testline and an absorption pad.</p></div></div><p>TEST How to read results of an LFA (with pictures): positive: two lines negative: one line (only control line) unreliable/invalid no line or more lines than those who were made</p><p><em>The results of our test have plenty of possible applications that can be found here: Link to IMPLEMENTATION.</em></p></article><article id="references"><h2>References</h2><ol><li id="citation1"><p class="author">Zhao, S., Wang, S., Zhang, S., Liu, J., & Dong, Y. 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