Thesis Open Access

Quantitative real-time PCR Detection of Yersinia ruckeri for Application in Aquaculture

Gesa Birkenbach

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  <identifier identifierType="DOI">10.5281/zenodo.7441338</identifier>
      <creatorName>Gesa Birkenbach</creatorName>
      <affiliation>Hochschule Rhein-Waal</affiliation>
    <title>Quantitative real-time PCR Detection of Yersinia ruckeri for Application in Aquaculture</title>
    <subject>DNA quantification</subject>
    <subject>Hydrolysis probe</subject>
    <subject>Quantitative real-time PCR (qPCR)</subject>
    <subject>Yersinia ruckeri</subject>
    <contributor contributorType="Supervisor">
      <contributorName>Mònica Palmada Fenés</contributorName>
      <affiliation>Hochschule Rhein-Waal</affiliation>
    <contributor contributorType="Supervisor">
      <contributorName>Florian Borutta</contributorName>
      <affiliation>TunaTech GmbH</affiliation>
    <date dateType="Issued">2022-07-18</date>
  <resourceType resourceTypeGeneral="Text">Thesis</resourceType>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.7441337</relatedIdentifier>
    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;To detect pathogen infections in aquaculture early and reduce their impact, a photonic biosensing chip is being developed in the PHOTO-SENS project, to enable fast and easy routine testing in aquaculture facilities. One target bacterial pathogen is&amp;nbsp;Yersinia ruckeri, the causative agent of enteric redmouth disease. Detection is based on short DNA sequences (probes), that are complementary to the DNA of their target pathogen.&lt;/p&gt;

&lt;p&gt;In this work, a&amp;nbsp;Yersinia ruckeri-specific probe was designed together with a set of qPCR primers. The probe and primers were tested in qPCR experiments, including quantifi- cation of extracted DNA, specificity and sensitivity testing, and detection of bacterial DNA from highly diluted samples to mimic the detection of environmental DNA. Three different standard series were created for the quantification of unknown samples. The influence of fish tissue on detection was tested, and the efficiency of Chelex-DNA ex- tractions were compared to peqGOLD Tissue DNA Mini Kit extractions.&lt;/p&gt;

&lt;p&gt;During quantification experiments with a first standard series (Y1P), the quantification output of most samples was 12&amp;ndash;175 times higher than expected. The lower limit of detection was at 100 copies based on that standard, with an efficiency of 88%. The discrepancy was reduced with a gBlocks standard (limit of detection: 5 copies; effi- ciency: 92%). A CFU standard provided quantification results in reasonable agreement with expected CFU starting quantities (limit of detection: 1 CFU; efficiency: 106%). De- tection of diluted samples after filtration was possible. Chelex DNA extractions yielded higher amounts of detectable DNA compared to a DNA extraction kit. Less bacterial DNA was extracted in bacterial culture samples containing fish tissue than in samples that did not contain fish tissue.&lt;/p&gt;

&lt;p&gt;Higher-than-expected quantification outputs were attributed to flaws in the creation of a first standard series as well as detectable DNA from dead cells or clusters that were not accounted for in the expected starting quantities. The gBlocks standard was as- sumed to be most reliable for quantification of exact copy numbers, while the CFU standard produced results that could be accounted for in CFU counts. As these chal- lenges concerned the standard series&amp;rsquo; and not the probe itself, it was concluded that the probe was suitable for application in the PHOTO-SENS project for detection of&amp;nbsp;Yersinia ruckeri.&lt;/p&gt;</description>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100010661</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/965643/">965643</awardNumber>
      <awardTitle>A plug and play PHOTOnics based bioSENSing platform for salmon pathogen detection</awardTitle>
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