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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Microbiol.</journal-id>
<journal-title>Frontiers in Microbiology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Microbiol.</abbrev-journal-title>
<issn pub-type="epub">1664-302X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmicb.2024.1390328</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Microbiology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Development of a triplex quantitative reverse transcription-polymerase chain reaction for the detection of porcine epidemic diarrhea virus, porcine transmissible gastroenteritis virus, and porcine rotavirus A</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Luo</surname> <given-names>Tingyu</given-names></name>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
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<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Li</surname> <given-names>Kaili</given-names></name>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/validation/"/>
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</contrib>
<contrib contrib-type="author">
<name><surname>Li</surname> <given-names>Changwen</given-names></name>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/project-administration/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Xia</surname> <given-names>Changyou</given-names></name>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Gao</surname> <given-names>Caixia</given-names></name>
<xref ref-type="corresp" rid="c002"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2664447/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
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<aff><institution>State Key Laboratory for Animal Disease Control and Prevention, Heilongjiang Provincial Key Laboratory of Laboratory Animal and Comparative Medicine, National Poultry Laboratory Animal Resource Center, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences</institution>, <addr-line>Harbin</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0001">
<p>Edited by: Peirong Jiao, South China Agricultural University, China</p>
</fn>
<fn fn-type="edited-by" id="fn0002">
<p>Reviewed by: Mengmeng Zhao, Foshan University, China</p>
<p>Mingjun Su, Zhejiang Agriculture and Forestry University, China</p>
<p>Changchao Huan, Yangzhou University, China</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Changyou Xia, <email>xiachangyou@caas.cn</email></corresp>
<corresp id="c002">Caixia Gao, <email>gaocaixia@caas.cn</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>10</day>
<month>05</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>15</volume>
<elocation-id>1390328</elocation-id>
<history>
<date date-type="received">
<day>23</day>
<month>02</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>17</day>
<month>04</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2024 Luo, Li, Li, Xia and Gao.</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Luo, Li, Li, Xia and Gao</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Porcine viral diarrhea is caused by many pathogens and can result in watery diarrhea, dehydration and death. Various detection methods, such as polymerase chain reaction (PCR) and real-time quantitative PCR (qPCR), have been widely used for molecular diagnosis. We developed a triplex real-time quantitative reverse transcription PCR (qRT-PCR) for the simultaneous detection of three RNA viruses potentially associated with porcine viral diarrhea: porcine epidemic diarrhea virus (PEDV), porcine transmissible gastroenteritis virus (TGEV), and porcine rotavirus A (PoRVA). The triplex qRT-PCR had <italic>R</italic><sup>2</sup> values of 0.999 for the standard curves of PEDV, TGEV and PoRVA. Importantly, the limits of detection for PEDV, TGEV and PoRVA were 10 copies/&#x03BC;L. The specificity test showed that the triplex qRT-PCR detected these three pathogens specifically, without cross-reaction with other pathogens. In addition, the approach had good repeatability and reproducibility, with intra-and inter-assay coefficients of variation &#x003C;1%. Finally, this approach was evaluated for its practicality in the field using 256 anal swab samples. The positive rates of PEDV, TGEV and PoRVA were 2.73% (7/256), 3.91% (10/256) and 19.14% (49/256), respectively. The co-infection rate of two or more pathogens was 2.73% (7/256). The new triplex qRT-PCR was compared with the triplex RT-PCR recommended by the Chinese national standard (GB/T 36871-2018) and showed 100% agreement for PEDV and TGEV and 95.70% for PoRVA. Therefore, the triplex qRT-PCR provided an accurate and sensitive method for identifying three potential RNA viruses for porcine viral diarrhea that could be applied to diagnosis, surveillance and epidemiological investigation.</p>
</abstract>
<kwd-group>
<kwd>porcine epidemic diarrhea virus</kwd>
<kwd>porcine transmissible gastroenteritis virus</kwd>
<kwd>porcine rotavirus A</kwd>
<kwd>porcine enteric viruses</kwd>
<kwd>triplex real-time qRT-PCR</kwd>
</kwd-group>
<contract-num rid="cn1">2021YFF0703000</contract-num>
<contract-num rid="cn2">NCTIP-XD1C09</contract-num>
<contract-num rid="cn3">1610302022018</contract-num>
<contract-sponsor id="cn1">National Key Research and Development Program<named-content content-type="fundref-id">10.13039/501100012166</named-content></contract-sponsor>
<contract-sponsor id="cn2">Pilot Technology Project of National Pig Technology Innovation Center</contract-sponsor>
<contract-sponsor id="cn3">Special Funds for Basic Scientific Research Operations of Central Public Welfare Scientific Research Institutions</contract-sponsor>
<counts>
<fig-count count="7"/>
<table-count count="5"/>
<equation-count count="0"/>
<ref-count count="38"/>
<page-count count="12"/>
<word-count count="6279"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Virology</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec1">
<label>1</label>
<title>Introduction</title>
<p>The main pathogens causing diarrhea in piglets are porcine epidemic diarrhea virus (PEDV), porcine transmissible gastroenteritis virus (TGEV) and porcine rotavirus A (PoRVA) (<xref ref-type="bibr" rid="ref34">Zhang et al., 2013</xref>; <xref ref-type="bibr" rid="ref20">Monteagudo et al., 2022</xref>). Co-infection by these viruses is common in swine and poses a serious challenge for diarrhea control in swine farms (<xref ref-type="bibr" rid="ref36">Zhang et al., 2019</xref>; <xref ref-type="bibr" rid="ref23">Shi et al., 2021</xref>). PEDV is an enveloped, single-stranded, positive-sense RNA virus belonging to the genus <italic>Coronavirus</italic> in the family <italic>Coronaviridae</italic>. In 1978, researchers first isolated PEDV from the intestinal contents of pigs in the UK (<xref ref-type="bibr" rid="ref21">Pensaert and de Bouck, 1978</xref>). PEDV has spread globally since then, causing watery diarrhea, vomiting, dehydration and death in pigs, resulting in severe economic losses for the swine industry (<xref ref-type="bibr" rid="ref28">Wang et al., 2016</xref>). The PEDV genome is approximately 28&#x2009;kb long and comprises seven open reading frames (ORFs). The <italic>M</italic> gene (ORF5) encodes the membrane protein M and has a relatively conserved sequence, which makes it a suitable molecular detection target for PEDV diagnosis (<xref ref-type="bibr" rid="ref13">Kocherhans et al., 2001</xref>; <xref ref-type="bibr" rid="ref31">Yang et al., 2014</xref>; <xref ref-type="bibr" rid="ref22">Rasmussen et al., 2018</xref>). TGEV is also an RNA virus that belongs to the <italic>Coronavirus</italic> genus and <italic>Coronaviridae</italic> family. It was the first coronavirus identified in pigs and is responsible for porcine viral diarrhea. The genome of TGEV is approximately 28.6&#x2009;kb in length and comprises nine major ORFs. The <italic>N</italic> gene (ORF6) encodes the capsid protein N and is relatively conserved in the TGEV genome (<xref ref-type="bibr" rid="ref6">Eleouet et al., 1995</xref>; <xref ref-type="bibr" rid="ref33">Yount et al., 2000</xref>). Another porcine enteric virus, PoRVA, is a non-enveloped double-stranded RNA virus belonging to the genus <italic>Rotavirus</italic> and family <italic>Reoviridae</italic>. It is one of the major pathogens responsible for severe diarrhea in piglets worldwide (<xref ref-type="bibr" rid="ref26">Vlasova et al., 2017</xref>; <xref ref-type="bibr" rid="ref16">Luo et al., 2023</xref>). The PoRVA genome is approximately 18.5&#x2009;kb and has 11 double-stranded RNA segments. <italic>NSP3</italic> is a relatively conserved gene that plays a key role in viral replication and transcription, and is a common target gene for detecting PoRVA infection (<xref ref-type="bibr" rid="ref8">Ghosh and Kobayashi, 2011</xref>).</p>
<p>Porcine viral diarrhea caused by these three enteric viruses poses serious health and economic threats to pig farming in China. It is also a challenge to the microbiological quality control of specific pathogen-free pigs for scientific research. To cope with the challenges of PEDV, TGEV and PoRVA, 34 standards have been publicly released in China so far, including 3 national standards, 6 agricultural industry and entry-exit inspection and quarantine industry standards, and 25 provincial local standards. These standards specify the detection methods for the three pathogens, such as reverse transcription polymerase chain reaction (RT-PCR), nested RT-PCR, single real-time quantitative RT-PCR (qRT-PCR) and duplex qRT-PCR. Among the 34 standards, a triplex RT-PCR technique was established only in the Chinese national standard (<xref ref-type="bibr" rid="ref5">GB/T 36871-2018, 2018</xref>) for simultaneous detection and diagnosis of PEDV, TGEV and PoRVA. In addition, the duplex RT-PCR and duplex qRT-PCR techniques for differential diagnosis of dual infections by porcine viral diarrhea viruses were developed in some Chinese provincial local standards, e.g., Zhejiang provincial local standard (<xref ref-type="bibr" rid="ref38">DB33/T 2254-2020, 2020</xref>) and Anhui provincial local standard (<xref ref-type="bibr" rid="ref1">DB34/T 2795-2016, 2016</xref>). Porcine viral diarrhea is also severe worldwide, which has led to development of various pathogen detection techniques, such as triplex RT-PCR, nested RT-PCR and qRT-PCR (<xref ref-type="bibr" rid="ref10">Huang et al., 2019</xref>; <xref ref-type="bibr" rid="ref4">Chen et al., 2023</xref>). The accurate and rapid molecular diagnosis is essential for the prevention and control of the diseases caused by PEDV, TGEV and PoRVA. Therefore, it is necessary to establish a detection method with high specificity, sensitivity and efficiency.</p>
<p>Real-time qPCR is an accurate, sensitive, and rapid method for detecting and quantifying target genomes. Compared to conventional single qPCR, multiplex qPCR can simultaneously detect multiple target genes in a single reaction, showing many advantages such as high efficiency, throughput, and cost effective (<xref ref-type="bibr" rid="ref17">Mackay, 2004</xref>; <xref ref-type="bibr" rid="ref32">Yang et al., 2022</xref>). Advances in molecular biology techniques have led to widespread use of multiplex qPCR in clinical detection (<xref ref-type="bibr" rid="ref27">Wang et al., 2020</xref>). In this study, we designed primers and probes based on the conserved fragments of PEDV <italic>M</italic> gene, TGEV <italic>N</italic> gene and PoRVA <italic>NSP3</italic> gene, and successfully developed a triplex qRT-PCR based on TaqMan probes. This method was highly sensitive and specific and did not cross-react with the genomes of other swine pathogens. It could be used for diagnosis, epidemiological investigation and microbiological quality control of specific pathogen-free pigs.</p>
</sec>
<sec sec-type="materials|methods" id="sec2">
<label>2</label>
<title>Materials and methods</title>
<sec id="sec3">
<label>2.1</label>
<title>Viral nucleic acids and clinical samples</title>
<p>The genomes (DNA or RNA) of PEDV, TGEV, PoRVA, pseudorabies virus (PRV), porcine circovirus type 2 (PCV2), porcine parvovirus (PPV), porcine deltacoronavirus (PDCoV), Seneca virus A (SVA), <italic>Toxoplasma gondii</italic>, <italic>Leptospira interrogans</italic>, <italic>Mycoplasma hyopneumoniae</italic>, <italic>Mycoplasma hyorhinis</italic>, <italic>Haemophilus parasuis</italic>, <italic>Streptococcus suis</italic>, <italic>Pasteurella multocida</italic> and <italic>Actinobacillus pleuropneumoniae</italic> were preserved by the State Key Laboratory for Animal Disease Control and Prevention of China or Heilongjiang Provincial Key Laboratory of Laboratory Animal and Comparative Medicine. In addition, 256 anal swab samples from pigs with or without clinical diarrhea were obtained from Animal Health Testing Center of Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences. The Institutional Review Board of Harbin Veterinary Research Institute or the Regulations on the Administration of Laboratory Animals of China did not require the study to be reviewed or approved by an ethics committee because the samples were collected from animals that were already dead or euthanized for other purposes, and no additional harm or intervention was imposed on the animals.</p>
</sec>
<sec id="sec4">
<label>2.2</label>
<title>Primers and TaqMan probes</title>
<p>To ensure the detection performance of the primers and probes used in the triplex qRT-PCR, <italic>M</italic> gene of PEDV genome, <italic>N</italic> gene of TGEV genome and <italic>NSP3</italic> gene of PoRVA genome were selected as the detection targets, based on their relative conservation. We obtained 86 PEDV <italic>M</italic> gene sequences, 46 TGEV <italic>N</italic> gene sequences and 20 PoRVA <italic>NSP3</italic> gene sequences from GenBank database. We used MegAlign to align them and determine the most conserved regions of each target gene. Using Primer Express 3.0.1, we designed primers and probes for the three viruses with the following conditions: primer length 18&#x2013;30&#x2009;bp, primer melting temperature (<italic>T</italic><sub>m</sub>) 58&#x2013;62&#x00B0;C, primer GC content 40&#x2013;60%, product <italic>T</italic><sub>m</sub> 70&#x2013;90&#x00B0;C and product size 70&#x2013;150&#x2009;bp. We ensured that the probe <italic>T</italic><sub>m</sub> value was higher than that of the primers. The specificity of the primers and probes was verified using the BLAST tool provided by the National Center for Biotechnology Information. For triplex detection, the probes for the three viral genes were labeled with different 5&#x2032;-reporting dyes: Victoria Blue (VIC), Cyanine 5 (Cy5) and Fluorescein (FAM) and corresponding 3&#x2032;-quenchers: Black Hole Quencher 1 (BHQ1), Black Hole Quencher 2 (BHQ2) and Minor Groove Binder (MGB). The triplex RT-PCR recommended by the Chinese national standard (<xref ref-type="bibr" rid="ref5">GB/T 36871-2018, 2018</xref>) was used to verify the accuracy of the results for clinical samples. The details of the primers and probes are provided in <xref ref-type="table" rid="tab1">Table 1</xref>. <xref ref-type="fig" rid="fig1">Figure 1</xref> shows the locations of the triplex qRT-PCR primers and probes for PEDV, TGEV and PoRVA in different reference strains.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Primers and probes used in this study.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Assays</th>
<th align="left" valign="top">Name</th>
<th align="left" valign="top">Sequence (5&#x2032;&#x2013;3&#x2032;)</th>
<th align="left" valign="top">Product size (bp)</th>
<th align="left" valign="top">Reference</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" rowspan="9">Triplex qRT-PCR</td>
<td align="left" valign="top">PEDV-<italic>M</italic>-F</td>
<td align="left" valign="top">GCGCAGGACACATTCTTGGT</td>
<td align="left" valign="top">74</td>
<td align="left" valign="top">This study</td>
</tr>
<tr>
<td align="left" valign="top">PEDV-<italic>M</italic>-R</td>
<td align="left" valign="top">GTCGGCCCATCACAGAAGTAG</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">PEDV-<italic>M</italic>-P</td>
<td align="left" valign="top">VIC-TTCAATCCTGAAACAGACGCGCTTCTC-BHQ1</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">TGEV-<italic>N</italic>-F</td>
<td align="left" valign="top">TTGTCTGGGTTGCCAAGGAT</td>
<td align="left" valign="top">74</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">TGEV-<italic>N</italic>-R</td>
<td align="left" valign="top">GGATTCATTATTAGCACCACGACTAC</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">TGEV-<italic>N</italic>-P</td>
<td align="left" valign="top">Cy5-TGCCATGAACAAACCAACCACGCT-BHQ2</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">PoRVA-<italic>NSP3-</italic>F</td>
<td align="left" valign="top">AWATTAACCATCTACACATGACCCTCTA</td>
<td align="left" valign="top">74</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">PoRVA-<italic>NSP3-</italic>R</td>
<td align="left" valign="top">AGCCATTTAGGTTTTTGACAGTGTT</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">PoRVA-<italic>NSP3-</italic>P</td>
<td align="left" valign="top">FAM-AGCACAATAGTTAAAAGC-MGB</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top" rowspan="6">Triplex RT-PCR</td>
<td align="left" valign="top">PEDV P1</td>
<td align="left" valign="top">TTCGGTTCTATTCCCGTTGATG</td>
<td align="left" valign="top">663</td>
<td align="left" valign="top">Chinese national standard (<xref ref-type="bibr" rid="ref5">GB/T 36871-2018, 2018</xref>)</td>
</tr>
<tr>
<td align="left" valign="top">PEDV P2</td>
<td align="left" valign="top">CCCATGAAGCACTTTCTCACTATC</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">TGEV P3</td>
<td align="left" valign="top">TTACAAACTCGCTATCGCATGG</td>
<td align="left" valign="top">528</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">TGEV P4</td>
<td align="left" valign="top">TCTTGTCACATCACCTTTACCTGC</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">PoRVA P5</td>
<td align="left" valign="top">CCCCGGTATTGAATATACCACAGT</td>
<td align="left" valign="top">333</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">PoRVA P6</td>
<td align="left" valign="top">TTTCTGTTGGCCACCCTTTAGT</td>
<td/>
<td/>
</tr>
</tbody>
</table>
</table-wrap>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Alignment of sequences of reference viral strains collected from GenBank database. The locations of the primers/probes specific for PEDV <italic>M</italic> gene, TGEV <italic>N</italic> gene and PoRVA <italic>NSP3</italic> gene are shown. The positions of the partial nucleotide fragments are indicated by numbers.</p>
</caption>
<graphic xlink:href="fmicb-15-1390328-g001.tif"/>
</fig>
</sec>
<sec id="sec5">
<label>2.3</label>
<title>Preparation of standard plasmids</title>
<p>A synthetic gene fragment (PEDV-<italic>M</italic>-TGEV-<italic>N</italic>-PoRVA-<italic>NSP3</italic>) containing partial sequences of PEDV <italic>M</italic> gene, TGEV <italic>N</italic> gene and PoRVA <italic>NSP3</italic> gene was constructed in Sangon Biotech Co., Ltd. (Shanghai, China). This fragment was inserted into the pUC57 cloning vector, forming a standard plasmid (pUC57-PEDV <italic>M</italic> &#x0026; TGEV <italic>N</italic> &#x0026; PoRVA <italic>NSP3</italic>) for subsequent detection (<xref ref-type="fig" rid="fig2">Figure 2</xref>). The sequence of the synthetic gene fragment is shown in <xref rid="SM1" ref-type="supplementary-material">Supplementary Table S1</xref>. The plasmids were quantified by ultraviolet absorbance at 260 and 280&#x2009;nm wavelengths using a NanoDrop spectrophotometer (Thermo Fisher Scientific, Waltham, MA, United States) and their copy number was calculated based on the size of the standard plasmid template using the following formula: copies/&#x03BC;L&#x2009;=&#x2009;(A260 (ng/&#x03BC;L)&#x2009;&#x00D7;&#x2009;10<sup>&#x2212;9</sup>&#x2009;&#x00D7;&#x2009;6.02&#x2009;&#x00D7;&#x2009;10<sup>23</sup>)/(DNA length&#x2009;&#x00D7;&#x2009;650). The standard plasmids were serially diluted 10-fold to a concentration gradient of 10<sup>8</sup>&#x2013;10<sup>0</sup> copies/&#x03BC;L with EASY Dilution (TaKaRa, China, Dalian).</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Standard plasmid containing three conserved gene fragments: PEDV <italic>M</italic> (693&#x2009;bp), TGEV <italic>N</italic> (649&#x2009;bp) and PoRVA <italic>NSP3</italic> (114&#x2009;bp). Each fragment had specific restriction enzyme cutting sites at both ends: <italic>Nde</italic>I and <italic>Sac</italic>I for PEDV <italic>M</italic>; <italic>Kpn</italic>I and <italic>Bam</italic>HI for TGEV <italic>N</italic>; and <italic>Apa</italic>I and <italic>Xho</italic>I for PoRVA <italic>NSP3</italic>.</p>
</caption>
<graphic xlink:href="fmicb-15-1390328-g002.tif"/>
</fig>
</sec>
<sec id="sec6">
<label>2.4</label>
<title>Optimization of the triplex qRT-PCR</title>
<p>The unoptimized triplex qRT-PCR consisted of 10&#x2009;&#x03BC;L 2&#x00D7; One Step U<sup>+</sup> Mix (Vazyme, China, Nanjing), 1&#x2009;&#x03BC;L One Step U<sup>+</sup> Enzyme Mix (Vazyme), 0.4&#x2009;&#x03BC;L 50&#x00D7; ROX Reference Dye II, 0.4&#x2009;&#x03BC;L each primer (final concentration of 200&#x2009;nM), 0.2&#x2009;&#x03BC;L each probe (final concentration of 100&#x2009;nM), 4&#x2009;&#x03BC;L template and 1.6&#x2009;&#x03BC;L RNase-free water in a total volume of 20&#x2009;&#x03BC;L. The amplification was performed on an ABI QuantStudio5 real-time PCR system (Thermo Fisher Scientific) with the following program: 55&#x00B0;C for 15&#x2009;min, 95&#x00B0;C for 30&#x2009;s; 40&#x2009;cycles of 95&#x00B0;C for 10&#x2009;s and 60&#x00B0;C for 30&#x2009;s. The fluorescence signal was automatically collected at the end of each cycle. To optimize the reaction system, we explored different primer volumes (10&#x2009;&#x03BC;M) and probe volumes (10&#x2009;&#x03BC;M). A range of primer volumes (0.3&#x2013;1.2&#x2009;&#x03BC;L) was assessed to achieve final concentrations spanning 150&#x2013;600&#x2009;nM. Additionally, probe volumes were varied from 0.1 to 0.6&#x2009;&#x03BC;L, covering a concentration range of 50&#x2013;300&#x2009;nM. Recombinant plasmids (10<sup>7</sup> copies/&#x03BC;L) served as the detection template for optimization. Finally, the fluorescence intensity and cycle threshold (Ct) values of each primer and probe concentration were compared to determine the optimal volumes. The annealing temperature was also optimized by setting six gradients from 56 to 61&#x00B0;C and comparing the fluorescence intensity and Ct values of each gradient.</p>
</sec>
<sec id="sec7">
<label>2.5</label>
<title>Establishment of standard curves for the triplex qRT-PCR</title>
<p>On the basis of the optimized reaction and protocol, three replicates of plasmid samples with serial dilutions from 10<sup>8</sup> to 10 copies/&#x03BC;L were detected using the triplex qRT-PCR and subjected to linear regression between Ct values and the logarithm of plasmid copy numbers. Eight-point standard curves were established for PEDV, TGEV and PoRVA, including negative controls.</p>
</sec>
<sec id="sec8">
<label>2.6</label>
<title>Specificity of the triplex qRT-PCR</title>
<p>To evaluate the specificity of the primer and probe sets, genomes (DNA or RNA) of PEDV, TGEV, PoRVA, PRV, PCV2, PPV, PDCoV, SVA, <italic>T. gondii</italic>, <italic>L. interrogans</italic>, <italic>M. hyopneumoniae</italic>, <italic>M. hyorhinis</italic>, <italic>H. parasuis</italic>, <italic>S. suis</italic>, <italic>P. multocida</italic> and <italic>A. pleuropneumoniae</italic> were tested using the triplex qRT-PCR. All nucleic acid samples were stored previously in our laboratory.</p>
</sec>
<sec id="sec9">
<label>2.7</label>
<title>Sensitivity of the triplex qRT-PCR</title>
<p>For sensitivity assessment, standard plasmids were serially diluted 10-fold to final concentrations ranging from 10<sup>8</sup> to 1 copies/&#x03BC;L. These dilutions were used as templates to determine the limit of detection (LoD) for triplex qRT-PCR and each reaction was repeated three times in a single test. We tested the standard plasmids at 100, 10 and 1 copies/&#x03BC;L 20 times to ensure the LoD accuracy. We set the LoD as the lowest concentration of standard plasmids that gave positive results in 85% of the replicates and marked it on the amplification curves. The threshold was set in the middle of the exponential amplification phase in the logarithmic view. A positive test result was defined as an exponential fluorescence curve that crossed the threshold within 35&#x2009;cycles [(Ct) &#x003C;35]. According to this definition, we calculated the positive rates at 100, 10 and 1 copies/&#x03BC;L of standard plasmids.</p>
</sec>
<sec id="sec10">
<label>2.8</label>
<title>Repeatability and reproducibility of the triplex qRT-PCR</title>
<p>The repeatability (intra-assay precision) and reproducibility (inter-assay precision) of the developed triplex qRT-PCR were determined using standard plasmids at three different concentrations (10<sup>6</sup>, 10<sup>4</sup> and 100 copies/&#x03BC;L). We analyzed each dilution in triplicate on the same day for intra-assay variability and in six independent experiments by two different operators on different days for inter-assay variability. The coefficient of variation (CV) of the Ct values of the samples at different concentrations was calculated in both intra-assay and inter-assay tests to estimate the repeatability and reproducibility.</p>
</sec>
<sec id="sec11">
<label>2.9</label>
<title>Detection of clinical samples by the triplex qRT-PCR</title>
<p>Viral RNA was extracted from 256 anal swab samples using AxyPrep Body Fluid Viral DNA/RNA Miniprep Kit (Corning Life Sciences, China, Wujiang). The RNA samples were tested in triplicate by the optimized triplex qRT-PCR. Subsequently, the sample RNA was reverse transcribed into cDNA using PrimeScript<sup>&#x2122;</sup> RT Master Mix (Perfect Real Time) (TaKaRa) and detected by the triplex RT-PCR recommended by the Chinese national standard (<xref ref-type="bibr" rid="ref5">GB/T 36871-2018, 2018</xref>), to validate the clinical performance of the developed triplex qRT-PCR assay. For the triplex RT-PCR, the reaction mixture (25&#x2009;&#x03BC;L) contained 12.5&#x2009;&#x03BC;L 2&#x00D7; Taq PCR Star Mix (Genstar, China, Beijing), 0.2&#x2009;&#x03BC;L PEDV primers (final concentration of 80&#x2009;nM), 0.4&#x2009;&#x03BC;L TGEV primers (final concentration of 160&#x2009;nM), 1&#x2009;&#x03BC;L PoRVA primers (final concentration of 400&#x2009;nM), 4&#x2009;&#x03BC;L cDNA template and 5.3&#x2009;&#x03BC;L RNase-free water. We performed the triplex RT-PCR with the following parameters: pre-denaturation at 94&#x00B0;C for 2&#x2009;min, followed by 35&#x2009;cycles of denaturation at 94&#x00B0;C for 30&#x2009;s, annealing at 55&#x00B0;C for 30&#x2009;s, extension at 72&#x00B0;C for 1&#x2009;min, and final extension at 72&#x00B0;C for 10&#x2009;min.</p>
</sec>
</sec>
<sec sec-type="results" id="sec12">
<label>3</label>
<title>Results</title>
<sec id="sec13">
<label>3.1</label>
<title>Construction of the standard plasmid</title>
<p>A plasmid with three conserved gene fragments of PEDV <italic>M</italic> (693&#x2009;bp), TGEV <italic>N</italic> (649&#x2009;bp) and PoRVA <italic>NSP3</italic> (114&#x2009;bp) was constructed, all containing their respective qRT-PCR amplicons. The plasmid was used as the standard for subsequent detection.</p>
</sec>
<sec id="sec14">
<label>3.2</label>
<title>Optimization of the triplex qRT-PCR</title>
<p>Using the standard plasmid pUC57-PEDV <italic>M</italic> &#x0026; TGEV <italic>N</italic> &#x0026; PoRVA <italic>NSP3</italic> with the target fragments as the template, we optimized the reaction conditions of the triplex qRT-PCR. Orthogonal experiments determined the optimal annealing temperature and concentrations of primers and probes. For TGEV and PoRVA, the optimal volumes of probes and primers were 0.4 and 0.7&#x2009;&#x03BC;L, respectively. For PEDV, both were 0.3&#x2009;&#x03BC;L (<xref ref-type="fig" rid="fig3">Figure 3</xref>). The confirmed reaction system was listed in <xref ref-type="table" rid="tab2">Table 2</xref>. The optimal annealing temperature was 60&#x00B0;C, which yielded the highest amplification efficiency (<xref ref-type="fig" rid="fig4">Figure 4</xref>).</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>Optimization of the triplex qRT-PCR assay. <bold>(A)</bold> Optimization of primer volumes and the final concentrations in the reaction. The optimal volumes of forward and reverse primers were 0.7&#x2009;&#x03BC;L for TGEV (final concentration: 350&#x2009;nM) and PoRVA (final concentration: 350&#x2009;nM), and 0.3&#x2009;&#x03BC;L for PEDV (final concentration: 150&#x2009;nM). <bold>(B)</bold> Optimization of probe volumes and the final concentrations in the reaction. The optimal volumes of probes were 0.4&#x2009;&#x03BC;L for TGEV (final concentration: 200&#x2009;nM) and PoRVA (final concentration: 200&#x2009;nM), and 0.3&#x2009;&#x03BC;L for PEDV (final concentration: 150&#x2009;nM).</p>
</caption>
<graphic xlink:href="fmicb-15-1390328-g003.tif"/>
</fig>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>The reaction system of triplex qRT-PCR.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Reagent</th>
<th align="center" valign="top">Volume (&#x03BC;L) or concentration (nM)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">2&#x00D7; One Step U<sup>+</sup> Mix</td>
<td align="center" valign="top">10&#x2009;&#x03BC;L</td>
</tr>
<tr>
<td align="left" valign="top">One Step U<sup>+</sup> Enzyme Mix</td>
<td align="center" valign="top">1&#x2009;&#x03BC;L</td>
</tr>
<tr>
<td align="left" valign="top">PEDV-<italic>M</italic>-F (10&#x2009;&#x03BC;M)</td>
<td align="center" valign="top">0.3&#x2009;&#x03BC;L (150&#x2009;nM)</td>
</tr>
<tr>
<td align="left" valign="top">PEDV-<italic>M</italic>-R (10&#x2009;&#x03BC;M)</td>
<td align="center" valign="top">0.3&#x2009;&#x03BC;L (150&#x2009;nM)</td>
</tr>
<tr>
<td align="left" valign="top">PEDV-<italic>M</italic>-P (10&#x2009;&#x03BC;M)</td>
<td align="center" valign="top">0.3&#x2009;&#x03BC;L (150&#x2009;nM)</td>
</tr>
<tr>
<td align="left" valign="top">TGEV-<italic>N</italic>-F (10&#x2009;&#x03BC;M)</td>
<td align="center" valign="top">0.7&#x2009;&#x03BC;L (350&#x2009;nM)</td>
</tr>
<tr>
<td align="left" valign="top">TGEV-<italic>N</italic>-R (10&#x2009;&#x03BC;M)</td>
<td align="center" valign="top">0.7&#x2009;&#x03BC;L (350&#x2009;nM)</td>
</tr>
<tr>
<td align="left" valign="top">TGEV-<italic>N</italic>-P (10&#x2009;&#x03BC;M)</td>
<td align="center" valign="top">0.4&#x2009;&#x03BC;L (200&#x2009;nM)</td>
</tr>
<tr>
<td align="left" valign="top">PoRVA-<italic>NSP3-</italic>F (10&#x2009;&#x03BC;M)</td>
<td align="center" valign="top">0.7&#x2009;&#x03BC;L (350&#x2009;nM)</td>
</tr>
<tr>
<td align="left" valign="top">PoRVA-<italic>NSP3-</italic>R (10&#x2009;&#x03BC;M)</td>
<td align="center" valign="top">0.7&#x2009;&#x03BC;L (350&#x2009;nM)</td>
</tr>
<tr>
<td align="left" valign="top">PoRVA-<italic>NSP3-</italic>P (10&#x2009;&#x03BC;M)</td>
<td align="center" valign="top">0.4&#x2009;&#x03BC;L (200&#x2009;nM)</td>
</tr>
<tr>
<td align="left" valign="top">50&#x00D7; ROX Reference Dye II</td>
<td align="center" valign="top">0.4&#x2009;&#x03BC;L</td>
</tr>
<tr>
<td align="left" valign="top">Template</td>
<td align="center" valign="top">4&#x2009;&#x03BC;L</td>
</tr>
<tr>
<td align="left" valign="top">RNase-free water</td>
<td align="center" valign="top">0.1&#x2009;&#x03BC;L</td>
</tr>
<tr>
<td align="left" valign="top">Total volume</td>
<td align="center" valign="top">20&#x2009;&#x03BC;L</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>Triplex qRT-PCR amplification curves of different annealing temperatures. The optimal annealing temperature for triplex qRT-PCR was determined by measuring the amplification efficiency of the reaction at different <italic>T</italic><sub>m</sub> values. The highest amplification efficiency was achieved at 60&#x00B0;C.</p>
</caption>
<graphic xlink:href="fmicb-15-1390328-g004.tif"/>
</fig>
</sec>
<sec id="sec15">
<label>3.3</label>
<title>Establishment of the standard curve</title>
<p>The standard plasmid was diluted in a 10-fold series and eight standard samples (10<sup>8</sup>&#x2013;10 copies/&#x03BC;L) were selected as templates to establish the standard curve of the triplex qRT-PCR. <xref ref-type="fig" rid="fig5">Figure 5</xref> shows the correlation coefficients (<italic>R</italic><sup>2</sup>), equation slopes and amplification efficiencies (<italic>E</italic>) for each virus: PEDV, 0.999, &#x2212;3.272 and 102.118%; TGEV, 0.999, &#x2212;3.294 and 101.179%; and PoRVA, 0.999, &#x2212;3.22 and 104.441%. The initial template and Ct value had a good linear relationship, as indicated by <italic>R</italic><sup>2</sup> and <italic>E</italic>.</p>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>Standard curve for the triplex qRT-PCR assay. <bold>(A)</bold> Standard curve for PEDV <italic>M</italic> gene. <bold>(B)</bold> Standard curve for TGEV <italic>N</italic> gene. <bold>(C)</bold> Standard curve for PoRVA <italic>NSP3</italic> gene.</p>
</caption>
<graphic xlink:href="fmicb-15-1390328-g005.tif"/>
</fig>
</sec>
<sec id="sec16">
<label>3.4</label>
<title>Specificity of the triplex qRT-PCR</title>
<p>Genomic DNA or RNA of 16 porcine pathogens (PEDV, TGEV, PoRVA, PRV, PCV2, PPV, PDCoV, SVA, <italic>T. gondii</italic>, <italic>L. interrogans</italic>, <italic>M. hyopneumoniae</italic>, <italic>M. hyorhinis</italic>, <italic>H. parasuis</italic>, <italic>S. suis</italic>, <italic>P. multocida</italic> and <italic>A. pleuropneumoniae</italic>) was used as a template for the triplex qRT-PCR. Amplification curves were obtained for PEDV, TGEV and PoRVA but not for the other porcine pathogens (<xref ref-type="fig" rid="fig6">Figure 6</xref>). Therefore, the triplex qRT-PCR assay was specific for detection of PEDV, TGEV and PoRVA, and had no cross-reaction with other porcine pathogens.</p>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption>
<p>Specific amplification curves for the triplex qRT-PCR assay. Three fluorescent signals were monitored by triplex qRT-PCR. RNA of PEDV, TGEV and PoRVA was used as a positive control. No fluorescent signal was observed when genomes of other porcine pathogens were used as templates. The graph type was set in linear phase to simultaneously display the three different fluorescent signals (VIC, Cy5 and FAM) with distinct signal intensities. Other pathogens included PRV, PCV2, PPV, PDCoV, SVA, <italic>T. gondii</italic>, <italic>L. interrogans</italic>, <italic>M. hyopneumoniae</italic>, <italic>M. hyorhinis</italic>, <italic>H. parasuis</italic>, <italic>S. suis</italic>, <italic>P. multocida</italic> and <italic>A. pleuropneumoniae.</italic></p>
</caption>
<graphic xlink:href="fmicb-15-1390328-g006.tif"/>
</fig>
</sec>
<sec id="sec17">
<label>3.5</label>
<title>Sensitivity of the triplex qRT-PCR</title>
<p>Different concentrations of standard plasmids were used as templates for the triplex qRT-PCR. <xref ref-type="table" rid="tab3">Table 3</xref> shows that a plasmid concentration of 100 copies/&#x03BC;L resulted in 100% positive detection rates for PEDV, TGEV and PoRVA. At 10 copies/&#x03BC;L, the positive detection rates were 100, 90 and 95% for PEDV, TGEV and PoRVA, respectively. At 1 copy/&#x03BC;L, the positive detection rates were 75, 5% and 0 for PEDV, TGEV and PoRVA, respectively. The LoD was defined as the lowest standard plasmid concentration with positive results in 85% of 20 replicates. Therefore, the triplex qRT-PCR showed high sensitivity, with a LoD of 10 copies/&#x03BC;L for PEDV, TGEV and PoRVA (<xref ref-type="fig" rid="fig7">Figure 7</xref>).</p>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Positive detection rate of 100 copies, 10 copies and 1 copy standard plasmids for 20 times.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Virus</th>
<th align="left" valign="top">Concentration</th>
<th align="center" valign="top">Positive number</th>
<th align="center" valign="top">Positive rate</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" rowspan="3">PEDV</td>
<td align="left" valign="middle">100 copies/&#x03BC;L</td>
<td align="center" valign="top">20</td>
<td align="center" valign="top">100%</td>
</tr>
<tr>
<td align="left" valign="middle">10 copies/&#x03BC;L</td>
<td align="center" valign="top">20</td>
<td align="center" valign="top">100%</td>
</tr>
<tr>
<td align="left" valign="middle">1 copy/&#x03BC;L</td>
<td align="center" valign="top">15</td>
<td align="center" valign="top">75%</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">TGEV</td>
<td align="left" valign="middle">100 copies/&#x03BC;L</td>
<td align="center" valign="top">20</td>
<td align="center" valign="top">100%</td>
</tr>
<tr>
<td align="left" valign="middle">10 copies/&#x03BC;L</td>
<td align="center" valign="top">18</td>
<td align="center" valign="top">90%</td>
</tr>
<tr>
<td align="left" valign="middle">1 copy/&#x03BC;L</td>
<td align="center" valign="top">1</td>
<td align="center" valign="top">5%</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">PoRVA</td>
<td align="left" valign="middle">100 copies/&#x03BC;L</td>
<td align="center" valign="top">20</td>
<td align="center" valign="top">100%</td>
</tr>
<tr>
<td align="left" valign="middle">10 copies/&#x03BC;L</td>
<td align="center" valign="top">19</td>
<td align="center" valign="top">95%</td>
</tr>
<tr>
<td align="left" valign="middle">1 copy/&#x03BC;L</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">0</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig position="float" id="fig7">
<label>Figure 7</label>
<caption>
<p>The sensitivity of the triplex qRT-PCR assay. <bold>(A)</bold> Sensitivity for PEDV <italic>M</italic> gene. <bold>(B)</bold> Sensitivity for TGEV <italic>N</italic> gene. <bold>(C)</bold> Sensitivity for PoRVA <italic>NSP3</italic> gene.</p>
</caption>
<graphic xlink:href="fmicb-15-1390328-g007.tif"/>
</fig>
</sec>
<sec id="sec18">
<label>3.6</label>
<title>Repeatability and reproducibility of the triplex qRT-PCR</title>
<p>Three concentrations of standard plasmids, 10<sup>6</sup>, 10<sup>4</sup> and 100 copies/&#x03BC;L, were used to assess the repeatability and reproducibility of the triplex qRT-PCR. The intra-and inter-assay CVs were 0.08&#x2013;0.79% and 0.37&#x2013;0.83%, respectively (<xref ref-type="table" rid="tab4">Table 4</xref>), which indicated good repeatability and reproducibility.</p>
<table-wrap position="float" id="tab4">
<label>Table 4</label>
<caption>
<p>Repeatability and reproducibility evaluation of the triplex qRT-PCR assay.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Virus</th>
<th align="center" valign="top" rowspan="2">Concentration (copies/&#x03BC;L)</th>
<th align="center" valign="top" colspan="3">Intra-assay</th>
<th align="center" valign="top" colspan="3">Inter-assay</th>
</tr>
<tr>
<th align="center" valign="top">Mean Ct value</th>
<th align="center" valign="top">SD</th>
<th align="center" valign="top">CV (%)</th>
<th align="center" valign="top">Mean Ct value</th>
<th align="center" valign="top">SD</th>
<th align="center" valign="top">CV (%)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" rowspan="3">PEDV</td>
<td align="center" valign="top">10<sup>6</sup></td>
<td align="center" valign="top">19.73</td>
<td align="center" valign="top">0.05</td>
<td align="center" valign="top">0.26%</td>
<td align="center" valign="top">19.63</td>
<td align="center" valign="top">0.16</td>
<td align="center" valign="top">0.83%</td>
</tr>
<tr>
<td align="center" valign="top">10<sup>4</sup></td>
<td align="center" valign="top">26.44</td>
<td align="center" valign="top">0.11</td>
<td align="center" valign="top">0.41%</td>
<td align="center" valign="top">26.34</td>
<td align="center" valign="top">0.19</td>
<td align="center" valign="top">0.73%</td>
</tr>
<tr>
<td align="center" valign="top">10<sup>2</sup></td>
<td align="center" valign="top">32.89</td>
<td align="center" valign="top">0.13</td>
<td align="center" valign="top">0.40%</td>
<td align="center" valign="top">32.62</td>
<td align="center" valign="top">0.27</td>
<td align="center" valign="top">0.82%</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">TGEV</td>
<td align="center" valign="top">10<sup>6</sup></td>
<td align="center" valign="top">18.56</td>
<td align="center" valign="top">0.02</td>
<td align="center" valign="top">0.08%</td>
<td align="center" valign="top">18.51</td>
<td align="center" valign="top">0.08</td>
<td align="center" valign="top">0.42%</td>
</tr>
<tr>
<td align="center" valign="top">10<sup>4</sup></td>
<td align="center" valign="top">25.32</td>
<td align="center" valign="top">0.03</td>
<td align="center" valign="top">0.11%</td>
<td align="center" valign="top">25.24</td>
<td align="center" valign="top">0.10</td>
<td align="center" valign="top">0.40%</td>
</tr>
<tr>
<td align="center" valign="top">10<sup>2</sup></td>
<td align="center" valign="top">31.54</td>
<td align="center" valign="top">0.22</td>
<td align="center" valign="top">0.71%</td>
<td align="center" valign="top">31.23</td>
<td align="center" valign="top">0.26</td>
<td align="center" valign="top">0.83%</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">PoRVA</td>
<td align="center" valign="top">10<sup>6</sup></td>
<td align="center" valign="top">19.12</td>
<td align="center" valign="top">0.10</td>
<td align="center" valign="top">0.51%</td>
<td align="center" valign="top">19.00</td>
<td align="center" valign="top">0.14</td>
<td align="center" valign="top">0.76%</td>
</tr>
<tr>
<td align="center" valign="top">10<sup>4</sup></td>
<td align="center" valign="top">25.82</td>
<td align="center" valign="top">0.08</td>
<td align="center" valign="top">0.31%</td>
<td align="center" valign="top">25.77</td>
<td align="center" valign="top">0.09</td>
<td align="center" valign="top">0.37%</td>
</tr>
<tr>
<td align="center" valign="top">10<sup>2</sup></td>
<td align="center" valign="top">32.14</td>
<td align="center" valign="top">0.26</td>
<td align="center" valign="top">0.79%</td>
<td align="center" valign="top">31.97</td>
<td align="center" valign="top">0.19</td>
<td align="center" valign="top">0.61%</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec19">
<label>3.7</label>
<title>Detection of clinical samples</title>
<p>A total of 256 porcine anal swab samples were tested using the triplex qRT-PCR. The positive rates for PEDV, TGEV and PoRVA were 2.73% (7/256), 3.91% (10/256) and 19.14% (49/256), respectively. To verify the accuracy of the method, the clinical samples were also tested by the triplex RT-PCR recommended by the Chinese national standard (<xref ref-type="bibr" rid="ref5">GB/T 36871-2018, 2018</xref>). The triplex RT-PCR results showed that the positive rates for PEDV, TGEV and PoRVA were 2.73% (7/256), 3.91% (10/256) and 14.84% (38/256), respectively. Both methods detected seven samples co-infected with PEDV and PoRVA. The new triplex qRT-PCR had 100% (PEDV), 100% (TGEV) and 95.70% (PoRVA) agreement with the triplex RT-PCR, indicating that the new approach was accurate, reliable and more sensitive (<xref ref-type="table" rid="tab5">Table 5</xref>).</p>
<table-wrap position="float" id="tab5">
<label>Table 5</label>
<caption>
<p>Detection of clinical samples by the triplex qRT-PCR and RT-PCR methods.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Virus</th>
<th align="center" valign="top" colspan="3">Triplex qRT-PCR (in this study)</th>
<th align="center" valign="top" colspan="3">Triplex RT-PCR Chinese national standard (<xref ref-type="bibr" rid="ref5">GB/T 36871-2018, 2018</xref>)</th>
<th align="center" valign="top" rowspan="2">Coincidence rate</th>
</tr>
<tr>
<th align="center" valign="top">Sample number</th>
<th align="center" valign="top">Positive number</th>
<th align="center" valign="top">Positive rate</th>
<th align="center" valign="top">Sample number</th>
<th align="center" valign="top">Positive number</th>
<th align="center" valign="top">Positive rate</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">PEDV</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">2.73%</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">2.73%</td>
<td align="center" valign="top">100%</td>
</tr>
<tr>
<td align="left" valign="top">TGEV</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">3.91%</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">10</td>
<td align="center" valign="top">3.91%</td>
<td align="center" valign="top">100%</td>
</tr>
<tr>
<td align="left" valign="top">PoRVA</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">49</td>
<td align="center" valign="top">19.14%</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">38</td>
<td align="center" valign="top">14.84%</td>
<td align="center" valign="top">95.70%</td>
</tr>
<tr>
<td align="left" valign="top">PEDV + TGEV</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">100%</td>
</tr>
<tr>
<td align="left" valign="top">PEDV + PoRVA</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">2.73%</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">7</td>
<td align="center" valign="top">2.73%</td>
<td align="center" valign="top">100%</td>
</tr>
<tr>
<td align="left" valign="top">TGEV + PoRVA</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">100%</td>
</tr>
<tr>
<td align="left" valign="top">PEDV + TGEV + PoRVA</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">256</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">0</td>
<td align="center" valign="top">100%</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
</sec>
<sec sec-type="discussion" id="sec20">
<label>4</label>
<title>Discussion</title>
<p>PEDV, TGEV and PoRVA are porcine enteric RNA viruses that cause porcine viral diarrhea (<xref ref-type="bibr" rid="ref3">Chen et al., 2010</xref>; <xref ref-type="bibr" rid="ref37">Zhao et al., 2016</xref>; <xref ref-type="bibr" rid="ref35">Zhang et al., 2017</xref>). Co-infections with various combinations and all three viruses are common in swine herds worldwide (<xref ref-type="bibr" rid="ref25">Song et al., 2006</xref>; <xref ref-type="bibr" rid="ref15">Liu et al., 2019</xref>; <xref ref-type="bibr" rid="ref7">El-Tholoth et al., 2021</xref>). These co-infections severely compromise the herd immunity and result in an increased risk of secondary infections, higher piglet mortality and significant economic losses, and they are a major concern for the swine industry (<xref ref-type="bibr" rid="ref12">Jung et al., 2008</xref>; <xref ref-type="bibr" rid="ref19">Mesonero-Escuredo et al., 2018</xref>; <xref ref-type="bibr" rid="ref24">Song et al., 2022</xref>).</p>
<p>Currently, the commonly used molecular detection techniques for PEDV, TGEV and PoRVA include RT-PCR, nested RT-PCR, qRT-PCR, reverse transcription loop-mediated isothermal amplification, reverse transcription recombinase-aided amplification, and CRISPR-Cas nucleic acid detection (<xref ref-type="bibr" rid="ref18">Marthaler et al., 2014</xref>; <xref ref-type="bibr" rid="ref2">Areekit et al., 2022</xref>; <xref ref-type="bibr" rid="ref29">Wu et al., 2022</xref>; <xref ref-type="bibr" rid="ref14">Lazov et al., 2023</xref>; <xref ref-type="bibr" rid="ref30">Xia et al., 2024</xref>). RT-PCR and nested RT-PCR are not capable of quantitative analysis, and their operation is cumbersome, time-consuming and less sensitive. Isothermal amplification techniques, including reverse transcription loop-mediated isothermal amplification and reverse transcription recombinase-aided amplification, are prone to false-positive results. CRISPR-Cas nucleic acid detection is expensive and not suitable for large-scale detection, and its multiplex technology is not yet matured. qRT-PCR is a highly specific and sensitive method for quantifying trace amounts of RNA in samples and is the most practical technique for the detection of viral RNA. It displays the results as fluorescent signals, which are easy to interpret. In particular, the multiplex qRT-PCR technique can detect multiple target genes of various pathogens in a single-tube reaction, using specific primers and probes with different fluorescent labels. Researchers have established some multiplex qRT-PCR detection methods for pathogens related to porcine viral diarrhea (<xref ref-type="bibr" rid="ref9">Han et al., 2019</xref>; <xref ref-type="bibr" rid="ref10">Huang et al., 2019</xref>; <xref ref-type="bibr" rid="ref11">Jia et al., 2019</xref>). The detection method using SYBR Green fluorescent dye requires validation of product specificity through melting curve analysis. However, in practical applications, issues such as false-positive signals, dye redistribution, and low sensitivity can affect the reliability of detection results. However, the one-step TaqMan probe-based multiplex qRT-PCR method allows simultaneous detection of various RNA viruses without prior reverse transcription. In practical applications, it is easier to operate and has strong practicality for daily monitoring of pig diseases.</p>
<p>In this study, we designed three pairs of virus-gene-specific primers and corresponding probes for one-step triplex qRT-PCR, which can simultaneously detect PEDV, TGEV and PoRVA in one tube. We inserted three gene fragments into the same vector to generate a standard plasmid containing three gene targets for the triplex qRT-PCR, rather than using a mixture of three standard plasmids. This approach reduced the preparation cost of standard plasmids and minimized the systematic errors from adding three different plasmids. The sensitivity test revealed a LoD of 10 copies/&#x03BC;L for each pathogen. A strong linear correlation between Ct values and standard copy numbers was demonstrated by the standard curve plots. The primer and probe sequences used in the detection method were highly specific, and the fluorescent dyes VIC, Cy5 and FAM did not interfere with each other. Thus, PEDV, TGEV and PoRVA were accurately detected without cross-reaction with other swine pathogens (PRV, PCV2, PPV, PDCoV, SVA, <italic>T. gondii</italic>, <italic>L. interrogans</italic>, <italic>M. hyopneumoniae</italic>, <italic>M. hyorhinis</italic>, <italic>H. parasuis</italic>, <italic>S. suis</italic>, <italic>P. multocida</italic> and <italic>A. pleuropneumoniae</italic>). Furthermore, we tested 256 porcine anal swab samples with the developed triplex qRT-PCR method to verify its practicality and usefulness in clinical samples. The results indicated that PEDV, TGEV and PoRVA were detected in 7 (2.73%), 10 (3.91%) and 49 (19.14%) samples, respectively. This suggested that PEDV, TGEV and PoRVA persisted in pig herds. Co-infection with two or more of PEDV, TGEV and PoRVA was also common, which can worsen immunosuppression and inflammation, increase the risk of secondary infection by other pathogens, and exacerbate these diseases. This was supported by the detection of seven samples that were co-infected with PEDV and PoRVA in 256 clinical samples. We also tested 256 samples with the triplex RT-PCR detection method recommended by the Chinese national standard (<xref ref-type="bibr" rid="ref5">GB/T 36871-2018, 2018</xref>). The results showed that consistency rates of 100% (PEDV), 100% (TGEV) and 95.70% (PoRVA) between the two methods. The sensitivity of the triplex qRT-PCR was significantly higher than that of triplex RT-PCR.</p>
</sec>
<sec sec-type="conclusions" id="sec21">
<label>5</label>
<title>Conclusion</title>
<p>We developed a triplex qRT-PCR for simultaneous and differential detection of PEDV, TGEV and PoRVA. This new method is cost-effective, efficient and user-friendly. It can obtain results within an hour regardless of the number of samples to be tested or diagnosed, whether for routine screening or temporary diagnosis of these three pathogens in pig herds. It provides a reliable detection technique for accurate diagnosis, epidemiological investigation and microbiological quality control of laboratory pigs.</p>
</sec>
<sec sec-type="data-availability" id="sec22">
<title>Data availability statement</title>
<p>The sequence presented in the study is showed in <xref rid="SM1" ref-type="supplementary-material">Supplementary Table S1</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec sec-type="ethics-statement" id="sec23">
<title>Ethics statement</title>
<p>The manuscript presents research on animals that do not require ethical approval for their study.</p>
</sec>
<sec sec-type="author-contributions" id="sec24">
<title>Author contributions</title>
<p>TL: Investigation, Methodology, Writing &#x2013; original draft. KL: Methodology, Validation, Writing &#x2013; original draft. CL: Investigation, Project administration, Writing &#x2013; original draft. CX: Project administration, Supervision, Writing &#x2013; original draft. CG: Funding acquisition, Project administration, Supervision, Writing &#x2013; review &#x0026; editing.</p>
</sec>
</body>
<back>
<sec sec-type="funding-information" id="sec25">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study was supported by the National Key Research and Development Program (2021YFF0703000), Pilot Technology Project of National Pig Technology Innovation Center (NCTIP-XD1C09), Special Funds for Basic Scientific Research Operations of Central Public Welfare Scientific Research Institutions (1610302022018).</p>
</sec>
<sec sec-type="COI-statement" id="sec26">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="sec100" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="sec27">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fmicb.2024.1390328/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fmicb.2024.1390328/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Table_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/>
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