key: cord-276542-lxwls664
authors: Pan, Zhongzhou; Lu, Jiaxuan; Wang, Ningning; He, Wan-Ting; Zhang, Letian; Zhao, Wen; Su, Shuo
title: Development of a TaqMan-probe-based multiplex real-time PCR for the simultaneous detection of emerging and reemerging swine coronaviruses
date: 2020-06-03
journal: Virulence
DOI: 10.1080/21505594.2020.1771980
sha: 
doc_id: 276542
cord_uid: lxwls664

With the outbreak of the recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, coronaviruses have become a global research hotspot in the field of virology. Coronaviruses mainly cause respiratory and digestive tract diseases, several coronaviruses are responsible for porcine diarrhea, such as porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and emerging swine acute diarrhea syndrome coronavirus (SADS-CoV). Those viruses have caused huge economic losses and are considered as potential public health threats. Porcine torovirus (PToV) and coronaviruses, sharing similar genomic structure and replication strategy, belong to the same order Nidovirales. Here, we developed a multiplex TaqMan-probe-based real-time PCR for the simultaneous detection of PEDV, PDCoV, PToV, and SADS-CoV for the first time. Specific primers and TaqMan fluorescent probes were designed targeting the ORF1a region of PDEV, PToV, and SADS-CoV and the ORF1b region of PDCoV. The method showed high sensitivity and specificity, with a detection limit of 1 × 10(2) copies/μL for each pathogen. A total of 101 clinical swine samples with signs of diarrhea were analyzed using this method, and the result showed good consistency with conventional reverse transcription PCR (RT-PCR). This method improves the efficiency for surveillance of these emerging and reemerging swine enteric viruses and can help reduce economic losses to the pig industry, which also benefits animal and public health.

Coronaviruses, belonging to the family Coronaviridae, order Nidovirales, are single-stranded, positive-sense RNA viruses with the largest genome among known RNA viruses [1, 2] . According to genetic and antigenic characteristics, coronaviruses can be divided into four genera:

α-coronaviruses, β-coronaviruses, γcoronaviruses, and δ-coronaviruses [3] [4] [5] . Coronaviruses can cause respiratory and gastrointestinal diseases in animals and humans [6] . Generally, αand β-coronaviruses only infect mammals, while γ-and δ-coronaviruses mainly infect birds, but some of them can also infect mammals [4] . Of note, coronaviruses exhibit a pronounced propensity for interspecies transmission as illustrated by important emerging viruses in humans such as SARS-CoV and Middle East respiratory syndrome-related coronavirus (MERS-CoV), as well as the recent SARS-CoV-2 that is causing a major human pandemic [7, 8, 9] .

Compared to many other species, pigs are in frequent contact with both humans and other animals such as pets, livestock and wild animals, and theoretically possess a greater chance to promote cross-species viral transmission. There are currently six coronaviruses that can infect pigs: PEDV, transmissible gastroenteritis virus (TGEV), porcine respiratory coronavirus (PRCV), porcine hemagglutinating encephalomyelitis virus (PHEV), SADS-CoV, and PDCoV [10] . With the exception of PRCV and PHEV, the remaining four can all cause severe diarrhea, dehydration, and death in pigs [3, 11] . PEDV is an αcoronavirus that causes long-lasting and extremely harmful swine diarrhea worldwide. PEDV may have originated from bat coronavirus [12] . It has high genome variability and different degrees of virulence among different strains [13] . PEDV strains can be divided into genotype G1 and genotype G2 with high genetic diversity. Both genotypes can cause catastrophic herd harm, of which the G2 variant has spread rapidly worldwide since 2010 [14] [15] [16] [17] . SADS-CoV is also an αcoronavirus and is regarded to share a relationship with rhinolophus bat coronavirus HKU2 [18] . It was first discovered in January, 2017 in Guangdong, China. Afterward, there were no other reemerging SADS-CoV strains detected until it appeared again in Guangdong, China causing devastating damage to the local pig industry in 2019 [11] . This suggests possible periodic outbreaks of SADS-CoV could be observed in years to come. PDCoV, a δ-coronavirus, was first detected in 2012 and caused PEDV-like signs in pigs [19] [20] [21] 22] . Birds can be considered as the natural hosts of δ-coronaviruses. Based on their ability to spread across species, δ-coronaviruses may "jump" the species barrier and adapt to mammals [23] . It has been reported that δ-coronaviruses have also been detected in Asian leopard cats and Chinese ferret-badgers [10, 24] . PToV was first discovered by Kroneman et al. in 1998 [2] . PToV was considered as a coronavirus for a long time before the ICTV (International Committee on Taxonomy of Viruses) classified it into family Tobaniviridae, order Nidovirales. PToV has a high positive rate in swine diarrhea samples [25] . However, it remains to be a potential pathogen in pigs [25] [26] [27] . It should be noted that frequent recombination events involving PToV have been discovered, some of which, especially those on the Hemagglutinin-esterases (HE) or Spike (S) genes, which encode proteins relating to attachment and invasion, could lead to changes in pathogenicity or host-specificity [28] [29] [30] [31] [32] .

So far, PEDV, PDCoV, SADS-CoV, and the coronavirus-like virus PToV have caused huge economic losses to the pig industry worldwide. In addition, their cross-species transmission ability may pose a threat to public health. In order to monitor these four viruses more efficiently, it is extremely important to develop a fast, simple, and accurate method for the detection and differentiation of those viral swine diarrhea pathogens. In clinical testing, multiplex real-time PCR has excellent performance. It has a larger detection capacity with higher speed and lower labor costs. However, the main reason hindering the application of multiplex real-time PCR on pathogen detection is the difficulty in assay design. Here, we developed a multiplex TaqMan-probe-based real-time PCR method for these four emerging and reemerging swine enteric viruses.

To ensure the detection performance of primers used in the multiplex real-time PCR method, all available sequences of PEDV, PDCoV, PToV, and SADS-CoV from GenBank were obtained and analyzed. The conserved region of ORF1a was chosen for designing primers and probes for PEDV, PToV, and SADS-CoV, and the ORF1b region was chosen for PDCoV. Four sets of primers and probes were designed using the Oligo 7 (Version 7.60) software (Table 1) . Primers and probes were synthesized by Sangon Biotech (Shanghai) Co., Ltd. Primers were also used for the construction of plasmid standards.

All primers for conventional RT-PCR in this study referred to former reports [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] .

Clinical samples collected during 2017-2019 were preserved at −80°C in our laboratory. Those samples were mainly from Henan, Jiangsu, Anhui and Guangdong provinces in China. PCR templates were DNA or cDNA, preserved at −20°C. All positive samples were identified by singleplex conventional RT-PCR in our laboratory and confirmed with DNA sequencing by Sangon Biotech (Shanghai) Co., Ltd.

Intestinal tissues or feces samples were treated with 3 to 5 volumes of PBS, mixed by shaking or vortex and supernatant was collected after centrifuged at 12,000 × g at 4°C for 15 minutes. Nucleic acids were extracted using the RNApure Virus Kit (Beijing ComWin Biotech Co., Ltd.) following the manufacturer's instructions. Reverse transcription was performed using the HiScript III RT SuperMix for qPCR (+gDNA wiper) Kit (Nanjing Vazyme biotechnology Co., Ltd.).

The target fragments of PEDV, PDCoV, PToV, and SADS-CoV were amplified separately via PCR using the cDNA obtained in the previous step with the Phanta Max Super-Fidelity DNA Polymerase (Nanjing Vazyme biotechnology Co., Ltd.) following the manufacturer's instructions. Primers used in the amplification were the same as used in multiplex real-time PCR method. The PCR fragments were then cloned into the pMD18-T vector (Takara Biomedical Technology (Beijing) Co., Ltd.) through TA colony and confirmed by DNA sequencing. The plasmid copy number was calculated and the plasmids were diluted from 1 × 10 7 copies/μL to 1 × 10 1 copies/μL. Singleplex real-time PCR was performed for each virus using the 10-fold diluted plasmids to generate standard curves, based on which the E value (amplification efficiency), R 2 (correlation coefficient), and the standard equation were calculated.

As shown in Table S1 , the total volume of the singleplex real-time PCR reaction was 20 μL, consisting of 10 μL of 2× AceQ qPCR Probe Master Mix (AceQ qPCR Probe Master Mix kit, Nanjing Vazyme biotechnology Co., Ltd.), 0.4 μL of each forward and reverse primer (10 μM), 0.2 μL of TaqMan probe (10 μM), 2 μL of template, and the remaining volume of nuclease-free water.

Amplification was carried out on a Roche LightCycler® 96 Instrument (Roche Life Science) using the following program: 95°C for 600 s; 40 cycles of 95°C for 10 s, 55°C for 10 s, and 72°C for 20 s. Fluorescence signal was automatically collected at the end of each cycle.

The singleplex real-time PCR assays for PEDV, PDCoV, PToV, and SADS-CoV described above were multiplexed into one reaction system consisting of 2× AceQ qPCR Probe Master Mix (AceQ qPCR Probe Master Mix kit, Nanjing Vazyme biotechnology Co., Ltd.), primers and probes for all four viruses, and templates. The multiplex reaction system was then optimized using different volumes of primers (10 μM) and probes (10 μM), and the optimal volumes of templates were determined. In the optimization stage, the final concentration of primers and probes in the system ranged from 1200 nM to 2400 nM and 200 nM to 1000 nM, respectively. The plasmid standards containing 1 × 10 3 copies/μL were chosen as templates. The same instrument and real-time PCR program were used as described above.

To determine the limit of detection (LOD) of the multiplex detection method, we performed real-time PCR reactions for each virus separately, using 10-fold serial dilutions of standard plasmid templates ranging from 1 × 10 7 copies/μL to 1 × 10 1 copies/μL. To confirm the detection limit, a multiplex real-time PCR was performed using plasmid templates of all four viruses at the concentration of the presumable detection limit with 23 replicates for each concentration. The lowest concentration that met the positive detection rate of 95% was considered as the reliable LOD.

To rule out potential false positives caused by other viruses that may present in the samples, positive samples for PEDV, PDCoV, PToV, SADS-CoV, TGEV, porcine kobuvirus (PKV), classical swine fever virus (CSFV), porcine sapelovirus (PSV), porcine teschenvirus (PTV), and porcine rotavirus (PoRV) were tested using the multiplex real-time PCR detection method. All the cDNA samples were previously synthesized and stored in our laboratory.

The assay was repeated three times with a 7-days interval, using 10-fold dilutions of the standard plasmid of each pathogen ranging from 1 × 10 7 copies/μL to the LOD with three replicates per reaction. Each template was a mixture of standard plasmid of four pathogens at the same concentration. The coefficient of variation (CV) of the Cq values of the samples at each concentration in the three experiments was calculated to estimate repeatability.

Plasmid standards of two, three or four target pathogens at the same concentration were randomly chosen and mixed as templates and detected using our new method. Three concentrations (1 × 10 7 copies/μL, LOD and 10 times the LOD) of the plasmid standards were tested.

To simulate actual co-infection events, we mixed the plasmid standards of the four target pathogens with one at 1 × 10 7 copies/μL and the other three at the LOD and then detected the template mixture using our multiplex detection method.

We tested 45 newly-collected samples from pigs showing signs of diarrhea and 56 previouslyconfirmed positive samples (31 with PEDV only, 16 with PDCoV only, 3 with PToV only, 1 with SADS-CoV only, 4 with PEDV and PToV, and 1 with PEDV, PDCoV and PToV) using our multiplex detection method. The clinical performance of our established methods was evaluated by comparing the results with those of singleplex conventional RT-PCR. Positive samples detected by either method were then confirmed through DNA sequencing by Sangon Biotech (Shanghai) Co., Ltd.

As shown in Table 1 , the sequences of the primers and probes designed in this study are presented. PEDV, PDCoV, PToV, and SADS-CoV probes were labeled with FAM, VIC, Texas Red, and Cy5 separately. Plasmid standards with concentrations ranging from 1 × 10 7 copies/μL to 1 × 10 1 copies/μL of each pathogen were selected to perform a singleplex realtime PCR (Figure 1 ). The standard curves showed an acceptable amplification efficiency and correlation coefficient: PEDV R 2 = 0.9957, E value = 99%; PDCoV R 2 = 0.9990, E value = 100%; PToV R 2 = 0.9943, E value = 94%; and SADS-CoV R 2 = 0.9982, E value = 99%, indicating that our plasmid standards were qualified, and the primers and probes designed were efficient.

Among the four fluorophores used in the multiplex detection method, the fluorescence of Cy5 was the weakest and very susceptible to interference from other fluorophores due to its own physical properties. Therefore, the main purpose of the reaction optimization system was to improve the performance of the Cy5 fluorophores without hindering other fluorophores, and to achieve the best amplification efficiency (i.e. the lowest Cq value). We performed multiplex realtime PCR with final concentration of probes ranging from 200 nM to 1000 nM, and of primers ranging from 1200 nM to 2400 nM and compared the fluorescence intensity and Cq values of each possible combination. We concluded that the best final concentrations for probes and primers are 1000 nM and 2400 nM, respectively (Table 2 and Figure 2 ). The maximum volume of template that can be loaded in this system is 4.8 μL as shown in Table S2 .

Using the optimized system and the plasmid standards of each pathogen with concentrations ranging from 1 × 10 7 copies/μL to 1 × 10 1 copies/μL, we found that the method could identify positive samples with the concentrations as low as 1 × 10 1 copies/μL (Figure 3a and Table S3 ). However, follow-up experiments indicated that the detection rate of samples at 1 × 10 1 copies/μL was less than 95% of replicates (Table 3) . Thus, the reliable LOD of this method is 1 × 10 2 copies/μL. In this experiment, the cutoff line of positivity was automatically decided by the LightCycler® 96 Instrument.

We set the cutoff line of positivity of our method at 35, which means samples with a Cq value less than or equal to 32 (≤ 32) are regarded as positive, higher than 32 but less than or equal to 35 (32 < and ≤ 35) are invalid, higher than 35 (>35) are negative. The criteria were set based on two reasons. First, the LOD of our detection method was 1 × 10 2 copies/μL, of which the Cq value was around 32. Second, some samples at 1 × 10 1 copies/μL were detectable, however, the detection rate was unqualified, and the Cq values of those detectable samples were around 35. All following experiments complied with these criteria.

The optimized method was used to detect PEDV, PDCoV, PToV, and SADS-CoV in positive samples and some other samples derived from pigs with diarrhea positive for TGEV, PKV, CSFV, PSV, PTV, and PoRV. As shown in Figure 3b and Table S4 , the target pathogens were detected while the other pathogens were negative, indicating good specificity.

As is shown in Table S5 , most %CV values of the Cq values of the plasmid standard were less than 1% (81/ 96) with only a few %CV values ranging from 1% to 5% (15/96), indicating that this multiplex detection method is stable.

We selected plasmid standards with concentrations of 1 × 10 7 copies/μL, 1 × 10 3 copies/μL, and 1 × 10 2 copies/μL of different pathogens as templates to perform a co-infection simulation experiment. As shown in Figures 4, 5, and 6 , the multiplex detection method could detect duplex, triplex, or quadruplex simulation co-infections of the target pathogens, even pathogens with different concentrations (Figure 7) .

Two batches of clinical samples were tested by our established method to validate its performance in clinical use. The first batch consisted of 45 digestive tract samples recently collected from pig farms in China. The results of our method were 100% consistent with the results of singleplex conventional RT-PCR (Table S6 ). The second batch consisted of 56 positive samples stored in our laboratory, of which 31 were positive for PEDV alone, 16 were positive for PDCoV alone, 1 was positive for SADS-CoV alone, and 8 were positive for PToV (not necessarily alone). Our method was 100% (Table S6 ).

Virus cross-species transmission from wildlife reservoirs poses a remarkable threat to human and domestic animal health [18, 43] . Coronaviruses can cross the species barrier and gradually adapt to new hosts [44, 45] . For example, the recently emerged SARS-CoV-2 was estimated to have originated from bats spreading to wild animals or livestock and then to humans [46] . Animals may potentially serve as mixing vessels for the generation of novel recombinant coronaviruses and facilitate the viruses to expand their host tropism to humans [47] . In current swine breeding practices, humans have close contact with pigs, which further increases the possibility of viral transmission to humans, posing potential threat to human health [10] . Therefore, the detection of emerging and reemerging coronaviruses is of significance for farming and public health.

Among the four target pathogens in this study, PEDV is a coronavirus with considerably high prevalence and frequent recombination and rapid evolution rate [13] . SADS-CoV and PDCoV are two emerging coronaviruses and have been reported to be spreading and causing economic losses [11, 23] . PToV is regarded as a swine diarrhea virus that has not caused huge economic losses [25] . However, given the high recombination rate and evolutionary characteristics of coronavirus and torovirus, we cannot underestimate their potential threat [28] [29] [30] . It is very likely that a virulent strain could emerge and cause unpredictable damage to the pig industry [13] . Thus, monitoring these currently less harmful viruses, such as SADS-CoV, PDCoV, and PToV, is of great significance.

Pathogen monitoring nowadays largely relies on laboratory detection methods. Singleplex conventional RT-PCR has been widely applied for pathogen detection [34] [35] [36] 38] . However, such kind of assays are not convenient for the simultaneous detection of co-infection of multiple pathogens, which hinders further study of viral recombination events [3] . Given that co-infections of different coronaviruses and torovirus are common in the field and the high recombination frequency of coronavirus and torovirus, it is necessary to develop a fast, convenient detection method (e.g. multiplex realtime PCR) for the diagnosis of co-infections. PCR is fast, accurate and convenient for clinical sample screening. Co-infection of all the four pathogens at different concentrations. A: the concentration of plasmid standard of PEDV was 1 × 10 7 copies/μL and the others were 1 × 10 2 copies/μL; B: the concentration of plasmid standard of PDCoV was 1 × 10 7 copies/μL and the others were 1 × 10 2 copies/μL; C: the concentration of plasmid standard of PToV was 1 × 10 7 copies/μL and the others were 1 × 10 2 copies/μL; D: the concentration of plasmid standard of SADS-CoV was 1 × 10 7 copies/μL and the others were 1 × 10 2 copies/ μL. Two replicates were set per reaction. X-axis: Cycle, Y-axis: Fluorescence.

Real-time PCR is better than conventional PCR due to its faster, more sensitive and accurate detection capacity [48] . The use of probes is the most obvious and critical difference [49, 50] . In general, conventional RT-PCR is less sensitive than real-time PCR. The LOD of our multiplex real-time PCR detection method can reach as low as 1 × 10 2 copies/μL for each pathogen, while that of the singleplex conventional RT-PCR is generally around 1 × 10 3 copies/μL to 1 × 10 4 copies/μL [51] . Likewise, multiplex conventional RT-PCR shows no noticeable advantage in terms of sensitivity [34, 52] . Hui et al. developed a multiplex conventional RT-PCR assay for pancoronaviruses, in which the limits of detection were no less than 1 × 10 3 copies/μL [40] . Zhao et al. developed a multiplex RT-PCR detection for CSFV, porcine reproductive and respiratory syndrome virus (PRRSV), PEDV, and TGEV. The limit of detection of this method was 1 × 10 3 copies/μL [52] . On the other hand, although multiplex real-time PCR combines high sensitivity and high detection efficiency, the design of qualified multiplex real-time PCR assays, especially of quadruplex quantitative real-time PCR assays, is challenging [48, 49, 53] . In multiplex real-time PCR assays, multiple sets of oligonucleotides exist simultaneously in the reaction system, increasing the possibility for nonspecific amplification, which poses high demands on the specificity of primers and probes.

Improvements in detection method can bring many benefits. Accurate detection of virus at lower concentration enables the diagnosis and prevention of porcine diarrhea at an early stage. Some virulent strains may cause severe signs at a low titer, and thus a sensitive detection method is indispensable in such situations. Due to its lower false negative rate caused by lower LODs, our new detection method enables more powerful surveillance over those four swine diarrhea viruses and, hopefully, can benefit the construction of pig farms with higher biosecurity. However, the improvement in sensitivity also increases the possibility of false positive results, which imposes higher requirements on the prevention of contamination during sampling and assay set up. Good practice in the laboratory is necessary in order to get credible results.

In short, an excellent and efficient detection method should accurately reflect the epidemiological data (e.g. the scale of the disease, the rate of transmission, and the severity of the epidemic), so as to be beneficial to the monitoring and prevention of the disease [53] . Multiplex real-time PCR achieves better detection capability in less time and with lower labor cost, but its development is still challenging compared to singleplex conventional RT-PCR due to technical difficulties at the development stage. To the best of our knowledge, this is the first multiplex real-time PCR detection method for PEDV, PDCoV, PToV, and emerging SADS-CoV, which often present simultaneously among pigs. The multiplex detection method developed here can detect multiple pathogens in a single reaction, making detection for co-infection more convenient. This method can ensure good specificity and sensitivity, which will undoubtedly save labor and material costs.

Here, we developed a TaqMan-probe-based multiplex real-time PCR method for the simultaneous detection of emerging and reemerging PEDV, PDCoV, PToV and SADS-CoV of swine. The limit of detection can reach as low as 1 × 10 2 copies/μL for each pathogen with good specificity and repeatability. The application of this method in clinical detection will not only improve the detection capacity, but also reduce workload and cost, benefiting clinicians and epidemiologists. Program 

SS provided the study design and experiment, other authors contributed to the experiment. All authors contributed to writing the manuscript. All authors have approved the final version of the manuscript.

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We thank Professor Huang Yaowei (College of Animal Sciences, Zhejiang University) and Professor Zhou Jiyong (College of Animal Sciences, Zhejiang University) for their guidance on our coronavirus research and the help they provided on biological materials. We thank Haitao Qi (New Hope Liuhe Company) and Ao Liao (Han Shiwei Company) for providing pig samples. We thank Jiexiong Xie (Laboratory of Virology, Faculty of Veterinary Medicine, Ghent University) for helping us improve the paper.

The authors declare no competing financial interest.

This work was financially supported by the National Natural Science Foundation of Outstanding Youth Fund in China (NSFC Grant no. 31922081), the National Key Research and Development