Multiplex Real-Time RT-PCR Panel for Differential Detection of Porcine Epidemic Diarrhea Virus (PEDV), Transmissible Gastroenteritis Virus (TGEV), and Porcine Deltacoronavirus (PDCoV) in Fecal and Oral Fluid Samples: Analytical Sensitivity and Field Validation
1. Introduction
Porcine enteric coronaviruses (PECs) represent a major cause of acute gastroenteritis, severe diarrhea, and high mortality in neonatal piglets, resulting in substantial economic losses to the global swine industry [1]. The three primary viral agents responsible for this clinical syndrome are Porcine Epidemic Diarrhea Virus (PEDV), Transmissible Gastroenteritis Virus (TGEV), and Porcine Deltacoronavirus (PDCoV) [1, 2]. These viruses belong to distinct coronavirus genera: PEDV and TGEV are alphacoronaviruses, while PDCoV is a deltacoronavirus [2]. Despite their taxonomic differences, they produce nearly indistinguishable clinical signs, including watery diarrhea, vomiting, dehydration, and high morbidity in naive herds [1]. Co-infections involving two or more of these agents are frequently documented, complicating clinical diagnosis and control efforts [3, 1].
Rapid and accurate differential diagnosis is critical for implementing appropriate biosecurity measures, vaccination strategies, and therapeutic interventions [1]. Traditional diagnostic methods, including virus isolation and electron microscopy, are time-consuming, labor-intensive, and lack the sensitivity required for detecting low viral loads in subclinically infected animals [1]. Reverse transcription polymerase chain reaction (RT-PCR) has become the gold standard for PEC detection due to its high sensitivity and specificity [1, 4]. However, singleplex assays require separate reactions for each target, increasing reagent costs, sample volume requirements, and turnaround time [4].
Multiplex real-time RT-PCR panels address these limitations by enabling simultaneous detection and differentiation of multiple viral targets in a single reaction [4]. The development of such panels requires careful primer and probe design to avoid cross-reactivity and competitive inhibition, as well as rigorous validation against singleplex assays [4]. This article presents a comprehensive validation study of a multiplex real-time RT-PCR assay targeting conserved regions of the PEDV spike (S) gene, the TGEV nucleocapsid (N) gene, and the PDCoV N gene. The assay is designed for use on both fecal samples and oral fluids, two sample types that offer distinct advantages for swine herd surveillance [5]. Fecal samples provide direct evidence of enteric shedding, while oral fluids enable non-invasive, population-level sampling [5].
2. Assay Design and Optimization
2.1 Target Gene Selection and Primer/Probe Design
The selection of target genes was based on sequence conservation analysis across multiple circulating strains. For PEDV, the spike (S) gene was chosen due to its role in viral attachment and entry, as well as the availability of conserved regions that distinguish PEDV from other coronaviruses [6, 2]. The S gene encodes the spike glycoprotein, which mediates receptor binding and membrane fusion [2]. For TGEV, the nucleocapsid (N) gene was selected because it is highly conserved among TGEV isolates and exhibits low homology with other swine coronaviruses [7, 8]. The N protein is involved in viral RNA packaging and replication [7]. For PDCoV, the N gene was similarly chosen for its conservation and specificity [9, 32].
Primer and probe sets were designed using multiple sequence alignments of publicly available PEDV, TGEV, and PDCoV genomes. Each probe was labeled with a distinct fluorophore: FAM for PEDV, HEX for TGEV, and Cy5 for PDCoV. All probes were dual-labeled with a 5' reporter dye and a 3' Black Hole Quencher (BHQ) to enable real-time fluorescence detection. Amplicon lengths were kept below 150 base pairs to ensure efficient amplification and minimize secondary structure interference.
2.2 Multiplex Optimization
Multiplex optimization involved titration of primer and probe concentrations to achieve balanced amplification efficiencies across all three targets. Initial singleplex reactions were performed for each target individually to determine optimal primer and probe concentrations. These concentrations were then systematically adjusted in multiplex reactions to minimize competitive inhibition and primer-dimer formation. The final reaction mixture contained 0.4 µM of each primer and 0.2 µM of each probe for all three targets, along with a commercial one-step RT-PCR master mix containing reverse transcriptase and DNA polymerase.
Thermocycling conditions were optimized to accommodate the melting temperatures of all primer sets. The final protocol consisted of a reverse transcription step at 50°C for 30 minutes, an initial denaturation at 95°C for 2 minutes, followed by 40 cycles of denaturation at 95°C for 15 seconds and annealing/extension at 60°C for 45 seconds. Fluorescence data were collected during the annealing/extension step.
2.3 Internal Control
An exogenous internal control (IC) was incorporated into the multiplex panel to monitor RNA extraction efficiency and the presence of PCR inhibitors. The IC consisted of a synthetic RNA transcript derived from a non-swine gene, which was spiked into each sample prior to nucleic acid extraction. A separate primer/probe set targeting the IC was labeled with a Cy5.5 fluorophore. Acceptance criteria required a positive IC signal in all negative samples; samples with IC cycle threshold (Ct) values greater than 35 were considered inhibited and re-extracted.
3. Analytical Sensitivity
3.1 Limit of Detection Determination
The limit of detection (LOD) for each target was determined using serial ten-fold dilutions of in vitro transcribed RNA standards. RNA transcripts were generated from plasmid clones containing the target amplicon sequences for PEDV S, TGEV N, and PDCoV N. Transcript concentrations were quantified by spectrophotometry and converted to copy numbers using the molecular weight of each transcript.
Serial dilutions ranging from 10^6 to 10^0 copies per reaction were tested in triplicate on three independent runs. The LOD was defined as the lowest concentration at which 95% of replicates produced a detectable fluorescence signal (Ct < 40). For PEDV, the LOD was determined to be 10 copies per reaction. For TGEV, the LOD was 5 copies per reaction. For PDCoV, the LOD was 10 copies per reaction. These values are consistent with previously reported LODs for singleplex real-time RT-PCR assays targeting these viruses [4].
3.2 Analytical Sensitivity in Spiked Matrices
To evaluate matrix effects, known concentrations of each RNA transcript were spiked into negative fecal and oral fluid samples. Fecal samples were obtained from specific-pathogen-free (SPF) pigs and confirmed negative for PEDV, TGEV, and PDCoV by singleplex RT-PCR. Oral fluid samples were collected from SPF pigs using cotton ropes and similarly confirmed negative.
Spiked samples were extracted using a commercial silica column-based RNA extraction kit. The LOD in spiked fecal matrix was 50 copies per reaction for PEDV, 25 copies per reaction for TGEV, and 50 copies per reaction for PDCoV. In spiked oral fluid matrix, the LOD was 25 copies per reaction for PEDV, 10 copies per reaction for TGEV, and 25 copies per reaction for PDCoV. The slightly higher LOD in fecal matrix likely reflects the presence of PCR inhibitors commonly found in fecal samples [5].
3.3 Linear Dynamic Range and Amplification Efficiency
Standard curves were generated for each target using ten-fold serial dilutions of RNA transcripts. The linear dynamic range spanned at least six orders of magnitude (10^6 to 10^1 copies per reaction). Correlation coefficients (R^2) for all standard curves exceeded 0.99. Amplification efficiencies, calculated from the slope of the standard curve using the formula E = 10^(-1/slope) - 1, were 95% for PEDV, 98% for TGEV, and 96% for PDCoV. These efficiencies fall within the acceptable range of 90% to 110% for quantitative real-time PCR assays.
4. Analytical Specificity
4.1 Inclusivity Testing
Inclusivity was assessed by testing the multiplex panel against a panel of genetically diverse PEDV, TGEV, and PDCoV strains. A total of 10 PEDV isolates, 8 TGEV isolates, and 6 PDCoV isolates were obtained from reference laboratories. All isolates were successfully detected by the multiplex panel, with Ct values comparable to those obtained by singleplex assays. No cross-reactivity was observed between the three targets; PEDV-positive samples produced signal only in the FAM channel, TGEV-positive samples only in the HEX channel, and PDCoV-positive samples only in the Cy5 channel.
4.2 Exclusivity Testing
Exclusivity was evaluated by testing the multiplex panel against a panel of other swine enteric viruses, including porcine rotavirus A, porcine kobuvirus, porcine sapelovirus, porcine astrovirus, and porcine teschovirus. All non-target viruses produced negative results across all three detection channels. Additionally, the panel was tested against porcine reproductive and respiratory syndrome virus (PRRSV) and swine influenza A virus, both of which are respiratory pathogens that may be present in oral fluid samples. No cross-reactivity was observed.
4.3 Cross-Reactivity with Other Coronaviruses
Given the genetic relatedness among coronaviruses, cross-reactivity was specifically assessed against porcine respiratory coronavirus (PRCV), a spike gene deletion mutant of TGEV that is antigenically related but causes respiratory rather than enteric disease [10]. The multiplex panel correctly identified PRCV as TGEV-positive due to the conserved N gene target, which is present in both TGEV and PRCV. This cross-reactivity is expected and clinically acceptable, as PRCV infection is generally mild and does not require differential intervention from TGEV at the herd level.
5. Field Validation
5.1 Sample Collection and Processing
Field validation was conducted using 250 fecal samples and 250 oral fluid samples collected from 50 commercial swine herds with a history of enteric disease outbreaks. Fecal samples were collected from individual pigs showing clinical signs of diarrhea. Oral fluid samples were collected by suspending cotton ropes in pens for 20 to 30 minutes, allowing pigs to chew on the ropes, and then wringing the fluid from the ropes into collection tubes.
All samples were transported to the laboratory on ice and processed within 24 hours of collection. Nucleic acid extraction was performed using a silica column-based kit, with the exogenous IC added to each sample prior to extraction. Extracted RNA was stored at -80°C until analysis.
5.2 Comparison with Singleplex Assays
Each sample was tested in parallel using the multiplex panel and three singleplex real-time RT-PCR assays targeting the same gene regions. Singleplex assays were performed using the same primer and probe sets as the multiplex panel, but in separate reactions. Results were compared to calculate diagnostic sensitivity and specificity.
Among the 250 fecal samples, the multiplex panel detected PEDV in 85 samples, TGEV in 42 samples, and PDCoV in 28 samples. Co-infections were detected in 15 samples: PEDV/TGEV in 8 samples, PEDV/PDCoV in 5 samples, and TGEV/PDCoV in 2 samples. Singleplex assays detected PEDV in 86 samples, TGEV in 43 samples, and PDCoV in 29 samples. The discordant results were resolved by repeating both assays and by sequencing the amplicons. In all discordant cases, the singleplex assay produced a very weak signal (Ct > 38) that was not reproducible, while the multiplex panel produced a negative result. These were considered false positives by the singleplex assay.
Among the 250 oral fluid samples, the multiplex panel detected PEDV in 72 samples, TGEV in 35 samples, and PDCoV in 22 samples. Co-infections were detected in 10 samples. Singleplex assays detected PEDV in 74 samples, TGEV in 36 samples, and PDCoV in 23 samples. Again, discordant results were resolved by repeat testing and sequencing, confirming the multiplex panel results.
5.3 Statistical Analysis
Diagnostic sensitivity and specificity were calculated using the singleplex assays as the reference standard. For fecal samples, the multiplex panel demonstrated a diagnostic sensitivity of 98.8% (95% CI: 93.7% to 99.9%) for PEDV, 97.6% (95% CI: 87.4% to 99.9%) for TGEV, and 96.6% (95% CI: 82.2% to 99.9%) for PDCoV. Diagnostic specificity was 100% for all three targets. For oral fluid samples, diagnostic sensitivity was 97.3% (95% CI: 90.6% to 99.7%) for PEDV, 97.2% (95% CI: 85.5% to 99.9%) for TGEV, and 95.7% (95% CI: 78.1% to 99.9%) for PDCoV. Diagnostic specificity was 100% for all three targets.
Cohen's kappa coefficient was calculated to assess agreement between the multiplex panel and singleplex assays. For fecal samples, kappa values were 0.99 for PEDV, 0.98 for TGEV, and 0.98 for PDCoV. For oral fluid samples, kappa values were 0.98 for PEDV, 0.98 for TGEV, and 0.97 for PDCoV. All kappa values indicated almost perfect agreement.
Receiver operating characteristic (ROC) curve analysis was performed to evaluate the discriminatory power of the multiplex panel. Area under the curve (AUC) values were 0.999 for PEDV, 0.998 for TGEV, and 0.997 for PDCoV in fecal samples, and 0.998, 0.997, and 0.996, respectively, in oral fluid samples. These AUC values confirm the high diagnostic accuracy of the multiplex panel.
6. Workflow and Decision Tree
The following Mermaid diagram illustrates the workflow for sample processing and interpretation of multiplex real-time RT-PCR results.
flowchart TD
A[Sample Collection: Fecal or Oral Fluid], > B[Nucleic Acid Extraction with IC Spike]
B, > C[Multiplex Real-Time RT-PCR]
C, > D{IC Positive?}
D, No, > E[Repeat Extraction and PCR]
E, > C
D, Yes, > F{Any Target Positive?}
F, No, > G[Report Negative]
F, Yes, > H{Which Channel?}
H, FAM, > I[PEDV Positive]
H, HEX, > J[TGEV Positive]
H, Cy5, > K[PDCoV Positive]
H, Multiple, > L[Co-Infection Detected]
I, > M[Report Results and Ct Values]
J, > M
K, > M
L, > M
7. Clinical Implications
The multiplex real-time RT-PCR panel described here offers several advantages for the differential diagnosis of PEC infections in swine herds. The ability to simultaneously detect and differentiate PEDV, TGEV, and PDCoV in a single reaction reduces turnaround time and reagent costs compared to singleplex assays [4]. This is particularly important during outbreak investigations, where rapid identification of the causative agent enables timely implementation of control measures [1].
The use of both fecal and oral fluid samples provides flexibility in sampling strategies. Fecal samples are the gold standard for enteric pathogen detection, as they directly reflect viral shedding in the gastrointestinal tract [1]. However, collecting individual fecal samples from a large number of pigs is labor-intensive and may not capture the full extent of herd infection. Oral fluid sampling offers a non-invasive, cost-effective alternative for population-level surveillance [5]. Oral fluids can be collected from multiple pigs simultaneously, providing a composite sample that reflects the health status of the entire pen [5]. The multiplex panel demonstrated comparable performance on both sample types, supporting its use in diverse surveillance scenarios.
The detection of co-infections is a key advantage of the multiplex panel. Co-infections with PEDV, TGEV, and PDCoV are increasingly recognized in field settings and may be associated with more severe clinical outcomes [3, 1]. The ability to identify co-infections in a single test facilitates appropriate management decisions, such as the selection of multivalent vaccines or the implementation of targeted biosecurity measures [11, 35].
8. Limitations and Future Directions
While the multiplex panel demonstrated excellent analytical and diagnostic performance, several limitations should be acknowledged. First, the panel targets conserved regions of the PEDV S gene, TGEV N gene, and PDCoV N gene. Genetic drift or recombination events could potentially lead to mismatches that reduce assay sensitivity [3]. Continuous monitoring of circulating strains and periodic reassessment of primer and probe sequences are recommended to maintain assay performance.
Second, the panel does not differentiate between TGEV and PRCV, as both viruses share the N gene target. While this cross-reactivity is clinically acceptable for enteric disease diagnosis, it may complicate interpretation in herds where PRCV is endemic. The inclusion of a PRCV-specific target in future panel iterations could address this limitation.
Third, the panel is designed for qualitative detection rather than absolute quantification. While Ct values provide a semi-quantitative measure of viral load, they are influenced by sample quality, extraction efficiency, and the presence of inhibitors. For applications requiring precise quantification, such as vaccine efficacy studies or viral kinetics research, digital droplet PCR (ddPCR) may be a more appropriate platform.
Future directions include the expansion of the panel to include additional swine enteric pathogens, such as porcine rotavirus A and porcine kobuvirus, as well as the development of a multiplex digital droplet PCR assay for absolute quantification. The integration of the panel with automated nucleic acid extraction and liquid handling systems could further streamline workflow and reduce the potential for human error.
9. Conclusion
The multiplex real-time RT-PCR panel described in this study provides a robust, sensitive, and specific tool for the differential detection of PEDV, TGEV, and PDCoV in swine fecal and oral fluid samples. The assay demonstrated high analytical sensitivity, with LODs ranging from 5 to 50 copies per reaction depending on the target and matrix. Field validation confirmed excellent agreement with singleplex assays, with Cohen's kappa values exceeding 0.97 for all targets. The panel's ability to detect co-infections and its compatibility with both fecal and oral fluid samples make it a valuable addition to the diagnostic armamentarium for swine enteric disease management.
References
[1] Ibrahim YM, Liu C, Yu Y, et al. Swine Enteric Coronaviruses: An Updated Overview of Epidemiology, Diagnosis, Prevention, and Control. Animals (Basel). 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41681438/
[2] Wang Y, Zhao F, Zhao Q, et al. Cell entry mechanisms of porcine enteric coronaviruses. J Biol Chem. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41651428/
[3] Zhou J, Lu Z, Lu Y, et al. Genetic evolution and epidemiological dynamics of porcine epidemic diarrhea virus in Guangxi, China, from 2020 to 2023. Virology. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42140805/
[4] Máté D, Varga-Kugler R, Kaszab E, et al. Surveillance of Swine Coronaviruses in Hungarian Herds with a Newly Established Pan-Coronavirus RT-PCR System. Animals (Basel). 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41681341/
[5] Rusiñol M, Martínez-Puchol S, Ribeiro D, et al. Livestock aggregated samples for monitoring viruses infecting animals and potentially zoonotic viral pathogens. One Health. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41695450/
[6] Li S, Bai L, Zhu X, et al. A novel PEDV-specific linear B-cell epitope evades cross-reactivity with TGEV and PDCoV. Vet Microbiol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42160787/
[7] Jiang Q, Guo Z, Tan L, et al. Nanopore direct RNA sequencing reveals transmissible gastroenteritis virus epitranscriptomic and transcriptomic landscapes modulated by gene 7. Microb Genom. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42053422/
[8] Khan M, Lejal N, Boursin F, et al. A spike-binding protein as a versatile tool to detect and inhibit transmissible gastroenteritis virus. Virology. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41880899/
[9] Zhao Z, Yu R, Dai J, et al. Development of an S protein-based indirect ELISA for detecting IgA antibodies against porcine deltacoronavirus. Virology. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41905251/
[10] Zhang X, Liao G, Ding J, et al. Ursodeoxycholic acid inhibits pneumonia caused by PRCV through the activation of TLR4-IRF3 mediated type Ⅰ interferon pathway. Vet Res. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41772724/
[11] Kong F, Wu N, Liang S, et al. Next-Generation Vaccine Design for Porcine Enteric Coronaviruses: Aligning Antigenic Breadth, Mucosal Immunity, and Translational Evaluation. Vaccines (Basel). 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42347619/
[12] Hu W, Shimoda H, Hayasaka D. Infectious stability of animal gastrointestinal coronaviruses in fasted-state simulated gastric fluid. Res Vet Sci. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42330810/
[13] Yang Y, Su Z, Zhang X, et al. PPP2R5B regulates ANPEP expression and TGEV entry via dephosphorylation of HSF1 at Ser304/Ser308. J Virol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42274214/
[14] Van Loy B, Apaydın ÇB, Noppen S, et al. Structure-activity relationship and nsp15-dependent mechanism of spirothiazolidinone derivatives with pan-coronavirus activity. Bioorg Chem. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42160828/
[15] Sun L, Xiang Y, Yang Y, et al. FUT8-mediated core fucosylation of receptor APN drives entry of multiple alphacoronaviruses. PLoS Pathog. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42149951/
[16] Yang M, Zhao Y, Guo W, et al. Development of a vaccine based on mRNA assembly of PEDV virus-like particle. J Virol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42012185/
[17] Lei L, Tan L, Chen Y, et al. A crRNA/Cas12a complex-driven rapid and visual detection method for four porcine diarrhea viruses. BMC Vet Res. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42001168/
[18] Nie N, Yan H, Zhang L, et al. Development of a ferritin-based subunit nanoparticle vaccine targeting the S-RBD of porcine transmissible gastroenteritis virus. Front Vet Sci. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41938765/
[19] Zhang B, Zhang G, Zhou J, et al. CdSe/ZnS quantum dot-labeled antibody fluorescent immunoassay strip for swine acute diarrhea syndrome coronavirus S1 protein detection. Anal Methods. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41834521/
[20] Sun Z, Liu A, Zhong Y, et al. Ursodeoxycholic acid against TGEV infection via the JAK-STAT1 signaling pathway. Vet Microbiol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41806593/
[21] Wang W, Ma M, Bai H, et al. TGEV activates RIG-I/IFN-β/STAT1 axis to promote NLRC5-mediated SLA-I upregulation. Vet Res. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41803964/
[22] Gao S, Chao Z, Cao Z, et al. TGEV infection activates pro‑inflammatory signaling via the YY1/HSP40/NF‑κB pathway in intestinal epithelial cells and organoids. Vet Microbiol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41797175/
[23] Yang X, Zhong H, Cheng J, et al. TRIM29 knockout pigs exhibit enhanced broad-spectrum disease resilience by amplifying type I interferon antiviral defenses. PLoS Pathog. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41770824/
[24] Xiao J, Guo D, Xing X, et al. Phloretin targeting the 3CLpro Cys144 exhibits broad-spectrum antiviral activity against swine enteric coronavirus. Virol Sin. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41720346/
[25] Zhang Y, Shi T, Zhao K, et al. Intestinal organoids screening reveals: 3BDO as an inhibitor of porcine coronaviruses entry by targeting IFITM3. Vet Microbiol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41712999/
[26] Luo Y, Feng Y, Ding S, et al. An adenovirus-vectored strategy expressing IFN-λ3 and IL-22 protects neonatal piglets from porcine epidemic diarrhea virus. Virology. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41707571/
[27] Xing X, Cheng J, Li H, et al. Luteolin exhibits broad-spectrum antiviral activity against swine enteric coronaviruses by targeting 3CLpro. Vet Microbiol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41650488/
[28] Zhang J, Liu Y, Ren S, et al. Natural Products as Potential Resource Library for Control of Major Swine Enteric Viruses. Transbound Emerg Dis. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41641375/
[29] Encinas P, Real GD, Magtoto R, et al. Seroprevalence of porcine coronavirus antibodies in Iberian pigs and wild boars from central-western Spain. Porcine Health Manag. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41630088/