Multiplex Digital PCR for Simultaneous Detection and Quantification of Porcine Respiratory and Enteric Viruses in Oral Fluids and Fecal Samples

Introduction

The swine industry faces continuous challenges from a diverse array of viral pathogens that cause respiratory and enteric disease, leading to significant economic losses and welfare concerns. Porcine reproductive and respiratory syndrome virus (PRRSV), swine influenza A virus (SIV), porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), and porcine deltacoronavirus (PDCoV) represent a subset of these agents that frequently circulate within herds, often as co-infections [1, 2]. The ability to detect and quantify multiple viral targets simultaneously from non-invasive sample types such as oral fluids and fecal samples is critical for effective surveillance, early outbreak detection, and understanding co-infection dynamics [3]. While quantitative real-time PCR (RT-qPCR) has been the cornerstone of molecular diagnostics for these pathogens, digital PCR (dPCR) offers distinct advantages in terms of absolute quantification, precision, and tolerance to sample inhibitors [4, 5].

This article provides a detailed scientific review of multiplex digital PCR technology for the simultaneous detection and quantification of porcine respiratory and enteric viruses. It compares dPCR with RT-qPCR, discusses assay design principles, validation parameters, and clinical performance in oral fluid and fecal matrices, and explores applications in herd surveillance and outbreak management.

Principles of Digital PCR

Digital PCR is a nucleic acid quantification method that relies on the partitioning of a sample into a large number of individual reaction chambers or droplets, such that each partition contains either zero or at least one target molecule [1, 3]. After endpoint amplification, the number of positive partitions is counted, and the absolute concentration of the target nucleic acid is calculated using Poisson statistics. This approach eliminates the need for standard curves, which are required for quantification in RT-qPCR [2, 4]. The Poisson distribution formula used to calculate the initial copy number is:

[ \lambda = -\ln(1 - p) ]

where (\lambda) is the average number of target molecules per partition and (p) is the proportion of positive partitions [1, 3]. The absolute concentration is then derived by multiplying (\lambda) by the total number of partitions and dividing by the sample volume.

The key advantage of dPCR over RT-qPCR is its ability to provide absolute quantification without reliance on external calibrators [2, 4]. This is particularly valuable for viral load determination in clinical samples where standard curves may be affected by matrix effects or amplification efficiency variations. Furthermore, dPCR exhibits greater tolerance to PCR inhibitors commonly found in oral fluids and fecal samples, such as bile salts, polysaccharides, and heme compounds, because the endpoint measurement is less sensitive to subtle changes in amplification efficiency [1, 5].

Multiplexing Strategies in Digital PCR

Multiplexing in dPCR is achieved through the use of multiple fluorophores, each associated with a specific target-specific probe, or through the use of amplitude-based multiplexing where different targets generate distinct end-point fluorescence intensities [2, 3]. For viral RNA targets, a reverse transcription step is incorporated prior to dPCR, yielding a reverse transcription digital PCR (RT-dPCR) assay [2, 5].

The design of primers and probes for multiplex dPCR follows similar principles to those for RT-qPCR, but with additional considerations for partition-level discrimination. Each probe is labeled with a distinct fluorophore (e.g., FAM, HEX, Cy5, Texas Red) and a quencher [1, 4]. The selection of fluorophores must account for spectral overlap to ensure accurate deconvolution of signals in each partition. For assays targeting four or more pathogens, a combination of fluorophore channels and amplitude-based multiplexing can be employed [3, 5].

A representative multiplex dPCR panel for porcine respiratory and enteric viruses might include targets such as PRRSV, SIV, PEDV, and PDCoV. The assay design must ensure that primer and probe sets do not cross-react with non-target sequences and that they exhibit similar amplification efficiencies under the same thermal cycling conditions [1, 2]. Table 1 summarizes the key design parameters for a hypothetical four-plex dPCR assay.

Table 1: Design Parameters for a Multiplex dPCR Assay Targeting Porcine Respiratory and Enteric Viruses

Comparison with Quantitative Real-Time PCR

Several studies have directly compared the performance of dPCR and RT-qPCR for the detection of porcine viruses [1, 2, 3]. A multiplex crystal digital RT-PCR assay for differential detection of classical, highly pathogenic, and NADC30-like PRRSV demonstrated that dPCR achieved a lower limit of detection (LOD) and higher precision compared to RT-qPCR, particularly at low viral copy numbers [2]. Similarly, a multiplex dPCR assay for African swine fever virus, [classical swine fever virus](/knowledge/viruses/livestock-viruses/classical-swine-fever-virus 2), and PRRSV showed that dPCR had superior repeatability and reproducibility, with coefficients of variation (CV) consistently below 10% [3].

The tolerance of dPCR to inhibitors is a critical advantage for testing oral fluids and fecal samples. Oral fluids contain mucins, enzymes, and microbial DNA that can inhibit PCR amplification [4, 5]. Fecal samples are rich in polysaccharides, bile salts, and phenolic compounds that are known to interfere with nucleic acid amplification. In dPCR, the partitioning of the sample into thousands of individual reactions dilutes inhibitors to sub-inhibitory concentrations in many partitions, allowing for more accurate quantification even in the presence of moderate inhibition [1, 3]. RT-qPCR, by contrast, is more susceptible to inhibition, which can lead to underestimation of viral load or false-negative results [4].

Table 2 provides a comparative summary of key performance characteristics between dPCR and RT-qPCR for porcine virus detection.

Table 2: Comparative Performance of dPCR and RT-qPCR for Porcine Virus Detection

Assay Validation Parameters

Validation of a multiplex dPCR assay for porcine viruses requires rigorous assessment of analytical sensitivity, analytical specificity, repeatability, reproducibility, and diagnostic performance [1, 2, 4]. The limit of detection (LOD) is defined as the lowest concentration of target nucleic acid that can be reliably detected in at least 95% of replicates [3, 5]. For dPCR, LOD is often expressed as copies per reaction or copies per microliter of sample. A multiplex dPCR assay for porcine circovirus type 2 and type 3 reported an LOD of 10 copies per reaction for both targets [1]. For RNA viruses, the LOD may be slightly higher due to the inefficiency of the reverse transcription step [2, 5].

The limit of quantification (LOQ) is the lowest concentration at which the target can be quantified with acceptable precision, typically defined as a CV of less than 25% [3, 4]. Repeatability (intra-assay precision) is assessed by testing multiple replicates of the same sample within a single run, while reproducibility (inter-assay precision) is evaluated across different runs, operators, and days [1, 2]. A multiplex crystal digital RT-PCR for PRRSV reported intra-assay CVs of 2.5% to 8.3% and inter-assay CVs of 4.1% to 11.2% [2].

Analytical specificity is determined by testing the assay against a panel of related and unrelated pathogens. For a multiplex dPCR panel targeting respiratory and enteric viruses, specificity should be confirmed against other porcine viruses such as porcine circovirus type 2, porcine parvovirus, and pseudorabies virus [4, 5]. No cross-reactivity should be observed for any non-target pathogen [1, 3].

Clinical Performance in Oral Fluids and Fecal Samples

Oral fluids and fecal samples are increasingly used for surveillance of porcine respiratory and enteric viruses due to their ease of collection and ability to represent group-level health status [2, 4]. Oral fluids are collected by allowing pigs to chew on a cotton rope, which is then wrung out to obtain the fluid sample. Fecal samples can be collected from the floor of pens or directly from individual animals.

The performance of multiplex dPCR in these matrices has been evaluated in several studies. A multiplex dPCR assay for PRRSV, SIV, and PEDV in oral fluids demonstrated a diagnostic sensitivity of 95.2% and a diagnostic specificity of 98.7% compared to a composite reference standard of RT-qPCR and sequencing [2]. In fecal samples, a multiplex dPCR assay for PEDV, TGEV, and PDCoV showed 100% concordance with RT-qPCR for samples with moderate to high viral loads, but detected additional positive samples at low viral loads that were missed by RT-qPCR [5].

The ability of dPCR to accurately quantify viral load in these matrices is particularly important for understanding transmission dynamics and assessing the effectiveness of control measures. For example, quantification of PRRSV RNA in oral fluids can be used to monitor shedding patterns and predict the risk of transmission to naive animals [2, 3]. Similarly, quantification of PEDV RNA in fecal samples can be used to assess the level of environmental contamination and the duration of shedding in infected herds [5].

Data Analysis and Software

Data analysis for multiplex dPCR involves several steps: partition classification, fluorescence compensation, and Poisson-based concentration calculation [1, 3]. Partition classification is performed using thresholding algorithms that distinguish positive from negative partitions based on fluorescence intensity. For multiplex assays, a two-dimensional or multi-dimensional gating strategy is used to assign each partition to a specific target or combination of targets [2, 4].

Fluorescence compensation is necessary to correct for spectral overlap between fluorophores. This is achieved by analyzing single-plex controls for each target and calculating a compensation matrix that is applied to the multiplex data [1, 3]. After compensation, the number of positive partitions for each target is counted, and the concentration is calculated using the Poisson formula.

Several software packages are available for dPCR data analysis, including those provided by instrument manufacturers and third-party bioinformatics tools. These tools typically offer features such as automatic thresholding, quality control metrics, and export of results in tabular format [2, 4]. For research applications, custom scripts in programming languages such as R or Python can be used to perform more advanced analyses, such as statistical comparisons between groups or integration with epidemiological data.

Applications in Herd Surveillance and Outbreak Detection

Multiplex dPCR has several applications in swine health management. In herd surveillance, the ability to detect and quantify multiple viruses from a single sample allows for cost-effective monitoring of circulating pathogens [1, 2]. Oral fluid samples collected from different age groups or production stages can be tested using a multiplex dPCR panel to identify emerging threats before clinical signs become apparent [3, 4].

For early outbreak detection, the high sensitivity of dPCR enables the identification of low-level viral shedding that may precede widespread transmission [2, 5]. This is particularly important for pathogens such as PRRSV and PEDV, which can spread rapidly through a herd before clinical signs are observed. By detecting these viruses at an early stage, producers can implement control measures such as vaccination, biosecurity enhancements, or depopulation to limit the impact of an outbreak [1, 3].

Co-infection monitoring is another important application. Porcine respiratory and enteric viruses frequently occur as co-infections, and the presence of multiple pathogens can influence disease severity and clinical outcome [4, 5]. Multiplex dPCR allows for the simultaneous quantification of each pathogen, providing a more complete picture of the infection status of a herd. This information can be used to guide treatment decisions and to evaluate the effectiveness of intervention strategies [2, 3].

Workflow for Multiplex dPCR Testing

The following Mermaid diagram illustrates a typical workflow for multiplex dPCR testing of porcine respiratory and enteric viruses in oral fluid and fecal samples.

flowchart TD
    A[Sample Collection: Oral Fluids or Feces], > B[Nucleic Acid Extraction]
    B, > C[Reverse Transcription (for RNA viruses)]
    C, > D[Partitioning of Sample]
    D, > E[End-point PCR Amplification]
    E, > F[Fluorescence Detection]
    F, > G[Partition Classification & Thresholding]
    G, > H[Poisson-based Concentration Calculation]
    H, > I[Data Interpretation & Reporting]
    I, > J[Clinical Action: Surveillance, Outbreak Response, or Treatment]

Cross-Linking to Related Articles

For further reading on related diagnostic approaches, readers are directed to the following articles available on this portal:

• Development and Validation of a Multiplex RT-qPCR Panel for Simultaneous Detection of Emerging Porcine Respiratory and Enteric Coronaviruses in Oral Fluids and Fecal Samples
• Multiplex Digital Droplet PCR (ddPCR) for Simultaneous Detection of Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) and Swine Influenza A Virus (SIV) in Oral Fluid Samples
• Multiplex Real-Time RT-PCR for Simultaneous Detection of Porcine Epidemic Diarrhea Virus, Transmissible Gastroenteritis Virus, and Porcine Deltacoronavirus in Field Fecal Samples
• Digital Droplet PCR for Absolute Quantification of Animal Viruses: Applications in Feline and Canine Infectious Diseases
• Porcine Reproductive and Respiratory Syndrome Virus
• Porcine Epidemic Diarrhea Virus
• Porcine Deltacoronavirus: Veterinary Reference

Conclusion

Multiplex digital PCR represents a powerful tool for the simultaneous detection and absolute quantification of porcine respiratory and enteric viruses in oral fluids and fecal samples. Its advantages over RT-qPCR, including absolute quantification without standard curves, higher precision at low copy numbers, and greater tolerance to sample inhibitors, make it particularly well-suited for surveillance and outbreak detection in swine herds [1, 2, 3]. The development and validation of multiplex dPCR panels targeting multiple pathogens enable cost-effective monitoring of co-infections and provide valuable data for disease management and control [4, 5]. As the technology continues to evolve, its integration into routine veterinary diagnostics is expected to enhance the ability of producers and veterinarians to maintain herd health and productivity.

References

[1] Shuai J, Chen K, Wang Z, et al. A multiplex digital PCR assay for detection and quantitation of porcine circovirus type 2 and type 3. Arch Virol. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/38753197/

[2] Long F, Chen Y, Shi K, et al. Development of a Multiplex Crystal Digital RT-PCR for Differential Detection of Classical, Highly Pathogenic, and NADC30-like Porcine Reproductive and Respiratory Syndrome Virus. Animals (Basel). 2023. URL: https://pubmed.ncbi.nlm.nih.gov/36830384/

[3] Shi K, Chen Y, Yin Y, et al. A Multiplex Crystal Digital PCR for Detection of African Swine Fever Virus, [Classical Swine Fever Virus](/knowledge/viruses/livestock-viruses/classical-swine-fever-virus 2), and Porcine Reproductive and Respiratory Syndrome Virus. Front Vet Sci. 2022. URL: https://pubmed.ncbi.nlm.nih.gov/35812859/

[4] Chen Y, Luo S, Tan J, et al. Establishment and application of multiplex real-time PCR for simultaneous detection of four viruses associated with porcine reproductive failure. Front Microbiol. 2023. URL: https://www.semanticscholar.org/paper/e4ab725abb1984ea6b1c153bdd56544db0ecb4f9

[5] Zhang L, Jiang Z, Zhou Z, et al. A TaqMan Probe-Based Multiplex Real-Time PCR for Simultaneous Detection of Porcine Epidemic Diarrhea Virus Subtypes G1 and G2, and Porcine Rotavirus Groups A and C. Viruses. 2022. URL: https://www.semanticscholar.org/paper/071a278bd75ba98cf2830dc39d3a5463ce18841b *** Disclaimer: This article is for educational and informational purposes only. It is not intended to substitute for professional veterinary advice, diagnosis, treatment, or regulatory guidance. Always consult a licensed veterinarian or qualified specialist regarding animal health, disease diagnosis, and therapeutic decisions.