A deadly virus strikes, but it doesn't always work alone.
Advanced genetic detective work reveals a hidden world of diverse viral co-infections in diarrheic pigs
When a devastating wave of porcine epidemic diarrhea virus (PEDV) swept across the United States in 2013, it caused the deaths of millions of piglets, delivering a severe blow to the swine industry. While scientists rushed to understand this known enemy, a deeper, more complex mystery was unfolding within the infected pigs. The surprising discovery was that PEDV, the obvious culprit, was often not acting alone.
Advanced genetic detective work has since revealed a hidden world of diverse viral co-infections in diarrheic pigs, suggesting that the story of this epidemic is far more complicated than it first appeared 1 .
PEDV was frequently accompanied by other viruses, with 73% of infected pigs showing evidence of multiple viral infections 1 .
Porcine epidemic diarrhea virus (PEDV) is a highly contagious coronavirus that attacks the intestinal system of pigs. It's a single-stranded RNA virus that primarily destroys the lining of the small intestine, leading to severe, watery diarrhea, vomiting, and devastating dehydration. In suckling piglets, the disease is particularly brutal, with mortality rates often reaching 100%.
For a long time, diagnostics focused on finding this single pathogen. However, the similar clinical signs caused by a range of other swine enteric viruses made it difficult to pinpoint the complete picture of infection in the field. The limitations of traditional, single-target tests meant that the full scope of the viral threat remained shrouded in mystery.
The key to unraveling this mystery came from a powerful new technology: metagenomic next-generation sequencing.
Like fishing for one specific type of fish in a vast ocean
Like casting a massive net that catches every living thing
Think of it this way: if traditional diagnostic tests are like fishing for one specific type of fish in a vast ocean, metagenomics is like casting a massive net that catches every living thing in its path. This "hypothesis-free" approach allows scientists to sequence all the genetic material—both DNA and RNA—in a sample without needing to know what they're looking for in advance. By comparing the sequences to massive databases, they can then identify every virus present, from well-known pathogens to entirely novel agents.
This method has revolutionized virology, enabling researchers to characterize the entire "virome"—the collective viral community—in a host or environment.
A pivotal 2018 study published in Virology Journal undertook the first large-scale effort to characterize the RNA virome in PEDV-infected pigs in the United States 1 .
The team analyzed 217 fecal swab samples from diarrheic piglets that had tested positive for PEDV. These samples were collected from swine operations across 17 U.S. states between 2015 and 2016 1 .
Researchers extracted all the nucleic acids from the fecal samples and then used enzymes to selectively remove DNA, isolating only the RNA fraction—the target for identifying RNA viruses like PEDV 1 .
The RNA was converted into DNA copies, prepared for sequencing, and then run on an Illumina MiSeq platform, a high-throughput sequencer that generated millions of genetic reads from each sample 1 .
The raw sequencing data was processed through a powerful bioinformatics pipeline. Using algorithms like Kraken, the sequences were classified by comparing them to extensive genetic databases, identifying which viruses were present and in what relative amounts 1 .
The results were striking. The study revealed that the gut of a PEDV-positive pig was a crowded ecosystem of viruses.
The analysis identified up to nine different RNA viral genera besides PEDV itself. The table below shows the prevalence of these co-infecting viruses 1 .
| Virus Genus | Common Name | Prevalence in Samples |
|---|---|---|
| Mamastrovirus | Porcine astrovirus | 52% (113/217) |
| Enterovirus | Porcine enterovirus | 39% (85/217) |
| Sapelovirus | Porcine sapelovirus | 31% (67/217) |
| Posavirus | Porcine stool-associated RNA virus | 30% (66/217) |
| Kobuvirus | Aichivirus C (porcine kobuvirus) | 23% (49/217) |
| Sapovirus | Porcine sapovirus | 13% (28/217) |
| Teschovirus | Porcine teschovirus | 10% (22/217) |
| Pasivirus | Porcine pasivirus | 9% (20/217) |
| Deltacoronavirus | Porcine deltacoronavirus (PDCoV) | 3% (6/217) |
Only 27% (58 out of 217) of the piglets had a solo PEDV infection. The remaining 73% were shedding between two and eight other RNA viruses alongside PEDV 1 .
| Number of Virus Types Detected | Description | Percentage of Samples |
|---|---|---|
| 1 | PEDV infection alone | 27% |
| 2-9 | PEDV plus other RNA viruses | 73% |
These co-infecting viruses belong to four main families: Astroviridae, Picornaviridae, Caliciviridae, and Coronaviridae 1 . While the role of some of these viruses in causing disease is still being studied, their presence complicates the diagnostic and clinical picture.
Uncovering this hidden viral world requires a sophisticated set of laboratory tools. The following table details some of the essential reagents and their functions as used in the featured experiment 1 .
| Research Reagent | Function in the Experiment |
|---|---|
| MagMAX™ Viral RNA Isolation Kit | Extracts and purifies total viral nucleic acids (RNA and DNA) from complex fecal samples. |
| RNase-free DNase I | Enzymatically degrades DNA post-extraction, ensuring only RNA is sequenced for RNA virome analysis. |
| Agencourt RNAClean XP Beads | Purifies and size-selects RNA, removing enzymes, salts, and other contaminants after DNA digestion. |
| NEXTflex™ Rapid RNA-Seq Kit | Converts the purified RNA into double-stranded DNA (cDNA) suitable for sequencing. |
| Nextera XT Library Prep Kit | Prepares the "library" by fragmenting cDNA and adding adapter sequences required for the sequencer. |
| Illumina MiSeq Platform | The next-generation sequencer that generates millions of short DNA sequences (reads) from the sample library. |
| Kraken Algorithm | A bioinformatics tool that rapidly and accurately classifies the raw sequencing reads by comparing them to a reference database. |
The discovery of extensive viral co-infections in pig herds has profound implications.
For the swine industry, it highlights that porcine diarrhea is often a multi-faceted disease. A diagnostic approach that only looks for PEDV might miss other contributing agents, leading to incomplete treatments or ineffective prevention strategies. Understanding the full spectrum of viruses is crucial for developing better vaccines and management practices.
Furthermore, pigs are known as "mixing vessels" for viruses. The close quarters of a co-infected intestine provide the perfect environment for viral recombination and reassortment—a process where different viruses swap genetic material. This can lead to the emergence of novel viral strains with unpredictable traits, including the potential for zoonotic transmission to humans 2 5 .
The application of metagenomics has peeled back the curtain on the complex viral drama unfolding in pig herds. What was once seen as a single-villain story is now understood to be a narrative with a large, diverse cast of characters, all potentially influencing the course of disease.
This powerful technology is shifting the paradigm of diagnostics from a targeted search to a broad surveillance tool, allowing us to see the entire battlefield, not just one enemy. As this approach becomes more widespread, it promises to transform our ability to monitor, understand, and ultimately control infectious disease outbreaks in animals and humans alike.