Mining Porcine Blood Whole-DNA Sequencing Datasets to Uncover Pig Viromes: An Exploratory Application to Identify Potential Infecting Agents of an Undefined Disease Outbreak

TL;DR

Researchers used whole-genome sequencing of pig blood to identify multiple viruses in diseased pigs, suggesting a new method for unbiased viral detection in veterinary diagnostics.

Contribution

This is the first application of whole-genome sequencing of unmapped reads for unbiased viral detection in livestock diagnostic settings.

Findings

Viral sequences from 12 different viruses were identified in blood samples from nine diseased pigs.

Porcine cytomegalovirus was the most frequently detected virus across the samples.

The method revealed a heterogeneous viral profile, potentially indicating co-infections or secondary infections.

Abstract

Pigs can be infected or co-infected with numerous pathogenic and non-pathogenic viruses, making it challenging to interpret clinical symptoms. Diagnostic assays should provide unbiased results to help identify the infecting viruses. In this study, we tested a new and potentially unbiased method to identify viral sequences in porcine blood. The approach involves whole-genome sequencing of all extracted DNA from blood, isolating short DNA sequences not part of the pig genome (unmapped reads) and identifying viral sequences within this fraction. This method was used to investigate a suspected outbreak of Post-weaning Multisystemic Wasting Syndrome on a pig farm. By utilising advanced DNA sequencing technology and bioinformatic analysis of DNA sequencing data, we identified sequences from 12 different viruses within the sequencing data of nine diseased pigs from the farm. The results suggest a heterogeneous profile among the analysed pigs, potentially indicating potential secondary infections or co-infections. Considering the results of this pilot application, mining unmapped reads from whole-genome sequencing data can provide useful information to better understand complex viral disease states, which can help improve veterinary surveillance.

Pigs are affected by a variety of pathogenic agents that need to be identified correctly and diagnosed even when co-infections may complicate the application of specific and targeted assays. Next-generation sequencing can provide new perspective to monitor viruses infecting or co-infecting diseased pigs. In this study, we tested, for the first time for diagnostic purposes in a livestock species, a new method based on whole-genome sequencing of all the DNAs extracted from the blood of nine pigs sampled from a farm where there was a suspected outbreak of Post-weaning Multisystemic Wasting Syndrome. We then used unmapped reads on the porcine reference genome to mine for viral sequences using a specifically designed bioinformatic pipeline. Within this fraction of reads, viral sequences ranged from 0.002% to 4.4% of the total unmapped reads and were derived from twelve different viruses known to infect pigs, where three were herpesviruses, eight were parvoviruses, and one was a circovirus. All pig sequencing datasets were positive for one or more viruses, with various potential viral loads. Suid betaherpesvirus 2, also known as Porcine cytomegalovirus (PCMV), was the most frequently identified virus as five out of the nine pig sequencing datasets contained viral sequences from this virus. The results may suggest a heterogeneous viral profile of the diseased pigs that may be derived from potential secondary infections or co-infections. This pilot application demonstrated that a whole-genome sequencing approach can complement other routine diagnostic assays in veterinary virology. Other studies and improvements are needed to validate the results and apply this approach in routine monitoring applications.

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