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. 2022 Jul;69(4):2306-2319.
doi: 10.1111/tbed.14249. Epub 2021 Aug 28.

Application of shotgun metagenomics sequencing and targeted sequence capture to detect circulating porcine viruses in the Dutch-German border region

Leonard Schuele  1   2 , Erley Lizarazo-Forero  1 , Katrin Strutzberg-Minder  3 , Sabine Schütze  4 , Sandra Löbert  4 , Claudia Lambrecht  4 , Jürgen Harlizius  4 , Alex W Friedrich  1 , Silke Peter  2 , John W A Rossen  1   5 , Natacha Couto  1   6
Affiliations

Application of shotgun metagenomics sequencing and targeted sequence capture to detect circulating porcine viruses in the Dutch-German border region

Leonard Schuele et al. Transbound Emerg Dis. 2022 Jul.

Abstract

Porcine viruses have been emerging in recent decades, threatening animal and human health, as well as economic stability for pig farmers worldwide. Next-generation sequencing (NGS) can detect and characterize known and unknown viruses but has limited sensitivity when an unbiased approach, such as shotgun metagenomics sequencing, is used. To increase the sensitivity of NGS for the detection of viruses, we applied and evaluated a broad viral targeted sequence capture (TSC) panel and compared it to an unbiased shotgun metagenomic approach. A cohort of 36 pooled porcine nasal swab and blood serum samples collected from both sides of the Dutch-German border region were evaluated. Overall, we detected 46 different viral species using TSC, compared to 40 viral species with a shotgun metagenomics approach. Furthermore, we performed phylogenetic analysis on recovered influenza A virus (FLUAV) genomes from Germany and revealed a close similarity to a zoonotic influenza strain previously detected in the Netherlands. Although TSC introduced coverage bias within the detected viruses, it improved sensitivity, genome sequence depth and contig length. In-depth characterization of the swine virome, coupled with developing new enrichment techniques, can play a crucial role in the surveillance of circulating porcine viruses and emerging zoonotic pathogens.

Keywords: influenza A virus; one health; porcine virome; shotgun metagenomics sequencing; surveillance; targeted sequence capture.

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Conflict of interest statement

John W. A. Rossen is employed by IDbyDNA. Silke Peter consults for IDbyDNA. This did not influence the interpretation of reviewed data and conclusions drawn nor the drafting of the manuscript, and no support was obtained from them. All other authors declare no conflict of interest.

Figures

FIGURE 1
FIGURE 1
Flow chart of the study design. Samples were first pre‐selected based on positive qPCR results for FLUAV and/or PRRSV. Subsequent NGS analysis using both a metagenomics and a targeted sequence capture approach was performed. For viral targeted sequence capture using ViroCap, two different hybridization times were evaluated. The relative location of the selected farms for NGS analysis is indicated as red dots on the map.
FIGURE 2
FIGURE 2
Impact of ViroCap hybridization times (20 and 72 h) on viral sensitivity compared to SISPA (n = 12 samples). The diagram highlights the most frequently detected viruses. Sequencing reads were analyzed with Taxonomer (full analysis) and normalized. Abbreviations: PERV, porcine endogenous retrovirus; PRRSV, porcine reproductive and respiratory syndrome virus; PPV, porcine parvovirus.
FIGURE 3
FIGURE 3
Viral reads (normalized) and fold changes between SISPA and ViroCap (n = 36 samples). Frequently detected viral genera in this study are shown. Numbers higher than 1 indicate increased sensitivity using ViroCap. Data analyzed with Taxonomer (full analysis).
FIGURE 4
FIGURE 4
Comparison of MEGAHIT, SPAdes and CLC assemblies (using SISPA and ViroCap). Assembly metrics: (a) Total length (sum of all contigs in bp); (b) Total viral length (sum of all viral contigs in bp); (c) Total number of contigs; (d) N50 (bp); (e) Total number of detected viruses; (f) Total number of detected viral species.
FIGURE 5
FIGURE 5
(a) Average PRRSV read count, average contig consensus length and average longest contig. The PRRSV genome size is approximately 15 kb. (b) An example of a genome‐wide comparison of sequence coverage and G/C content of a PRRSV genome using SISPA and ViroCap. The proportion of G/C content (scale 0%–100%) is shown in pink; the sequencing depth coverage is shown in blue for SISPA and red for ViroCap
FIGURE 6
FIGURE 6
Phylogenetic reconstruction of PRRSV and FLUAV. (a) Map indicating the geographical origin of the samples in this study. Please note, for privacy reasons, the numbers do not correlate with the farm ID in Table 1. (b) Regression of sequence sampling dates against root‐to‐tip genetic distances from the maximum likelihood tree. (c) Phylogenetic analysis of the whole genome of PRRSV. PRRSV 2 prototype strain VR2332 (AY150564) was used as an outgroup. Blue coloured taxa depict the samples from this study. (d) Phylogenetic analysis of the HA sequence from FLUAV. The analysis involved influenza A viruses from swine‐origin from 2010 to 2020 (blue dots) and influenza A viruses isolated from humans from 2015 to 2020 (red dots). A total of 61 representative sequences were used to generate the phylogenetic reconstruction. Samples in this study are highlighted in yellow. The evolutionary history was inferred using the maximum likelihood method implemented in RA×ML with bootstrapping of 1000 replicates
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