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. 2019 Oct;127(4):1246-1254.
doi: 10.1111/jam.14363. Epub 2019 Jul 12.

Evidence for swine and human papillomavirus in pig slurry in Italy

Affiliations

Evidence for swine and human papillomavirus in pig slurry in Italy

P Di Bonito et al. J Appl Microbiol. 2019 Oct.

Abstract

Aims: The diversity and the geographical distribution of swine papillomaviruses (PVs) are virtually unknown. The occurrence and the diversity of swine PV were therefore investigated in pig slurry collected in Italy, to contribute towards filling this gap in knowledge.

Methods and results: Twenty-two slurry samples underwent analysis by nested PCR and DNA sequencing using published and newly designed specific primer pairs for Sus scrofa papillomavirus (SsPV) type 1 and 2 (SsPV1 and 2), along with degenerate PV-specific primers targeting the major coat protein L1 and the helicase protein E1. Overall, three samples (13·6%) were positive for SsPV1 by specific primers, and nucleotide (nt) sequences showed 99-100% nt identity with SsPV1 variant a (EF395818), while SsPV2 was not found in any sample. Using generic primers, eight samples (36·4%) were tested positive for human papillomavirus (HPV), and were characterized as follows: β1-HPV8, β1-HPV14, β1-HPV206, β2-HPV113, β2-HPV120 and γ1-HPV173. Moreover, one unclassified γ-type was detected.

Conclusions: Both swine and human PVs were detected in pig slurry in this study. The unexpected presence of HPV in pig waste could be explained as the result of an improper use of the sewage collection pits and/or with improper procedures of the operators.

Significance and impact of the study: This study reports the first detection of SsPV1 in Italy, along with the first detection of HPVs in pig slurry samples in Italy, and expands our knowledge about PV diversity and geographic distribution.

Keywords: diversity; environmental; identification; viruses; waste.

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Conflict of interest statement

The authors declare that there are no conflict of interest.

Figures

Figure 1
Figure 1
Phylogenetic tree constructed with the sequences obtained in the L1 region. The tree was constructed using the maximum likelihood method based on the general time reversible (GTR) model. The sequences identified in this study are in bold.

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