Molecular epidemiology and phyloevolutionary analysis of porcine parvoviruses (PPV1 through PPV7) detected in replacement gilts from Colombia

Abstract

Eight porcine parvovirus (PPV) species, designated as PPV1 through PPV8, have been identified in swine. Despite their similarities, knowledge about their distribution and genetic differences remains limited, resulting in a gap in the genetic classification of these viruses. In this study, we conducted a comprehensive analysis using PPV1 to PPV7 genome sequences from Colombia and others available in the GenBank database to propose a classification scheme for all PPVs. Sera from 234 gilts aged 180 to 200 days were collected from 40 herds in Colombia. Individual detection of each PPV (PPV1 through PPV7) was performed using end-point PCR. Complete nucleotide (nt) sequencing was performed on the PPV1 viral protein (VP), and near-complete genome (NCG) sequencing was carried out for novel porcine parvoviruses (nPPVs) (PPV2 through PPV7). Phylogenetic analyses were conducted by comparing PPV1-VP sequences to 94 available sequences and nPPVs with 565 NCG, 846 nPPV-VP, and 667 nPPV–nonstructural protein (NS) sequences. Bayesian phylogenetic analysis was used to estimate substitution rates and the time to the most recent common ancestor for each PPV. The highest prevalence was detected for PPV3 (40.1%), followed by PPV5 (20.5%), PPV6 (17%), PPV1 (14.5%), PPV2 (9.8%), PPV4 (4.2%), and PPV7 (1.3%). Notably, all tested sera were negative for PPV8 genomes. An analysis of the PPV1-VP sequences revealed two main clades (PPV1-I and PPV1-II), with the sequences recovered in this study grouped in the PPV1-II clade. Comparative analysis showed significant genetic distances for PPV2 to PPV7 at the NCG (>6.5%), NS (>6.3%), and VP (>7.5%) regions, particularly when compared to equivalent regions of PPV genomes recovered worldwide. This study highlights the endemic circulation of nPPVs in Colombian pig herds, specifically among gilts. Additionally, it contributes to the phylogenetic classification and evolutionary studies of these viruses. The proposed method aims to categorize and divide subtypes based on current knowledge and the genomes available in databanks.