Abstract:

The purpose of this research is to determine the pathogen of piglet diarrhea in pig farms in Hezhou area of Guangxi in the spring of 2023 by using the Meta-transcriptomics sequencing technology to screen the incidence and infection of pigs in this area, so as to provide theoretical basis for the prevention and control of piglet diarrhea diseases in local pig farms. In March 2023, swabs and feces of six adjacent pig farms with simultaneous outbreak of diarrhea within a range of 10 kilometers were collected in Hezhou, Guangxi, and Meta-transcriptomics sequencing was performed by MGISEQ 200 sequencing platform for porcine pathogenic infectomes research. The pathogenic spectrum of piglet diarrhea in this area was systematically screened and the abundance of each pathogen was quantitatively analyzed. The most important viruses were confirmed by Real-time RT-PCR, after which the identified viral gene sequences were selected for phylogenetic analysis.Pearson analysis was used to analyze the correlation of pathogenic co-infection. The results showed that a total of 17 pathogenic bacteria, 12 viruses, and 3 parasites were detected in these samples by Meta-transcriptomics sequencing. The predominant viruses were diarrhea-associated viruses represented by the porcine epidemic diarrhea virus (PEDV), including porcine sapovirus (SaV), porcine kobuvirus (PKV), porcine astrovirus (PAstV), porcine sapelovirus (PSV), and rotavirus A (RVA). The bacteria mainly consisted of three kinds of Enterobacteriaceae, three kinds of Lactobacillaceae, and two kinds of Bacillaceae. The parasites included two kinds of Trichomonads and Iodamoeba. The phylogenetic analysis of spike gene (S gene) of PEDV from five farms showed that the strains all belonged to the G2c cluster group, that the nucleotide similarity between the strains was 99.99%, and that S gene was recombined. Additionally, partial VP4 gene of rotavirus A, of the P[6] genotype, was detected in one of the farms, which had the highest nucleotide similarity with human rotavirus. In addition, more than 2 piglet diarrhea-related viral infections were detected in 4 pig farms. Phylogenetic analysis showed that there was a multi-lineage co-epidemic of diarrheal pathogens in this region, and even different lineages of the same virus were circulating in the same farm. Pathogen correlation analysis showed that there was a significant negative correlation between PEDV/PSV (P < 0.001), PEDV/porcine torovirus (PToV) (P < 0.001) and PEDV/PAstV (P < 0.05), while PEDV/PKV had a significant positive correlation (P < 0.05). The above findings indicate a diverse pathogenic spectrum of piglet diarrhea in adjacent breeding regions of this area, with PEDV identified as the primary pathogen. Furthermore, a correlation between PEDV and other diarrhea-related viruses was observed in the samples. This study offers a comprehensive overview of the infection spectrum of diarrhea pathogens in piglets in this region, pinpointing the most direct causes of diarrhea. Additionally, it enables the analysis of the relationship between diarrhea-associated pathogens in small-scale breeding areas, providing precise guidance and reference for the prevention and control of piglet diarrhea in this region.

Key words: meta-transcriptomics, piglet diarrhea disease, pathogen identification, PEDV, genetic evolution analysis, correlation analysis