Abstract
The enteric disorders represent a serious hazard for bovine and camelid breeding. The aim of this study was to examine the frequency of detection and molecular characteristics of enteric coronavirus (CoV) infections in cattle, alpaca, and llama herds bred in family-based farms in Brazil and Peru. Stool samples were collected from calves from Brazil and camelids from Peru for detection and characterization of CoV by reverse transcription polymerase chain reaction (RT-PCR) and sequence analysis. 46.5% (47/101) samples from calves and 26.8% (70/261) from alpaca tested positive for CoV. All strains belong to lineage A1 of the Betacoronavirus genus. Phylogenetic analysis showed high identity between CoV strains detected in calves and alpacas. This study characterised CoV strains from dairy cattle herds in the state of Rio de Janeiro, Brazil, and indicated that this virus is spread among the state herds. The results also indicate widespread circulation of CoV among the alpacas of Cuzco, Peru.
Highlights
The enteric disorders represent a serious hazard for bovine and camelid breeding
Bovine coronaviruses (BCoVs) was detected in the stool of 47 (46.5%) of the 101 calves tested from all studied farms, with a frequency ranging from 24% to 81.8%, (Table 1)
Phylogenetic analysis (Figure 1) showed that all strains belong to lineage A1 of the Betacoronavirus genus [14]
Summary
The aim of this study was to examine the frequency of detection and molecular characteristics of enteric coronavirus (CoV) infections in cattle, alpaca, and llama herds bred in familybased farms in Brazil and Peru. Methodology: Stool samples were collected from calves from Brazil and camelids from Peru for detection and characterization of CoV by reverse transcription polymerase chain reaction (RT-PCR) and sequence analysis. Phylogenetic analysis showed high identity between CoV strains detected in calves and alpacas. Coronaviruses (CoVs) are responsible for enteric and respiratory infections in bovine and camelid flocks throughout the world and are associated with significant economic losses [1,5,6,7,8]
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