Bovine coronavirus (BCoV) is zoonotically transmissible among species, since BCoV-like viruses have been detected in wild ruminants and humans. BCoV causing enteric and respiratory disease is widespread in cattle farms worldwide; however, limited information is available regarding the molecular characterization of BCoV because of its large genome size, despite its significant economic impact. This study aimed to better understand the genomic characterization and evolutionary dynamics of BCoV via comparative sequence and phylogenetic analyses through whole genome sequence analysis using 67 BCoV isolates collected throughout Japan from 2006 to 2017. On comparing the genomic sequences of the 67 BCoVs, genetic variations were detected in 5 of 10 open reading frames (ORFs) in the BCoV genome. Phylogenetic analysis using whole genomes from the 67 Japanese BCoV isolates in addition to those from 16 reference BCoV strains, revealed the existence of two major genotypes (classical and US wild ruminant genotypes). All Japanese BCoV isolates originated from the US wild ruminant genotype, and they tended to form the same clusters based on the year and farm of collection, not the disease type. Phylogenetic trees on hemagglutinin-esterase protein (HE), spike glycoprotein (S), nucleocapsid protein (N) genes and ORF1 revealed clusters similar to that on whole genome, suggesting that the evolution of BCoVs may be closely associated with variations in these genes. Furthermore, phylogenetic analysis of BCoV S genes including those of European and Asian BCoVs and human enteric coronavirus along with the Japanese BCoVs revealed that BCoVs differentiated into two major types (European and American types). Moreover, the European and American types were divided into eleven and three genotypes, respectively. Our analysis also demonstrated that BCoVs with different genotypes periodically emerged and predominantly circulated within the country. These findings provide useful information to elucidate the detailed molecular characterization of BCoVs, which have spread worldwide. Further genomic analyses of BCoV are essential to deepen the understanding of the evolution of this virus.

Bovine respiratory diseases (BRD) are associated with various predisposing factors, such as physical and physiological stress factors, and bacterial and viral pathogens. These stressors and viruses suppress immune defenses, leading to bacterial growth in the upper respiratory tract and invasion of pathogens into the lower respiratory tract. Therefore, continuous monitoring of the causative pathogens would contribute to the early detection of BRD. Nasal swabs and sera from 63 clinically healthy calves were continuously collected from seven farms in Iwate prefecture from 2019 to 2021. We attempted to monitor dynamics of BRD-associated pathogens by multiplex real-time RT-PCR (RT-qPCR) using their nasal swab samples. In addition, we attempted to monitor fluctuation of antibody titers against each BRD-associated pathogen by virus neutralization test (VNT) using their sera. In contrast, nasal swabs from 89 calves infected with BRD were collected from 28 farms in Iwate prefecture from 2019 to 2021. We attempted to analyze their nasal swab samples by multiplex RT-qPCR aim to detect BRD-associated pathogens that are dominant in this region. As a result, our analyses using samples from clinically healthy calves showed that positive results by multiplex RT-qPCR were closely related to a significant increase of antibody titers by VNT in bovine coronavirus (BCoV), bovine torovirus (BToV), and bovine respiratory syncytial virus (BRSV). In addition, our data exhibited that BCoV, BToV, BRSV, bovine parainfluenza virus 3, and Mycoplasma bovis have been more frequently detected in calves infected with BRD compared to those detected in clinically healthy calves. Moreover, the data presented herein revealed co-infections by combination multiple viral pathogens with bacterial pathogens are closely involved in the onset of BRD. Taken together, our study demonstrates multiplex RT-qPCR which can simultaneously analyze multiple pathogens, including viruses and bacteria, and is useful for the early detection of BRD.

Bovine viral diarrhea virus (BVDV) is a viral pathogen associated with serious problems in the cattle industry. Cattle persistently infected (PI) with BVDV are mild or asymptomatic; however, they become a source of BVDV transmission to other cattle. Hence, it is important to rapidly identify and remove the PI animals from cattle herds. Whereas cattle acutely infected (AI) with BVDV have various symptoms, yet they generally recover within 3 weeks. However, there is a paucity of information concerning clinical characteristics of AI cattle. Further accumulation of information would be required to accurately diagnose AI cattle with BVDV. Here, we attempted to obtain valuable information via various analyses using a case report of BVD outbreak that occurred for approximately four months in Iwate Prefecture in 2017. Using eight calves and multiple tests (real-time RT-PCR, virus isolation, enzyme-linked immunosorbent assay, and virus neutralization assay) over 6 weeks, we diagnosed the continuous BVD outbreak as an acute infection and not a persistent one. Additionally, we revealed that the sporadic case was caused by low pathogenic BVDV2 via BVDV genotyping and phylogenetic analysis. The data suggest that BVDV2 AI animals might also be a source of transmission to susceptible calves; hence, it might persist for a long period owing to multiple AI animals. These findings provide useful information to diagnose AI and PI cattle with BVDV in the field.

Bovine viral diarrhea virus (BVDV) infection results in a wide variety of clinical manifestations and is a pathogen that is able to cause huge economic losses in the cattle industry worldwide. It is important to identify cattle that are persistently infected (PI) by BVDV within the herd as early as possible because PI animals are the main reservoir of the virus. In contrast, cattle who are acutely infected (AI) with BVDV show various clinical signs, but most cattle show either mild symptoms or are asymptomatic. In general, AI and PI animals can be distinguished by repeat testing within an interval of at least 21 days. However, we found a rare case of a BVDV2-infected AI animal with long-term viral presence, making it indistinguishable from PI through two tests within an interval of 21 days. As a result, we diagnosed one infected animal as AI after 35 days from the initial sample collection via multiple analyses. Our findings recommend performing an additional test using samples that have been collected after 14–21 days from the second sample collection in cases where it is difficult to accurately differentiate an AI diagnosis from a PI diagnosis after only two tests. Additionally, our analysis exhibits that monitoring the number of copies of viruses with similar genomes in the sera by means of quantitative real-time RT-PCR through several sample collections periods might be useful to distinguish AI from PI. Furthermore, our data suggest that the AI animals with a long-term viral presence who show test results similar to those of PI animals might be the result of a coincidental combination of various factors that are present in cattle fields. These findings provide useful information that can be used to improve the diagnosis of BVDV in the field.