A Combined Approach for Detection of Ovine Small Ruminant Retrovirus Co-Infections

Rosato, Giuliana; Abril, Carlos; Hilbe, Monika; Seehusen, Frauke

doi:10.3390/v15020376

Cited by 3 publications

(1 citation statement)

References 46 publications

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“…Due to the identical envelope glycoproteins, JSRV and Enzootic Nasal Tumor Virus (ENTV) of sheep and goat nasal adenocarcinomas can cause cell transformation and malignancy (Monot et al 2015). The occurrence of co-morbidities has been suggested by the frequent reports of JSRV-induced OPA in sheep flocks together with MVV and CAEV in recent years (Rosato et al 2023). In a similar study in India, MVV, JSRV, and mycoplasma co-infection were reported in sheep and goats (Valecha et al 2023).…”

Section: Introductionmentioning

confidence: 99%

Ovine pulmonary adenocarcinoma (OPA) in sheep: an update on epidemiology, pathogenesis and diagnosis

B N,

K N

et al. 2023

J Exp Bio & Ag Sci

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Ovine pulmonary adenocarcinoma (OPA) is a spontaneous lung tumor in sheep caused by Jaagsiekte sheep retrovirus (JSRV) belonging to the Retroviridae. The primary aim of this review work is to give brief insights into the epidemiological aspects of OPA based on a meta-analysis of available research work. This review article also discussed pathogenesis, diagnostic tests and control strategies available for OPA in Sheep. This will help in developing future strategies for disease-free status in India. This disease is endemic in Europe, Africa, Asia, and American continents, causing significant economic losses due to chronic respiratory illness and persistent infections in flocks. The virus is unique among retroviruses with selective affinity to lungs and is the only virus known to cause spontaneous lung tumors in sheep. The incubation time ranges for sheep with naturally occurring OPA ranged from one to four years. There are two pathological forms of the disease: classical and atypical. At an early stage, OPA is difficult to detect in sheep due to a lack of preclinical diagnostic methods, as JSRV is poorly immunogenic and doesn't induce an immune response. PCR, histopathology, and immunohistochemistry are recommended methods for OIE diagnosis. To become a JSRV-free country, mandatory surveillance, detection, and removal of positive animals are required, as OPA is difficult to control due to a lack of vaccines and preclinical diagnostic tests. Due to its similar histological and molecular pathogenesis to that of human lung cancer, OPA is considered an ideal large animal model of human lung adenocarcinoma.

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Section: Introductionmentioning

confidence: 99%

Ovine pulmonary adenocarcinoma (OPA) in sheep: an update on epidemiology, pathogenesis and diagnosis

B N,

K N

et al. 2023

J Exp Bio & Ag Sci

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Differential gene expression and immune cell infiltration in maedi-visna virus-infected lung tissues

Shi,

Zhang,

Chen

et al. 2024

BMC Genomics

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Background Maedi-visna virus (MVV) is a lentivirus that infects monocyte/macrophage lineage cells in sheep, goats, and wild ruminants and causes pneumonia, mastitis, arthritis, and encephalitis. The immune response to MVV infection is complex, and a complete understanding of its infection and pathogenesis is lacking. This study investigated the in vivo transcriptomic patterns of lung tissues in sheep exposed to MVV using the RNA sequencing technology. Result The results indicated that 2,739 genes were significantly differentially expressed, with 1,643 downregulated genes and 1,096 upregulated genes. Many variables that could be unique to MVV infections were discovered. Gene Ontology analysis revealed that a significant proportion of genes was enriched in terms directly related to the immune system and biological responses to viral infections. Kyoto Encyclopedia of Genes and Genomes analysis revealed that the most enriched pathways were related to virus-host cell interactions and inflammatory responses. Numerous immune-related genes, including those encoding several cytokines and interferon regulatory factors, were identified in the protein-protein interaction network of differentially expressed genes (DEGs). The expression of DEGs was evaluated using real-time polymerase chain reaction and western blot analysis. CXCL13, CXCL6, CXCL11, CCR1, CXCL8, CXCL9, CXCL10, TNFSF8, TNFRSF8, IL7R, IFN-γ, CCL2, and MMP9 were upregulated. Immunohistochemical analysis was performed to identify the types of immune cells that infiltrated MVV-infected tissues. B cells, CD4+ and CD8+ T cells, and macrophages were the most prevalent immune cells correlated with MVV infection in the lungs. Conclusion Overall, the findings of this study provide a comprehensive understanding of the in vivo host response to MVV infection and offer new perspectives on the gene regulatory networks that underlie pathogenesis in natural hosts.

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Lesion Localization and Pathological Diagnosis of Ovine Pulmonary Adenocarcinoma Based on MASK R-CNN

Chen,

Zhang,

Duan

et al. 2024

Animals

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Ovine pulmonary adenocarcinoma (OPA) is a contagious lung tumour caused by the Jaagsiekte Sheep Retrovirus (JSRV). Histopathological diagnosis is the gold standard for OPA diagnosis. However, interpretation of traditional pathology images is complex and operator dependent. The mask regional convolutional neural network (Mask R-CNN) has emerged as a valuable tool in pathological diagnosis. This study utilized 54 typical OPA whole slide images (WSI) to extract 7167 typical lesion images containing OPA to construct a Common Objects in Context (COCO) dataset for OPA pathological images. The dataset was categorized into training and test sets (8:2 ratio) for model training and validation. Mean average specificity (mASp) and average sensitivity (ASe) were used to evaluate model performance. Six WSI-level pathological images (three OPA and three non-OPA images), not included in the dataset, were used for anti-peeking model validation. A random selection of 500 images, not included in the dataset establishment, was used to compare the performance of the model with assessment by pathologists. Accuracy, sensitivity, specificity, and concordance rate were evaluated. The model achieved a mASp of 0.573 and an ASe of 0.745, demonstrating effective lesion detection and alignment with expert annotation. In Anti-Peeking verification, the model showed good performance in locating OPA lesions and distinguished OPA from non-OPA pathological images. In the random 500-image diagnosis, the model achieved 92.8% accuracy, 100% sensitivity, and 88% specificity. The agreement rates between junior and senior pathologists were 100% and 96.5%, respectively. In conclusion, the Mask R-CNN-based OPA diagnostic model developed for OPA facilitates rapid and accurate diagnosis in practical applications.

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A Combined Approach for Detection of Ovine Small Ruminant Retrovirus Co-Infections

Cited by 3 publications

References 46 publications

Ovine pulmonary adenocarcinoma (OPA) in sheep: an update on epidemiology, pathogenesis and diagnosis

Ovine pulmonary adenocarcinoma (OPA) in sheep: an update on epidemiology, pathogenesis and diagnosis

Differential gene expression and immune cell infiltration in maedi-visna virus-infected lung tissues

Lesion Localization and Pathological Diagnosis of Ovine Pulmonary Adenocarcinoma Based on MASK R-CNN

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