Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) in humans, has a wide host range, naturally infecting felids, canids, cervids, rodents and mustelids. Transmission of SARS-CoV-2 is universally accepted to occur via contact with contaminated secretions from the respiratory epithelium, either directly or indirectly. Transmission via droplet nuclei, generated from a cough or sneeze, has also been reported in several human and experimental animal scenarios. However, the role of droplet transmission at the human–animal interface remains to be fully elucidated. Here, the ferret infection model was used to investigate the routes of infection for the SARS-CoV-2 beta variant (B.1.351). Ferrets were exposed to droplets containing infectious SARS-CoV-2, ranging between 4 and 106 µm in diameter, simulating larger droplets produced by a cough from an infected person. Following exposure, viral RNA was detected on the fur of ferrets, and was deposited onto environmental surfaces, as well as the fur of ferrets placed in direct contact; SARS-CoV-2 remained infectious on the fur for at least 48 h. Low levels of viral RNA were detected in the nasal washes early post-exposure, yet none of the directly exposed, or direct-contact ferrets, became robustly infected or seroconverted to SARS-CoV-2. In comparison, ferrets intranasally inoculated with the SARS-CoV-2 beta variant became robustly infected, shedding viral RNA and infectious virus from the nasal cavity, with transmission to 75 % of naive ferrets placed in direct contact. These data suggest that larger infectious droplet nuclei and contaminated fur play minor roles in SARS-CoV-2 transmission among mustelids and potentially other companion animals.

Rabies virus (RABV) causes a fatal encephalitis that can be prevented through timely vaccination. The levels of virus neutralising antibodies against rabies virus induced by vaccination can be measured using the fluorescent antibody virus neutralisation (FAVN) test. Following incubation of live virus with sera, this method involves the fixation of cell monolayers and staining of rabies virus-specific antigen using fluorescein isothiocyanate (FITC) -conjugated antibody to enable visualisation of rabies virus antigen using a fluorescence microscope. To simplify this procedure, a fluorescent recombinant rabies virus was constructed using reverse genetics by inserting the gene for the mCherry fluorescent protein in front of the ribonucleoprotein gene of the SAD B-19 genome and replacing its glycoprotein with that of the Challenge Virus Standard (CVS)-11 RABV strain to ensure antigenic authenticity with the FAVN. This new recombinant virus (termed mCCCG) expressed the mCherry protein to high levels enabling direct observation of infected cells. In vitro growth kinetics of mCCCG were indistinguishable from that of CVS-11. The stability of the recombinant virus was assessed by sequencing several passages of the rescued virus and only minor changes were detected. Comparative assessment of the virus neutralisation test using mCherry producing virus (NTmCV) against the FAVN demonstrated that test results were equivalent to each other; therefore, mCCCG can be used as an alternative to CVS-11 for measuring antibody titres against the rabies virus. The use of NTmCV removes the need for expensive antibody conjugates and significantly reduces assay time. This would be particularly beneficial for RABV serological assessment in resource limited settings. Moreover, the reading of the plates can be automatically using a cell imaging reader.

Reverse zoonotic transmission events of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been described since the start of the pandemic, and the World Organisation for Animal Health (WOAH) designated the detection of SARS-CoV-2 in animals a reportable disease. Eighteen domestic and zoo animals in Great Britain and Jersey were tested by APHA for SARS-CoV-2 during 2020–2023. One domestic cat (Felis catus), three domestic dogs (Canis lupus familiaris), and three Amur tigers (Panthera tigris altaica) from a zoo were confirmed positive during 2020–2021 and reported to the WOAH. All seven positive animals were linked with known SARS-CoV-2 positive human contacts. Characterisation of the SARS-CoV-2 variants by genome sequencing indicated that the cat was infected with an early SARS-CoV-2 lineage. The three dogs and three tigers were infected with the SARS-CoV-2 Delta variant of concern (B.1.617.2). The role of non-human species in the onward transmission and emergence of new variants of SARS-CoV-2 remain poorly defined. Continued surveillance of SARS-CoV-2 in relevant domestic and captive animal species with high levels of human contact is important to monitor transmission at the human−animal interface and to assess their role as potential animal reservoirs.

Rabies remains a major neglected disease, causing tens of thousands of deaths annually in endemic regions. Cell culture-based assays are central to rabies diagnostics and antibody quantification, yet interpretation relies on manual fluorescence image reading, which is labour-intensive, subjective, and difficult to scale. Here, we present, what is to our knowledge, the first AI-based workflow for detecting rabies virus infection in BHK-21 cell cultures and quantifying antibody titres. Three state-of-the-art architectures–ResNet, Swin Transformer V2, and MambaOut–were trained on a large dataset of 2344 fluorescence images (36,822 annotated patches) capturing biological and technical variability. Evaluation at patch, image, and well levels showed MambaOut consistently outperformed other models, achieving 0.996 accuracy, 0.993 F1-score, and 0.999 AUC-ROC at the well level. To assess applicability, models were tested on unseen images from the WHO/WOAH-recommended fluorescent antibody virus neutralisation assay. MambaOut demonstrated complete agreement with ground truth in predicting antibody concentrations, confirming workflow reliability for vaccine assessment and pet travel schemes. These results establish a foundation for AI-assisted rabies diagnostics and open opportunities for applying deep learning to other cell culture-based viral assays. AI-driven automation for high-throughput image analysis offers a scalable and time-efficient solution for diagnostic laboratories, particularly in endemic countries.