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Background The clustering of immune repertoire data is challenging due to the computational cost associated with a very large number of pairwise sequence comparisons. To overcome this limitation, we developed Anchor Clustering, an unsupervised clustering method designed to identify similar sequences from millions of antigen receptor gene sequences. First, a Point Packing algorithm is used to identify a set of maximally spaced anchor sequences. Then, the genetic distance of the remaining sequences to all anchor sequences is calculated and transformed into distance vectors. Finally, distance vectors are clustered using unsupervised clustering. This process is repeated iteratively until the resulting clusters are small enough so that pairwise distance comparisons can be performed. Results Our results demonstrate that Anchor Clustering is faster than existing pairwise comparison clustering methods while providing similar clustering quality. With its flexible, memory-saving strategy, Anchor Clustering is capable of clustering millions of antigen receptor gene sequences in just a few minutes. Conclusions This method enables the meta-analysis of immune-repertoire data from different studies and could contribute to a more comprehensive understanding of the immune repertoire data space.

Abstract Background T cell clonality assays in veterinary medicine currently target only the T cell receptor gamma (TRG) locus. Existing assays have suboptimal sensitivity because of insufficient primer coverage of all possible rearrangements. Objective Develop higher sensitivity clonality assays targeting the TRG, delta (TRD), and beta (TRB) loci in cats. Animals Cats with histopathologically confirmed lymphoma (n = 89), non-lymphoma (n = 35), and possible hepatic small cell lymphoma (n = 31). Methods Molecular clonality assay development utilizing our recently reported topology and expressed repertoire data of the T cell receptor loci in cats. Determination of clonality status of lymphoma, non lymphoma, and possible hepatic small cell lymphoma samples, and calculation of assay sensitivity and specificity. Results The new multiplex TRG assay yielded the highest sensitivity (95.5%). All assays yielded 100% specificity except for the new multiplex TRG assay (97.3%). The combination of the new TRG and TRB assays yielded sensitivity of 98.9% and specificity of 97.0%. The new TRG assay detected clonality in 17/31 possible small cell lymphoma livers, whereas an existing TRG assay detected clonality in 6/31 livers. Conclusions and Clinical Importance The assessment of multiple T cell loci compensates for the potential shortcomings of individual assays. Using a combination of molecular clonality assays will increase the overall sensitivity for the diagnosis of T-cell lymphoma in cats, especially intestinal, and hepatic small cell lymphoma. Hepatic small cell lymphomas detected by the new TRG assay utilized rarely expressed V and J genes not recognized by previous assays, likely indicating unique biology of hepatic small cell lymphoma in cats.

Lymphoma is the most common hematopoietic tumour in dogs and is remarkably similar to the human disease. Tumour biomarker discovery is providing new tools for diagnostics and predicting therapeutic response and clinical outcome. MicroRNAs are small non-coding RNAs that participate in post-transcriptional gene regulation and their aberrant expression can impact genes involved in cancer. The aim of this study was to characterize microRNA expression in lymph nodes and plasma from dogs with multicentric B or T cell lymphoma compared to healthy control dogs. We further compared expression between lymph nodes and corresponding plasma samples and assessed changes in expression at relapse compared to time of diagnosis. Lastly, we investigated microRNAs for association with clinical outcome in patients treated with CHOP chemotherapy. A customized PCR array was utilized to profile 38 canine target microRNAs. Quantification was performed using real time RT-qPCR and relative expression was determined by the delta-delta Ct method. In lymph nodes, there were 16 microRNAs with significantly altered expression for B cell lymphoma and 9 for T cell lymphoma. In plasma, there were 15 microRNAs altered for B cell lymphoma and 3 for T cell lymphoma. The majority of microRNAs did not have correlated expression between lymph node and plasma and only 8 microRNAs were significantly different between diagnosis and relapse. For B cell lymphoma, 8 microRNAs had differential expression in the non-remission group compared to dogs that completed CHOP in complete remission. Four of these microRNAs were also altered in patients that died prior to one-year. Kaplan-Meier survival curves for high versus low microRNA expression revealed that 10 microRNAs were correlated with progression-free survival and 3 with overall survival. This study highlights microRNAs of interest for canine multicentric lymphoma. Future goals include development of microRNA panels that may be useful as biomarkers with the intent to provide improved outcome prediction to veterinary cancer patients.

The dog is valued as a companion animal and increasingly recognized as a model for human disorders. Given the importance of T cells in health and disease, comprehensive knowledge of canine T cells can contribute to our understanding of pathogenesis mechanisms and inform the development of new treatment strategies. However, the diversity of canine T cells is still poorly understood mainly due to the lack of species-reactive antibodies for use in flow cytometry. The aim of this study was to generate a detailed atlas of peripheral blood TCRαβ + T cells of healthy dogs using single-cell RNA-sequencing (scRNAseq) combined with immune repertoire sequencing. A total of 22 TCRαβ + T cell clusters were identified, which were classified into three major groups: CD4-dominant (11 clusters), CD8A-dominant (8 clusters), and CD4/CD8A-mixed (3 clusters). Based on differential gene expression, distinct differentiation states (naïve, effector, memory, exhausted) and lineages (e.g. CD4 T helper and regulatory T cells) could be distinguished. Importantly, several T cell populations were identified, which have not been described in dogs before. Of particular note, our data provide first evidence for the existence of canine mucosa-associated invariant T cell (MAIT)-like cells, representing one of three newly identified FCER1G + innate-like CD8A + T cell populations in the peripheral blood of healthy dogs. In conclusion, using scRNAseq combined with immune repertoire sequencing we were able to resolve canine TCRαβ + T cell populations at unprecedented resolution. The peripheral blood TCRαβ + T cell atlas of healthy dogs generated here represents an important reference data set for future studies and is of relevance for identifying new targets for T cell-specific therapies.

The domestic cat (Felis catus) is a valued companion animal and a model for virally induced cancers and immunodeficiencies. However, species-specific limitations such as a scarcity of immune cell markers constrain our ability to resolve immune cell subsets at sufficient detail. The goal of this study was to characterize circulating feline T cells and other leukocytes based on their transcriptomic landscape and T-cell receptor repertoire using single cell RNA-sequencing. Peripheral blood from 4 healthy cats was enriched for T cells by flow cytometry cell sorting using a mouse anti-feline CD5 monoclonal antibody. Libraries for whole transcriptome, αβ T cell receptor transcripts and γδ T cell receptor transcripts were constructed using the 10x Genomics Chromium Next GEM Single Cell 5' reagent kit and the Chromium Single Cell V(D)J Enrichment Kit with custom reverse primers for the feline orthologs. Unsupervised clustering of whole transcriptome data revealed 7 major cell populations - T cells, neutrophils, monocytic cells, B cells, plasmacytoid dendritic cells, mast cells and platelets. Sub cluster analysis of T cells resolved naive (CD4+ and CD8+), CD4+ effector T cells, CD8+ cytotoxic T cells and γδ T cells. Cross species analysis revealed a high conservation of T cell subsets along an effector gradient with equitable representation of veterinary species (horse, dog, pig) and humans with the cat. Our V(D)J repertoire analysis identified a subset of CD8+ cytotoxic T cells with skewed TRA and TRB gene usage, conserved TRA and TRB junctional motifs, restricted TRA/TRB pairing and reduced diversity in TRG junctional length. We also identified a public γδ T cell subset with invariant TRD and TRG chains and a CD4+ TEM-like phenotype. Among monocytic cells, we resolved three clusters of classical monocytes with polarization into pro- and anti-inflammatory phenotypes in addition to a cluster of conventional dendritic cells. Lastly, our neutrophil sub clustering revealed a larger mature neutrophil cluster and a smaller exhausted/activated cluster. Our study is the first to characterize subsets of circulating T cells utilizing an integrative approach of single cell RNA-sequencing, V(D)J repertoire analysis and cross species analysis. In addition, we characterize the transcriptome of several myeloid cell subsets and demonstrate immune cell relatedness across different species.

Background The domestic cat ( Felis catus ) is an important companion animal and is used as a large animal model for human disease. However, the comprehensive study of adaptive immunity in this species is hampered by the lack of data on lymphocyte antigen receptor genes and usage. The objectives of this study were to annotate the feline T cell receptor (TR) loci and to characterize the expressed repertoire in lymphoid organs of normal cats using high-throughput sequencing. Results The Felis catus TRG locus contains 30 genes: 12 TRGV, 12 TRGJ and 6 TRGC, the TRB locus contains 48 genes: 33 TRBV, 2 TRBD, 11 TRBJ, 2 TRBC, the TRD locus contains 19 genes: 11 TRDV, 2 TRDD, 5 TRDJ, 1 TRDC, and the TRA locus contains 127 genes: 62 TRAV, 64 TRAJ, 1 TRAC. Functional feline V genes form monophyletic clades with their orthologs, and clustering of multimember subgroups frequently occurs in V genes located at the 5′ end of TR loci. Recombination signal (RS) sequences of the heptamer and nonamer of functional V and J genes are highly conserved. Analysis of the TRG expressed repertoire showed preferential intra-cassette over inter-cassette rearrangements and dominant usage of the TRGV2–1 and TRGJ1–2 genes. The usage of TRBV genes showed minor bias but TRBJ genes of the second J-C-cluster were more commonly rearranged than TRBJ genes of the first cluster. The TRA/TRD V genes almost exclusively rearranged to J genes within their locus. The TRAV/TRAJ gene usage was relatively balanced while the TRD repertoire was dominated by TRDJ3. Conclusions This is the first description of all TR loci in the cat. The genomic organization of feline TR loci was similar to that of previously described jawed vertebrates ( gnathostomata ) and is compatible with the birth-and-death model of evolution. The large-scale characterization of feline TR genes provides comprehensive baseline data on immune repertoires in healthy cats and will facilitate the development of improved reagents for the diagnosis of lymphoproliferative diseases in cats. In addition, these data might benefit studies using cats as a large animal model for human disease.

Anticoagulant rodenticide (AR) poisoning has emerged as a significant concern for conservation and management of non-target wildlife. The purpose for these toxicants is to suppress pest populations in agricultural or urban settings. The potential of direct and indirect exposures and illicit use of ARs on public and community forest lands have recently raised concern for fishers (Martes pennanti), a candidate for listing under the federal Endangered Species Act in the Pacific states. In an investigation of threats to fisher population persistence in the two isolated California populations, we investigate the magnitude of this previously undocumented threat to fishers, we tested 58 carcasses for the presence and quantification of ARs, conducted spatial analysis of exposed fishers in an effort to identify potential point sources of AR, and identified fishers that died directly due to AR poisoning. We found 46 of 58 (79%) fishers exposed to an AR with 96% of those individuals having been exposed to one or more second-generation AR compounds. No spatial clustering of AR exposure was detected and the spatial distribution of exposure suggests that AR contamination is widespread within the fisher's range in California, which encompasses mostly public forest and park lands Additionally, we diagnosed four fisher deaths, including a lactating female, that were directly attributed to AR toxicosis and documented the first neonatal or milk transfer of an AR to an altricial fisher kit. These ARs, which some are acutely toxic, pose both a direct mortality or fitness risk to fishers, and a significant indirect risk to these isolated populations. Future research should be directed towards investigating risks to prey populations fishers are dependent on, exposure in other rare forest carnivores, and potential AR point sources such as illegal marijuana cultivation in the range of fishers on California public lands.

Background In the rapidly evolving landscape of veterinary healthcare, integrating machine learning (ML) clinical decision-making tools with electronic health records (EHRs) promises to improve diagnostic accuracy and patient care. However, the seamless integration of ML classifiers into existing EHR systems in veterinary medicine is often hindered by the inherent rigidity of these systems or by the limited availability of IT resources to implement the modifications necessary for ML compatibility. Results Anna is a standalone analytics platform that can host ML classifiers and interfaces with EHR systems to provide classifier predictions for laboratory data in real-time. Following a request from the EHR system, Anna retrieves patient-specific data from the EHR system, merges diagnostic test results based on user-defined temporal criteria and returns predictions for all available classifiers for display in real-time. Anna was developed in Python and is freely available. Because Anna is a stand-alone platform, it does not require substantial modifications to the existing EHR, allowing for easy integration into existing computing infrastructure. To demonstrate Anna’s versatility, we implemented three previously published ML classifiers to predict a diagnosis of hypoadrenocorticism, leptospirosis, or a portosystemic shunt in dogs. Conclusion Anna is an open-source tool designed to improve the accessibility of ML classifiers for the veterinary community. Its flexible architecture supports the integration of classifiers developed in various programming languages and with diverse environment requirements. Anna facilitates rapid prototyping, enabling researchers and developers to deploy ML classifiers quickly without modifications to the existing EHR system. Anna could drive broader adoption of ML in veterinary practices, ultimately enhancing diagnostic capabilities and patient outcomes.

Abstract Background Necrotizing meningoencephalitis (NME) in the pug dogs is a fatal neuroinflammatory disease associated with rapid progression and poor response to conventional immunosuppressive therapy. Diagnosis is typically made after severe neurological abnormalities have manifested. Hypothesis/Objective Pug dogs at genetic risk for NME might manifest neurological abnormalities before developing pathognomonic clinical signs of NME. Animals Thirty-six pug dogs less than 4 years of age asymptomatic for NME. Methods Prospective observational cohort study with germline genome-wide genotyping. Neurological examinations were performed 4 weeks apart to document reproducible findings of central nervous system disease. Magnetic resonance imaging, cerebrospinal fluid analysis, and testing for infectious diseases were performed in all pugs with reproducible abnormalities detected on neurological examination. Results The overall risk allele frequency in this cohort was 40%; 5 (14%) dogs were high risk, 19 (53%) dogs were medium risk, and 12 (33%) dogs were low genetic risk for NME. Reproducible abnormalities detected on neurological examination were identified in 8/24 (33%) genetically at-risk dogs and 0/12 (0%) low risk dogs. Clinical abnormalities included multifocal spinal pain in 8/8, reduced menace response in 5/8, and lateralizing postural reaction deficits in 5/8 pugs. There was a strong association between genotype risk and the presence of this clinical phenotype (P = .03). Conclusions and Clinical Importance Our findings suggest the presence of a novel early clinical phenotype of NME in apparently asymptomatic genetically at-risk pugs which might be used to plan early diagnostic and therapeutic clinical trials.

While some companion animals have been shown to be susceptible to SARS-CoV-2, their role in the COVID-19 pandemic has remained poorly investigated. Equids are susceptible to SARS-CoV-2 based on the similarity of the human ACE-2 receptor and reports of infection. Clinical disease and prevalence factors associated with SARS-CoV-2 infection in equids have not yet been investigated. The aim of this study was to determine the seroprevalence of SARS-CoV-2 and selected prevalence factors in 1186 equids presented for various conditions to a Veterinary Medical Teaching Hospital over a two-year period. Blood samples were tested for SARS-CoV-2 antibodies using an ELISA targeting the receptor binding domain (RBD) of the SARS-CoV-2 spike protein. Further, selected prevalence factors (season, age, breed, sex, presenting complaint) were retrieved from the medical records. No information was available on whether the horses had come into contact with COVID-19-positive individuals. Among the study animals, 42/1186 (3.5%) horses had detectable SARS-CoV-2 antibodies. Amongst the prevalence factors investigated, only seasonality (spring) was associated with a greater frequency of seropositivity to SARS-CoV-2. Horses with medical and surgical complaints were more likely to test seropositive to SARS-CoV-2 compared to horses presented for routine health care procedures, suggesting more frequent and/or longer interactions with individuals with COVID-19. While horses can become infected with SARS-CoV-2 via the occasional spillover from COVID-19 individuals, clinical disease expression remains subclinical, making horses an unlikely contributor to the spread of SARS-CoV-2.