Cryptic susceptibility to penicillin/ß-lactamase inhibitor combinations in emerging multidrug-resistant, hospital-adapted Staphylococcus epidermidis lineages.

Global spread of multidrug-resistant, hospital-adapted Staphylococcus epidermidis lineages underscores the need for new therapeutic strategies. Here we show that many S. epidermidis isolates belonging to these lineages display cryptic susceptibility to penicillin/ß-lactamase inhibitor combinations under in vitro conditions, despite carrying the methicillin resistance gene mecA. Using a mouse thigh model of S. epidermidis infection, we demonstrate that single-dose treatment with amoxicillin/clavulanic acid significantly reduces methicillin-resistant S. epidermidis loads without leading to detectable resistance development. On the other hand, we also show that methicillin-resistant S. epidermidis is capable of developing increased resistance to amoxicillin/clavulanic acid during long-term in vitro exposure to these drugs. These findings suggest that penicillin/ß-lactamase inhibitor combinations could be a promising therapeutic candidate for treatment of a high proportion of methicillin-resistant S. epidermidis infections, although the in vivo risk of resistance development needs to be further addressed before they can be incorporated into clinical trials.

Comparison of cone-beam and fan-beam computed tomography and low-field magnetic resonance imaging for detection of proximal phalanx dorsoproximal osteochondral defects.

BACKGROUND: Dorsoproximal osteochondral defects commonly affect the proximal phalanx, but information about diagnosis on computed tomography (CT) and magnetic resonance imaging (MRI) is limited. OBJECTIVES: To assess CT and MRI diagnoses of osteochondral defects, describe the lesions and compare sensitivity and specificity of the modalities using macroscopic pathology as gold standard. STUDY DESIGN: Cross-sectional study. METHODS: Thirty-five equine cadaver limbs underwent standing cone-beam CT (CBCT), fan-beam CT (FBCT), low-field MRI and pathological examination. CT and MR images were examined for proximal phalanx dorsomedial and dorsolateral eminence osteochondral defects. Defect dimensions were measured. Imaging diagnoses and measurements were compared with macroscopic examination. RESULTS: Fifty-six defects were seen over 70 potential locations. On CBCT and FBCT, osteochondral defects appeared as subchondral irregularity/saucer-shaped defects. On MRI, osteochondral defects were a combination of articular cartilage defect on dorsal images and subchondral flattening/irregularity on sagittal images. Subchondral thickening and osseous short tau inversion recovery hyperintensity were found concurrent with osteochondral defects. Compared with pathological examination, the sensitivity and specificity of diagnosis were 86% (95% confidence interval [95% CI] 75%-93%) and 64% (95% CI 38%-85%) for FBCT; 64% (95% CI 51%-76%) and 71% (95% CI 46%-90%) for CBCT; and 52% (95% CI 39%-65%) and 71% (95% CI 46%-90%) for MRI. Sensitivity of all modalities increased with defect size. Macroscopic defect dimensions were strongly correlated with CBCT (r = 0.76, p < 0.001) and moderately correlated with FBCT and MRI (r = 0.65, p < 0.001). Macroscopic measurements were significantly greater than all imaging modality dimensions (p < 0.001), potentially because macroscopy included articular cartilage pathology. MAIN LIMITATIONS: Influence of motion artefact could not be assessed. CONCLUSIONS: Osteochondral defects could be visualised using both CT and MRI with sensitivity increasing with defect size. Diagnostic performance was best using FBCT, followed by CBCT then MRI, but CBCT-measured defect size best correlated with macroscopic examination. MRI provided useful information on fluid signal associated with defects, which could represent active pathology.

HAM-ART: An optimised culture-free Hi-C metagenomics pipeline for tracking antimicrobial resistance genes in complex microbial communities.

Shotgun metagenomics is a powerful tool to identify antimicrobial resistance (AMR) genes in microbiomes but has the limitation that extrachromosomal DNA, such as plasmids, cannot be linked with the host bacterial chromosome. Here we present a comprehensive laboratory and bioinformatics pipeline HAM-ART (Hi-C Assisted Metagenomics for Antimicrobial Resistance Tracking) optimised for the generation of metagenome-assembled genomes including both chromosomal and extrachromosomal AMR genes. We demonstrate the performance of the pipeline in a study comparing 100 pig faecal microbiomes from low- and high-antimicrobial use pig farms (organic and conventional farms). We found significant differences in the distribution of AMR genes between low- and high-antimicrobial use farms including a plasmid-borne lincosamide resistance gene exclusive to high-antimicrobial use farms in three species of Lactobacilli. The bioinformatics pipeline code is available at https://github.com/lkalmar/HAM-ART.

Optimal Bayesian design for model discrimination via classification.

Performing optimal Bayesian design for discriminating between competing models is computationally intensive as it involves estimating posterior model probabilities for thousands of simulated data sets. This issue is compounded further when the likelihood functions for the rival models are computationally expensive. A new approach using supervised classification methods is developed to perform Bayesian optimal model discrimination design. This approach requires considerably fewer simulations from the candidate models than previous approaches using approximate Bayesian computation. Further, it is easy to assess the performance of the optimal design through the misclassification error rate. The approach is particularly useful in the presence of models with intractable likelihoods but can also provide computational advantages when the likelihoods are manageable. Supplementary Information: The online version contains supplementary material available at 10.1007/s11222-022-10078-2.

Eimeria stiedae causes most of the white-spotted liver lesions in wild European rabbits in Cambridgeshire, United Kingdom.

In rabbits, a white-spotted liver can be indicative of one of several disease processes, frequently caused by parasites. To date, the prevalence of white-spotted liver in wild rabbits, Oryctolagus cuniculus, in the United Kingdom is undetermined. We evaluated the prevalence and main parasitic etiologies of this entity in a U.K. population of wild rabbits. Wild rabbits (n = 87) were shot in Cambridgeshire for population control, and cadavers were donated for research. Postmortem examination was undertaken, including gross and histologic hepatic examination. Macroscopic lesions consistent with white-spotted liver were found in 46 of 87 (53%) rabbits examined; most of these lesions were considered to be mild. For 28 of 46 (59%) rabbits with gross hepatic lesions, an etiologic agent was apparent histologically. Eimeria stiedae was detected in 21 of 87 (24%) rabbits, and Calodium hepaticum (syn. Capillaria hepatica) was detected in 7 of 87 (8%). In the subset of rabbits killed in the summer, there was a significant association between white-spotted liver and juvenile age class. There was also an association between white-spotted liver caused by E. stiedae and juvenile age class. When restricting analysis to rabbits with white-spotted liver caused by E. stiedae and submitted in the summer, both juvenile age class and female had significant effects. E. stiedae and C. hepaticum can be transmitted to pet lagomorphs via contaminated vegetation, and to humans in the case of the latter, which demonstrates the importance of monitoring the prevalence of these parasitic diseases in wild rabbits.

Ecology, evolution and spillover of coronaviruses from bats.

In the past two decades, three coronaviruses with ancestral origins in bats have emerged and caused widespread outbreaks in humans, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the first SARS epidemic in 2002-2003, the appreciation of bats as key hosts of zoonotic coronaviruses has advanced rapidly. More than 4,000 coronavirus sequences from 14 bat families have been identified, yet the true diversity of bat coronaviruses is probably much greater. Given that bats are the likely evolutionary source for several human coronaviruses, including strains that cause mild upper respiratory tract disease, their role in historic and future pandemics requires ongoing investigation. We review and integrate information on bat-coronavirus interactions at the molecular, tissue, host and population levels. We identify critical gaps in knowledge of bat coronaviruses, which relate to spillover and pandemic risk, including the pathways to zoonotic spillover, the infection dynamics within bat reservoir hosts, the role of prior adaptation in intermediate hosts for zoonotic transmission and the viral genotypes or traits that predict zoonotic capacity and pandemic potential. Filling these knowledge gaps may help prevent the next pandemic.

Challenges in modelling the dynamics of infectious diseases at the wildlife-human interface.

The Covid-19 pandemic is of zoonotic origin, and many other emerging infections of humans have their origin in an animal host population. We review the challenges involved in modelling the dynamics of wildlife-human interfaces governing infectious disease emergence and spread. We argue that we need a better understanding of the dynamic nature of such interfaces, the underpinning diversity of pathogens and host-pathogen association networks, and the scales and frequencies at which environmental conditions enable spillover and host shifting from animals to humans to occur. The major drivers of the emergence of zoonoses are anthropogenic, including the global change in climate and land use. These, and other ecological processes pose challenges that must be overcome to counterbalance pandemic risk. The development of more detailed and nuanced models will provide better tools for analysing and understanding infectious disease emergence and spread.

Optimizing noninvasive sampling of a zoonotic bat virus.

Outbreaks of infectious viruses resulting from spillover events from bats have brought much attention to bat-borne zoonoses, which has motivated increased ecological and epidemiological studies on bat populations. Field sampling methods often collect pooled samples of bat excreta from plastic sheets placed under-roosts. However, positive bias is introduced because multiple individuals may contribute to pooled samples, making studies of viral dynamics difficult. Here, we explore the general issue of bias in spatial sample pooling using Hendra virus in Australian bats as a case study. We assessed the accuracy of different under-roost sampling designs using generalized additive models and field data from individually captured bats and pooled urine samples. We then used theoretical simulation models of bat density and under-roost sampling to understand the mechanistic drivers of bias. The most commonly used sampling design estimated viral prevalence 3.2 times higher than individual-level data, with positive bias 5-7 times higher than other designs due to spatial autocorrelation among sampling sheets and clustering of bats in roosts. Simulation results indicate using a stratified random design to collect 30-40 pooled urine samples from 80 to 100 sheets, each with an area of 0.75-1 m2, and would allow estimation of true prevalence with minimum sampling bias and false negatives. These results show that widely used under-roost sampling techniques are highly sensitive to viral presence, but lack specificity, providing limited information regarding viral dynamics. Improved estimation of true prevalence can be attained with minor changes to existing designs such as reducing sheet size, increasing sheet number, and spreading sheets out within the roost area. Our findings provide insight into how spatial sample pooling is vulnerable to bias for a wide range of systems in disease ecology, where optimal sampling design is influenced by pathogen prevalence, host population density, and patterns of aggregation.

Defining nosocomial transmission of Escherichia coli and antimicrobial resistance genes: a genomic surveillance study.

BACKGROUND: Escherichia coli is a leading cause of bloodstream infections. Developing interventions to reduce E coli infections requires an understanding of the frequency of nosocomial transmission, but the available evidence is scarce. We aimed to detect and characterise transmission of E coli and associated plasmids in a hospital setting. METHODS: In this prospective observational cohort study, patients were admitted to two adult haematology wards at the Cambridge University Hospitals NHS Foundation Trust in England. Patients aged 16 years and older who were treated for haematological malignancies were included. Stool samples were collected from study participants on admission, once per week, and at discharge. We sequenced multiple E coli isolates (both extended spectrum ß-lactamase [ESBL]-producing and non-ESBL-producing) from each stool sample. A genetic threshold to infer E coli transmission was defined by maximum within-host single nucleotide polymorphism (SNP) diversity and the probability of drawing observed pairs of between-patient isolates at different SNP thresholds. Putative transmission clusters were identified when sequences were less than the genetic threshold. Epidemiological links for each transmission event were investigated. We sequenced all E coli positive blood samples from the two adult haematology wards. FINDINGS: We recruited 174 (51%) of 338 adult patients admitted to the wards between May 13 and Nov 13, 2015. We obtained and cultured 376 stool samples from 149 patients, of which 152 samples from 97 (65%) patients grew E coli. Whole-genome sequencing was done on 970 isolates. We identified extensive diversity in the bacterial population (90 sequence types) and mixed E coli sequence type carriage. 24 (26%) patients carried two sequence types, 12 (13%) carried three, and six (6%) patients carried four or more sequence types. Using a 17 SNP cutoff we identified ten clusters in 20 patients. The largest cluster contained seven patients, whereas four patients were included in multiple clusters. Strong epidemiological links were found between patients in seven clusters. 17 (11%) of 149 patients had stool samples positive for ESBL-producing E coli, the most common of which was associated with bla CTX-M-15 (12 [71%] of 17). Long-read sequencing revealed that bla CTX-M-15 was often integrated into the chromosome, with little evidence for plasmid transmission. Seven patients developed E coli bloodstream infection, four with identical strains to those in their stool; two of these had documented nosocomial acquisition. INTERPRETATION: We provide evidence of bacterial transmission and endogenous infection during routine care by integrating genomic and epidemiological data and by determining a genetic cutoff informed by within-host diversity in the studied population. Our findings challenge single colony-based investigations, and the widely accepted notion of plasmid spread. FUNDING: UK Department of Health, Wellcome Trust, UK National Institute for Health Research.

Longitudinal Secretion of Paramyxovirus RNA in the Urine of Straw-Coloured Fruit Bats (Eidolon helvum).

The straw-coloured fruit bat (Eidolon helvum) is widespread in sub-Saharan Africa and is widely hunted for bushmeat. It is known to harbour a range of paramyxoviruses, including rubuloviruses and henipaviruses, but the zoonotic potential of these is unknown. We previously found a diversity of paramyxoviruses within a small, captive colony of E. helvum after it had been closed to contact with other bats for 5 years. In this study, we used under-roost urine collection to further investigate the paramyxovirus diversity and ecology in this colony, which had been closed to the outside for 10 years at the time of sampling. By sampling urine weekly throughout an entire year, we investigated possible seasonal patterns of shedding of virus or viral RNA. Using a generic paramyxovirus L-gene PCR, we detected eight distinct paramyxovirus RNA sequences. Six distinct sequences were detected using a Henipavirus-specific PCR that targeted a different region of the L-gene. Sequence detection had a bi-annual pattern, with the greatest peak in July, although different RNA sequences appeared to have different shedding patterns. No significant associations were detected between sequence detection and birthing season, environmental temperature or humidity, and no signs of illness were detected in any of the bats in the colony during the period of sample collection.

Persistence of Multiple Paramyxoviruses in a Closed Captive Colony of Fruit Bats (Eidolon helvum).

Bats have been identified as the natural hosts of several emerging zoonotic viruses, including paramyxoviruses, such as Hendra and Nipah viruses, that can cause fatal disease in humans. Recently, African fruit bats with populations that roost in or near urban areas have been shown to harbour a great diversity of paramyxoviruses, posing potential spillover risks to public health. Understanding the circulation of these viruses in their reservoir populations is essential to predict and prevent future emerging diseases. Here, we identify a high incidence of multiple paramyxoviruses in urine samples collected from a closed captive colony of circa 115 straw-coloured fruit bats (Eidolon helvum). The sequences detected have high nucleotide identities with those derived from free ranging African fruit bats and form phylogenetic clusters with the Henipavirus genus, Pararubulavirus genus and other unclassified paramyxoviruses. As this colony had been closed for 5 years prior to this study, these results indicate that within-host paramyxoviral persistence underlies the role of bats as reservoirs of these viruses.

Spatial dynamics of pathogen transmission in communally roosting species: Impacts of changing habitats on bat-virus dynamics.

The spatial organization of populations determines their pathogen dynamics. This is particularly important for communally roosting species, whose aggregations are often driven by the spatial structure of their environment. We develop a spatially explicit model for virus transmission within roosts of Australian tree-dwelling bats (Pteropus spp.), parameterized to reflect Hendra virus. The spatial structure of roosts mirrors three study sites, and viral transmission between groups of bats in trees was modelled as a function of distance between roost trees. Using three levels of tree density to reflect anthropogenic changes in bat habitats, we investigate the potential effects of recent ecological shifts in Australia on the dynamics of zoonotic viruses in reservoir hosts. We show that simulated infection dynamics in spatially structured roosts differ from that of mean-field models for equivalently sized populations, highlighting the importance of spatial structure in disease models of gregarious taxa. Under contrasting scenarios of flying-fox roosting structures, sparse stand structures (with fewer trees but more bats per tree) generate higher probabilities of successful outbreaks, larger and faster epidemics, and shorter virus extinction times, compared to intermediate and dense stand structures with more trees but fewer bats per tree. These observations are consistent with the greater force of infection generated by structured populations with less numerous but larger infected groups, and may flag an increased risk of pathogen spillover from these increasingly abundant roost types. Outputs from our models contribute insights into the spread of viruses in structured animal populations, like communally roosting species, as well as specific insights into Hendra virus infection dynamics and spillover risk in a situation of changing host ecology. These insights will be relevant for modelling other zoonotic viruses in wildlife reservoir hosts in response to habitat modification and changing populations, including coronaviruses like SARS-CoV-2.

Expression of Phosphorylated Signal Transducer and Activator of Transcription 3 and its Prognostic Significance in Canine Anal Sac Adenocarcinoma.

Prognostication in canine anal sac adenocarcinomas (ASACs) is difficult due to conflicting evidence regarding metastatic rates and median survival times (MSTs). The transcription factor signal transducer and activator of transcription 3 (STAT3) is a prognostic predictor in several human cancers. The aim of this retrospective study was to assess STAT3 expression in ASACs and to explore its association with clinical presentation and outcome. We hypothesized that STAT3 expression would distinguish tumours with early versus late metastasis. Records from The Queen's Veterinary School Hospital, Cambridge, UK, were searched for dogs diagnosed with ASAC from 2008 to 2019. Immunohistochemical expression of phosphorylated STAT3 (pSTAT3) was assessed in primary tumours (n = 57) and metastatic lymph nodes (n = 30) and MSTs were calculated for cases with low and high pSTAT3 expression. Of the 57 cases assessed, 27 presented with primary tumours but no metastasis and 30 with both primary and local metastatic disease. Most cases (50/57) expressed nuclear pSTAT3 within neoplastic cells in both primary tumour and metastatic lymph nodes. pSTAT3 expression was predominantly observed in neoplastic cells at the edges of neoplastic lobules, suggesting a potential role in invasion. There was no significant difference in pSTAT3 expression between cases metastatic at presentation and those that did not have detectable metastasis at presentation. There was no significant difference between the MSTs in cases with high and low pSTAT3 expression. Cases that presented with metastatic disease had shorter MSTs (395 days) than those with primary tumours alone (623 days). Although pSTAT3 is variably expressed in primary and metastatic ASAC cells, pSTAT3 did not provide prognostic information for canine ASAC.

An experimental design tool to optimize inference precision in data-driven mathematical models of bacterial infections in vivo.

The management of bacterial diseases calls for a detailed knowledge about the dynamic changes in host-bacteria interactions. Biological insights are gained by integrating experimental data with mechanistic mathematical models to infer experimentally unobservable quantities. This inter-disciplinary field would benefit from experiments with maximal information content yielding high-precision inference. Here, we present a computationally efficient tool for optimizing experimental design in terms of parameter inference in studies using isogenic-tagged strains. We study the effect of three experimental design factors: number of biological replicates, sampling timepoint selection and number of copies per tagged strain. We conduct a simulation study to establish the relationship between our optimality criterion and the size of parameter estimate confidence intervals, and showcase its application in a range of biological scenarios reflecting different dynamics patterns observed in experimental infections. We show that in low-variance systems with low killing and replication rates, predicting high-precision experimental designs is consistently achieved; higher replicate sizes and strategic timepoint selection yield more precise estimates. Finally, we address the question of resource allocation under constraints; given a fixed number of host animals and a constraint on total inoculum size per host, infections with fewer strains at higher copies per strain lead to higher-precision inference.

Key questions for modelling COVID-19 exit strategies.

Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.

A data-based mathematical modelling study to quantify the effects of ciprofloxacin and ampicillin on the within-host dynamics of Salmonella enterica during treatment and relapse.

Antibiotic therapy has drastically reduced the mortality and sequelae of bacterial infections. From naturally occurring to chemically synthesized, different classes of antibiotics have been successfully used without detailed knowledge of how they affect bacterial dynamics in vivo. However, a proportion of patients receiving antimicrobial therapy develop recrudescent infections post-treatment. Relapsing infections are attributable to incomplete clearance of bacterial populations following antibiotic administration; the metabolic profile of this antibiotic-recalcitrant bacterial subpopulation, the spatio-temporal context of its emergence and the variance of antibiotic-bacterial interactions in vivo remain unclear. Here, we develop and apply a mechanistic mathematical model to data from a study comparing the effects of ciprofloxacin and ampicillin on the within-host dynamics of Salmonella enterica serovar Typhimurium in murine infections. Using the inferential capacity of our model, we show that the antibiotic-recalcitrant bacteria following ampicillin, but not ciprofloxacin, treatment belong to a non-replicating phenotype. Aligning with previous studies, we independently estimate that the lymphoid tissues and spleen are important reservoirs of non-replicating bacteria. Finally, we predict that post-treatment, the progenitors of the non-growing and growing bacterial populations replicate and die at different rates. Ultimately, the liver, spleen and mesenteric lymph nodes are all repopulated by progenitors of the previously non-growing phenotype in ampicillin-treated mice.

Within-host spatiotemporal dynamic of systemic salmonellosis: Ways to track infection, reaction to vaccination and antimicrobial treatment.

During the last two decades our understanding of the complex in vivo host-pathogen interactions has increased due to technical improvements and new research tools. The rapid advancement of molecular biology, flow cytometry and microscopy techniques, combined with mathematical modelling, have empowered in-depth studies of systemic bacterial infections across scales from single molecules, to cells, to organs and systems to reach the whole organism level. By tracking subpopulations of bacteria in vivo using molecular or fluorescent tags, it has been possible to reconstruct the spread of infection within and between organs, allowing unprecedented quantification of the effects of antimicrobial treatment and vaccination. This review illustrates recent advances in the study of heterogeneous traits of the infection process and illustrate approaches to investigate the reciprocal interactions between antimicrobial treatments, bacterial growth/death as well as inter- and intra-organ spread. We also discuss how vaccines impact the in vivo behaviour of bacteria and how these findings can guide vaccine design and rational antimicrobial treatment.

Mechanisms of ß-lactam resistance of Streptococcus uberis isolated from bovine mastitis cases.

A number of veterinary clinical pathology laboratories in New Zealand have been reporting emergence of increased minimum in inhibitory concentrations for ß-lactams in the common clinical bovine mastitis pathogen Streptococcus uberis. The objective of this study was to determine the genetic basis of this increase in MIC for ß-lactams amongst S. uberis. Illumina sequencing and determination of oxacillin MIC was performed on 265 clinical isolates. Published sequences of the five penicillin binding proteins pbp1a, pbp1b, pbp2a, pbp2b, and pbp2x were used to identify, extract and align these sequences from the study isolates. Amino acid substitutions resulting from single nucleotide polymorphisms (SNP) within these genes were analysed for associations with elevated (≥ 0.5 mg/L) oxacillin MIC together with a genome wide association study. The population structure of the study isolates was approximated using a phylogenetic tree generated from an alignment of the core genome. A total of 53 % of isolates had MIC ≥ 0.5 mg/L for oxacillin. A total of 101 substitutions within the five pbp were identified, of which 11 were statistically associated with an MIC ≥ 0.5 mg/L. All 140 isolates which exhibited an increased ß-lactam MIC had SNPs leading to pbp2x E381K and Q554E substitutions. The phylogenetic tree indicated that the genotype and phenotype associated with the increased MIC for oxacillin were present in several different lineages suggesting that acquisition of this increased ß-lactam MIC had occurred in multiple geographically distinct regions. Reanalysis of the data from the intervention studies from which the isolates were originally drawn found a tendency for the pbp2x E381K substitution to be associated with lower cure rates. It is concluded that there is geographically and genetically widespread presence of pbp substitutions associated with reduced susceptibility to ß-lactam antimicrobials. Additionally, presence of pbp substitutions tended to be associated with poorer cure rate outcomes following antimicrobial therapy for clinical mastitis.

Preliminary evaluation of a salivary urea test strip method for use in dogs.

BACKGROUND: Salivary urea concentrations correlate with serum urea concentrations in dogs and humans. Salivary urea concentrations can now be determined semi-quantitatively using a salivary urea test strip method that has been validated for use in humans. OBJECTIVES: We aimed to evaluate the repeatability of the salivary urea test strip score, and the correlation between the salivary urea test strip scores and serum urea concentrations in dogs. METHODS: Intra-run and inter-run variabilities were determined (n = 10 in triplicate). Correlations between salivary urea test strip scores and serum urea concentrations in dogs were assessed using the Spearman's correlation coefficient. Receiver operator curve analysis was used to evaluate the diagnostic performance of the salivary urea test strip score to identify dogs with serum urea concentration >7.4 mmol/L (upper limit of laboratory RI). RESULTS: The intra-run repeatability was good (28/30 concordant results) whereas the inter-run repeatability was moderate (23/30 concordant results). Salivary and serum urea concentrations showed a moderately positive correlation (rs  = .63, n = 33; P < .0001). A salivary urea test strip score ≥4 was 57% sensitive and 96% specific for detecting a serum urea concentration >7.4 mmol/L. CONCLUSIONS: Uremia can be detected using salivary urea test strips in dogs. Based on our preliminary data, salivary urea test strip scores of 1 or 2 might exclude clinically relevant uremia in most cases; however, it is recommended that the salivary urea test be repeated in dogs with a test strip score of 3. Dogs with a salivary urea test strip score of ≥4 would likely require additional investigations.