Background/Objectives: Infections in dogs caused by methicillin-resistant staphylococci (MRS) present limited treatment options. This study’s objective was to investigate the molecular epidemiology of Staphylococcus spp. cultured exclusively from clinical canine skin and ear samples in Queensland, Australia, using whole-genome sequencing (WGS). Methods: Forty-two Staphylococcus spp. isolated from clinical canine skin and ear samples, from an unknown number of dogs, were sourced from two veterinary diagnostic laboratories between January 2022 and May 2023. These isolates underwent matrix-assisted laser desorption ionisation– time of flight bacterial identification, minimum inhibitory concentration testing using Sensititre^TM plates and WGS. Phylogenetic trees and core genome multilocus sequence typing (cgMLST) minimum spanning trees (MSTs) were constructed. Results: The isolates included methicillin-resistant and -sensitive S. pseudintermedius (MRSP: 57.1%, 24/42; and MSSP: 19.1%, 8/42), methicillin-resistant and -sensitive S. coagulans (MRSC: 14.3%, 6/42; and MSSC: 2.4%, 1/42) and methicillin-resistant coagulase-negative staphylococci (MR-CoNS: 7.1%, 3/42). Thirty-nine isolates were included after WGS, where all MRS harboured the mecA gene. Eighteen sequence types (STs) were identified, including three novel MRSP and six novel MSSP STs. MRSP ST496-V-VII (23%; 9/39) and MRSP ST749-IV-(IVg) (12.8%; 5/39) were commonly isolated. Phylogenetic analysis of single nucleotide polymorphisms showed that MRSP, MRSC and MSSC were similar to globally isolated staphylococci from canine skin and ear infections. Using cgMLST MSTs, MRSP isolates were not closely related to global strains. Conclusions: Our findings revealed a genotypically diverse geographical distribution and phylogenetic relatedness of staphylococci cultured from clinical canine skin and ear samples across Queensland. This highlights the importance of ongoing surveillance to aid in evidence-based treatment decisions and antimicrobial stewardship.

This study aimed to identify the pathogens isolated from the milk of cows with clinical mastitis in the subtropical region of Australia and to determine the antimicrobial susceptibility of these bacteria. Thirty dairy herds in the subtropical dairy region were asked to submit milk samples for the first 5 cases of clinical mastitis each month for 12 mo. Samples underwent aerobic culture, and isolates were identified via MALDI-TOF mass spectrometry. Antimicrobial susceptibility was determined for Escherichia coli, Enterococcus spp., Streptococcus agalactiae, Streptococcus uberis, Streptococcus dysgalactiae, Staphylococcus aureus, and non-aureus staphylococci and mammaliicocci (NASM). Between March 2021 and July 2022, 1,230 milk samples were collected. A positive culture result was recorded for 812 (66%) of the milk samples; from these samples, 909 isolates were obtained, including 49 isolates where no identification was possible. The remaining samples were classified as having no growth (16.8%) or as being contaminated (17.2%). The most common isolates with a MALDI-TOF diagnosis (n = 909) were Strep. uberis (23.6%), followed by the NASM group (15.0%). Farms enrolled in the study were in 3 distinct locations within the subtropical dairy region: North Queensland, Southeast Queensland, and Northern New South Wales. Some variation in isolate prevalence occurred between these 3 locations. We found lower odds of a sample being positive for E. coli in North Queensland (odds ratio [OR]: 0.25; 95% confidence interval [CI]: 0.07-0.87) and higher odds in Southeast Queensland (OR: 4.01; 95% CI: 1.96-8.20) compared with the reference, Northern New South Wales. We further found higher odds of Strep. dysgalactiae in North Queensland (OR: 5.69; 95% CI: 1.85-17.54) and Southeast Queensland compared with Northern New South Wales (OR: 3.99; 95% CI: 1.73-9.22). Although some seasonal patterns were observed, season was not significant for any of the analyzed isolates. Farm-level differences in pathogen profiles were obvious. Overall, clinical mastitis pathogens had low levels of resistance to the antimicrobials tested. This research demonstrates that Strep. uberis and the NASM bacterial group are the most common pathogens causing clinical mastitis in the subtropical dairy region. It highlights the importance of understanding pathogenic causes of mastitis at the farm and regional level for targeted control and therapy.

A 5-year retrospective study was conducted to describe the mastitis-causing organisms isolated from bovine milk samples submitted to four veterinary diagnostic laboratories in Australia. The aim of this study was to identify temporal, geographical, and seasonal patterns of occurrence for the organisms and report the in vitro susceptibility of the most common mastitis-causing pathogens. In total, 22,102 milk samples were submitted between 2015 and 2019. The results were reported as positive growth for at least one significant organism (n = 11,407; 51.6%), no growth (n = 5,782; 26.2%), and mixed/contaminated growth (n = 4,913; 22.2%). Culture results for no growth, gram-negative bacteria, and eukaryotic organisms were combined for each region, and they were accounted for between 23 and 46% of submissions. These results represent a subset of mastitis cases for which the antibiotic treatment may not be warranted. A total of 11,907 isolates were cultured from 11,407 milk samples. The most common isolated organisms were Streptococcus uberis [41.3%; 95% confidence interval (CI): 40.4–42.1%] and Staphylococcus aureus (23.6%; 95% CI: 22.8–24.3%). For S. uberis and S. aureus, there was an association between a positive culture result and the dairy region. All regions except for the Sub-tropical Dairy region were more likely to culture S. uberis compared to the reference, Dairy NSW (P < 0.001). Similarly, for S. aureus, a positive culture result was more likely in all other dairy regions compared to Dairy NSW (P < 0.001). The LISA cluster analysis identified differences between High-High (hotspot) postcodes for S. aureus and S. uberis throughout all the analyzed dairy regions. These results highlight the need for further investigations into specific risk factors, such as environmental factors and herd-level predictors, which may have influenced the observed regional variations. Common mastitis-causing pathogens showed overall good susceptibility to a range of antimicrobials used in the treatment of mastitis. On-going surveillance of mastitis-causing pathogens and their antimicrobial susceptibilities will facilitate targeted mastitis control and treatment programs.

While the effects of cleaning and disinfection practices on the reduction of environmental nosocomial bacteria are well-established in human and large animal veterinary hospitals, how animal movements within animal health care facilities influence environmental bacterial recovery is poorly understood. During three consecutive weeks, 155 electrostatic wipes were collected from the environment pre- and post-cleaning only or following disinfection from seven target locations within an animal shelter. All samples were cultured, and isolates were identified using a matrix-assisted laser desorption ionization—time of flight mass spectrometry. Social network analysis of animal movements during the sampling period was performed to estimate the level of connectivity of the seven target locations. The relationship between bacterial levels and connectivity estimates of the target locations were investigated using a negative binomial regression model with a random effect of sampling areas. Overall, our results indicate a significant reduction in the total bacterial contamination with disinfection when compared to cleaning only [Coefficient (Coef.) = −1.72, 95% Confidence Interval (CI) = −3.09, −0.34, P = 0.015]. Higher total bacterial contamination was significantly more likely in sampled areas with less animal movement connectivity (Coef. = −0.32, 95% CI = −0.49, −0.15, P ≤ 0.001). Pseudomonas aeruginosa and ampicillin resistant Enterobacteriaceae (Escherichia coli, Enterobacter spp. and Klebsiella spp.) were present in the animal holdings and in the shelters' veterinary clinic environment at all sampling times. Our findings demonstrate that cleaning followed by disinfection practices are effective at reducing environmental bacterial levels. Areas with less animal connectivity are more likely to have a higher bacterial contamination. These areas could represent environmental reservoirs for bacterial infection and should be targeted with effective cleaning and disinfection protocols.

Gut bacterial communities play a vital role in a host's digestion and fermentation of complex carbohydrates, absorption of nutrients, and energy harvest/storage. Dugongs are obligate seagrass grazers with an expanded hindgut and associated microbiome. Here, we characterised and compared the faecal bacterial communities of dugongs from genetically distinct populations along the east coast of Australia, between subtropical Moreton Bay and tropical Cleveland Bay. Amplicon sequencing of fresh dugong faecal samples (n=47) revealed Firmicutes (62%) dominating the faecal bacterial communities across all populations. Several bacterial genera (Bacteroides, Clostridium sensu stricto 1, Blautia and Polaribacter) were detected in samples from all locations, suggesting their importance in seagrass digestion. Principal coordinate analysis showed the three southern-most dugong populations having different faecal bacterial community compositions from northern populations. The relative abundances of the genera Clostridium sensu stricto 13 and dgA-11 gut group were higher, but Bacteroides was lower, in the southern dugong populations, compared to the northern populations, suggesting potential adaptive changes associated with location. This study contributes to our knowledge of the faecal bacterial communities of dugongs inhabiting Australian coastal waters. Future studies of diet selection in relation to seagrass availability throughout the dugong's range will help to advance our understanding of the roles that seagrass species may play in affecting the dugong's faecal bacterial community composition.

Mastitis, a prevalent and economically important disease in the dairy industry, poses substantial challenges to dairy cow health, milk quality, and farm profitability worldwide. Mastitis is predominantly caused by bacterial infections. The objective of this study was to estimate the sensitivity (Se) and specificity (Sp) of bacterial culture and the VetMAXTM MastiType Multi Kit PCR in identified clinical mastitis pathogens. A total of 396 quarter-level milk samples were collected from 396 cows with clinical mastitis on 29 farms in the subtropical dairy region of Australia between March and December 2021. These samples were cultured and tested by PCR, and analysed using Bayesian latent class analysis under the assumption of one population two tests and also of three populations two tests, by dividing the population into subpopulations based on regions. Informative priors used in the analysis were calculated from published evidence. Models were compared using the Deviance Information Criterion (DIC). Sensitivity analysis was performed to evaluate the impact of changes in priors. The most common isolates cultured and detected by PCR were Streptococcus uberis (17.4% and 27.3%, respectively) and Escherichia coli (12.6% and 25.0%, respectively). Under the assumption of one population two tests, the Se of PCR (at cycle threshold (Ct) <= 37) was higher than that of bacterial culture for both pathogens: for E. coli, the Se was 50.2 % (95% posterior probability interval (PPI): 37.4; 74.1) for bacterial culture, and 93.7% (95% PPI: 85.5; 98.4) for PCR. For S. uberis, the Se was 50.4% (95% PPI: 40.9; 61.3) for bacterial culture, and 81.5% (73.0; 88.9) for PCR. Conversely, the Sp of bacterial culture was higher than that of PCR for both pathogens: for E. coli, the Sp was 99.2% (97.8; 100) for bacterial culture, and 95.1 % (87.8; 99.4) for PCR. For S. uberis, the Sp was 99.2% (95% PPI: 97.6; 100) for bacterial culture, and 96.7% (95% PPI: 92.1; 99.2) for PCR. Bayesian latent class analysis with three populations two tests was only performed for S. uberis. For E. coli, this could not be performed because there were no PCR-positive results in one subpopulation. Under the assumption of three populations two tests, for S. uberis, the Se was 49.6% (40.6; 59.4) for bacterial culture, and 81.1% (72.6; 88.6) for PCR; and the Sp for bacterial culture was 99.1 % (97.7; 100), and for PCR was 96.9% (93.0; 99.3). The DIC for the one population two tests model was lower than the DIC for the three populations two tests model. The sensitivity analysis for the one population two tests model demonstrated that a 10% reduction in priors led to substantial changes in Se of both bacterial culture and PCR tests for E. coli and S. uberis, with overlap percentages ranging from 80.6% to 92.2%. In contrast, the Sp of bacterial culture and PCR tests remained relatively stable despite changes in priors, except for the Sp of PCR test for E. coli. In summary, the VetMAXTM MastiType Multi Kit demonstrated higher Se compared to bacterial culture, suggesting its potential as a routine test for identifying mastitis pathogens in milk samples from cows with clinical mastitis. While the bacterial culture method offered higher Sp in pathogen detection; results obtained following bacterial culture and subsequent susceptibility testing remain valuable, particularly in guiding antimicrobial treatment for mastitis.