Background:Antimicrobial resistance (AMR) in Candida species is an emerging global health threat. This study aims to document the implementation of standardized surveillance tools from the Global Antimicrobial Resistance and Use Surveillance System (GLASS) and to describe the distribution and antifungal resistance profiles of Candida species in bloodstream infections generated through the study outputs. Methods:The GLASS-Fungi pilot was a multicentre observational demonstration study where twenty-four laboratories were invited to collect and share Candida bloodstream infections (BSIs) data with the World Health Organization (WHO) using a standardized surveillance protocol and WHONET software. Data were collected for patients with laboratory-confirmed Candida bloodstream infections between January 2017 and July 2021. Participating sites were trained to collect, deduplicate, and report clinical and microbiological data. Patient demographic and microbiological data were summarized using descriptive statistics. The percent distribution of Candida species and resistance profiles were analysed with a 95% confidence interval (CI) calculated using robust standard errors clustered at the site level. Participating sites shared experiences with using the standardised GLASS surveillance tools and procedures through structured feedback forms and consultative meetings. This study was not designed to support causal inference or population-level generalization; analyses are descriptive and intended to illustrate outputs generated through pilot surveillance implementation. Findings:Fourteen laboratories from 13 countries contributed data from 3447 patients with candidemia. Overall, Candida albicans was the predominant species (37.6%; 95% CI: 33.8-41.5). C. albicans was most common in the Americas, Europe, and Africa, whereas Candida tropicalis was more prevalent in Southeast Asia. Candida auris was detected by two laboratories in Southeast Asia and Africa. Among isolates with interpretable antifungal susceptibility testing (AFST) results and corresponding established breakpoints, 13.6% (95% CI: 10.1-17.2%) were resistant to at least one antifungal, with fluconazole resistance highest among C. parapsilosis isolates (29.7%; 95% CI: 18.2-41.2). Challenges to scaling up fungal AMR surveillance globally included limited fungal laboratory testing capacity, restricted access to antifungal susceptibility testing, and lack of sustained funding, particularly in low and middle-income countries. Interpretation:The study was a global, multi-centre initiative to systematically collect and report surveillance data on Candida BSIs using standardised data collection tools and reporting procedures. The study identified major training capacity and infrastructure gaps. Addressing those is an essential step for anticipating and responding to emerging invasive fungal infections. Funding:This work was supported by the United States Centers for Disease Control and Prevention.

BACKGROUND:From a public health standpoint, there is merit in determining the levels of Escherichia coli in drinking water, but surveillance datasets often report censored values that may hinder traditional statistical analysis. This study aims to identify sociodemographic factors associated with the presence of E. coli in household drinking water in Bangladesh using Bayesian models for censored data, utilizing data from 6069 households in the Multiple Indicator Cluster Survey 2019. METHODS:In terms of censoring, we considered two different Bayesian regression strategies: Bayesian Tobit Poisson regression and Bayesian Censored Generalized Poisson regression. RESULTS:The Bayesian Censored Generalized Poisson regression model was identified as the optimal model for analyzing household fecal contamination. Regression analysis revealed significant associations between household E. coli levels and various factors including division, livestock ownership, location of water sources, treatment of drinking water, household head education, wealth index, source of drinking water, place of handwashing and toilet facility. Households using tube wells had lower E. coli levels than those using other sources. Furthermore, households using pit latrines had 1.03 times higher contamination levels than those using flush latrines. CONCLUSIONS:Levels of fecal contamination in household water in Bangladesh were alarming. Our findings underscore the need for targeted policy interventions in specific population segments to address household fecal contamination, highlighting the link between sociodemographic and environmental factors with E. coli levels in drinking water.

Escherichia coli (E. coli) is a key indicator of fecal contamination in freshwater and can signal the presence of other harmful bacteria and viruses. The aim of the study is to evaluate the performance of machine learning (ML) tools to detect E. coli in drinking water in Bangladesh using surveillance data under two scenarios: an imbalanced dataset and a balanced dataset. We utilized data from the 2019 Bangladesh Multiple Indicator Cluster Survey, which included a total of 6,069 household drinking water samples. We used agglomerative hierarchical clustering with Ward's linkage to identify district-level hotspots. Extreme Gradient Boosting with SHapley Additive exPlanations values were used for feature selection, and the Synthetic Minority Over-sampling Technique (SMOTE) was used to address class imbalance in the classification task. We applied nine classical ML models in this study: Adaptive Boosting (AdaBoost), Decision Trees (DT), Gradient Boosting Algorithm (GBA), k-Nearest Neighbors (KNN), Light Gradient-Boosting Machine (LightGBM), Logistic Regression (LR), Naïve Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM), along with a Deep Learning Multi-Layer Perceptron (DL-MLP) model to predict the risk of E. coli contamination (REcC) in water. Model performance was evaluated using accuracy, precision, recall, F1 score, Cohen Kappa, area under the curve (AUC), and a violin plot. E. coli contamination in drinking water was detected in 39.2% (95% CI: 37.4-41.2) of households. Bandarban district had the highest REcC. After applying SMOTE and 10-fold cross-validation with hyperparameter tuning, model performance was more consistent across algorithms. In terms of model evaluation, AdaBoost slightly outperformed the others with an accuracy of 81.6%, Cohen kappa statistic of 19.4%, precision of 82.2%, recall of 99%, F1-score of 89.8%, and an AUC of 68.6%. Ensemble model for example AdaBoost and GBA models had ability to accurately classify drinking water samples with respect to the presence of E. coli using surveillance data than others selected model in this study.

Introduction:Colistin is a last-resort antimicrobial used to treat infections caused by multidrug-resistant Gram-negative bacteria in humans. In Indonesia, widespread detection of colistin use and resistance in commensal Escherichia coli from poultry, particularly broilers, led to a national ban on its use in livestock effective since July 1st, 2020. However, the impact of this policy intervention on colistin resistance in both humans and livestock has not yet been evaluated. The COINCIDE study aims to investigate the ban's effect on colistin resistance, compliance, and transmission dynamics of resistance between humans and poultry. Methods and analysis:COINCIDE will: (i) assess phenotypic and genotypic colistin resistance in E. coli from humans and poultry; (ii) estimate transmission of colistin resistant E. coli between humans and animals; (iii) explore colistin and antimicrobial use (AMU) at the community level; (iv) identify social and cultural factors driving AMU; and (v) strengthen multisectoral One Health collaboration. Post-ban sampling will be conducted in three districts of Central Java Province (Klaten, Karanganyar, and Sukoharjo), where pre-ban samples were already available. We will recruit participants from primary healthcare centers (PHC) (n = 683), poultry farmers (n = 120), and visit a total of 60 small-scale layer farms. Broiler isolates (n = 2865) from Indonesia's routine antimicrobial resistance (AMR) surveillance (2018-2023) will also be included. In terms of sample collection, post-ban samples will include rectal swabs from patients visiting PHC and farmers and boot swabs from small-scale layer farms. Colistin resistance will be screened using CHROMagar COL-APSE agar medium and confirmed by broth microdilution. Results of long-read whole-genome sequencing will identify resistance mechanisms and transmission pathways. A qualitative ethnography work will include participant observation and informal conversations during field visits, alongside in-depth interviews with healthcare professionals and stakeholders. "Drug bag" method interviews will assess antimicrobial use, access, and drivers at the community level. Simulated patient visits to pharmacies and local shops (warung or toko obat), and interviews with agrovet outlets and poultry shops will be conducted to evaluate compliance with antimicrobial sales regulations. Conclusion:By integrating microbiological, epidemiological, policy, and social science data, findings from the COINCIDE study will provide a strong scientific basis to inform AMR policies in Indonesia, with potential significance to inform other countries across Southeast Asia.

We analyzed Google Trends data on measles-related searches in Canada from January 1 to May 21, 2025; web, news, and YouTube search trends increased significantly across provinces (all P values were <.05), aligning with rising case numbers. Our findings emphasize the importance of timely, targeted risk communication for enhancing public awareness and responses during this outbreak.

Bovine mastitis, a prevalent disease in dairy farms, exerts a profound negative influence on both the health and productivity of dairy cattle, leading to substantial economic losses for the dairy industry. The disease is associated with different bacterial agents, primarily Gram-positive cocci (e.g., Staphylococcus spp., Streptococcus spp.) and Gram-negative bacilli (e.g., Escherichia coli, Klebsiella pneumoniae). These pathogens induce mastitis through diverse mechanisms, intricately linked to the virulence factors they carry. Despite previous research on the virulence factors of mastitis-causing bacteria in dairy cattle, there remains a significant gap in our comprehensive understanding of these factors. To bridge these gaps, this manuscript reviews and compiles research on the virulence factors of these pathogens, focusing on their roles in mammary tissue infection, immune evasion, adherence to mammary epithelial cells, and invasion and colonization of the mammary gland. These processes are analyzed in depth to provide a comprehensive framework to promote a deeper understanding of dairy pathogenic bacteria and their pathogenic mechanisms and to provide new insights into the control of mastitis in dairy cattle.

SUMMARY Numerous questions persist regarding the role of companion animals as potential reservoirs of antimicrobial-resistant organisms that can infect humans. While relative antimicrobial usage in companion animals is lower than that in humans, certain antimicrobial-resistant pathogens have comparable colonization rates in companion animals and their human counterparts, which inevitably raises questions regarding potential antimicrobial resistance (AMR) transmission. Furthermore, the close contact between pets and their owners, as well as pets, veterinary professionals, and the veterinary clinic environment, provides ample opportunity for zoonotic transmission of antimicrobial-resistant pathogens. Here we summarize what is known about the transmission of AMR and select antimicrobial-resistant organisms between companion animals (primarily dogs, cats, and horses) and humans. We also describe the global distribution of selected antimicrobial-resistant organisms in companion animals. The impact of interspecies AMR transmission within households and veterinary care settings is critically reviewed and discussed in the context of methicillin-resistant staphylococci, extended-spectrum β-lactamase and carbapenemase-producing bacteria. Key research areas are emphasized within established global action plans on AMR, offering valuable insights for shaping future research and surveillance initiatives.

Klebsiella spp. infections are an important cause of severe clinical mastitis and recurrent infections, resulting in a poor response to antimicrobial agents and causing substantial economic impacts on the dairy industry. Therefore, investigating underlying causes of Klebsiella spp. infections is essential. Here, we used high-throughput DNA sequencing to characterize the milk microbiota of healthy dairy cows (HDCs) and cows with a history of recurrent Klebsiella mastitis (KLB). Our goal was to identify potential pathogenic genera associated with recurrent Klebsiella infections in cows. Relative abundances of Firmicutes and Faecalibacterium were greater in the KLB group than in the HDC group. In contrast, Proteobacteria and Labrenzia were less abundant than they were in the HDC group. Although species distributions differed between groups, diversity and abundance of communities were comparable. Notably, genera enriched in the KLB group were mostly associated with the intestine, which suggests that cows in the KLB group resided in a contaminated environment or had increased teat-end exposure to fecal bacteria. There were no major differences in microbiota among quarters or between foremilk and milk collected after foremilking. Conversely, the milk of heifers had increased alpha diversity compared to the milk of multiparous cows.

Abstract Background Hospitals represent ideal locations for developing wastewater (WW) surveillance for antibiotics (Abx), owing to the high frequency of Abx use and robust record-keeping. To investigate this technology as a potentially useful stewardship tool, we compared the concentration of several Abx in WW from tertiary care hospitals to their corresponding levels in the surrounding municipality. Concentration of 4 common antimicrobials found in hospital wastewater effluent over a 4-month period Concentrations of 4 antimicrobials measured in WW from 3 tertiary care hospitals and the corresponding wastewater treatment plant (WWTP) in the same city. Displayed statistics represent the results of a Wilcoxon test, antimicrobials labelled “*” are commonly administered intravenously. Methods WW was collected bi-weekly from three tertiary care hospitals (two adult and one pediatric, with 600, 650 and 135 inpatient beds, respectively) and the associated municipal WW treatment plant (serving a population of ∼1,000,000) between February and May of 2024. Aliquots of WW were filtered and run directly on a liquid-chromatography paired triple quadrupole mass spectrometer (LC-QQQ) to quantify specific Abx (azithromycin, doxycycline, ciprofloxacin, levofloxacin, metronidazole, cefazolin, ceftriaxone, piperacillin, tazobactam, meropenem, vancomycin, and sulfamethoxazole). Spiked and replicate samples were randomly included to validate analyte recovery and reproducibility. Agilent MassHunter software (Version 10.1, 2019) was utilized to process and export raw data to R. Box plots and Wilcoxon tests were utilized to compare the concentration of each Abx. Results Validation experiments confirmed that filtering WW samples and directly running them on LC-QQQ yields reproducible and reliable results. Serial monitoring revealed that WW from hospitals generally exhibited a broader range of Abx concentrations than was observed city-wide (Figure 1). This variability was particularly evident among the most used Abx, consistent with the changing treatment needs of highly dynamic hospital populations. In addition to this, ceftriaxone, an IV-administered antimicrobial was found at significantly higher concentrations in all hospital sites when compared to the municipal WW treatment plant. Conclusion Validating Abx monitoring in WW from a range of scales will enable this approach to be applied across diverse environments as a tool to mitigate Abx resistance. This approach will be strengthened as it is integrated with clinical metadata and metagenomic assessment of antimicrobial resistance genes from the same samples. Disclosures All Authors: No reported disclosures

Non-aureus staphylococci (NAS) are an essential group of bacteria causing antimicrobial resistant intramammary infections in livestock, particularly dairy cows. Therefore, bacteriophages emerge as a potent bactericidal agent for NAS mastitis. This study aimed to obtain NAS-specific bacteriophages using bacterial strains isolated from cows with mastitis, subsequently evaluating their morphological, genomic, and lytic characteristics. Four distinct NAS bacteriophages were recovered from sewage or the environment of Chinese dairy farms; PT1-1, PT94, and PT1-9 were isolated using Staphylococcus chromogenes and PT1-4 using Staphylococcus gallinarum. Both PT1-1 (24/54, 44%) and PT94 (28/54, 52%) had broader lysis than PT1-4 (3/54, 6%) and PT1-9 (10/54, 19%), but PT1-4 and PT1-9 achieved cross-species lysis. All bacteriophages had a short latency period and good environmental tolerance, including surviving at pH=4-10 and at 30-60℃. Except for PT1-9, all bacteriophages had excellent bactericidal efficacy within 5h of co-culture with host bacteria in vitro at various multiplicity of infection (MOIs). Based on whole genome sequencing, average nucleotide identity (ANI) analysis of PT1-1 and PT94 can be classified as the same species, consistent with whole-genome synteny analysis. Although motifs shared by the 4 bacteriophages differed little from those of other bacteriophages, a phylogenetic tree based on functional proteins indicated their novelty. Moreover, based on whole genome comparisons, we inferred that cross-species lysis of bacteriophage may be related to the presence of “phage tail fiber.” In conclusion 4 novel NAS bacteriophages were isolated; they had good biological properties and unique genomes, with potential for NAS mastitis therapy.

Conventional Mycoplasma spp. diagnostics involve culture, often considered the gold standard in diagnostic test evaluation. However, culture protocols lack empirical derivation and primarily adhere to National Mastitis Council recommendations, tracing back to initial cultivation of Mycoplasma bovis. Despite a wide range of carbon dioxide (CO2) supplementation reported in literature, specific impacts of CO2 on Mycoplasma spp. growth remain unexplored. Our objective was to assess the effect of CO2 concentration on growth detection rates of 24 Mycoplasma spp. isolates from dairy cows. These isolates, mainly M. bovis, were incubated at 37°C in triplicate and three dilution ranges under three CO2 conditions: ambient air or 5% CO2 or 10% CO2. Bacterial growth was evaluated on incubation days 3, 5, 7, and 10. When cultured using ambient air, log10 cfu/mL was lower on days 3, 5, and 7 of incubation compared with isolates incubated in the recommended 5% or 10% CO2, with less variation observed in ambient air compared with 5% or 10% CO2. However, by 10 days of incubation, no differences in the detection of observable growth were noted among isolates incubated in ambient air, 5% CO2, or 10% CO2. Consequently, Mycoplasma spp. isolated from dairy cattle demonstrated growth after the recommended 7-10 days of culture, even in the absence of supplemental CO2. Given the expected concentration of M. bovis in (sub)clinical samples had similar concentrations to those used in our study, with the majority of isolates being M. bovis, we recommend expanding CO2 concentration ranges in M. bovis culture from 10% CO2 to ambient air when incubating for 10 days. However, the turnaround time could be shortened when incubating with supplemental CO2. IMPORTANCE:Current Mycoplasma spp. culture protocols lack empirical derivation concerning carbon dioxide (CO2) supplementation and are primarily based on the initial cultivation of Mycoplasma bovis. This study indicates that the suitable range for CO2 supplementation is broader than what is currently recommended by the National Mastitis Council for culturing within the specified 7-10 days. No differences in bacterial growth detection rates were observed among ambient air, 5% CO2, or 10% CO2 supplementation during the 7- and 10-day incubation intervals. These new insights provide evidence supporting the possibility of culturing Mycoplasma spp. under ambient air conditions in a laboratory setting.

Using on-farm microbiological culture (OFC), based on chromogenic culture media, enables the identification of mastitis causing pathogens in about 24 h, allows rapid decision making on selective treatment and control management measures of cows with clinical mastitis (CM). However, accurate interpretation of OFC results requires trained and experienced operators, which could be a limitation for the use of OFC in dairy farms. Our hypothesis was that AI-based automated plate reading mobile application can analyze images of microorganisms’ colonies in chromogenic culture media with similar diagnostic performance as a trained specialist evaluator. Therefore, the aim of the present study was to evaluate the diagnostic accuracy of an AI-based application (Rumi; OnFarm, Piracicaba, São Paulo, Brazil) for interpreting images of mastitis causing microorganism colonies grown in chromogenic culture media. For this study two trials were organized to compare the results obtained using an AI-based application Rumi with the interpretation of: (1) a trained specialist, using MALDI-TOF MS as the gold standard; (2) farm personnel users (FPU). In trial 1, a total of 476 CM milk samples, from 11 farms located in São Paulo (n = 7) and Minas Gerais (n = 4), southeast Brazil, were inoculated in chromogenic culture media plates (Smartcolor 2, OnFarm, Piracicaba, São Paulo, Brazil) by specialists under lab conditions, and digital images were recorded 24 h after incubation at 37 °C. After that, all the 476 digital images were analyzed by the Rumi and by another specialist (who only had access to the digital images) and the diagnostic accuracy indicators sensitivity (Se) and specificity (Sp) were calculated using MALDI-TOF MS microbiological identification of the isolates as the reference. In Trial 2, a total of 208 CM milk samples, from 150 farms from Brazil, were inoculated in chromogenic culture media plates by FPU, and the results of microbiological growth were visually interpreted by FPU under on-farm conditions. After visual interpretation, results were recorded using an OnFarmApp application (herd manage application for mastitis by OnFarm, Piracicaba, São Paulo, Brazil), and the images of the chromogenic culture plates were captured by the OnFarmApp to be evaluated by Rumi and Bayesian Latent Class Models were performed to compare Rumi and the FPU. In Trial 1, Rumi presented high and intermediate accuracy results, with the only exception of the low Enterococcus spp.’s Se. In comparison with the specialist, Rumi performed similarly in Se and Sp for most groups of pathogens, with the only exception of non-aureus staphylococci where Se results were lower. Both Rumi and the specialist achieved Sp results > 0.96. In Trial 2, Rumi had similar results as the FPU in the Bayesian Latent Class Model analysis. In conclusion, the use of the AI-based automated plate reading mobile application can be an alternative for visual interpretation of OFC results, simplifying the procedures for selective treatment decisions for CM based on OFC.

We investigated the prevalence and spatial distribution of selected pathogens associated with infectious diseases of dairy cattle in Ontario, Canada. The cross-sectional study surveyed bulk tank milk for antibodies against bovine leukemia virus (BLV), Mycobacterium avium ssp. paratuberculosis (MAP), and Salmonella Dublin, and for the presence of mastitis pathogens (Staphylococcus aureus, Streptococcus agalactiae, Mycoplasma bovis). Between October 2021 and June 2022, bulk tank milk samples were obtained from every commercial dairy farm in Ontario (n = 3,286). Samples underwent ELISA testing for the presence of BLV, MAP, and S. Dublin antibodies, and quantitative PCR testing for the detection of specific antigens of pathogens associated with mastitis. Bayesian models were used to estimate prevalence, and spatial analysis was carried out to identify regional clusters of high pathogen prevalence. Prevalence varied for different pathogens, and BLV was widespread across dairy farms in Ontario, with an estimated prevalence of 88.3%. The prevalence of MAP, Staph. aureus and S. Dublin in Ontario dairy herds was 39.8%, 31.5%, and 5.1%, respectively. The vast majority of dairy herds in Ontario were free of intramammary infections caused by Strep. agalactiae and M. bovis. Clusters of increased positive test rates were detected for S. Dublin, MAP, and Staph. aureus, indicating potential geographic risk factors for pathogen transmission. For S. Dublin, an area of increased test positivity rates was detected in southwestern Ontario, close to the Canada-United States border where most of the dairy herds in Ontario are located. Conversely, a localized cluster of positive test outcomes involving 14 subdivisions located in the southeastern region of Ontario was detected for Staph. aureus. Findings from our survey highlight the importance of the testing of aggregated samples and conducting spatial analysis as part of disease surveillance programs, and for implementing risk-based trading approaches among dairy producers.

Background: In China’s expanding dairy industry, a lack of oversight regarding antimicrobial use and increasing antimicrobial resistance are evident. Selective treatments of dairy cows for clinical mastitis or dry cow therapy are proposed to promote judicious antimicrobial use without adversely impacting cattle health. These approaches have been successfully implemented on farms in other countries. Methods: On 28 October 2023, a 2-day in-person seminar was held in Beijing, China, on selective antimicrobial treatments of dairy cows for clinical mastitis or dry cow therapy on large Chinese dairy farms. Concurrently, a qualitative study involving 15 technical managers from the 13 largest Chinese dairy groups used focus group discussions and questionnaires to explore perspectives on selective treatments of dairy cows for clinical mastitis or dry cow therapy. The main outcomes assessed were opinions and concerns regarding implementing selective antimicrobial treatments. Results: Although there was diversity of cognition on AMR and selective treatments, the technical managers were generally positive regarding adoption of selective treatments. However, they expressed a need for more evidence and tools, including anticipated economic impacts, effects of delaying treatment until diagnosis, accurate interpretation of milk recording data, safe use of internal teat sealants, and spread of pathogens. Participants stressed the need for awareness, staff training, farm management, and China-specific standards, suggesting large-scale trials to assess efficacy of selective treatments. Conclusion: The findings revealed key challenges and barriers currently impeding selective AMU practices. These insights could inform efforts to promote judicious AMU on farms through targeted treatment regimens, reducing mounting selective pressure driving resistance.

IntroductionBovine mastitis caused by Escherichia coli compromises animal health and inflicts substantial product losses in dairy farming. It may manifest as subclinical through severe acute disease and can be transient or persistent in nature. Little is known about bacterial factors that impact clinical outcomes or allow some strains to outcompete others in the mammary gland (MG) environment. Mastitis-associated E. coli (MAEC) may have distinctive characteristics which may contribute to the varied nature of the disease. Given their high levels of intraspecies genetic variability, virulence factors of commonly used MAEC model strains may not be relevant to all members of this group.MethodsIn this study, we sequenced the genomes of 96 MAEC strains isolated from cattle with clinical mastitis (CM). We utilized clinical severity data to perform genome-wide association studies to identify accessory genes associated with strains isolated from mild or severe CM, or with high or low competitive fitness during in vivo competition assays. Genes associated with mastitis pathogens or commensal strains isolated from bovine sources were also identified.ResultsA type-2 secretion system (T2SS) and a chitinase (ChiA) exported by this system were strongly associated with pathogenic isolates compared with commensal strains. Deletion of chiA from MAEC isolates decreased their adherence to cultured bovine mammary epithelial cells.DiscussionThe increased fitness associated with strains possessing this gene may be due to better attachment in the MG. Overall, these results provide a much richer understanding of MAEC and suggest bacterial processes that may underlie the clinical diversity associated with mastitis and their adaptation to this unique environment.

Population-based surveillance was undertaken to determine clinical factors, susceptibility patterns, and incidence rates (IR) of Pseudomonas aeruginosa causing bloodstream infections (BSIs) in a Canadian region (2010–2018). We combined clinical data with genomics to characterize P. aeruginosa (BSIs) (n = 167) in a well-defined Canadian (Calgary) human population over a 9-year period (2010–2018). The annual population IR per 100,000 patient years increased from 3.4/100,000 in 2010 to 5.9/100,000 in 2018, with the highest IRs in elderly males from the hospital setting. Over a quarter of patients presented with febrile neutropenia, followed by urinary tract infections and pneumonia. Antimicrobial resistance (AMR) rates and determinants were rare. The P. aeruginosa population was polyclonal consisting of three dominant sequence types (STs), namely ST244, ST111, and ST17. Antimicrobial-susceptible ST244 was the most common clone and belonged to three clades (A, B, C). The ST244 IR/100,000 increased over time due to the expansion of clade C. Multidrug-resistant ST111 was the second most common clone and IR/100,000 decreased over time. ST111 belonged to three clades (A, B, C) with clade C containing blaVIM-2. Different serotypes were linked to various STs. The IR/100,000 of P. aeruginosa that belonged to serotypes O6 increased significantly over time. An effective multivalent vaccine consisting of five serotypes (O1, O3, O5, O6, O11) would confer protection to > 70

Antimicrobial resistance (AMR) poses an imminent threat to global public health, driven in part by the widespread use of antimicrobials in both humans and animals. Within the dairy cattle industry, Gram-negative coliforms such as Escherichia coli and Klebsiella pneumoniae stand out as major causative agents of clinical mastitis. These same bacterial species are frequently associated with severe infections in humans, including bloodstream and urinary tract infections, and contribute significantly to the alarming surge in antimicrobial-resistant bacterial infections worldwide. Additionally, mastitis-causing coliforms often carry AMR genes akin to those found in hospital-acquired strains, notably the extended-spectrum beta-lactamase genes. This raises concerns regarding the potential transmission of resistant bacteria and AMR from mastitis cases in dairy cattle to humans. In this narrative review, we explore the distinctive characteristics of antimicrobial-resistant E. coli and Klebsiella spp. strains implicated in clinical mastitis and human infections. We focus on the molecular mechanisms underlying AMR in these bacterial populations and critically evaluate the potential for interspecies transmission. Despite some degree of similarity observed in sequence types and mobile genetic elements between strains found in humans and cows, the existing literature does not provide conclusive evidence to assert that coliforms responsible for mastitis in cows pose a direct threat to human health. Finally, we also scrutinize the existing literature, identifying gaps and limitations, and propose avenues for future research to address these pressing challenges comprehensively.

Testing of bulk milk (BM) samples is a convenient, cost-effective strategy that can easily be implemented as part of disease surveillance programs on dairy farms. Here, we performed a scoping review to summarize the literature reporting on the testing of BM samples to detect infectious diseases of dairy cattle caused by bacteria. We also provide a non-exhaustive, albeit significant, list of diagnostic tests that are marketed for BM samples, as well as a list of disease surveillance activities that included testing of BM samples. A literature search was carried out in 5 databases, yielding 8,829 records from which 474 were retained. Overall, 575 eligible bacterial pathogens were screened for using BM samples, ranging from 1 to 6 individual pathogens per study. Staphylococcus aureus, including methicillin-resistant Staph. aureus, were the most studied bacteria (n = 179 studies), followed by Streptococcus agalactiae (86), Mycobacterium avium ssp. paratuberculosis (79), Coxiella burnetii (79), and Mycoplasma spp. (67). Overall, culture-based protocols, ELISA, real-time PCR, and PCR were the most commonly adopted methodologies to screen BM samples. Sensitivity of BM testing for bovine paratuberculosis was generally low and varied greatly according to the ELISA cut-offs adopted and herd-level definition of disease. In general, protocols had low to moderate sensitivities (<50%), which increased for herds with high within-herd seroprevalence. Specificity of BM testing for paratuberculosis was generally high. With respect to mastitis pathogens, BM testing demonstrated high sensitivity and specificity for Strep. agalactiae, in general. However, we observed inconsistency among studies with respect to the sensitivity of BM culture to detect infected herds, which was notably higher if enrolled herds were heavily infected or had history of clinical disease. Among Salmonella spp. pathogens, Salmonella Dublin was the most frequently studied bacterium for which BM testing has been validated. Specificity of BM ELISA was high, ranging from 89.0 to 99.4. In contrast, sensitivity varied greatly among studies, ranging from 50.6% to 100%. Our findings support that one of most important factors affecting sensitivity of BM ELISA for Salmonella Dublin is whether nonlactating cattle are considered in the definition of herd infection status. In general, protocols analyzed in this review suffered from very low sensitivities, which hardly justifies their use as part of disease surveillance as single testing. Nevertheless, test sensitivity can be increased by the adoption of more inclusive definitions of disease-free herds. Further, low-sensitivity and high-specificity methods can be valuable tools for surveillance when used repeatedly over time.

In this scoping review, we characterized the literature reporting on the testing of bulk milk samples to detect microorganisms other than bacteria that can cause diseases in dairy cattle, including viruses, helminths, algae, and protozoa. A search strategy was completed by screening databases, conference proceedings, animal health agency websites, disease surveillance program websites, and handbooks of cattle-related diagnostic tests for potentially relevant articles. Two reviewers independently screened articles in English, Portuguese, or Spanish; original studies reporting on the testing of farm-level, unprocessed bulk milk samples for pres-ence of pathogens or specific antibodies against agents other than bacteria that can cause diseases in cows were retained. From all studies, we used spreadsheets to extract relevant information, including pathogen screened, test used, and country of origin of bulk milk samples. Additionally, for studies reporting sufficient data to estimate test characteristics, we extracted detailed information about herd eligibility, testing protocol, and herd-level infection definition. A total of 8,829 records were identified, from which 1,592 were retained and assessed for eligibility, and 306 were in-cluded. Bovine viral diarrhea virus, Fasciola hepatica, Ostertagia ostertagi, and bovine herpesvirus 1 were the most frequently screened agents, reported from 107, 45, 45, and 33 studies, respectively. Sensitivity of bulk milk ELISA to detect herds with animals infected by bovine herpesvirus 1 ranged from 2 to 100%, and was affected mostly by antigen selection, cut-off adopted, herd vaccination status, and seroprevalence of lactating cows. Bulk milk ELISA had very high specificity to detect herds free of bovine leukemia virus, and varying sensitivity to detect herds with infected animals, which depended on the within-herd seroprevalence of lactat-ing cattle. As for bovine viral diarrhea virus, in general, the sensitivity of bulk milk ELISA was moderate tohigh (>80%) when infection status was defined based on presence of persistently infected cattle or a high pro-portion of seropositive lactating cattle. Nevertheless, bulk milk ELISA was not able to distinguish infected and noninfected herds based on presence of seropositive unvaccinated weanlings. The PCR or quantitative PCR protocols employed had very low sensitivities (<40%) and very high specificities (>95%) to classify bovine viral diarrhea virus infection status of dairy herds. Sensitivity and specificity of bulk milk ELISA to clas-sify herds with regards to presence of F. hepatica- or O. ostertagi-parasitized cattle were generally high and driven mostly by the definition of herd infection status. Conversely, bulk milk ELISA demonstrated varying characteristics to detect herds with or without Dictyo-caulus viviparus-parasitized cattle, depending primar-ily on the antigen selected and presence of cattle with clinical signs of lungworm infection.

Klebsiella pneumoniae can cause severe clinical mastitis in dairy cows, with K. pneumoniae type K57 (K57-KP) being the most common capsular serotype. To identify virulence factors and antimicrobial-resistance (AMR) genes of K57-KP with varying virulence, Galleria mellonella (greater wax moth) larvae were infected as a screening model to characterize virulence of 90 K57-KP strains, with 10 and 11 strains defined as virulent or attenuated, respectively, based on larval survival rates. Next, virulence of these 21 isolates was subsequently confirmed in adhesion and lactate dehydrogenase release assays, using bovine mammary epithelial cells cultured in vitro. Finally, genes associated with virulence and AMR were characterize with whole-genome sequencing. These 21 K57-KP strains were designated into 16 sequence types based on multi-locus sequence typing and allocated in phylogenetic analysis based on single nucleotide polymorphisms. We found great genetic diversity among isolates. In addition, adhesion-associated genes (e.g., fimA, sfaA, and focA) aminoglycoside-resistance genes (aph(6)-Id, strAB) were associated with virulence. This study provided new knowledge regarding virulence of K57-KP associated with bovine mastitis, which may inform development of novel diagnostic tools and prevention strategies for bovine mastitis.