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ABSTRACT: To support antimicrobial stewardship in livestock production, there is a growing array of point-of-care diagnostics to guide antimicrobial treatment. The primary objective of this observational study was to evaluate the diagnostic performance of 5 point-of-care tests currently available in Australia for guiding lactational treatment of nonsevere clinical mastitis. A secondary objective was to describe the pathogen profiles of mastitis-causing organisms in cows managed in barns (“intensive”) and on pasture (“nonintensive”). Foremilk samples (n = 641) were collected by farm staff in dairy herds in Australia (n = 30) and tested at a university laboratory using a reference test and 5 index tests. The reference test was aerobic culture on trypticase soy agar with 5% sheep blood followed by MALDI-TOF for identification of isolates. The following point-of-care tests were evaluated as index tests: Accumast, biplate, Check-Up, Mastatest (with AUP3-2022 product), and 3M Petrifilm. We found that 23% of samples were contaminated, with the median herd contamination prevalence being 22%. After excluding contaminated samples, the most common diagnoses (according to the reference test) in intensive herds were no growth (31.7%), Klebsiella spp. (28.1%), Escherichia coli (15.0%), and Streptococcus uberis (8.4%). The most common diagnoses in noncontaminated samples from cows in nonintensive herds were Strep. uberis (35.0%), no growth (26.9%), and E. coli (13.3%). After 24 h of incubation, all index tests demonstrated limited diagnostic sensitivity for identification of pathogens of interest (range: 0.06–0.63). Diagnostic performance was better at the group-level, with sensitivity and specificity for identification of noncontaminated gram-positive growths (i.e., cases that are widely considered to be candidates for antimicrobial treatment) being 0.84 and 0.75, respectively (biplate), 0.76 and 0.90 (Accumast), 0.89 and 0.79 (Check-Up), 0.67 and 0.83 (Petrifilm), and 0.55 and 0.81 (Mastatest). In intensive herds, 22.7% to 40% of cases were classified as antimicrobial treatment candidates by index tests, which was less than for cows in nonintensive herds (41.3%–61.0%). Despite limited diagnostic reliability at the genus level and species level, and the need to ensure samples are collected aseptically, our findings indicate that implementation of selective treatment protocols using the tests evaluated in this study would likely reduce antimicrobial usage in Australian herds.

IntroductionWe investigated the genetic determinants of variation in the hemoglobin glycation index (HGI), an emerging biomarker for the risk of diabetes complications.MethodsWe conducted a genome-wide association study (GWAS) for HGI in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (N = 7,913) using linear regression and additive genotype encoding on variants with minor allele frequency greater than 3%. We conducted replication analyses of top findings in the Atherosclerosis Risk in Communities (ARIC) study with inverse variance-weighted meta-analysis. We followed up with stratified GWAS analyses by sex and self-reported race.ResultsIn ACCORD, we identified single nucleotide polymorphisms (SNPs) associated with HGI, including a peak with the strongest association at the intergenic SNP rs73407935 (7q11.22) (P = 5.8e−10) with a local replication in ARIC. In black individuals, the variant rs10739419 on chromosome 9 in the Whirlin (WHRN) gene formally replicated (meta-P = 2.2e−9). The SNP-based heritability of HGI was 0.39 (P< 1e−10). HGI had significant sex-specific associations with SNPs in or near GALNT11 in women and HECW2 in men. Finally, in Hispanic participants, we observed genome-wide significant associations with variants near USF1 and NXNL2/SPIN1.DiscussionMany HGI-associated SNPs were distinct from those associated with fasting plasma glucose or HbA1c, lending further support for HGI as a distinct biomarker of diabetes complications. The results of this first evaluation of the genetic etiology of HGI indicate that it is highly heritable and point to heterogeneity by sex and race.

Introduction: Apparent treatment-resistant hypertension (aTRH) is characterized by the use of four or more antihypertensive (AHT) classes to achieve blood pressure (BP) control. In the current study, we conducted single-variant and gene-based analyses of aTRH among individuals from 12 Trans-Omics for Precision Medicine cohorts with whole-genome sequencing data.Methods: Cases were defined as individuals treated for hypertension (HTN) taking three different AHT classes, with average systolic BP ≥ 140 or diastolic BP ≥ 90 mmHg, or four or more medications regardless of BP (n = 1,705). A normotensive control group was defined as individuals with BP < 140/90 mmHg (n = 22,079), not on AHT medication. A second control group comprised individuals who were treatment responsive on one AHT medication with BP < 140/ 90 mmHg (n = 5,424). Logistic regression with kinship adjustment using the Scalable and Accurate Implementation of Generalized mixed models (SAIGE) was performed, adjusting for age, sex, and genetic ancestry. We assessed variants using SKAT-O in rare-variant analyses. Single-variant and gene-based tests were conducted in a pooled multi-ethnicity stratum, as well as self-reported ethnic/racial strata (European and African American).Results: One variant in the known HTN locus, KCNK3, was a top finding in the multi-ethnic analysis (p = 8.23E-07) for the normotensive control group [rs12476527, odds ratio (95% confidence interval) = 0.80 (0.74–0.88)]. This variant was replicated in the Vanderbilt University Medical Center’s DNA repository data. Aggregate gene-based signals included the genes AGTPBP, MYL4, PDCD4, BBS9, ERG, and IER3.Discussion: Additional work validating these loci in larger, more diverse populations, is warranted to determine whether these regions influence the pathobiology of aTRH.

Summary: Antimicrobial susceptibility testing is used to determine the minimum inhibitory concentration (MIC), the standard measurement of antibiotic activity. Here, we present a protocol for evaluating MIC values of clinically relevant antibiotics against bacterial isolates cultured in standard bacteriologic medium and in mammalian cell culture medium. We describe steps for pathogen identification, culturing bacteria, preparing MIC plates, MIC assay incubation, and determining MIC. This protocol can potentially optimize the use of existing antibiotics while enhancing efforts to discover new ones.For complete details on the use and execution of this protocol, please refer to Heithoff et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Introduction: Asthma is a chronic disease of the airways that impairs normal breathing. The etiology of asthma is complex and involves multiple factors, including the environment and genetics, especially the distinct genetic architecture associated with ancestry. Compared to early-onset asthma, little is known about genetic predisposition to late-onset asthma. We investigated the race/ethnicity-specific relationship among genetic variants within the major histocompatibility complex (MHC) region and late-onset asthma in a North Carolina-based multiracial cohort of adults.Methods: We stratified all analyses by self-reported race (i.e., White and Black) and adjusted all regression models for age, sex, and ancestry. We conducted association tests within the MHC region and performed fine-mapping analyses conditioned on the race/ethnicity-specific lead variant using whole-genome sequencing (WGS) data. We applied computational methods to infer human leukocyte antigen (HLA) alleles and residues at amino acid positions. We replicated findings in the UK Biobank.Results: The lead signals, rs9265901 on the 5’ end of HLA-B, rs55888430 on HLA-DOB, and rs117953947 on HCG17, were significantly associated with late-onset asthma in all, White, and Black participants, respectively (OR = 1.73, 95%CI: 1.31 to 2.14, p = 3.62 × 10−5; OR = 3.05, 95%CI: 1.86 to 4.98, p = 8.85 × 10−6; OR = 19.5, 95%CI: 4.37 to 87.2, p = 9.97 × 10−5, respectively). For the HLA analysis, HLA-B*40:02 and HLA-DRB1*04:05, HLA-B*40:02, HLA-C*04:01, and HLA-DRB1*04:05, and HLA-DRB1*03:01 and HLA-DQB1 were significantly associated with late-onset asthma in all, White, and Black participants.Conclusion: Multiple genetic variants within the MHC region were significantly associated with late-onset asthma, and the associations were significantly different by race/ethnicity group.

Monitoring 100-day in-calf rate (100DICR) is an integral part of the assessment of reproductive performance in year-round calving dairy herds. The objective of this study was to investigate the effect of month on 100DICR in year-round calving herds in New South Wales (NSW), Australia and determine whether a fluctuating 100DICR target is an appropriate alternative to a constant 100DICR target. The 100DICR is defined as the percentage of all current lactating cows over 100 days in milk (DIM) that conceive on or before 100 DIM. As dairy cows are typically dried off 7 months after conception, 100DICR was an approximate 7-month rolling average. Mean monthly 100DICRs were calculated with a generalised linear model for six NSW north coast herds located 15–140 km from the coast and four NSW south coast herds located less than 10 km from the coast, over a two-year period. The mean 100DICR was lowest in May at 28.62% (95%CI 28.31–28.93) and increased during winter and spring, peaking in December at 34.74% (95%CI 34.32–35.15). The observed trend was similar for north and south coast herds, although north coast herds experienced a greater change in 100DICR from the peak to a nadir of 27.58% (95%CI 27.18–27.98), a 7.15-point difference, compared to south coast herds with a nadir of 30.18% (95%CI 29.69–30.67), a 4.67-point difference between the peak and nadir. In conclusion, 100DICR is affected by month with the lowest 100DICRs observed in late autumn and the highest 100DICRs observed in late spring and early summer. Therefore, a fluctuating target 100DICR is an appropriate alternative to a constant target when assessing reproductive performance in year-round calving herds. While the district does not affect mean 100DICR per se, the district does affect the difference between peak and nadir 100DICR.

The skin is the first line of defense to cutaneous microbes and viruses, and epidermal keratinocytes play a critical role in preventing infection by viruses and pathogens through activation of the type I interferon (IFN) response. Using RNAseq analysis, here we report that the conditional deletion of C/EBPβ transcription factor in mouse epidermis (CKOβ mice) resulted in the upregulation of IFNβ and numerous keratinocyte interferon-stimulated genes (ISGs). The expression of cytosolic pattern recognition receptors (cPRRs), that recognize viral RNA and DNA, were significantly increased, and enriched in the RNAseq data set. cPRRs stimulate a type I IFN response that can trigger cell death to eliminate infected cells. To determine if the observed increases in cPRRs had functional consequences, we transfected CKOβ primary keratinocytes with the pathogen and viral mimics poly(I:C) (dsRNA) or poly(dA:dT) (synthetic B-DNA) that directly activate PRRs. Transfected CKOβ primary keratinocytes displayed an amplified type I IFN response which was accompanied by increased activation of IRF3, enhanced ISG expression, enhanced activation of caspase-8, caspase-3 and increased apoptosis. Our results identify C/EBPβ as a critical repressor of the keratinocyte type I IFN response, and demonstrates that the loss of C/EBPβ primes keratinocytes to the activation of cytosolic PRRs by pathogen RNA and DNA to induce cell death mediated by caspase-8 and caspase-3.

Summary: Background: Although sepsis accounts for 1 in 5 deaths globally, few molecular therapies exist for this condition. The development of effective biomarkers and treatments for sepsis requires a more complete understanding of host responses and pathogenic mechanisms at early stages of disease to minimize host-driven pathology. Methods: An alternative to the current symptom-based approach used to diagnose sepsis is a precise assessment of blood proteomic changes during the onset and progression of Salmonella Typhimurium (ST) murine sepsis. Findings: A distinct pattern of coagulation factor protein abundance was identified in the pre-septic state– prior to overt disease symptoms or bacteremia– that was predictive of the dysregulation of fibrinolytic and anti-coagulant activities and resultant consumptive coagulopathy during ST murine sepsis. Moreover, the changes in protein abundance observed generally have the same directionality (increased or decreased abundance) reported for human sepsis. Significant overlap of ST coagulopathic activities was observed in Gram-negative Escherichia coli– but not in Gram-positive staphylococcal or pneumococcal murine sepsis models. Treatment with matrix metalloprotease inhibitors prevented aberrant inflammatory and coagulopathic activities post-ST infection and increased survival. Antibiotic treatment regimens initiated after specific changes arise in the plasma proteome post-ST infection were predictive of an increase in disease relapse and death after cessation of antibiotic treatment. Interpretation: Altered blood proteomics provides a platform to develop rapid and easy-to-perform tests to predict sepsis for early intervention via biomarker incorporation into existing blood tests prompted by patient presentation with general malaise, and to stratify Gram-negative and Gram-positive infections for appropriate treatment. Antibiotics are less effective in microbial clearance when initiated after the onset of altered blood proteomics as evidenced by increased disease relapse and death after termination of antibiotic therapy. Treatment failure is potentially due to altered bacterial / host-responses and associated increased host-driven pathology, providing insight into why delays in antibiotic administration in human sepsis are associated with increased risk for death. Delayed treatment may thus require prolonged therapy for microbial clearance despite the prevailing notion of antibiotic de-escalation and shortened courses of antibiotics to improve drug stewardship. Funding: National Institutes of Health, U.S. Army.

Cancer patients exhibit a broad range of inter-individual variability in response and toxicity to widely used anticancer drugs, and genetic variation is a major contributor to this variability. To identify new genes that influence the response of 44 FDA-approved anticancer drug treatments widely used to treat various types of cancer, we conducted high-throughput screening and genome-wide association mapping using 680 lymphoblastoid cell lines from the 1000 Genomes Project. The drug treatments considered in this study represent nine drug classes widely used in the treatment of cancer in addition to the paclitaxel + epirubicin combination therapy commonly used for breast cancer patients. Our genome-wide association study (GWAS) found several significant and suggestive associations. We prioritized consistent associations for functional follow-up using gene-expression analyses. The NAD(P)H quinone dehydrogenase 1 (NQO1) gene was found to be associated with the dose-response of arsenic trioxide, erlotinib, trametinib, and a combination treatment of paclitaxel + epirubicin. NQO1 has previously been shown as a biomarker of epirubicin response, but our results reveal novel associations with these additional treatments. Baseline gene expression of NQO1 was positively correlated with response for 43 of the 44 treatments surveyed. By interrogating the functional mechanisms of this association, the results demonstrate differences in both baseline and drug-exposed induction.

Abstract Wildfire smoke is a growing public health concern in the United States. Numerous studies have documented associations between ambient smoke exposure and severe patient outcomes for single‐fire seasons or limited geographic regions. However, there are few national‐scale health studies of wildfire smoke in the United States, few studies investigating Intensive Care Unit (ICU) admissions as an outcome, and few specifically framed around hospital operations. This study retrospectively examined the associations between ambient wildfire‐related PM2.5 at a hospital ZIP code with total hospital ICU admissions using a national‐scale hospitalization data set. Wildfire smoke was characterized using a combination of kriged PM2.5 monitor observations and satellite‐derived plume polygons from National Oceanic and Atmospheric Administration's Hazard Mapping System. ICU admissions data were acquired from Premier, Inc. and encompass 15%–20% of all U.S. ICU admissions during the study period. Associations were estimated using a distributed‐lag conditional Poisson model under a time‐stratified case‐crossover design. We found that a 10 μg/m3 increase in daily wildfire PM2.5 was associated with a 2.7% (95% CI: 1.3, 4.1; p = 0.00018) increase in ICU admissions 5 days later. Under stratification, positive associations were found among patients aged 0–20 and 60+, patients living in the Midwest Census Region, patients admitted in the years 2013–2015, and non‐Black patients, though other results were mixed. Following a simulated severe 7‐day 120 μg/m3 smoke event, our results predict ICU bed utilization peaking at 131% (95% CI: 43, 239; p < 10−5) over baseline. Our work suggests that hospitals may need to preposition vital critical care resources when severe smoke events are forecast.

The emergence and prevalence of antibiotic-resistant bacteria are an increasing cause of death worldwide, resulting in a global ‘call to action’ to avoid receding into an era lacking effective antibiotics. Despite the urgency, the healthcare industry still relies on a single in vitro bioassay to determine antibiotic efficacy. This assay fails to incorporate environmental factors normally present during host-pathogen interactions in vivo that significantly impact antibiotic efficacy. Here we report that standard antimicrobial susceptibility testing (AST) failed to detect antibiotics that are in fact effective in vivo; and frequently identified antibiotics that were instead ineffective as further confirmed in mouse models of infection and sepsis. Notably, AST performed in media mimicking host environments succeeded in identifying specific antibiotics that were effective in bacterial clearance and host survival, even though these same antibiotics failed in results using standard test media. Similarly, our revised media further identified antibiotics that were ineffective in vivo despite passing the AST standard for clinical use. Supplementation of AST medium with sodium bicarbonate, an abundant in vivo molecule that stimulates global changes in bacterial structure and gene expression, was found to be an important factor improving the predictive value of AST in the assignment of appropriate therapy. These findings have the potential to improve the means by which antibiotics are developed, tested, and prescribed.

A detailed characterization of the chemical composition of complex substances, such as products of petroleum refining and environmental mixtures, is greatly needed in exposure assessment and manufacturing. The inherent complexity and variability in the composition of complex substances obfuscate the choices for their detailed analytical characterization. Yet, in lieu of exact chemical composition of complex substances, evaluation of the degree of similarity is a sensible path toward decision-making in environmental health regulations. Grouping of similar complex substances is a challenge that can be addressed via advanced analytical methods and streamlined data analysis and visualization techniques. Here, we propose a framework with unsupervised and supervised analyses to optimally group complex substances based on their analytical features. We test two data sets of complex oil-derived substances. The first data set is from gas chromatography-mass spectrometry (GC-MS) analysis of 20 Standard Reference Materials representing crude oils and oil refining products. The second data set consists of 15 samples of various gas oils analyzed using three analytical techniques: GC-MS, GC×GC-flame ionization detection (FID), and ion mobility spectrometry-mass spectrometry (IM-MS). We use hierarchical clustering using Pearson correlation as a similarity metric for the unsupervised analysis and build classification models using the Random Forest algorithm for the supervised analysis. We present a quantitative comparative assessment of clustering results via Fowlkes-Mallows index, and classification results via model accuracies in predicting the group of an unknown complex substance. We demonstrate the effect of (i) different grouping methodologies, (ii) data set size, and (iii) dimensionality reduction on the grouping quality, and (iv) different analytical techniques on the characterization of the complex substances. While the complexity and variability in chemical composition are an inherent feature of complex substances, we demonstrate how the choices of the data analysis and visualization methods can impact the communication of their characteristics to delineate sufficient similarity.

Prenatal cadmium exposure at non-occupational levels has been associated with poor birth outcomes. The intake of essential metals, such as iron and selenium, may mitigate cadmium exposure effects. However, at high levels, these metals can be toxic. The role of dietary patterns rich in these metals is less studied. We used a linear and logistic regression in a cohort of 185 mother–infant pairs to assess if a Mediterranean diet pattern during pregnancy modified the associations between prenatal cadmium exposure and (1) birth weight and (2) preterm birth. We found that increased cadmium exposure during pregnancy was associated with lower birth weight (β = −210.4; 95% CI: −332.0, −88.8; p = 0.008) and preterm birth (OR = 0.11; 95% CI: 0.01, 0.72; p = 0.04); however, these associations were comparable in offspring born to women reporting high adherence to a Mediterranean diet (β = −274.95; 95% CI: −701.17, 151.26; p = 0.20) and those with low adherence (β = −64.76; 95% CI: −359.90, 230.37; p = 0.66). While the small sample size limits inference, our findings suggest that adherence to a Mediterranean dietary pattern may not mitigate cadmium exposure effects. Given the multiple organs targeted by cadmium and its slow excretion rate, larger studies are required to clarify these findings.

Background: Maternal diet during pregnancy has been shown to influence the child neuro-developmental outcomes. Studies examining effects of dietary patterns on offspring behavior are sparse.Objective: Determine if maternal adherence to a Mediterranean diet is associated with child behavioral outcomes assessed early in life, and to evaluate the role of differentially methylated regions (DMRs) regulating genomically imprinted genes in these associations.Methods: Among 325 mother/infant pairs, we used regression models to evaluate the association between tertiles of maternal periconceptional Mediterranean diet adherence (MDA) scores derived from a Food Frequency Questionnaire, and social and emotional scores derived from the Infant Toddler Social and Emotional Assessment (ITSEA) questionnaire in the second year of life. Methylation of nine genomically imprinted genes was measured to determine if MDA was associated with CpG methylation.Results: Child depression was inversely associated with maternal MDA (Bonferroni-corrected p = 0.041). While controlling for false-discovery, compared to offspring of women with the lowest MDA tertile, those with MDA scores in middle and high MDA tertiles had decreased odds for atypical behaviors [OR (95% CI) = 0.40 (0.20, 0.78) for middle and 0.40 (0.17, 0.92) for highest tertile], for maladaptive behaviors [0.37 (0.18, 0.72) for middle tertile and 0.42 (0.18, 0.95) for highest tertile] and for an index of autism spectrum disorder behaviors [0.46 (0.23, 0.90) for middle and 0.35 (0.15, 0.80) for highest tertile]. Offspring of women with the highest MDA tertile were less likely to exhibit depressive [OR = 0.28 (0.12, 0.64)] and anxiety [0.42 (0.18, 0.97)] behaviors and increased odds of social relatedness [2.31 (1.04, 5.19)] behaviors when compared to low MDA mothers. Some associations varied by sex. Perinatal MDA score was associated with methylation differences for imprinted control regions of PEG10/SGCE [females: Beta (95% CI) = 1.66 (0.52, 2.80) – Bonferroni-corrected p = 0.048; males: -0.56 (-1.13, -0.00)], as well as both MEG3 and IGF2 in males [0.97 (0.00, 1.94)] and -0.92 (-1.65, -0.19) respectively.Conclusion: In this ethnically diverse cohort, maternal adherence to a Mediterranean diet in early pregnancy was associated with favorable neurobehavioral outcomes in early childhood and with sex-dependent methylation differences of MEG3, IGF2, and SGCE/PEG10 DMRs.

Current antibiotic testing does not include the potential influence of host cell environment on microbial susceptibility and antibiotic resistance, hindering appropriate therapeutic intervention. We devised a strategy to identify the presence of host–pathogen interactions that alter antibiotic efficacy in vivo. Our findings revealed a bacterial mechanism that promotes antibiotic resistance in vivo at concentrations of drug that far exceed dosages determined by standardized antimicrobial testing. This mechanism has escaped prior detection because it is reversible and operates within a subset of host tissues and cells. Bacterial pathogens are thereby protected while their survival promotes the emergence of permanent drug resistance. This host-dependent mechanism of transient antibiotic resistance is applicable to multiple pathogens and has implications for the development of more effective antimicrobial therapies.

Cell-based assays are an attractive option to measure gene expression response to exposure, but the cost of whole-transcriptome RNA sequencing has been a barrier to the use of gene expression profiling for in vitro toxicity screening. In addition, standard RNA sequencing adds variability due to variable transcript length and amplification. Targeted probe-sequencing technologies such as TempO-Seq, with transcriptomic representation that can vary from hundreds of genes to the entire transcriptome, may reduce some components of variation. Analyses of high-throughput toxicogenomics data require renewed attention to read-calling algorithms and simplified dose–response modeling for datasets with relatively few samples. Using data from induced pluripotent stem cell-derived cardiomyocytes treated with chemicals at varying concentrations, we describe here and make available a pipeline for handling expression data generated by TempO-Seq to align reads, clean and normalize raw count data, identify differentially expressed genes, and calculate transcriptomic concentration–response points of departure. The methods are extensible to other forms of concentration–response gene-expression data, and we discuss the utility of the methods for assessing variation in susceptibility and the diseased cellular state.

**Background:** Pain is a leading cause of admission to the emergency department (ED) and moderate-to-severe acute pain in medically supervised settings is often treated with intravenous (IV) opioids. With novel noninvasive analgesic products in development for this indication, it is important to assess the costs associated with IV administration of opioids. **Materials and Methods:** A retrospective observational study of data derived from the Premier database was conducted. All ED encounters of adult patients treated with IV opioids during a 2-year time period, who were charged for at least one IV opioid administration in the ED were included. Hospital reported costs were used to estimate the costs to administer IV opioids. **Results:** Over a 24 month-period, 7.3 million encounters, which included the administration of IV opioids took place in 614 US EDs. The mean cost per encounter of IV administration of an initial dose of the three most frequently prescribed opioids were: morphine $145, hydromorphone $146, and fentanyl $147. The main driver of the total costs is the cost of nursing time and equipment cost to set up and maintain an IV infusion ($140 ± 60). Adding a second dose of opioid, brings the average costs to $151-$154. If costs associated with the management of opioid-related adverse events and IV-related complications are also added, the total costs can amount to $269-$273. Of these 7.3 million encounters, 4.3 million (58%) did not lead to hospital admission of the patient and, therefore, the patient may have only required an IV catheter for opioid administration. **Conclusions:** IV opioid use in the ED is indicated for moderate-to-severe pain but is associated with significant costs. In subjects who are discharged from the ED and may not have required an IV for reasons other than opioid administration, rapid-onset analgesics for moderate-to-severe pain that do not require IV administration could lead to direct cost reductions and improved care.

Mycoplasma spp. are a major cause of mastitis, arthritis and pneumonia in cattle, and have been associated with reproductive disorders in cows. While culture is the traditional method of identification the use of PCR has become more common. Several investigators have developed PCR protocols to detect M. bovis in milk, yet few studies have evaluated other sample types or other important Mycoplasma species. Therefore the objective of this study was to develop a multiplex PCR assay to detect M. bovis, M. californicum and M. bovigenitalium, and evaluate its analytical performance against traditional culture of bovine milk, semen and swab samples. The PCR specificity was determined and the limit of detection evaluated in spiked milk, semen and swabs. The PCR was then compared to culture on 474 field samples from individual milk, bulk tank milk (BTM), semen and swab (vaginal, preputial, nose and eye) samples. Specificity analysis produced appropriate amplification for all M. bovis, M. californicum and M. bovigenitalium isolates. Amplification was not seen for any of the other Mollicutes or eubacterial isolates. The limit of detection of the PCR was best in milk, followed by semen and swabs. When all three Mycoplasma species were present in a sample, the limit of detection increased. When comparing culture and PCR, overall there was no significant difference in the proportion of culture and PCR positive samples. Culture could detect significantly more positive swab samples. No significant differences were identified for semen, individual milk or BTM samples. PCR identified five samples with two species present. Culture followed by 16S-23S rRNA sequencing did not enable identification of more than one species. Therefore, the superior method for identification of M. bovis, M. californicum and M. bovigenitalium may be dependent on the sample type being analysed, and whether the identification of multiple target species is required.