Associations between early lactation intramammary infections and udder health and performance during the first 180 days in milk in first-lactation organic dairy cows.

Prior data from our group showed that first-lactation cows under organic management in United States have a high prevalence of Staphylococcus aureus, Streptococcus spp., and Staphylococcus chromogenes intramammary infections (IMI) in early lactation. Nonetheless, the relationship between IMI, udder health, and milk production in organically reared primiparous cows remains elusive. The objectives of this observational study were to investigate the relationship between presence and persistence of IMI in the first 35 d in milk (DIM) and somatic cell count (SCC) and milk production during the first 6 mo of lactation on first-lactation organic dairy cows. The analysis included a total of 1,348 composite milk samples collected during the first 35 DIM that were submitted for milk culture and 1,674 Dairy Herd Improvement Association (DHIA) tests during the first 180 DIM from 333 heifers in 4 organic dairy farms, enrolled between February 2019 and January 2020. The association between IMI in the first 35 DIM and new high SCC (SCC > 200,000 cells/mL) and milk production during the first 6 mo of lactation was investigated using Cox proportional hazards regression and mixed linear regression, respectively. The association between IMI persistence (harboring the same microorganism as reported by the laboratory for 2 or more samples) in the first 35 DIM and number of DHIA tests with high SCC during the first 6 mo of lactation was modeled using negative binomial regression. The presence of IMI by Staph. aureus (hazard ratio [HR] [95% confidence interval {CI}]: 3.35 [2.64, 4.25]) or Streptococcus spp. (HR [95% CI]: 2.25 [2.12, 2.39]) during the first 35 DIM was associated with an increased risk of new high SCC during the first 6 mo of lactation. Milk production was reduced when Streptococcus spp. were identified in milk samples. However, there was no evidence of a difference in milk production in Staph. aureus IMI. Isolation of non-aureus staphylococci and mammaliicocci was related to a mild increase in the hazards of high SCC (HR [95% CI]: 1.34 [0.97, 1.85]) and a decrease in milk production during one or more postpartum tests. Presence of gram-negative or Streptococcus-like organisms IMI was not associated with either high SCC or milk production. Presence of Bacillus IMI was associated with a lower hazard of new high SCC (HR [95% CI]: 0.45 [0.30, 0.68]), and higher milk production during the first 180 d of lactation (overall estimate [95% CI]: 1.7 kg/d [0.3, 3.0]). The persistence of IMI in the first 35 DIM was associated with the number of tests with high SCC during the lactation for all microorganisms except for Staphylococcus chromogenes. Therefore, our results suggest that the persistence of IMI in the first 35 DIM could be an important factor to understand the association between IMI detected in early lactation and lactational SCC and milk production in organic dairy heifers. Our study described associations between IMI, udder health, and milk production in first-lactation organic dairy cows that are consistent with findings from conventional dairy farms.

Investigation of intramammary infections in primiparous cows during early lactation on organic dairy farms.

Previous studies have shown that organically raised dairy cows have an increased prevalence of Staphylococcus aureus compared with conventionally raised dairy cows. However, little information exists about the dynamics of intramammary infection (IMI) in primiparous cows during early lactation on organic dairy farms. The objective of this study was to describe the IMI dynamics of primiparous cows on certified organic farms during early lactation. This longitudinal study enrolled 503 primiparous cows from 5 organic dairy farms from February 2019 to January 2020. Quarter-level milk samples were collected aseptically on a weekly basis during the first 5 wk of lactation. Samples were pooled by cow and time point into composite samples inside a sterilized laminar hood and submitted for microbiological culture. For each of the different microorganisms identified, we estimated the prevalence in each postpartum sample, period prevalence (PP), cumulative incidence, and persistence of IMI. Logistic regression models were used to investigate whether the prevalence of IMI differed by farm or sampling time points and whether IMI persistence differed between detected microorganisms. Our findings revealed a high prevalence of Staphylococcus aureus (PP = 18.9%), non-aureus staphylococci and closely related mammaliicoccal species (PP = 52.1%), and Streptococcus spp. and Streptococcus-like organisms (PP = 32.1%) within the study population. The prevalence of these microorganisms varied significantly between farms. Staphylococcus aureus and Staphylococcus chromogenes exhibited significantly higher IMI persistence compared with other detected bacterial taxa, confirming the divergent epidemiological behavior in terms of IMI chronicity across different microorganisms. This study improves our understanding of the epidemiology of mastitis-causing pathogens in organically raised primiparous cows, which can be used to tailor mastitis control plans for this unique yet growing subpopulation of dairy cows.

Stereotactic Radiosurgery for Spinal Haemangioblastoma: A Retrospective Single-Centre Experience from the United Kingdom.

INTRODUCTION: Haemangioblastoma is a benign, vascular tumour of the central nervous system. Stereotactic radiosurgery (SRS) is increasingly being used as a treatment for spinal lesions to avoid complex surgery, especially in patients with multi-focal tumours associated with von Hippel-Lindau syndrome (VHL). Here, we present the outcomes of patients treated in our centre using a CyberKnife VSI (Accuray, Inc.). METHODS: Retrospective analysis of all patients treated at our institution was conducted. Assessment of radiological response was based upon RANO criteria. Solid and overall tumour progression-free survival (PFS) was calculated using the Kaplan-Meier method. The development of a symptomatic new or enlarging cyst was included in the definition of progression when determining overall PFS. RESULTS: Fourteen tumours in 10 patients were included. Seven patients were male, and nine had VHL. Nine (64%) tumours had an associated cyst. The median (IQR) age at treatment was 45.5 (43.5-53) years. The median gross tumour volume was 0.355cc. Patients received a mean marginal prescribed dose of 9.6 Gy in a single fraction (median maximum dose: 14.3 Gy), which was constrained by spinal cord tolerance. Mean follow-up was 15.4 months. Radiologically, 11 (78.6%) tumours were stable or regressed and three (21.4%) progressed. Eight patients' symptoms improved or were stable, and two worsened, both of which were secondary to cyst enlargement. The 1-year solid-tumour and overall PFS was 92.3% and 75.7%, respectively. All patients were alive at the most recent follow-up. One patient developed grade 1 back pain following treatment. DISCUSSION/CONCLUSION: SRS appears to be a safe and effective treatment for spinal haemangioblastoma. Prospective trials with longer follow-up are required to establish the optimum management.

Evaluation of Contamination in Milk Samples Pooled From Independently Collected Quarters Within a Laboratory Setting.

The primary objective of this observational study was to evaluate the prevalence of contamination from independently collected quarter-level milk samples pooled in a laboratory and subjected to bacterial culture. To address this objective, weekly quarter-level milk samples were collected longitudinally from a cohort of 503 primiparous cows from five organic dairy farms during the first 5 weeks after calving. Individual quarter milk samples were pooled in a laboratory using aseptic technique ("lab-pooled") and subjected to bacterial culture. In the sample set of 2,006 lab-pooled milk samples, 207 (10.3%) were classified as contaminated using a standard definition (i.e., growth of three or more distinct microorganisms). Subsequent culturing of corresponding quarter-level milk samples revealed that many of the contaminated lab-pooled sample results (i.e., 46.7%) were the result of intramammary infections with different pathogens across the quarters, rather than actual contamination within any single quarter (i.e., "true contamination"). The odds of true contamination were lower when the lab-pooled sample exhibited growth of three microorganisms compared to more than 3 microorganisms. Our findings suggest that pooling of quarter samples within a laboratory setting may yield lower rates of contamination compared to those previously reported from samples composited on-farm, but that current cut-offs to define contamination may need to be evaluated for use with lab-pooled samples. Further investigation of use of lab-pooled samples may be warranted to reduce costs while still providing useful scientific insight.

Considerations and best practices in animal science 16S ribosomal RNA gene sequencing microbiome studies.

Microbiome studies in animal science using 16S rRNA gene sequencing have become increasingly common in recent years as sequencing costs continue to fall and bioinformatic tools become more powerful and user-friendly. The combination of molecular biology, microbiology, microbial ecology, computer science, and bioinformatics-in addition to the traditional considerations when conducting an animal science study-makes microbiome studies sometimes intimidating due to the intersection of different fields. The objective of this review is to serve as a jumping-off point for those animal scientists less familiar with 16S rRNA gene sequencing and analyses and to bring up common issues and concerns that arise when planning an animal microbiome study from design through analysis. This review includes an overview of 16S rRNA gene sequencing, its advantages, and its limitations; experimental design considerations such as study design, sample size, sample pooling, and sample locations; wet lab considerations such as field handing, microbial cell lysis, low biomass samples, library preparation, and sequencing controls; and computational considerations such as identification of contamination, accounting for uneven sequencing depth, constructing diversity metrics, assigning taxonomy, differential abundance testing, and, finally, data availability. In addition to general considerations, we highlight some special considerations by species and sample type.

Hierarchical Hidden Markov models enable accurate and diverse detection of antimicrobial resistance sequences.

The characterization of antimicrobial resistance genes from high-throughput sequencing data has become foundational in public health research and regulation. This requires mapping sequence reads to databases of known antimicrobial resistance genes to determine the genes present in the sample. Mapping sequence reads to known genes is traditionally accomplished using alignment. Alignment methods have high specificity but are limited in their ability to detect sequences that are divergent from the reference database, which can result in a substantial false negative rate. We address this shortcoming through the creation of Meta-MARC, which enables detection of diverse resistance sequences using hierarchical, DNA-based Hidden Markov Models. We first describe Meta-MARC and then demonstrate its efficacy on simulated and functional metagenomic datasets. Meta-MARC has higher sensitivity relative to competing methods. This sensitivity allows for detection of sequences that are divergent from known antimicrobial resistance genes. This functionality is imperative to expanding existing antimicrobial gene databases.

Enrichment allows identification of diverse, rare elements in metagenomic resistome-virulome sequencing.

BACKGROUND: Shotgun metagenomic sequencing is increasingly utilized as a tool to evaluate ecological-level dynamics of antimicrobial resistance and virulence, in conjunction with microbiome analysis. Interest in use of this method for environmental surveillance of antimicrobial resistance and pathogenic microorganisms is also increasing. In published metagenomic datasets, the total of all resistance- and virulence-related sequences accounts for < 1% of all sequenced DNA, leading to limitations in detection of low-abundance resistome-virulome elements. This study describes the extent and composition of the low-abundance portion of the resistome-virulome, using a bait-capture and enrichment system that incorporates unique molecular indices to count DNA molecules and correct for enrichment bias. RESULTS: The use of the bait-capture and enrichment system significantly increased on-target sequencing of the resistome-virulome, enabling detection of an additional 1441 gene accessions and revealing a low-abundance portion of the resistome-virulome that was more diverse and compositionally different than that detected by more traditional metagenomic assays. The low-abundance portion of the resistome-virulome also contained resistance genes with public health importance, such as extended-spectrum betalactamases, that were not detected using traditional shotgun metagenomic sequencing. In addition, the use of the bait-capture and enrichment system enabled identification of rare resistance gene haplotypes that were used to discriminate between sample origins. CONCLUSIONS: These results demonstrate that the rare resistome-virulome contains valuable and unique information that can be utilized for both surveillance and population genetic investigations of resistance. Access to the rare resistome-virulome using the bait-capture and enrichment system validated in this study can greatly advance our understanding of microbiome-resistome dynamics.

MEGARes: an antimicrobial resistance database for high throughput sequencing.

Antimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of high throughput sequencing data that is pre-packaged for use with the MEGARes database.