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Background Many dairy cows experience a state of energy deficit as they transition from late gestation to early lactation. The aims of this study were to 1) determine if the development of hyperketonemia in early lactation dairy cows is indicated by their gut microbiome, and 2) to identify microbial features which may inform health status. We conducted a prospective nested case-control study in which cows were enrolled 14 to 7 days before calving and followed through their first 14 days in milk (DIM). Hyperketonemic cows (HYK, n = 10) were classified based on a blood β-hydroxybutyrate (BHB) concentration 1.2 mmol/L within their first 14 DIM. For each HYK cow, two non-HYK (CON, n = 20) cows were matched by parity and 3 DIM, with BHB n = 9). Rumen and fecal samples were collected on the day of diagnosis or matching and subjected to 16S rRNA profiling. Results No differences in taxa abundance, or alpha and beta diversity, were observed among CON, C-HYK, and HYK health groups for fecal microbiomes. Similar microbiome composition based on beta diversity analysis was detected for all health statuses, however the rumen microbiome of CON and HYK cows were found to be significantly different. Interestingly, highly similar microbiome composition was observed among C-HYK cow rumen and fecal microbiomes, suggesting that these individual animals which initially appear healthy with late onset of hyperketonemia were highly similar to each other. These C-HYK cows had significantly lower abundance of Ruminococcus 2 in their rumen microbiome compared to CON and HYK groups. Multinomial regressions used to compute log-fold changes in microbial abundance relative to health status were not found to have predictive value, therefore were not useful to identify the role of certain microbial features in predicting health status. Conclusions Lower relative abundance of Ruminococcus 2 in C-HYK cow rumens was observed, suggesting these cows may be less efficient at degrading cellulose although the mechanistic role of Ruminococcus spp. in rumen metabolism is not completely understood. Substantial differences in fecal or rumen microbiomes among cows experiencing different levels of energy deficit were not observed, suggesting that hyperketonemia may not be greatly influenced by gut microbial composition, and vice versa. Further studies using higher resolution -omics approaches like meta-transcriptomics or meta-proteomics are needed to decipher the exact mechanisms at play.

A major concern for plant nurseries and land stewards is managing pathogens that induce soilborne diseases. Plant diseases cost nurseries millions of dollars in lost revenue. Plant pathogens spread into the environment from nursery soil used for out-plantings. Recent research shows that steaming soil at high temperatures can effectively kill plant pathogens, however, few studies investigate the influence of steaming on the soil microbiome, an essential component of plant health. We conducted a controlled experiment where nursery soil underwent a steaming event within a rectangular mesocosm (2.04 x 3.55 x 0.25 m) located at the National Ornamentals Research Site at Dominican University (NORS-DUC) (San Rafael, CA, US). Soil samples were collected at four time points post-steaming. Thirty-two soil samples were used for DNA extraction and 18 for chemical analysis. The 16S rRNA gene and ITS genetic markers were used for amplicon-based sequencing methods to identify the bacterial and fungal soil communities. Results indicate that microbial diversity and composition shifted overtime, but that soil depth was not an important factor. Important bacterial taxa were the Firmicutes, especially 1 day post-steaming, and common fungal taxa included Aspergillus sp., Cladosporium sp., and Pseudallescheria sp.. Plant nutrients such as B, C, Cl, K, Mg, SO4, and Zn in addition to essential soil properties such as CEC, gypsum, moisture, and SAR changed significantly with soil recovery. These results can help nursery practitioners make informed decisions for biotic and nutrient amendments post-steaming to promote soil and plant health.

Mastitis is the costliest disease facing dairy producers today; consequently, it has been the subject of substantial research focus. Efforts have evolved from an initial focus on understanding the etiology of intramammary infections to the application of preventative measures, including attempts to breed cows that are resistant to infection. However, breeding for resistance to infection has proven difficult, given the complexity of the disease and the high expense associated with assembling high-quality genotypes and phenotypes. This review provides a brief background on mastitis; illustrates current understanding of the genetics influencing mastitis and the application of this knowledge; and discusses challenges and limitations in understanding these mechanisms and applying these findings to genetic improvement strategies.

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.

Many dairy cows experience a state of energy deficit as they transition from late gestation to early lactation. The aims of this study were to 1) determine if the development of hyperketonemia in early lactation dairy cows is indicated by their gut microbiome, and 2) to identify microbial features which may inform health status. We conducted a prospective nested case-control study in which cows were enrolled 14 to 7 days before calving and followed through their first 14 days in milk (DIM). Hyperketonemic cows (HYK, n = 10) were classified based on a blood β-hydroxybutyrate (BHB) concentration 1.2 mmol/L within their first 14 DIM. For each HYK cow, two non-HYK (CON, n = 20) cows were matched by parity and 3 DIM, with BHB 1.2 mmol/L. Daily blood BHB measures were used to confirm CON cows maintained their healthy status; some CON cows displayed BHB 1.2 mmol/L after matching and these cows were reclassified as control-HYK (C-HYK, n = 9). Rumen and fecal samples were collected on the day of diagnosis or matching and subjected to 16S rRNA profiling.No differences in taxa abundance, or alpha and beta diversity, were observed among CON, C-HYK, and HYK health groups for fecal microbiomes. Similar microbiome composition based on beta diversity analysis was detected for all health statuses, however the rumen microbiome of CON and HYK cows were found to be significantly different. Interestingly, highly similar microbiome composition was observed among C-HYK cow rumen and fecal microbiomes, suggesting that these individual animals which initially appear healthy with late onset of hyperketonemia were highly similar to each other. These C-HYK cows had significantly lower abundance of Ruminococcus 2 in their rumen microbiome compared to CON and HYK groups. Multinomial regressions used to compute log-fold changes in microbial abundance relative to health status were not found to have predictive value, therefore were not useful to identify the role of certain microbial features in predicting health status.Lower relative abundance of Ruminococcus 2 in C-HYK cow rumens was observed, suggesting these cows may be less efficient at degrading cellulose although the mechanistic role of Ruminococcus spp. in rumen metabolism is not completely understood. Substantial differences in fecal or rumen microbiomes among cows experiencing different levels of energy deficit were not observed, suggesting that hyperketonemia may not be greatly influenced by gut microbial composition, and vice versa. Further studies using higher resolution -omics approaches like meta-transcriptomics or meta-proteomics are needed to decipher the exact mechanisms at play.

Classroom observation tools are used to evaluate teaching and learning activities, and to provide constructive feedback to instructors. To help instructors with selecting a suitable tool based on their needs and available resources, in this study, a group of observers assessed lectures of an introductory biology course using three, broadly cited classroom assessment tools in the STEM field: the Classroom Observation Protocol for Undergraduate STEM (COPUS); the Practical Observation Rubric to Assess Active Learning (PORTAAL); and the Decibel Analysis for Research in Teaching (DART). From a user’s perspective, we evaluated 1) the type and extent of information each tool provides, and 2) the time investment and difficulty of working with each tool. The assessment result of each tool was compared, with a list of expected outcomes generated by surveying a group of college instructors and with the result of a self-teaching assessment tool, Teaching Practices Inventory (TPI). Our findings conclude that each tool provided valuable assessment with a broad range of outcomes and time investment: PORTAAL offered the most detailed information on the quality of teaching practices and students’ engagement, but it demanded the greatest time investment. DART provided a basic estimation of active learning proportion with the least effort. The level of assessment outcome and the time investment when using COPUS was found to be less than PORTAAL, and more than DART. The TPI self-assessment outcome was found to be slightly optimistic regarding the proportion of active learning practices used in the studied course. This comparative study can help instructors in selecting a tool that suits their needs and available resources for a better assessment of their classroom teaching and learning.

Our primary objective was to identify udder and teat conformational risk factors associated with the occurrence of elevated somatic cell count ( SCC ) and clinical mastitis using a prospective cohort study design with careful assessment of exposure and disease outcomes. Mastitis prevalence was evaluated by parity across 6 sampling periods representing key physiological transitions during lactation: 0–1 day in milk (DIM), 3–5 DIM, 10–14 DIM, 50–60 DIM, 90–110 DIM, and 210–230 DIM. Cows were scored for front and rear teat length, width, end shape, and placement, fore udder attachment, udder cleft, udder depth, rear udder height, and rear udder width. Two independent multivariable logistic regression models were used to generate odds ratios ( OR ) for elevated SCC (≥ 200,000 cells/ml) and farm-diagnosed clinical mastitis. We identified that loose fore udder attachment (reference level: strong fore udder attachment, OR = 2.1, 95% confidence interval (CI) = 1.2–3.8) and flat teat end shape (reference level: round teat end shape, OR = 1.4, 95% CI = 1.1–1.9) increased the odds of an elevated SCC event, whereas a negative California Mastitis Test score at 0–1 DIM decreased the odds of an elevated SCC event (OR = 0.6, 95% CI = 0.4 to 0.8). Loose fore udder attachment (reference level: strong fore udder attachment, OR = 3.7, 95% CI = 1.3–10.7), flat teat end shape (reference level: round teat end shape, OR = 1.5, 95% CI = 1.0–2.4), low rear udder height (reference level: intermediate rear udder height, OR = 2.8, 95% CI = 0.3–6.2), and increasing rear teat width (OR = 2.2, 95% CI = 1.2–4.4) heightened the odds of developing clinical mastitis. We identified that within our study cohort, loose fore udder attachment and flat teat ends had an important association with increased odds of both an elevated SCC event and clinical mastitis diagnosis. The identification of these udder and teat conformational risk factors for mastitis can provide farmers an effective and inexpensive tool to manage mastitis.

Lameness is a major animal welfare and economic issue for the dairy industry and is a challenge to overcome due to multifaceted causes. Digital cushion thickness (DCT) is a strong predictor of lameness and is phenotypically associated with incidence of claw horn disruption lesions (CHDL; sole ulcers and white line disease). We hypothesized that DCT varies between digits and across lactation within the cow. This variation could be characterized to predict the occurrence of CHDL or compromised locomotion. BCS, visual locomotion score (VLS), DCT, and presence or absence of lesions were collected at 4 time points

The objective of this study was to determine whether genetic regulation of bovine milk somatic cell count (SCC) varied throughout the course of an individual lactation and to identify quantitative trait loci (QTL) that may differentiate populations of chronically mastitic and robustly healthy cows. Milk SCC has long been a proxy for clinical mastitis diagnosis in management and genetic improvement strategies to control the disease. Cows (n = 471) were genotyped on the Illumina BovineHD 777K BeadChip (Illumina Inc., San Diego, CA), and composite milk samples were collected for SCC at 0-1 d in milk (DIM), 3-5 DIM, 10-14 DIM, 90-110 DIM, and 210-230 DIM, with each time span representing key physiological transitions for the cow. Median lactation somatic cell score (SCS) and area under the SCS curve were calculated from farm test data. A total of 8 genome-wide associations were performed and 167 SNP spanning the genome were significantly associated (false discovery rate0.05). Of these associated regions, 27 of 48 associated QTL were novel for clinical mastitis or SCC. The linkage disequilibrium block surrounding the associated QTL or a 1-Mb window in the absence of linkage disequilibrium was interrogated for candidate genes, and many of those identified were related to multiple arms of the immune system, including toll-like receptor signaling, macrophage activation, B-cell maturation, T-cell recruitment, and the complement pathway. These genes included EXOC4, BAMBI, ITSN2, IL34, FCN3, CD8A, and CD8B. In addition, we identified populations of robustly healthy (SCS ≤4 from 10-14 DIM until study end), chronically mastitic (SCS4 from 10-14 DIM until study end), and average cows with fluctuating SCS, and calculated fixation indices to identify regions of the genome differentiating these 3 populations. A total of 12 SNP were identified that showed moderate allelic differentiation (Wright's F statistic, F

Our objectives were to robustly characterize a cohort of Holstein cows for udder and teat type traits and perform high-density genome-wide association studies for those traits within the same group of animals, thereby improving the accuracy of the phenotypic measurements and genomic association study. Additionally, we sought to identify a novel udder and teat trait composite risk index to determine loci with potential pleiotropic effects related to mastitis. This approach was aimed at improving the biological understanding of the genetic factors influencing mastitis. Cows (N = 471) were genotyped on the Illumina BovineHD777k beadchip and scored for front and rear teat length, width, end shape, and placement, fore udder attachment, udder cleft, udder depth, rear udder height, and rear udder width. We used principal component analysis to create a single composite measure describing type traits previously linked to high odds of developing mastitis within our cohort of cows. Genome-wide associations were performed, and 28 genomic regions were significantly associated (Bonferroni-corrected p &lt, 0.05). Interrogation of these genomic regions revealed a number of biologically plausible genes whicht may contribute to the development of mastitis and whose functions range from regulating cell proliferation to immune system signaling, including ZNF683, DHX9, CUX1, TNNT1, and SPRY1. Genetic investigation of the risk composite trait implicated a novel locus and candidate genes that have potentially pleiotropic effects related to mastitis.

The United States Environmental Protection Agency has proposed new categorical pretreatment effluent standards for the Metal Products and Machinery Industry, which are more stringent than current discharge limits in the automotive industry. Therefore, this study was conducted to evaluate metal-sulfide precipitation chemistry as an alternative to metal-hydroxide precipitation chemistry for removing Cu, Ni, Pb, and Zn. There were three aspects of this study: (1) theoretical analysis of both metal–hydroxide and metal–sulfide chemistry; (2) experimental evaluation of commercially available sulfur-containing precipitants using deionized water; and (3) experimental evaluation of the precipitants using wastewater samples from three automotive manufacturing plants (transmission, engine, and assembly plants). The primary findings are: (1) In theory, metal–hydroxide chemistry can achieve the proposed standards when no chelating agents are present. This is not true when as small as 1 mg/L of ethylenediaminetetra-ace...