Blood parameters associated with residual feed intake in beef heifers.

Blood chemistry may provide indicators to greater feed efficient cattle. As a side objective to previous research, 17 Angus heifers approximately two years old underwent a feed efficiency trial to determine residual feed intake (RFI) and identify variation in blood chemistry in beef cattle divergent in feed efficiency. Heifers were categorized as high- or low-RFI based ± 0.25 standard deviations around mean RFI. Blood samples were analyzed using an i-STAT handheld blood analyzer to measure sodium, potassium, glucose, blood urea nitrogen (BUN), creatinine, hematocrit, and hemoglobin. BUN was greater in high-RFI heifers (µ = 8.7 mg/dL) contrasted to low-RFI heifers (µ = 6.5 mg/dL; P = 0.01), whereas glucose was greater in low-RFI heifers (µ = 78.1 mg/dL) contrasted to high-RFI heifers (µ = 82.0 mg/dL; P = 0.05). No other blood chemistry parameters differed by RFI. The greater abundance of BUN in high-RFI heifers may indicate inefficient utilization of protein or mobilization of tissue protein for non-protein use. Greater blood glucose concentrations in low-RFI heifers may indicate greater utilization of energy precursors, such as volatile fatty acids, or metabolites. These data suggest there are readily measurable indicators of physiological variation in nutrient utilization; however, this warrants additional studies to explore.

The Impacts of Supplemental Protein during Development on Amino Acid Concentrations in the Uterus and Pregnancy Outcomes of Angus Heifers.

Replacement heifer development is one of the most critical components in beef production. The composition of the ideal uterine environment could maximize fertility and reproductive efficiency. Our hypothesis was that protein supplementation would affect the uterine environment of beef heifers without inhibiting development or reproduction. To test the effects of dietary supplementation on these outcomes, a randomized complete block design with repeated measures was implemented. Angus heifers (n = 60) were blocked by body weight (BW) and randomly assigned to one of three supplemental protein treatment groups (10% (CON), 20% (P20), and 40% (P40)). Mixed model ANOVAs were used to determine whether protein supplementation treatments, time, and the interaction or protein supplementation, semen exposure, and the interaction influenced uterine luminal fluid (ULF) and pregnancy outcomes. Amino acids (AAs) were impacted (p < 0.001), specifically, the essential AAs: Arg, Iso, Leu, Val, His, Lys, Met, Phe, Trp. Protein supplementation influenced multiple AAs post-insemination: Arg (p = 0.03), CC (p = 0.05), 1-MH (p = 0.001), and Orn (p = 0.03). In conclusion, protein supplementation did not affect the reproductive development via puberty attainment or the timing of conception even with alterations in growth. However, uterine AA concentrations did change throughout development and protein supplementation influenced ULF d 14 post-insemination, which may affect the conception rates.

The effects of differing nutritional levels and body condition score on scrotal circumference, motility, and morphology of bovine sperm.

Bulls often experience various levels of nutrient availability throughout the year. Nutritional management is a critical factor on overall ejaculate composition and the ability to get females pregnant. We hypothesized that differing nutritional levels and body condition score (BCS) affect reproductive fertility parameters in bulls. Mature Angus bulls (n = 11) were individually housed and randomly assigned to one of two dietary regimens: 1) over-fed (n = 5) or 2) restricted (n = 6). Bulls were fed the same ration at different volumes to achieve desired effects resulting in eight individual treatments: gain to an over-fed body condition score ([BCS]; GO), gain after nutrient restriction (GR), loss after an over-fed BCS (LO), loss from nutrient restriction (LR), maintenance at ideal adiposity (BCS = 6) after overfeeding (IMO), maintenance at ideal adiposity after nutrient restriction (IMR), maintenance at an over-fed BCS (BCS = 8; MO), and maintenance at a restricted BCS (BCS = 4; MR). Body weight (BW) and BCS were recorded every 2 wk to monitor bull weight and BCS changes. Scrotal circumference was measured every 28 d. Body fat and sperm motility and morphology were evaluated every 84 d. Scrotal circumference, motility, and morphology were normalized to the initial value of each bull. Thus, allowing the individual bull to serve as a control. Statistical analyses were conducted with PROC GLIMMIX of SAS as a complete randomized design to determine if treatment influenced BW, BCS, scrotal circumference, motility, morphology, and adipose thickness. Scrotal circumference (P < 0.001) had the least amount of deviation from initial during the LR (0.29 ±â€…0.44) treatment and the greatest during the MO (3.06 ±â€…0.44), LO (2.28 ±â€…0.44), MR (2.43 ±â€…0.44), GR (3.03 ±â€…0.44), and IMR (2.91 ±â€…0.44) treatments. Sperm motility was not affected by nutritional treatments (P = 0.55). Both head and total defects of sperm differed (P = 0.02) due to nutritional treatments. Increased head abnormalities occurred during the LO (37.60 ±â€…8.61) treatment, with no differences between the other treatments. Total defects increased during the LO (43.80 ±â€…9.55) treatment with similar increases in bulls during the GR (29.40 ±â€…9.55) and IMR (35.60 ±â€…9.55) treatments. In conclusion, male fertility was impacted when a deviation from a BCS of 6 occurred which could be detrimental to reproductive and beef production efficiency.

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.

The effects of protein level on cytokines and chemokines in the uterine environment of beef heifers during development.

The development of replacement heifers is crucial for breeding success and herd efficiency. Nutritional management can affect not only reproductive development but also the inflammatory status of the uterine environment, which may impact reproductive functions such as pregnancy establishment and development. The study herein evaluated the concentration of cytokines and chemokines in the uterus of heifers supplemented with different levels of protein. Angus heifers (n = 60) were blocked by body weight (BW) and randomly assigned to 1 of 3 treatments based on protein supplementation level: control of 10% crude protein (CON), 20% crude protein (P20), or 40% crude protein (P40). BW, body condition score, and blood samples were taken every 2 wk for 140 d to monitor development. Uterine flushes were performed monthly and concentrations of cytokines (IL-1α, IL-1ß, TNF-α, IFN-γ, IL-10, VEGF-α, IL-17A, and IL-36RA) and chemokines (IL-8, MCP-1, MIP-1α, and MIP-1ß) were quantified via ELISA multiplex. To test if there were mean differences in cytokines between the treatment groups or over time, PROC GLIMMIX (SAS v 9.4) was utilized. Concentrations of all cytokines and chemokines, except IL-1α, changed throughout heifer development (P < 0.05). Heifers in the P40 treatment group displayed reduced concentrations of MCP-1 (P = 0.007) and tended to have decreased concentrations of IFN-γ (P = 0.06). Cytokine IL-36RA tended (P = 0.06) to be affected by protein level, with the lowest concentrations observed in CON heifers. Most cytokines and chemokines increased following the initial month of supplementation (P < 0.05). The increase in concentrations after 1 mo may indicate an adaptive response in the uterus to diet change. Cytokines and chemokines fluctuated due to physiological changes occurring during development. Further research is needed to determine the influence of nutrition on uterine inflammation and long-term impacts on reproductive function.

Rumen and Serum Metabolomes in Response to Endophyte-Infected Tall Fescue Seed and Isoflavone Supplementation in Beef Steers.

Fescue toxicosis impacts beef cattle production via reductions in weight gain and muscle development. Isoflavone supplementation has displayed potential for mitigating these effects. The objective of the current study was to evaluate isoflavone supplementation with fescue seed consumption on rumen and serum metabolomes. Angus steers (n = 36) were allocated randomly in a 2 × 2 factorial arrangement of treatments including endophyte-infected (E+) or endophyte-free (E-) tall fescue seed, with (P+) or without (P-) isoflavones. Steers were provided a basal diet with fescue seed for 21 days, while isoflavones were orally administered daily. Following the trial, blood and rumen fluid were collected for metabolite analysis. Metabolites were extracted and then analyzed by UPLC-MS. The MAVEN program was implemented to identify metabolites for MetaboAnalyst 4.0 and SAS 9.4 statistical analysis. Seven differentially abundant metabolites were identified in serum by isoflavone treatment, and eleven metabolites in the rumen due to seed type (p < 0.05). Pathways affected by treatments were related to amino acid and nucleic acid metabolism in both rumen fluid and serum (p < 0.05). Therefore, metabolism was altered by fescue seed in the rumen; however, isoflavones altered metabolism systemically to potentially mitigate detrimental effects of seed and improve animal performance.

Rumen fluid metabolomics of beef steers differing in feed efficiency.

INTRODUCTION: Beef is the most consumed red meat in the United States, and the US is the largest producer and consumer of beef cattle globally. Feed is one of the largest input costs for the beef cattle industry, accounting for 40-60% of the total input costs. Identifying methods for improving feed efficiency in beef cattle herds could result in decreased cost to both producers and consumers, as well as increased animal protein available for global consumption. METHODS: In this study, rumen fluid was collected from low- (n = 14) and high-RFI (n = 15) steers. Rumen fluid was filtered through a 0.22 µM syringe filter, extracted using 0.1% formic acid in acetonitrile:water:methanol (2:2:1) and injected into the Dionex UltiMate 3000 UHPLC system with an Exactive Plus Orbitrap MS. Peaks were identified using MAVEN and analyzed using MetaboAnalyst 4.0 and SAS. Significance was determined using an α ≤ 0.05. RESULTS: Eight metabolites were greater in low-RFI steers compared to high-RFI steers, including 3,4-dihydroxyphenylacetate, 4-pyridoxate, citraconate, hypoxanthine, succinate/methylmalonate, thymine, uracil, and xylose (P ≤ 0.05). These metabolites were predominantly involved in amino acid and lipid metabolism. CONCLUSIONS: Rumen fluid metabolomes differ in steers of varying feed efficiencies. These metabolites may be used as biomarkers of feed efficiency, and may provide insight as to factors contributing to differences in feed efficiency that may be exploited to improve feed efficiency in beef cattle herds.