Effects of protein concentration and beta-adrenergic agonists on ruminal bacterial communities in finishing beef heifers.

To improve animal performance and modify growth by increasing lean tissue accretion, beef cattle production has relied on use of growth promoting technologies such as beta-adrenergic agonists. These synthetic catecholamines, combined with the variable inclusion of rumen degradable (RDP) and undegradable protein (RUP), improve feed efficiency and rate of gain in finishing beef cattle. However, research regarding the impact of beta-adrenergic agonists, protein level, and source on the ruminal microbiome is limited. The objective of this study was to determine the effect of different protein concentrations and beta-adrenergic agonist (ractopamine hydrochloride; RAC) on ruminal bacterial communities in finishing beef heifers. Heifers (n = 140) were ranked according to body weight and assigned to pens in a generalized complete block design with a 3 × 2 factorial arrangement of treatments of 6 different treatment combinations, containing 3 protein treatments (Control: 13.9% CP, 8.9% RDP, and 5.0% RUP; High RDP: 20.9% CP, 14.4% RDP, 6.5% RUP; or High RUP: 20.9% CP, 9.7% RDP, 11.2% RUP) and 2 RAC treatments (0 and 400 mg/day). Rumen samples were collected via orogastric tubing 7 days before harvest. DNA from rumen samples were sequenced to identify bacteria based on the V1-V3 hypervariable regions of the 16S rRNA gene. Reads from treatments were analyzed using the packages 'phyloseq' and 'dada2' within the R environment. Beta diversity was analyzed based on Bray-Curtis distances and was significantly different among protein and RAC treatments (P < 0.05). Alpha diversity metrics, such as Chao1 and Shannon diversity indices, were not significantly different (P > 0.05). Bacterial differences among treatments after analyses using PROC MIXED in SAS 9 were identified for the main effects of protein concentration (P < 0.05), rather than their interaction. These results suggest possible effects on microbial communities with different concentrations of protein but limited impact with RAC. However, both may potentially act synergistically to improve performance in finishing beef cattle.

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.

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.

Data of bacterial community dynamics resulting from total rumen content exchange in beef cattle.

OBJECTIVES: Extensive efforts have been made to characterize the rumen microbiome under various conditions. However, few studies have addressed the long-term impacts of ruminal microbiome dysbiosis and the extent of host control over microbiome stability. These data can also inform host-microbial symbioses. The objective was to develop preliminary data to measure the changes that occur in the rumen bacterial communities following a rumen content exchange to understand the effects major perturbations may impart upon the rumen microbiome, which may be host-driven. DATA DESCRIPTION: We report here an initial rumen content exchange between two SimAngus (Simmental/Angus) non-pregnant, non-lactating cows of ~ 6 years of age weighing 603.4 ± 37.5 kg. To measure bacterial community succession and acclimation following the exchange, rumen content was collected via rumen cannula at the beginning of the study immediately prior to and following the rumen content exchange, and weekly for 12 weeks. The V4 hypervariable region of the 16S rRNA gene was targeted for DNA sequencing and bacterial analysis. Over 12 weeks, numerous genera and diversity varied, before partial return to pre-exchange metrics. These preliminary data help support potential host control for the rumen microbiome, aiding in efforts to define bovine host-microbe relationships.

Classification of 16S rRNA reads is improved using a niche-specific database constructed by near-full length sequencing.

Surveys of microbial populations in environmental niches of interest often utilize sequence variation in the gene encoding the ribosomal small subunit (the 16S rRNA gene). Generally, these surveys target the 16S genes using semi-degenerate primers to amplify portions of a subset of bacterial species, sequence the amplicons in bulk, and assign to putative taxonomic categories by comparison to databases purporting to connect specific sequences in the main variable regions of the gene to specific organisms. Due to sequence length constraints of the most popular bulk sequencing platforms, the primers selected amplify one to three of the nine variable regions, and taxonomic assignment is based on relatively short stretches of sequence (150-500 bases). We demonstrate that taxonomic assignment is improved through reduced unassigned reads by including a survey of near-full-length sequences specific to the target environment, using a niche of interest represented by the upper respiratory tract (URT) of cattle. We created a custom Bovine URT database from these longer sequences for assignment of shorter, less expensive reads in comparisons of the upper respiratory tract among individual animals. This process improves the ability to detect changes in the microbial populations of a given environment, and the accuracy of defining the content of that environment at increasingly higher taxonomic resolution.