Supplementing interleukin-6 (IL6) to in vitro-produced bovine embryos increases inner cell mass (ICM) cell numbers in blastocysts. A series of studies were completed to further dissect this effect. Treatment with IL6 increased ICM cell numbers in early, regular and expanded blastocysts but had no effect on morulae total cell number. Treatment with IL6 for 30 min induced signal transducer and activator of transcription 3 (STAT3) phosphorylation and nuclear translocation in all blastomeres in early morulae and specifically within the ICM in blastocysts. Also, IL6 supplementation increased SOCS3 mRNA abundance, a STAT3-responsive gene, in blastocysts. Chemical inhibition of Janus kinase (JAK) activity from day 5 to day 8 prevented STAT3 activation and the IL6-induced ICM cell number increase. Global transcriptome analysis of blastocysts found that transcripts for IL6 and its receptor subunits (IL6R and IL6ST) were the most abundantly expressed IL6 family ligand and receptors. These results indicate that IL6 increases ICM cell numbers as the ICM lineage emerges at the early blastocyst stage through a STAT3-dependent mechanism. Also, IL6 appears to be the primary IL6 cytokine family member utilized by bovine blastocysts to control ICM cell numbers.
BackgroundGrazing mammals rely on their ruminal microbial symbionts to convert plant structural biomass into metabolites they can assimilate. To explore how this complex metabolic system adapts to the host animal’s diet, we inferred a microbiome-level metabolic network from shotgun metagenomic data.ResultsUsing comparative genomics, we then linked this microbial network to that of the host animal using a set of interface metabolites likely to be transferred to the host. When the host sheep were fed a grain-based diet, the induced microbial metabolic network showed several critical differences from those seen on the evolved forage-based diet. Grain-based (e.g., concentrate) diets tend to be dominated by a smaller set of reactions that employ metabolites that are nearer in network space to the host’s metabolism. In addition, these reactions are more central in the network and employ substrates with shorter carbon backbones. Despite this apparent lower complexity, the concentrate-associated metabolic networks are actually more dissimilar from each other than are those of forage-fed animals. Because both groups of animals were initially fed on a forage diet, we propose that the diet switch drove the appearance of a number of different microbial networks, including a degenerate network characterized by an inefficient use of dietary nutrients. We used network simulations to show that such disparate networks are not an unexpected result of a diet shift.ConclusionWe argue that network approaches, particularly those that link the microbial network with that of the host, illuminate aspects of the structure of the microbiome not seen from a strictly taxonomic perspective. In particular, different diets induce predictable and significant differences in the enzymes used by the microbiome. Nonetheless, there are clearly a number of microbiomes of differing structure that show similar functional properties. Changes such as a diet shift uncover more of this type of diversity.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-017-0274-6) contains supplementary material, which is available to authorized users.
We surveyed the ruminal metagenomes of 16 sheep under two different diets using Illumina pair-end DNA sequencing of raw microbial DNA extracted from rumen samples. The resulting sequence data were bioinformatically mapped to known prokaryotic 16S rDNA sequences to identify the taxa present in the samples and then analysed for the presence of potentially new taxa. Strikingly, the majority of the microbial individuals found did not map to known taxa from 16S sequence databases. We used a novel statistical modelling approach to compare the taxonomic distributions between animals fed a forage-based diet and those fed concentrated grains. With this model, we found significant differences between the two groups both in the dominant taxa present in the rumen and in the overall shape of the taxa abundance curves. In general, forage-fed animals have a more diverse microbial ecosystem, whereas the concentrate-fed animals have ruminal systems more heavily dominated by a few taxa. As expected, organisms from methanogenic groups are more prevalent in forage-fed animals. Finally, all of these differences appear to be grounded in an underlying common input of new microbial individuals into the rumen environment, with common organisms from one feed group being present in the other, but at much lower abundance.
The Beef Improvement Federation recommends residual feed intake (RFI) be calculated from 70-d tests preceded by a 21-d adjustment period. Individual animal feed intake and gain measurements are expensive and time consuming, which limits the number of animals available for national genetic evaluation of feed intake. If a shorter test period of comparable accuracy could be used, the cost would decrease and more animals could be tested annually. The objective of this study was to determine if data from shortened tests is equally as predictive of average daily DMI (ADMI) and RFI values from 70-d tests. Feed intake and weight measures were collected after weaning from Bos taurus bulls, steers, and heifers (n = 612) during four 70-d performance tests. For each individual, ADMI and RFI were calculated. Residual feed intake was calculated by regressing ADMI on metabolic midweight (MMWT) and ADG with the effect of breed included where appropriate. Based on four 70-d intake tests, ADMI, RFI, ADG, and MMWT were evaluated using shortened test lengths in a post hoc analysis where shortened test lengths were imposed on the full-period tests. The ADMI, RFI, ADG, and MMWT values from the full 70-d test were regressed on ADMI, RFI, ADG, and MMWT values resulting from the constructed shorter data subsets. The 8 subsets ranged from 14 to 56 d in length. The fixed effects of test, breed, animal's origin, and sex were included in each comparison for ADMI, ADG, and MMWT. Estimates for regression coefficients of ADMI values from a full test on various subsets ranged from 0.63 to 1.02. Likewise, estimated coefficients obtained from the regression of full test RFI, ADG, and MMWT values on subsets ranged from 0.50 to 1.00, 0.09 to 0.85, and 0.48 to 1.02, respectively. We conclude that ADMI values from a 42-d test ( < 0.0001) and RFI values from a 56-d test (P < 0.0001) adequately predict ADMI and RFI when compared to a 70-d test. These results suggest that testing periods of 42 d for determining ADMI and 56 d for RFI could ultimately reduce testing costs and result in collection of data on a larger number of animals per year, in turn resulting in more data for genetic evaluation.
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