Gut microbiome and resistome characterization of pigs treated with commonly used post-weaning diarrhea treatments.

BACKGROUND: The global burden of antimicrobial resistance demands additional measures to ensure the sustainable and conscious use of antimicrobials. For the swine industry, the post-weaning period is critical and for many years, antimicrobials have been the most effective strategy to control and treat post-weaning related infections. Among them, post-weaning diarrhea causes vast economic losses, as it severely compromises piglets' health and growth performance. In this study, 210 piglets were transferred from a farm with recurrent cases of post-weaning diarrhea to an experimental farm and divided into six different treatment groups to determine the effect of the different treatments on the growth performance and survival, the microbiome, and the resistome in a cross-sectional and longitudinal study. The different treatments included antimicrobials trimethoprim/sulfamethoxazole, colistin, and gentamicin, an oral commercial vaccine, a control with water acidification, and an untreated control. An extra group remained at the farm of origin following the implemented amoxicillin routine treatment. A total of 280 fecal samples from pigs at four different sampling times were selected for metagenomics: before weaning-treatment at the farm of origin, and three days, two weeks, and four weeks post-treatment. RESULTS: The control group with water acidification showed a reduced death risk in the survival analyses and non-significant differences in average daily weight gain in comparison to the antibiotic-treated groups. However, the growth-promoting effect among antibiotic-treated groups was demonstrated when comparing against the untreated control group at the experimental farm. After four weeks of treatment, diversity indexes revealed significantly decreased diversity for the untreated control and the group that remained at the farm of origin treated with amoxicillin. For this last group, impaired microbial diversity could be related to the continuous amoxicillin treatment carried out at the farm. Analysis of the resistome showed that both gentamicin and amoxicillin treatments significantly contributed to the emergence of resistance, while trimethoprim/sulphonamide and colistin did not, suggesting that different treatments contribute differently to the emergence of resistance. CONCLUSIONS: Overall, this shotgun longitudinal metagenomics analysis demonstrates that non-antibiotic alternatives, such as water acidification, can contribute to reducing the emergence of antimicrobial resistance without compromising pig growth performance and gut microbiome.

Smart nanopaper based on cellulose nanofibers with hybrid PEDOT:PSS/polypyrrole for energy storage devices.

In the current work, flexible, lightweight, and strong conductive nanopapers based on cellulose nanofibers (CNFs) with poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) and/or polypyrrole (PPy) were prepared by following a mixing and in situ chemical polymerization method. A successful homogeneous coating of PEDOT:PSS on cellulose nanofibers occurred by means hydrogen-bonding interactions between the hydroxyl functionalized CNF and the electronically charged PEDOT:PSS, as shown by FTIR spectra. The electrical conductivity and the specific capacitance of CNF-PEDOT:PSS nanopapers were 2.58Scm-1 and 6.21Fg-1, respectively. Further coating of PPy produced a substantial improvement on the electrical conductivity (10.55Scm-1) and the specific capacitance (315.5Fg-1) of the resulting CNF-PEDOT:PSS-PPy nanopaper. A synergistic phenomenon between both conductive polymers supported the high electrical conductivity and specific capacitance of the ternary formulation. Moreover, CNF-PEDOT:PSS-PPy nanopaper showed higher mechanical properties and it was more flexible than the nanopaper containing only polypyrrole conducting polymer (CNF-PPy). It is concluded that the good mechanical, electrical and electrochemical properties of the ternary formulation can apply for smart nanopaper in flexible electronics and energy storage devices.

Carcass conformation and fat cover scores in beef cattle: a comparison of threshold linear models vs grouped data models.

BACKGROUND: Beef carcass conformation and fat cover scores are measured by subjective grading performed by trained technicians. The discrete nature of these scores is taken into account in genetic evaluations using a threshold model, which assumes an underlying continuous distribution called liability that can be modelled by different methods. METHODS: Five threshold models were compared in this study: three threshold linear models, one including slaughterhouse and sex effects, along with other systematic effects, with homogeneous thresholds and two extensions with heterogeneous thresholds that vary across slaughterhouses and across slaughterhouse and sex and a generalised linear model with reverse extreme value errors. For this last model, the underlying variable followed a Weibull distribution and was both a log-linear model and a grouped data model. The fifth model was an extension of grouped data models with score-dependent effects in order to allow for heterogeneous thresholds that vary across slaughterhouse and sex. Goodness-of-fit of these models was tested using the bootstrap methodology. Field data included 2,539 carcasses of the Bruna dels Pirineus beef cattle breed. RESULTS: Differences in carcass conformation and fat cover scores among slaughterhouses could not be totally captured by a systematic slaughterhouse effect, as fitted in the threshold linear model with homogeneous thresholds, and different thresholds per slaughterhouse were estimated using a slaughterhouse-specific threshold model. This model fixed most of the deficiencies when stratification by slaughterhouse was done, but it still failed to correctly fit frequencies stratified by sex, especially for fat cover, as 5 of the 8 current percentages were not included within the bootstrap interval. This indicates that scoring varied with sex and a specific sex per slaughterhouse threshold linear model should be used in order to guarantee the goodness-of-fit of the genetic evaluation model. This was also observed in grouped data models that avoided fitting deficiencies when slaughterhouse and sex effects were score-dependent. CONCLUSIONS: Both threshold linear models and grouped data models can guarantee the goodness-of-fit of the genetic evaluation for carcass conformation and fat cover, but our results highlight the need for specific thresholds by sex and slaughterhouse in order to avoid fitting deficiencies.

Connectedness among herds of beef cattle bred under natural service.

BACKGROUND: A procedure to measure connectedness among herds was applied to a beef cattle population bred by natural service. It consists of two steps: (a) computing coefficients of determination (CDs) of comparisons among herds; and (b) building sets of connected herds. METHODS: The CDs of comparisons among herds were calculated using a sampling-based method that estimates empirical variances of true and predicted breeding values from a simulated n-sample. Once the CD matrix was estimated, a clustering method that can handle a large number of comparisons was applied to build compact clusters of connected herds of the Bruna dels Pirineus beef cattle. Since in this breed, natural service is predominant and there are almost no links with reference sires, to estimate CDs, an animal model was used taking into consideration all pedigree information and, especially, the connections with dams. A sensitivity analysis was performed to contrast single-trait sire and animal model evaluations with different heritabilities, multiple-trait animal model evaluations with different degrees of genetic correlations and models with maternal effects. RESULTS: Using a sire model, the percentage of connected herds was very low even for highly heritable traits whereas with an animal model, most of the herds of the breed were well connected and high CD values were obtained among them, especially for highly heritable traits (the mean of average CD per herd was 0.535 for a simulated heritability of 0.40). For the lowly heritable traits, the average CD increased from 0.310 in the single-trait evaluation to 0.319 and 0.354 in the multi-trait evaluation with moderate and high genetic correlations, respectively. In models with maternal effects, the average CD per herd for the direct effects was similar to that from single-trait evaluations. For the maternal effects, the average CD per herd increased if the maternal effects had a high genetic correlation with the direct effects, but the percentage of connected herds for maternal effects was very low, less than 12%. CONCLUSIONS: The degree of connectedness in a bovine population bred by natural service mating, such as Bruna del Pirineus beef cattle, measured as the CD of comparisons among herds, is high. It is possible to define a pool of animals for which estimated breeding values can be compared after an across-herds genetic evaluation, especially for highly heritable traits.

A strategy for QTL fine-mapping using a dense SNP map.

BACKGROUND: Dense marker maps require efficient statistical methods for QTL fine mapping that work fast and efficiently with a large number of markers. In this study, the simulated dataset for the XIIth QTLMAS workshop was analyzed using a QTL fine mapping set of tools. METHODS: The QTL fine-mapping strategy was based on the use of statistical methods combining linkage and linkage disequilibrium analysis. Variance component based linkage analysis provided confidence intervals for the QTL. Within these regions, two additional analyses combining both linkage analysis and linkage disequilibrium information were applied. The first method estimated identity-by-descent probabilities among base haplotypes that were used to group them in different clusters. The second method constructed haplotype groups based on identity-by-state probabilities. RESULTS: Two QTL explaining 9.4 and 3.3% of the genetic variance were found with high significance on chromosome 1 at positions 19.5 and 76.6 cM. On chromosome 2, two QTL were also detected at positions 26.0 and 53.2 explaining respectively 9.0 and 7.8 of total genetic variance. The QTL detected on chromosome 3 at position 11.9 cM (5% of variance) was less important. The QTL with the highest effect (37% of variance) was detected on chromosome 4 at position 3.1 cM and another QTL (13.6% of variance) was detected on chromosome 5 at position 93.9 cM. CONCLUSION: The proposed strategy for fine-mapping of QTL combining linkage and linkage disequilibrium analysis allowed detecting the most important QTL with an additive effect in a short period but it should be extended in the future in order to fine-map linked and epistatic QTL.

Data transformation for rank reduction in multi-trait MACE model for international bull comparison.

Since many countries use multiple lactation random regression test day models in national evaluations for milk production traits, a random regression multiple across-country evaluation (MACE) model permitting a variable number of correlated traits per country should be used in international dairy evaluations. In order to reduce the number of within country traits for international comparison, three different MACE models were implemented based on German daughter yield deviation data and compared to the random regression MACE. The multiple lactation MACE model analysed daughter yield deviations on a lactation basis reducing the rank from nine random regression coefficients to three lactations. The lactation breeding values were very accurate for old bulls, but not for the youngest bulls with daughters with short lactations. The other two models applied principal component analysis as the dimension reduction technique: one based on eigenvalues of a genetic correlation matrix and the other on eigenvalues of a combined lactation matrix. The first one showed that German data can be transformed from nine traits to five eigenfunctions without losing much accuracy in any of the estimated random regression coefficients. The second one allowed performing rank reductions to three eigenfunctions without having the problem of young bulls with daughters with short lactations.

Validation of an approximate approach to compute genetic correlations between longevity and linear traits.

The estimation of genetic correlations between a nonlinear trait such as longevity and linear traits is computationally difficult on large datasets. A two-step approach was proposed and was checked via simulation. First, univariate analyses were performed to get genetic variance estimates and to compute pseudo-records and their associated weights. These pseudo-records were virtual performances free of all environmental effects that can be used in a BLUP animal model, leading to the same breeding values as in the (possibly nonlinear) initial analyses. By combining these pseudo-records in a multiple trait model and fixing the genetic and residual variances to their values computed during the first step, we obtained correlation estimates by AI-REML and approximate MT-BLUP predicted breeding values that blend direct and indirect information on longevity. Mean genetic correlations and reliabilities obtained on simulated data confirmed the suitability of this approach in a wide range of situations. When nonzero residual correlations exist between traits, a sire model gave nearly unbiased estimates of genetic correlations, while the animal model estimates were biased upwards. Finally, when an incorrect genetic trend was simulated to lead to biased pseudo-records, a joint analysis including a time effect could adequately correct for this bias.