Microbiome composition as a potential predictor of longevity in rabbits.

BACKGROUND: Longevity and resilience are two fundamental traits for more sustainable livestock production. These traits are closely related, as resilient animals tend to have longer lifespans. An interesting criterion for increasing longevity in rabbit could be based on the information provided by its gut microbiome. The gut microbiome is essential for regulating health and plays crucial roles in the development of the immune system. The aim of this research was to investigate if animals with different longevities have different microbial profiles. We sequenced the 16S rRNA gene from soft faeces from 95 does. First, we compared two maternal rabbit lines with different longevities; a standard longevity maternal line (A) and a maternal line (LP) that was founded based on longevity criteria: females with a minimum of 25 parities with an average prolificacy per parity of 9 or more. Second, we compared the gut microbiota of two groups of animals from line LP with different longevities: females that died/were culled with two parities or less (LLP) and females with more than 15 parities (HLP). RESULTS: Differences in alpha and beta diversity were observed between lines A and LP, and a partial least square discriminant analysis (PLS-DA) showed a high prediction accuracy (> 91%) of classification of animals to line A versus LP (146 amplicon sequence variants (ASV)). The PLS-DA also showed a high prediction accuracy (> 94%) to classify animals to the LLP and HLP groups (53 ASV). Interestingly, some of the most important taxa identified in the PLS-DA were common to both comparisons (Akkermansia, Christensenellaceae R-7, Uncultured Eubacteriaceae, among others) and have been reported to be related to resilience and longevity. CONCLUSIONS: Our results indicate that the first parity gut microbiome profile differs between the two rabbit maternal lines (A and LP) and, to a lesser extent, between animals of line LP with different longevities (LLP and HLP). Several genera were able to discriminate animals from the two lines and animals with different longevities, which shows that the gut microbiome could be used as a predictive factor for longevity, or as a selection criterion for these traits.

Modulation of Caecal Microbiota and Metabolome Profile in Salmonella-Infected Broilers by Phage Therapy.

Bacteriophage therapy is considered one of the most promising tools to control zoonotic bacteria, such as Salmonella, in broiler production. Phages exhibit high specificity for their targeted bacterial hosts, causing minimal disruption to the niche microbiota. However, data on the gut environment's response to phage therapy in poultry are limited. This study investigated the influence of Salmonella phage on host physiology through caecal microbiota and metabolome modulation using high-throughput 16S rRNA gene sequencing and an untargeted metabolomics approach. We employed 24 caecum content samples and 24 blood serum samples from 4-, 5- and 6-week-old broilers from a previous study where Salmonella phages were administered via feed in Salmonella-infected broilers, which were individually weighed weekly. Phage therapy did not affect the alpha or beta diversity of the microbiota. Specifically, we observed changes in the relative abundance of 14 out of the 110 genera using the PLS-DA and Bayes approaches. On the other hand, we noted changes in the caecal metabolites (63 up-accumulated and 37 down-accumulated out of the 1113 caecal metabolites). Nevertheless, the minimal changes in blood serum suggest a non-significant physiological response. The application of Salmonella phages under production conditions modulates the caecal microbiome and metabolome profiles in broilers without impacting the host physiology in terms of growth performance.

Selection for environmental variance shifted the gut microbiome composition driving animal resilience.

BACKGROUND: Understanding how the host's microbiome shapes phenotypes and participates in the host response to selection is fundamental for evolutionists and animal and plant breeders. Currently, selection for resilience is considered a critical step in improving the sustainability of livestock systems. Environmental variance (V E), the within-individual variance of a trait, has been successfully used as a proxy for animal resilience. Selection for reduced V E could effectively shift gut microbiome composition; reshape the inflammatory response, triglyceride, and cholesterol levels; and drive animal resilience. This study aimed to determine the gut microbiome composition underlying the V E of litter size (LS), for which we performed a metagenomic analysis in two rabbit populations divergently selected for low (n = 36) and high (n = 34) V E of LS. Partial least square-discriminant analysis and alpha- and beta-diversity were computed to determine the differences in gut microbiome composition among the rabbit populations. RESULTS: We identified 116 KEGG IDs, 164 COG IDs, and 32 species with differences in abundance between the two rabbit populations studied. These variables achieved a classification performance of the V E rabbit populations of over than 80%. Compared to the high V E population, the low V E (resilient) population was characterized by an underrepresentation of Megasphaera sp., Acetatifactor muris, Bacteroidetes rodentium, Ruminococcus bromii, Bacteroidetes togonis, and Eggerthella sp. and greater abundances of Alistipes shahii, Alistipes putredinis, Odoribacter splanchnicus, Limosilactobacillus fermentum, and Sutterella, among others. Differences in abundance were also found in pathways related to biofilm formation, quorum sensing, glutamate, and amino acid aromatic metabolism. All these results suggest differences in gut immunity modulation, closely related to resilience. CONCLUSIONS: This is the first study to show that selection for V E of LS can shift the gut microbiome composition. The results revealed differences in microbiome composition related to gut immunity modulation, which could contribute to the differences in resilience among rabbit populations. The selection-driven shifts in gut microbiome composition should make a substantial contribution to the remarkable genetic response observed in the V E rabbit populations. Video Abstract.

Incorporation of feeding behaviour traits to increase the genetic gain of feed efficiency in Pietrain pigs.

Improved feed efficiency is an essential goal for the sustainability of pig production in economic and environmental terms. Traits such as feed conversion rate (FCR), residual feed intake (RFI), residual body weight gain (RG) and feeding behaviour, such as duration (TPV) and feeding rate per visit (FR) can now be measured by automatic feeding systems. The aim of this study was to evaluate the benefits of incorporating feeding behaviour traits into a selection index to improve feed efficiency in a nucleus of purebred Pietrain pigs. Data on body weight, feed intake and duration were recorded at each visit in 1608 animals. The information contained in 843,605 visits was grouped by animal ID to obtain a set of feed efficiency and feeding behaviour traits. These traits were obtained in three periods (first, second and total period). Bayesian models were built to estimate the posterior marginal distribution of the variance components. The heritabilities were between 0.44 and 0.59 for feeding behaviour traits and between 0.31 and 0.49 for feed efficiency traits. The FCR and RFI showed a considerable genetic correlation with daily feed intake (~0.65). FCR showed a genetic correlation with feeding behaviour traits, such as feed intake per visit (FPV) (0.44) and FR (0.33). Furthermore, the fast-eating pigs were less efficient. This was due to the positive genetic correlation found between the FR and the FCR (0.33) and the RFI (0.23), and the negative correlation found with the RG (-0.28). On the other hand, the inclusion of the feeding behaviour traits into a selection index slightly increased the selection response for FCR (4%) and RFI (1.8%). However, there was an increase of up to 19% in the selection response for RG and an improvement in accuracy from 0.59 to 0.70. Therefore, we concluded that it would be interesting to include feeding behaviour traits in a selection index to improve the selection response and accuracy of feed efficiency traits.

Effect of environmental variance-based resilience selection on the gut metabolome of rabbits.

BACKGROUND: Gut metabolites are key actors in host-microbiota crosstalk with effect on health. The study of the gut metabolome is an emerging topic in livestock, which can help understand its effect on key traits such as animal resilience and welfare. Animal resilience has now become a major trait of interest because of the high demand for more sustainable production. Composition of the gut microbiome can reveal mechanisms that underlie animal resilience because of its influence on host immunity. Environmental variance (VE), specifically the residual variance, is one measure of resilience. The aim of this study was to identify gut metabolites that underlie differences in the resilience potential of animals originating from a divergent selection for VE of litter size (LS). We performed an untargeted gut metabolome analysis in two divergent rabbit populations for low (n = 13) and high (n = 13) VE of LS. Partial least square-discriminant analysis was undertaken, and Bayesian statistics were computed to determine dissimilarities in the gut metabolites between these two rabbit populations. RESULTS: We identified 15 metabolites that discriminate rabbits from the divergent populations with a prediction performance of 99.2% and 90.4% for the resilient and non-resilient populations, respectively. These metabolites were suggested to be biomarkers of animal resilience as they were the most reliable. Among these, five that derived from the microbiota metabolism (3-(4-hydroxyphenyl)lactate, 5-aminovalerate, and equol, N6-acetyllysine, and serine), were suggested to be indicators of dissimilarities in the microbiome composition between the rabbit populations. The abundances of acylcarnitines and metabolites derived from the phenylalanine, tyrosine, and tryptophan metabolism were low in the resilient population and these pathways can, therefore impact the inflammatory response and health status of animals. CONCLUSIONS: This is the first study to identify gut metabolites that could act as potential resilience biomarkers. The results support differences in resilience between the two studied rabbit populations that were generated by selection for VE of LS. Furthermore, selection for VE of LS modified the gut metabolome, which could be another factor that modulates animal resilience. Further studies are needed to determine the causal role of these metabolites in health and disease.

Examining the effects of Salmonella phage on the caecal microbiota and metabolome features in Salmonella-free broilers.

Bacteriophages selectively infect and kill their target bacterial host, being a promising approach to controlling zoonotic bacteria in poultry production. To ensure confidence in its use, fundamental questions of safety and toxicity monitoring of phage therapy should be raised. Due to its high specificity, a minimal impact on the gut ecology is expected; however, more in-depth research into key parameters that influence the success of phage interventions has been needed to reach a consensus on the impact of bacteriophage therapy in the gut. In this context, this study aimed to investigate the interaction of phages with animals; more specifically, we compared the caecum microbiome and metabolome after a Salmonella phage challenge in Salmonella-free broilers, evaluating the role of the phage administration route. To this end, we employed 45 caecum content samples from a previous study where Salmonella phages were administered via drinking water or feed for 24 h from 4, 5 to 6-weeks-old broilers. High-throughput 16S rRNA gene sequencing showed a high level of similarity (beta diversity) but revealed a significant change in alpha diversity between broilers with Salmonella-phage administered in the drinking water and control. Our results showed that the phages affected only a few genera of the microbiota's structure, regardless of the administration route. Among these, we found a significant increase in Streptococcus and Sellimonas in the drinking water and Lactobacillus, Anaeroplasma and Clostridia_vadinBB60_group in the feed. Nevertheless, the LC-HRMS-based metabolomics analyses revealed that despite few genera were significantly affected, a substantial number of metabolites, especially in the phage administered in the drinking water were significantly altered (64 and 14 in the drinking water and feed groups, respectively). Overall, our study shows that preventive therapy with bacteriophages minimally alters the caecal microbiota but significantly impacts their metabolites, regardless of the route of administration.

Selection for environmental variance of litter size in rabbits involves genes in pathways controlling animal resilience.

BACKGROUND: Environmental variance (VE) is partially under genetic control, which means that the VE of individuals that share the same environment can differ because they have different genotypes. Previously, a divergent selection experiment for VE of litter size (LS) during 13 generations in rabbit yielded a successful response and revealed differences in resilience between the divergent lines. The aim of the current study was to identify signatures of selection in these divergent lines to better understand the molecular mechanisms and pathways that control VE of LS and animal resilience. Three methods (FST, ROH and varLD) were used to identify signatures of selection in a set of 473 genotypes from these rabbit lines (377) and a base population (96). A whole-genome sequencing (WGS) analysis was performed on 54 animals to detect genes with functional mutations. RESULTS: By combining signatures of selection and WGS data, we detected 373 genes with functional mutations in their transcription units, among which 111 had functions related to the immune system, stress response, reproduction and embryo development, and/or carbohydrate and lipid metabolism. The genes TTC23L, FBXL20, GHDC, ENSOCUG00000031631, SLC18A1, CD300LG, MC2R, and ENSOCUG00000006264 were particularly relevant, since each one carried a functional mutation that was fixed in one of the rabbit lines and absent in the other line. In the 3'UTR region of the MC2R and ENSOCUG00000006264 genes, we detected a novel insertion/deletion (INDEL) variant. CONCLUSIONS: Our findings provide further evidence in favour of VE as a measure of animal resilience. Signatures of selection were identified for VE of LS in genes that have a functional mutation in their transcription units and are mostly implicated in the immune response and stress response pathways. However, the real implications of these genes for VE and animal resilience will need to be assessed through functional analyses.

Identification of functional mutations associated with environmental variance of litter size in rabbits.

BACKGROUND: Environmental variance (VE) is partly under genetic control and has recently been proposed as a measure of resilience. Unravelling the genetic background of the VE of complex traits could help to improve resilience of livestock and stabilize their production across farming systems. The objective of this study was to identify genes and functional mutations associated with variation in VE of litter size (LS) in rabbits. To achieve this, we combined the results of a genome-wide association study (GWAS) and a whole-genome sequencing (WGS) analysis using data from two divergently selected rabbit lines for high and low VE of LS. These lines differ in terms of biomarkers of immune response and mortality. Moreover, rabbits with a lower VE of LS were found to be more resilient to infections than animals with a higher VE of LS. RESULTS: By using two GWAS approaches (single-marker regression and Bayesian multiple-marker regression), we identified four genomic regions associated with VE of LS, on chromosomes 3, 7, 10, and 14. We detected 38 genes in the associated genomic regions and, using WGS, we identified 129 variants in the splicing, UTR, and coding (missense and frameshift effects) regions of 16 of these 38 genes. These genes were related to the immune system, the development of sensory structures, and stress responses. All of these variants (except one) segregated in one of the rabbit lines and were absent (n = 91) or fixed in the other one (n = 37). The fixed variants were in the HDAC9, ITGB8, MIS18A, ENSOCUG00000021276 and URB1 genes. We also identified a 1-bp deletion in the 3'UTR region of the HUNK gene that was fixed in the low VE line and absent in the high VE line. CONCLUSIONS: This is the first study that combines GWAS and WGS analyses to study the genetic basis of VE. The new candidate genes and functional mutations identified in this study suggest that the VE of LS is under the control of functions related to the immune system, stress response, and the nervous system. These findings could also explain differences in resilience between rabbits with homogeneous and heterogeneous VE of litter size.