Background: Feed efficiency is a crucial parameter in swine production, given both its economic and environmental impact. The gut microbiota plays an essential role in nutrient digestibility and is, therefore, likely to affect feed efficiency. This study aimed to characterize feed efficiency, fatness traits, and gut microbiome composition in three major breeds of domesticated swine and investigate a possible link between feed efficiency and gut microbiota composition.Results: Average daily feed intake (ADFI), average daily gain (ADG), feed conversion ratio (FCR), residual feed intake (RFI), backfat, loin depth, and intramuscular fat of 615 pigs belonging to the Duroc (DR), Landrace (LR), and Large White (LW) breeds were measured. Gut microbiota composition was characterized by 16S rRNA gene sequencing. Orthogonal contrasts between paternal line (DR) and maternal lines (LR+LW) and between the two maternal lines (LR versus LW) were performed. Average daily feed intake and ADG were statistically different with DR having lower ADFI and ADG compared to LR and LW. Landrace and LW had a similar ADG and RFI, with higher ADFI and FCR for LW. Alpha diversity was higher in the fecal microbial communities of LR pigs than in those of DR and LW pigs for all time points considered. Duroc communities had significantly higher proportional representation of theCatenibacteriumandClostridiumgenera compared to LR and LW, while LR pigs had significantly higher proportions ofBacteroidesthan LW for all time points considered. Amplicon sequence variants from multiple genera (includingAnaerovibrio,Bacteroides,Blautia,Clostridium,Dorea,Eubacterium,Faecalibacterium,Lactobacillus,Oscillibacter, andRuminococcus) were found to be significantly associated with feed efficiency, regardless of the time point considered.Conclusions: In this study, we characterized differences in the composition of the fecal microbiota of three commercially relevant breeds of swine, both over time and between breeds. Correlations between different microbiome compositions and feed efficiency were established. This suggests that the microbial community may contribute to shaping host productive parameters. Moreover, our study provides important insights into how the intestinal microbial community might influence host energy harvesting capacity. A deeper understanding of this process may allow us to modulate the gut microbiome in order to raise more efficient animals.

Background: The interplay between the gut microbiota and feeding behavior has consequences for host metabolism and health. The present study aimed to explore gut microbiota overall influence on feeding behavior traits and to identify specific microbes associated with the traits in three commercial swine breeds at three growth stages. Feeding behavior measures were obtained from 651 pigs of three breeds (Duroc, Landrace, and Large White) from an average 73 to 163 days of age. Seven feeding behavior traits covered the information of feed intake, feeder occupation time, feeding rate, and the number of visits to the feeder. Rectal swabs were collected from each pig at 73 ± 3, 123 ± 4, and 158 ± 4 days of age. DNA was extracted and subjected to 16 S rRNA gene sequencing. Results: Differences in feeding behavior traits among breeds during each period were found. The proportion of phenotypic variances of feeding behavior explained by the gut microbial composition was small to moderate (ranged from 0.09 to 0.31). A total of 21, 10, and 35 amplicon sequence variants were found to be significantly (q-value < 0.05) associated with feeding behavior traits for Duroc, Landrace, and Large White across the three sampling time points. The identified amplicon sequence variants were annotated to five phyla, with Firmicutes being the most abundant. Those amplicon sequence variants were assigned to 28 genera, mainly including Christensenellaceae_R-7_group, Ruminococcaceae_UCG-004, Dorea, Ruminococcaceae_UCG-014, and Marvinbryantia. Conclusions: This study demonstrated the importance of the gut microbial composition in interacting with the host feeding behavior and identified multiple archaea and bacteria associated with feeding behavior measures in pigs from either Duroc, Landrace, or Large White breeds at three growth stages. Our study provides insight into the interaction between gut microbiota and feeding behavior and highlights the genetic background and age effects in swine microbial studies.

In pigs, gut bacteria have been shown to play important roles in nutritional, physiological, and immunological processes in the host. However, the contribution of their metagenomes or part of them, which are normally reflected by fragments of 16S rRNA-encoding genes, has yet to be fully investigated. Fecal samples, collected from a population of crossbred pigs at three time points, including weaning, week 15 post weaning (hereafter “week 15”), and end-of-feeding test (hereafter “off-test”), were used to evaluate changes in the composition of the fecal microbiome of each animal over time. This study used 1205, 1295, and 1283 samples collected at weaning, week 15, and off-test, respectively. There were 1039 animals that had samples collected at all three time points and also had phenotypic records on back fat thickness (BF) and average daily body weight gain (ADG). Firmicutes and Bacteroidetes were the most abundant phyla at all three time points. The most abundant genera at all three time points included Clostridium, Escherichia, Bacteroides, Prevotella, Ruminococcus, Fusobacterium, Campylobacter, Eubacterium, and Lactobacillus. Two enterotypes were identified at each time point. However, only enterotypes at week 15 and off-test were significantly associated with BF. We report herein two novel findings: (i) alpha diversity and operational taxonomic unit (OTU) richness were moderately heritable at week 15, h2 of 0.15 ± 0.06 to 0.16 ± 0.07 and 0.23 ± 0.09 to 0.26 ± 0.08, respectively, as well as at off-test, h2 of 0.20 ± 0.09 to 0.33 ± 0.10 and 0.17 ± 0.08 to 0.24 ± 0.08, respectively, whereas very low heritability estimates for both measures were detected at weaning; and (ii) alpha diversity at week 15 had strong and negative genetic correlations with BF, − 0.53 ± 0.23 to − 0.45 ± 0.25, as well as with ADG, − 0.53 ± 0.32 to − 0.53 ± 0.29. These results are important for efforts to genetically improve the domesticated pig because they suggest fecal microbiota diversity can be used as an indicator trait to improve traits that are expensive to measure.

Clinical mastitis (CM) is one of the health disorders with large impacts on dairy farming profitability and animal welfare. The objective of this study was to perform a genome-wide association study (GWAS) for CM in first-lactation Holstein. Producer-recorded mastitis event information for 103,585 first-lactation cows were used, together with genotype information on 1,361 bulls from the Illumina BovineSNP50 BeadChip. Single-step genomic-BLUP methodology was used to incorporate genomic data into a threshold-liability model. Association analysis confirmed that CM follows a highly polygenic mode of inheritance. However, 10-adjacent-SNP windows showed that regions on chromosomes 2, 14 and 20 have impacts on genetic variation for CM. Some of the genes located on chromosome 14 (LY6K, LY6D, LYNX1, LYPD2, SLURP1, PSCA) are part of the lymphocyte-antigen-6 complex (LY6) known for its neutrophil regulation function linked to the major histocompatibility complex. Other genes on chromosome 2 were also involved in regulating immune response (IFIH1, LY75, and DPP4), or are themselves regulated in the presence of specific pathogens (ITGB6, NR4A2). Other genes annotated on chromosome 20 are involved in mammary gland metabolism (GHR, OXCT1), antibody production and phagocytosis of bacterial cells (C6, C7, C9, C1QTNF3), tumor suppression (DAB2), involution of mammary epithelium (OSMR) and cytokine regulation (PRLR). DAVID enrichment analysis revealed 5 KEGG pathways. The JAK-STAT signaling pathway (cell proliferation and apoptosis) and the ‘Cytokine-cytokine receptor interaction’ (cytokine and interleukines response to infectious agents) are co-regulated and linked to the ‘ABC transporters’ pathway also found here. Gene network analysis performed using GeneMania revealed a co-expression network where 665 interactions existed among 145 of the genes reported above. Clinical mastitis is a complex trait and the different genes regulating immune response are known to be pathogen-specific. Despite the lack of information in this study, candidate QTL for CM were identified in the US Holstein population.

The objectives were to evaluate (1) the use of 2 types of experimental silos (S) to characterize whole-crop oat (Avena sativa L.) silage with or without addition of an inoculant (I), and (2) the effect of inoculation on the microbial community structure of oats ensiled using only plastic bucket silos (BKT). From each of 6 sections in a field, oats were harvested, treated (INO) or not (CON) with inoculant, packed into 19-L BKT or vacuum bags (BG), and ensiled for 217 d. The inoculant added contained Lactobacillus buchneri and Pediococcus pentosaceus (4 × 105 and 1 × 105 cfu/g of fresh oats, respectively). The experimental design was a complete randomized design replicated 6 times. Treatment design was the factorial combination of 2 S × 2 I. Some differences existed between BG versus BKT at silo opening (217 d), including a decreased CP (7.73 vs. 7.04 ± 0.247% of DM) and ethanol (1.93 vs. 1.55 ± 0.155) and increased lactic acid (4.28 vs. 3.65 ± 0.241), respectively. Also, WSC and mold counts were reduced in BG versus BKT for CON (1.78 vs. 2.70 ± 0.162% of DM and 0.8 vs. 2.82 ± 0.409 log cfu/fresh g) but not for INO (∼1.53 and 1.55), respectively. Application of INO increased DM recovery (96.1 vs. 92.9 ± 0.63%), aerobic stability (565 vs. 133 ± 29.2 h), acetic acid (2.38 vs. 1.22 ± 0.116% of DM), and reduced NDF (65.0 vs. 67.0 ± 0.57), ADF (36.7 vs. 38.1 ± 0.60), ethanol (0.63 vs. 2.85 ± 0.155), and yeast counts (1.10 vs. 4.13 ± 0.484 log cfu/fresh g) in INO versus CON, respectively. At d 0, no differences were found for S and I on the nutritional composition and background microbial counts. Leuconostocaceae (82.9 ± 4.27%) and Enterobacteriaceae (15.2 ± 3.52) were the predominant bacterial families and unidentified sequences were predominant for fungi. A higher relative abundance of the Davidiellaceae fungal family (34.3 vs. 19.6 ± 4.47) was observed in INO versus CON. At opening (217 d), INO had a lower relative abundance of Leuconostocaceae (42.3 vs. 95.8 ± 4.64) and higher Lactobacillaceae (57.4 vs. 3.9 ± 4.65) versus CON. Despite several differences were found between BKT and BG, both techniques can be comparable for characterizing effects of INO on the most basic measures used in silage evaluation. The use of inoculant improved oat silage quality partially by a shift in the bacterial community composition during ensiling, which mainly consisted of an increased relative abundance of Lactobacillaceae and reduction of Leuconostocaceae relative to CON.

Despite recent efforts to characterize longitudinal variation in the swine gut microbiome, the extent to which a host’s genome impacts the composition of its gut microbiome is not yet well understood in pigs. The objectives of this study were: i) to identify pig gut microbiome features associated with growth and fatness, ii) to estimate the heritability of those features, and, iii) to conduct a genome-wide association study exploring the relationship between those features and single nucleotide polymorphisms (SNP) in the pig genome. A total of 1,028 pigs were characterized. Animals were genotyped with the Illumina PorcineSNP60 Beadchip. Microbiome samples from fecal swabs were obtained at weaning (Wean), at mid-test during the growth trial (MidTest), and at the end of the growth trial (OffTest). Average daily gain was calculated from birth to week 14 of the growth trial, from weaning to week 14, from week 14 to week 22, and from week 14 to harvest. Backfat and loin depth were also measured at weeks 14 and 22. Heritability estimates (±SE) of Operational Taxonomic Units ranged from 0.025 (±0.0002) to 0.139 (±0.003), from 0.029 (±0.003) to 0.289 (±0.004), and from 0.025 (±0.003) to 0.545 (±0.034) at Wean, MidTest, and OffTest, respectively. Several SNP were significantly associated with taxa at the three time points. These SNP were located in genomic regions containing a total of 68 genes. This study provides new evidence linking gut microbiome composition with growth and carcass traits in swine, while also identifying putative host genetic markers associated with significant differences in the abundance of several prevalent microbiome features.