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Selection for feed efficiency elicits different postprandial plasma metabolite profiles in response to poor hygiene of housing conditions in growing pigs.

ABSTRACT: This study was conducted to compare postprandial plasma concentrations of insulin, energy-related metabolites, and amino acids measured after a 6-week challenge consisting of exposure to good or poor hygiene of housing conditions of 24 growing pigs divergently selected for low-RFI (LRFI) and high-RFI (HRFI). Blood indicators of immune responses were assessed from samples collected before 0 (W0), and 3 (W3), and 6 weeks (W6) after pigs transfer to their respective hygiene of housing conditions. Plasma haptoglobin concentrations and blood neutrophil granulocyte numbers were greater in poor than in good hygiene of housing conditions at W3. Plasma concentrations of total immunoglobulin G were greater (p = 0.04) in poor than in good hygiene of housing conditions at W6. At W6, pigs were fitted with an intravenous catheter for serial blood samplings. Low-RFI pigs had greater insulin (p < 0.001) and lower triglyceride (p = 0.04) average plasma concentrations than HRFI pigs in both conditions. In poor hygiene of housing conditions, the peaks of insulin and glucose were observed earlier and that of insulin was greater in LRFI than in HRFI pigs. Irrespective of genetic line, average plasma concentrations of histidine, isoleucine, leucine, methionine, threonine, valine, and alanine were greater in poor compared with good hygiene of housing conditions. Only HRFI pigs had greater lysine, asparagine, proline, and tyrosine plasma concentrations in poor than in good hygiene of housing conditions. Conversely, arginine, tryptophan, proline, and tyrosine plasma concentrations were lower only for LRFI pigs housed in poor hygiene conditions. Our results suggest that, contrary to HRFI, LRFI pigs increase or maintain their utilization of tryptophan, arginine, and lysine when housed in poor hygiene conditions. This indicates that this difference may contribute to the better capacity of LRFI to cope with poor hygiene of housing conditions.

SUBMITTER: Zem Fraga A

PROVIDER: S-EPMC8006997 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Poor hygiene of housing induces a systemic inflammatory response. Because inflammation and oxidative stress are processes that can sustain each other, the ways pigs are able to activate their antioxidant defenses are critical for production performance and health during periods when the immune system is solicited. Selection for production performance can also influence reactive oxygen species (ROS) production and expression levels of genes involved in cellular response to oxidative stress in different tissues. To establish the extent by which poor hygiene and selection for feed efficiency affected redox status, pigs divergently selected for residual feed intake (RFI) were housed in poor or good hygiene during 6 weeks. At the end, blood was collected in all pigs, and half of them were killed for tissue sampling. The remaining pigs were reared in good hygiene conditions during a recovery period of 7-8 weeks. RESULTS:At week 6, poor hygiene was associated with a lower total antioxidant capacity assessed by plasma ferric reducing ability in all pigs, and with greater plasma levels of hydrogen peroxides in the high RFI pigs (less efficient). Adipose tissue of high RFI pigs exhibited higher activities of catalase and glutathione reductase, and greater thiobarbituric acid reactive substances (TBARS) concentrations when compared with the low RFI pigs (more efficient). Poor hygiene conditions activated the antioxidant enzymes activities (glutathione reductase, superoxide dismutase and catalase) in adipose tissue of both lines, but led to higher ROS production by mature adipocytes isolated from the high RFI pigs only. In liver and muscle, there were only minor changes in antioxidant molecules due to genetics and hygiene conditions. After the resilience period, adipose tissue of pigs previously challenged by poor hygiene maintained higher antioxidant enzyme activities, and for the high RFI line, displayed higher TBARS concentrations. CONCLUSIONS:Pigs selected for improved feed efficiency showed a lower susceptibility to oxidative stress induced by poor hygiene conditions. This could led to a lower inflammatory response and less impaired growth when these pigs are facing sanitary challenges during the production period.

Project description:Metabolites represent the ultimate response of biological systems, so metabolomics is considered the link between genotypes and phenotypes. Feed efficiency is one of the most important phenotypes in sustainable pig production and is the main breeding goal trait. We utilized metabolic and genomic datasets from a total of 108 pigs from our own previously published studies that involved 59 Duroc and 49 Landrace pigs with data on feed efficiency (residual feed intake (RFI)), genotype (PorcineSNP80 BeadChip) data, and metabolomic data (45 final metabolite datasets derived from LC-MS system). Utilizing these datasets, our main aim was to identify genetic variants (single-nucleotide polymorphisms (SNPs)) that affect 45 different metabolite concentrations in plasma collected at the start and end of the performance testing of pigs categorized as high or low in their feed efficiency (based on RFI values). Genome-wide significant genetic variants could be then used as potential genetic or biomarkers in breeding programs for feed efficiency. The other objective was to reveal the biochemical mechanisms underlying genetic variation for pigs' feed efficiency. In order to achieve these objectives, we firstly conducted a metabolite genome-wide association study (mGWAS) based on mixed linear models and found 152 genome-wide significant SNPs (p-value < 1.06 × 10-6) in association with 17 metabolites that included 90 significant SNPs annotated to 52 genes. On chromosome one alone, 51 significant SNPs associated with isovalerylcarnitine and propionylcarnitine were found to be in strong linkage disequilibrium (LD). SNPs in strong LD annotated to FBXL4, and CCNC consisted of two haplotype blocks where three SNPs (ALGA0004000, ALGA0004041, and ALGA0004042) were in the intron regions of FBXL4 and CCNC. The interaction network revealed that CCNC and FBXL4 were linked by the hub gene N6AMT1 that was associated with isovalerylcarnitine and propionylcarnitine. Moreover, three metabolites (i.e., isovalerylcarnitine, propionylcarnitine, and pyruvic acid) were clustered in one group based on the low-high RFI pigs. This study performed a comprehensive metabolite-based genome-wide association study (GWAS) analysis for pigs with differences in feed efficiency and provided significant metabolites for which there is significant genetic variation as well as biological interaction networks. The identified metabolite genetic variants, genes, and networks in high versus low feed efficient pigs could be considered as potential genetic or biomarkers for feed efficiency.

Project description:Feed efficiency is one of the most important issues for sustainable pig production. Daily-phase feeding (DPF) is a form of precision feeding that could improve feed efficiency in pigs. Gut microbiota can regulate host nutrient digestion, absorption, and metabolism. However, which key microbes may play a vital role in improving the feed efficiency during DPF remains unclear. In the present study, we used a DPF program compared to a three-phase feeding (TPF) program in growing-finishing pigs to investigate the effects of gut microbiota on feed efficiency. A total of 204 Landrace × Yorkshire pigs (75 d) were randomly assigned into 2 treatments. Each treatment was replicated 8 times with 13 to 15 pigs per replicate pen. Pigs in the TPF group were fed with a commercial feeding program that supplied fixed feed for phases I, II, and III, starting at 81, 101, and 132 d of age, respectively, and pigs in the DPF group were fed a blend of adjacent phase feed from 81 to 155 d at a gradual daily ratio and phase III feed from 155 to 180 d of age. Daily feed intake and body weight were recorded by a computerized device in the feeders. Feces and blood samples were collected from 1 pig per replicate at 155 and 180 d of age. The results showed that the DPF program remarkably improved the feed efficiency at 155 d (P < 0.001) and 180 d of age (P < 0.001), with a significant reduction of the intake of crude protein (P < 0.01), net energy (P < 0.001), crude fiber (P < 0.001), ether extract (P < 0.01), and ash (P < 0.001). The daily-phase feeding program increased the abundance of Prevotella copri (P < 0.05) and Paraprevotella clara (P < 0.05), while it decreased the abundance of Ocilibacter (P < 0.05) at 155 d of age. The results of correlation analysis indicated that the differentially abundant microbiota communities were closely associated with 20 metabolites which enriched amino acid and phenylalanine metabolism. Our results suggest that 2 key microbes may contribute to feed efficiency during daily-phase feeding strategies in pigs.

Project description:Some definitions of feed efficiency such as residual energy intake (REI) and residual gain (RG) may not truly reflect production efficiency. The energy sinks used in the derivation of the traits include metabolic live-weight; producers finishing cattle for slaughter are, however, paid on the basis of carcass weight, as opposed to live-weight. The objective of the present study was to explore alternative definitions of REI and RG which are more reflective of production efficiency, and quantify their relationship with performance, ultrasound, and carcass traits across multiple breeds and sexes of cattle. Feed intake and live-weight records were available on 5,172 growing animals, 2,187 of which also had information relating to carcass traits; all animals were fed a concentrate-based diet representative of a feedlot diet. Animal linear mixed models were used to estimate (co)variance components. Heritability estimates for all derived REI traits varied from 0.36 (REICWF; REI using carcass weight and carcass fat as energy sinks) to 0.50 (traditional REI derived with the energy sinks of both live-weight and ADG). The heritability for the RG traits varied from 0.24 to 0.34. Phenotypic correlations among all definitions of the REI traits ranged from 0.90 (REI with REICWF) to 0.99 (traditional REI with REI using metabolic preslaughter live-weight and ADG). All were different (P < 0.001) from one suggesting reranking of animals when using different definitions of REI to identify efficient cattle. The derived RG traits were either weakly or not correlated (P > 0.05) with the ultrasound and carcass traits. Genetic correlations between the REI traits with carcass weight, dressing difference (i.e., live-weight immediately preslaughter minus carcass weight) and dressing percentage (i.e., carcass weight divided by live-weight immediately preslaughter) implies that selection on any of the REI traits will increase carcass weight, lower the dressing difference and increase dressing percentage. Selection on REICW (REI using carcass weight as an energy sink), as opposed to traditional REI, should increase the carcass weight 2.2 times slower but reduce the dressing difference 4.3 times faster. While traditionally defined REI is informative from a research perspective, the ability to convert energy into live-weight gain does not necessarily equate to carcass gain, and as such, traits such as REICW and REICWF provide a better description of production efficiency for feedlot cattle.

Project description:BackgroundImproving feed efficiency (FE) is an important goal due to its economic and environmental significance for farm animal production. The FE phenotype is complex and based on the measurements of the individual feed consumption and average daily gain during a test period, which is costly and time-consuming. The identification of reliable predictors of FE is a strategy to reduce phenotyping efforts.ResultsGene expression data of the whole blood from three independent experiments were combined and analyzed by machine learning algorithms to propose molecular biomarkers of FE traits in growing pigs. These datasets included Large White pigs from two lines divergently selected for residual feed intake (RFI), a measure of net FE, and in which individual feed conversion ratio (FCR) and blood microarray data were available. Merging the three datasets allowed considering FCR values (Mean = 2.85; Min = 1.92; Max = 5.00) for a total of n = 148 pigs, with a large range of body weight (15 to 115 kg) and different test period duration (2 to 9 weeks). Random forest (RF) and gradient tree boosting (GTB) were applied on the whole blood transcripts (26,687 annotated molecular probes) to identify the most important variables for binary classification on RFI groups and a quantitative prediction of FCR, respectively. The dataset was split into learning (n = 74) and validation sets (n = 74). With iterative steps for variable selection, about three hundred's (328 to 391) molecular probes participating in various biological pathways, were identified as important predictors of RFI or FCR. With the GTB algorithm, simpler models were proposed combining 34 expressed unique genes to classify pigs into RFI groups (100% of success), and 25 expressed unique genes to predict FCR values (R2 = 0.80, RMSE = 8%). The accuracy performance of RF models was slightly lower in classification and markedly lower in regression.ConclusionFrom small subsets of genes expressed in the whole blood, it is possible to predict the binary class and the individual value of feed efficiency. These predictive models offer good perspectives to identify animals with higher feed efficiency in precision farming applications.

Project description:BackgroundImproving feed efficiency (FE) is a major challenge in pig production. This complex trait is characterized by a high variability. Therefore, the identification of predictors of FE may be a relevant strategy to reduce phenotyping efforts in breeding and selection programs. The aim of this study was to investigate the suitability of expressed muscle genes in prediction of FE traits in growing pigs. The approach considered different transcriptomics experiments to cover a large range of FE values and identify reliable predictors.ResultsMicroarrays data were obtained from longissimus muscles of two lines divergently selected for residual feed intake (RFI). Pigs (n = 71) from three experiments belonged to generations 6 to 8 of selection, were fed either a diet with a standard composition or a diet rich in fiber and lipids, received feed ad libitum or at restricted level, and weighed between 80 and 115 kg at slaughter. For each pig, breeding value for RFI was estimated (RFI-BV), and feed conversion ratio (FCR) and energy-based feed conversion ratio (FCRe) were calculated during the test periods. Gradient boosting algorithms were used on the merged muscle transcriptomes to identify very important predictors of FE traits. About 20,405 annotated molecular probes were commonly expressed in longissimus muscle across experiments. Six to 267 expressed muscle genes covering a variety of biological processes were found as important predictors for RFI-BV (R2 = 0.63-0.65), FCR (R2 = 0.61-0.70) and FCRe (R2 = 0.49-0.52). The error of prediction was less than 8% for FCR. Altogether, 56 predictors were common to RFI-BV and FCR. Expression levels of 24 target genes were further measured by qPCR. Linear regression confirmed the good accuracy of combining mRNA levels of these genes to fit FE traits (RFI-BV: R2 = 0.73, FRC: R2 = 0.76; FCRe: R2 = 0.75). Stepwise regression procedure highlighted 10 genes (FKBP5, MUM1, AKAP12, FYN, TMED3, PHKB, TGF, SOCS6, ILR4, and FRAS1) in a linear combination predicting FCR and FCRe. In addition, FKBP5 and expression levels of five other genes (IGF2, SERINC3, CSRNP3, EZR and RPL16) significantly contributed to RFI-BV.ConclusionIt was possible to identify few genes expressed in muscle that might be reliable predictors of feed efficiency.

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Selection for feed efficiency elicits different postprandial plasma metabolite profiles in response to poor hygiene of housing conditions in growing pigs.

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