Dataset Information

Comparison of Productivity and Fecal Microbiotas of Sows in Commercial Farms.

ABSTRACT: Sow productivity, that is, the number of weaned piglets per sow per year, depends on their health status. The gut microbiota is considered a crucial factor in the health of pigs and may affect sow productivity. In the present study, we aimed to investigate the relationship between productivity and the fecal microbiotas of sows in different farms. Feces of sows were collected from 18 farms (10 samples/farm). A total of 90 fecal samples of high-reproductive performance farms were labeled as group H, and 90 fecal samples from low-reproductive performance farms were labeled as group L. Fecal microbiotas were analyzed by 16S rRNA metagenomics, and the organic acids and putrefactive metabolites of the microbiotas were measured. ?-diversity was significantly different between groups H and L (P < 0.01), and the relative abundances of 43 bacterial genera, including short-chain fatty acid-producing and fiber-degrading bacteria such as Ruminococcus, Fibrobacter and Butyricicoccus, significantly differed between groups (P < 0.05). In addition, the concentrations of acetate, propionate and n-butyrate were significantly higher in group H than in group L (P < 0.05). In conclusion, sow productivity in farms was likely associated with the compositions of the fecal microbiotas.

SUBMITTER: Uryu H

PROVIDER: S-EPMC7599717 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Comparison of Productivity and Fecal Microbiotas of Sows in Commercial Farms.

Uryu Haruka H Tsukahara Takamitsu T Ishikawa Hiromichi H Oi Munetaka M Otake Satoshi S Yamane Itsuro I Inoue Ryo R

Microorganisms 20200924 10

Sow productivity, that is, the number of weaned piglets per sow per year, depends on their health status. The gut microbiota is considered a crucial factor in the health of pigs and may affect sow productivity. In the present study, we aimed to investigate the relationship between productivity and the fecal microbiotas of sows in different farms. Feces of sows were collected from 18 farms (10 samples/farm). A total of 90 fecal samples of high-reproductive performance farms were labeled as group ...[more]

PMID: 32987859

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Project description:Strategies to combat microbiota-associated health problems are of high interest in pig production. Successful intervention strategies with beneficial long-term effects are still missing. Most studies on pig microbiota have been conducted under standardized experimental conditions, but the situation in commercial farms differs dramatically. This study describes the fecal microbiota in German commercial pig farms under practical conditions. The study is part of the larger project "Optibiom" that aims to use bacterial composition and farm metadata to formulate tailor-made solutions for farm-specific health maintenance strategies. Special consideration is given to the sow-piglet relationship. Fecal samples from sows and their piglets were collected at two time points each in 20 different farms (sows ante- and postpartum and piglets before and after weaning). The extracted DNA was sequenced with Illumina 16S rDNA sequencing. For data analysis and visualization, differential abundance analyses, as well as hierarchical clustering and nonmetric multidimensional scaling (NMDS) were performed. A new "family unit" was implemented to compare farms based on the association between the microbiota in sows and their offspring. There are distinct changes in the microbial communities in sows before and after birth as well as in suckling and post-weaning piglets. The suckling pig microbiota is particularly different from all other groups and shows a lower bacterial diversity. While dominant genera in antepartum sows further displace the abundance of non-dominant genera postpartum, the opposite was true for piglets, where non-dominant bacteria in the suckling phase became dominant after weaning. The family unit for sows and their piglets led to separate cluster formation for some farms. The results indicate that the sow-piglet relationship is one driving force for the observed differences of the pig farms. The next step in the analysis will be the combination of metadata (feeding, housing and management practices) to find farm-specific differences that can be exploited to formulate a farm-specific health maintenance strategy.

Project description:BackgroundThe majority of chicken microbiota studies have used the ceca as a sampling site due to the specific role of ceca in chicken productivity, health and wellbeing. However, sampling from ceca and other gastrointestinal tract sections requires the bird to be sacrificed. In contrast, fecal sampling does not require sacrifice and thus allows the same bird to be sampled repeatedly over time. This is a more meaningful and preferred way of sampling as the same animals can be monitored and tracked for temporal studies. The commonly used practice of selecting a subset of birds at each time-point for sacrifice and sampling introduces added variability due to the known animal to animal variation in microbiota.ResultsCecal samples and fecal samples via cloacal swab were collected from 163 birds across 3 replicate trials. DNA was extracted and 16S rRNA gene sequences amplified and pyrosequenced to determine and compare the phylogenetic profile of the microbiota within each sample. The fecal and cecal samples were investigated to determine to what extent the microbiota found in fecal samples represented the microbiota of the ceca. It was found that 88.55% of all operational taxonomic units (OTUs), containing 99.25% of all sequences, were shared between the two sample types, with OTUs unique for each sample type found to be very rare. There was a positive correlation between cecal and fecal abundance in the shared sequences, however the two communities differed significantly in community structure, represented as either alpha or beta diversity. The microbial populations present within the paired ceca of individual birds were also compared and shown to be similar.ConclusionsFecal sample analysis captures a large percentage of the microbial diversity present in the ceca. However, the qualitative similarities in OTU presence are not a good representation of the proportions of OTUs within the microbiota from each sampling site. The fecal microbiota is qualitatively similar to cecal microbiota but quantitatively different. Fecal samples can be effectively used to detect some shifts and responses of cecal microbiota.

Project description:Rabbits are cecotrophic, hindgut-fermenters that rely heavily on their gastrointestinal microbiota for optimal digestion of plant-based diets. Dysbiosis, caused by disruption of the gastrointestinal microbiota, is known to predispose rabbits to rabbit enteritis complex (REC), a major cause of morbidity and mortality. The objectives of this study were to describe the fecal microbiota of domestic rabbits from a variety of settings (commercial meat, companion, laboratory, and shelter) and to identify how factors such as age, season, and routine antimicrobial use affect the fecal microbiota composition.A total of 86 pooled commercial meat, 54 companion, 14 pooled laboratory, and 14 shelter rabbit fecal samples were evaluated using 16S rRNA gene sequencing of the V4 region. In all sample types, the predominant bacterial phylum was Firmicutes. Other commonly identified phyla (composing ??1% of the total microbiota composition) were Verrucomicrobia, Proteobacteria, and Bacteroidetes. Significant differences in composition were noted between commercial, companion, laboratory, and shelter rabbit samples for proportions of Verrucomicrobia (P?<?0.01), Proteobacteria (P?<?0.01), and Lentisphaerae (P?=?0.01) within the total microbiota. Within the commercial meat rabbit samples, significant differences between the microbiota composition of growers (n?=?42) and does (n?=?44) were limited to one unclassified Firmicutes (P?=?0.03) and no differences were identified at the phylum level. Significant differences were present between fecal samples taken from rabbits during the summer (n?=?44) compared to the winter (n?=?42), with Firmicutes (P?=?0.04), Verrucomicrobia (P?=?0.03), Proteobacteria (P?=?0.02), Deinococcus-Thermus (P?=?0.04), Armatimonadates (P?=?0.003), and Actinobacteria (P?=?0.03) forming significantly different proportions of the microbiota. The only significant difference in composition between those farms that routinely reported antimicrobial use and those that did not was in one unclassified Bacteroidetes (P?<?0.05) and no differences were identified at the phylum level.Rabbit husbandry and diet, in addition to season, significantly influence the fecal microbiota composition of domestic rabbits, while age of the rabbit post-weaning has minimal impact.

Project description:Hair cortisol is a stress indicator and could be used to assess the pigs' exposure to stressors in the weeks/months prior to non-invasive hair sampling. The main aim of this study was to describe the hair cortisol concentration (HCC) variability between individuals within a batch, between farms and between batches within a farm. The secondary aim was to determine how the number of sampled pigs influences the characterization of HCC within a batch. Twenty farrow-to-finish pig farms were recruited considering the diversity of their management practices and health status (data collected). Hair was sampled in two separate batches, 8 months apart. The necks of 24 finishing pigs were clipped per batch the week prior to slaughter. To describe the variability in HCC, an analysis of the variance model was run with three explanatory variables (batch, farm and their interaction). To identify farm clusters, a principal component analysis followed by a hierarchical clustering was carried out with four active variables (means and standard deviations of the two batches per farm) and 17 supplementary variables (management practices, herd health data). We determined how the number of sampled pigs influenced the characterization of HCC within a batch by selecting subsamples of the results. HCC ranged from 0.4 to 121.6 pg/mg, with a mean of 25.9 ± 16.2 pg/mg. The variability in HCC was mainly explained by differences between pigs (57%), then between farms (24%), between batches within the same farm (16%) and between batches (3%). Three clusters of farms were identified: low homogeneous concentrations (n = 3 farms), heterogeneous concentrations with either higher (n = 7) or lower (n = 10) HCC in batch 2 than in batch 1. The diversity of management practices and health statuses allowed to discuss hypotheses explaining the HCC variations observed. We highlighted the need to sample more than 24 pigs to characterize HCC in a pig batch. HCC differences between batches on six farms suggest sampling pigs in more than one batch to describe the HCC at the farm level. HCC variations described here confirm the need to study its links with exposure of pigs to stressors.

Dataset Information

Comparison of Productivity and Fecal Microbiotas of Sows in Commercial Farms.

Publications

Comparison of Productivity and Fecal Microbiotas of Sows in Commercial Farms.

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