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ShareScore release 0.9.0
Dataset results
12 results for “Microbiota, Pig”
Small intestinal microbiota data of pigs receiving control or pharmaceutical levels of ZincOxide
<p>To improve our understanding of host and intestinal microbiome interaction, this research investigated the effects of a high level zinc oxide in the diet as model intervention on the intestinal microbiome and small intestinal functionality in clinically healthy post-weaning piglets.</p> <p>In study 1 piglets received either a high concentration of zinc as zinc oxide (Zn, 2690 mg/kg) or a low Zn concentration (100 mg/kg) in the diet during the post weaning period (d 14-23). We investigated the effects on the piglet’s small intestinal microbiome and functionality of intestinal tissue. In study 2 we investigated the impact of timing of the dietary zinc intervention, i.e. between d 0-14 and/or d 14-23 post weaning, and the consecutive effects on the piglet’s intestinal functionality. We acquired data on the microbiota composition in small intestinal digesta and gene expression profiles of both jejunum and ileum tissue.</p> <p>Overall, we observed differences in the small intestinal functionality during the post weaning period between piglets receiving a diet with a low or high concentration ZnO content.</p>
Inflammatory responses induced by the monophasic variant of Salmonella typhimurium in pigs play a role in the high shedder phenotype and fecal microbiota composition
<p>Pigs infected with <em><span>Salmonella</span></em> may excrete large amounts of <em><span>Salmonella</span></em>, increasing the risk of spread of this pathogen in the food chain. Identifying <em><span>Salmonella</span></em> high shedder pigs is therefore required to mitigate this risk. We analyzed immune-associated markers and composition of the gut microbiota in specific-pathogen-free pigs presenting different shedding levels after an oral infection with <span>Salmonella</span>. Immune response was studied through total blood cell counts, production of anti-<em><span>Salmonella</span></em> antibodies and cytokines, and gene expression quantification. Total <em><span>Salmonella</span></em> shedding for each pig was estimated and hierarchical clustering was used to cluster pigs into high, intermediate, and low shedders. Gut microbiota compositions were assessed using 16S rRNA microbial community profiling. Comparisons were made between control and inoculated pigs, then between high and low shedders pigs. Prior to infection, high shedders had similar immunological profiles compared to low shedders. As soon as 1 day postinoculation (dpi), significant differences in the cytokine production level and on the expression level of several host genes related to a proinflammatory response were observed between high and low shedders. Infection with <em><span>Salmonella</span></em> induced an early and profound remodeling of the immune response in all pigs, but the intensity of the response was stronger in high shedders. In contrast, low shedders seroconverted earlier than high shedders. Just after induction of the proinflammatory response (at 2 dpi), some taxa of the fecal microbiota were specific to the shedding phenotypes. This was related to the enrichment of several functional pathways related to anaerobic respiration in high shedders. In conclusion, our data show that the immune response to <em><span>Salmonella</span></em> modifies the fecal microbiota and subsequently could be responsible for shedding phenotypes. Influencing the gut microbiota and reducing intestinal inflammation could be a strategy for preventing <em><span>Salmonella</span></em> high shedding in livestock.</p>
Inflammatory responses induced by the monophasic variant of Salmonella typhimurium in pigs play a role in the high shedder phenotype and fecal microbiota composition
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An updated catalog of genes and species of the pig gut microbiota
<p></p><h1>Dataset overview</h1><br>We built an updated catalog of 9.3M genes found in the pig gut microbiota.<br>Co-abundant genes were binned in 1523 Metagenomic Species Pan-genomes (MSPs) for which we provide taxonomic labels and a phylogenetic tree. In addition, we reconstituted 7059 Metagenome-Assembled Genomes (MAGs) covering of 760 Metagenomic Species and we extracted 7331 viral genomes from assemblies.<br>Finally, we used Pairwise Comparative Modelling to predict 6140 antibiotic resistance genes.<br><br>This dataset can be used to analyze shotgun sequencing data of the pig gut microbiota.<br><h1>Methods</h1><br><h2>Sequencing data availability</h2><br>Sequencing data from Xiao et al. (PRJEB11755, n=287) and Kim et al. (PRJEB32496, n=36) was downloaded from the European Nucleotide Archive.<br><h2>Sequencing data quality control</h2><br>Illumina adapters removal and read trimming was performed with fastp . Reads mapped on the host genome (GCF_000003025.6) with bowtie2 were removed with samtools.<br><h2>Metagenomic assembly</h2><br>Metagenomic assembly was performed with metaSPAdes. Contigs of less than 1500 bp were removed.<br><h2>MAGs creation</h2><br>Reads of each sample were aligned to their respective assembly with bowtie2 and results were indexed in sorted bam files with samtools. Then, contigs coverage was computed in each sample with jgi_summarize_bam_contig_depths. MAGs were generated with MetaBAT 2 and MaxBin2. Finally, results of both tools were combined with DAS Tool and MAGs quality was assessed with checkM. MAGs with completeness < 70% or contamination > 5% were discarded.<br><h2>Extraction of viral genomes</h2><br>Candidates viral sequences were identified in assemblies with VirFinder. Then, viral genomes quality was assessed with checkV and those low or undetermined quality were discarded.<br><h2>Non-redundant gene catalog</h2><br>Genes were predicted on all contigs with Prodigal (parameters : -m -p meta ). Genes with missing start codon or shorter than 99 bp were discarded.<br>Then, partial and complete genes were separately clustered with cd-hit-est (parameters -c 0.95 -aS 0.90 -G 0 -d 0 -M 0 -T 0 ). The two non-redundant gene sets were merged by considering at first complete genes from the longest contigs (contact us for futher details).<br><h2>MSPs creation</h2><br>Using the Meteor software suite, reads from each sample were mapped against the non redundant catalog to build a raw gene abundance table (9.3 million genes quantified in 323 samples). This table was submitted to MSPminer that reconstituted 1523 clusters of co-abundant genes named Metagenomic-Species Pangenomes (MSPs).<br>Quality control of each MSP was manually performed by visualizing heatmaps representative of the normalized gene abundance profiles.<br><h2>Taxonomic annotation</h2><br>MAGs and MSPs were annotated with GTDB-Tk based on GTDB Release 05-RS95.<br><h2>Construction of the phylogenetic tree</h2><br>39 universal phylogenetic markers genes were extracted from the 1523 MSPs (or the corresponding MAGs if available) with fetchMGs. Then, the markers were separately aligned with MUSCLE. The 40 alignments were merged and trimmed with trimAl (parameters: -automated1). Finally, the phylogenetic tree was computed with FastTreeMP (parameters: -gamma -pseudo -spr -mlacc 3 -slownni).<br><h2>Prediction of antibiotic resistance genes</h2><br>Antibiotic resistance genes were predicted with the Pairwise Comparative Modelling approach (last version available here).<h1>Mapping rate distribution across public cohorts</h1>We generated mapping rate distribution plots using Meteor2 (default parameters), comparing performance between: PRJEB11755 and PRJEB32496 (cohort used in catalogue assembly) and PRJEB60032 and PRJNA494875 (independent cohort not used in assembly).<p></p>
Population genomic, olfactory, dietary, and gut microbiota analyses demonstrate the unique evolutionary trajectory of feral pigs
<p><span><span><span><span><span><span><span><span><span><span><span>Domestication is an intriguing evolutionary process. Many domestic populations are subjected to strong human-mediated selection, and when some individuals return to the wild, they are again subjected to selective forces associated with new environments. Generally, these feral populations evolve into something different from their wild predecessors and their members typically possess a combination of both wild and human selected traits. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>Feralisation can manifest in different forms on a spectrum from a wild to a domestic phenotype. This depends on how the re-wilded domesticated populations can re-adapt to natural environments based on how much potential and flexibility the ancestral genome retains after its domestication signature. Whether feralisation leads to the evolution of new traits that do not exist in the wild or to convergence with wild forms, however, remains unclear. To address this question, we performed population genomic, olfactory, dietary, and gut microbiota analyses on different populations of <i>Sus scrofa </i>(wild boar, hybrid, feral and several domestic pig breeds). Porcine Single Nucleotide Polymorphisms (SNPs) analysis shows that the feral population represents a cluster distinctly separate from all others. Its members display signatures of past artificial selection, as demonstrated by values of <i>F</i><sub>ST</sub> in specific regions of the genome and bottleneck signature, such as the number and length of runs of homozygosity. Generalised <i>F</i><sub>ST</sub> values, re-acquired olfactory abilities, diet, and gut microbiota variation show current responses to natural selection. Our results suggest that feral pigs are an independent evolutionary unit which can persist so long as levels of human intervention remain unchanged.</span></span></span></span></span></span></span></span></span></span></span></p>
Population genomic, olfactory, dietary, and gut microbiota analyses demonstrate the unique evolutionary trajectory of feral pigs
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Microbiota-associated intestinal methylation changes confer immune-metabolic gene network of NEC in preterm pig model
GEO Series GSE88697. Sus scrofa. 14 samples. Type: Methylation profiling by high throughput sequencing.
Data from: Olive oil bioactives protect pigs against experimentally-induced chronic inflammation independently of alterations in gut microbiota
Subclinical chronic inflammation (SCI) is associated with impaired animal growth. Previous work has demonstrated that olive-derived plant bioactives exhibit anti-inflammatory properties that could possibly counteract the growth-depressing effects of SCI. To test this hypothesis and define the underlying mechanism, we conducted a 30-day study in which piglets fed an olive-oil bioactive extract (OBE) and their control counterparts (C+) were injected repeatedly during the last 10 days of the study with increasing doses of Escherichia coli lipopolysaccharides (LPS) to induce SCI. A third group of piglets remained untreated throughout the study and served as a negative control (C-). In C+ pigs, SCI increased the circulating concentration of interleukin 1 beta (p < 0.001) and decreased feed ingestion (p < 0.05) and weight gain (p < 0.05). These responses were not observed in OBE animals. Although intestinal inflammation and colonic microbial ecology was not altered by treatments, OBE enhanced ileal mRNA abundance of tight and adherens junctional proteins (p < 0.05) and plasma recovery of mannitol (p < 0.05) compared with C+ and C-. In line with these findings, OBE improved transepithelial electrical resistance (p < 0.01) in TNF-α-challenged Caco-2/TC-7 cells, and repressed the production of inflammatory cytokines (p < 0.05) in LPS-stimulated macrophages. In summary, this work demonstrates that OBE attenuates the suppressing effect of SCI on animal growth through a mechanism that appears to involve improvements in intestinal integrity unrelated to alterations in gut microbial ecology and function.
Data from: Olive oil bioactives protect pigs against experimentally-induced chronic inflammation independently of alterations in gut microbiota
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Effects of starter microbiota on the gastric transcriptome profile of 2 weeks old caesarean derived pigs
GEO Series GSE87124. Sus scrofa. 12 samples. Type: Expression profiling by array.
AOS10 could benefit the pig's sperm quantity via improvement of intestinal microbiota.
GEO Series GSE178723. Sus scrofa. 19 samples. Type: Other.
Effects of starter microbiota and early life feeding of medium chain triglycerides on the gastric transcriptome profile of 3 weeks old caesarean derived pigs
GEO Series GSE87125. Sus scrofa. 24 samples. Type: Expression profiling by array.
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OpenNeuro
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