Sanitary Conditions Affect the Colonic Microbiome and the Colonic and Systemic Metabolome of Female Pigs

Pas, M.F.W. te; Jansman, A.J.M.; Kruijt, L.; Meer, Yvonne van der; Vervoort, Jacques; Schokker, Dirkjan

doi:10.3389/fvets.2020.585730

Cited by 19 publications

(26 citation statements)

References 58 publications

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“…All reads with unlinked rRNA genes found from the horses were mapped in KMA software 22 to genus Cellulosilyticum or Anaerocolumna and were quality filtered by CCMetagen software 23 to family Lachnospiraceae , order Clostridiales , or phylum Firmicutes , depending on their mapping qualities. Members of the Lachnospiraceae can ferment diverse plant polysaccharides to produce short-chain fatty acids 32 , and make up the largest single group in rumen microbes of cows 33 . No unlinked rRNA gene in three complete genomes of genus Anaerocolumna was found (Tables S6 , S6 _1–3).…”

Section: Resultsmentioning

confidence: 99%

Establishment and assessment of an amplicon sequencing method targeting the 16S-ITS-23S rRNA operon for analysis of the equine gut microbiome

Kinoshita

Niwa

Uchida‐Fujii

et al. 2021

Sci Rep

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Microbial communities are commonly studied by using amplicon sequencing of part of the 16S rRNA gene. Sequencing of the full-length 16S rRNA gene can provide higher taxonomic resolution and accuracy. To obtain even higher taxonomic resolution, with as few false-positives as possible, we assessed a method using long amplicon sequencing targeting the rRNA operon combined with a CCMetagen pipeline. Taxonomic assignment had > 90% accuracy at the species level in a mock sample and at the family level in equine fecal samples, generating similar taxonomic composition as shotgun sequencing. The rRNA operon amplicon sequencing of equine fecal samples underestimated compositional percentages of bacterial strains containing unlinked rRNA genes by a fourth to a third, but unlinked rRNA genes had a limited effect on the overall results. The rRNA operon amplicon sequencing with the A519F + U2428R primer set was able to detect some kind of archaeal genomes such as Methanobacteriales and Methanomicrobiales, whereas full-length 16S rRNA with 27F + 1492R could not. Therefore, we conclude that amplicon sequencing targeting the rRNA operon captures more detailed variations of equine microbiota.

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Section: Resultsmentioning

confidence: 99%

Establishment and assessment of an amplicon sequencing method targeting the 16S-ITS-23S rRNA operon for analysis of the equine gut microbiome

Kinoshita

Niwa

Uchida‐Fujii

et al. 2021

Sci Rep

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“…Notably, in the above study, all the participants were men rather than women. In contrast, another study on female pigs rather than male also proved that sanitary conditions affected the colonic microbiome and metabolome ( te Pas et al, 2020 ). The differences of metabolic profile between pig sexes may largely contribute to the sex-related microbial compositions by sex hormones which had been confirmed to modulate gut microbiota ( Razavi et al, 2019 ).…”

Section: Discussionmentioning

confidence: 99%

Low Crude Protein Diet Affects the Intestinal Microbiome and Metabolome Differently in Barrows and Gilts

et al. 2021

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Low protein diets are commonly used in the growing-finishing pig stage of swine production; however, the effects of low dietary protein on the intestinal microbiota and their metabolites, and their association with pig sex, remain unclear. The present study aimed to assess the impact of a low crude protein (CP) diet on the gut microbiome and metabolome, and to reveal any relationship with sex. Barrows and gilts (both n = 24; initial body = 68.33 ± 0.881 kg) were allocated into two treatments according to sex. The four groups comprised two pairs of gilts and barrows fed with a high protein diet (CP 17% at stage I; CP 13% at stage II) and a low protein diet (CP 15% at stage I; CP 11% at stage II), respectively, for 51 d. Eight pigs in each group were slaughtered and their colon contents were collected. Intestinal microbiota and their metabolites were assessed using 16S rRNA sequencing and tandem mass spectrometry, respectively. The low protein diet increased intestinal microbiota species and richness indices (P < 0.05) in both sexes compared with the high protein diet. The sample Shannon index was different (P < 0.01) between barrows and gilts. At the genus level, unidentified Clostridiales (P < 0.05), Neisseria (P < 0.05), unidentified Prevotellaceae (P < 0.01) and Gracilibacteria (P < 0.05) were affected by dietary protein levels. The relative abundance of unidentified Prevotellaceae was different (P < 0.01) between barrows and gilts. The influence of dietary protein levels on Neisseria (P < 0.05), unidentified Prevotellaceae (P < 0.01) and Gracilibacteria (P < 0.05) were associated with sex. Metabolomic profiling indicated that dietary protein levels mainly affected intestinal metabolites in gilts rather than barrows. A total of 434 differentially abundant metabolites were identified in gilts fed the two protein diets. Correlation analysis identified that six differentially abundant microbiota communities were closely associated with twelve metabolites that were enriched for amino acids, inflammation, immune, and disease-related metabolic pathways. These results suggested that decreasing dietary protein contents changed the intestinal microbiota in growing-finishing pigs, which selectively affected the intestinal metabolite profiles in gilts.

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“…All reads with unlinked rRNA genes found from the horses were mapped in KMA v. 1.3.0 software 19 to genus Cellulosilyticum or Anaerocolumna and were quality ltered by CCMetagen v. 1.2.2 software 20 to family Lachnospiraceae, order Clostridiales, or phylum Firmicutes, depending on their mapping qualities. Members of the Lachnospiraceae can ferment diverse plant polysaccharides to produce short-chain fatty acids 21 , and make up the largest single group in rumen microbes of cows 22 . No unlinked rRNA in three complete genomes of genus Anaerocolumna was found (Table S2).…”

Section: Unlinked Rrna Genesmentioning

confidence: 99%

Establishment and Assessment of An Amplicon Sequencing Method Targeting The 16S-ITS-23S rRNA Operon For Analysis of The Equine Gut Microbiome

Kinoshita

Niwa

Uchida‐Fujii

et al. 2021

Preprint

View full text Add to dashboard Cite

Microbial communities are commonly studied by using amplicon sequencing of part of the 16S rRNA gene. Sequencing of the full-length 16S rRNA gene can provide higher taxonomic resolution and accuracy. To obtain even higher taxonomic resolution, with as few false-positives as possible, we assessed a method using long amplicon sequencing targeting the rRNA operon combined with a CCMetagen pipeline. Taxonomic assignment had >90% accuracy at the species level in a mock sample and at the family level in equine fecal samples, generating similar taxonomic composition as shotgun sequencing. The rRNA operon amplicon sequencing of equine fecal samples underestimated compositional percentages of bacterial strains containing unlinked rRNA genes by a third to almost a half, but unlinked rRNA genes had a limited effect on the overall results. The rRNA operon amplicon sequencing with the A519F + U2428R primer set was able to reflect archaeal genomes, whereas full-length 16S rRNA with 27F + 1492R could not. Therefore, we conclude that amplicon sequencing targeting the rRNA operon captures more detailed variations of bacterial and archaeal microbiota.

show abstract

Sanitary Conditions Affect the Colonic Microbiome and the Colonic and Systemic Metabolome of Female Pigs

Cited by 19 publications

References 58 publications

Establishment and assessment of an amplicon sequencing method targeting the 16S-ITS-23S rRNA operon for analysis of the equine gut microbiome

Establishment and assessment of an amplicon sequencing method targeting the 16S-ITS-23S rRNA operon for analysis of the equine gut microbiome

Low Crude Protein Diet Affects the Intestinal Microbiome and Metabolome Differently in Barrows and Gilts

Establishment and Assessment of An Amplicon Sequencing Method Targeting The 16S-ITS-23S rRNA Operon For Analysis of The Equine Gut Microbiome

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