Frontiers in Veterinary Science (Oct 2020)

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

  • Marinus F. W. te Pas,
  • Alfons J. M. Jansman,
  • Leo Kruijt,
  • Yvonne van der Meer,
  • Jacques J. M. Vervoort,
  • Dirkjan Schokker

DOI
https://doi.org/10.3389/fvets.2020.585730
Journal volume & issue
Vol. 7

Abstract

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Differences in sanitary conditions, as model to induce differences in subclinical immune stimulation, affect the growth performance and nutrient metabolism in pigs. The objective of the present study was to evaluate the colonic microbiota and the colonic and systemic metabolome of female pigs differing in health status induced by sanitary conditions. We analyzed blood and colon digesta metabolite profiles using Nuclear Magnetic Resonance (1H NMR) and Triple quadrupole mass spectrometry, as well as colonic microbiota profiles. 1H NMR is a quantitative metabolomics technique applicable to biological samples. Weaned piglets of 4 weeks of age were kept under high or low sanitary conditions for the first 9 weeks of life. The microbiota diversity in colon digesta was higher in pigs subjected to low sanitary conditions (n = 18 per treatment group). The abundance of 34 bacterial genera was higher in colon digesta of low sanitary condition pigs, while colon digesta of high sanitary status pigs showed a higher abundance for four bacterial groups including the Megasphaera genus (p < 0.003) involved in lactate fermentation. Metabolite profiles (n = 18 per treatment group) in blood were different between both groups of pigs. These different profiles suggested changes in general nutrient metabolism, and more specifically in amino acid metabolism. Moreover, differences in compounds related to the immune system and responses to stress were observed. Microbiome-specific metabolites in blood were also affected by sanitary status of the pigs. We conclude that the microbiome composition in colon and the systemic metabolite profiles are affected by sanitary conditions and related to suboptimal health. These data are useful for exploring further relationships between health, metabolic status and performance and for the identification of biomarkers related to health (indices) and performance.

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