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Charting host-microbe co-metabolism in skin aging and application to metagenomics data

Author

Listed:
  • Wynand Alkema
  • Jos Boekhorst
  • Robyn T Eijlander
  • Steve Schnittger
  • Fini De Gruyter
  • Sabina Lukovac
  • Kurt Schilling
  • Guus A M Kortman

Abstract

During aging of human skin, a number of intrinsic and extrinsic factors cause the alteration of the skin’s structure, function and cutaneous physiology. Many studies have investigated the influence of the skin microbiome on these alterations, but the molecular mechanisms that dictate the interplay between these factors and the skin microbiome are still not fully understood. To obtain more insight into the connection between the skin microbiome and the human physiological processes involved in skin aging, we performed a systematic study on interconnected pathways of human and bacterial metabolic processes that are known to play a role in skin aging. The bacterial genes in these pathways were subsequently used to create Hidden Markov Models (HMMs), which were applied to screen for presence of defined functionalities in both genomic and metagenomic datasets of skin-associated bacteria. These models were further applied on 16S rRNA gene sequencing data from skin microbiota samples derived from female volunteers of two different age groups (25–28 years (‘young’) and 59–68 years (‘old’)). The results show that the main bacterial pathways associated with aging skin are those involved in the production of pigmentation intermediates, fatty acids and ceramides. This study furthermore provides evidence for a relation between skin aging and bacterial enzymes involved in protein glycation. Taken together, the results and insights described in this paper provide new leads for intervening with bacterial processes that are associated with aging of human skin.

Suggested Citation

  • Wynand Alkema & Jos Boekhorst & Robyn T Eijlander & Steve Schnittger & Fini De Gruyter & Sabina Lukovac & Kurt Schilling & Guus A M Kortman, 2021. "Charting host-microbe co-metabolism in skin aging and application to metagenomics data," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-16, November.
  • Handle: RePEc:plo:pone00:0258960
    DOI: 10.1371/journal.pone.0258960
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