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

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 interp...

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Autores principales:	Wynand Alkema, Jos Boekhorst, Robyn T Eijlander, Steve Schnittger, Fini De Gruyter, Sabina Lukovac, Kurt Schilling, Guus A M Kortman
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/694e0ebfbe3c47d8b60c786fdeddd1fd
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spelling	oai:doaj.org-article:694e0ebfbe3c47d8b60c786fdeddd1fd2021-12-02T20:07:39ZCharting host-microbe co-metabolism in skin aging and application to metagenomics data.1932-620310.1371/journal.pone.0258960https://doaj.org/article/694e0ebfbe3c47d8b60c786fdeddd1fd2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0258960https://doaj.org/toc/1932-6203During 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.Wynand AlkemaJos BoekhorstRobyn T EijlanderSteve SchnittgerFini De GruyterSabina LukovacKurt SchillingGuus A M KortmanPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11, p e0258960 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Wynand Alkema Jos Boekhorst Robyn T Eijlander Steve Schnittger Fini De Gruyter Sabina Lukovac Kurt Schilling Guus A M Kortman Charting host-microbe co-metabolism in skin aging and application to metagenomics data.
description	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.
format	article
author	Wynand Alkema Jos Boekhorst Robyn T Eijlander Steve Schnittger Fini De Gruyter Sabina Lukovac Kurt Schilling Guus A M Kortman
author_facet	Wynand Alkema Jos Boekhorst Robyn T Eijlander Steve Schnittger Fini De Gruyter Sabina Lukovac Kurt Schilling Guus A M Kortman
author_sort	Wynand Alkema
title	Charting host-microbe co-metabolism in skin aging and application to metagenomics data.
title_short	Charting host-microbe co-metabolism in skin aging and application to metagenomics data.
title_full	Charting host-microbe co-metabolism in skin aging and application to metagenomics data.
title_fullStr	Charting host-microbe co-metabolism in skin aging and application to metagenomics data.
title_full_unstemmed	Charting host-microbe co-metabolism in skin aging and application to metagenomics data.
title_sort	charting host-microbe co-metabolism in skin aging and application to metagenomics data.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/694e0ebfbe3c47d8b60c786fdeddd1fd
work_keys_str_mv	AT wynandalkema chartinghostmicrobecometabolisminskinagingandapplicationtometagenomicsdata AT josboekhorst chartinghostmicrobecometabolisminskinagingandapplicationtometagenomicsdata AT robynteijlander chartinghostmicrobecometabolisminskinagingandapplicationtometagenomicsdata AT steveschnittger chartinghostmicrobecometabolisminskinagingandapplicationtometagenomicsdata AT finidegruyter chartinghostmicrobecometabolisminskinagingandapplicationtometagenomicsdata AT sabinalukovac chartinghostmicrobecometabolisminskinagingandapplicationtometagenomicsdata AT kurtschilling chartinghostmicrobecometabolisminskinagingandapplicationtometagenomicsdata AT guusamkortman chartinghostmicrobecometabolisminskinagingandapplicationtometagenomicsdata
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Charting host-microbe co-metabolism in skin aging and application to metagenomics data.

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