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Cited by 113Dermatology and Skin DiseasesMicrobial Community Ecology and PhysiologyGut microbiota and health

Segregation of age-related skin microbiome characteristics by functionality

Open access
Kim, Hye-Jin, Kim, Jin Ju, Myeong, Nu Ri, Kim, Taeyune, Kim, DooA, An, Susun, Kim, Hanbyul, Park, Taehun +4 more·2019·Scientific Reports
DOI 10.1038/s41598-019-53266-3PMC PMC6856112
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Abstract

Although physiological changes are the most evident indicators of skin aging by alteration of the skin's structure and function, we question whether skin aging is also affected by the structure and assembly process of the skin microbiome. We analysed the skin microbiomes of 73 healthy Chinese women in two age groups (25-35 years old and 56-63 years old) using 16S rRNA gene amplicon sequencing; the overall microbiome structure was significantly different between the two age groups. An analysis using ecological theory to evaluate the process of microbial community assembly processes revealed that the microbiomes of the older group were formed under a greater influence of the niche-based process, with the network of microbes being more collapsed than that of the younger group. Inferred metagenomic functional pathways associated with replication and repair were relatively more predominant in the younger group whereas, among the various metabolism-related pathways, those associated with biodegradation were more predominant in the older group. Interestingly, we found two segregated sub-typing patterns in the younger group which were also observed in the skin microbiomes of young Chinese women living in four other cities in China. The results of our study highlights candidate microbes and functional pathways that are important for future research into preventing skin aging and which could lead to a comprehensive understanding of age-related skin microbiome characteristics.

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  • Proteobacteria and Corynebacterium were reported to be the predominant phylum and genus, respectively, on the skin with aging.

    “Proteobacteria and Corynebacterium were reported to be the predominant phylum and genus, respectively, on the skin with aging [60,61].”

    From Host–Candida auris interactions in the skin (2026) · cites this paper as [61]

    The Results (‘Differences in cheek microbiomes between the two age groups’; page not provided) identify Proteobacteria as the most abundant phylum, but list Corynebacterium as one of ten most abundant genera, not the predominant genus. The ‘Age-dependent microbial signatures’ Results report Corynebacterium-specific OTUs only in the older group, which supports an age association rather than predominance. (LLM, conf=0.88)

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Research works printed but not linked: 41

  1. [2]Gupta MA Gilchrest BA Psychosocial aspects of aging skin Dermatol Clin 2005 23 643 648 10.1016/j.det.2005.05.012 16112440 · DOI
  2. [3]Fore J A review of skin and the effects of aging on skin structure and function Ostomy Wound Manage 2006 52 24 35 16980727
  3. [4]Gilhar A Ageing of human epidermis: the role of apoptosis, Fas and telomerase The British journal of dermatology 2004 150 56 63 10.1111/j.1365-2133.2004.05715.x 14746617 · DOI
  4. [5]Potts RO Buras EM Jr. Chrisman DA Jr. Changes with age in the moisture content of human skin The Journal of investigative dermatology 1984 82 97 100 10.1111/1523-1747.ep12259203 6690633 · DOI
  5. [6]Miyahara T Shiozawa S Murai A The effect of age on amino acid composition of human skin collagen J Gerontol 1978 33 498 503 10.1093/geronj/33.4.498 752039 · DOI
  6. [7]Wilhelm KP Cua AB Maibach HI Skin aging. Effect on transepidermal water loss, stratum corneum hydration, skin surface pH, and casual sebum content Arch Dermatol 1991 127 1806 1809 10.1001/archderm.1991.04520010052006 1845280 · DOI
  7. [8]Oh J Biogeography and individuality shape function in the human skin metagenome Nature 2014 514 59 64 10.1038/nature13786 25279917 PMC4185404 · DOI · Paper page
  8. [9]Grice EA Segre JA The skin microbiome Nature reviews. Microbiology 2011 9 244 253 10.1038/nrmicro2537 21407241 PMC3535073 · DOI · Paper page
  9. [10]Ying S The Influence of Age and Gender on Skin-Associated Microbial Communities in Urban and Rural Human Populations PloS one 2015 10 e0141842 10.1371/journal.pone.0141842 26510185 PMC4624872 · DOI
  10. [12]Kim HJ Fragile skin microbiomes in megacities are assembled by a predominantly niche-based process Sci Adv 2018 4 e1701581 10.1126/sciadv.1701581 29532031 PMC5842045 · DOI
  11. [13]Oh J The altered landscape of the human skin microbiome in patients with primary immunodeficiencies Genome research 2013 23 2103 2114 10.1101/gr.159467.113 24170601 PMC3847779 · DOI
  12. [14]Makrantonaki E Bekou V Zouboulis CC Genetics and skin aging Dermatoendocrinol 2012 4 280 284 10.4161/derm.22372 23467395 PMC3583889 · DOI
  13. [15]Blume-Peytavi U Age-Associated Skin Conditions and Diseases: Current Perspectives and Future Options Gerontologist 2016 56 Suppl 2 S230 242 10.1093/geront/gnw003 26994263 · DOI · Paper page
  14. [16]Gragnani, A. et al. Review of major theories of skin aging. 3, 265 (2014).
  15. [17]Shibagaki N Aging-related changes in the diversity of women’s skin microbiomes associated with oral bacteria. 2017 7 10567 PMC5585242 28874721
  16. [19]Zapata HJ Quagliarello VJ The microbiota and microbiome in aging: potential implications in health and age-related diseases J Am Geriatr Soc 2015 63 776 781 10.1111/jgs.13310 25851728 PMC4406803 · DOI · Paper page
  17. [21]Vaiserman AM Koliada AK Marotta F Gut microbiota: A player in aging and a target for anti-aging intervention Ageing Res Rev 2017 35 36 45 10.1016/j.arr.2017.01.001 28109835 · DOI · Paper page
  18. [22]Ogawa T Composition of salivary microbiota in elderly subjects Scientific reports 2018 8 414 10.1038/s41598-017-18677-0 29323208 PMC5765146 · DOI
  19. [23]Lira-Junior R Akerman S Klinge B Bostrom EA Gustafsson A Salivary microbial profiles in relation to age, periodontal, and systemic diseases PloS one 2018 13 e0189374 10.1371/journal.pone.0189374 29538390 PMC5851536 · DOI
  20. [24]Dimitriu PA New Insights into the Intrinsic and Extrinsic Factors That Shape the Human Skin Microbiome. 2019 10 e00839 00819 PMC6606800 31266865
  21. [25]Varani J Decreased collagen production in chronologically aged skin: roles of age-dependent alteration in fibroblast function and defective mechanical stimulation Am J Pathol 2006 168 1861 1868 10.2353/ajpath.2006.051302 16723701 PMC1606623 · DOI · Paper page
  22. [26]Gunin AG Kornilova NK Petrov VV Vasil’eva OV [Age-related changes in the number and proliferation of fibroblasts in the human skin] Adv Gerontol 2011 24 43 47 21809619
  23. [27]Li Y Age-Associated Increase in Skin Fibroblast-Derived Prostaglandin E2 Contributes to Reduced Collagen Levels in Elderly Human Skin The Journal of investigative dermatology 2015 135 2181 2188 10.1038/jid.2015.157 25905589 PMC4537382 · DOI
  24. [28]Fisher GJ Varani J Voorhees JJ Looking older: fibroblast collapse and therapeutic implications Arch Dermatol 2008 144 666 672 10.1001/archderm.144.5.666 18490597 PMC2887041 · DOI · Paper page
  25. [29]Varani J Reduced fibroblast interaction with intact collagen as a mechanism for depressed collagen synthesis in photodamaged skin The Journal of investigative dermatology 2004 122 1471 1479 10.1111/j.0022-202X.2004.22614.x 15175039 · DOI
  26. [30]Lee, H. J. et al. Effects of cosmetics on the skin microbiome of facial cheeks with different hydration levels. 7, e00557 (2018). PMC5911989 29193830
  27. [31]Grice EA Topographical and temporal diversity of the human skin microbiome Science 2009 324 1190 1192 10.1126/science.1171700 19478181 PMC2805064 · DOI · Paper page
  28. [32]Kong HH Skin microbiome: genomics-based insights into the diversity and role of skin microbes Trends Mol Med 2011 17 320 328 10.1016/j.molmed.2011.01.013 21376666 PMC3115422 · DOI
  29. [33]Berardesca E Distante F Vignoli GP Oresajo C Green B Alpha hydroxyacids modulate stratum corneum barrier function The British journal of dermatology 1997 137 934 938 10.1111/j.1365-2133.1997.tb01554.x 9470910 · DOI
  30. [34]Eren AM Vineis JH Morrison HG Sogin ML A filtering method to generate high quality short reads using illumina paired-end technology PloS one 2013 8 e66643 10.1371/journal.pone.0066643 23799126 PMC3684618 · DOI
  31. [35]Caporaso JG QIIME allows analysis of high-throughput community sequencing data Nature methods 2010 7 335 336 10.1038/nmeth.f.303 20383131 PMC3156573 · DOI · Paper page
  32. [36]Edgar RC Search and clustering orders of magnitude faster than BLAST Bioinformatics 2010 26 2460 2461 10.1093/bioinformatics/btq461 20709691 · DOI
  33. [37]Wang Q Garrity GM Tiedje JM Cole JR Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy Applied and environmental microbiology 2007 73 5261 5267 10.1128/AEM.00062-07 17586664 PMC1950982 · DOI
  34. [38]DeSantis TZ Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB Applied and environmental microbiology 2006 72 5069 5072 10.1128/AEM.03006-05 16820507 PMC1489311 · DOI · Paper page
  35. [39]Caporaso JG PyNAST: a flexible tool for aligning sequences to a template alignment Bioinformatics 2010 26 266 267 10.1093/bioinformatics/btp636 19914921 PMC2804299 · DOI
  36. [40]Price MN Dehal PS Arkin AP FastTree: computing large minimum evolution trees with profiles instead of a distance matrix Mol Biol Evol 2009 26 1641 1650 10.1093/molbev/msp077 19377059 PMC2693737 · DOI · Paper page
  37. [41]Segata N Metagenomic biomarker discovery and explanation Genome biology 2011 12 R60 10.1186/gb-2011-12-6-r60 21702898 PMC3218848 · DOI · Paper page
  38. [42]Sloan WT Quantifying the roles of immigration and chance in shaping prokaryote community structure Environmental microbiology 2006 8 732 740 10.1111/j.1462-2920.2005.00956.x 16584484 · DOI
  39. [44]Kurtz ZD Sparse and compositionally robust inference of microbial ecological networks PLoS Comput Biol 2015 11 e1004226 10.1371/journal.pcbi.1004226 25950956 PMC4423992 · DOI · Paper page
  40. [46]Liu H Roeder K Wasserman L Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models Adv Neural Inf Process Syst 2010 24 1432 1440 25152607 PMC4138724
  41. [48]Arumugam M Enterotypes of the human gut microbiome Nature 2011 473 174 180 10.1038/nature09944 21508958 PMC3728647 · DOI · Paper page

Cited by

Sorted by citations

Authors
Kim, H.-J., Kim, J. J., Myeong, N. R., Kim, T., Kim, D., An, S., Kim, H., Park, T., Jang, S. I., Yeon, J. H., Kwack, I., & Sul, W. J.
Affiliations
  • Chung-Ang University (KR)
  • Amorepacific (South Korea) (KR)
Corresponding author
Sul, Woo Jun
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2019-11-14
Volume
9
Issue
1
Pages
16748-16748
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-019-53266-3
PMC
PMC6856112
OpenAlex
W2984177031
Cited by
113
References
4
Citations by year
2026: 10 · 2025: 13 · 2024: 15 · 2023: 18 · 2022: 23 · 2021: 18 · 2020: 12 · 2019: 3 · 2018: 1
FWCI
14.12
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
National Research Foundation of Korea (2016R1A6A3A11933991, 2019R1C1C1009360)
Topics
  • Health Sciences › Medicine › Dermatology › Dermatology and Skin Diseases
  • Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
Keywords
skin microbiome, skin aging, microbial community assembly, niche-based assembly, biodegradation, microbial network structure, Chinese women
MeSH terms
Adult, Bacteria, China, Female, Humans, Middle Aged, Phylogeny, RNA, Ribosomal, 16S, Skin, Case-Control Studies, Sequence Analysis, DNA, Age Distribution, Biodiversity, Microbiota

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