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      New Insights Into the Skin Microbial Communities and Skin Aging

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          Abstract

          Although it is well-known that human skin aging is accompanied by an alteration in the skin microbiota, we know little about how the composition of these changes during the course of aging and the effects of age-related skin microbes on aging. Using 16S ribosomal DNA and internal transcribed spacer ribosomal DNA sequencing to profile the microbiomes of 160 skin samples from two anatomical sites, the cheek and the abdomen, on 80 individuals of varying ages, we developed age-related microbiota profiles for both intrinsic skin aging and photoaging to provide an improved understanding of the age-dependent variation in skin microbial composition. According to the landscape, the microbial composition in the Children group was significantly different from that in the other age groups. Further correlation analysis with clinical parameters and functional prediction in each group revealed that high enrichment of nine microbial communities (i.e., Cyanobacteria, Staphylococcus, Cutibacterium, Lactobacillus, Corynebacterium, Streptococcus, Neisseria, Candida, and Malassezia) and 18 pathways (such as biosynthesis of antibiotics) potentially affected skin aging, implying that skin microbiomes may perform key functions in skin aging by regulating the immune response, resistance to ultraviolet light, and biosynthesis and metabolism of age-related substances. Our work re-establishes that skin microbiomes play an important regulatory role in the aging process and opens a new approach for targeted microbial therapy for skin aging.

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          Most cited references58

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          UPARSE: highly accurate OTU sequences from microbial amplicon reads.

          Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.
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            A new mathematical model for relative quantification in real-time RT-PCR.

            M. Pfaffl (2001)
            Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.
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              Microbiota-mediated colonization resistance against intestinal pathogens.

              Commensal bacteria inhabit mucosal and epidermal surfaces in mice and humans, and have effects on metabolic and immune pathways in their hosts. Recent studies indicate that the commensal microbiota can be manipulated to prevent and even to cure infections that are caused by pathogenic bacteria, particularly pathogens that are broadly resistant to antibiotics, such as vancomycin-resistant Enterococcus faecium, Gram-negative Enterobacteriaceae and Clostridium difficile. In this Review, we discuss how immune- mediated colonization resistance against antibiotic-resistant intestinal pathogens is influenced by the composition of the commensal microbiota. We also review recent advances characterizing the ability of different commensal bacterial families, genera and species to restore colonization resistance to intestinal pathogens in antibiotic-treated hosts.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                26 October 2020
                2020
                : 11
                : 565549
                Affiliations
                [1] 1Department of Burns and Cutaneous Surgery, Xijing Hospital, Fourth Military Medical University , Xi’an, China
                [2] 2Department of Cardiology, Tangdu Hospital, Fourth Military Medical University , Xi’an, China
                [3] 3West China School of Public Health and West China Fourth Hospital, Sichuan University , Chengdu, China
                [4] 4Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University , Xi’an, China
                Author notes

                Edited by: Amparo Latorre, University of Valencia, Spain

                Reviewed by: Lionel Breton, RAV, l’Oreal, Canada; Bing Niu, Shanghai University, China

                *Correspondence: Linlin Su, linlinsu@ 123456fmmu.edu.cn

                These authors have contributed equally to this work

                This article was submitted to Microbial Symbioses, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2020.565549
                7649423
                33193154
                0088a8dc-5e7f-4276-b308-eb1603eb563f
                Copyright © 2020 Li, Bai, Peng, Yi, Luo, Yang, Liu, Wang, He, Wang, Zhu, Wang, Tao, Zheng, Su and Hu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 28 May 2020
                : 28 September 2020
                Page count
                Figures: 5, Tables: 2, Equations: 0, References: 58, Pages: 13, Words: 0
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 81772071
                Award ID: 81971835
                Award ID: 81772072
                Award ID: 81201470
                Award ID: 81501663
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                skin microbiomes,intrinsic skin aging,photoaging,visia,skin immune regulation

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