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      A cross‐sectional cohort study on the skin microbiota in patients with different acne durations

      1 , 1 , 2 , 3 , 1
      Experimental Dermatology
      Wiley

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          Abstract

          Acne is a chronic disease that often persists for years. Skin microbial communities play an essential role in the development of acne. However, limited information is available about the dynamic patterns of skin microbiota in acne. This study aimed to characterize microbial community changes in skin pores and surfaces of acne patients with varying disease time. In this study, a total of 70 skin samples from 22 subjects were collected and sequenced using 16S rRNA amplicon sequencing. Although microbial compositions in skin pores were similar over time, significant differences in microbial structure were observed on the skin surface, with the dominance of Cutibacterium in the first 3 years and replacement by Staphylococcus in 4–6 years. Lactobacillus and Acinetobacter were more abundant in the normal group and continuingly decreased with disease time on the skin surface. Microbial networks further revealed substantial increases in microbial interactions in the 4–6 years group in both skin surfaces and pores. These results demonstrate that the skin microbiota alters with the disease duration and may provide a potential guide in redirecting skin microbiota towards healthy states.

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          Most cited references54

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          Is Open Access

          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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              Is Open Access

              The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

              SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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                Author and article information

                Journal
                Experimental Dermatology
                Experimental Dermatology
                Wiley
                0906-6705
                1600-0625
                December 2023
                October 17 2023
                December 2023
                : 32
                : 12
                : 2102-2111
                Affiliations
                [1 ] Human Microbiome and Health Group, Department of Microbiology, School of Basic Medical Science Central South University Changsha China
                [2 ] Department of Dermatology The Fourth Hospital of Changsha Changsha China
                [3 ] Department of Parasitology, School of Basic Medical Science Central South University Changsha China
                Article
                10.1111/exd.14951
                932e0e3f-208b-4daf-a6fd-7f33b27de75f
                © 2023

                http://onlinelibrary.wiley.com/termsAndConditions#vor

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