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- W4285992371 abstract "The skin is a habitat for commensal and pathogenic microbiota. The detection of the presence and relative abundance of bacteria and fungi, as well as disease-specific shifts in their composition is of immense interest in skin biology. Currently, deep sequencing methods are the gold standard to assess the bacterial microbiome. However, there are alternative methods available. We used the recently described method of determining bacterial communities by two-parameter flow cytometry analysis of scatter and DNA content. For analysis, we developed FlowSoFine™, an interactive, free web application. This tool works out the biological patterns from flow cytometry plots via automated gating strategies to publication ready figures. Loading and processing the raw flow cytometry data, running statistical tests and visualization through our graphical user interface can be done within an hour. To validate our method, we sampled skin (18 cm2) from the forehead, the volar arm and the toe-web spaces of 54 subjects and analyzed the samples by FlowSoFine™ and by 16S rRNA sequencing in parallel. We found that we could robustly discriminate community patterns by anatomical region. Skin microbiome analysis by 16S deep sequencing confirmed the impact of body site on microbial composition using either method. In FlowSoFine™, a non-metric multidimensional scaling (NMDS) plot is used for visualization of differences in microbial patterns between groups (e.g. treatment). Beyond that automated heatmap clustering can be applied to the samples to highlight areas with similarities within groups, which will be useful in sorting regions of interest by FACS for further down-stream analyses." @default.
- W4285992371 created "2022-07-21" @default.
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- W4285992371 date "2022-08-01" @default.
- W4285992371 modified "2023-09-28" @default.
- W4285992371 title "549 Robust detection of microbial patterns on different skin regions by flow cytometry" @default.
- W4285992371 doi "https://doi.org/10.1016/j.jid.2022.05.559" @default.
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