Commensal microbiome dysbiosis in keloid disease
Description
Wound healing is an intensely studied topic involved in many relevant pathophysiological processes, including fibrosis. Despite the large interest in fibrosis, the network that related to commensal microbiota and skin fibrosis remain mysterious. Here, we pay attention to keloid, a classical yet intractable skin fibrotic disease to establish the association between commensal microbiota to scaring tissue. Our histological data reveal the presence of microbiota in the keloids. 16S rRNA sequencing characterize microbial composition and divergence between the pathological and normal skin tissue. Our research provides insights into the pathology of human fibrotic diseases, advocating commensal bacteria and IL-8 signaling as useful targets in future interventions of recurrent keloid disease.
Notes
Methods
16S rDNA sequencing data
The data files here are raw 16S rDNA sequencing accompanied by R scripts that were used to analyze these data.
The source of the data was: (1) a swab test from the surface of normal and keloid skin; (2) the tissues of keloid patients from deeper parts of the skin.
Surface microbiota samples were collected from the pathological location or the normal lateral location of patients using a swab (Catch-all Sample Collection Swab, Epicenter) moistened in Yeast Cell Lysis Buffer (from MasterPure Yeast DNA Purification Kit; Epicenter). Samples were snap-frozen on dry ice, and DNA was isolated from specimens using the PureLink Genomic DNA Mini Kit (Invitrogen).
Amplification of the 16S-V3+V4 region was performed according to the manufacturer's specifications. Sequencing of 16S rRNA amplicons was conducted by Apexbio Co., Shanghai, China using the Illumina Novaseq platform. The data were analyzed with the attached R scripts.
Bulk RNA-Seq
For RNA sequencing, human dermal fibroblasts were treated with interleukin 8 and transforming growth factor beta in vitro. RNA was extracted using RNeasy Mini Kit (Qiagen). RNA purity and concentration measurement, preparation of RNA library, and transcriptome sequencing were conducted by TIANGEN Co. We used the HISAT2 software to compare clean reads with reference genomes. Next, we apply HTSeq-countb (v0.6.0) to analyze the gene expression level of each sample(model union). Finaly, FPKM(Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced)was used to estimate related gene expression, as seen in expression table.
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Additional details
Related works
- Is cited by
- 10.1101/2023.09.19.558395 (DOI)
- Is derived from
- 10.5281/zenodo.12596980 (DOI)
- Is source of
- 10.5281/zenodo.12596984 (DOI)