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. 2019 May 9;9:7160. doi: 10.1038/s41598-019-43682-w

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© The Author(s) 2019

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Comparison of microRNA expression during wound healing of skin and oral mucosal epithelium. Using a murine wound healing model of paired skin and oral mucosa wounds, microRNA profiling was performed on wound tissue samples acquired at 6 hr, 24 hr and 5 days post-wounding, and compared with unwounded baseline tissue samples (0 hr). (A) Principal component analysis (PCA) was performed on the whole dataset, and PC1 and PC2 explain 23.7% and 19.9% of the variance, respectively. PC1 can explain the variance associated with tissue specificity and PC2 appears to be associated with the variance related to wound healing time course. A total of 200 and 33 differentially expressed microRNAs (p < 0.01) were identified during oral mucosal (B) and skin epithelium (C) wound healing time course (0 hr, 6 hr, 24 hr and 5 days post-wounding), respectively. Among these microRNAs, 18 were concurrently differentially expressed (differentially expressed in both during skin and oral mucosa epithelium wound healing) (D, also see Supplementary Table S5). Common KEGG pathways regulated by differentially expressed microRNAs were predicted by DIANA-mirPath (v3.0)³⁸ using microT-CDS^39,40 as microRNA target prediction method (microT threshold = 0.8). Top 5 common KEGG pathways were presented. (E) A panel of 18-concurrently differentially expressed microRNAs was able to determine tissue specificity and wound healing time points based on hierarchical clustering analysis using on all samples (n = 24).