Twelve adult male mice with C57BL/6 were selected for this study. These mice originate from the experimental Animal Center of Third Xiangya Hospital, Central South University, China. The mice were aged about 8 weeks old and weighed 25–30 g. Mice were kept in a temperature and humidity-controlled facility with enough food and water. All animal feeding procedures were performed following the National Institutes of Health's Guidelines for the Care and Use of Laboratory Animals. Central South University's Bioethics Committee authorized all animal experiment procedures.

The mice were randomly divided into three experimental groups and one control group, which were control group A (with a radiance of 0 mJ/cm2), UVB irradiation group B (with a radiance of 90 mJ/cm2), UVB irradiation group C (with the radiance of 180 mJ/cm2), and UVB irradiation group D (with the radiance of 360 mJ/cm2). The mice were first sedated (intraperitoneal injection of sodium pentobarbital), and then their backs were depilated. The experiment was carried out using the UVB (290–320 nm) spectrum of the SS-03BUltraviolet Phototherapy Instrument. The mice in groups A, B, C, and D were irradiated at the dose of 0, 90, 180, and 360 mJ/m2 respectively. The modifications in the mouse's back skin were continuously monitored and photographed during the experiment. On the ninth day, the mice were killed, and the skin tissues were collected.

On day 9th, skin tissue was taken. These samples were fixed in 0.1 M phosphate buffer (PB, Ph 7.4) with 4% paraformaldehyde for 24 hours. The tissues were embedded in paraffin. Sample sections were prepared (5 μm). Hematoxylin staining of the nuclei and cytoplasmic eosin staining of the cytoplasm was done. The photographs were taken and analyzed after wiping with a microscope.

The library was prepared using the NEBNext® Multiplex Small RNA Library Prep Set for Illumina® and the nanodropND-1000 Agilent 2100 Bioanalyzer.

Agarose electrophoresis was used to check the integrity of the RNA, which was then quantified on the NanoDrop ND-1000 instrument. To remove RNA modifications that interfere with small RNA-seq library construction, the total RNA samples underwent 3’-aminoacyl (charged) deacylation to 3’-OH for 3’-adaptor ligation, 3’-cP ('2',3’-cyclic phosphate) removal to 3’-OH for 3’-adaptor ligations, 5’-OH (hydroxyl group) phosphorylation to 5’-P for 5’-adaptor ligations, and m1A and m3C demethylation for efficient reverse transcription. For miRNA-seq library preparation, each sample's total RNA was pretreated. The library preparation procedures included: 3’-adapter ligation, 5’-adapter ligation, cDNA synthesis, Polymerase Chain Reaction (PCR) amplification, size selection of ∼134–160 bp PCR amplified fragments (corresponding to ∼14–40 nt small RNAs). The Agilent 2100 Bioanalyzer was used to quantify the completed libraries. Based on the quantification results, the libraries were combined in equal proportions and used for sequencing.

The DNA fragments from the well-mixed libraries were denatured with 0.1 M NaOH to generate single-stranded DNA molecules and loaded onto the reagent cartridge at 1.8 pM. The sequencing runs were performed on the Illumina NextSeq 500 system using the NextSeq 500/550 V2 kit (#FC-404-2005, Illumina) according to the package recommendations. The sequencing was performed by running 50 cycles.

Sequence quality was examined via FastQC, and trimmed reads were aligned, which were allowed for one mismatch only. Afterward, align the unmapped reads, which were allowed for one mismatch only with bowtie software.15 Align the remaining read segments, allowing just one to mismatch with the miRNA reference sequence and miRDeep2.16 Based on the number of reads mapped, miRNA expression profiling may be estimated. The miRNAs differentially expressed are screened based on the count value with R package edgeR.17 miRNA-seq data analysis workflow is shown in Fig. 1. Figures were produced in R or Perl environment for statistical calculation and graphics of 'miRNAs' expression.

Figure 1.

miRNA-seq experiment workflow.

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Past studies have suggested TargetScan that mirdbV5 predicts miRNA targets. Only genes that were predicted by both programs to be miRNA were accepted. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) signal transduction pathway enrichment analyses were performed to predict functions of specific miRNA. The GO database was classified into three categories: biological process, cellular component, and molecular function. To assess the network of differentially expressed genes, the authors used KEGG, a pathway analysis reference database. The meaning of GO words and route terms was assessed using the p-value. The lower the p-value means a more important term (recommended p-value was ≤0.05).

Design primers: the related primers were designed and synthesized by software in Table 1. Real-time quantitative PCR: the system was established for real-time quantitative analysis. All cDNA samples were configured with a Real-time PCR reaction system. Add the sample to each hole corresponding to the PCR plate. Place the PCR plate on the real-time PCR instrument for PCR reaction. Each sample's target genes and housekeeping genes were submitted to a real-time PCR reaction. The machine-generated the concentration findings of target genes and housekeeper genes in each sample based on the gradient dilution DNA standard curve. Relative miRNA levels were normalized according to U6 snRNA, and the mean and standard error were calculated.

The data were presented as means ± standard deviations. miRNA expression followed a discrete distribution. Accordingly, the significant differences between groups were compared by a negative binomial distribution. The differentially expressed miRNAs were then screened. The recommended p-value was ≤0.05.

H&E and Masson staining were exhibited in Fig. 2. Compared to the control group A, the epidermis layer of the experimental 'groups' B/C/D increased at different levels. Furthermore, the thickness increased with the increase in radiation dose. The dermis layer in control group A had a uniform distribution of fibrous tissue, whereas the dermis layer in experimental groups B/C/D showed a disordered fiber arrangement. Compared with control group A, experimental group B had mild epidermal thickening, dermal papillary layer, intact basement membrane, and a small amount of inflammatory cell infiltration, indicating that ultraviolet radiation had a damaging effect on the skin. Compared with experimental group B, the epidermis of experimental group C continues to thicken, and the dermal papilla layer could be seen, the basement membrane degradation and inflammatory cell infiltration could be seen. Compared with control group A, the thickness of the skin epidermis in experimental group D was significantly different, and even some areas of skin necrosis and falling off, the arrangement of dermis tissue was disordered, the basement membrane degradation and inflammatory cell infiltration could be seen.

Figure 2.

Histological changes of mouse back skin under different doses of UVB irradiation. See Figure A for HE is staining and Figure B for Masson staining. Radiation of Group A dose is 0 mJ/cm2; Radiation of Group B dose is 90 mJ/cm2; Radiation of Group C dose is 180 mJ/cm2; Radiation of Group D dose is 360 mJ/cm2. Scale bars are 100 µm.

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Volcano plots were plotted based on miRNA with CPM values (see Fig. 3). According to these volcano plots, the authors could find the differential expression of miRNAs. There were 87 up-regulated miRNAs and 100 downregulated miRNAs in Fig. 3A (B vs. A). In Fig. 3B (C vs. A), there were 106 up-regulated miRNA and 113 downregulated miRNAs. In Fig. 3C (D vs. A), there were 105 up-regulated miRNA and 163 downregulated miRNAs.

Figure 3.

Differentially expressed miRNA screening. (A), The volcano plots. Red circles indicate statistically up-regulated expression, green circles indicate down-regulated, and grey circles indicate non-differentially expressed miRNAs. (B), The hierarchical clustering heatmap for miRNAs. The color scale is show below: blue represents an expression level below the mean, and red represents an expression lever above the mean.

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Hierarchical clustering using differentially expressed miRNAs is shown in Fig. 3. Each row represented a different miRNA, and each column represented a different sample. The findings of hierarchical clustering revealed that there were differences in the expression of miRNAs between samples. The authors screened 7 significantly up-regulated miRNAs and 16 significantly down-regulated miRNAs in groups B vs. A, C vs. A, and D vs. A (see Fig. 3D/E/F).

First, standardize the original data. Then, 23 differentially expressed miRNAs were exposed by miRNA sequencing results. Compared with the Ctrl-A group, 16 miRNAs were downregulated, and 7 miRNAs were up-regulated in the irradiated mice group (Supplementary Tables 1 and 2).

Targetscan7.1 and mirdbV5wereused to predict 'miRNAs' target genes. Targetscan7.1: (from http://www.targetscan.org/mmu_71/). MirdbV5: (from http://mirdb.org/miRDB/.Targetscan7.1 identified 463 target genes in the 7 up-regulated miRNAs; mirdbV5 predicted 988 target genes, and the intersection of two target genes was 191, as shown by the Venn diagram (Fig. 4A). In the 16 down-regulated miRNAs, targetscan7.1 predicted 4146 target genes, mirdbV5 predicted 4711 target genes, and the intersection of two target genes was 1756, which were reflected by the Venn diagram (Fig. 4B). Using the 191 up-regulated target genes and 1,756 down-regulated target genes that the authors predicted, the authors developed a network diagram (Fig. 4C-D) to show the relationship between miRNAs and target genes. The blue circular nodes in the following network represent mRNAs, whereas the red rectangle nodes represent miRNAs. It is necessary to predict the target of the miRNA regulatory gene to further understand the miRNA function. Through GO analysis, the authors have detected the GO terms to predict the function of these target genes. Fig. 4E shows all of the up-regulated miRNA target genes, as well as the top ten GO terms with the highest enrichment. Similarly, the target genes for miRNA with a downregulation trend are listed in Fig. 4F. According to bioinformatics analysis, the authors believe that the predicted target gene function of up-regulating miRNA is mainly concentrated in the intracellular part, cellular macromolecule metabolic process, and protein binding. The target gene's function in downregulating miRNA is primarily focused on intracellular binding and control of the macromolecule metabolic process. The gene was shown to be a component of the KEGG signaling pathway. Through Pathway analysis, the authors screened out some signal pathways closely related to UV-induced acute skin injury. According to the findings, the most prevalent genes in the down-regulation genes were those involved in cancer, human papillomavirus infection, and the MAPK signaling system (see Fig. 4G-H). The authors chose the MAPK signaling pathway for further study because the first two pathways had minimal correlation with the acute injury the authors evaluated.

Figure 4.

Bioinformatic Prediction. (A-B), Venn diagram. (C), The up-regulated miRNA network analysis. (D), The downregulated miRNA network analysis. The general GO annotations for cellular component, molecular function, and biological processes of the target genes regulated by the up-regulated miRNAs (E) and downregulated miRNAs (F). KEGG pathway analysis of the target genes regulated by the up-regulated miRNAs (G) and downregulated miRNAs (H).

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MAPK pathway is a common pathway in the human body which is related to stress and other complex physiological processes. Radiation, osmotic pressure changes, growth factors, and cytokines are all instances of stimuli that might activate the MAPK signal transduction pathway. The five important target genes predicted by miR-195a-5p were all located in the MAPK signaling pathway; they were AKT(AKT323797), RTK (INSR 16337), JNK (MAPK8 26419), MEK1(MAP2K1 26395), MNK1/2(MKNK1 17346), GF (VEGFA 22339) (see Fig. 5). It was suggested that ultraviolet radiation could induce acute skin injury by down-regulating miR-195a-5p and activating MAPK signaling pathway.

Figure 5.

MAPK Signaling Pathway.

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The relative expression of miR-195a-5p in several experimental groups was statistically examined. It can be seen from Fig. 6 that the expression of miR-195a-5p in the three experimental groups showed a downward trend after UV irradiation, which was in accord with the prediction of miR-195a-5p. Therefore, miR-195a-5p was selected for further study.

Figure 6.

Validation of miRNA-195a-5p using RT-qPCR. The data were normalized using the mean ± Standard Error of the Mean (SEM). ∗∗∗p ≤ 0.001, ∗∗∗∗p ≤ 0.0001.

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