, Volume 18, Issue 3, pp 361–371 | Cite as

Genome-wide expression analysis of wounded skin reveals novel genes involved in angiogenesis

  • Simone Brönneke
  • Bodo Brückner
  • Jörn Söhle
  • Ralf Siegner
  • Christoph Smuda
  • Franz Stäb
  • Horst Wenck
  • Ludger Kolbe
  • Elke Grönniger
  • Marc WinnefeldEmail author
Original Paper


Wound healing is a multistage process involving collaborative efforts of different cell types and distinct cellular functions. Among others, the high metabolic activity at the wound site requires the formation and sprouting of new blood vessels (angiogenesis) to ensure an adequate supply of oxygen and nutrients for a successful healing process. Thus, a cutaneous wound healing model was established to identify new factors that are involved in vascular formation and remodeling in human skin after embryonic development. By analyzing global gene expression of skin biopsies obtained from wounded and unwounded skin, we identified a small set of genes that were highly significant differentially regulated in the course of wound healing. To initially investigate whether these genes might be involved in angiogenesis, we performed siRNA experiments and analyzed the knockdown phenotypes using a scratch wound assay which mimics cell migration and proliferation in vitro. The results revealed that a subset of these genes influence cell migration and proliferation in primary human endothelial cells (EC). Furthermore, histological analyses of skin biopsies showed that two of these genes, ALBIM2 and TMEM121, are colocalized with CD31, a well known EC marker. Taken together, we identified new genes involved in endothelial cell biology, which might be relevant to develop therapeutics not only for impaired wound healing but also for chronic inflammatory disorders and/or cardiovascular diseases.


Angiogenesis Genome-wide expression analyses Human skin Wound healing 



We thank Sonja Wessel, Boris Kristof, and Thomas Lange for helpful discussions and support concerning capillary microscopy and analyses.

Conflict of interest

All authors were employees at Beiersdorf at the time point of the study. B. Brückner received consultation fees from Beiersdorf.

Supplementary material

10456_2015_9472_MOESM1_ESM.pptx (58 kb)
Supplementary material 1 S1 Preprocessing of the microarray data. Flowchart showing the different steps in the microarray experiments and the preprocessing of the microarray data. (PPTX 57 kb)
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Supplementary material 2 S2 FGFR-1 knockdown reduced endothelial wound closure in vitro. a Expression of FGFR-1 after siRNA-induced knockdown was analyzed 24 h after transfection using qRT-PCR. b The Relative Wound Density in % of scrambled siRNA-transfected blood endothelial cells was compared with siFGFR-1-transfected cells, 30 h after cell scraping. The Relative Wound Density of control-transfected cells was set as 100% and is shown as the dotted line. The horizontal black lines denote medians and whiskers the 2.5th and 97.5th percentiles. Significant differences are indicated by asterisks. * = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001 (unpaired t test). N (scrambled) = 10, n(siFGFR-1) = 6. c Primary endothelial cell viability was measured using Cell-Titer-Blue-Cell Viability Assay (Promega). The data were normalized to scrambled siRNA which is marked as the dotted line. As a negative control, we used cells which were treated with cis-diammineplatinum(II)dichloride (10 µg/mL) for 24 h. n = 12–24. (PPTX 55 kb)
10456_2015_9472_MOESM3_ESM.pptx (77 kb)
Supplementary material 3 S3 Efficiency of siRNA-induced gene knockdown. Primary endothelial cells were transfected with 3 different siRNAs per gene, indicated by the number 1, 2, or 3 (only the two most potent ones are depicted). Expression of siRNA-induced knockdown of a ABLIM2, b GGCT, c SULF2, d TMEM121, and e ZSCAN18 were analyzed 24 h after transfection using qRT-PCR. Knockdown of the corresponding genes was compared to scrambled siRNA-transfected endothelial cells, which were set to 100 %. The horizontal black lines denote medians and whiskers the 2.5th and 97.5th percentiles. Significant differences are indicated by asterisks. * = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001 (unpaired t test). n = 6. (PPTX 76 kb)
10456_2015_9472_MOESM4_ESM.pptx (148 kb)
Supplementary material 4 S4 Cell viability and apoptotic activity after siRNA knockdown. Primary endothelial cells were transfected with 3 different siRNAs per gene, indicated by the number 1, 2, or 3 (only the two most potent ones are depicted). a Cell viability was analyzed 48 h after knockdown of the following genes: ABLIM2, GGCT, SULF2, TMEM121, ZSCAN18, and FGFR-1. Scrambled siRNA-transfected endothelial cells served as controls and were set to 100 %. b Apoptotic activity was determined 48 h after knockdown. For a positive control, cell populations were cultivated for 24 h in the presence of staurosporine. (PPTX 147 kb)
10456_2015_9472_MOESM5_ESM.pptx (75 kb)
Supplementary material 5 S5 Proliferative effects in in vitro wound closure. To analyze the effects of proliferation, cell nuclei were counted via propidium iodide staining. The impact of gene knockdown of a ABLIM2, b GGCT, c SULF2, d TMEM121, and e ZSCAN18 was studied. The left panel shows the results from the first, and the right panel the results from the second screen. The average value of the scrambled control is shown as the dotted line. The horizontal black lines denote medians and whiskers the 2.5th and 97.5th percentiles. Comparison between scrambled siRNA- and siFGFR-1-transfected cells was significant with p ≤ 0,001 (asterisks not shown). Significant differences are indicated by asterisks. * = p ≤ 0.05; ** = p ≤ 0.01; *** = p ≤ 0.001 (unpaired t test). n (per single siRNA) = 6. (PPTX 75 kb)
10456_2015_9472_MOESM6_ESM.pptx (1.4 mb)
Supplementary material 6 S6 Histological analysis of ABLIM2 and TMEM121. Images captured by immunofluorescence microscopy are shown for one representative volunteer. Skin samples were taken 2 weeks after suction blistering and embedded in paraffin. For DNA staining, Hoechst 33342 was used. a) (Co)localization of CD31, ABLIM2. Bar 50 µm. b) (Co)localization of CD31, ABLIM2 in a higher resolution. Bar: 20 µm. c) (Co)localization of CD31, TMEM121. Bar 50 µm. d) (Co)localization of CD31, TMEM121 in a higher resolution. Bar: 20 µm. (PPTX 1425 kb)
10456_2015_9472_MOESM7_ESM.pptx (43 kb)
Supplementary material 7 S7 Expression of ABLIM2, GGCT, SULF2, TMEM121, and ZSCAN18 in different tissues and cell types. The heat map shows the expression intensities (in percent) of the selected genes normalized to GAPDH intensities (Gene Intensity / GAPDH Intensity * 100). The mean values of 5 or 3 independent microarray experiments have been determined. Color code: blue = highly expressed; red = slightly expressed. (PPTX 43 kb)
10456_2015_9472_MOESM8_ESM.xlsx (18 kb)
Supplementary material 8 Table S1: Summary of cleaned set of 90 samples. sb: suction blister; co: control. (XLSX 18 kb)
10456_2015_9472_MOESM9_ESM.xlsx (16 kb)
Supplementary material 9 Table S2: Differentially expressed genes between wounded and unwounded skin that are enriched in the “Function Angiogenesis.” The analysis has been conducted using the Ingenuity software. (XLSX 15 kb)
10456_2015_9472_MOESM10_ESM.xlsx (25 kb)
Supplementary material 10 Table S3: List of the 48 genes, which are differentially expressed between unwounded (co) and wounded (sb) skin as well as expressed in primary human dermal endothelial cells. Three different siRNAs (Qiagen) were tested per gene. Target sequences are listed, respectively. (XLSX 24 kb)
10456_2015_9472_MOESM11_ESM.xlsx (17 kb)
Supplementary material 11 Table S4: RNA expression differences (FC) of the 48 genes between unwounded skin and skin 2 weeks after wounding. (XLSX 17 kb)
10456_2015_9472_MOESM12_ESM.xlsx (15 kb)
Supplementary material 12 Table S5: RNA expression differences (FC) of the 5 genes between unwounded and wounded skin are listed over time of the wound healing process. Positive data reflect repression, whereas negative data reflect increased expression of the associated gene in sb vs. co. (XLSX 15 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Simone Brönneke
    • 1
  • Bodo Brückner
    • 2
  • Jörn Söhle
    • 1
  • Ralf Siegner
    • 1
  • Christoph Smuda
    • 1
  • Franz Stäb
    • 1
  • Horst Wenck
    • 1
  • Ludger Kolbe
    • 1
  • Elke Grönniger
    • 1
  • Marc Winnefeld
    • 1
    Email author
  1. 1.Research and DevelopmentBeiersdorf AGHamburgGermany
  2. 2.HeidelbergGermany

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