# Comparison of Stemness and Gene Expression between Gingiva and Dental Follicles in Children

Authors: Chung-Min Kang; Seong-Oh Kim; Mijeong Jeon; Hyung-Jun Choi; Han-Sung Jung; Jae-Ho Lee
Journal: Stem Cells International
 (2016)

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## Abstract

The aim of this study was to compare the differential gene expression and stemness in the human gingiva and dental follicles (DFs) according to their biological characteristics. Gingiva (n=9) and DFs (n=9) were collected from 18 children. Comparative gene expression profiles were collected using cDNA microarray. The expression of development, chemotaxis, mesenchymal stem cells (MSCs), and induced pluripotent stem cells (iPSs) related genes was assessed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Histological analysis was performed using hematoxylin-eosin and immunohistochemical staining. Gingiva had greater expression of genes related to keratinization, ectodermal development, and chemotaxis whereas DFs exhibited higher expression levels of genes related to tooth and embryo development. qRT-PCR analysis showed that the expression levels of iPSc factors includingSOX2,KLF4, andC-MYC were 58.5±26.3, 12.4±3.5, and 12.2±1.9 times higher in gingiva andVCAM1 (CD146) andALCAM (CD166) were 33.5±6.9 and 4.3±0.8 times higher in DFs. Genes related to MSCs markers includingCD13,CD34,CD73,CD90, andCD105 were expressed at higher levels in DFs. The results of qRT-PCR and IHC staining supported the microarray analysis results. Interestingly, this study demonstrated transcription factors of iPS cells were expressed at higher levels in the gingiva. Given the minimal surgical discomfort and simple accessibility, gingiva is a good candidate stem cell source in regenerative dentistry.


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## Body

## 1. Introduction

Tissue engineering using mesenchymal stem cells (MSCs) is one of the most promising therapeutic strategies because MSCs have a high proliferation potential and may be manipulated to permit differentiation before transplantation [1, 2]. To date, different human dental stem cells have been isolated from dental pulp stem cells (DPSCs) [3], stem cells from exfoliated deciduous teeth (SHED) [4], periodontal ligament (PDL) stem cells [5], stem cells from apical papilla (SCAP) [6], and dental follicle precursor cells (DFPCs) [7]. Recently, mounting evidence suggests that gingiva derived mesenchymal stem cells were isolated and characterized as having multilineage differentiation capacity and immunomodulatory properties [8]. The presence of stem cell populations in dental follicles and the gingiva was revealed recently, and the related gene expression patterns remain unclear.The dental follicle (DF) tissue is a connective fibrous tissue sac surrounding the enamel organ and the dental papilla of the developing tooth germ [9]. The DF cells have been proposed to have the capacity to differentiate into periodontium consisting of cementum, alveolar bone, and PDL [10, 11]. Despite an ectomesenchymal origin similar to that of the DFs, the gingiva appears to exhibit distinct functional activities during the maintenance of tissue integrity and during inflammatory responses [12]. It possesses a unique scarless healing process after wounding instead of the scar formation that is frequently observed in damaged extraoral tissues. So gingival tissue is postulated to have distinctive characteristics that accelerate wound closure, suggesting unique stemness with the ability to induce directed differentiation and regeneration.Although some efforts were made to identify the genes that are differentially expressed in the periodontium [12–14], the genetic differences between the gingiva and DFs remain unknown. Given the anatomical and functional differences between the two tissues, it is reasonable to assume that there are also differences in the gene expression patterns. Thus, genetic investigation related to epithelial-mesenchyme interaction between gingiva and dental follicle can provide critical importance in regulating cell population and signaling system in the regeneration of periodontium. The aim of this study is to compare the gene expression patterns of the gingiva and DFs to enhance our understanding of the distinct regenerative ability in gingiva and tissue differentiation capacity in DFs.


## 2. Materials and Methods

The Institutional Review Board of the Yonsei University Dental Hospital approved the experimental protocol (approval number 2-2015-0005). All the subjects or their guardians have provided written informed consent. We used procedures similar to that recently applied by Song et al. [15] and Lee et al. [14].


### 2.1. Tissue Sampling and RNA Isolation

Gingival tissues were collected from children (n=9) (5 males and 4 females, aged 7–12 years) with a healthy gingiva who underwent surgical gingival resection for the extraction of a supernumerary tooth, for odontoma, or for orthodontic reasons. The DF tissues were obtained from children (n=9) (6 males and 3 females, aged 6–8 years), and they were separated from the coronal portion of the tooth during the extraction of supernumerary teeth. In DF, a piece of gingival tissue around the extraction socket was carefully curetted. These samples were immediately frozen and stored in liquid nitrogen. We used fresh tissue instead of cultured cells because, at the tissue level, gene expression reflects simultaneous profiles of many genes and can provide additional insights into the physiological processes or tissue-specific functions that are mediated by the coordinated action of sets of genes. Gingiva and DFs were immediately submerged in RLT buffer, which is a component of the RNeasy Fibrous Mini kit® (Qiagen, CA, USA). Prior to the RNA extraction, the tissues in RLT buffer were homogenized using a Bullet Blender® Bead (Next Advanced, Inc., NY, USA). Total RNA was extracted from gingiva and DFs using the RNeasy Fibrous Mini kit (Qiagen, USA) according to the manufacturer’s instructions. The extracted RNA was eluted in 25 μL of sterile water. RNA concentrations were measured from absorbance values at a wavelength of 260 nm using a spectrophotometer (NanoDrop ND-2000, Thermo Scientific, IL, USA). The RNA samples used in this study had 260/280 ratios of at least 1.8.


### 2.2. cDNA Microarray Construction and Data Analysis

Global gene expression analyses were performed using Affymetrix Gene Chip® Human Gene 1.0 ST oligonucleotide arrays (Affymetrix Inc., CA, USA). The average amount of RNA isolated from the gingiva and DFs was 1μg. As recommended by the manufacturer’s protocol, 300 ng of total RNA from each sample was converted to double-stranded cDNA. The cDNA was regenerated via random-primed reverse transcription using a dNTP mix containing dUTP. The fragmented, end-labeled cDNA was hybridized to the Gene Chip® Human Gene 1.0 ST array for 16 hours at 45°C and 60 rpm with a terminal transferase reaction incorporating a biotinylated dideoxynucleotide. After hybridization, the chips were stained and washed in a Genechip Fluidics Station 450® (Affymetrix) and scanned using a Genechip Array scanner 3000 G7® (Affymetrix). To determine whether genes were differentially expressed between the separated tissue groups, a one-way ANOVA was performed on the Robust Multi-Average (RMA) expression values. A multiple testing correction was applied to the p values of the F-statistics to adjust the false discovery rate. Genes with adjusted F-statistic p values <0.05 were extracted. Genes that were highly expressed in the gingiva or DFs and that exhibited differences greater than 4-fold between the signal value of the control and the test group were selected for further study. These genes were then classified based on the information related to gene function that is available in Gene Ontology from the KEGG Pathway database (http://david.abcc.ncifcrf.gov/home.jsp). This microarray data set was approved by the Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo/); the GEO accession numbers of the data set are GSE58480 (gingiva) and GSE51342 (dental follicle).


### 2.3. Quantitative RT-PCR

The single-stranded cDNA required for the polymerase chain reaction (PCR) analysis was produced using 500 ng of extracted total RNA as a template for reverse transcription (RT) (Superscript III Reverse Transcriptase and random primer, Invitrogen, UK). The RT reaction was incubated at 65°C for 5 minutes, then 25°C (5 min), 50°C (1 hr), and 70°C (15 min) to inactivate the activity of the reverse transcriptase. The synthesized cDNA was diluted 1 : 10 in distilled water and used as a template for quantitative RT-PCR using the ABI7300 RT-PCR system (Applied Biosystems, Warrington, UK). The samples were prepared in triplicate with a volume of 25μL containing 1x Universal TaqMan Master Mix (4369016, Applied Biosystems), the PCR primers at 0.9 μM, and the diluted cDNA. The amplification conditions were 50°C for 2 minutes and 95°C for 10 minutes, followed by 40 cycles of 95°C for 15 seconds and 60°C for 1 minute. The following TaqMan gene expression assay primers (Applied Biosystems) were used: KRT6A, CXCL10, CSTA, AMBN, ADAM12, CXCL12, cMYC, KLF4, SOX2, CD106 (VCAM1), CD166 (ALCAM), and 18S rRNA. We selected known genes that are representative of the two tissues and little-known genes that are involved in their physiological functions.ABI 7300 SDS 1.3.1 software (Applied Biosystems) recorded the fluorescence intensity of the reporter and quencher dyes, and results are plotted versus time, represented by the cycle number. The amplification plots were examined during the early log phase of product accumulation above background (the threshold cycle number, Ct) to obtain a precise quantification of initial target. The Ct values (the threshold cycle (Ct) number) were subsequently used to determine ΔCt values (ΔCt = Ct of the gene minus Ct of the 18S rRNA control). Relative expressions were expressed as the relative change by applying the equation2-ΔΔCt (ΔΔCt; differences in ΔCt values). All these quantitative RT-PCR procedures were done obtaining triplicated data. The results were analyzed using SPSS 20 software (SPSS Inc., IL, USA). Statistical differences were calculated by Mann–Whitney U tests, and p<0.05 was considered statistically significant. The specific primer assay ID and product sizes for each gene are listed in Table 1.Table 1
Specific primer used for quantitative RT-PCR analysis.
Gene symbol Functions Assay ID Product size (bp) KRT6A Ectoderm development, positive regulation of cell proliferation, cell differentiation Hs01699178_g1 83 CXCL10 Positive regulation of leukocyte, chemotaxis Hs01124251_g1 135 CSTA Keratinocyte differentiation, negative regulation of peptidase activity Hs00193257_m1 114 AMBN Cell proliferation, bone mineralization, odontogenesis of dentin-containing tooth Hs00212970_m1 61 ADAM12 Cell-cell and cell-matrix interactions, including fertilization, muscle development, neurogenesis Hs01106101_m1 54 CXCL12 Immune response, positive regulation of monocyte chemotaxis Hs03676656_mH 88 C-MYC Regulation of transcription, DNA-dependent Hs00153408_m1 107 KLF4 Mesodermal cell fate determination, negative regulation of cell proliferation, regulation of transcription Hs00358836_m1 110 SOX2 Negative regulation of transcription from RNA polymerase II promoter, osteoblast differentiation Hs01053049_s1 91 CD106 Response to hypoxia, acute inflammatory response, chronic inflammatory response Hs01003372_m1 62 CD166 Cell adhesion, signal transduction, motor axon guidance Hs00977641_m1 103 18S rRNA  Hs03003631_g1 69


### 2.4. Immunohistochemical Staining

For immunohistochemical staining, gingival tissue and DF tissue were fixed in 10% buffered formalin for 1 day, embedded in paraffin, and then sectioned at a thickness of 3μm. The specimens were subjected to IHC staining with antibodies specific for CXCL10 (rabbit polyclonal, diluted 1 : 50; Ab9807, Abcam, Cambridge, UK), CSTA (rabbit polyclonal, diluted 1 : 2,000; Ab61223, Abcam), AMBN (rabbit polyclonal, diluted 1 : 200; Ab116347, Abcam), and CXCL12 (rabbit polyclonal, diluted 1 : 50; Ab9797, Abcam). Endogenous peroxidase activity was quenched via addition of 3% hydrogen peroxide. The sections were incubated in 5% bovine serum albumin to block nonspecific binding. The primary antibodies were diluted to facilitate optimal staining, and the sections were incubated overnight. After incubation, EnVision+ System HRP-Labeled Polymer anti-rabbit (K4003, Dako North America, Inc., CA, USA) was applied for 20 min. Color development was performed using labeled streptavidin biotin kits (Dako) according to the manufacturer’s instructions.


## 2.1. Tissue Sampling and RNA Isolation

Gingival tissues were collected from children (n=9) (5 males and 4 females, aged 7–12 years) with a healthy gingiva who underwent surgical gingival resection for the extraction of a supernumerary tooth, for odontoma, or for orthodontic reasons. The DF tissues were obtained from children (n=9) (6 males and 3 females, aged 6–8 years), and they were separated from the coronal portion of the tooth during the extraction of supernumerary teeth. In DF, a piece of gingival tissue around the extraction socket was carefully curetted. These samples were immediately frozen and stored in liquid nitrogen. We used fresh tissue instead of cultured cells because, at the tissue level, gene expression reflects simultaneous profiles of many genes and can provide additional insights into the physiological processes or tissue-specific functions that are mediated by the coordinated action of sets of genes. Gingiva and DFs were immediately submerged in RLT buffer, which is a component of the RNeasy Fibrous Mini kit® (Qiagen, CA, USA). Prior to the RNA extraction, the tissues in RLT buffer were homogenized using a Bullet Blender® Bead (Next Advanced, Inc., NY, USA). Total RNA was extracted from gingiva and DFs using the RNeasy Fibrous Mini kit (Qiagen, USA) according to the manufacturer’s instructions. The extracted RNA was eluted in 25 μL of sterile water. RNA concentrations were measured from absorbance values at a wavelength of 260 nm using a spectrophotometer (NanoDrop ND-2000, Thermo Scientific, IL, USA). The RNA samples used in this study had 260/280 ratios of at least 1.8.


## 2.2. cDNA Microarray Construction and Data Analysis

Global gene expression analyses were performed using Affymetrix Gene Chip® Human Gene 1.0 ST oligonucleotide arrays (Affymetrix Inc., CA, USA). The average amount of RNA isolated from the gingiva and DFs was 1μg. As recommended by the manufacturer’s protocol, 300 ng of total RNA from each sample was converted to double-stranded cDNA. The cDNA was regenerated via random-primed reverse transcription using a dNTP mix containing dUTP. The fragmented, end-labeled cDNA was hybridized to the Gene Chip® Human Gene 1.0 ST array for 16 hours at 45°C and 60 rpm with a terminal transferase reaction incorporating a biotinylated dideoxynucleotide. After hybridization, the chips were stained and washed in a Genechip Fluidics Station 450® (Affymetrix) and scanned using a Genechip Array scanner 3000 G7® (Affymetrix). To determine whether genes were differentially expressed between the separated tissue groups, a one-way ANOVA was performed on the Robust Multi-Average (RMA) expression values. A multiple testing correction was applied to the p values of the F-statistics to adjust the false discovery rate. Genes with adjusted F-statistic p values <0.05 were extracted. Genes that were highly expressed in the gingiva or DFs and that exhibited differences greater than 4-fold between the signal value of the control and the test group were selected for further study. These genes were then classified based on the information related to gene function that is available in Gene Ontology from the KEGG Pathway database (http://david.abcc.ncifcrf.gov/home.jsp). This microarray data set was approved by the Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo/); the GEO accession numbers of the data set are GSE58480 (gingiva) and GSE51342 (dental follicle).


## 2.3. Quantitative RT-PCR

The single-stranded cDNA required for the polymerase chain reaction (PCR) analysis was produced using 500 ng of extracted total RNA as a template for reverse transcription (RT) (Superscript III Reverse Transcriptase and random primer, Invitrogen, UK). The RT reaction was incubated at 65°C for 5 minutes, then 25°C (5 min), 50°C (1 hr), and 70°C (15 min) to inactivate the activity of the reverse transcriptase. The synthesized cDNA was diluted 1 : 10 in distilled water and used as a template for quantitative RT-PCR using the ABI7300 RT-PCR system (Applied Biosystems, Warrington, UK). The samples were prepared in triplicate with a volume of 25μL containing 1x Universal TaqMan Master Mix (4369016, Applied Biosystems), the PCR primers at 0.9 μM, and the diluted cDNA. The amplification conditions were 50°C for 2 minutes and 95°C for 10 minutes, followed by 40 cycles of 95°C for 15 seconds and 60°C for 1 minute. The following TaqMan gene expression assay primers (Applied Biosystems) were used: KRT6A, CXCL10, CSTA, AMBN, ADAM12, CXCL12, cMYC, KLF4, SOX2, CD106 (VCAM1), CD166 (ALCAM), and 18S rRNA. We selected known genes that are representative of the two tissues and little-known genes that are involved in their physiological functions.ABI 7300 SDS 1.3.1 software (Applied Biosystems) recorded the fluorescence intensity of the reporter and quencher dyes, and results are plotted versus time, represented by the cycle number. The amplification plots were examined during the early log phase of product accumulation above background (the threshold cycle number, Ct) to obtain a precise quantification of initial target. The Ct values (the threshold cycle (Ct) number) were subsequently used to determine ΔCt values (ΔCt = Ct of the gene minus Ct of the 18S rRNA control). Relative expressions were expressed as the relative change by applying the equation2-ΔΔCt (ΔΔCt; differences in ΔCt values). All these quantitative RT-PCR procedures were done obtaining triplicated data. The results were analyzed using SPSS 20 software (SPSS Inc., IL, USA). Statistical differences were calculated by Mann–Whitney U tests, and p<0.05 was considered statistically significant. The specific primer assay ID and product sizes for each gene are listed in Table 1.Table 1
Specific primer used for quantitative RT-PCR analysis.
Gene symbol Functions Assay ID Product size (bp) KRT6A Ectoderm development, positive regulation of cell proliferation, cell differentiation Hs01699178_g1 83 CXCL10 Positive regulation of leukocyte, chemotaxis Hs01124251_g1 135 CSTA Keratinocyte differentiation, negative regulation of peptidase activity Hs00193257_m1 114 AMBN Cell proliferation, bone mineralization, odontogenesis of dentin-containing tooth Hs00212970_m1 61 ADAM12 Cell-cell and cell-matrix interactions, including fertilization, muscle development, neurogenesis Hs01106101_m1 54 CXCL12 Immune response, positive regulation of monocyte chemotaxis Hs03676656_mH 88 C-MYC Regulation of transcription, DNA-dependent Hs00153408_m1 107 KLF4 Mesodermal cell fate determination, negative regulation of cell proliferation, regulation of transcription Hs00358836_m1 110 SOX2 Negative regulation of transcription from RNA polymerase II promoter, osteoblast differentiation Hs01053049_s1 91 CD106 Response to hypoxia, acute inflammatory response, chronic inflammatory response Hs01003372_m1 62 CD166 Cell adhesion, signal transduction, motor axon guidance Hs00977641_m1 103 18S rRNA  Hs03003631_g1 69


## 2.4. Immunohistochemical Staining

For immunohistochemical staining, gingival tissue and DF tissue were fixed in 10% buffered formalin for 1 day, embedded in paraffin, and then sectioned at a thickness of 3μm. The specimens were subjected to IHC staining with antibodies specific for CXCL10 (rabbit polyclonal, diluted 1 : 50; Ab9807, Abcam, Cambridge, UK), CSTA (rabbit polyclonal, diluted 1 : 2,000; Ab61223, Abcam), AMBN (rabbit polyclonal, diluted 1 : 200; Ab116347, Abcam), and CXCL12 (rabbit polyclonal, diluted 1 : 50; Ab9797, Abcam). Endogenous peroxidase activity was quenched via addition of 3% hydrogen peroxide. The sections were incubated in 5% bovine serum albumin to block nonspecific binding. The primary antibodies were diluted to facilitate optimal staining, and the sections were incubated overnight. After incubation, EnVision+ System HRP-Labeled Polymer anti-rabbit (K4003, Dako North America, Inc., CA, USA) was applied for 20 min. Color development was performed using labeled streptavidin biotin kits (Dako) according to the manufacturer’s instructions.


## 3. Results

### 3.1. Gene Expression Profiles of the Gingiva and Dental Follicles

1,182 out of 33,297 (3.6%) genes exhibited an absolute expression change of at least 4-fold. The expression levels of 555 genes were 4-fold higher in the gingiva than in DFs, while the expression levels of 627 genes were at least 4-fold higher in DFs than in the gingiva. The overall data distribution and frequency were confirmed by density and box plots of the ratio of the standardized log intensity to the average intensity. Ultimately, 829 genes were analyzed further, with the exception of several genes with unknown biological functions. The data were further filtered, and the genes are listed in Tables2 and 3 according to their relative biological functions. In the gingiva, the expression levels of 387 genes were upregulated by 4-fold or more in comparison to DFs, while the expression levels of 442 genes were upregulated by 4-fold in DFs in comparison to the gingiva.Table 2
Representative genes differentially expressed with higher expression levels in the gingiva than in dental follicles (absolute fold change > 4.0).
Functional category Gene symbol Biological process Accession number Absolute fold change Standard deviation Metabolism and catabolism LIPK Lipid catabolic process NM_001080518 90.99 11.87 FMO2 Organic acid metabolic process NM_001460 34.26 7.05 ARG1 Arginine catabolic process NM_000045 18.91 5.06 LIPN Lipid catabolic process NM_001080518 13.27 4.19  Protein modification and maintenance KLK7 Proteolysis NM_139277 30.47 6.52 KLK10 Proteolysis NM_002776 28.97 6.34 KLK6 Protein autoprocessing NM_002774 25.58 6.10 TGM1 Protein modification process NM_000359 22.21 5.48 OCLN Protein complex assembly NM_002538 12.48 4.48  Structural process SPRR2A Keratinization NM_005988 207.84 18.61 KRT1 Keratinization NM_006121 146.08 15.41 CNFN Keratinization NM_032488 74.92 10.64 CSTA Keratinocyte differentiation NM_005213 69.63 10.22 KRT4 Cytoskeleton organization NM_002272 39.48 7.50 KRT3 Cytoskeleton organization NM_057088 36.71 7.23 FLG Keratinocyte differentiation NM_002016 24.31 5.75 DSP Keratinocyte differentiation NM_004415 17.15 5.22  Transport activity CLCA4 Ion transport NM_012128 48.96 8.48 AQP3 Water transport NM_004925 27.74 6.41 SLC5A1 Transmembrane transport NM_000343 19.52 5.09 GLTP Glycolipid transport NM_016433 7.56 3.04  Developmental process KRT10 Epidermis development NM_000421 152.93 15.74 SCEL Epidermis development NM_144777 134.38 14.68 KRT6B Ectoderm development NM_005555 90.30 12.11 KRT6A Ectoderm development NM_005554 57.61 9.64 SPINK5 Epidermal cell differentiation NM_001127698 55.60 9.34 EHF Epithelial cell differentiation NM_012153 14.27 5.50 SOX2 Embryonic development NM_003106 8.67 3.34 TUFT1 Odontogenesis NM_020127 7.87 3.19  Physiologic process RHCG Regulation of pH NM_016321 51.23 8.68 ABCA12 Cellular homeostasis NM_173076 39.33 7.55 EREG Angiogenesis NM_001432 13.04 4.29 NMU Gastric acid secretion NM_006681 12.72 4.05 SCD Oxidation reduction NM_005063 4.35 2.25  Nucleic acid synthesis and modification MACC1 Regulation of cell division NM_182762 20.30 5.38 ESRP1 mRNA processing NM_017697 17.02 5.85 HIST1H1B Nucleosome assembly NM_005322 6.85 2.91  Signal transduction and regulation IL1F9 Cell-cell signaling NM_019618 26.31 6.03 ARAP2 Signal transduction NM_015230 9.88 3.89 DAPP1 Signal transduction NM_014395 8.90 3.32  Apoptosis MAL Induction of apoptosis NM_002371 49.41 8.48 ALOX12 Antiapoptosis NM_000697 31.70 6.69 FAM3B Apoptosis NM_058186 27.28 6.16 BNIPL Apoptosis NM_001159642 18.88 5.01  Cell adhesion CLDN17 Cell-cell adhesion NM_012131 91.67 11.90 CRNN Cell-cell adhesion NM_016190 71.09 10.39 DSC3 Homophilic cell adhesion NM_024423 27.40 6.38 CDSN Cell adhesion NM_001264 26.60 5.80 DSG3 Cell adhesion NM_001944 23.82 7.07  Cell cycle and transcriptional regulation GRHL1 Regulation of transcription NM_198182 31.32 6.62 IRF6 Cell cycle arrest NM_006147 13.05 4.87 CASZ1 Regulation of transcription NM_001079843 4.29 2.27 E2F8 Regulation of transcription NM_024680 4.20 2.21  Immune and inflammatory process SERPINB4 Immune response NM_002974 73.33 10.65 IL1F6 Inflammatory response NM_014440 43.13 7.87 IL1RN Inflammatory response NM_173842 26.09 6.48 IL1A Inflammatory response NM_000575 23.93 5.74 CD1A Immune response NM_001763 4.16 2.19  Cytokine and chemokine activity CXCL17 Chemotaxis NM_198477 11.34 3.83 CCL21 Chemotaxis NM_002989 6.25 2.78 ANLN Cytokinesis NM_018685 5.84 2.63 CXCL10 Chemotaxis NM_001565 4.29 2.37Table 3
Representative genes differentially expressed with higher expression levels in dental follicles than in the gingiva (absolute fold change > 4.0).
Functional category Gene symbol Biological process Accession number Absolute fold change Standard deviation Metabolism and catabolism ALDH1L2 Carbon metabolic process NM_001034173 19.63 5.13 MOXD1 Histidine catabolic process NM_015529 17.92 4.91 ELOVL2 Fatty acid metabolic process NM_017770 12.62 4.07 FBXL7 Protein catabolic process NM_012304 8.58 3.27  Protein modification and maintenance ADAM12 Metalloendopeptidase activity NM_003474 37.09 7.25 MMP16 Metalloendopeptidase activity NM_005941 24.32 5.82 MMP2 Metalloendopeptidase activity NM_004530 19.64 5.17 MMP8 Metalloendopeptidase activity NM_002424 11.86 3.89 MMP13 Metalloendopeptidase activity NM_002427 7.60 3.16 ADAM22 Proteolysis NM_021723 5.97 2.75  Structural process COL11A1 Extracellular matrix organization NM_001854 29.15 6.38 MAP1B Microtubule bundle formation NM_005909 10.30 3.61 FBN2 Anatomical structure morphogenesis NM_001999 9.02 3.40 LUM Collagen fibril organization NM_002345 8.68 3.32  Transport activity KCNT2 Ion transport NM_198503 11.30 3.80 ABCC9 Potassium ion transport NM_005691 11.18 3.77 RHOBTB3 Retrograde transport NM_014899 10.62 3.72 SLC4A4 Sodium ion transport NM_001098484 10.12 3.68 HEPH Copper ion transport NM_138737 8.34 3.28  Developmental process AMBN Odontogenesis NM_016519 117.54 16.99 CDH11 Ossification NM_001797 38.12 7.40 ALPL Biomineral tissue development NM_000478 33.21 6.83 ASPN Bone mineralization NM_017680 33.05 6.85 FGF7 Embryonic development NM_002009 29.53 6.44 COL1A2 Skeletal system development NM_000089 14.50 4.41 RUNX2 Ossification NM_001024630 13.85 4.23 PDGFRB Embryonic development NM_002609 11.85 3.93 WNT2 Mesenchymal cell proliferation NM_003391 10.28 3.73 BMP5 Ossification NM_021073 7.13 3.28 LEF1 Wnt receptor signaling pathway NM_016269 5.83 2.66 PAX3 Organ morphogenesis NM_181457 4.70 2.38 MSX1 Organ morphogenesis NM_002448 4.23 2.24  Physiologic process VAT1L Oxidation reduction NM_020927 12.30 3.98 TFPI Blood coagulation NM_006287 9.49 3.49 TPM1 Muscle contraction NM_000366 8.78 3.30 SOBP Sensory perception NM_018013 8.27 3.21  Nucleic acid synthesis and modification EYA4 DNA repair NM_004100 24.90 5.86 NAP1L3 Nucleosome assembly NM_004538 16.47 4.68 SNRPN RNA splicing BC043194 5.05 1.58  Signal transduction and regulation PDE7B Signal transduction NM_018945 22.99 5.59 CHN1 Signal transduction NM_018945 22.98 5.60 LIFR Cytokine-mediated signaling pathway NM_002310 8.78 3.31 FSTL1 BMP signaling pathway NM_007085 8.75 3.31  Apoptosis SEMA3A Apoptosis NM_006080 51.87 8.72 PEG10 Apoptosis NM_015068 21.89 5.43 SULF1 Apoptosis NM_001128205 11.18 3.77 NELL1 Induction of apoptosis NM_006157 8.67 3.27  Cell adhesion OMD Cell adhesion NM_005014 40.83 7.69 VCAN Cell adhesion NM_004385 35.76 7.25 SPON1 Cell adhesion NM_006108 32.63 6.78  Cell cycle and transcriptional regulation MYEF2 Transcription NM_016132 6.71 2.88 SYCP2 Cell cycle NM_014258 5.41 2.53 APBB2 Cell cycle arrest NM_004307 5.25 2.49  Immune and inflammatory process TPST1 Inflammatory response NM_003596 9.00 3.34 PXDN Immune response NM_012293 8.89 3.40 IFI44L Immune response NM_006820 6.01 2.79 PECAM1 Phagocytosis NM_000442 4.26 2.25 COLEC12 Phagocytosis, recognition NM_130386 4.23 2.22  Cytokine and chemokine activity CXCL12 Chemotaxis NM_000609 11.04 3.79 SLIT3 Chemotaxis NM_003062 8.94 3.34 CMTM3 Chemotaxis NM_144601 5.24 2.52 STX2 Cytokinesis NM_194356 4.39 2.27 CCR1 Chemotaxis NM_001295 4.31 2.36


### 3.2. Gene Ontology Analysis

To identify the biological functions and features of the selected genes, the expression data sets were organized into Gene Ontology Consortium (GO) groups using the DAVID web-based tool. These genes were then classified based on information regarding gene function in gene ontology from the KEGG Pathway database. Figure1 shows GO classes for the two data sets analyzed (F-statistic p<0.05).Figure 1
Main categories of genes expressed in the gingiva and dental follicles according to biological process.x-axis: the number of involved genes.A total of 66 genes encoding metabolic and catabolic process were expressed more abundantly in the gingiva than in the DFs. Fifty-five genes related to structural processes such as keratinization and cytoskeleton organization were expressed at higher levels in the gingiva. On the other hand, 92 developmental process-related genes were highly expressed in DFs as a result of biological processes including odontogenesis, ossification, and bone mineralization. Cell cycle-associated genes and signal transduction- and regulation-related genes were expressed at higher levels in DFs. These results are consistent with the occurrence of higher proliferation rates in DFs.


### 3.3. Confirmation of Gene Differential Expression Using Quantitative RT-PCR

Quantitative RT-PCR analysis verified the cDNA microarray results. Six genes for which the difference in expression levels between the gingiva and DFs was at least 4-fold were selected. Mann–Whitney “U” test was performed to correlate the relative change with differential expression as detected by PCR. The expression levels ofKRT6A,CSTA, andCXCL10 were 13406.7±14962.8, 1524.4±714.8, and 4.7±2.0 times higher in gingiva, andAMBN,ADAM12, andCXCL12 were 20585.4±24267.0, 192.5±66.5, and 66.0±6.5 times higher in DFs (Figure 2). These results were consistent with the microarray results.Figure 2
The relative difference in mRNA expression of six differentially expressed genes between the gingiva and dental follicles using quantitative RT-PCR. The data are presented as the mean + standard deviation and expressed as the relative change by applying the equation2-ΔΔCt. y-axis: a log scale measure. p∗∗<0.05.


### 3.4. Verification of Array Results by Immunohistochemical Staining

The following four proteins were the targets of the IHC study:CXCL10,CSTA,AMBN, andCXCL12 (Figure 3).CXCL10 was broadly stained in the epithelial area of the gingiva.CSTA was strongly stained in all of the layers of the gingiva.AMBN was not stained in the gingiva but stained around the outer area of the DFs.CXCL12 was stained in a single cellular layer and in the collagenous connective tissue of DFs. The results were consistent with those of the cDNA microarray analysis at the protein level.Figure 3
Verification of microarray results by immunohistochemical (IHC) staining. Hematoxylin-eosin staining in the gingiva (a, f) and dental follicles (DFs) (k, p) (asterisk: outer border neighboring alveolar bone). IHC staining forCXCL10 in the gingiva (b, g) and DFs (l, q). IHC staining forCSTA in the gingiva (c, h) and DFs (m, r). The expression ofCXCL10 andCSTA was stained markedly in the gingival epithelium. The IHC staining forAMBN in the gingiva (d, i) and DFs (n, s). AMBN was stained around the outer layer of the DFs. The IHC staining forCXCL12 in the gingiva (e, j) and dental follicles (o, t). CXCL12 was stained in both a cellular layer and the collagenous connective tissue of DFs (scale bars: 200 μm).


### 3.5. Stemness Characterization by Surface Protein Markers

Based on previous studies, dental stem cells were characterized using surface protein markers [16, 17]. The comparative expression results for stem cell marker genes are listed in Figure 4(a). Our results indicated that DF tissue derived MSCs are a cell population that is more positive for mesenchymal MSC markers (includingCD13,CD34,CD73,CD90, andCD105) according to the International Society for Cell Therapy [18]. The comparative expression of four induced pluripotent stem cells (iPSCs) marker genes (i.e.,OCT-3,4,SOX2,cMYC, andKLF4) were expressed at higher levels in the gingiva. As a result of qRT-PCR,SOX2,KLF4, andcMYC appeared 58.5, 12.43, and 12.23 times higher from the gingiva andVCAM1 (CD106) andALCAM (CD166) were 33.54 and 4.27 times higher in DFs (Figure 4(b)). However, OCT-3, 4 did not show a clear difference in comparison to the other markers (0.46-fold difference).Figure 4
The relative gene expression of dental-derived stem cell and induced pluripotent stem cell markers using cDNA microarray (a). The relative fold difference in the expression of five stem cell marker genes between the gingiva and dental follicles using quantitative RT-PCR (b). The data are presented as the mean + standard deviation (a, b) and expressed as the relative change by applying the equation2-ΔΔCt (b). p∗∗<0.05.
(a) (b)


## 3.1. Gene Expression Profiles of the Gingiva and Dental Follicles

1,182 out of 33,297 (3.6%) genes exhibited an absolute expression change of at least 4-fold. The expression levels of 555 genes were 4-fold higher in the gingiva than in DFs, while the expression levels of 627 genes were at least 4-fold higher in DFs than in the gingiva. The overall data distribution and frequency were confirmed by density and box plots of the ratio of the standardized log intensity to the average intensity. Ultimately, 829 genes were analyzed further, with the exception of several genes with unknown biological functions. The data were further filtered, and the genes are listed in Tables2 and 3 according to their relative biological functions. In the gingiva, the expression levels of 387 genes were upregulated by 4-fold or more in comparison to DFs, while the expression levels of 442 genes were upregulated by 4-fold in DFs in comparison to the gingiva.Table 2
Representative genes differentially expressed with higher expression levels in the gingiva than in dental follicles (absolute fold change > 4.0).
Functional category Gene symbol Biological process Accession number Absolute fold change Standard deviation Metabolism and catabolism LIPK Lipid catabolic process NM_001080518 90.99 11.87 FMO2 Organic acid metabolic process NM_001460 34.26 7.05 ARG1 Arginine catabolic process NM_000045 18.91 5.06 LIPN Lipid catabolic process NM_001080518 13.27 4.19  Protein modification and maintenance KLK7 Proteolysis NM_139277 30.47 6.52 KLK10 Proteolysis NM_002776 28.97 6.34 KLK6 Protein autoprocessing NM_002774 25.58 6.10 TGM1 Protein modification process NM_000359 22.21 5.48 OCLN Protein complex assembly NM_002538 12.48 4.48  Structural process SPRR2A Keratinization NM_005988 207.84 18.61 KRT1 Keratinization NM_006121 146.08 15.41 CNFN Keratinization NM_032488 74.92 10.64 CSTA Keratinocyte differentiation NM_005213 69.63 10.22 KRT4 Cytoskeleton organization NM_002272 39.48 7.50 KRT3 Cytoskeleton organization NM_057088 36.71 7.23 FLG Keratinocyte differentiation NM_002016 24.31 5.75 DSP Keratinocyte differentiation NM_004415 17.15 5.22  Transport activity CLCA4 Ion transport NM_012128 48.96 8.48 AQP3 Water transport NM_004925 27.74 6.41 SLC5A1 Transmembrane transport NM_000343 19.52 5.09 GLTP Glycolipid transport NM_016433 7.56 3.04  Developmental process KRT10 Epidermis development NM_000421 152.93 15.74 SCEL Epidermis development NM_144777 134.38 14.68 KRT6B Ectoderm development NM_005555 90.30 12.11 KRT6A Ectoderm development NM_005554 57.61 9.64 SPINK5 Epidermal cell differentiation NM_001127698 55.60 9.34 EHF Epithelial cell differentiation NM_012153 14.27 5.50 SOX2 Embryonic development NM_003106 8.67 3.34 TUFT1 Odontogenesis NM_020127 7.87 3.19  Physiologic process RHCG Regulation of pH NM_016321 51.23 8.68 ABCA12 Cellular homeostasis NM_173076 39.33 7.55 EREG Angiogenesis NM_001432 13.04 4.29 NMU Gastric acid secretion NM_006681 12.72 4.05 SCD Oxidation reduction NM_005063 4.35 2.25  Nucleic acid synthesis and modification MACC1 Regulation of cell division NM_182762 20.30 5.38 ESRP1 mRNA processing NM_017697 17.02 5.85 HIST1H1B Nucleosome assembly NM_005322 6.85 2.91  Signal transduction and regulation IL1F9 Cell-cell signaling NM_019618 26.31 6.03 ARAP2 Signal transduction NM_015230 9.88 3.89 DAPP1 Signal transduction NM_014395 8.90 3.32  Apoptosis MAL Induction of apoptosis NM_002371 49.41 8.48 ALOX12 Antiapoptosis NM_000697 31.70 6.69 FAM3B Apoptosis NM_058186 27.28 6.16 BNIPL Apoptosis NM_001159642 18.88 5.01  Cell adhesion CLDN17 Cell-cell adhesion NM_012131 91.67 11.90 CRNN Cell-cell adhesion NM_016190 71.09 10.39 DSC3 Homophilic cell adhesion NM_024423 27.40 6.38 CDSN Cell adhesion NM_001264 26.60 5.80 DSG3 Cell adhesion NM_001944 23.82 7.07  Cell cycle and transcriptional regulation GRHL1 Regulation of transcription NM_198182 31.32 6.62 IRF6 Cell cycle arrest NM_006147 13.05 4.87 CASZ1 Regulation of transcription NM_001079843 4.29 2.27 E2F8 Regulation of transcription NM_024680 4.20 2.21  Immune and inflammatory process SERPINB4 Immune response NM_002974 73.33 10.65 IL1F6 Inflammatory response NM_014440 43.13 7.87 IL1RN Inflammatory response NM_173842 26.09 6.48 IL1A Inflammatory response NM_000575 23.93 5.74 CD1A Immune response NM_001763 4.16 2.19  Cytokine and chemokine activity CXCL17 Chemotaxis NM_198477 11.34 3.83 CCL21 Chemotaxis NM_002989 6.25 2.78 ANLN Cytokinesis NM_018685 5.84 2.63 CXCL10 Chemotaxis NM_001565 4.29 2.37Table 3
Representative genes differentially expressed with higher expression levels in dental follicles than in the gingiva (absolute fold change > 4.0).
Functional category Gene symbol Biological process Accession number Absolute fold change Standard deviation Metabolism and catabolism ALDH1L2 Carbon metabolic process NM_001034173 19.63 5.13 MOXD1 Histidine catabolic process NM_015529 17.92 4.91 ELOVL2 Fatty acid metabolic process NM_017770 12.62 4.07 FBXL7 Protein catabolic process NM_012304 8.58 3.27  Protein modification and maintenance ADAM12 Metalloendopeptidase activity NM_003474 37.09 7.25 MMP16 Metalloendopeptidase activity NM_005941 24.32 5.82 MMP2 Metalloendopeptidase activity NM_004530 19.64 5.17 MMP8 Metalloendopeptidase activity NM_002424 11.86 3.89 MMP13 Metalloendopeptidase activity NM_002427 7.60 3.16 ADAM22 Proteolysis NM_021723 5.97 2.75  Structural process COL11A1 Extracellular matrix organization NM_001854 29.15 6.38 MAP1B Microtubule bundle formation NM_005909 10.30 3.61 FBN2 Anatomical structure morphogenesis NM_001999 9.02 3.40 LUM Collagen fibril organization NM_002345 8.68 3.32  Transport activity KCNT2 Ion transport NM_198503 11.30 3.80 ABCC9 Potassium ion transport NM_005691 11.18 3.77 RHOBTB3 Retrograde transport NM_014899 10.62 3.72 SLC4A4 Sodium ion transport NM_001098484 10.12 3.68 HEPH Copper ion transport NM_138737 8.34 3.28  Developmental process AMBN Odontogenesis NM_016519 117.54 16.99 CDH11 Ossification NM_001797 38.12 7.40 ALPL Biomineral tissue development NM_000478 33.21 6.83 ASPN Bone mineralization NM_017680 33.05 6.85 FGF7 Embryonic development NM_002009 29.53 6.44 COL1A2 Skeletal system development NM_000089 14.50 4.41 RUNX2 Ossification NM_001024630 13.85 4.23 PDGFRB Embryonic development NM_002609 11.85 3.93 WNT2 Mesenchymal cell proliferation NM_003391 10.28 3.73 BMP5 Ossification NM_021073 7.13 3.28 LEF1 Wnt receptor signaling pathway NM_016269 5.83 2.66 PAX3 Organ morphogenesis NM_181457 4.70 2.38 MSX1 Organ morphogenesis NM_002448 4.23 2.24  Physiologic process VAT1L Oxidation reduction NM_020927 12.30 3.98 TFPI Blood coagulation NM_006287 9.49 3.49 TPM1 Muscle contraction NM_000366 8.78 3.30 SOBP Sensory perception NM_018013 8.27 3.21  Nucleic acid synthesis and modification EYA4 DNA repair NM_004100 24.90 5.86 NAP1L3 Nucleosome assembly NM_004538 16.47 4.68 SNRPN RNA splicing BC043194 5.05 1.58  Signal transduction and regulation PDE7B Signal transduction NM_018945 22.99 5.59 CHN1 Signal transduction NM_018945 22.98 5.60 LIFR Cytokine-mediated signaling pathway NM_002310 8.78 3.31 FSTL1 BMP signaling pathway NM_007085 8.75 3.31  Apoptosis SEMA3A Apoptosis NM_006080 51.87 8.72 PEG10 Apoptosis NM_015068 21.89 5.43 SULF1 Apoptosis NM_001128205 11.18 3.77 NELL1 Induction of apoptosis NM_006157 8.67 3.27  Cell adhesion OMD Cell adhesion NM_005014 40.83 7.69 VCAN Cell adhesion NM_004385 35.76 7.25 SPON1 Cell adhesion NM_006108 32.63 6.78  Cell cycle and transcriptional regulation MYEF2 Transcription NM_016132 6.71 2.88 SYCP2 Cell cycle NM_014258 5.41 2.53 APBB2 Cell cycle arrest NM_004307 5.25 2.49  Immune and inflammatory process TPST1 Inflammatory response NM_003596 9.00 3.34 PXDN Immune response NM_012293 8.89 3.40 IFI44L Immune response NM_006820 6.01 2.79 PECAM1 Phagocytosis NM_000442 4.26 2.25 COLEC12 Phagocytosis, recognition NM_130386 4.23 2.22  Cytokine and chemokine activity CXCL12 Chemotaxis NM_000609 11.04 3.79 SLIT3 Chemotaxis NM_003062 8.94 3.34 CMTM3 Chemotaxis NM_144601 5.24 2.52 STX2 Cytokinesis NM_194356 4.39 2.27 CCR1 Chemotaxis NM_001295 4.31 2.36


## 3.2. Gene Ontology Analysis

To identify the biological functions and features of the selected genes, the expression data sets were organized into Gene Ontology Consortium (GO) groups using the DAVID web-based tool. These genes were then classified based on information regarding gene function in gene ontology from the KEGG Pathway database. Figure1 shows GO classes for the two data sets analyzed (F-statistic p<0.05).Figure 1
Main categories of genes expressed in the gingiva and dental follicles according to biological process.x-axis: the number of involved genes.A total of 66 genes encoding metabolic and catabolic process were expressed more abundantly in the gingiva than in the DFs. Fifty-five genes related to structural processes such as keratinization and cytoskeleton organization were expressed at higher levels in the gingiva. On the other hand, 92 developmental process-related genes were highly expressed in DFs as a result of biological processes including odontogenesis, ossification, and bone mineralization. Cell cycle-associated genes and signal transduction- and regulation-related genes were expressed at higher levels in DFs. These results are consistent with the occurrence of higher proliferation rates in DFs.


## 3.3. Confirmation of Gene Differential Expression Using Quantitative RT-PCR

Quantitative RT-PCR analysis verified the cDNA microarray results. Six genes for which the difference in expression levels between the gingiva and DFs was at least 4-fold were selected. Mann–Whitney “U” test was performed to correlate the relative change with differential expression as detected by PCR. The expression levels ofKRT6A,CSTA, andCXCL10 were 13406.7±14962.8, 1524.4±714.8, and 4.7±2.0 times higher in gingiva, andAMBN,ADAM12, andCXCL12 were 20585.4±24267.0, 192.5±66.5, and 66.0±6.5 times higher in DFs (Figure 2). These results were consistent with the microarray results.Figure 2
The relative difference in mRNA expression of six differentially expressed genes between the gingiva and dental follicles using quantitative RT-PCR. The data are presented as the mean + standard deviation and expressed as the relative change by applying the equation2-ΔΔCt. y-axis: a log scale measure. p∗∗<0.05.


## 3.4. Verification of Array Results by Immunohistochemical Staining

The following four proteins were the targets of the IHC study:CXCL10,CSTA,AMBN, andCXCL12 (Figure 3).CXCL10 was broadly stained in the epithelial area of the gingiva.CSTA was strongly stained in all of the layers of the gingiva.AMBN was not stained in the gingiva but stained around the outer area of the DFs.CXCL12 was stained in a single cellular layer and in the collagenous connective tissue of DFs. The results were consistent with those of the cDNA microarray analysis at the protein level.Figure 3
Verification of microarray results by immunohistochemical (IHC) staining. Hematoxylin-eosin staining in the gingiva (a, f) and dental follicles (DFs) (k, p) (asterisk: outer border neighboring alveolar bone). IHC staining forCXCL10 in the gingiva (b, g) and DFs (l, q). IHC staining forCSTA in the gingiva (c, h) and DFs (m, r). The expression ofCXCL10 andCSTA was stained markedly in the gingival epithelium. The IHC staining forAMBN in the gingiva (d, i) and DFs (n, s). AMBN was stained around the outer layer of the DFs. The IHC staining forCXCL12 in the gingiva (e, j) and dental follicles (o, t). CXCL12 was stained in both a cellular layer and the collagenous connective tissue of DFs (scale bars: 200 μm).


## 3.5. Stemness Characterization by Surface Protein Markers

Based on previous studies, dental stem cells were characterized using surface protein markers [16, 17]. The comparative expression results for stem cell marker genes are listed in Figure 4(a). Our results indicated that DF tissue derived MSCs are a cell population that is more positive for mesenchymal MSC markers (includingCD13,CD34,CD73,CD90, andCD105) according to the International Society for Cell Therapy [18]. The comparative expression of four induced pluripotent stem cells (iPSCs) marker genes (i.e.,OCT-3,4,SOX2,cMYC, andKLF4) were expressed at higher levels in the gingiva. As a result of qRT-PCR,SOX2,KLF4, andcMYC appeared 58.5, 12.43, and 12.23 times higher from the gingiva andVCAM1 (CD106) andALCAM (CD166) were 33.54 and 4.27 times higher in DFs (Figure 4(b)). However, OCT-3, 4 did not show a clear difference in comparison to the other markers (0.46-fold difference).Figure 4
The relative gene expression of dental-derived stem cell and induced pluripotent stem cell markers using cDNA microarray (a). The relative fold difference in the expression of five stem cell marker genes between the gingiva and dental follicles using quantitative RT-PCR (b). The data are presented as the mean + standard deviation (a, b) and expressed as the relative change by applying the equation2-ΔΔCt (b). p∗∗<0.05.
(a) (b)


## 4. Discussion

In this study, a cDNA microarray comparison analysis was performed to focus on differences in the gene expression profiles of gingiva and DFs in children. The majority of genes (32,115 out of 33,297, 96.5%) showed similar expression level between the gingiva and DFs when using a 4-fold absolute change cutoff value. Most of those genes encoded cell adhesion proteins, proteins involved in structural processes, or proteins related to signal transduction and regulation. This finding suggests that the gingiva and DFs differentiate into different tissue later although they originate from an ectomesenchymal cell. This is likely due to the regulation of comparable intracellular signaling pathways. In contrast, approximately 4% of genes were differentially expressed above the selected threshold. While accounting for only a small portion of the whole gene array, these genes might contribute to the distinct biological functions and distinguish each other phenotypically and morphologically. To investigate this assumption, comparative gene expression was analyzed with respect to the biological functions of the genes.In the gingiva,KRT1,CSTA, andFLG were expressed at significantly higher levels. The gingival epithelium is a stratified squamous keratinizing tissue, and these genes are related to keratinization or keratinocyte differentiation.KRT1 marks the cornification pathway of differentiation and is expressed in keratinized areas [19].CSTA is one of the precursor proteins of the cornified cell envelope in keratinocytes and plays a role in epidermal development and maintenance [20].FLG is essential for the regulation of epidermal homeostasis and interacts with keratin intermediate filaments [21]. Epidermis and ectoderm development-related genes were strongly upregulated in the gingiva versus DFs.KRT6B andKRT6A were markedly upregulated in the gingiva, with 90.30- and 57.61-fold differential expression, respectively. These proteins are rapidly induced in wound-proximal epidermal keratinocytes after skin injury and regulate the migratory potential of skin keratinocytes during wound repair [22].SCEL may function in the assembly or regulation of proteins in the keratinized envelope [23]. The upregulation of these genes may indicate the existence of a fast turnover rate in the gingiva and may facilitate fibroblast proliferation, which is an important event for tissue repair.The oral mucosa is affected by exposure to various extrinsic factors such as chemicals and microorganisms. Genes related to apoptosis and chemotaxis such asCXCL10,CXCL17,ANLN, andCCL21 were strongly expressed in the gingiva.CXCL10 is secreted by the keratinocytes and is a marker of the host immune response [24]. This chemokine plays an important role in the infiltration of Th1 cells and affects the gingiva by exacerbating periodontal disease [25]. The overexpression of these chemokines might be associated with the generation and delivery of immune and inflammatory responses in the gingiva.On the other hand, genes related to tooth and embryo development exhibited significantly higher expression in DFs. These results are consistent with those of a previous DF gene expression study that compared DFs to the PDL [14]. The increased expression ofAMBN indicates that DFs play an important role in enamel matrix formation and mineralization [26]. In this study,WNT2 andLEF1 were upregulated in DFs suggesting that DFs are involved in the complex interplay of signaling factors that regulate tooth initiation and morphogenesis [27, 28].Runx2 is a key regulator of osteoblast marker genes and promotes the differentiation of mesenchymal stem cells into osteoblasts. The literature indicates thatRunx2 functions in the dental mesenchyme and mediates transduction signals from the dental epithelium to the mesenchyme during tooth development [29]. It also influences the molecular events that regulate tooth eruption—the most important physiologic role is likely being at the eruptive site [30]. Given the adaptive role of DFs, the presence of these genes suggests a central role of DFs in tooth formation.Genes encoding protein modification- and signal transduction-related proteins tend to be expressed at higher levels in DFs than in the gingiva. The metalloproteaseADAM 12 has been implicated in biological processes including fertilization and neurogenesis in DFs [11]. MMP-13 may be a major collagenolytic enzyme that degrades the extracellular matrix during tooth eruption. The upexpression of MMP-13 means DFs have important functions for the coordination of tooth eruption [31]. CXCL12 is a chemotactic factor for mesenchymal stem cells and mediates the suppressive effect of those cells on osteoclastogenesis. This factor can be expressed in DFs during tooth development including the epithelium surrounding the developing tooth bud [32].To verify cDNA microarray results, six genes of different functions were selected for quantitative RT-PCR analyses. The expression levels ofKRT6A,CSTA, andCXCL10 were upregulated in the gingiva;AMBN,ADAM12, andCXCL12 were upregulated in DFs. These results were consistent with the microarray results. To better understand the roles of the differentially expressed genes, IHC analysis was performed to identify their functions at tissue level.CXCL10 andCSTA were strongly stained in all of the layers of the gingival tissue but were not stained in DFs. The genes that are highly expressed in the gingiva are stained in the epithelium because the prominent difference in structure between the gingiva and DFs is in the keratinized epithelium.AMBN andCXCL12 were broadly stained in the outer area of DFs especially in the reduced enamel epithelium.Several cell populations with stem cells properties have been isolated from different parts of dental tissue. Their participation in tissue repair and maintenance has been proposed [1]. Although it is difficult to characterize dental stem cells using surface protein markers, our results indicate the relative overexpression of important markers including CD13, CD34, CD73, and CD105 in DFs. These are ubiquitously expressed by all dental stem or precursor cells [6, 16]. With the exception of CD90, CD13, and CD34 which were frequently cited as dental-derived stem cell markers in previous studies, we selected CD106(VCAM1) and CD166(ALCAM), which are expressed more strongly in dental follicles. Other dental-derived stem marker genes including CD29, CD90, and CD73 were expressed at higher levels indicating self-renewing and differentiation capacities in DFs [33].Interestingly, the gingiva expressed high levels of iPS-associated markers(OCT4,cMYC, SOX2, andKLK4) versus DFs [34]. These proteins are transcription factors that are essential for maintaining the self-renewal capacity or pluripotency [35]. The iPS cells offer an advantage over traditional MSCs because they display an unlimited growth capacity that can serve as an inexhaustible source of stem cells [36]. A similar comparable report analyzed that dental tissue derived mesenchymal-like stem cells can be reprogrammed into iPSCs more efficiently, when compared to other mature somatic cells from human body such as adult MSCs and adult dermal fibroblasts [37].The accessibility of dental tissue, including MSCs, might still be limited because these cells can only be isolated under specific circumstances, such as during the extraction of teeth. However, the gingiva is one of the most convenient tissues to collect by biopsy, with less scar formation and less postsurgical donor discomfort. In addition, gingival tissues are routinely resected during dental procedures in children, such as surgical extraction of impacted teeth and surgical opening for teeth with delayed eruption, and these tissues are generally treated as biomedical waste. In the laboratory, it is also feasible to isolate stem cells from gingival tissue based on their highly proliferative nature. Thus, the gingiva can be an important alternative source of stem cells in regenerative dentistry. If stem cells isolated from gingival tissue can be utilized similar to the storage of umbilical cord blood, the dynamic features of these cells reveal much potential for their use. Although this study is limited to monitoring expression patterns without a clinical link, comparative gene expression analysis of different tissues might provide genetic information concerning functions, such as tissue repair and tooth development. Further investigations are needed to evaluate the neurogenesis capacity, mineralization potential, and cell proliferation capacity of stem cells from gingiva and dental follicles based on of this study.


## 5. Conclusion

For the first time, this study profiles differential gene expression between the gingiva and DFs. cDNA microarray was performed to characterize and compare the molecular fingerprints of stemness. The DFs have been considered a multipotent tissue based on their ability to generate cementum, bone, and PDL. While the gingiva was not noticed for pluripotent stemness before, this study demonstrated transcription factors of iPS cells were expressed at higher levels in the gingiva and most dental-derived stem cell markers were strongly upregulated in the DFs. Given the minimal postsurgical discomfort and simple accessibility of gingival tissue, the gingiva is a good candidate stem cell source in regenerative dentistry.



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