Open Access

Comparison of gene expression profiles between dental pulp and periodontal ligament tissues in humans

  • Authors:
    • Ai-Xiu Gong
    • Jing-Han Zhang
    • Jing Li
    • Jun Wu
    • Lin Wang
    • Deng-Shun Miao
  • View Affiliations

  • Published online on: July 12, 2017     https://doi.org/10.3892/ijmm.2017.3065
  • Pages: 647-660
  • Copyright: © Gong et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

There are anatomical and functional differences between human dental pulp (DP) and periodontal ligament (PDL). However, the molecular biological differences and function of these tissues are poorly understood. In the present study, we employed a cDNA microarray array to screen for differentially expressed genes (DEGs) between human DP and PDL tissues, and used the online software WebGestalt to perform the functional analysis of the DEGs. In addition, the STRING database and KEGG pathway analysis were applied for interaction network and pathway analysis of the DEGs. DP and PDL samples were obtained from permanent premolars (n=16) extracted for orthodontic purposes. The results of the microarray assay were confirmed by RT-qPCR. The DEGs were found to be significantly associated with the extracellular matrix and focal adhesion. A total of 10 genes were selected to confirm the results. The mRNA levels of integrin alpha 4 (ITGA4), integrin alpha 8 (ITGA8), neurexin 1 (NRXN1) and contactin 1 (CNTN1) were significantly higher in the DP than in the PDL tissues. However, the levels of collagen type XI alpha 1 (COL11A1), aggrecan (ACAN), collagen type VI alpha 1 (COL6A1), chondroadherin (CHAD), laminin gamma 2 (LAMC2) and laminin alpha 3 (LAMA3) were higher in the PDL than in the DP samples. The gene expression profiles provide novel insight into the characterization of DP and PDL tissues, and contribute to our understanding of the potential molecular mechanisms of dental tissue mineralization and regeneration.

Introduction

Dental pulp (DP) tissue, termed as the 'ectomesenchyme', is derived from ectodermal cells that grow on the periphery of the neural tube, migrate to the oral position and then differentiate into cells of the mesenchymal phenotype (1). Epithelial cells form ameloblasts and odontoblasts, DP and periodontal ligament (PDL) (2). DP is responsible for the maintenance and repair of the periodontal tissue and its related immune system, and it has a high regenerative potency and responds to various types of damage (3). PDL connects the tooth and the alveolar jaw bone in the area surrounding the root surface, and functions as continuous support, attachment, proprioception and physical protection for the teeth, and minimizes tissue damage arising from trauma and infection (4). Owing to the anatomical and functional differences between human DP and PDL, it is reasonable to assume that there are also differences in the gene expression profiles of these tissues.

Previous studies have indicated that the gene expression patterns of mesenchymal stem cells (MSCs) derived from dental tissues are different from those of other tissue by employing genome-wide gene expression profiling and gene ontology analysis (5). Differentially expressed proteins have also been demonstrated between dental and non-dental ovine MSC populations from the same donor, which may attribute to their unique growth and capacity to generate structures resembling the specific microenvironments from which they were derived in vivo (6,7).

Recent findings suggest that human DP-derived stem cells (DPSCs) and PDL-derived stem cells (PDLSCs) have the ability to regenerate a dentin/pulp-like and cementum/PDL-like complex, respectively when they are transplanted into the subcutaneous space of immunocompromised mice (811). Stem cell-based dentistry has emerged as a promising alternative for the development of regenerative therapies, which have unavoidable limitations and the effects of which have not yet been fully determined (12).

The cDNA microarray technique can provide global profiles of gene expression and facilitate the evaluation of large-scale genes simultaneously. This method has been used in dental studies to compare differentially expressed genes (DEGs) among various types of stem cells (13), or tissues (1416), or diseases (1719). However, the differences in gene expression profiles between DP and PDL tissue have not yet been fully elucidated. The use of tissue samples provides more information of the actual situation as the interactions between different cell types can be important for the function of tissues.

Therefore, the present study aimed to evaluate and compare the gene expression patterns in DP and PDL tissues from human permanent teeth, and to identify their molecular biological differences and functions. Furthermore, the results may provide insight into the potential molecular mechanisms of dental tissue regeneration.

Materials and methods

Gene expression data

A gene expression data set (accession no. GSE50639), which included 3 DP and PDL tissues, was downloaded from the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo). Gene expression levels were measured through the Affymetrix Human Gene 1.0 ST Array beadchip platform (Affymetrix, Santa Clara, CA, USA) (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL6244). Platform annotation files were also acquired.

DP and PDL samples

Tissues were obtained from healthy permanent premolars (n=16; from 8 males and 8 females, aged 11–14 years) extracted for orthodontic purposes under approved guidelines set by Nanjing Children's Hospital, Nanjing, China. Written informed consent was obtained from all the respective parents or legal guardians.

The DP and PDL samples used for the experiment were collected according to a previously described procedure (8,9). Briefly, tooth surfaces were cleaned with sterile water, and PDL tissues were gently separated from the middle-third of root with a scalpel. The root was then cut around the cementum-enamel junction using sterilized dental fissure burs, and fractured off along the cutting line with sharp-edged pliers to reveal the pulp chamber. The DP tissues were carefully removed from the crown and root. The extracted PD and PDL samples were then immediately frozen and stored in liquid nitrogen.

Microarray data analysis

The expression data were generated using Affymetrix Expression Console software version 1.4 (Affymetrix). The Robust Multi-array Average (RMA) algorithm implemented through the Affymetrix Expression Console software was used to normalize the data. A one-way ANOVA was performed on the RMA expression values to determine whether genes were differentially expressed between DP and PDL groups. A multiple-testing correction was applied to the p-values of the F-statistics to adjust the false discovery rate (20). Genes with adjusted F-statistic p-values of <0.05 were extracted. Microarray analysis identified 1,405 genes with differences in expression of ≥2-fold, 920 and 485 of which were more abundant in the DP and PDL tissue, respectively. However, only strongly expressed genes in the DP or PDL tissue, which differed by >4- or 2.5-fold from the signal of the DP and PDL tissues, respectively, were selected for further analysis.. In order to classify the co-expression gene group with a similar expression pattern, hierarchical clustering analysis was conducted using Affymetrix Transcriptome Analysis Console (TAC) software. The WEB-based Gene Set AnaLysis Toolkit was performed for the biological interpretation of DEGs (21,22). WebGestalt is a system that facilitates the analysis of sets of genes that can be visualized and organized by a user-selected method. These genes were classified based on data on gene function in the gene ontology of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. Protein-protein interaction (PPI) networks represents a significant step in the elucidation of the underlying molecular mechanisms. In our study, PPI networks were constructed for the protein products using information from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, version 9.1; http://string-db.org/) (23). Interactions with a score (i.e., required confidence) >0.4 were retained in the network.

Reverse-transcription-quantitative polymerase chain reaction (RT-qPCR)

RNA was isolated from the DP and PDL tissues using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's instructions. To determine the number of cDNA molecules in the reverse-transcribed samples, qPCR analyses were performed using the LightCycler system (Roche, Indianapolis, IN, USA). PCR was conducted using 2 µl LightCycler DNA Master SYBR-Green I (Roche), 12.5 µl of reaction mixture, 2 µl of each 5′ and 3′ primer, 2 µl samples. H2O was then added to a final volume of 25 µl. The samples were denatured at 95°C for 10 sec, with a temperature transition rate of 20°C/sec. Four steps were carried out in amplification and fluorescence determination: denaturation at 95°C for 1 sec, with a temperature transition rate of 20°C/sec; annealing for 5 sec, with a temperature transition rate of 8°C/sec; extension at 72°C for 20 sec, with a temperature transition rate of 4°C/sec; and detection of SYBR-Green fluorescence, which reflects the amount of double-stranded DNA, at 86°C for 3 sec. The amplification cycle number was 35. To discriminate specific from non-specific cDNA products, a melting curve was obtained at the end of each run. Products were denatured at 95°C for 3 sec, and the temperature then decreased to 58°C for 15 sec and increased slowly from 58 to 95°C using a temperature transition rate of 0.1°C/sec. To determine the number of copies of the targeted DNA in the samples, purified PCR fragments of known concentrations were serially diluted and served as external standards that were measured in each experiment. Data were normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) levels in the samples. The primer sequences used for PCR are listed in Table I.

Table I

Specific primer sequences used for RT-qPCR.

Table I

Specific primer sequences used for RT-qPCR.

NamePrimers sequences (5′→3′)Product size (bp)
ITGA4F: CACAACACGCTGTTCGGCTA
R: CGATCCTGCATCTGTAAATCGC139
ITGA8F: AGAATGGAGACCTTATTGTGGGA
R: GAGCCACTTCCGTCTGCTTT147
NRXN1F: TAAGTGGCCTCCTAATGACCG
R: TCGCACCAATACGGCTTCTTT91
CNTN1F: CAGCCCTTTCCCGGTTTACAA
R: TGCTTCTGACCATCCCGTAGT170
ACANF: GTGCCTATCAGGACAAGGTCT
R: GATGCCTTTCACCACGACTTC167
COL11A1F: ACCCTCGCATTGACCTTCC
R: TTTGTGCAAAATCCCGTTGTTT128
COL6A1F: ACAGTGACGAGGTGGAGATCA
R: GATAGCGCAGTCGGTGTAGG122
CHADF: CGCGGCCTCAAGCAACTTA
R: TAGGTCAGCTCGGTCAGGTC95
LAMC2F: CAAAGGTTCTCTTAGTGCTCGAT
R: CACTTGGAGTCTAGCAGTCTCT153
LAMA3F: CACCGGGATATTTCGGGAATC
R: AGCTGTCGCAATCATCACATT165
GAPDHF: GGAGCGAGATCCCTCCAAAAT
R: GGCTGTTGTCATACTTCTCATGG197

[i] ITGA, integrin alpha NRXN1, neurexin 1; CNTN1, contactin 1; ACAN, aggrecan; COL11A1, collagen type XI alpha1; COL6A1, collagen type VI alpha 1; CHAD, chondroadherin; LAMC2, laminin gamma2; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; F, forward; R, reverse.

Statistical analysis

Data from image analysis are presented as the means ± SEM. Statistical comparisons were made using a two-way ANOVA. A value of p<0.05 was considered to indicate a statistically significant difference.

Results

Gene expression profiles in human DP and PDL tissue

Affymetrix Transcriptome Analysis Console software was applied to analyze the cDNA microarray data set (GSE50639). The results indicated that the expression of a total of 1,405 genes was altered by at least 2-fold in one tissue type relative to the other. In the DP tissue, the expression levels of 920 genes were at least double those in the PDL tissues, while in the latter, the expression levels of 485 genes were at least double those in the DP tissue. Ultimately, only strongly expressed genes (529 genes) in the DP or PDL tissue whose expression differed by >4- or 2.5-fold from the signal of the DP or PDL tissue were evaluated further. In the DP tissue, 255 genes were upregulated by at least 4-fold relative to the PDL tissue, while 274 genes were upregulated by at least 2.5-fold in the PDL tissue relative to the DP tissue. Hierarchical clustering and a heatmap of the DEGs in the DP and PDL tissue are shown in Fig. 1, and the up- and downregulated genes in the DP tissues (compared with the PDL tissues) are shown in Table II.

Table II

Up- and downregulated genes in the DP tissues (compared with the PDL tissues).

Table II

Up- and downregulated genes in the DP tissues (compared with the PDL tissues).

Upregulated genes in the DP tissues
Downregulated genes in the DP tissue
NameGene symbolFold changeNameGene symbolFold change
Anoctamin 1, calcium activated chloride channelANO16.87Cathepsin KCTSK−6.62
ScinderinSCIN28.26ADAM metallopeptidase with thrombospondin type 1 motif 14ADAMTS14−2.64
Bone morphogenetic protein 7BMP75.71Denticleless E3 ubiquitin protein ligase homolog (Drosophila)DTL−3.16
Sorbin and SH3 domain containing 2SORBS29.62Sushi-repeat containing protein, X-linked 2SRPX2−7.94
Leucine-rich repeat containing G protein-coupled receptor 5LGR543.19Extended synaptotagmin-like protein 3ESYT3−2.82
Adherens junctions associated protein 1AJAP110.07Fibroblast activation protein alphaFAP−16.58
TransferrinTF53.65ATPase, class V, type 10AATP10A−2.95
Solute carrier family 16, member 4SLC16A48.58Collagen type IV alpha 1COL4A1−2.87
Family with sequence similarity 134, member BFAM134B5.39Bone gamma-carboxyglutamate (gla) proteinBGLAP; PMF1-BGLAP; PMF1−3.84
Homer homolog 2 (Drosophila)HOMER24.24Lysyl oxidase-like 2LOXL2−3.11
KN motif and ankyrin repeat domains 1KANK14.27Integrin alpha 11ITGA11−6.81
Chromosome 10 open reading frame 107C10orf1078.01Secreted phosphoprotein 1SPP1−14.77
T-cell lymphoma invasion and metastasis 1TIAM17.23 Methylenetetrahydrofolate dehydrogenase (NADP+ dependent) 2MTHFD2−3.41
Phosphate regulating endopeptidase homolog, X-linkedPHEX68.57Collagen type XVI alpha1COL16A1−5.89
Transmembrane protein 156TMEM15621.87Retinol binding protein 4, plasmaRBP4−7.29
MOB kinase activator 3BMOB3B6.42G protein-coupled receptor 1GPR1−3.2
Ras homolog family member URHOU7.76Nicotinamide N-methyltransferaseNNMT; LOC101928916−3.94
Retinoic acid receptor responder (tazarotene induced) 1RARRES110.38Collagen type XVII alpha 1COL17A1−2.91
Peroxidasin homolog (Drosophila)-likePXDNL10.05 Methylenetetrahydrofolate dehydrogenase (NADP+ dependent) 2MTHFD2P7; MTHFD2−2.88
KIAA1324KIAA132410.36ChondroadherinCHAD−4.19
UDP-Gal:betaGlcNAc beta1,3-galactosyltransferaseB3GALT110.82Semaphorin 7A, GPI membrane anchorSEMA7A−4.13
Unc-80 homolog (C. elegans)UNC808.46Dynamin 1DNM1−2.91
Abhydrolase domain containing 12B; microRNA 4454ABHD12B; MIR445433.54Carbonic anhydrase XIICA12−2.85
ClusterinCLU6.84Collagen type IV alpha 2COL4A2−2.59
WNT1 inducible signaling pathway protein 1WISP15.12Collagen type VI alpha 1COL6A1−3.29
Cadherin 12, type 2 (N-cadherin 2)CDH1256.93microRNA 21; vacuole membrane protein 1MIR21; VMP1−5.57
Epithelial cell adhesion moleculeEpCAM9.81Matrix metallopeptidase 19MMP19−3.26
Sema domain, immunoglobulin domain (Ig),SEMA3E46.94Scavenger receptor class A, member 5 (putative)SCARA5−3.77
EPH receptor A5EPHA512.41MIR155 host gene (non-protein coding); microRNA 155MIR155HG; MIR155−2.97
Charged multivesicular body protein 4CCHMP4C8.81CUB domain containing protein 1CDCP1−2.71
Bone morphogenetic protein receptor, type IBBMPR1B19.06Tumor necrosis factor receptor superfamily, member 21TNFRSF21−3.05
Tripartite motif containing 36TRIM365.13Myosin IDMYO1D−3.13
Aldehyde dehydrogenase 1 family, member A3ALDH1A36.01Neuroblastoma 1, DAN family BMP antagonistNBL1; MINOS1-NBL1−4.74
Nucleic acid binding protein 1NABP1−3.17Gamma-aminobutyric acid (GABA) A receptor beta 2GABRB2−3.03
Uridine-cytidine kinase 2; microRNA 3658UCK2; MIR36587.34RNA, 7SK small nuclear pseudogene 137RN7SKP137−4.57
Dystrobrevin binding protein 1DTNBP16.06Matrix metallopeptidase 3 (stromelysin 1, progelatinase)MMP3−5.72
G protein-coupled receptor 63GPR6313.14Coronin 6CORO6−2.73
1-Acylglycerol-3-phosphate O-acyltransferase 4AGPAT44.7CD109 moleculeCD109−8.66
Distal-less homeobox 3DLX35.61Parathyroid hormone 1 receptorPTH1R−3.29
Cytoplasmic FMR1 interacting protein 2CYFIP212.55Cadherin-related 23; cadherin-23-likeCDH23; LOC100653137−3.1
Protein tyrosine phosphatase, receptor type UPTPRU4.67Cholinergic receptor, nicotinic alpha 9 (neuronal)CHRNA9−4.68
NestinNES8.01Acid phosphatase 5, tartrate resistantACP5−7.5
Unc-80 homolog (C. elegans)UNC806.22Anillin, actin binding proteinANLN−3.76
Solute carrier family 2 (facilitated glucose transporter), member 13SLC2A136.24AggrecanACAN−5.66
Calpain 6CAPN64.23Angiopoietin-like 2ANGPTL2−7.12
Dehydrogenase/reductase (SDR family) member 3DHRS35.68Protein tyrosine phosphatase, non-receptor type 22 (lymphoid)PTPN22−4.17
Meiotic nuclear divisions 1 homolog (S. cerevisiae)MND16.24Marker of proliferation Ki-67MKI67−4.31
Coiled-coil domain containing 148CCDC1484.97Zinc finger protein 385AZNF385A−2.56
Carboxypeptidase A6CPA622.33Matrix metallopeptidase 9MMP9−22.27
SH2 domain containing 4ASH2D4A6.27Collagen type VI alpha 3COL6A3−8.54
Ameloblastin (enamel matrix protein)AMBN56.17Sushi-repeat containing protein, X-linkedSRPX−5.77
Gastrin-releasing peptide receptorGRPR12.65Collagen type XIII alpha 1COL13A1−2.61
Family with sequence similarity 69, member CFAM69C6.29Aldo-keto reductase family 1, member C2AKR1C2; LOC101930400−2.9
Scavenger receptor class A, member 3SCARA37.45Collagen type VI alpha 2COL6A2−3.05
Dentin sialophosphoproteinDSPP40.4Collagen type XII alpha 1COL12A1−34.05
Myosin XVIMYO169.15V-maf avian musculoaponeurotic fibrosarcoma oncogene homolog BMAFB−2.81
Activating transcription factor 7 interacting protein 2ATF7IP26.18Absent in melanoma 1AIM1−4.65
Serine/threonine kinase 33STK336.99 Dipeptidyl-peptidase 4DPP4−5.8
Galactosidase β1-like 3GLB1L34.97Xg blood groupXG; XGY2−8.18
Transforming growth factor-beta 1TGFB12.13Laminin alpha 3LAMA3−3.45
Solute carrier family 12 (sodium/potassium/chloride transporter), member 2SLC12A26.02Cell division cycle 6CDC6−2.54
Transforming growth factor-beta 2TGFB23.04Laminin gamnma 2LAMC2−3.29
G protein-coupled receptor 64GPR6411.44Paraneoplastic Ma antigen 2PNMA2−3.24
Lipid phosphate phosphatase-related protein type 5LPPR532.35Glycoprotein (transmembrane) nmbGPNMB−3.6
Transmembrane protein 132BTMEM132B6.76X-prolyl aminopeptidase (aminopeptidase P) 2, membrane-boundXPNPEP2−3.15
Sodium channel, voltage gated, type VIII alpha subunitSCN8A5.21Collagen type V alpha 1COL5A1−6.45
Gamma-aminobutyric acid (GABA) A receptor beta 1GABRB118.02Asp (abnormal spindle) homolog, microcephaly associated (Drosophila)ASPM−2.9
Long intergenic non-protein coding RNA 943LINC009437.72Solute carrier family 38, member 5SLC38A5−2.71
Contactin associated protein-like 4CNTNAP44.1ATPase, H+ transporting, lysosomal 38 kDa, V0 subunit d2ATP6V0D2−7.72
Wingless-type MMTV integration site family, member 5AWNT5A4.44Leucine rich repeat containing 15LRRC15−14.31
Gamma-aminobutyric acid (GABA) A receptor gamma 1GABRG111.14Fibroblast growth factor 9FGF9−3.9
Transmembrane protein 38BTMEM38B5.8Syntaxin binding protein 6 (amisyn)STXBP6−3.91
VitrinVIT4.77Mesenchyme homeobox 1MEOX1−3.02
Dynein, cytoplasmic 1, intermediate chain 1DYNC1I16.4Inhibin beta AINHBA−2.59
Sparc/osteonectin, cwcv and kazal-like domains proteoglycan (testican) 3SPOCK366.65Parathyroid hormone-like hormonePTHLH−7.65
EF-hand calcium binding domain 1EFCAB14.09Reticulocalbin 3, EF-hand calcium binding domainRCN3−2.65
Phosphorylase, glycogen, liverPYGL5.28Coagulation factor V (proaccelerin, labile factor)F5−3.15
Phospholipase C delta 4PLCD47.52Topoisomerase (DNA) II alpha 170 kDaTOP2A−5.27
Fibulin 2FBLN25.8Protease, serine 35PRSS35−4.54
Ras association (RalGDS/AF-6) domain family member 2RASSF24.3Bone morphogenetic protein 3BMP3−15.22
Hyaluronoglucosaminidase 4HYAL49.39B-cell CLL/lymphoma 11B (zinc finger protein)BCL11B−2.84
Integrin alpha 4 (antigen CD49D, alpha4 subunit of VLA-4 receptor)ITGA46.2Collagen type XI alpha 1COL11A1−23.93
Integrin alpha 8ITGA85.52Wingless-type MMTV integration site family member 2WNT2−3.36
Neurexin 1NRXN15.64Dickkopf WNT signaling pathway inhibitor 2DKK2−5.21
Potassium channel, subfamily K, member 2KCNK218.13Bone morphogenetic protein 8aBMP8A−2.22
Contactin 1CNTN14.73Transforming growth factor beta 3TGFB3−2.78
Dentin matrix acidic phosphoprotein 1DMP15.88Chemokine (C-X-C motif) ligand 13CXCL13−3.51
Integrin alpha 2 (CD49B alpha 2 subunit of VLA-2 receptor)ITGA22.35Chemokine (C-X-C motif) ligand 2CXCL2−2.33
Collagen, type XI, alpha 2COL11A24.26Chemokine (C-X-C motif) ligand 8CXCL8−3.19
ReelinRELN8.59Chemokine (C-X-C motif) receptor 1CXCR1−2.76
Solute carrier family 1 (neuronal/epithelial high affinity glutamatetransporter, system Xag), member 1SLC1A14.81Collagen, type XI, alpha 1COL11A1−23.93
Potassium intermediate/small conductance calcium-activated channel, subfamily N, member 4KCNN44.15Tenascin NTNN−21.91
ATPase, Na+/K+ transporting, alpha 2 polypeptideATP1A25Integrin-binding sialoproteinIBSP−5
MET proto-oncogene, receptor tyrosine kinaseMET6.93Carboxypeptidase A3 (mast cell)CPA3−4.09
Nitric oxide synthase 1 (neuronal)NOS14.43Insulin-like growth factor 1 (somatomedin C)IGF1−5.2
Poliovirus receptor-related 3PVRL35.7Interleukin 1βIL1β−4.78
Claudin 10CLDN105.11Phospholipase C, beta 1 (phosphoinositide-specific)PLCB1−2.68
Claudin 11CLDN116Cystatin SNCST1−5.14
Neuronal growth regulator 1NEGR16.06Cystatin SCST4−2.67
Catenin (cadherin-associated protein), alpha 2CTNNA29.47LysozymeLYZ−2.86
KIT ligandKITLG5.53Selectin ESELE−2.73
Bone morphogenetic protein 5BMP53.92Peroxisome proliferator-activated receptor gammaPPARG−2.56
Bone morphogenetic protein 6BMP63.31Fas cell surface death receptorFAS−2.75
Matrix metallopeptidase 2 (gelatinase A, 72 kDa gelatinase, 72 kDa type IV collagenase)MMP2−3.43
Cyclin-dependent kinase 6CDK6−2.83
Interleukin 7IL7−2.65
CD4 moleculeCD4−2.91
CD1c moleculeCD1C−2.52
Alanyl (membrane) aminopeptidaseANPEP−4.4
Leukemia inhibitory factorLIF−3.17

[i] DP, dental pulp; PDL, periodontal ligament.

Gene Ontology (GO) analysis

To analyze the specific biological functions and features of the selected genes, an analysis toolkit (WebGestalt) was applied for GO annotation and enrichment analysis. The DEGs were classified according to biological process (BP), molecular function (MF) or cellular component (CC) using the WebGestalt software package on the basis of hypergeometric tests. The Resulting BP, MF and CC networks are shown as directed acyclic graphs (DAG), which are color-coded (red for p-values <0.05) (Fig. 2A). Biological process enrichment was found for genes associated with cell adhesion, extracellular matrix (ECM) organization, regulation of anatomical structure, morphogenesis and system development. Molecular function enrichment was discovered for genes associated with heparin binding, calcium ion binding, integrin binding and metalloendopeptidase activity. Cellular component enrichment was detected for genes associated with the plasma membrane and ECM. Significantly enriched GO categories under biological process, molecular function and cellular component are indicated in Fig. 2B–D. In the biological process category, the GO terms of biological regulation (257 genes), multicellular organismal process (235 genes), response to stimulus (219 genes), related to metabolic process (211 genes) and developmental process were enriched. In the molecular function category, GO terms related to protein binding (213 genes) and ion binding (167 genes) were enriched. In the cellular component category, GO terms related to membrane (254 genes) were enriched.

Interaction network and pathway analysis of DEGs

To further detect the biological function of the DEGs in the DP and PDL tissue, an interaction network was carried out using STRING 9.1 (23), as shown in Fig. 3A. The interaction network was generated on the basis of experimental and database knowledge. Markov cluster algorithm (MCL) was used to find group associations between these DEGs. The inflation factor was set as 1 on a scale of 1–5.

WebGestalt was used to identify the significantly enriched KEGG pathways. The shared enriched pathways, including ECM-receptor interaction, protein digestion and absorption, focal adhesion and cell adhesion molecules (CAMs) (Fig. 3B and Table III) were determined at the significance levels of p<0.05 in WebGestalt. Among the enriched pathways, the upregulated pathways in the DP group included CAMs and salivary secretion pathways and the downregulated pathways in the DP group included ECM-receptor interaction, protein digestion and absorption and focal adhesion. Compared with GO analysis, KEGG pathway analysis provides biological information in a more detailed and specific manner. Furthermore, good concordance was observed from the STRING interaction network and the enriched functional modules identified by the KEGG and GO enrichment analyses.

Table III

List of enriched KEGG pathways of the differentially expressed proteins.

Table III

List of enriched KEGG pathways of the differentially expressed proteins.

KEGG pathwayNo. of hitsExpressed gene participating in the pathwayStatistics for the enrichment of the pathway
ECM-receptor interaction18COL11A2, ITGA8, ITGA4, RELN, COL11A1, COL6A3, SPP1, CHAD, LAMA3, COL6A1, COL5A1, ITGA11, COL4A1, TNN, LAMC2, IBSP, COL4A2, COL6A2C=82; O=18; E=2.12; R=8.47; rawP=2.55e-12; adjP=2.63e-10
Protein digestion and absorption16COL6A2, COL17A1, COL4A2, COL11A2, CPA3, COL11A1, SLC1A1, COL12A1, COL6A3, KCNN4, COL6A1, COL5A1, DPP4, XPNPEP2, COL4A1, ATP1A2C=76; O=16; E=1.97; R=8.12; rawP=8.33e-11; adjP=4.29e-09
Focal adhesion20COL6A2, COL4A2, COL11A2, ITGA8, ITGA4, RELN, COL11A1, COL6A3, SPP1, CHAD, LAMA3, COL6A1, COL5A1, IGF1, ITGA11, COL4A1, TNN, MET, LAMC2, IBSPC=195; O=20; E=5.05; R=3.96; rawP=1.80e-07; adjP=6.18e-06
Amoebiasis11LAMA3, COL4A2, COL11A2, COL5A1, IL8, TGFB3, COL4A1, COL11A1, PLCB1, IL1B, LAMC2C=104; O=11; E=2.69; R=4.08; rawP=8.03e-05; adjP=0.0021
Salivary secretion8NOS1, CST1, PLCB1, SLC12A2, ATP1A2, KCNN4, CST4, LYZC=78; O=8; E=2.02; R=3.96; rawP=0.0009; adjP=0.0185
Cell adhesion molecules (CAMs)10CD4, ITGA8, ITGA4, PVRL3, SELE, NRXN1, CLDN10, CLDN11, NEGR1, CNTN1C=126; O=10; E=3.26; R=3.06; rawP=0.0016; adjP=0.0265
Pathways in cancer18MMP9, FGF9, COL4A2, PPARG, WNT2, CTNNA2, WNT5A, FAS, LAMA3, IL8, MMP2, IGF1, TGFB3, KITLG, COL4A1, MET, LAMC2, CDK6C=319; O=18; E=8.27; R=2.18; rawP=0.0018; adjP=0.0265
Hematopoietic cell lineage7IL7, KITLG, CD4, IL1B, ITGA4, CD1C, ANPEPC=80; O=7; E=2.07; R=3.38; rawP=0.0047; adjP=0.0543
Cytokine-cytokine receptor interaction14IL7, LIF, CXCL13, BMP7, TNFRSF21, IL8, TGFB3, KITLG, MET, IL1B, CXCR1, INHBA, BMPR1B, FASC=248; O=14; E=6.43; R=2.18; rawP=0.0054; adjP=0.0543
Rheumatoid arthritis7ATP6V0D2, MMP3, IL1B, CTSK, IL8, ACP5, TGFB3C=82; O=7; E=2.12; R=3.29; rawP=0.0054; adjP=0.0543

[i] KEGG, Kyoto Encyclopedia of Genes and Genomes; ECM, extracellular matrix.

Results of RT-Qpcr

We selected 10 genes [integrin alpha4 (ITGA4), integrin alpha8 (ITGA8), contactin 1 (CNTN1), neurexin 1 (NRXN1), laminin alpha3 (LAMA3), laminin gamma2 (LAMC2), collagen type XI alpha1 (COL11A1), collagen type VI alpha3 (COL6A3), collagen type VI alpha1 (COL6A1) and chondroadherin (CHAD)] to validate the expression data from microarray analysis using SYBR-Green based RT-qPCR. The expression of these genes was significantly altered in various functional modules, as shown in Table III. The 10 genes with expression levels differing by at least 2-fold between the DP and PDL tissues were selected. The results indicated that the mRNA levels of ITGA4, ITGA8, NRXN1 and CNTN1 were significantly higher in the DP compared with the PDL tissues. However, the levels of COL11A1, ACAN, COL6A1, CHAD, LAMC2 and LAMA3 were higher in the PDL tissue compared with the DP tissue (Fig. 4). The mRNA expression levels demonstrated a consistent trend as the cDNA microarray. Taken together, these results suggested that the two types of tissues have a similar mRNA expression profile, paralleling the results determined by RT-qPCR.

Discussion

With global gene expression profiling, this study uncovered DEGs from DP and PDL tissues. The cDNA microarray results indicated that the expression levels of 1,405 out of 29,096 (4.82%) genes were altered by at least 2-fold in one tissue type relative to the other. Lee et al (14) reported that only 490 out of 33,297 (1.49%) genes were differentially expressed between dental follicle and PDL tissues. This discrepancy may arise from the relative heterogeneity between DP and PDL tissues.

To further analyze the DEGs, functional enrichment analyses were conducted using the WebGestalt tool. Our results revealed that the DEGs were associated with ECM-receptor interaction, protein digestion and absorption and focal adhesion, which were the three most enriched terms. The most enriched term ECM-receptor interaction is a complex network of different combinations of collagens, proteoglycans, hyaluronic acid, laminin, fibronectin and many other glycoproteins, including proteolytic enzymes involved in the degradation and remodeling of the ECM. Dentin ECM proteins play important roles in the dynamics of dentinogenesis (24,25). Detailed studies of dentin matrix proteins may give some insights into unelucidated mechanisms of dentinogenesis.

Focal adhesion formation is initiated upon the binding of adhesion receptors to ECM ligands. The cell adhesion molecule, EpCAM, CNTN1 and NRXN1 had a higher expression in the DP tissues, while CHAD, LAMC2 and LAMA3 were upregulated in the PDL tissues. A recent study presented a close interaction of EpCAM with other cell-cell contact molecules, such as E-cadherin and claudins (26). CNTN1, a prototypical member of the contactin (CNTN) family, is involved, through cis- and trans-interactions with specific cell adhesion molecules, in neural cell migration, axon guidance and the organization of myelin subdomains (27). NRXN functions as synaptic transmission and maturation of contacts (28,29). CHAD, a leucine rich repeat ECM protein with functions in cell to matrix interactions, is associated with both cartilage and bone homeostasis (30). Laminin, one of the major glycoprotein components, may maintain and regulate odontoblast differentiation and enamel crystallization (31).

As the ECM receptors in focal adhesions, integrins are heterodimeric transmembrane proteins that connect the actin cytoskeleton to the extracellular microenvironment and bidirectionally mediate signals across cell membrane (32,33). ITGA2, ITGA4 and ITGA8 were upregulated in the DP compared with the PDL tissues. It has been have found that ITGA2 is positively expressed in DP cells (34) and ITGA4 was stained in the dental neural crest-derived progenitor cells (dNC-PCs) (35). Adherent cells can identify laminin through ITGA2 for adhesion and differentiation (36), and recognize fibronectin via ITGA4 for attachment and migration (37). However, ITGA11 was upregulated in the DPL compared with the PD tissues. A previous study demonstrated that the ITGA11 knockout mice were characterized by a disorganized PDL, which may be attributable to the disturbed matrix metallopeptidase synthesis, and greatly reduced cell adhesion and spreading on collagen I (38). The regulation of matrix metalloproteinase-13 (MMP-13) and cathepsin K is ITGA11-dependent, which is involved in the coordinated extracellular and intracellular collagen proteolysis (39). In addition, integrin-binding sialoprotein (IBSP), which is a major structural protein of the bone matrix (40), was found to be upregulated in the PDL compared with the DP tissue in this study.

Some of the genes that were relatively strongly expressed in PDL tissues were associated with the degradation of the ECM. MMPs, the major players in collagen breakdown, have been identified in periodontal inflammation (41). The robust expressions of collagenases cathepsin K (CTSK) and MMP-3, -9 and -19, which were higher in the PDL tissue than in the DP tissue, are likely to play a part in the turnover of ECM in normal or pathological processes (4143). A disintegrin and metalloproteinase with thrombospondin motif (ADAMTS14), which is zinc-dependent metalloproteinase and a member of the ADAMTS family of extracellular proteases, is involved connective tissue remodeling and inflammation (44). PDL cells may play a role in both the production and degradation of versican through the secretion of ADAMTS1, ADAMTS4 and ADAMTS5 (45).

In this study, the Wnt pathway member, Wnt family member 2 (WNT2), and Dickkopf-related protein 2 (DKK2), as well as the transforming growth factor (TGF)β/bone morphogenetic protein (BMP) pathway member, BMP3, BMP8A and TGFβ3 were upregulated in the PDL tissues. Cells in the periodontal complex are Wnt responsive, and removing an important member of the Wnt signaling network gives rise to a pathological widening of the PDL space (46). However, other BMP family members (BMP7, BMP6 and BMP5) were upregulated in the DP tissues.

Of note, the PDL expressed more genes associated with inflammation or immune reaction than did the DP tissues. For example, CXCL2, 8 and 13, which are associated with chemotaxis, were upregulated in the PDL tissues. CXCL13, constitutively expressed in secondary lymphoid tissue, is a potent lymphoid chemokine (47). Studies have shown that CXCL13 is associated with B-cell recruitment in chronic inflammatory periodontal lesions (48). The results of this study suggest that anti-CXCL13 may be a promising approach to modulate pathogenic immune responses in PDL tissues.

Dentin sialophosphoprotein (DSPP), the most abundant non-collagenous protein in dentin, is a marker for DPSC differentiation into odontoblasts and is essential for the normal mineralization of dentin (24,25,49,50). DSPP is processed by proteases into three primary domains: dentin sialoprotein (DSP), dentin phosphoprotein (DPP) and dentin glycoprotein (DGP). The dentin matrix proteins (DMPs) lead to tissue calcification due to inherent calcium binding properties in the ECM (50). Both DSPP and DMP1 were upregulated in the DP compared with the PDL tissue in this study.

Genes associated with osteogenic [osteopontin (OPN and osteocalcin (OCN)], osteoclastic [tartrate-resistant acid phosphatase (TRAP)] and chondrogenic (ACAN) functions were more strongly expressed in the PDL than in the DP tissue. OPN, indicated as Spp-1, is a multifunctional sialic acid-rich phosphorylated glycoprotein. OCN, shown as bone Gla protein, is a major non-collagenous protein. TRAP, known as ACP5, is involved in dissolugion of bone mineral though extracellular acidification (51). ACAN, one of the major components of the ECM, is mainly responsible for the high resistance to compression of the load-bearing tissue (52).

RT-qPCR analyses were performed to verify our cDNA microarray results. ITGA4, ITGA8, NRXN1 and CNTN were upregulated in the DP relative to the PDL tissue, while COL11A1, ACAN, COL6A1, CHAD, LAMC2 and LAMA3 were overexpressed in the PDL tissue compared with the DP tisue. These findings are in line with the microarray results.

In conclusion, this study compared gene expression profiles between DP and PDL tissues from human permanent teeth. Although only the RNA from the entire PD and PDL tissues was detected in this study, and not from the individual cell that constitutes these tissues, we consider that our results provide some novel insight into the characterization of DP and PDL tissues, and provide the potential molecular mechanisms concerning dental tissue mineralization and regeneration. The two types of tissue expressed specific genes related to their functions. The knowledge generated from this study demonstrated the differences between the DP and PDL tissues at the molecular biological level and may narrow down the field of potentially important signaling pathways for clinically relevant tissue regeneration.

Acknowledgments

We acknowledge financial support from the Nanjing Medical Science and Technology Development Project (grant no. YKK15133), and the Maternal and Child Healthcare Project of Jiangsu Province (grant no. F201557). This work was also funded by the National Natural Science Foundation of China (grant no. 81230022), the Priority Academic Program Development of Jiangsu Higher Education Institutions (grant no. PAPD-2014-37), the Natural Science Foundation of Jiangsu Province (grant nos. BL2014073 and 15KJA320002) and the Jiangsu Provincial Key Medical Discipline.

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Gong A, Zhang J, Li J, Wu J, Wang L and Miao D: Comparison of gene expression profiles between dental pulp and periodontal ligament tissues in humans. Int J Mol Med 40: 647-660, 2017.
APA
Gong, A., Zhang, J., Li, J., Wu, J., Wang, L., & Miao, D. (2017). Comparison of gene expression profiles between dental pulp and periodontal ligament tissues in humans. International Journal of Molecular Medicine, 40, 647-660. https://doi.org/10.3892/ijmm.2017.3065
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Gong, A., Zhang, J., Li, J., Wu, J., Wang, L., Miao, D."Comparison of gene expression profiles between dental pulp and periodontal ligament tissues in humans". International Journal of Molecular Medicine 40.3 (2017): 647-660.
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Gong, A., Zhang, J., Li, J., Wu, J., Wang, L., Miao, D."Comparison of gene expression profiles between dental pulp and periodontal ligament tissues in humans". International Journal of Molecular Medicine 40, no. 3 (2017): 647-660. https://doi.org/10.3892/ijmm.2017.3065