Keywords
amelogenesis - genes - genetics - preameloblasts - secretory ameloblasts - tooth development
Introduction
Amelogenesis is the process by which enamel is formed by epithelial ameloblasts facing
the odontoblast layer. More advanced odontoblasts and stratum intermedium cells initiate
ameloblast differentiation via molecular signals. Amelogenins, enamelins, ameloblastins,
and tuftelins, which are released into the extracellular space by ameloblasts, are
the major proteins of the enamel matrix. Enamel changes into highly mineralized tissue,
and as a result, ameloblasts consume debris.[1] Apoptosis kills approximately half of the ameloblasts during amelogenesis, and the
remaining half dies after the process has been completed. Amelogenesis is a process
of gradual differentiation governed by a number of molecular and morphogenetic events
and is distinguished by the formation of enamel and the differentiation of ameloblasts.
Enamel is made by epithelial cells called ameloblasts that fuse with the odontoblast
layer in a process called amelogenesis. The process of amelogenesis ends when the
tooth erupts, and there is no secondary or regenerative enamel development afterward.
Therefore, amelogenesis is distinguished by the transition from preameloblast (PAB)
to secretory ameloblast (SAB). Following the disintegration of the basement membrane
during the bell stage of tooth formation,[2] induced by signals from the underlying dental mesenchymal compartment, PABs differentiate
into SABs, thereby initiating the differentiation process. These extracellular matrix
proteins are necessary for the formation and mineralization of enamel,[3] and disruption of ameloblast protein production results in deformed enamel.[4] Ameloblasts differentiate into short mature ameloblasts (MABs) that regulate enamel
mineralization after laying down a full-thickness enamel matrix. MABs die by apoptosis[5] following tooth eruption. Because adults lack easily available ameloblast-lineage
cells, enamel cannot be restored or regenerated. Amelogenesis imperfecta (AI) is a
collection of inherited diseases that cause changes in the structure and appearance
of dental enamel and are frequently associated with changes in other intraoral or
extraoral tissues. AI is a group of genetically determined disorders that have a relatively
uniform effect on the structure and clinical appearance of the enamel on all or nearly
all teeth and that can be linked to morphologic or biochemical abnormalities elsewhere
in the body.[6] Amelogenin is expressed in humans and cattle from genes on the X and Y chromosomes.
In human males, amelogenin (AMELX) transcripts are expressed from the X chromosomal
copy of the gene, while 10% are expressed from the Y chromosomal copy (AMELY). The
ENAM gene in this region has been identified as a potential gene affected in the form
of AI.[7]
The ENAM gene contains 10 exons and 9 introns. The ameloblastin (AMBN) gene is strongly
expressed by ameloblasts and weakly expressed by odontoblasts and preodontoblasts,
with moderate expression also observed in Hertwig's epithelial root sheath and odontogenic
benign tumors with malignant behavior such as ameloblastoma. The gene encoding human
enamelysin (matrix metalloproteinase-20, or MMP-20) resides on chromosome 11. Many
studies have found that MMP-20 is only present in teeth. A genetic mutation of MMP-20
was discovered in two family members affected with autosomal-recessive pigmentary
hypomaturity. This mutation removes the splice acceptor at the 3′ end of intron 6
and results in the production of a hypomature enamel product. The most likely outcomes
appear faulty splicing with both defects introducing an upstream translation termination
codon.[8] The KLK4 gene, found on chromosome 19, is a member of the human tissue kallikrein
gene family. KLK4 is involved in fragmenting smaller pieces of the tumor necrosis
factor receptor-associated protein amelogenin cleavage product. In the case of KLK4,
one mutation leads to a shortened protein that has 152 but lacks the S207 site, which
is required for the enzyme to function; because of this aberrant enzyme activity,
the enamel crystallites expand to standard length but only partial thickness.[9]
Amelogenesis is one of the important mechanisms in tooth development. Unraveling the
role of genes associated with the mechanisms will open new avenues for diagnostic
techniques and cures related to tooth disorders. In silico studies in which gene identification and functional genomics studies are performed
before designing follow-up laboratory research, are very useful. In the present study,
various bioinformatics tools were used to identify and characterize amelogenesis-related
genes to unravel their roles in tooth development. Moreover, using bioinformatics
tools to study genes associated with dental biology and health is frequent in the
dental sciences. Identification of relevant molecules and signaling networks with
greater precision will shed light on the mechanisms that govern enamel formation and
lay the groundwork for elucidating the mechanisms that regulate the differentiation
of PABs into SABs to better understand enamel regeneration. This study has provided
new information that will be helpful in finding pragmatic treatments for genetic disorders
associated with amelogenesis.
Materials and Methods
Data Mining and Quality Control Analysis
The data was retrieved from the Gene Expression Omnibus (GEO) data set series GSE59214.
After collecting expression profiling using array data, the GEO2R Web tool was used
for further analysis to identify genes differing in expression across various experimental
conditions. GEO2R is an interactive resource for contrasting two or more sample groups
within a GEO series to locate genes that are expressed differentially in differing
experimental settings.
The findings have been presented in the form of a gene table in order of importance,
a series of graphical plots to aid in the visualization of differentially expressed
genes, and a quality assessment of the data set, using the Bioconductor project's
GEO query[10] and limma R packages.[11] Limma (linear models for microarray analysis) is a popular statistical technique
for identifying differentially expressed genes using the R programming language. Statistical
p-values were subjected to multiple-testing corrections in a wide range of experimental
designs and data sources to reduce the likelihood of false-positive results. For comparison,
the data was divided into two groups, namely, PAB and SAB, and each group contained
three replications. To normalize data[12] and visualize the distribution of the values in the selected samples, an expression
box plot and a density plot were generated.[13]
Uniform Manifold Approximation and Projection Analysis
Next, a uniform manifold approximation and projection (UMAP) plot was generated. UMAP
is a technique of dimension reduction that can be used to better view the connections
that exist between individual samples.[14]
Value Histogram
To analyze the distribution of all genes according to their p-values, a p-value histogram plot[15] was generated.
Mean Difference and Mean-Variance Plots
A mean difference plot was constructed to display the results of a single comparison
(one group of PABs compared to another group of SABs). A mean-variance plot was generated
to analyze the variation in the data.[16]
Volcano Plot
To identify the top-upregulated genes, a volcano plot[17] analysis was employed. The top 20 upregulated genes were selected according to the
lowest adjusted p-values. The most dependable genes exhibited the lowest p-values ([Table 1]).
Table 1
Top upregulated genes
|
ID
|
Adjusted p-value
|
p-Value
|
Log FC
|
Gene symbol
|
Gene title
|
|
8151341
|
0.00178
|
0.00000010
7
|
4.357
|
TRPA1
|
Transient receptor potential cation channel subfamily A member 1
|
|
8138289
|
0.00584
|
0.00000114
|
3.912
|
ETV1
|
ETS variant 1
|
|
8056572
|
0.00584
|
0.00000158
|
3.749
|
SPC25
|
SPC25, NDC80
kinetochore complex component
|
|
7940147
|
0.00584
|
0.00000138
|
3.551
|
FAM111B
|
Family with sequence similarity 111 member B
|
|
7923086
|
0.00584
|
0.00000082
5
|
3.218
|
ASPM
|
Abnormal spindle microtubule assembly
|
|
7967993
|
0.00584
|
0.00000105
|
2.564
|
FGF9
|
Fibroblast growth factor 9
|
|
8124531
|
0.00584
|
0.00000151
|
2.367
|
HIST1H3I
|
Histone cluster 1, H3i
|
|
8117594
|
0.01494
|
0.0000056
|
3.903
|
HIST1H2BM
|
Histone cluster 1, H2bm
|
|
7909946
|
0.01494
|
0.00000844
|
3.592
|
FAM177B
|
Family with sequence similarity 177 member B
|
|
8052355
|
0.01494
|
0.00000775
|
3.241
|
EFEMP1
|
EGF containing fibulin-like extracellular matrix protein 1
|
|
8171260
|
0.01494
|
0.00000886
|
3.189
|
FAM9A
|
Family with sequence similarity 9 member A
|
|
8094278
|
0.01494
|
0.00000679
|
2.939
|
NCAPG
|
Non-SMC condensin I complex subunit G
|
|
8103932
|
0.01494
|
0.00000783
|
2.862
|
CENPU
|
Centromere protein U
|
|
7926728
|
0.01494
|
0.00000823
|
2.285
|
MYO3A
|
Myosin IIIA
|
|
7910997
|
0.01494
|
0.00000791
|
2.149
|
EXO1
|
exonuclease 1
|
|
8117426
|
0.01494
|
0.0000085
|
1.94
|
HIST1H2BH///HIST1H2B H
|
Histone cluster 1, H2bh///histone cluster 1, H2bh
|
|
8101788
|
0.01528
|
0.00000964
|
2.355
|
UNC5C
|
unc-5 netrin receptor C
|
|
7982889
|
0.01651
|
0.0000109
|
3.443
|
NUSAP1
|
Nucleolar and spindle associated protein 1
|
|
8120838
|
0.01659
|
0.0000118
|
2.563
|
TTK
|
TTK protein kinase
|
Abbreviations: EGF, epidermal growth factor; ETS, erythroblast transformation-specific;
FC, fold change; SMC, structural maintenance of chromosomes.
Note: The top 20 upregulated genes, selected according to the lowest adjusted p-values (< 0.05).
Protein-Protein Interaction and Gene Enrichment Analysis
An investigation of protein-protein interactions[18] was performed on the selected genotypes. The g:Profiler web was used for gene enrichment
analysis[19] to analyze the ontology, relevant biological processes, and molecular functions
of selected genes.
Results
Data Normalization Quality Control
Because the expression data was normalized, all selected samples had the same value
distribution. The box plots in [Fig. 1A] show the normalization of two samples. The first sample represents PABs with three
replications, and the second sample represents SABs with three replications. The plots
show the data variation between the PABs and the SABs with their replications. The
density expression plot in [Fig. 1B] shows that the variation between the PABs and the SABs was small.
Fig. 1 (A) Diagnostic plots for microarray data from three samples of preameloblasts and three
samples of secretory ameloblasts. (B) Density plot of preameloblast and secretory ameloblast samples.
UMAP and p-Value Histogram Plot
The plot in [Fig. 2A] shows that there were substantial differences among thousands of genes in PABs and
SABs. Variations among three biological replicates of PABs and three biological replicates
of SABs were minimal; however, a distinct difference between samples of PABs and SABs
was noted. The histogram in [Fig. 2B] displays the set of p-values. From the p-value histogram, it is evident that the p-values were not uniformly distributed.
Fig. 2 (A) Uniform manifold approximation and projection (UMAP) plot generated from three samples
of preameloblasts and three samples of secretory ameloblasts. (B) Adjusted p-value histogram showing the p-value distribution for all analyzed genes.
Variance Trend and Mean Difference Plot
The graph shown in [Fig. 3A] illustrates the relationship between the mean and variance of the PAB and SAB expression
data and aided in determining whether there was a high level of variety in the data.
This graph could also be used to determine whether the precision weights option for
accounting for mean-variance trends should be used; precision weights improve test
result precision when there is a strong mean-variance trend. Each dot corresponds
to a gene. The mean difference plot of PABs versus SABs denotes upregulated genes
by red dots and downregulated genes by blue dots, showing the average of normalized
counts versus log2 fold changes for all genes studied.
Fig. 3 (A) Variance trend plot of preameloblasts versus secretory ameloblasts. Each dot corresponds
to a gene. The red line represents an approximation of the mean-variance trend. The
blue line is an approximation to a constant variance. (B) Mean difference plot of preameloblasts versus secretory ameloblasts.
Venn Diagram
A Venn diagram of the genes indicated that out of a total of 33,140 genes, 157 were
significant in the PAB versus SAB comparison ([Fig. 4]). Data regarding the significant genes has been provided in the Excels spreadsheet.
Fig. 4 Venn diagram of preameloblasts versus secretory ameloblasts.
Volcano Plot
The volcano plot ([Fig. 5]) of PABs versus SABs presents p-value versus magnitude of change statistical significance (fold change). It represents
the identification of genes with large, statistically significant changes. In this
volcano plot, the most upregulated genes are on the right, the most downregulated
genes are on the left, and the most statistically significant genes are at the top.
Fig. 5 Volcano plot of upregulated and downregulated genes in preameloblasts versus secretory
ameloblasts.
The volcano plot was constructed to identify the top-upregulated genes in PABs versus
SABs. The increase in upregulated genes was fourfold in the PAB versus SAB plot. All
of the gene data is presented in an Excel spreadsheet.
Protein-Protein Interactions
Protein-protein interaction analysis was performed on the set of genes selected according
to the adjusted p-values. According to this analysis, HIST1H31 revealed strong interaction with HIST1H2BM,
and EXO1, ASPM, SPC25, and TTK showed strong interaction with one other ([Fig. 6]). The STRING database indicates that NCAPG, CENPU, NUSAP1, HIST1H2BM, and HIST1H3I
are involved in biological processes. NCAPG, CENPU, SPC25, ETV5, TTK, ETV1, FAM9A,
NUSAP1, HIST1H2BM, and HIST1H3I are related to cellular components ([Table 1]).
Fig. 6 Protein-protein interaction analysis.
Gene Enrichment Analysis
Functional enrichment analysis was performed on selected genes from PABs and SABs.
This analysis provided information regarding the molecular function of gene ontology,
biological process of gene ontology, and cellular components of gene ontology. The
analysis revealed that the genes are involved in biological processes, cellular components,
and KEGG pathways, as shown in [Fig. 7]. The table of gene ontology with p-value is shown in [Fig. 8], and the functional descriptions are provided in the Excel data sheet.
Fig. 7 Functional enrichment analysis graph.
Fig. 8 Table of gene ontology with terms, term identifiers (IDs), and p-values.
Discussion
Ameloblasts are a type of cells responsible for the deposition of enamel and the production
of extracellular matrix proteins.[3] SABs deposit extracellular matrix, and the MABs mineralize the organic matrix, resulting
in the production of enamel,[20] one of the hardest mineralized tissues in vertebrates.[21] Three stages of ameloblast differentiation together produce a fully developed ameloblast:
the presecretory, secretary, and maturation stages.[2] Terminally developed cells called squamous ameloblasts and molar ameloblasts are
formed from undifferentiated ameloblasts called PABs during odontogenesis.[22] PABs are dental epithelial cells that are elongated and columnar in shape, with
their nuclei clustered along the stellate reticulum as well as their cytoplasm, which
contains the organelles required for protein synthesis and secretion of enamel. Enamel
formation and ameloblast differentiation are hallmarks of the process of amelogenesis,
which is governed by a number of molecular and morphogenetic events. It is generally
agreed that one of the defining characteristics of amelogenesis is the change from
PAB to SAB. The niche in which ameloblasts differentiate is composed of secreted proteins,
enzymes, signaling molecules, and other components.
The transition from PAB to postameloblast occurs during ameloblast differentiation,
and it has a profound effect on the secretion of matrix proteins in the enamel and
the commencement of mineralization. Signaling molecules, their receptors, and transcriptional
regulators all work together to control this process.[22] However, the transcriptional pathways governing ameloblast development remain poorly
understood. Specifically, we sought to identify genes that upregulate during the ameloblast
transition from PAB to SAB. According to a study by Liu et al,[23] four genes (AMBN, AMTN, ENAM, and MMP-20) are associated with SABs, consistent with
previous studies. They revealed that cell cycle control, deoxyribonucleic acid (DNA)
damage repair, and apoptosis were linked to high-expression genes in PABs among other
differentially expressed genes. On the other hand, highly expressed genes in SABs
were linked to cell adhesion and extracellular matrix.[23] Another study revealed that SABs released extracellular matrix proteins into the
enamel matrix consisting of three structural proteins (AMELX, AMBN, and ENAM). MMP-20
and KLK4 separate these proteins from the matrix in phases during the ameloblast secretory
and maturation processes, respectively.[22]
Real-time polymerase chain reaction (PCR) validated AMELX enrichment in SABs, whereas
microarray analysis did not. Microarrays have a lower detection limit as opposed to
real-time PCR; thus, the fold changes seen by microarrays are typically smaller.[24] Additional gene enrichment analysis of SABs revealed the presence of five genes
(DSPP, DMP1, PHEX, ALPL, and MMP-16) involved in biomineralized tissue production,
all of which have the potential to control ameloblast differentiation and enamel formation.
In this study, an analysis of gene enrichment was performed in order to conduct a
comprehensive study of the genes. In the gene enrichment study, it was discovered
that of the selected genes, TTK, NUSAP1, HIST1H2BM, NCAPG, CENPU, FAM9A, SPC25, ETV5,
ETV1, MYO3A, EFEMP1, and HIST1H3I are engaged in biological processes such as regulation
of reproductive processes, nuclear division, and mitotic sister chromatid segregation.
They are also present in cellular components, condensed chromosomes, centromeric regions,
kinetochores, supramolecular complexes, and chromosomal regions. When compared to
SABs, PABs have higher expression data. The genes TTK, NUSAP1, CENPU, NCAPG, FAM9A,
ASPM, SPC25, and HIST1H3I function in mitotic sister chromatid segregation, cell division,
and organelle fission. In comparisons of conditions of PABs and SABs, the p-values of these genes were lower than 0.05.
Conclusion
We compared two groups, namely, PABs and SABs. During tooth development, the expression
of genes involved in the regulation of the cell cycle, repair of DNA damage, and apoptosis
pathways regulate PAB maturation. Several signaling mechanisms govern SAB cell behavior,
specifically the production of enamel matrix proteins and cell adhesion, both of which
are required for enamel development and cell-cell interactions. PAB versus SAB expression
data was used to study gene function. The TTK, NUSAP1, CENPU, NCAPG, FAM9A, ASPM,
SPC25, and HIST1H3I genes function in cell division, and these genes may play a role
in ameloblast development. These results will be useful in developing new methods
to stimulate ameloblast development, which is essential for tooth regeneration and
tissue engineering. However, further research is required to validate the functions
of these genes and the genes with which they interact. A wide variety of genetic,
epigenetic, and exogenous signaling factors regulate these genes and pathways to direct
throughout development and differentiation, cell fate, and behavior.
