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J Cell Biochem. 2020;1–12. wileyonlinelibrary.com/journal/jcb © 2020 Wiley Periodicals, Inc. | 1
Received: 22 June 2019 | Accepted: 9 December 2019
DOI: 10.1002/jcb.29578
RE S EARCH ART I C L E
Transcriptome‐wide study of the response of human
trabecular meshwork cells to the substrate stiffness
increase
Jinjun Tie1,3 | Dong Chen2,5 | Junhong Guo4,6 | Shengjie Liao2,5 | Xiaotian Luo5 |
Yu Zhang2 | Ruru Guo1 | Chenjia Xu1,3 | Dandan Huang1,3 | Yi Zhang2,5 |
Jiantao Wang4,6
1Tianjin Medical University Eye Institute, Tianjin Medical University, Tianjin, China
2Center for Genome Analysis, ABLife Inc., Wuhan, Hubei, China
3College of Optometry and Ophthalmology, Tianjin Medical University, Tianjin, China
4Shenzhen Key Laboratory of Ophthalmology, Shenzhen Eye Institute, Shenzhen Eye Hospital, Jinan University, Shenzhen, Guangdong, China
5Laboratory for Genome Regulation and Human Health, ABLife Inc., Wuhan, Hubei, China
6School of Ophthalmology & Optometry, Shenzhen University, Shenzhen, Guangdong, China
Correspondence
Yi Zhang, Center for Genome Analysis,
ABLife, Inc., 430075 Wuhan, China.
Email: yizhang@ablife.cc
Jiantao Wang, Shenzhen Key Laboratory
of Ophthalmology, Shenzhen Eye
Institute, Shenzhen Eye Hospital
Affiliated to Jinan University, 518040
Shenzhen, Guangdong, China.
Email: wangjiantao65@126.com
Funding information
Science and Technology Programs of
Shenzhen, Grant/Award Number:
GJHZ20190929145402153; Sanming
Project of Medicine in Shenzhen,
Grant/Award Number: SZSM201812091;
National Natural Science Foundation of
China, Grant/Award Number: 81270994;
Appreciate the Beauty of Life
Incorporation, Wuhan,
Grant/Award Number: 201411009
Abstract
Elevated intraocular pressure, a major risk factor of glaucoma, is caused by the
abnormal function of trabecular outflow pathways. Human trabecular meshwork
(HTM) tissue plays an important role in the outflow pathways. However, the
molecular mechanisms that how TM cells respond to the elevated IOP are largely
unknown. We cultured primary HTM cells on polyacrylamide gels with tunable
stiffness corresponding to Young's moduli ranging from 1.1 to 50 kPa. Then next‐
generation RNA sequencing (RNA‐seq) was performed to obtain the transcriptomic
profiles of HTM cells. Bioinformatics analysis revealed that genes related to
glaucoma including DCN, SPARC, and CTGF, were significantly increased with
elevated substrate stiffness, as well as the global alteration of HTM transcriptome.
Extracellular matrix (ECM)‐related genes were selectively activated in response to
the elevated substrate stiffness, consistent with the known molecular alteration in
glaucoma. Human normal and glaucomatous TM tissues were also obtained to
perform RNA‐seq experiments and supported the substrate stiffness‐altered
transcriptome profiles from the in vitro cell model. The current study profiled
the transcriptomic changes in human TM cells upon increasing substrate stiffness.
Global change of ECM‐related genes indicates that the in vitro substrate stiffness
could greatly affect the biological processes of HTM cells. The in vitro HTM cell
model could efficiently capture the main pathogenetic process in glaucoma
Abbreviations: AFM, atomic force microscopy; DEGs, differentially expressed genes; ECM, extracellular matrix; FPKM, fragments per kilobase per
million mapped reads; IOP, intraocular pressure; JCT, juxtacanalicular tissue; qPCR, quantitative polymerase chain reaction; SC, Schlemm's canal;
TM, trabecular meshwork.
Jinjun Tie, Dong Chen, and Junhong Guo contributed equally to the work.
http://orcid.org/0000-0003-2756-1855
mailto:yizhang@ablife.cc
http://crossmark.crossref.org/dialog/?doi=10.1002%2Fjcb.29578&domain=pdf&date_stamp=2020-03-01
patients, and provide a powerful method to investigate the underlying molecular
mechanisms.
KEYWORD S
extracellular matrix, glaucoma, HTMCs, substrate stiffness, transcriptome
1 | INTRODUCTION
Elevated intraocular pressure (IOP) is a major and the
only treatable risk factor for glaucoma, one of the leading
causes of blindness in the world.1 IOP homeostatic is
dependent on the rate of fluid removal, which is mainly
finished by the conventional human trabecular mesh-
work (HTM) outflow pathways.2,3 Normal IOP changes
alter aqueous outflow, mechanical stress that induce
deformation in ocular tissues, particularly the pressure‐
responsive HTM.4–6 The HTM tissue includes three
regions from inner to outermost: The uveal meshwork
(UTM), the corneoscleral meshwork (CTM), and the
juxtacanalicular tissue (JCT).7,8 Cell membranes fluor-
escent labeling showed that CTM and JCT harbored a
high density of HTM cells than the UTM.9 Several studies
also revealed that dysfunction of TM cells can eventually
result in IOP dysregulation and glaucoma.8,10
It has been reported that the HTM is markedly stiffer
in patients with glaucoma, and the stiffness is positively
correlated with the outflow resistance.11 By atomic force
microscopy (AFM) surveying, the elastic modulus in
normal HTM ranged from 1.7 to 8.8 kPa, while glauco-
matous HTM had a significant increase in elastic
modulus ranging from 29.6 to 138.4 kPa.12 It has been
reported that substratum compliance by polyacrylamide
hydrogels treatment could regulate HTM behaviors and
biophysical effects, and alter cytoskeletal dynamics and
the elastic modulus of the overlying HTM cells.13,14
Similar phenomena were also found in normal and
glaucomatous Schlemm's canal (SC) cells with the
enhanced Young's moduli using polyacrylamide hydrogel
model.15 All these results demonstrate that the in vitro
growth of HTM and SC cells on polyacrylamide hydrogel
cells can mimic the in vivo conditions of TM tissues.
Recently, genome‐wide association study of thousands
of patients with glaucoma revealed the association of
genetic variations from tens of genes,16–19 which could be
treated as one of the risk factors of glaucoma.20 Tran-
scriptome studies revealed that gene expression alteration
plays important roles in TM development and glaucoma
progression.21–25 The previous studies have demonstrated
the importance of the extracellular matrix (ECM) metabo-
lism in glaucoma pathology. Remodeling of ECM synthe-
sized by HTMCs is important in the homeostatic regulation
of IOP.26–29 However, the molecular mechanisms regulating
the HTM response to the cyclic IOP changes and
developing the HTM dysfunction in glaucoma remain
largely unclear.
To further study the molecular mechanisms regulating
the HTM response to IOP changes under the normal and
glaucomatous conditions, we applied for the recent
advance in deep RNA‐sequencing technology to study
the HTM transcriptome changes when grown in vitro on
polyacrylamide hydrogel to mimic differential substratum
compliance ranging from homeomimetic to pathomimetic
conditions. The results revealed an extensive change in the
expression of ECM‐related genes in response to glauco-
matous substratum stiffness. This finding was confirmed
by the RNA‐seq experiment of HTM tissues from patients
with glaucoma and normal individuals.
2 | MATERIALS AND METHODS
2.1 | HTM cells cultivation
HTM cells (Catalog No. #6590) were obtained from
ScienCell (http://www.Sciencell.com.cn/) and cultured in
monolayers in basal HTM cell medium (Catalog No. 6591).
2.2 | Immunofluorescence
Immunofluorescence experiments for HTM cells were
performed following one published experimental protocol.30
The following primary antibodies used: rabbit anti‐human
myocilin (CUSABIO, CSB‐PA859950LA01HU), rabbit anti‐
GAPDH monoclonal antibody (AC033; ABclonal), was
added and incubated overnight at 4°C in bovine serum
albumin 0.3%. Samples were washed once with phosphate‐
buffered saline (PBS). Secondary antibodies including
rhodamine goat anti‐rabbit IgG (H+L) (AS040; ABclonal),
was added to the membrane and incubated for 1 hour at
room temperature. The samples were washed three times
and for 5minutes at each time, with PBS and then
counterstained and mounted with 4′,6‐diamidino‐2‐
phenylindole (D9542‐1Mg;Sigma). Samples were visualized
using Nikon confocal microscope (Nikon, Japan, Nikon
Eclipse Ti) and the acquisition settings were identical for all
2 | TIE ET AL.
http://www.Sciencell.com.cn/
treatments. Protein expressions were quantified from 488
fluorescence images using software Image J (https://imagej.
nih.gov/ij/).
2.3 | Model construction
To prepare polyacrylamide hydrogel, we followed two
published protocols.13,15 Young's moduli of the gels were
measured using AFM to be 1.1, 2.5, 4.2, 11.9, 34.4, and
50 kPa for bisacrylamide concentrations of 0.04%, 0.1%,
0.2%, 0.5%, 1.3%, and 2.08%, respectively. HTM cells were
seeded confluently on the gels. We prepared two sets of
HTM cells, which were cultured for 3 and 5 days. We
seeded the two sets of HTM cells on the gels separately.
2.4 | RNA extraction and sequencing
The treated HTMCs were ground into a fine powder
before RNA extraction. Total RNA was extracted by the
hot phenol method. The RNA was further purified with
two phenol‐chloroform treatments and then treated with
RQ1 DNase (Promega, Madison, WI) to remove DNA.
The quality, quantity, and integrity of the purified RNA
were determined by Agilent Bioanalyzer2100.
For each sample, 10 μg of the total RNA was used for
RNA‐seq library preparation. Polyadenylated RNAs were
purified and concentrated with oligo (dT)‐conjugated
magnetic beads (Invitrogen, Carlsbad, CA) before direc-
tional library preparation. The purified RNAs were then
iron fragmented at 95°C followed by end repair and
5′ adapter ligation. Then, reverse transcription was
performed with RT primer harboring 3′ adapter sequence
and randomized hexamer. The complementary DNAs
(cDNA) were purified, amplified, and stored at −80°C
until for sequencing.
2.5 | Clinical samples treatment
The study was conducted in accordance with the
Declaration of Helsinki, and the protocol was authorized
and supervised by Tianjin Medical University Eye
Hospital with ID 2016KY‐20. All human samples were
from glaucomatous patients, the remaining glaucoma-
tous donor eyeballs after corneal transplantation. The
light brown, banded, loose, and translucent trabecular
tissue (often containing a small amount of pigments)
between the Schwalbe line and the white scleral process
was identified. We then gently separated and cut the
whole trabecular tissue. We cut the trabecular tissue into
3 to 5 mm long tissue blocks in a small amount of
DMEM/F12 culture medium and prevented the drying of
the tissue blocks during the shearing process. HTM
tissues were then kept in vats of liquid nitrogen.
For each sample, 50 ng of total RNA was used for
RNA‐seq library preparation. Ribosomal RNAs were
depleted with Ribo‐Zero rRNA depletion kit for humans
(Epicenter) before used for directional RNA‐seq library
preparation. Purified RNA was fragmented. Reverse
transcription was performed with a random primer
harboring adapter sequence and a randomized hexamer,
then the synthesized DNA with Terminal‐Tagging oligo
cDNA using ScriptSeq v2 RNA‐seq Library Preparation
kit (Epicenter). The cDNAs were purified and amplified.
Polymerase chain reaction (PCR) products corresponding
to 300 to 500 bps were purified, quantified and stored at
−80°C until for sequencing.
For high‐throughput sequencing, the libraries were
prepared following the manufacturer's instructions and
applied to NextSeq 500 system for 151 nt pair‐end
sequencing (ABlife. Inc).
2.6 | Reverse transcription quantitative
polymerase chain reaction
To test the reliability of the constructed cell model, HTM
cells under different substrate stiffness were selected for
Reverse transcription quantitative (RT‐q) PCR experiments.
Polyadenylated RNAs were reversely transcribed into cDNA
using M‐MLV Reverse Transcriptase (Lot R011‐01, Vazyme,
Nanjing, China) and random primers. RT‐qPCR was
performed using the StepOne RealTime PCR System
(QuantStudio 6 Flex Real‐Time PCR System Contains the
OptiFlex Optics System (Applied Biosystems)) with the
SYBR Green PCR Reagents Kit (Lot 11202ES08, Yeasen,
Shanghai, China). The PCR conditions consisted of
denaturing at 95°C for 30 seconds, followed by 40 cycles
of denaturing at 95°C for 10 seconds and annealing and
extension at 60°C for 30 seconds. PCR amplifications were
performed in triplicate for each sample and normalized
using the human GNB2L gene. Data were assessed using
the comparative Ct ( CΔΔ t) method.
31 Primers for RT‐qPCR
analysis are listed in Table S4.
2.7 | Western blot analysis experiment
Cell pellets were resuspended in 0.1% sodium dodecyl sulfate
(SDS) lysis buffer, incubated on ice for 30minutes with
frequent agitation for lysis. The protein samples were
incubated for 10minutes in boiling water with 1× SDS
sample buffer and separated on 10% SDS polyacrylamide gel
electrophoresis, followed by transferring onto polyvinylidene
TIE ET AL. | 3
https://imagej.nih.gov/ij/
https://imagej.nih.gov/ij/
fluoride membrane (ISQE00010; Millipore). The membranes
were blocked with 5% skim milk (in a buffer containing
10mM Tris, pH 8.0, 150mM NaCl, 0.05% Tween 20) for an
hour, After blocking, membranes were incubated with
primary antibody: MYOC (1:500; CUSABIO), GAPDH
(1:1000; ABclonal) overnight at 4℃, and then with a HRP‐
conjugated secondary antibody for 1 hour at room tempera-
ture. Bound secondary antibody (anti‐mouse or anti‐rabbit
1:10 000) (Abcam) was detected using the enhanced
chemiluminescence (ECL) reagent (32106; Thermo Fisher
Scientific).
2.8 | Bioinformatics analysis
The quality‐filtered reads were generated after removing
adapter sequences and low‐quality sequences. TopHat232
was used to map the reads on the current human genome
(GRCH38) with the parameter –N 4. Only uniquely mapped
reads were used to calculate the fragments per kilobase per
million mapped reads (FPKM). The software edgeR33 was
used to screen out the differentially expressed genes (DEGs),
based on the fold change (FC≥ 1.5) and P‐value (P≤ .01).
For the clinical samples, we performed the same RNA‐
seq analysis pipeline. We then obtained the expression level
of normal TM tissues from Carnes et al.25 To eliminate the
variation from the experiment, the FPKM values of genes
from normal and glaucoma patients were normalized by
dividing the FPKM of GAPDH.
2.9 | Statistical analysis
Hypergeometric test and Benjamini‐Hochberg FDR con-
trolling procedure were used to define the enrichment of
each GO term. Cluster3.0 and Java TreeView were used
to plot the heatmap of the clusters of genes and samples.
K‐means was also used to cluster the differently express
pattern genes. For another statistical method, all values
were presented as mean ± standard deviation. For
comparison, the significance of differences between
means was determined by Student's t‐test. P< .05 was
regarded as statistically significant.
3 | RESULTS
3.1 | The different compliance hydrogel
model construction for HTM cells culture
As a result of the mechanical properties of HTM cells, the
compliance of the substrate is as important as its
topography in modulating HTM cell behaviors and
interactions.7 Previous work showed high modulus
induced more rigid and cytoskeletal architecture in
HTM cells.8 To study the global transcriptional response
of HTM cells to the physiological and pathological
substrate stiffness, we cultured normal HTM cells on
polyacrylamide gels mimicking substrate compliance
from normal to the glaucomatous TM.15 According to
the relationship between polyacrylamide hydrogel con-
centrations and Young's moduli,15,34 we prepared poly-
acrylamide hydrogels of tunable stiffness corresponding
to Young's moduli 1.1, 4.2, 11.9, 34.4, and 50 kPa.
To test whether the purchased HTM cells have the
features of true HTM cells, we performed immunocyto-
chemistry and Western blot analysis experiments to
check the responsiveness of myocilin (MYOC) expression
by stimulating with dexamethasone (DEX).35,36 After
DEX treatment, the protein level of MYOC was
significantly increased (Figure S1A‐C), which was con-
sistent with the reportedproperties of isolated HTM
cells.37
We prepared two sets of HTM cells with different
cellular densities cultured for 3 days (A group) and 5 days
(C group), respectively (Figure 1A). On the home-
omimetic polyacrylamide gel (1.1 to 4.2 kPa), the cells
were predominantly adhered to in a radially symmetric
fashion and were mildly spindle‐shaped in appearance
(Figure 1A). At day 3, the HTM cells grown on the
glaucomatous (pathomimetic) polyacrylamide gel stiff-
ness (34.4 and 50 kPa) became predominantly elongated,
and a spindle‐shaped morphology. Meanwhile, the
number of cells was reduced (Figure 1A). At day 5, cells
on 11.9 and 34.4 kPa substrates were recovered from the
stress, however, the cell stress‐response on 50 kPa
substrates remained. These morphological and cellular
proliferation changes by increased substrate stiffness
were consistent with the disease characteristics of
glaucoma.38,39
To explore the underlying transcriptional changes of
HTM cells under elevated substrate stiffness, several
marker genes linked to mechanosensing, glaucoma, ECM
remodeling, or TGF‐β2/connective tissue growth factor
(CTGF) signaling were investigated in our HTM cell
model. By performing the RT‐qPCR experiment, we
found obviously increased expression level of DCN and
SPARC with elevated stiffness (Figure 1B,C; P< .01;
t‐test). The expression level of DCN was dramatically
increased at 11.9 to 34.4 kPa substrates, while the
expression of SPARC was increased at 2.5 kPa substrate,
consistent with the observation that some important
ECM remodeling genes were induced under pathomi-
metic polyacrylamide gel concentration, and some were
even induced under the homeomimetic polyacrylamide
gel concentration. The higher expression level of the
4 | TIE ET AL.
ECM remodeling genesMMP2 and BMP4 were associated
with higher substrate stiffness (Figure 1D,E; P< .01;
t‐test). CTGF showed the highest expression level at
34.4 kPa, which might indicate the onset of the abnormal
IOP (Figure 1F; P< .01; t‐test).
3.2 | Whole transcriptome alteration
reveals the high substrate stiffness
extensively induces the transcription of
ECM‐related genes
To explore the global transcriptional alteration in
response to the substrate stiffness change, the RNA
sequencing (RNA‐seq) approach was applied to obtain
transcriptome profiles of HTM cells with elevated
substrate stiffness. A total of 39.3 to 84.2 million cDNA
reads were generated in the two groups, with 27.7 to
38.6 million quality‐filtered reads, respectively (Table S1).
Most of the filtered reads were mapped to the coding
sequence (ranging from 62.52% to 68.75%). Among the
annotated genes, 15 425 protein‐coding genes (76.0%),
2156 long intergenic noncoding RNA (lincRNAs)
(10.62%), and 2717 other type noncoding RNAs
(13.38%) were expressed in our data set.
Pearson correlation coefficients among all samples in
both A (day 3) and C (day 5) groups were over 0.95
(Figure S1D‐E), suggesting that the substrate stiffness did
not alter the transcriptome on a large scale. We then
plotted the expression profiles of 26 selected genes that
have been reported to be involved in mechanosensing,
glaucoma, ECM remodeling, or TGF‐β2/connective tissue
growth factor (CTGF) signaling.15,21,40,41 We found that
the expression profile of these genes was different
between groups A and C. In group C that cells grew at
high density, FPKM values were globally higher than the
value in group A (Figure 2A, right). In group C, most of
these genes reached the highest expression level at 50kPa,
the highest substrate stiffness in this study (Figure 2A,
middle). Nevertheless, these genes showed quite diver-
gent expression patterns in group A that cells grew at low
density (Figure 2A, left). These data suggested that
expression of the glaucoma‐related genes in HTM cells
could respond to the elevated substrate stiffness in a cell
density‐dependent manner in vitro.
To analyze genes responding to the elevated
substrate stiffness corresponding to the glaucomatous
polyacrylamide gel condition at the whole transcrip-
tome level, we obtained DEGs between 50kPa and
1.1kPa in the group C. Using edgeR33 with a cutoff
FIGURE 1 Morphology and stress response of HTMCs revealed the dramatic morphological and molecular change with substrate
stiffness. A, Morphology and response of HTC cells to the substrate stiffness increase. HTC cells were cultured for 3 days and 5 days on
polyacrylamide gel substrate with Young's moduli varying from 1.1 to 50 kPa. B‐F, Barplot showing the elevated expression level of glaucoma
marker genes by reverse transcription quantitative polymerase chain reaction experiment. Three biological replicates were performed for
each gene in each Substrate Stiffness. Statistical analysis was performed for relative levels between 1.1 and 34.4 kPa. Stars in the figure
represent significant level of P‐value by t‐test (**P< .01; ***P< .001; ****P< .0001)
TIE ET AL. | 5
P ≤ .01 and fold change more than equal to 2 or less
than equal to 0.5, we identified 337 and 142 upregu-
lated and downregulated genes, respectively (Figure
S2; Table S2). These substrate stiffness‐responsive
genes contained 288 mRNAs and 75 were lincRNAs.
GO functional clustering analysis revealed that the
upregulated protein‐coding genes (199) were highly
enriched in the extracellular region (27), proteinaceous
ECM (7), integral to the membrane (57) (Figure 2B and
Table S3). These results were consistent with the
previous findings that the ECM related genes were
involved in the glaucoma disease state.27,29
FIGURE 2 The expression dynamics of glaucoma‐related genes revealed by transcriptome profiles. A, Heat map presentation of
glaucoma‐related genes showing the elevated expression upon increasing the substrate stiffness. Left panel showed the expression pattern in
group A, and the middle panel for group C. Right panel was the combined expression pattern of A and C. B, Bar plot showing the top ten
enriched GO CC terms for genes upregulated in C_50 kPa compared with C_1.1 kPa. C, Bar plot showing the top ten enriched GO BP terms
for genes upregulated in C_50 kPa compared with C_1.1 kPa. D, Linear plot showing the validation of differentially expressed genes by
reverse transcription quantitative polymerase chain reaction (RT‐qPCR) analysis for group C samples. RNA‐seq results (red lines) and
RT‐qPCR results (box plot linked by green lines) were both presented to show the consistency of these two methods. RT‐qPCR was
performed with three biological replicates. P‐values showed in each panel were obtained by one‐way analysis of variance for RT‐qPCR
results
6 | TIE ET AL.
Among the upregulated genes by the elevated substrate
stiffness, six genes enriched in the cell surface receptor
signaling pathway were identified, including AGER, ITPKB,
GIPR, TRPV1, NCAM1, and P2RX7. Genes in regulating cell
proliferation were also significantly enriched (Figure 2C
and Table S3), which is consistent with the reduced cell
proliferation phenotype. Genes that were enriched in the
negative regulation of the cell proliferation included
PTH1R, PODN, CDKN1C, RARRES3, RARRES1, FABP7,
FBXO2, MEG3, PROX1 (P= .0046).
To verify the gene expression alteration generated
from RNA‐seq, the RT‐qPCR experiment was performed
to identify the selected gene expression. We selected nine
genes that showed increased expression levels with
elevated substrate stiffness. Six genes from the nine
tested genes showed good consistency in their expression
dynamics between RNA‐seq and RT‐qPCR in all or part
samples (Figure 2D).
3.3 | Genes responding to substrate
stiffness showed clustered expression
patterns with functionally enriched
pathways
To further characterize the expression dynamics of HTM
cells by elevated substrate stiffness, we identified 2546
and 3616 DEGs in group A and group C by using an
arbitrarily threefold change criterion (FPKM> 0 in every
sample), respectively. Genes from these two groups were
highly overlapped (Figure 3A; P= 6.79e−59, hypergeo-
metric test). Gene expressionclustering analysis could
efficiently identify clusters with similar expression
changes and similar functions. So we performed
K‐means clustering analysis for these DEGs to identify
genes with similar expression patterns. We identified
12 major expression patterns (Figure 3B and 3E),
representing the general trends of genes responding to
the elevated substrate stiffness. Interestingly, in group C,
there were four clusters (Cluster 1 to 4) showing a
sharply increased expression pattern from 34.4 to 50 kPa,
similar to the known glaucoma‐related genes (Figures 3E
and 2A, middle). In contrast, there was only one cluster
(Cluster 9) showing such a sharp increase from 34.4 to
50 kPa. Most of the identified clusters showed different
expression patterns between groups A and C. The
transcriptome difference of these two groups supported
their phenotypic difference shown in Figure 1, implying
that HTM cells grown to different densities respond to
the substrate stiffness differently.
We then performed functional analysis for the clusters
with a sharp increase from 34.4 to 50 kPa, as well as those
clusters with a gradual increase from 2.5 to 50 kPa. In
group A, the 253 genes in cluster 12 gradually increased
with the elevated substratum stiffness, which might
represent a class of substrate stiffness‐responsive genes in
HTM cells. Genes in cluster 12 were enriched in some
transcription and pathology‐related GO terms, including
regulation of transcription, positive regulation of angio-
genesis and blood coagulation, as well as in response to
hypoxia (Figure 3C). The 124 genes in cluster 9 showed a
sharp increase from 34.4 to 50 kPa in group A. Genes in
cluster 9 were also enriched in the regulation of
transcription related terms (Figure 3D).
In group C, genes in cluster 12 (258 genes) were
gradually increased with the elevated substratum stiff-
ness (Figure 3E). Functional enrichment analysis of
genes in cluster 12 also revealed the transcription and cell
proliferation‐related terms (Figure 3F). At the same time,
genes in cluster 1 (471 genes), cluster 3 (290 genes), and
cluster 4 (139 genes) showed a sharp increase when the
substratum stiffness was increased from 34.4 to 50 kPa.
Genes with this expression pattern might represent a
class of genes responding to the elevating stiffness change
under the pathomimetic condition. GO analysis of these
genes in cluster 3 showed terms enriched in ECM
organization, cell adhesion, ECM disassembly, and cell
surface receptor signaling pathway (Figure 3G). GO
terms for genes in cluster 1 and cluster 4 were also
enriched in ECM (Figure S3).
3.4 | Clinical HTM tissues exhibited
upregulated expression of ECM genes
similar to the in vitro HTM cells
To validate the transcriptional changes of HTM cells
cultured in vitro, we obtained several HTM tissues from
patients with glaucoma and sequenced them by RNA‐seq
method. The glaucoma samples in our study include one
patient with primary open‐angle glaucoma, three patients
with chronic angle‐closure glaucoma (CACG), and four
patients with acute angle‐closure glaucoma (AACG). To
have a comparison between glaucomatous and normal
TM cells, we downloaded the transcriptome data from
Carnes et al,25 which minutely describes the transcrip-
tome profile of adult and fetal TM and other tissues by
RNA‐seq. To reduce the experimental error between our
samples and the published control samples, we used
house‐keeping gene GAPDH as an internal control to
normalize the expression profile of each sample. DCN
and CTGF were shown to be strongly upregulated by
elevated substrate stiffness in glaucomatous SC cells15
and in normal HTM cells in Figure 1. After normal-
ization, we found that the decorin (DCN) expression level
was increased 2 to 6 folds in glaucomatous samples
TIE ET AL. | 7
FIGURE 3 Expression profile of protein‐coding genes in human trabecular meshwork cells under stiffness. A, Venn diagram
showing the overlapped differentially expressed genes between A and C group. B, Differentially expressed mRNAs were clustered by
k‐means method and separated into 12 expression patterns from A group samples. The black line represents the mean expression
value of all genes in each cluster. C, Bar plot showing the top ten enriched biological process (BP) terms of cluster 12 in (A).
D, Bar plot showing the top five enriched BP terms of cluster 9 in group A. E, The same as (B) but for the differentially expressed
mRNAs from group C samples. F, G, The same as (C) but for the differentially expressed mRNAs in clusters 12 and 3 from group C
samples
8 | TIE ET AL.
compared with control (Figure 4A, left). Three glauco-
matous samples exhibited a higher expression levels than
control (Figure 4B, right).
We then plotted the expression patterns of all ECM‐
related genes in these samples. The human ECM related
genes (extracellular region and extracellular space) were
retrieved from the GO database. Except for the AACG1
sample, a significant increase was observed in glaucoma-
tous samples compared with normal control (Figure 4B;
P< .01; t‐test). This result was consistent with the behavior
of HTM cells in vitro (Figure 2A). As collagens are the most
abundant protein in the ECM, we systematically analyzed
the expression pattern of all types of collagen encoded
genes. These genes were clearly separated into two main
clusters (Figure 4C). The dominant cluster, which accounts
for 62.79% (27/43) of all expressed collagen genes, showed
obviously elevated expression levels in glaucoma patients
except for AACG1 (Figure 4C). The dominant cluster
includes type I (COL1A1, COL1A2), type III (COL3A1),
type IV (COL4A3, COL4A4, COL4A5, COL4A6), type V
(COL5A1), and type VI (COL6A1, COL6A2, COL6A3)
collagen genes, which are the most common types of
collagen. These results all together suggested that our in
vitro HTM cell model could efficiently mimic the process
from normal to glaucomatous conditions in vitro and
provide an available method to explore the molecular
mechanism of the pathogenesis of glaucoma.
4 | DISCUSSION
Omics technologies have been used to find biomarkers
for clinical treatment and powerfully extend ophthalmic
research in the aspects of molecular mechanisms.42 The
cell model is particularly important for studying the
molecular mechanisms of glaucoma pathogenesis, as well
FIGURE 4 Clinical data of glaucoma patients and normal samples. A, Bar plot showing the expression pattern of DCN and CTGF in
clinical samples. B, Boxplot of the total expressed extracellular matrix genes in clinical samples showing the increased expression level in
patients with glaucoma. C, Heat map presentation of collagen genes in clinical samples
TIE ET AL. | 9
as disease therapies. In this study, we applied the NGS
RNA‐seq method to extend a recently developed cell
model to study the response of HTM cells to the high
substrate stiffness that mimics the in vivo glaucoma state.
Such a global transcriptome profiling approach allowed
us to study the gene expression changes in HTM cells
under elevated substrate stiffness. We showed that gene
expression profiles were greatly altered in response to the
elevated substrate stiffness by adjusting the concentra-
tions of polyacrylamide hydrogels, which mimicked the
compliance of the normal (physiological) HTM and
glaucomatous (pathological) HTM. The ECM‐related
genes were dominantly upregulated in response to the
elevated substrate stiffness, with the most extensive
increase occurring at the transition to the highest
substrate stiffness. To assess the relevance of this finding
with the glaucoma state, we obtained HTM tissues from
patients with glaucoma. RNA‐seq experiment of the
glaucomatous HTM samples confirmed the prevalent
upregulation of ECM‐related genes. These results con-
firmed that the in vitro cell model could efficiently
capture the transcriptomic alteration of TM tissue under
glaucomatous states, which could be widely used in the
study of the molecular pathogenesis of glaucoma in the
future.
In our study, we culturedthe same batch of cells on
the same serials of substrate stiffness under two popula-
tion conditions, the disperse (A) and dense (C), by
culturing for 3 and 5 days, respectively. Besides mimick-
ing Young's moduli 1.1 to 34.4 kPa according to that
reported by Overby et al,15 we increased the Young's
moduli to 50 kPa according to the polyacrylamide
hydrogel condition reported by Wood et al.14 Transcrip-
tome analysis showed that the density of cell population
could greatly influence gene expression response to the
elevated substrate stiffness. The reduced cell density and
elongated and spindle‐shaped morphology were observed
at 34.4 and 50 kPa at dispersing (A) growth condition, but
only observed at 50 kPa at dense (C) growth condition.
Under the dense growth condition, an extensively
upregulated expression of the ECM‐related genes was
observed when the substrate stiffness was shifted from
34.4 to 50 kPa, which did not occur under dispersing
growth conditions. These results have two aspects of the
application. First, the substrate stiffness‐induced expres-
sion of ECM‐related genes depends on adequate cell
density in vitro. Considered that the low cellularity is a
feature of the aged state and the glaucoma state (as
discussed below), the lack of the induction of ECM‐
related genes by substrate stiffness may reflect the
abnormal HCTM response of the change by the substrate
stiffness. Secondly, the substrate stiffness higher than
34.4 kPa could better induce the dysfunction of HTM
cells in vitro. Genes that were remarkably induced from
34.4 to 50 kPa stress may represent potential markers for
early prevention and diagnosis of glaucoma.
It has been reported that the TM from the open‐angled
glaucoma patients contained lower cellularity than normal
samples.43 Interestingly, the age‐regulated depletion of
HTM cellularity is also reported.44 The decreased cell
density at higher substrate stiffness in the in vitro cell model
was consistent with that in the glaucomatous TMs, as well
as in the aging‐related states. Furthermore, we showed that
over a dozen of genes in regulating cell proliferation were
upregulated with the elevated substrate stiffness, including
PTH1R, PODN, CDKN1C, RARRES3, RARRES1, FABP7,
FBXO2, MEG3, PROX1, NTF3, EPGN, HSF4, WNT2,
ST8SIA1, SLC25A27 (Figure 2C and Table S3). Further
exploration of the interconnection between the ECM‐
related genes and the cell proliferation genes should lead
to a more comprehensive understanding of the glaucoma-
tous pathogenesis.
Treatment with corticosteroids leading to ocular
hypertension is linked to the development of steroid‐
induced glaucoma.45 Previous study has shown that
treatment with corticosteroids can stiffen TM in vivo, as
well as the TM cells and matrix in vitro.46 In fact,
glucocorticoid‐induced cross‐linking of actin networks,
reflecting the cell stiffness, has also been reported in
HTM cells.47 Our results demonstrated that the increased
substrate stiffness extensively increased the expression of
ECM‐related genes in HTM cells, indicating the presence
of a cross‐regulation between the stiffness of the cells and
its matrix. Further studies of this cross‐regulation might
lead to the development of new therapeutic strategies to
break the cross‐regulation and relieve the glaucomatous
state.
Extracellular environment plays important roles in
regulating TM normal functions.29,48 Various parts of
the cell, including the ECM, cell membrane, cytoske-
leton, and nucleus, are closely interconnected and
respond together to biomechanical stress.49 Cells in the
HTM tissue play a key role in maintaining the
homeostasis of the IOP.50 However, the study of TM
cells isolated from ocular hypertensive eyes has shown
a compromised ability to execute their daily duties. For
instance, TM cells on a daily basis experience
mechanical stress, such as eye rubbing, squinting,
blinking, ocular pulse and saccades, which could
increase their original dimensions ranging from a
20% to 105%.8 The transcriptome‐wide characterization
of the in vitro cell model in this study underlines the
feasibility of studying the whole cell‐coordinated
response of HTMCs to the biomechanical stress in the
future, which is critical not only for the disease eye
state but also under the physiological eye conditions.
10 | TIE ET AL.
5 | CONCLUSIONS
In summary, the whole‐transcriptome analysis re-
vealed that the normal HTM cells respond to the
substrate stiffness change in our in vitro model can
efficiently capture the expression changes between
the normal and glaucomatous TM tissues. The
extensively induced expression of ECM‐related genes
by elevated substrate stiffness indicated the presence
of an intriguing transcriptional regulation, which
should be studied in the future. The presented
findings not only provided potential markers for the
early prevention and diagnosis of glaucoma but also
could be useful for developing novel anti‐glaucoma
therapies.
ACKNOWLEDGMENTS
The authors thank all the individuals who donated their
eye tissues for this project. Without their support, this
study would not be feasible. The authors also thanks
Ms. Yuting Li and Dr. Shengchun Li for their help in
establishing the cell model. This study was supported by
grants from National Natural Science Foundation of
China (81270994), Sanming Project of Medicine in
Shenzhen (SZSM201812091), Science and Technology
Programs of Shenzhen (GJHZ20190929145402153), and
from Appreciate the Beauty of Life, Incorporation,
Wuhan (201411009).
CONFLICT OF INTERESTS
The authors declare that there are no conflict of interests.
AUTHOR CONTRIBUTION
YZ and JW designed the experiments. XL conducted
the cell model and RT‐qPCR analyses. YZ conducted
the RNA‐seq analysis. JT, DC, JG, and SL analyzed the
data and wrote the paper. RG, CX, and DH collected
the samples. All authors read and approved the final
manuscript.
DATA AVAILABILITY STATEMENT
The raw reads produced in this study were deposited
in the NCBI GEO database with the accession number
GSE123100.
ORCID
Junhong Guo http://orcid.org/0000-0003-2756-1855
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SUPPORTING INFORMATION
Additional supporting information may be found online
in the Supporting Information section.
How to cite this article: Tie J, Chen D, Guo J,
et al. Transcriptome‐wide study of the response of
human trabecular meshwork cells to the substrate
stiffness increase. J Cell Biochem. 2020;1–12.
https://doi.org/10.1002/jcb.29578
12 | TIE ET AL.
https://doi.org/10.1002/jcb.29578