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Theranostics 2020, Vol. 10, Issue 24
http://www.thno.org
10908
Theranostics
2020; 10(24): 10908-10924. doi: 10.7150/thno.48264
Research Paper
Circular RNA circPPM1F modulates M1 macrophage
activation and pancreatic islet inflammation in type 1
diabetes mellitus
Caiyan Zhang1,2#, Xiao Han1,2#, Lan Yang1,2#, Jinrong Fu1#, Chengjun Sun3, Saihua Huang1,2, Wenfeng
Xiao1,2, Yajing Gao1,2, Qiuyan Liang1,2, Xiang Wang1,2, Feihong Luo3, Wei Lu3, Yufeng Zhou1,2
1. Institute of Pediatrics, Children’s Hospital of Fudan University, and the Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of
Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
2. National Health Commission (NHC) Key Laboratory of Neonatal Diseases, Fudan University, Shanghai, China.
3. Department of Pediatric Endocrinology and Inherited Metabolic Diseases, Children’s Hospital of Fudan University, Shanghai, 201102, China.
#These authors contributed equally to this work.
Corresponding author: Yufeng Zhou, M.D., Ph.D., 399 Wanyuan Rd, Minhang, Shanghai 201102, China. Telephone: 86-021-64932907; E-mail: yfzhou1@fudan.edu.cn.
© The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).
See http://ivyspring.com/terms for full terms and conditions.
Received: 2020.05.16; Accepted: 2020.08.21; Published: 2020.08.29
Abstract
Rationale: Macrophages play critical roles in the pathogenesis of type 1 diabetes mellitus (T1DM). Circular
RNAs (circRNAs) are a novel class of endogenous RNAs with covalently closed loop structures, implicated in
various disease processes. However, their impact on macrophage activation and T1DM pathogenesis remains
elusive.
Methods: circRNA expression profiles of peripheral blood mononuclear cells (PBMCs) from T1DM children
were determined by whole transcriptome microarray. Bioinformatics, quantitative real-time PCR, Western
blot, RNA immunoprecipitation (RIP), cell co-culture, cell proliferation, and cell apoptosis assays were
performed to investigate the expression, function, and regulatory mechanisms of circPPM1F in vitro. The
regulatory role of circPPM1F in vivo was evaluated in the streptozocin-induced diabetic mouse model.
Results: We identified 27 upregulated and 31 downregulated differentially expressed circRNAs in T1DM
patients. circPPM1F, a circRNA with unknown function, was dominantly expressed in monocytes and
significantly upregulated in T1DM patients. Functionally, circPPM1F promoted lipopolysaccharide (LPS)-induced
M1 macrophage activation via enhancement of the NF-κB signaling pathway. Mechanistically, circPPM1F
competitively interacted with HuR to impair the translation of protein phosphatase, Mg2+/Mn2+ dependent 1F
(PPM1F), thus alleviating the inhibitory effect of PPM1F on the NF-κB pathway. Moreover, eukaryotic initiation
factor 4A-III (EIF4A3) and fused in sarcoma (FUS) coordinately regulated circPPM1F expression during M1
macrophage activation. In addition, circPPM1F could exacerbate pancreas injury in the streptozocin-induced
diabetic mice by activation of M1 macrophages in vivo.
Conclusions: circPPM1F is a novel positive regulator of M1 macrophage activation through the
circPPM1F-HuR-PPM1F-NF-κB axis. Overexpression of circPPM1F could promote pancreatic islet injury by
enhancing M1 macrophage activation and circPPM1F may serve as a novel potential therapeutic target for T1DM
in children.
Key words: Circular RNA; Type 1 diabetes mellitus; Macrophage activation; RNA-binding protein; Islet injury
Introduction
Type 1 diabetes mellitus (T1DM, also known as
insulin-dependent diabetes) is a chronic autoimmune
disease, driven by the interplay between individual
genetics and environmental triggers [1, 2]. T1DM is
diagnosed at all ages [3, 4], and is characterized by
aberrant autoimmune destruction of pancreatic islet β
cells, resulting in a complete lack of insulin synthesis
and necessitating lifelong hormone replacement
therapy [5]. Recent studies have revealed that a spike
in the incidence of T1DM was found at ages 10–14
Ivyspring
International Publisher
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years, and worldwide estimates of numbers of
children and adolescents with T1DM continue to
increase [6].
Emerging evidence has suggested that,
throughout the immune system, macrophages play a
critical role in insulitis, and support autoimmune T
cells to aggravate the infiltration of inflammatory cells
during T1DM [7]. Macrophages have been classified
as two extreme examples on the activation spectrum:
classically activated macrophages (M1) with a pro-
inflammatory phenotype and alternatively activated
macrophages (M2) with an anti-inflammatory
phenotype. Generally, lipopolysaccharide (LPS) and
interferon (IFN)-γ are the main stimulating factors for
M1 macrophage activation, while interleukin (IL)-4
and IL-13 can activate macrophages to M2 [8, 9].
Notably, M1 macrophage activation drives
pathogenesis and progression of diabetes through
exacerbation of inflammatory responses via secretion
of inflammatory cytokines [10, 11]. For example,
Arnush et al. found M1 macrophages promoted
destruction of β cells in T1DM mice through excessive
production of IL-1β [12]. In addition, Tim-3
exacerbated podocyte injury via M1 macrophage
activation in streptozocin (STZ)-induced diabetic
nephropathy [13]. Importantly, blocking macrophage
infiltration into the pancreas or restraining
macrophage activation in diabetic mice maintained
pancreas function and prevented T1DM initiation [14,
15]. Therefore, elucidating the underlying mechanism
of M1 macrophage activation is likely to lead to a
better understanding of the pathogenesis and therapy
of T1DM.
Circular RNA (circRNA) is a covalently closed
loop molecule ligated by a 3′–5′ phosphodiester bond
at the junction site, which is generated through back-
splicing and often considered to be a byproduct of
aberrant splicing [16, 17]. Recently, high-throughput
sequencing has been used to identify thousands of
endogenous circRNA species in mammalian cells,
which are stable, conserved, and abundant [18, 19]. By
modulation of gene expression, interaction with RNA
binding proteins (RBPs), circRNAs directly or
indirectly participate in autoimmune diseases and
cancers. For instance, circ-RasGEF1B promotes the
antigen presentation process by positively regulating
the stability of intercellular adhesion molecule 1
(ICAM-1) mRNA in macrophages exposed to LPS [20].
Additionally, circZKSCAN1 negatively regulates
cancer stem cells by physically binding fragile X
mental retardation protein (FMRP) against cell cycle
and apoptosis regulator 1 (CCAR1) complex in
hepatocellular carcinoma [21]. However, the roles of
circRNAs in regulating M1 macrophage activation
and T1DM are currently undefined.
In this study, we conducted a genome-wide
analysis of circRNA expression profiles in peripheral
blood mononuclear cells (PBMCs) from T1DM
patients and healthy controls and identified a novel
circRNA, circPPM1F, which was significantly
upregulated in the PBMCs of T1DM patients.
Functionally, circPPM1F could promote LPS-induced
M1 macrophage activation via enhancement of NF-κB
signaling. Mechanistically, circPPM1F competitively
interacted with HuR to impair the translation of
PPM1F, thus alleviating the inhibitory effect of
PPM1F on the NF-κB pathway. Moreover, we found
that EIF4A3 and FUS participated in the maintenance
of high levels of circPPM1F expression. In addition,
circPPM1F could exacerbate pancreas injury in STZ-
induced diabetic mice by activating M1 macrophages.
Overall, our study indicates that circPPM1F plays an
important role in the development of T1DM and
suggests a potential therapeutic target for T1DM.
Materials and Methods
Human study subjects
T1DM patients were diagnosed according to the
criteria of American Diabetes Association (ADA) [22].
Human peripheral blood samples were collected from
T1DM patients (8.5 ± 0.6 y) and age-matched healthy
controls (8.0 ± 1.2 y), following informed consent from
all patients, at the Children′s Hospital of Fudan
University, Shanghai, China. Detailed characteristics
of the study subjects are presented in Table S1. The
study was approved by the Research Ethics Board of
the Children′s Hospital of Fudan University [No.
(2016) 96].
PBMCs were isolated using Ficoll-Hypaque (GE
Healthcare, USA). Briefly, peripheral blood was
mixed with phosphate-buffered saline (PBS) and
overlaid on the Ficoll-Hypaque solution (density:
1.077 g/mL). Following centrifugation at 400 ×g for 30
min, PBMCs were aspirated from the interface. The
cell pellet was washed twice with PBS and
resuspended in TRIzol for subsequent RNA extraction
and quantitative real-time PCR (qRT-PCR). In
addition, CD14+, CD3+, and CD19+ cells were sorted
from PBMCs with a magnetic cell sorting system
(Miltenyi Biotec, Germany). Sorted cells were
subjected to RNA extraction and qRT-PCR.
RNA extraction and quantitative real-time
PCR
The nuclear and cytoplasmic fractions or total
RNA were extracted using TRIzol (Invitrogen, USA)
followed by reverse transcription of mRNAs and
circRNAs using PrimeScript II 1st Strand cDNA
Synthesis Kit (Takara, Japan) according to the
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standard manufacturer′s instructions. A qRT-PCR
assay was performed to measure mRNAs and
circRNAs expression with SYBR® Premix Ex Taq™ II
(Takara, Japan) using the Roche 480 Real Time PCR
System. β-actin served as internal control for mRNAs
and circRNAs. Relative quantification (2−ΔΔCT) was
used for results analysis. The primers sequences in
qRT-PCR are listed in Table S2.
Microarray
The circRNA microarray analysis was performed
at the Shanghai Biotechnology Corporation. In brief,
Total RNA of PBMCs from T1DM patients (n = 4) and
age-matched healthy controls (n = 4) were extracted
and purified followed by amplification and labeling
with a Low Input Quick Amp WT Labeling Kit.
Labeled cRNAs were purified using the RNeasy mini
kit. Each slide was hybridized with 1.65 μg
Cy3-labeled cRNA for 17 h using a gene expression
hybridization kit, and then scanned with an Agilent
microarray scanner using default settings. Data were
extracted with the Feature Extraction software 10.7
(Agilent Technologies, Santa Clara, CA, US). Raw
data were normalized by the Quantile algorithm and
limma package in R. Overall, 88750 circRNAs were
tested.
Cell culture and transfection
The human THP1 cell line was obtained from the
American Type Culture Collection (ATCC, Manassas,
VA, USA), and MIN6 and Raw264.7 cells were
obtained from the Fudan IBS cell resource center
(FDCC, Shanghai, China). THP1 and MIN6 cells were
maintained in RPMI-1640 medium (Gibco,
Gaithersburg, MD, USA) with 10% fetal bovine serum
(FBS, Gibco) and 1% penicillin/streptomycin (Gibco),
and the MIN6 cell culture medium was supplemented
with 50 μM 2-mercaptoethanol. Raw264.7 cells were
maintained in Dulbecco′s modified Eagle′s medium
with high glucose (DMEM, Gibco) supplemented
with 10% FBS. All cells were kept in a humidified cell
incubator with 5% CO2 at 37 °C.
Cells were transiently transfected with
Lipofectamine RNAiMAX reagent (Invitrogen, USA)
and chemically synthesized si-circPPM1F, siPPM1F,
siHuR, siEIF4A3, or siFUS (GenePharma, Shanghai,
China) according to standard protocols. Cells were
transiently transfected with 500 ng/mL ectopic
expression vector of circPPM1F with Lipofectamine
2000 reagent (Invitrogen, USA), according to the
manufacturer’s instructions. qRT-PCR assay was used
to assess RNA expression levels 48 h after
transfection. Relative sequences of siRNA are listed in
Table S3.
For the activation of THP1-derived macrophage,
THP1 cells were treated as previously described [23].
Briefly, THP1 were treated with 500 ng/mL phorbol
12-myristate 13-acetate (PMA) for 48 h to induce the
differentiation of THP1 into macrophages (THP1
macrophages), and then 200 ng/mL LPS was used to
induce M1 macrophage activation.
Western blot
Total protein was extracted using Radio
Immunoprecipitation Assay (RIPA) lysis buffer
(Thermo Scientific, USA). Lysates were resolved by
electrophoresis, transferred to polyvinylidene
fluoride (PVDF) membranes, and probed with
antibodies directed against PPM1F (Abcam); HuR,
phosphorylated NF-κB p65 (Ser536) (p-p65), p65,
phosphorylated p38 (T180/Y182) (p-p38), p38,
phosphorylated JNK (T183/Y185) (p-JNK), JNK,
phosphorylated ERK1/2 (T202/Y204) (p-ERK1/2),
ERK1/2, phosphorylated m-TOR (Ser2448)
(p-mTOR), mTOR, phosphorylated Stat3 (Y705)
(p-Stat3), Stat3, Bcl2 (Cell Signaling Technology,
USA); Bax (EMD Millipore, USA), and β-tubulin
(Abcam, USA). The bands were detected by
developing with chemiluminescent HRP substrate
(Thermo Scientific, USA), and intensity of bands was
determined by imaging with a Molecular Imager®
(Bio-RAD, ChemiDocTM XRS+ Imaging System,
USA). All results were normalized to those of
β-tubulin, which was used as a loading control.
Detailed characteristics of the antibodies are
presented in Table S4.
RNase R digestion
Four micrograms total RNA from THP1 cells
was either untreated (control) or treated with 20 units
of RNase R (Epicenter; USA, RNR07250) in the
presence of 1 × Reaction Buffer, and incubated for 30
min at 37 °C. The digested RNA was isolated using
acid phenol-chloroform (5:1). Then reverse
transcription and qRT-PCR were performed, as
described in the RNA extraction and qRT-PCR
section.
RNA stability
THP1 cells (1 × 105) were placed in 24-well plates
and treated with 250 ng/mL actinomycin D (Act D,
Sigma) added to the cell culture medium. The levels
of circPPM1F and PPM1F were detected at 0, 3, 6, 12,
and 24 h.
Subcellular fractionation and localization
Nuclear and cytosolic fractions were separated
using the Nuclear and Cytoplasmic Extraction Kit
(Cwbio, China). A total of 1 × 107 cells were harvested,
re-suspended in 1 mL of Nc-buffer A and 55 µL
Nc-Buffer B, and incubated for 20 min on ice. Cells
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were then centrifuged for 15 min at 12, 000 ×g; the
resulting supernatants (containing the cytoplasmic
component) and nuclear pellets were used for RNA
extraction.
RNA immunoprecipitation
The RNA immunoprecipitation (RIP) assay was
performed using the Magna RIP RNA-Binding
Protein Immunoprecipitation Kit (EMD Millipore
Corp., Billerica MA, USA). Two 10-cm culture dishes
of THP1 macrophages (1 × 107/dish) were harvested,
centrifuged and re-suspended using 100 μL RIP lysis
buffer supplemented with protease and RNase
inhibitors, and 5 g IgG or HuR antibody-coated
beads were incubated with the cell lysates under
rotary agitation at 4 °C overnight. Following
proteinase K treatment, the immunoprecipitated
RNAs were extracted and reversely transcribed as
described in the RNA extraction and qRT-PCR
section. Levels of circPPM1F and PPM1F were
detected by qRT-PCR assay.
circPPM1F vector construction
3D5 is a modified plasmid based on the pZW1
vector. Two reverse complementary sequences helped
to form a circular structure derived from the POLR2A
gene and were inserted upstream of the restriction site
Xho I and downstream of Pac I. Primer 1 or primer 2
(Table S2) was used to amplify the sequence of
circPPM1F upstream (~340 bp) or downstream (~3800
bp) of cDNA or gDNA. Two PCR segments were
inserted into the 3D5 vector following digestion with
restriction enzymes Xho I and Pac I using a seamless
cloning assay (Figure S1), and the product was
transformed into STBL3 competent cells. The
recombinant vector sequences were validated by
Sanger sequencing.
Conditional media collection and cell
treatment
Raw264.7 cells were seeded in six-well plates,
and transfected with 3D5-circPPM1F, or
corresponding negative control plasmids according to
the cell transfection method used. Next, 48 h post
transfection, the transfected cells were stimulated
with 200 ng/mL LPS for 20 h. Culture media were
gathered and centrifuged at 3000 rpm at 4 °C for 30
min, after which the supernatants (conditional media)
were collected. The conditional media were used for
treatment of MIN6 cells, at a ratio of 3:1 with complete
medium.
Enzyme-linked immunosorbent assay (ELISA)
The protein levels of IL-6 and TNF-α in the
conditional media were measured with the mouse
IL-6 and TNF-α DuoSet ELISA kit (eBioscience)
according to the manufacturer’s instructions. A
microplate reader (Synergy4; BioTek, Winooski, VT,
USA) was used to read the absorbance at 450/570 nm.
Cell proliferation assay
The CCK8 assay was performed to assess the
proliferative ability of MIN6 cells according to the
manufacturer’s instructions (DOJINDO Molecular
Technologies, Inc., Kumamoto, Japan). Briefly, MIN6
cells (1.8 × 103) were placed in 96-well plates and
cultured in conditional medium. Each sample was
assayed in triplicate. Cell viability was determined at
0, 24, 48, and 72 h using 10 μL CCK8 solution
treatment for 2 h. The optical density of each well was
assessed using a Microplate reader (Synergy4; BioTek,
Winooski, VT, USA) at 450 nm.
Cell apoptosis assay
MIN6 cells were cultured in six-well plates (1 ×
105 cells/well) for 48 h using conditional media,
followed by H2O2 (500 μΜ in FBS-free medium)
treatment for 15 h, and then pooled together after
trypsin without EDTA digestion. Cell apoptosis was
analyzed using the Annexin V-FITC/Propidium
Iodide (PI) Apoptosis Detection Kit (BD Pharmingen,
New York, USA, #556547) according to the
manufacturer’s instructions. MIN6 cells were stained
with FITC and PI and then analyzed by
fluorescence-activated cell sorting using FACS Canto
II (BD Biosciences, San Jose, CA, USA). The cell
apoptosis data were analyzed by FlowJo V10 software
(Tree Star, San Francisco, CA, USA). Cells of quadrant
4 that were considered viable were FITC Annexin V
and PI negative; cells of quadrant 3 that were in early
apoptosis were FITC Annexin V positive and PI
negative; cells of quadrant 2 that were in late
apoptosis were both FITC Annexin V and PI positive;
and cells of quadrant 1 that were necrotic were FITC
Annexin V negative and PI positive. The percentages
of cell apoptosis were the sum of that from early
apoptosis and late apoptosis.
Animal studies in the STZ-induced diabetic
mouse model
C57BL/6 mice (8-week-old, male) were
purchased from Shanghai Slac Laboratory Animal Co.
Ltd. All mice were housed at the Experiment Animal
Center of Children′s Hospital of Fudan University at
room temperature 22 °C under a 12:12 h light/dark
cycle, and were provided with rodent chow and tap
water. The mice were randomly divided into four
experimental groups: Control, STZ, STZ+pZW1, and
STZ+circPPM1F group. On day 0, STZ+circPPM1F
and STZ+pZW1 group mice were intraperitoneally
(i.p.) injected with circPPM1F plasmid (8 μg/mouse,
150 μL) and an equal amount of pZW1 using the
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Entranster™-in vivo Transfection Reagent (Engreen,
China), respectively; control and STZ group mice
were injected with PBS. From day one, STZ,
STZ+pZW1, and STZ+circPPM1F group mice were
i.p. injected with repeated low doses of STZ (50
mg/kg body weight/day, 300 μL/mouse for five
consecutive days); control group mice were injected
with sodium citrate buffer (Fankew, FK4006). On day
seven, mice were injected circPPM1F, control
plasmids, or PBS again, and then received two
injections per week. The animal experiments were
repeated independently 3 times.
Body weight was measured weekly from day
one. Blood glucose was also detected weekly from the
tail vein blood using a Roche glucose reader (Roche
Diagnostics GmbH, Germany). All mice were fasted
for 12 h before glucose detection. On day 29, mice
were sacrificed and pancreas tissues dissected and
analyzed for pathology.
This project complied with the institutional
guidelines and laws for the care and use of laboratory
animals. The study was approved and overseen by
the Animal Studies Committee of the Children′s
Hospital of Fudan University [No. (2016) 96].
Immunohistochemistry and
Immunofluorescence studies
Pancreas tissues were fixed with 4%
paraformaldehyde and then embedded in paraffin
and cut into slices. For immunohistochemical
analysis, a portion of paraffin sections were routinely
stained with hematoxylin and eosin (H&E), while
others were incubated with antibodies against Ki-67
(Signalway Antibody, USA), Insulin (Proteintech,
USA), and F4/80 (Cell Signaling Technology, USA).
Islets from consecutive tissue cross-sections were
photographed at identical exposure conditions and
magnification (400×) using a microscope (Leica). For
immunofluorescence analysis, paraffin slides of 3-4
μm were prepared, and then incubated with rabbit
anti-mouse F4/80 and rabbit anti-mouse iNOS
(Servicebio, China). FITC (green) and Cy3
(red)-conjugated goat anti-rabbit IgG (Servicebio)
were used to visualize F4/80 and iNOS, respectively.
DAPI (4′, 6-diamidino-2-phenylindole) was used to
stain the cell nuclei (blue). Images were captured with
a fluorescence microscope (Leica). Detailed
characteristics of the antibodies used are presented in
Table S4.
Preparation of pancreas single cell suspensions
and flow cytometry
Pancreas tissues were collected into the
gentleMACS C Tubes (#130-093-237; Miltenyi Biotec,
Germany) containing the enzyme mix of the Multi
Tissue Dissociation Kit 1 (#130-110-201, Miltenyi
Biotec,Germany) in serum-free RPM-1640 and cut into
2 × 4-mm pieces. Tissues were subjected to the run
program Multi_37C_m (30 min) on the gentleMACS
Octo Dissociator with Heaters (#130-096-427, Miltenyi
Biotec, Germany). The cell suspensions were passed
through a 70-μm MACS SmartStrainer (#130-098-462,
Miltenyi Biotec, Germany), followed by centrifuging
at 300 ×g for 7 min at 4 °C. All isolated cells were
suspended in 100 μL iced PBS supplemented with 2%
FBS. Cells were then counted with trypan blue and
processed for flow cytometry in as indicated below.
For surface marker analysis, cells were stained
with anti-mouse F4/80 (eBioscience, USA) for 30 min
at 4 °C. For intracellular cytokine staining, cells were
fixed and permeabilized and labeled with anti-mouse
iNOS (eBioscience, USA) after anti-F4/80 staining.
The concentration of each antibody was used
according to the recommended product protocol.
Cells were examined by flow cytometry using a BD
FACSCanto II instrument (BD Biosciences, San Jose,
CA, USA) and analyzed with FlowJo V10 software
(Tree Star, San Francisco, CA, USA). Detailed
characteristics of the antibodies used are presented in
Table S4.
Statistical analysis
Results from three independent experiments are
expressed as mean ± standard error of the mean
(SEM). The two-tailed Student’s t-tests were used for
comparisons between two groups, and one-way
analysis of variance (ANOVA) was used for
multifactorial comparisons. A p-value of < 0.05 was
considered statistically significant. The relationship
between circPPM1F and IL-6, IL-1β, TNF-α, EIF4A3 or
FUS was tested using Pearson’s correlation and linear
regression. Statistical analyses were performed with
SPSS v.19.0 software or GraphPad Prism 7.0 software.
Results
circPPM1F was upregulated in PBMCs from
children with type 1 diabetes mellitus
To identify differentially expressed circRNAs in
T1DM, we first analyzed circRNA transcript profiles
of PBMCs from T1DM children (n = 4) and
age-matched healthy controls (n = 4) by circRNA
microarray. Using a two-fold change and p < 0.05 as
the threshold to define up- or down-regulated
circRNAs, we identified 27 upregulated and 31
downregulated differentially expressed circRNAs in
T1DM patients compared with healthy controls
(Figure 1A). We analyzed the composition of the
differentially expressed circRNAs in light of the
positions of circRNAs in the transcripts; the profile
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consisted of 27 exonic circRNAs (47%), three intronic
circRNAs (5%), two exonic-intronic circRNAs (3%), 21
exonic-UTR circRNA (36%), and others (9%) (Figure
1B). Next, we evaluated the expression of 27
upregulated circRNAs in PBMCs from children with
T1DM and healthy control subjects in an expanded
cohort. The results showed that only hsa_circ_0062444,
hsa_circ_0009718 and hsa_circ_0060450 were detectable
and significantly upregulated in PBMCs from T1DM
patients compared with healthy controls (Figure 1C).
Furthermore, higher expression levels of IL-6, IL-1β,
and TNF-α were also observed in T1DM patients
(Figure 1D). Importantly, the positive correlation
between hsa_circ_0062444 and IL-6, IL-1β or TNF-α was
validated in human patients with T1DM, while no
correlations between the hsa_circ_0009718 or
hsa_circ_0060450 and IL-6, IL-1β or TNF-α were
identified (Figure 1E and Figure S2A). Furthermore,
the ability of hsa_circ_0062444 to differentiate T1DM
patients from healthy subjects was assessed by
receiver operating curve (ROC) analysis, which
yielded an area under the curve of 0.839 (Figure 1F).
Together, these findings implied that hsa_circ_0062444
might have important role in T1DM pathogenesis.
Next, bioinformatics analysis showed that
hsa_circ_0062444 was 4291 nt long and was the
back-spliced circular product of the last three exons of
the PPM1F transcript; thus, as an exonic circRNA, it
was named as circPPM1F (Figure 1G). To assess the
role of circPPM1F in the regulation of subsets of
PBMCs, we separated human PBMCs into T cells, B
cells, and monocytes to detect the expression levels of
circPPM1F. Surprisingly, circPPM1F was mainly
expressed in monocytes rather than T and B cells
(Figure S2B). Considering monocytes can transform
into macrophages in inflammatory tissues and
circPPM1F was closely associated with inflammatory
cytokines in T1DM patients, we subsequently focused
on the regulatory role of circPPM1F in LPS-induced
M1 macrophage activation.
circPPM1F promoted M1 macrophage
activation through enhancement of NF-κB
signaling
To verify whether circPPM1F was a truly
circRNA and not a linear RNA, we performed
RT-PCR and Sanger sequencing assays. A strict
concordance between the sequencing results and the
public circPPM1F sequence in circBase (http://www.
circbase.org/cgi-bin/simplesearch.cgi) was observed
(Figure 2A). Furthermore, we found the endogenous
expression of circPPM1F was resistant to excessive
ribonuclease R (RNase R) digestion while linear
mRNAs were severely degraded (Figure 2B).
Additionally, the stability of circPPM1F after Act D
treatment in THP1 macrophages was examined. We
found that circPPM1F was highly stable, with a
half-life > 24 h, whereas PPM1F mRNA was readily
degraded and had a half-life < 6 h (Figure 2C).
Collectively, this evidence suggested that endogenous
circPPM1F was truly a circular RNA.
To determine the functional influence of
circPPM1F on M1 macrophage activation, we first
knocked down the expression of circPPM1F in
THP1-derived macrophages with two small
interfering RNAs (siRNAs) targeting the circPPM1F
junction site; the knockdown efficiency was
confirmed by qRT-PCR and si-circPPM1F-2 was
selected for the later study (Figure 2D). We found the
expression of M1 macrophage associated genes (IL-1β,
TNF-α and CXCL10) was downregulated in the cells
with circPPM1F knockdown after LPS stimulation
(Figure 2E). Meanwhile, the IL-6 and TNF-α protein
expression were suppressed in the supernatant
(Figure 2F). Further, in the “gain-of-function” studies
with ectopically expressing circPPM1F, we found the
expression of IL-1β, TNF-α, and CXCL10 were
upregulated following LPS stimulation (Figure 2G),
concomitant with significantly enhanced IL-6 and
TNF-α protein levels in the supernatant (Figure 2H).
Taken together, these findings suggested that
circPPM1F can promote M1 macrophage activation.
Upon activation, LPS-TLR4 augments
macrophage activity through the production of
inflammatory cytokines, and activation of NF-κB and
MAPK pathways [24]. To explore signaling pathways
involved in circPPM1F regulation of M1 macrophage
activation, we investigated the effects of circPPM1F on
NF-κB and MAPK pathways. Intriguingly, western
blotting showed that circPPM1F knockdown did
indeed result in markedly reduced levels of
phosphorylated p65 in THP1 macrophages, whereas
ectopic expression of circPPM1F significantly
increased the levels of phosphorylated p65. However,
THP1 macrophages with circPPM1F knockdown
exhibited no differences in phosphorylation levels of
JNK, p38, and ERK (Figure 2I-J). Overall, these
findings implied that circPPM1F can promote M1
macrophage activation by enhancing NF-κB signaling.
circPPM1F inhibited PPM1F translation
through competitively binding to HuR
PPM1F, a member of the PP2C family of Ser/Thr
protein phosphatases, is a negative regulator of the
IKK-NF-κB pathway through its effects on the
dephosphorylation of TAK1 [25]. As circPPM1F is the
back-spliced circular product of the coding gene,
PPM1F, and circRNAs have been reported to exert
regulatory effects on host genes at both transcriptional
and post-transcriptional levels [26, 27], we questioned
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whether the effects of circPPM1F on NF-κB signaling
activation were due to its influence on PPM1F
expression. To verify our hypothesis, the levels of
PPM1F protein and mRNA expression were
determined in THP1 macrophages following
circPPM1F knockdown. Surprisingly, knockdown of
circPPM1F resulted in a significant increase of PPM1F
protein expression, with no changes in its mRNA
expression (Figure 3A-B), indicating that circPPM1F
negatively regulated the expression of PPM1F at the
translational stage. Furthermore, we knocked down
the expression of PPM1F in macrophages and found
phosphorylation of p65 and the expression of IL-6,
and CXCL10 were increased following LPS
stimulation (Figure 3C-E). Taken together, these data
implied that circPPM1F suppressed PPM1F
translation, thereby facilitating NF-κB pathway and
M1 macrophage activation.
Figure 1. circPPM1F is upregulated and is associated with inflammatory cytokines in peripheral blood mononuclear cells from type 1 diabetes mellitus
patients. A. Heatmap showing 27 upregulated and 31 downregulated differentially expressed circRNAs in peripheral blood mononuclear cell (PBMC)s of type 1 diabetes
mellitus (T1DM) patients (n = 4) and age-matched healthy controls (n = 4) (fold change > 2.0, p < 0.05). B. Composition of the circRNAs according to the position of the gene
in the transcript. C, D. Analyses of the expression levels of hsa_circ_0062444, hsa_circ_0009718, hsa_circ_0060450, IL-6, IL-1β, and TNF-α (normalized to β-actin) in PBMCs from
43 T1DM patients and 45 healthy controls, as determined by qRT-PCR. E. Correlation analysis of the expression of hsa_circ_0062444 and IL-6, IL-1β or TNF-α in 43 T1DM
patients (Pearson’s correlation). F. Receiver operating curve (ROC) analysis of circPPM1F levels in the study population. G. Schematic illustration showing the location of
hsa_circ_0062444 in host gene PPM1F. Data are presented as mean ± SEM. *p ≤ 0.05, ***p ≤ 0.001.
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Figure 2. circPPM1F promotes M1 macrophage activation by enhancing NF-κB signaling. A. The location of circPPM1F in the PPM1F transcript was validated by
Sanger sequencing. B. Total RNA was digested with or without RNase R, followed by quantitative real-time PCR (qRT-PCR) measurements of circPPM1F, PPM1F, MALAT1, and
GAPDH. C. The stability of circPPM1F was detected by qRT-PCR in THP1 macrophages after actinomycin D (Act D) treatment. D. qRT-PCR analysis of circPPM1F expression
levels in THP1 macrophages following circPPM1F knockdown by two distinct siRNAs. E. qRT-PCR analyses of IL
‐
1β, TNF
‐α
, and CXCL10 in THP1 macrophages with conditional
treatment. Mock-, untransfected, and unstimulated cells; mock+, LPS stimulated alone cells; si-scramble, LPS-stimulated cells following transfection with si-scramble;
si-circPPM1F-2, LPS-stimulated cells following transfection with si-circPPM1F-2. F. ELISA analyses of secreted cytokine levels in THP1 macrophages with circPPM1F knockdown,
followed by LPS treatment. G. qRT-PCR analyses of circPPM1F in THP1 macrophages with 3D5-circPPM1F or pZW1 transfection (left); M1-associated gene expressions in LPS
stimulated THP1 macrophages overexpressing circPPM1F were quantified by qRT-PCR analysis (right). H. ELISA analyses of secreted cytokine levels in circPPM1F-overexpressed
THP1 macrophages, followed by LPS treatment. I. Western blot showing total p65, p38, ERK1/2, JNK and their phosphorylation levels in THP1 macrophages with or without
circPPM1F knockdown after LPS treatment. J. Western blotting analysis to evaluate levels of total p65, phosphorylated p65 in circPPM1F-overexpressed THP1 macrophages. The
levels of p-p65 were normalized to that of β-tubulin and quantified using Image J software. Data are presented as mean ± SEM from three independent experiments. *p ≤ 0.05,
**p ≤ 0.01, ***p ≤ 0.001, ns indicates no significance.
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Figure 3. circPPM1F competitively binds to HuR to impair PPM1F translation. A. Western blotting analysis to evaluate levels of PPM1F in circPPM1F knocked
down-THP1 macrophages. B. qRT-PCR analyses of PPM1F expression in THP1 macrophages with circPPM1F knockdown. C. Analysis of PPM1F expression in THP1 macrophages
transfected with PPM1F siRNA (200 nM) or control siRNA by qRT-PCR. D. Western blot analysis of PPM1F, p65, and p-p65 in THP1 macrophages with PPM1F knockdown,
followed by LPS stimulation. E. Quantitative real-time PCR (qRT-PCR) analysis of M1-associated gene expression in THP1 macrophages with PPM1F knockdown, followed by LPS
stimulation. F. qRT-PCR results showing the distribution of circPPM1F in the cytoplasmic and nuclear fractions of THP1 macrophages. GAPDH as cytoplasm control transcript, and
U1 as nuclear control transcript. G. Putative HuR binding sites within circPPM1F full-length sequence. H. The enrichment levels of circPPM1F and PPM1F in the products of the
RNA immunoprecipitation (RIP) assay (HuR IP compared with IgG IP) as detected by qRT-PCR. I. qRT-PCR analysis of HuR in THP1 macrophages transfected with HuR siRNA
(200 nM) or control siRNA. J. Protein levels of PPM1F and HuR were detected by western blotting in THP1 macrophages with HuR knockdown. K. qRT-PCR analysis of
circPPM1F and PPM1F in THP1 macrophages with HuR knockdown. The levels of PPM1F, p-p65 and HuR were normalized to those of β-tubulin and quantified using Image J
software. Data are presented as mean ± SEM from three independent experiments. *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, ns indicates no significance.
Subcellular localization contributes to the
modulatory mechanism of circRNAs on their targets.
To further explore the mechanism underlying
circPPM1F-mediated effects on PPM1F, we performed
subcellular fractionation and localization assays.
Surprisingly, in contrast to the cytoplasmic
localization observed for a large number of verified
exonic circRNAs, circPPM1F was primarily localized
to the nucleus of THP1 macrophages (Figure 3F).
circRNAs in the nucleus are reported to regulate gene
translation via interaction with RNA-binding proteins
(RBPs). We therefore searched for all putative RBPs
binding to circPPM1F using the circRNA interactome
database (https://circinteractome.nia.nih.gov/
RNA_Binding_Protein/rna_binding_protein.html).
Notably, the analysis revealed that the RBP containing
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the most potential binding sites with the circPPM1F
was HuR (Figure 3G). HuR, a member of the ELAVL
family of RBPs and selectively bind to AU-rich
elements (AREs) within the 3′-untranslated regions
(UTRs) of mRNA, stabilizing ARE-containing mRNA
to regulate gene translation [28]. To determine
whether the interaction between circPPM1F and HuR
was responsible for circPPM1F-mediated translational
inhibition of PPM1F, we conducted RIP using an
antibody specific for HuR and found a 5-fold
enrichment of circPPM1F and 30-fold enrichment of
PPM1F when the anti-HuR antibody was used,
relative to use the IgG control (Figure 3H). These
results thus implied a direct interaction of HuR with
circPPM1F or PPM1F.
Next, we explored whether HuR is involved in
the effects of circPPM1F on PPM1F translation; thus,
siRNA directed at HuR was transfected to knock
down HuR expression in THP1 macrophages. The
knockdown of HuR resulted in a significant decrease
in protein expression of PPM1F in THP1 macrophages
(Figure 3I-J), whereas no changes in circPPM1F and
PPM1F mRNA expression were detected (Figure 3K).
Collectively, these studies strongly suggested that
circPPM1F could suppress PPM1F translation through
competitive interaction with HuR, which
subsequently promotes activation of M1
macrophages.
EIF4A3 and FUS coordinately regulated
circPPM1F expression
Next, we explored the biogenesis of circPPM1F.
Previous studies have shown that the biogenesis of
circRNA depends on the spliceosomal machinery
containing with cis- and trans-regulatory elements.
Reverse intronic complementary sequences (ICS)
induced “head-to-tail” splicing by bringing the 5′- and
3′-termini of an exon or of consecutive exons into
spatial proximity [29, 30]. However, there were no ICS
in either of the intronic flanking regions of the splice
Figure 4. EIF4A3 and FUS cooperatively regulate circPPM1F expression. A, B. Bioinformatic prediction of binding sites of EIF4A3 (A) and FUS (B) on circPPM1F. C.
Expression levels of circPPM1F, EIF4A3, and FUS were detected by quantitative real-time PCR (qRT-PCR) in THP1 macrophages treated with LPS. D. qRT-PCR analyses of the
expression levels of EIF4A3 and FUS in PBMCs from 43 T1DM patients and 45 healthy controls. E. Correlation analysis of the expression of circPPM1F and EIF4A3, or FUS levels
in patients with type 1 diabetes mellitus (T1DM) (Pearson’s correlation). F. qRT-PCR was used to measure the expression levels of EIF4A3 and FUS in THP1 macrophages with
EIF4A3 or FUS knockdown. G. qRT-PCR analyses of the expression levels of circPPM1F in EIF4A3 or FUS
knocked down THP1 macrophages with or without lipopolysaccharide
(LPS) treatment. Data are presented as mean ± SEM from three independent experiments. **p ≤ 0.01, ***p ≤ 0.001, ns indicates no significance.
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junction sites of circPPM1F. Therefore, RBPs might be
responsible for expression of circPPM1F. Using a
bioinformatics method (https://circinteractome.nia.
nih.gov/index.html), we queried all RBPs that were
reported to be involved in circRNA generation. The
result revealed that a binding site for EIF4A3 is
present in the downstream region of the circPPM1F
transcript, and FUS-binding sites were identified in
the mature circPPM1F (Figure 4A-B). We then
measured the levels of circPPM1F, EIF4A3, and FUS
expression over time in THP1 macrophages
stimulated by LPS. Interestingly, FUS exhibited a
time-dependent increased expression following LPS
treatment, while EIF4A3 was upregulated at 3 h after
stimulation, dropped to a basic level at 6 h, and
thereafter was gradually upregulated. circPPM1F was
downregulated at 3 h, but afterward its expression
appeared to be gradually upregulated (Figure 4C).
Furthermore, we analyzed the levels of EIF4A3 and
FUS expression in PBMCs from T1DM patients and
healthy controls. The results indicated that the
expression level of EIF4A3 was significantly
decreased, whereas that of FUS was increased in
T1DM patients compared with healthy controls
(Figure 4D). Importantly, there was a negative
correlation between EIF4A3 and circPPM1F, while a
positive correlation was observed between FUS and
circPPM1F (Figure 4E). The above results implied that
EIF4A3 and FUS may play important roles in
circPPM1F expression.
To further investigate the roles of EIF4A3 and
FUS in circPPM1F expression, we knocked down
EIF4A3 and FUS expression in THP1 macrophages by
transfection with their individual siRNAs (Figure 4F).
Surprisingly, knockdown of EIF4A3 or FUS resulted
in no differences in the expression level of circPPM1F
in THP1 macrophages without LPS treatment.
However, knockdown of EIF4A3 significantly
elevated the expression level of circPPM1F, while
knockdown of FUS decreased its level in THP1
macrophages treated with LPS (Figure 4G). Overall,
these results implied that EIF4A3 and FUS
coordinately regulate circPPM1F expression during
M1 macrophage activation.
circPPM1F induced pancreatic β-cell apoptosis
by promoting M1 macrophage activation in
vitro
To assess the pathological effects of circPPM1F-
induced M1 macrophage activation on pancreatic
β-cells, we performed a cell co-culture assay with
Raw264.7 cells overexpressing circPPM1F and murine
pancreatic β-cells MIN6. Consistent with the mRNA
levels, the IL-6 and TNF-α protein levels were
enhanced in conditional media from Raw264.7 cells
overexpressing circPPM1F (Figure 5A). Notably, we
found that the proliferation rate of MIN6 cells was
significantly inhibited by the conditional media
(Figure 5B). In addition, the media markedly
enhanced the rate of apoptosis in MIN6 cells (Figure
5C). Previous studies have indicated that mTOR and
MAPK pathways are crucial for pancreatic β-cell
Figure 5. circPPM1F induces pancreatic β cell apoptosis through M1 macrophage activation. A.
ELISA analyses of secreted cytokine levels in conditional media
from circPPM1F-overexpressed Raw264.7 cells, followed by LPS treatment. B.
Following incubation with conditional media, cell proliferation of MIN6 cells was assessed by the
CCK-8 assay. C. After the incubation with conditional media, MIN6 cells were stained with Annexin V-FITC and propidium iodide (PI) before fluorescence analys
is by flow
cytometry. The percentage of cells in the four different quadrants was calculated and the results presented in different hist
ograms indicating the fraction of apoptotic cells were
Annexin V+/PI- and Annexin V+/PI+. D. Western blotting analysis to detect expression levels of Bcl2, Bax, p38, p-p38, JNK, p-JNK, ERK1/2, p-ERK1/2, mTOR, and p-
mTOR in
MIN6 cells cultured with conditional media. Data are presented as means ± SEM from three independent experiments. **p ≤ 0.01, ***p ≤ 0.001.
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apoptosis [31, 32]. To investigate the potential
molecular mechanisms inducing MIN6 cell apoptosis,
we confirmed the effects of the conditional media on
mTOR and MAPK pathways in MIN6 cells via
western blotting. Decreased expression levels of Bcl2
and elevated Bax were observed in MIN6 cells
cultured with media from circPPM1F overexpressing
Raw264.7, and this was accompanied by increased
levels of p38 and JNK phosphorylation (Figure 5D).
However, there were no apparent changes in the
phosphorylation levels of mTOR and ERK (Figure
5D). Collectively, these data suggested that
circPPM1F-mediated M1 macrophage activation
could induce pancreatic β cell apoptosis through the
MAPK pathway in vitro.
circPPM1F exacerbated pancreas injury in
STZ-induced diabetic mice through M1
macrophage activation
To assess the role of circPPM1F in pancreas
injury of diabetic mice, we generated a diabetic mouse
model using intraperitoneal (i.p.) injection of STZ
(Figure 6A). We first investigated the dynamic
expression profiles of circPPM1F in the pancreas,
liver, spleen, and PBMCs of mice injected with
circPPM1F or pZW1 plasmid for 3, 5, and 7 days. The
results showed that the level of circPPM1F expression
was highest in pancreas compared with that in the
liver, spleen and PBMCs, and peaked on day 5 (Figure
S3A). Next, successful induction of the diabetic mouse
model was evidenced by significant weight loss one
week after initial injection of STZ, and hyperglycemia
two weeks after the injection. Importantly, the
STZ+circPPM1F group mice achieved more severe
weight reduction and hyperglycemia than STZ or
STZ+pZW1 treated mice groups (Figure 6B). Further,
the levels of circPPM1F and insulin expression in
pancreas tissues were measured. Mice in the
STZ+circPPM1F group displayed significantly
enhanced circPPM1F and decreased insulin expression
in the pancreas compared with the other three groups
(Figure 6C). Furthermore, we assessed the effects of
circPPM1F on pancreatic injury. The expression levels
of inflammatory cytokines, oxidative stress indicators,
indicators related to insulin secretion and cell
apoptosis were detected. Specifically, STZ+circPPM1F
group mice exhibited significantly higher levels of
IL-6, IL-1β, iNOS, and Bax expression, accompanied by
lower levels of Sod, Cat, GSH-Px, Glut2, Gck, and Bcl2
expression, relative to control, STZ, and STZ+pZW1
groups (Figure S3B). Similar to the results in Bcl2 and
Bax at the mRNA level, decreased levels of Bcl2 and
enhanced Bax protein were detected in mice of the
STZ+circPPM1F group compared with those of the
STZ+pZW1 group (Figure S3C).
Pancreatic dysfunction usually represents
pathological changes in the diabetic pancreas.
Notably, Histological analysis showed that STZ and
STZ+pZW1 groups displayed distinctly abnormal
islets structure as compared with the control group,
appearing as small islets, inhomogeneous islet cells,
and cytoplasmic vacuolation. Specifically,
STZ+circPPM1F group mice exerted more severe
damage of islets. Furthermore, Ki-67 staining
indicated decreased proliferation of pancreas cells in
the STZ and STZ+pZW1 groups, and a greater
decrease in the STZ+circPPM1F group, compared
with the control group. In addition, similar to the
mRNA expression patterns observed for insulin in the
experimental mice, protein levels of insulin were
significantly lower in mice overexpressing circPPM1F
(Figure 6D). Altogether, these findings indicated that
circPPM1F could aggravate the pancreas injury of
STZ-induced diabetic mice.
Subsequently, we wanted to examine the
molecular mechanism of pancreas injury. Considering
that the Stat3, MAPK, and Akt-mTOR pathways play
a prominent role in oxidative stress, inflammatory
response, and cell apoptosis [33, 34], we measured the
levels of Stat3, p38/JNK, mTOR and their
corresponding phosphorylated protein expression.
Importantly, the results showed that the mice of the
STZ+circPPM1F group exhibited significantly
enhanced levels of phosphorylated Stat3, p38, and
JNK expression compared with control, STZ and
STZ+pZW1 groups. However, there were no
differences in the phosphorylation levels of mTOR
(Figure 6E). Therefore, these data suggested that
circPPM1F could increase pancreas injury by
activating MAPK and Stat3 pathways in vivo.
In order to further evaluate effects of circPPM1F
on macrophage activation in pancreas islets of
diabetic mice, we assessed the infiltration of
macrophages into islets cells. Compared with control
mice, increased levels of F4/80+ cells were observed in
pancreas islets in STZ and STZ+pZW1 group mice,
and the highest levels of F4/80+ cells were detected in
the STZ+circPPM1F group (Figure 6F). Moreover, to
demonstrate whether circPPM1F promoted
infiltration of macrophages into the islet cells due to
M1 macrophage activation, we detected levels of
F4/80+/iNOS+ cells by immunofluorescence staining.
Notably, elevated levels of F4/80+/iNOS+ cells were
observed in pancreas islets of mice from the
STZ+circPPM1F group compared with that from mice
with or without STZ treatment (Figure 6G). In
addition, the levels of M1 macrophage activation in
the pancreas were validated by flow cytometry.
Similar to the positive patterns of F4/80 and iNOS
observed in immunohistochemistry (IHC) and
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immunofluorescence assays, the STZ+circPPM1F
group mice displayed higher frequencies of
macrophages (F4/80+) and M1 macrophages
(F4/80+/iNOS+) in comparison to the other groups
(Figure 6H). Taken together, these findings implied
that circPPM1F could facilitate injury of pancreatic
islets in diabetic mice by promoting M1 macrophage
activation.
Figure 6. circPPM1F facilitates pancreatic islet injury in diabetic mice through M1 macrophage activation. A. Treatment of circPPM1F in the STZ-induced diabetic
mouse model (15 mice per group). B. Mean weekly body weight (left) and fasting blood glucose (right) change in four-group mice. C. Levels of circPPM1F and insulin in pancreas
tissues were detected by quantitative real-time PCR (qRT-PCR). D. Representative hematoxylin and eosin (H&E)-stained pancreas tissues, immunohistochemistry (IHC) images
of Ki-67 and insulin expression in pancreatic islets from experimental mice. Scale bar indicates 50 µm. Semi-quantification of Ki-67 and insulin staining of per islet were done by
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using Image J software. E. The levels of total p38, JNK, Stat3, mTOR, and their corresponding phosphorylated forms in pancreas tissues from experimental models were
quantified by western blot. F. Representative IHC images of F4/80 expression in pancreatic islets from experimental mice. Scale bar indicates 50 µm. Semi-quantification of F4/80
staining of per islet were done by using Image J software. G. Immunofluorescence staining of infiltrated F4/80+/iNOS+ M1 macrophages in mice pancreatic islets. Green represents
anti-F4/80 Ab; red represents anti-iNOS Ab; yellow represents F4/80 and iNOS merged; blue represents DAPI. Scale bar indicates 50 µm. H. The percentages of M1
macrophages in pancreas tissue cells from STZ-treated mice with or without circPPM1F overexpression and control mice were determined by flow cytometry (left).
Quantification analyses of macrophages (F4/80+) and M1 macrophages (F4/80+/iNOS+) in pancreas tissue cells (right). *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001.
Discussion
In this study, we showed for the first time that
circPPM1F was overexpressed in PBMCs from T1DM
patients, and it increased M1 macrophage activation
through the circPPM1F-HuR-PPM1F-NF-κB axis.
Moreover, EIF4A3 and FUS were critical for
coordinately controlling circPPM1F expression. In
addition, circPPM1F could accelerate pancreatic islet
cell apoptosis in diabetic mice by promoting the
activation of M1 macrophages. Thus, we speculate
that circPPM1F might potential represent a new
therapeutic target for T1DM, adding a new dimension
to the functional importance of circRNA regulation in
diabetes mellitus.
Exonic circRNAs are usually abundant in the
cytoplasm and function mainly through the
microRNA “sponge” mechanism [35]. In contrast,
intron-containing circRNAs (intronic circRNAs and
exon-intron circRNAs), in general, are enriched in the
nucleus and are involved in regulation of host gene
expression [36]. However, Errichelli et al. found that
three completely spliced exonic circRNAs were
almost exclusively located to the nucleus [37].
Consistent with this finding, in our study, as an
exonic circRNA, circPPM1F was also constitutively
expressed in the nucleus rather than in the cytoplasm
of THP1 macrophages. Among the predicted RBPs of
circPPM1F, we found 14 binding sites for fragile X
mental retardation 1 (FMR1, also known as FMRP)
were present in circPPM1F. Interestingly, FMRP
participated in RNA trafficking from the nucleus to
the cytoplasm, displaying different subcellular
distribution due to alternative splicing [38, 39]. We
speculated that FMRP might be responsible for the
nuclear and cytoplasmic localization of circPPM1F. It
would be helpful to investigate the interaction of
FMRP with circPPM1F to better understand the
nuclear location of circPPM1F.
Recently, circRNAs have attracted increasing
attention for their potential roles in regulating
parental gene expression [26, 27]. Meanwhile,
parental genes may also be involved in circRNA
biosynthesis [40]. PPM1F has been reported to
regulate cancer cell growth and metastasis [41],
whereas its roles in the pathogenesis of T1DM and M1
macrophage activation remain unclear. Notably, our
findings provide evidence supporting the hypothesis
that circPPM1F-mediated M1 macrophage activation
may be attributable to reduced protein levels of the
PPM1F gene. Recently, HuR is a well-studied RBP
that positively augments stability of a number of
linear mRNAs and ncRNAs, but also binds to introns
of pre-mRNAs to modulate splicing [28]. It has been
revealed that the interaction of HuR and circPABPN1
impaired the normal interaction of HuR’s with linear
mRNAs, especially parental pre-mRNA of
circPABPN1, which consequently suppressed the
production of PABPN1 protein [42]. Importantly, our
data provide further evidence that HuR is a key
contributor to circPPM1F and PPM1F interactions.
Instead of impacting on circPPM1F transcription, the
interaction with HuR and circPPM1F prevented HuR
binding to PPM1F mRNA, resulting in a reduction of
PPM1F translation. Such a relationship between
circRNA and host mRNA is conceptually intriguing,
and it might be generalizable to other RBPs.
Additionally, our study was the first to reveal the role
of PPM1F in M1 macrophage activation, implying that
the circPPM1F-HuR-PPM1F axis may represent a
novel potential therapeutic target in T1DM.
RBPs are required for regulation of the
biogenesis specific circRNAs in a positive or negative
way. In this study, our data showed that EIF4A3 and
FUS oppositely regulated circPPM1F expression in
response to external stimuli. EIF4A3, a member of the
DEAD box protein family, has been implicated in
nuclear and mitochondrial splicing, ribosome and
spliceosome assembly, and translation initiation.
Recent studies have revealed that EIF4A3 promoted
circMMP9 and circSEPT9 expression via binding to
parental pre-mRNAs [43, 44]. However, in our study
we found that EIF4A3 could inhibit circPPM1F
expression. Unexpectedly, we identified a binding site
for EIF4A3 in the downstream region (i.e., at intron 6
of PPM1F transcript) of circPPM1F. Therefore, we
assume that this unusual binding site might be
responsible for the suppression of EIF4A3 on
circPPM1F biogenesis. In addition, Errichelli et al.
found FUS either increased or repressed circRNA
biogenesis by binding to the introns flanking the
back-splicing junctions, and the interaction machinery
could control a complex interplay between linear and
back-splicing [37]. In contrast to back-splicing
regulation, our data indicated that FUS might also
bind to mature circPPM1F at the post-transcriptional
level and positively mediate its expression upon
stimulation. Overall, these findings demonstrated that
diverse RBPs participate in circRNA biogenesis, and
that some may contribute to diverse regulatory
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10922
mechanisms, even antagonistically. Hopefully, our
study will prompt future work exploring RBP-based
diverse regulation of circRNA biogenesis.
STZ is a broad-spectrum antibiotic possessing
antitumor, oncogenic, and diabetogenic properties,
and multiple small dose injections of STZ in mice
produce pancreatic insulitis, with progression to
nearly complete β-cell destruction and diabetes
mellitus [45]. Although the timing and appearance of
the inflammatory islet lesions do not demonstrate that
STZ stimulation acts by initiating a cell-mediated
immune reaction, multiple low doses of STZ have
been shown to selectively destruct β-cells, which in
turn induces immune reactions against pancreatic
islets, leading to β-cell apoptosis and subsequently
diabetes mellitus. This model resembles the key
features of T1DM patients with a loss of β-cell
function and the development of hyperglycemia
[46-48]. At present, the STZ-induced mouse model is
one of the most widely used animal models of human
autoimmune diabetes in T1DM studies [46, 49-51]. In
our study, we focused the effect of circPPM1F on
development of STZ-induced diabetes mellitus.
Consistent with in vitro studies of increased pancreatic
β-cell apoptosis, we found that circPPM1F-mediated
M1 macrophage activation could also facilitate
pancreas injury in diabetic mice. However, it remains
to be clarified whether macrophage-specific
expression of circPPM1F facilitates the development
of T1DM. Treatment of circPPM1F with a
macrophage-specific promoter in the STZ-treated
NOD mouse model, or generating a chimeric,
macrophage-specific circPPM1F knocked-in T1DM
mouse model would be helpful to address the issue.
In summary, our studies demonstrate the
positive role of circPPM1F in LPS-induced M1
macrophage activation through the circPPM1F-HuR-
PPM1F-NF-κB axis. In vivo, circPPM1F facilitated
pancreas injury in STZ-induced diabetic mice by
promoting M1 macrophage activation. Additionally,
EIF4A3 and FUS might be required for the
maintenance of circPPM1F expression during the
progression of T1DM. Taken together, our work
provides new insights into the pathogenesis of T1DM
and suggests a potential novel biomarker or
therapeutic target for T1DM.
Abbreviations
Act D: actinomycin D; circRNAs: circular RNAs;
EIF4A3: eukaryotic initiation factor 4A-III; FMR1:
fragile X mental retardation 1 (also known as FMRP);
FUS: fused in sarcoma; GEO: Gene Expression
Omnibus; HuR: human antigen R; MAPK: mitogen-
activated protein kinase; NF-κB: nuclear factor kappa
B; mTOR: mammalian target of rapamycin; PPM1F:
protein phosphatase, Mg2+/Mn2+ dependent 1F;
PBMCs: peripheral blood mononuclear cells; qRT-
PCR: quantitative real-time PCR; RBP: RNA-binding
protein; RIP: RNA immunoprecipitation; ROC:
receiver operating curve; siRNA: small interfering
RNA; Stat3: signal transducers and activators of
transcription 3; STZ: streptozocin; T1DM: type 1
diabetes mellitus.
Supplementary Material
Supplementary figures and tables.
http://www.thno.org/v10p10908s1.pdf
Acknowledgments
Availability of data and material
The datasets and computer code produced in
this study are available in the following databases:
circBase (http://www.circbase.org/cgi-bin/
simplesearch.cgi), and circRNA interactome database
(https://circinteractome.nia.nih.gov/RNA_Binding_
Protein/rna_binding_protein.html).
Accession numbers
Microarray data have been deposited in the Gene
Expression Omnibus (GEO) under accession numbers
GSE133225.
Ethics approval and consent to participate
T1DM patients and age-matched healthy
controls were recruited from the Children’s Hospital
of Fudan University following informed consent from
their parents was obtained. The study was approved
by the Research Ethics Board of the Children′s
Hospital of Fudan University [No. (2016) 96].
Funding
This work was supported by grants from the
National Key R&D Program of China
(2016YFC1305102 to YZ), National Natural Science
Foundation of China (81671561, 81974248 to YZ,
81900751 to HX), the International Joint Laboratory
Program of National Children’s Medical Center
(EK1125180109 to YZ), Program for Outstanding
Medical Academic Leader (2019LJ19 to YZ) and
Shanghai Municipal Planning Commission of Science
and Research Fund (201740065 to YZ and 20174Y0079
to HX). Shanghai Pujiang Program (16PJ1401600 to
FJ). Shanghai Committee of Science and Technology
(19ZR1406400 to FJ).
Authors' contributions
CZ, XH, LY, JR, SH, WX, YG, QL and XW
designed and carried out experiments, and analyzed
data. CS, FL and WL recruited and characterized the
human participants. CZ and YZ wrote the
Theranostics 2020, Vol. 10, Issue 24
http://www.thno.org
10923
manuscript. YZ planned, designed, supervised, and
coordinated the overall research efforts.
Competing Interests
The authors have declared that no competing
interest exists.
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