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Research Article
Originally Published 26 July 2018
Free Access

SREBF1/MicroRNA-33b Axis Exhibits Potent Effect on Unstable Atherosclerotic Plaque Formation In Vivo

Arteriosclerosis, Thrombosis, and Vascular Biology

Abstract

Objective—

Atherosclerosis is a common disease caused by a variety of metabolic and inflammatory disturbances. MicroRNA (miR)-33a within SREBF2 (sterol regulatory element-binding factor 2) is a potent target for treatment of atherosclerosis through regulating both aspects; however, the involvement of miR-33b within SREBF1 remains largely unknown. Although their host genes difference could lead to functional divergence of miR-33a/b, we cannot dissect the roles of miR-33a/b in vivo because of lack of miR-33b sequences in mice, unlike human.

Approach and Results—

Here, we analyzed the development of atherosclerosis using miR-33b knock-in humanized mice under apolipoprotein E–deficient background. MiR-33b is prominent both in human and mice on atheroprone condition. MiR-33b reduced serum high-density lipoprotein cholesterol levels and systemic reverse cholesterol transport. MiR-33b knock-in macrophages showed less cholesterol efflux capacity and higher inflammatory state via regulating lipid rafts. Thus, miR-33b promotes vulnerable atherosclerotic plaque formation. Furthermore, bone marrow transplantation experiments strengthen proatherogenic roles of macrophage miR-33b.

Conclusions—

Our data demonstrated critical roles of SREBF1-miR-33b axis on both lipid profiles and macrophage phenotype remodeling and indicate that miR-33b is a promising target for treating atherosclerosis.

Graphical Abstract

Introduction

MicroRNAs (miRs) are small noncoding RNAs, ≈20 to 22 base pairs, which repress translation or promote degradation of target mRNAs by complementarily binding to their 3′ untranslated region. MiR-33a/b are transcribed from the intron of the SREBF (sterol regulatory element-binding factor) 2 and 1 genes, respectively, and have been reported to regulate lipid homeostasis with their host genes.1–3 Antisense inhibition of miR-33 regressed atherosclerotic plaque volume in low-density lipoprotein (Ldl) receptor–deficient mice.4 miR-33a knockout (miR-33−/−) apolipoprotein E–deficient (Apoe−/−) mice also showed a decrease in atherosclerotic plaque formation compared with miR-33+/+Apoe−/− mice.5 Thus, miR-33a within SREBF2 has become a focus of attention as promising targets for treating dyslipidemia and subsequent atherosclerosis.
See accompanying editorial on page 2272
Mammalian SREBP (sterol regulatory element-binding protein) has 3 isoforms: SREBP-1a and SREBP-1c are encoded from a single gene, SREBF1, and SREBP2 are encoded from SREBF2. As with the miR-1/133 genes,6 there are differential regulations of miR-33a/b transcription, as well as SREBFs through their promoters or enhancers. Because mammalian SREBP-1 and SREBP-2 have their preferential roles in fatty acid and cholesterol metabolism, respectively,7 we hypothesized miR-33a/b might have differential roles via their own spatiotemporal regulation, and their pathological importance might be different. Facts that SREBP-1c promoter is highly regulated by both insulin and oxysterols and that steatosis and hypertriglyceridemia associated with elevated hepatic SREBP-1c expression suggest the higher importance of SREBF1-miR-33b axis in metabolic syndrome.
However, functions of miR-33b in vivo especially pathological conditions remain unclear. One of the reasons making it difficult to assess miR-33b functions in vivo is the lack of miR-33b sequences in rodents. Although some groups have confirmed the efficacy of antisense oligos for miR-33a/b on serum lipid homeostasis using primates,8,9 miR-33b functions in atherogenesis in vivo remain largely unknown. Furthermore, miR-33a/b have hundreds of target genes, which might result in unexpected adverse effects in the course of long-term modulation.10,11 Thus, we need to clarify the in vivo roles of Srebf1-miR33b axis. For this purpose, we generated miR-33b knock-in (KI; miR-33b+/+) mice, which have the human miR-33b sequence in the same intron of mouse Srebf1 as in human.12 To elucidate roles of SREBF1/miR-33b axis in atherogenesis, we generated miR-33b+/+Apoe−/− mice and analyzed atherogenesis, including bone marrow transplantation (BMT) experiments, along with human atherosclerotic plaque sample analyses.

Materials and Methods

Human Excised Carotid Endarterectomy Samples

We analyzed the miR-33a/b expression levels in atherosclerotic plaques and their adjacent relatively healthy intima (plaque edge) from carotid endarterectomy specimens. These were obtained from 14 patients who were diagnosed with severe carotid artery stenosis and were underwent carotid endarterectomy at the Department of Neurosurgery, Kyoto University Hospital from 2012 to 2015.

Animals

All the in vivo experiments were performed in C57BL/6J background mice. MiR-33b+/+ mice were generated as reported previously.12 To obtain miR-33b+/+Apoe−/− mice, we mated miR-33b+/+ mice with Apoe−/− mice. MiR-33b−/− or miR-33b−/−Apoe−/− littermates were used as the controls. To assess changes in miR-33a/b expression levels in the liver, miR-33b+/+ and miR-33b+/+Apoe−/− mice at the age of 8 weeks were fed on normal chow containing 4.5% fat (Oriental Yeast, Tokyo, Japan) or a Western-type diet (WTD) containing 0.15% cholesterol and 40% fat (Oriental Yeast) for 2 weeks. To investigate the plaque formation, after being weaned at 4 weeks of age, miR-33b+/+Apoe−/− mice and their control mice were fed normal chow until 6 weeks of age and then switched to WTD for the next 12 weeks. We used male mice for our experiments unless otherwise stated.13

Quantitative PCR for MicroRNAs

Total RNA was isolated using TRIzol reagent (Invitrogen). MiR-33a/b were measured in accordance with the TaqMan MicroRNA Assays (Applied Biosystems) protocol, and the products were analyzed using a thermal cycler (Applied Biosystems StepOnePlus real-time polymerase chain reaction [PCR] system). Samples were normalized by U6 small nuclear RNA expression.

Quantification of Atherosclerosis

Atherosclerotic plaque lesions were quantified by cross-sectional analysis of the proximal aorta.14–16 For the cross-sectional analysis of the aorta, Tissue-Tek OCT compound (Sakura Finetek Japan)–embedded aortas were sectioned using a cryostat, and the 6-μm sections were obtained sequentially beginning at the aortic valve. Eight sections obtained every 24 μm from the aortic sinus were stained with oil red O, hematoxylin-eosin, and picrosirius red stain. The lesion areas of each aorta were measured using ImageJ. The average of the 8 sections from 1 mouse was taken as a value that represented the mouse.

Cell Culture and Reagents

Peritoneal macrophages (PEMs) were obtained from the peritoneal cavity of mice 4 days after the intraperitoneal injection of 3 mL of 3% thioglycollate. The obtained cells were washed, centrifuged at 1000 rpm for 5 minutes, and plated at a density of 8×105 cells/mL with RPMI 1640 medium (Nacalai Tesque, Japan) containing 10% fetal bovine serum (FBS). THP-1 cells were cultured with RPMI 1640 supplemented with 10% FBS. To differentiate THP-1 monocytes into macrophages, cells were treated with 100 nmol/L PMA (phorbol 12-myristate 13-acetate) for 3 days. For cholesterol depletion experiments, cells were precultured in RPMI 1640 with or without 10 mmol/L methyl-β-cyclodextrin for 30 minutes and washed twice with RPMI 1640, followed culturing in RPMI 1640 containing 10% FBS with 10 ng/mL lipopolysaccharides (LPS). The antibodies used were a polyclonal anti–ATP-binding cassette transporter (ABC) A1 antibody (NB400-105), a polyclonal anti-ABCG1 antibody (NB400-132), a polyclonal anti–SR-BI (SCARB1) antibody (NB400-104; Novus Biologicals, Littleton, CO), an anti–single strand DNA antibody (no. 18731; IBL, Gunma, Japan), an anti-CPT1α (carnitine palmitoyltransferase 1A) antibody (ab128568), an anti-CROT (carnitine O-octanoyltransferase) antibody (ab103448), an anti–LDL receptor antibody (ab52818; Abcam, Cambridge, United Kingdom), an anti–β-actin antibody (AC-15; A5441, Sigma-Aldrich, St. Louis, MO), a PE (phycoerythrin)-conjugated anti-CD11b antibody (no. 12-0112; eBioscience, Santa Clara, CA), an APC (allophycocyanin)-conjugated anti-F4/80 antibody (no. 123115; BioLegend, San Diego, CA), and an anti-CD68 antibody (FA-11, Serotec, Kidlington, United Kingdom). Human acetylated LDL (AcLDL) and human HDL-C (high-density lipoprotein cholesterol) were purchased from Biomedical Technologies Inc. (Stoughton, MA). Anti-rabbit and anti-mouse IgG horseradish peroxidase (HRP)–linked antibody were purchased from GE Healthcare (Amersham, United Kingdom). Human apoA-I (apolipoprotein A1), polyethylene glycol, acyl-CoA: cholesterol acyl-transferase inhibitor, and oil red O were purchased from Sigma-Aldrich. [1, 2-3H (N)]-Cholesterol was purchased from Perkin Elmer (Boston, MA).

Immunohistochemistry

Eight sections of the aortic root per mouse were stained with an anti-CD68 antibody (5 μg/mL) and anti–single strand DNA antibody (0.083 μg/mL). The lesion positively stained areas or cells of each aortic were measured using ImageJ. The average of the 8 sections from 1 mouse was taken as a value that represented the mouse.

RNA Extraction and Quantitative Real-Time PCR

Total RNA was isolated and purified using TRIzol reagent (Invitrogen), and cDNA was synthesized from 1 μg of total RNA using Verso cDNA synthesis kit (Thermo Fisher SCIENTIFIC) in accordance with the manufacturer’s instructions. For quantitative real-time PCR, specific genes were amplified by 40 cycles using THUNDERBIRD SYBR qPCR MIX (TOYOBO). Expression was normalized to the housekeeping gene β-actin. Gene-specific primers are summarized in the Table in the online-only Data Supplement.

Western Blotting

Western blotting was performed using standard procedures as described previously.17 A total of 20 μg of protein was fractionated using NuPAGE 4% to 12% Bis-Tris (Invitrogen) gels and transferred to a Protran nitrocellulose transfer membrane (Whatman). The membrane was blocked using 1× PBS containing 5% nonfat milk for 1 hour and incubated with a primary antibody (anti-ABCA1, 1 μg/mL; anti-ABCG1, 1 μg/mL; anti-CPT1a, 1 μg/mL; anti-CROT, 8 μg/m; anti-βactin, 1 μg/mL; anti-SCARB1, 0.5 μg/mL; and anti–LDL receptor, 0.4 μg/mL) overnight at 4°C. After a washing step in PBS-0.05% Tween 20 (0.05% T-PBS), the membrane was incubated with the secondary antibody (anti-rabbit IgG HRP-linked, 1:2000; anti-mouse IgG HRP-linked, 1:2000) for 1 hour at 4°C. The membrane was then washed in 0.05% T-PBS and detected using ECL Western Blotting Detection Reagent (GE Healthcare), using an LAS-4000 system (Fuji Film).

Serum Lipid Profiling

Blood was obtained from the inferior vena cava of anesthetized mice in the early morning without fasting or after a 4 to 6 hours fasting period. Serum was separated by centrifugation at 4°C and stored at −80°C. Biochemical data were measured using standard methods with a Hitachi 7180 Auto Analyzer (Nagahama Life Science Laboratory, Nagahama, Japan). Serum lipoproteins were analyzed using high-performance liquid chromatography (HPLC) methods18,19 (Sky Light Biotech, Akita, Japan).

Cholesterol Efflux via Mouse ApoB-Depleted Serum

Cholesterol efflux via mouse apoB (apolipoprotein B)–depleted serum was measured as described previously.20 Briefly, J774 mouse macrophage cells were plated in 24-well dish (7×104 cells/well) and labeled with 2 μCi/mL 3H-cholesterol for 24 hours in RPMI 1640 with 1% FBS. Cells were incubated in RPMI 1640 containing Cpt-cAMP (0.3 mmol/L) and 0.2% BSA for an additional 16 hours to upregulate ABCA1 in J774 cells. Cells were washed 4× with RPMI 1640 and incubated for 4 hours in MEM-HEPES containing 2.8% apoB-depleted serum (equivalent to 2% serum), which was obtained after apoB lipoproteins were removed with polyethylene glycol. All steps were performed in the presence of acyl-CoA: cholesterol acyl-transferase inhibitor (2 μg/mL). Cholesterol efflux was expressed as the percentage of radioactivity released from the cells in the medium relative to the total radioactivity in cells plus medium.

Measurement of Reverse Cholesterol Transport In Vivo

PEMs from miR-33b−/−Apoe−/− mice were seeded at a density of 1.2×106/mL in a 100 mm dish, incubated for 1 hour, and washed with PBS. After 4-hour incubation, cells were washed twice with PBS and incubated for another 24 hours with labeling RPMI 1640 medium containing 0.1 mg/mL AcLDL and 5 μCi/mL 3H-cholesterol. Cells were dissociated using Accutase (M&S TechnoSystems, Japan) followed by suspension in cold PBS. Each mouse was administered 500 μL of cell suspension intraperitoneally. Serum samples were collected at 6 and 24 hours after administration via the orbital sinus. Forty-eight hours after administration, we dissected the mice and collected serum, liver, bile, and all feces during the experiment. Liver samples were cut and then crushed using a BioMasher I (Nippi, Incorporated, Japan). After adding 500 μL hexane-isopropanol solution, crushed liver samples were centrifuged at 15 000 rpm for 3 minutes. Supernatants were moved to new tube and then a 30% volume of 0.47 mol/L Na2SO4 was applied. After shaking intensely for 1 minute, they were centrifuged and only upper layer was collected for measurement.
Feces samples were homogenized with 10 mL/g-feces water and incubated at 4°C over night. Then, an equal volume of ethanol was added and mixed.
All serum, liver, bile, and feces samples were counted their radioactivity by liquid scintillation counting. Part of 3H-cholesterol–labeled macrophage suspension in each experiment was used to measure the input value. Raw serum, liver, and feces radioactivity values were adjusted for the total individual values based on the body weight, the ratio of sampling liver weight to entire liver weight, and the whole amount of feces during experimental period, respectively. Full bile samples from each mouse were used for counting their raw radioactivity values. The percentages of macrophage-derived 3H-cholesterol in each specimen were calculated by dividing each estimated (serum, liver, and feces) or raw (bile) total individual value by the input value.

Measurement of Intestinal Chylomicron Production

Mice aged 6 to 8 weeks old were fed WTD for 2 weeks. After a 4-hour fasting period, mice were injected with 500 mg/kg Triton WR-1339 (Tyloxapol, Sigma) via the postorbital vein to block lipolysis and hepatic VLDL (very-low-density lipoprotein) uptake. Mice were challenged with a bolus of 200 μL of olive oil by intragastric gavage 15 minutes after Triton WR-1339 injection. Blood samples for measuring triglyceride (TG) concentration were obtained from the opposite postorbital vein at 0, 1, 2, and 3 hours after olive oil administration. Serum TG levels were measured as described above. Intestinal chylomicron production rates were estimated using linear regression for serial TG data from each mouse.

Measurement of Hepatic TG Secretion

Mice aged 6 to 8 weeks old were fed WTD for 2 weeks. After a 4-hour fasting period, mice were injected with 500 mg/kg Triton WR-1339 (Tyloxapol, Sigma) via the postorbital vein to block lipolysis and hepatic VLDL uptake. No food was available during the time course. Blood samples for measuring TG concentration were obtained from the opposite postorbital vein at 0, 30, 60, 90, and 120 minutes after Triton WR-1339 administration. Serum TG levels were measured as described above. Hepatic TG production rates were estimated using linear regression for serial TG data from each mouse.

Measurement of Lipoprotein Lipase Activity

Mice aged 6 to 8 weeks old were fed WTD for 3 weeks. After a 4-hour fasting period, mice were injected the 0.2 U/g heparin intravenously. Blood was obtained before and 10 minutes after heparin injection for the measurement of serum lipoprotein lipase (LPL) activity using an LPL activity assay kit (Cell Biolab no. STA-610) in accordance with the manufacturer’s instructions.

Cholesterol Efflux From Mouse PEMs

Cellular cholesterol efflux via apoA-1 and HDL was determined as described previously.3,21 Briefly, thioglycollate-elicited mouse PEMs were plated in 24-well dishes (5×106 cells/mL) and were cultured for 24 hours in RPMI 1640 containing 3H-labeled AcLDL (1.0 μCi/mL 3H-cholesterol and 25 μg/mL of AcLDL). Cells were washed 4× with RPMI 1640 and then incubated for 6 hours in RPMI 1640 with or without 10 μg/mL apoA-1 and 100 μg/mL HDL. Cholesterol efflux was expressed as a percentage of radioactivity released from the cells into the medium relative to the total radioactivity in the cells and medium.

Apoptosis Assay

Thioglycollate-elicited PEMs from miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− mice were incubated with RPMI 1640 containing 10% FBS supplemented with or without 300 μg/mL AcLDL plus 10 μg/mL acyl-CoA: cholesterol acyl-transferase inhibitor (58-035) for 24 hours. To assess early-to-mid-stage apoptosis, cells were stained with Alexa Fluor 488–conjugated Annexin V (green) and DAPI (4’,6-diamidino-2-phenylindole; blue), as described previously,22 using a Vybrant Apoptosis Assay Kit (Molecular Probes). We counted the number of Annexin V–positive cells from representative fields (8–9 fields containing ≈650–1000 cells) and expressed as a percentage of the total number of cells.

Lipid Raft Staining

To investigate an amount of lipid rafts, we used fluorescein isothiocyanate (FITC)-cholera toxin subunit B (CTB; Sigma, C1655) for labeling. Thioglycollate-elicited PEMs were prestained by PE-conjugated anti-CD11b antibody (1.25 μg/mL) and APC-conjugated anti-F4/80 antibody (2.5 μg/mL) to confirm cells as macrophages and followed by being stained with FITC-CTB at 4°C for 15 minutes. To quantify lipid rafts, we measured the signal intensity of FITC-CTB using a BD FACSAriaII (Becton Dickinson). THP-1 macrophages infected with miR-control or miR-33b by lentivirus vector were collected with or without 10 mmol/L methyl-β-cyclodextrin pre-treatment for 2 hours. Afterward, cells were stained with FITC-CTB and measured their FITC signals using BD FACSAriaII.

Lentivirus Production and DNA Transduction

We produced lentiviral stocks in 293FT cells in accordance with the manufacturer’s protocol (Invitrogen). In brief, virus-containing medium was collected 48 hours post-transfection and filtered through a 0.45-μm filter. One round of lentiviral infection was performed by replacing the medium with virus-containing medium (containing 8 μg/mL of Polybrene), followed by centrifugation at 2500 rpm for 30 minutes at 32°C. Cells were used for analysis 3 days after DNA transduction.

Bone Marrow Transplantation

BMT experiments were performed using the same protocol as reported previously.5 Male, 8-week-old age mice with genotypes of miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− were used as bone marrow (BM) donors. BM recipients were 8-week-old female miR-33b−/−Apoe−/− mice and miR-33b+/+Apoe−/− mice. All mice used for BMT had an Apoe−/− background. BM donors were euthanized by cervical dislocation, and BM cells were collected by flushing femurs and tibias with PBS supplemented with 3% FBS. The suspension was passed through 40 μm nylon mesh cell strainer (BD Biosciences). Red blood cells were lysed using ACK (ammonium-chloride-potassium) lysing buffer (Lonza). BM cells were then washed twice with PBS supplemented with 3% FBS. To induce BM aplasia, recipients were irradiated with twice of 6 Gy within an interval of 3 hours (Cs137; Gammacell 40 Exactor) and injected intravenously with 5×106 BM cells 6 hours after irradiation.23,24 After BMT, mice were fed normal chow diet for 4 weeks and then switched to a WTD for 10 weeks. At 22 weeks old, mice were euthanized and analyzed. Successful hematopoietic reconstitution after BMT was confirmed by PCR amplification of the whole-blood genome and tail genome at the time of euthanization.

Analyses of Predicted Target Genes Using an In Silico Database

We obtained the data about target genes for miR-33a/b-5p from TargetScan Human/Mouse release 7.125 and subsequent division of these genes into 3 distinctive groups: target genes that only exist in mouse, those only in human, and those in both mouse and human. Afterward, we analyzed the enriched KEGG pathways in each of the 3 groups using R clusterProfiler package.26

Statistics

Measurements are presented as means±SEM. Statistical comparisons were performed using paired or unpaired 2-tailed Student t-tests, Mann-Whitney test, a 1-way ANOVA with the Tukey post hoc test, or Kurskal-Wallis test with post hoc Dunn test where appropriate, with a P<0.05 taken to indicate significance. Parametric tests (such as t test) and nonparametric tests (such as Mann-Whitney test) were performed based on whether data passed the normality and equal variance tests. Statistical analyses were performed using GraphPad Prism 6 (GraphPad Software, Inc).

Study Approval

When we collect human carotid artery samples, informed consent was given by all patients or their families in accordance with the Declaration of Helsinki. Participants are identified by number, not by name. The Institutional Review Board of Kyoto University Graduate School and Faculty of Medicine approved this study.
The Ethics Committee for Animal Experiments of Kyoto University approved all animal experimental protocols.

Results

Expression Levels of MiR-33a/b Are Differentially Regulated in Atheroprone Conditions Both in Human and MiR-33b KI Mice

SREBF2/1 are expressed ubiquitously and transcriptionally regulate cholesterol and fatty acid homeostasis, respectively.27 MiR-33a/b are transcribed from and with SREBF2/1, respectively.1–3 We measured miR-33a/b expression levels in human plaque and adjacent relatively healthy intima using carotid endarterectomy specimens (Table 1). As a result, miR-33a expression levels were significantly repressed in the plaque area compared with those in the adjacent area. MiR-33b expression levels also tended to decrease in plaque area, but this was not significant (Figure 1A). Next, to elucidate the expression levels of miR-33a/b and their host genes in the livers with an atheroprone diet, we used miR-33b KI humanized mice. Expression levels of miR-33b and Srebf1 were significantly increased with a WTD, however, those of miR-33a and Srebf2 were decreased in the same conditions (Figure 1B). At the same time, the expression levels of miR-33b in liver is much higher than those of miR-33a (Figure IA in the online-only Data Supplement). MiR-33b is a much more prominent member of the miR-33 family in atheroprone conditions.
Table 1. Characteristics of Patients Who Underwent Carotid Endarterectomy
Patient CharacteristicsCohort
No. of subjects14
Men13
Mean age74.9 (63–82)
Past medical history
 Stroke/transient ischemic attack12 (86%)
 Coronary artery disease9 (64%)
 Peripheral artery disease2 (14%)
 Thoracic/abdominal aortic aneurysm3 (21%)
Laboratory data
 Total cholesterol, mg/dL155 (100–215)
 AST, IU18.4 (13.0–38.0)
 ALT, IU15.3 (8.0–32.0)
 BUN, mg/dL16.9 (10.0–47.0)
 Cre, mg/dL1.09 (0.70–2.59)
 Hb, g/dL13.0 (11.3–15.3)
Drugs
 Antiplatelet14 (100%)
 Statin11 (79%)
 ACEi/ARB8 (57%)
 β-Blocker3 (21%)
 Ca blocker5 (36%)
 Diuretics4 (29%)
 Antidiabetes mellitus5 (36%)
ACEi/ARB indicates angiotensin-converting enzyme inhibitor/angiotensin receptor blocker; ALT, alanine aminotransferase; AST, aspartate transaminase; BUN, blood urea nitrogen; Cre, creatinine; and Hb, hemoglobin.
Figure 1. Expression levels of microRNA (miR)-33a/b are differentially regulated in atheroprone conditions both in human and miR-33b knock-in (KI) mice. A, Expression levels of miR-33a (right) and miR-33b (left) in human atherosclerotic plaques () and adjacent plaque edge area (). Atherosclerotic plaques and their adjacent edge area were obtained by carotid endarterectomy (n=14). *P<0.05, plaque edge vs plaque, paired t test. B, Expression levels of miR-33a (upper-right), miR-33b (upper-left), and their host genes, Srebf2 (lower-right) and Srebf1 (lower-left) in livers of miR-33b KI mice with normal chow (NC) feeding and 2-wk Western-type diet (WTD) feeding conditions at the age of 8 wk. Values are mean±SEM (NC, n=5; WTD, n=5). *P<0.05, **P<0.01 vs NC, Mann-Whitney test.

MiR-33b KI Promotes Vulnerable Atherosclerotic Plaque Formation

To clarify the role of miR-33b in atherogenesis, we generated miR-33b+/+Apoe−/− mice and fed them a WTD for 12 weeks. There are no significant differences in hepatic miR-33a/b and their host genes expression levels between miR-33b+/+ mice and miR-33b+/+Apoe−/− mice (Figure IA and IB in the online-only Data Supplement). MiR-33b KI has little effect on expression levels of Srebf2/miR-33a under the background of Apoe−/− mice (Figure IC in the online-only Data Supplement). MiR-33b+/+Apoe−/− mice were born with the expected Mendelian ratios and were viable and fertile. MiR-33b+/+Apoe−/− mice gained less weight compared with miR-33b−/−Apoe−/− mice (miR-33b−/−Apoe−/− 40.23 g versus miR-33b+/+Apoe−/− 34.63 g; P<0.0001; n=25–32). Although we previously reported on the diet consumption of miR-33−/− mice fed a high-fat diet,10 miR-33b+/+Apoe−/− mice showed a decrease in food intake with WTD feeding (miR-33b−/−Apoe−/− 20.92 g/week per mouse versus miR-33b+/+Apoe−/− 19.40 g/week per mouse; P=0.001; n=13–23). The resultant atherosclerotic plaque area was significantly larger in miR-33b+/+Apoe−/− mice (Figure 2A and 2B). We found a greater hematoxylin-eosin–free area in plaques from miR-33b+/+Apoe−/− mice, which indicated that plaques in miR-33b+/+Apoe−/− mice contained larger necrotic core areas and more cholesterol crystals compared with those in miR-33b−/−Apoe−/− mice (Figure 2C and 2D). Next, we analyzed the infiltration of macrophages, the degree of fibrosis, and the number of apoptotic cells. As a result, a larger number of macrophages infiltrated into plaques in miR-33b+/+Apoe−/− mice than in miR-33b−/−Apoe−/− mice (Figure 2E and 2F). Fibrotic areas in plaques were smaller in miR-33b+/+Apoe−/− mice than those in miR-33b−/−Apoe−/− mice (Figure 2G and 2H). In addition, the number of apoptotic cells in plaques of miR-33b+/+Apoe−/− mice was significantly larger compared with miR-33b−/−Apoe−/− mice (Figure 2I and 2J). These data indicated that Srebf1-miR-33b axis promote the development of a so-called unstable plaque.
Figure 2. MicroRNA (miR)-33b promotes vulnerable atherosclerotic plaque formation. A, Representative microscopic images of cross-sections at proximal aorta level in miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− mice. Images in the lower row are enlarged images from the boxed area in each upper image. Scale bar, 500 μm (top) and 200 μm (bottom). B, Quantification of the atherosclerotic plaque area in cross-sections at proximal aorta level (n=10). C, Representative microscopic images of hematoxylin-eosin staining for assessing necrotic core and cholesterol crystals at proximal aorta level. Scale bar, 200 μm. D, Quantification of the necrotic core and cholesterol crystal area in cross-sections at proximal aorta level (n=10). E, Representative microscopic images of immunohistochemical staining for the macrophage marker CD68. Scale bars, 200 μm. F, Quantification of the CD68-positive area in cross-sections at proximal aorta (n=10). G, Representative microscopic images of picrosirius red staining for collagen in plaques. Scale bars, 100 μm. H, Quantification of the picrosirius red-positive area in cross-sections at proximal aorta (n=10). I, Representative microscopic images of immunohistochemical staining for the apoptosis marker single strand DNA (ssDNA). Arrowheads show ssDNA-positive cells. Scale bars, 100 μm. J, Quantification of ssDNA-positive cells in cross-sections at proximal aorta (n=10). Values are mean±SEM. *P<0.05 and **P<0.01, Mann-Whitney test (B, D, F, H, J). Apoe−/− indicates apolipoprotein E–deficient.

Decreased Serum HDL-C Levels With Less Cholesterol Efflux Capacity Leads to Repression of Systemic Reverse Cholesterol Transport in MiR-33b+/+Apoe−/− Mice

As shown in Figure 3A, the expression levels of miR-33b were significantly increased, and on the contrary, those of miR-33a were decreased in the livers of miR-33b+/+Apoe−/− mice fed on WTD as with miR-33b+/+ mice (Figure 1B). These data indicated that miR-33a/b are differentially regulated in the livers after WTD feeding and suggested that miR-33b could have stronger repressive effects on target genes than miR-33a in such an atheroprone context. To determine whether miR-33b has additional repressive effects on hepatic target genes of miR-33a or not, we measured hepatic ABCA1, CPT1a, and CROT mRNA and protein levels as representative target genes after 12 weeks WTD feeding. We found further repression of ABCA1 and CROT at both the mRNA and protein levels in the livers of miR-33b+/−Apoe−/− and miR-33b+/+Apoe−/− mice, except for CPT1A (Figure 3B and 3C). The additive repressive effect of miR-33b on ABCA1 protein levels was also confirmed in small intestines (Figure IIIA and IIIB in the online-only Data Supplement). As a result, serum HDL-C levels were significantly decreased in miR-33b+/+Apoe−/− mice compared with miR-33b−/−Apoe−/− mice (Figure 3D). Although we reported that miR-33−/− mice showed fatty liver when they were fed a high-fat diet or were old,10 there were no significant differences in liver histology (Figure IIIC in the online-only Data Supplement) or serum liver enzymes (data not shown) between miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− mice at the age of 6 to 8 weeks. Next, we examined the cholesterol efflux capacity of serum HDL and found that the cholesterol efflux capacity of apoB-depleted serum was significantly attenuated in miR-33b+/+Apoe−/− mice compared with miR-33b−/−Apoe−/− mice (Figure 3E). In addition to in vitro cholesterol efflux experiments, systemic reverse cholesterol transport (RCT) measured by tracing 3H-labeled cholesterol was significantly repressed in miR-33b+/+Apoe−/− mice (Figure 3F). There are no significant differences in both mRNA and protein levels of hepatic SCARB1 which have potential contribution to RCT (Figure IVA and IVB in the online-only Data Supplement). These results indicated that Srebf1-miR-33b axis significantly reduces serum HDL-C levels via repressing both liver and small intestine ABCA1 levels and represses systemic RCT.
Figure 3. Decreased serum high-density lipoprotein cholesterol (HDL-C) levels with less cholesterol efflux capacity leads to repression of systemic reverse cholesterol transport in microRNA (miR)-33b+/+Apoe−/− mice. A, Expression levels of miR-33a (right) and miR-33b (left) in livers of miR-33b+/+Apoe−/− mice after 12 wk of being fed a Western-type diet (WTD; 8W_normal chow [NC], n=7; 18W_WTD, n=9). B, Quantitative real-time polymerase chain reaction analysis of Abca1, Cpt1a (carnitine palmitoyltransferase 1A), and Crot (carnitine O-octanoyltransferase) in livers from miR-33b−/−Apoe−/−, miR-33b+/Apoe−/−, and microRNA-33b+/+Apoe−/− mice. Values from miR-33b−/−Apoe−/− mice were set at 1 (n=7 each). C, Western blotting analysis of ABCA1, CPT1a, and CROT expression in livers from miR-33b−/−Apoe−/−, miR-33b+/Apoe−/−, and miR-33b+/+Apoe−/− mice. Representative images from independent several experiments are shown. β-Actin was used as the loading control (left). Densitometry of hepatic ABCA1, CPT1a, and CROT (right). Values from miR-33b−/−Apoe−/− mice were set at 1 (n=3 each). D, Serum total cholesterol, HDL-C, low-density lipoprotein cholesterol (LDL-C), LDL-C/HDL-C ratio, triglyceride (TG), and glucose levels determined by standard methods. Serum samples were collected from 18-wk-old male mice fed a WTD after 4 to 6 h fasting (miR-33b−/−Apoe−/−, n=8; miR-33b+/+Apoe−/−, n=10). E, Cholesterol efflux via apoB-depleted serum from miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− mice using 3H-cholesterol-labeled J774 mouse macrophages (n=13 each). F, Reverse cholesterol transport rates measured in serum at 6, 24, and 48 h after 3H-cholesterol loaded macrophages by intraperitoneal administration (left). Those measured in liver, bile from the gallbladder, and feces at the time of euthanasia (n=12–16). Values are the means±SEM. *P<0.05, **P<0.01, ***P<0.001, and ****P<0.0001, Mann-Whitney test (A, D, E, F), Kruskal-Wallis test with post hoc Dunn test (B), and 1-way ANOVA with post hoc Tukey test (C). Apoe−/− indicates apolipoprotein E–deficient.

MiR-33b+/+Apoe−/− Mice Show a Higher Ratio of Serum LDL-C to HDL-C and Lower Serum TG via Repression of Intestinal Absorption

We found serum TG levels in miR-33b+/+Apoe−/− mice were lower than those in miR-33b−/−Apoe−/− mice. Moreover, we found a higher ratio of serum LDL cholesterol (LDL-C) to HDL-C in miR-33b+/+Apoe−/− mice (Figure 3D). To further investigate serum lipoprotein profiles, we performed analyses using HPLC. HPLC analysis for cholesterol content showed a decreased peak in the HDL-C fraction in miR-33b+/+Apoe−/− mice and decreased cholesterol levels in the chylomicron fraction and a peak shift from the large VLDL fraction to small LDL fraction. In addition, HPLC analysis of TG content showed that TG levels were reduced especially in the chylomicron and VLDL fractions in miR-33b+/+Apoe−/− mice (Figure 4A; Table 2).
Table 2. Serum Lipid Profiling of miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− Mice by HPLC
LipoproteinSubclass (Fraction No.)miR-33b−/−Apoe−/− n=5miR-33b+/+Apoe−/− n=5 
Major, Diameter
Total cholesterol 1154±86.1962.2±68.6 
 Chylomicron, >80 nm 178.4±14.7110.1±14.9*
 VLDL, 30–80 nm 755.1±72.7580.5±52.4 
Large VLDL (3–5)472.6±41.7327.9±36.5*
Medium VLDL (6)213.8±26.2179.3±14.7 
Small VLDL (7)68.65±7.1373.24±7.12 
 LDL, 16–30 nm 190.7±12.4259.6±34.9 
Large LDL (8)77.82±6.8391.92±10.7 
Medium LDL (9)55.30±3.9382.44±12.9 
Small LDL (10)32.59±1.7553.61±8.16*
Very small LDL (11–13)21.01±1.0731.67±3.73 
 HDL, 8–16 nm 30.15±2.3412.00±0.98
Very large HDL (14–15)4.89±0.163.10±0.10
Large HDL (16)6.45±0.662.25±0.23
Medium HDL (17)10.48±1.133.19±0.52
Small HDL (18)3.75±0.331.46±0.14
Very small HDL (19–20)4.58±0.352.01±0.37
Triglyceride 114.0±26.139.39±4.76*
Apoe−/− indicates apolipoprotein E–deficient; HDL, high-density lipoprotein; HPLC, high-performance liquid chromatography; LDL, low-density lipoprotein; miR, microRNA; and VLDL, very-low-density lipoprotein.
*
P<0.05, †P<0.0001, and ‡P<0.001 compared with miR-33b−/−Apoe−/− mice, by Student t test.
Figure 4. MicroRNA (miR)-33b+/+Apoe−/− mice show a higher ratio of serum low-density lipoprotein cholesterol (LDL-C) to high-density lipoprotein cholesterol (HDL-C) and lower serum triglyceride (TG) via repression of intestinal absorption. A, Representative high-performance liquid chromatography analysis of serum cholesterol and TG from miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− mice. B, Intestinal TG secretion rates in miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− mice. Mice fasted for 4 to 6 h were injected intravenously with Triton WR-1339 and after gavage with olive oil. Plasma was collected at 0, 1, 2, and 3 h after gavage with olive oil (miR-33b−/−Apoe−/−, n=10; miR-33b+/+Apoe−/−, n=12). *P<0.05, Mann-Whitney test. C, Hepatic TG production rates in miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− mice. These mice fasted for 4 to 6 h were injected with Triton WR-1339 intravenously. Plasma was collected at 0, 30, 60, 90, and 120 min after injection (miR-33b−/−Apoe−/−, n=4; miR-33b+/+Apoe−/−, n=7). D, Serum lipoprotein lipase (LPL) activity was measured before and 10 min after intravenous heparin injection. Values from miR-33b−/−Apoe−/− mice before heparin treatment were set at 1 (n=5 each). Values are means±SEM (B, C, D). Apoe−/− indicates apolipoprotein E–deficient; CM, chylomicron; and VLDL, very-low-density lipoprotein.
Serum TG levels reflected the balance among production by the small intestine and the liver and clearance by peripheral organs and tissues.28,29 Using Triton WR-1339, which inhibits LPL activity, we measured the lipid absorption after chylomicron-TG production from the small intestine and hepatic VLDL-TG production. As a result, lipid absorption and subsequent chylomicron-TG production rates were significantly repressed in miR-33b+/+Apoe−/− mice (Figure 4B), and hepatic VLDL-TG production rates were similar between miR-33b+/+Apoe−/− and miR-33b−/−Apoe−/− mice (Figure 4C). Hepatic lipogenic genes expression levels were also similar (Figure VA in the online-only Data Supplement). Post-heparin administration, serum LPL activity was also similar between them (Figure 4D). Furthermore, there were no significant differences in hepatic expression of genes involved in modulating LPL activity (Figure VB in the online-only Data Supplement). These results were consistent with HPLC data that showed a reduction in serum TGs, especially in the chylomicron fraction in miR-33b+/+Apoe−/− mice (Figure 4A). The reduction rate of serum TGs from the fed state to 4 to 6 hours fast was much higher in miR-33b+/+Apoe−/− mice than in miR-33b−/−Apoe−/− mice (−54.7% versus −26.1%, respectively; Figure VC in the online-only Data Supplement), which also supports the reduction in lipid absorption and subsequent chylomicron-TG production in the small intestine. Next, we checked gene expression profiles related to serum LDL-C clearance because HPLC data showed a cholesterol peak shift from the large VLDL fraction to small LDL fraction. There were no significant changes in hepatic expression levels of genes related to LDL-C uptake and hepatic LDL receptor protein levels (Figure VD and VE in the online-only Data Supplement). These results indicated that Srebf1-miR-33b axis remodels lipoprotein metabolism broadly, as well as the reduction in serum HDL-C with attenuated cholesterol efflux capacity.

Macrophage MiR-33b Decreases Cellular Cholesterol Efflux and Increases Susceptibility of Free Cholesterol (FC)–Induced Apoptosis

Because previous reports have shown that miR-33a regulates macrophage phenotypes,4,5,30,31 we examined whether miR-33b altered macrophage characteristics or not. We measured ABCA1 and ABCG1 protein levels in PEMs. When PEMs were treated with acetylated LDL-C as the indicated time, induction of ABCA1/G1 was significantly repressed in PEMs from miR-33b+/+Apoe−/− mice (Figure 5A). The cholesterol efflux rate to apolipoprotein A-1 was significantly reduced to the same degree both in PEMs from miR-33b+/−Apoe−/− and miR-33b+/+Apoe−/− mice, whereas the cholesterol efflux rate to HDL was attenuated according to the number of miR-33b KI alleles (Figure 5B). To investigate whether this attenuated cholesterol efflux capacity affected PEMs survival or not, we analyzed FC-induced apoptosis in PEMs. Annexin V–positive apoptotic cells increased significantly in PEMs from miR-33b+/+Apoe−/− mice after FC loading (Figure 5C). Thus, miR-33b enhances the susceptibility of FC-induced apoptosis, which might lead to a plaque with increased number of apoptotic cells in vivo (Figure 2J).
Figure 5. MicroRNA (miR)-33b alters macrophage functions and characteristics via repression of cholesterol efflux. A, Western blotting analysis of ATP-binding cassette transporter (ABC) A1 and ABCG1 expression in peritoneal macrophages (PEMs). PEMs were treated with 300 μg/mL acetylated low-density lipoprotein (AcLDL-C) for the indicated times. Representative images from several independent experiments are shown. β-actin was used as the loading control. B, Cholesterol efflux from PEMs in the presence or absence of 10 μg/mL ApoA-1 and 100 μg/mL high-density lipoprotein (HDL) cholesterol (n=8). C, Quantification of Annexin V–positive PEMs in the presence or absence of 300 μg/mL AcLDL-C and 10 ng/mL acyl-CoA: cholesterol acyl-transferase inhibitor (ACATi) for 24 h (total 8–9 fields each containing ≈1000 cells). D, Quantitative real-time polymerase chain reaction (PCR) analysis of Il-1β, Il-6, and Ccl2 in PEMs from miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− mice. Values from miR-33b−/−Apoe−/− mice were set at 1. E, PEMs were stained with fluorescein isothiocyanate (FITC)–conjugated cholera toxin subunit B (CTB) to assess the amount of lipid rafts on the cellular membrane. FITC-CTB was quantified using flow cytometry: a representative histogram (left) and a bar graph of mean fluorescence intensity (MFI) from replicated samples (right; n=4). F, Expression levels of inflammatory genes in THP-1 macrophage transfected with miR-control and miR-33b overexpression vector. Values from miR-control vector transfected cells were set at 1 (n=9). G, MiR-control or miR-33b–overexpressed THP-1 macrophages with or without cholesterol depletion using methyl-β-cyclodextrin (MβCD) stained with FITC-CTB: a representative histogram (left) and a bar graph of MFI (the second from the left; n=3). Quantitative real-time PCR analysis of IL-1β and IL-6 from miR-control or miR-33b overexpressed THP-1 macrophage with or without cholesterol depletion using MβCD (the second from right and right). Values from miR-control vector transfected cells were set at 1 (n=9 each). Error bars indicate the SEM. *P<0.05, **P<0.01, and ****P<0.0001, by 1-way ANOVA with post hoc Tukey test (B, C, G) and Student t test (D, E, F). Apoe−/− indicates apolipoprotein E–deficient.

Macrophage MiR-33b Enhances Proinflammatory Gene Expression via Lipid Raft Remodeling

We reported that a loss of miR-33a might have multiple effects on both pro- and anti-inflammatory process in PEMs.5 We checked the expression levels of proinflammatory genes in thioglycollate-elicited PEMs from miR-33b+/+Apoe−/− and miR-33b−/−Apoe−/− mice. PEMs from miR-33b+/+Apoe−/− mice showed increased expression levels of Il-6 and Ccl2 (Figure 5D). Because miR-33b represses cholesterol efflux capacity in PEMs (Figure 5B), we hypothesized that miR-33b alters the cellular membrane lipid raft compartment, which is enriched in FC and is important for regulating inflammatory signal transduction. The amount of lipid rafts labeled with FITC-CTB on the membrane of PEMs from miR-33b+/+Apoe−/− mice were significantly increased compared with those from miR-33b−/−Apoe−/− mice (Figure 5E). We could recapitulate these phenotypes in THP-1 macrophages transduced with miR-33b expression vectors (Figure 5F). To confirm whether increased lipid rafts is responsible for proinflammatory gene expression profile or not, we depleted lipid raft cholesterol using methyl-β-cyclodextrin treatment. After methyl-β-cyclodextrin treatment, the amount of lipid rafts was similar between miR-control and miR-33b overexpressing THP-1 macrophages. In these conditions, increased expression levels of Il-1β and Il-6 shown in miR-33b–expressing THP-1 macrophages after LPS treatment were rescued (Figure 5G). Furthermore, to access the possibility of controlling miR-33a/b expression levels separately and its efficacy on inflammatory status, we treated PEMs from miR-33b+/+Apoe−/− using locked ribonucleotides, which have complementary sequences to miR-33b selectively. We could significantly repress miR-33b expression levels without changing miR-33a expression levels (Figure VIA in the online-only Data Supplement). As a result, the expression levels of Abca1 were increased and those of proinflammatory genes were significantly repressed in a dose-dependent manner (Figure VIB in the online-only Data Supplement). These data indicated that miR-33b could reprogram macrophages to a more proinflammatory phenotype in a proinflammatory milieu via regulating lipid rafts.

Hematopoietic MicroRNA-33b Promotes Atherogenesis in the Same Lipoprotein Condition

To elucidate the contribution of miR-33b in macrophages to atherogenesis, we performed BMT experiments. As a result, regardless of the recipients’ genotype, the resultant atherosclerotic plaque areas and CD68-positive macrophage infiltration areas were significantly increased in mice transfused with miR-33b+/+Apoe−/− BM cells compared with miR-33b−/−Apoe−/− BM cells (Figure 6A–6C). Serum HDL-C levels and serum TG levels were decreased in the miR-33b+/+Apoe−/− recipient group regardless of the genotype of transfused BM cells (Figure 6D). However, we could not detect significant differences in the resultant plaque areas between miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− mice transfused with the same genotype BM cells (Figure 6A–6C).
Figure 6. Hematopoietic microRNA (miR)-33b promotes atherogenesis in the same lipoprotein condition. A, Representative microscopic images of cross-sections at proximal aorta level in miR-33b−/−Apoe−/− mice transplanted with miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− bone marrow (BM) cells and miR-33b+/+Apoe−/− mice transplanted with miR-33b−/−Apoe−/− and miR-33b+/+Apoe−/− BM cells. Scale bar, 300 μm. B, Quantification of the atherosclerotic plaque area in cross-sections at proximal aorta level. Values are mean±SEM (n=7–9). C, Quantification of the CD68-positive area in cross-sections at proximal aorta level. Values are mean±SEM (n=7–9). D, Serum total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels determined by standard methods. Serum samples were collected after 4 to 6 h fasting. Values are means±SEM (n=7–9). *P<0.05, **P<0.01, and ****P<0.0001, by 1-way ANOVA with ad hoc Tukey test. Apoe−/− indicates apolipoprotein E–deficient.

discussion

Here, we show that Srebf1-miR-33b axis promotes atherogenesis with more necrotic core areas, increased macrophages infiltration, and less fibrotic components, using a miR-33b KI humanized mice model. MiR-33b, which increases in the livers after atheroprone feeding, reduces serum HDL-C levels and increases a ratio of serum LDL-C to HDL-C levels. Moreover, miR-33b reprograms macrophages toward a proinflammatory phenotype via modulating cholesterol amount of lipid rafts that aggravate vulnerable plaque characteristics.
In human atherosclerotic plaque specimens from carotid endarterectomy surgery, we confirmed the expression of both miR-33a/b. In the plaque area, both miR-33a/b expression levels were downregulated compared with the adjacent relatively healthy intima. There are several possible explanations, as follows: (1) the host genes, SREBF2/1, are repressed by a negative feedback mechanism in cholesterol-rich plaque areas, or (2) the reduction in their expression levels might suggests acellularity or a difference in cell composition in the plaque-rich area.
MiR-33a (miR-33 in rodents) deficiency using a genetically knockout model or antisense oligonucleotides raised serum HDL-C levels and increased macrophage cholesterol efflux capacity, which prevented atherogenesis or promoted the regression of atherosclerosis.1,5,32 Furthermore, recently we reported that genetic ablation of miR-33a attenuated abdominal aortic aneurysm formation via several anti-inflammatory pathways.33 Therefore, miR-33a could be a therapeutic target for atherosclerosis. However, before we translate these data into a clinical setting, we should consider that all these studies were performed using mice lacking miR-33b in an intron of Srebf1.
The inhibition of miR-33a/b using antisense oligonucleotides increases serum HDL-C levels in primates that have both miR-33a/b.8,9 These data strengthen the importance of both miR-33a/b on regulating serum HDL-C levels. From recent clinical studies, however, serum HDL-C values do not always associated with cardiovascular events rate.34 Thus, it is important to elucidate the effects of SREBF1-miR-33b axis on the development of atherosclerosis in animals that have both miR-33a/b. To this end, we used miR-33b KI humanized mice, in which miR-33b expression levels are coregulated with Srebf1 and are within physiological levels.12 We found that hepatic miR-33a/b expression levels were differentially regulated under a WTD feeding. These data suggested that although miR-33a/b have identical seed sequences, their functions could be different because of differences in expression levels depending on cells, tissues, organs, or on nutritional conditions. This concept seems to be reasonable given that miR-33a/b expression levels are coregulated with their host genes. Thus, we think miR-33b KI humanized mice could help to unravel the precise roles of miR-33a/b in vivo. Recently, Price et al35 reported another genetically modified miR-33b KI model, which replace entire mouse Srebf1 with human SREBF1, including miR-33b. However their KI mouse showed the sub-Mendelian birth rates and poor survival, whereas our KI mice were born with the expected Mendelian ratios and were viable and fertile. That is why they could not address systemic function of miR-33b. FANTOM5 miR atlas data showed the much higher expression levels of hepatic miR-33b than those of miR-33a, which support the importance of investigation of hepatic SREBF1-miR-33b axis (Figure VIIA in the online-only Data Supplement).36
From HPLC analysis, miR-33b+/+Apoe−/− mice showed a non–HDL-C peak shift from the VLDL cholesterol to small LDL-C fraction and a decrease in chylomicron-TG, in addition to a significant reduction in HDL-C. Reduction in serum HDL-C levels with attenuated cholesterol efflux capacity and individual RCT in miR-33b+/+Apoe−/− mice was consistent with previous reports using miR-33a deficiency models. Therefore, this result indicated that miR-33b is also essential for HDL-C metabolism in vivo. We also found that miR-33b impaired lipid absorption or chylomicron production in the small intestine, which lead to decrease in TG levels. Furthermore, the reduction in food intake might also contribute to this phenotype. Thus, the Srebf1-miR-33b axis could be responsible for the overall regulation of serum lipid profiles, not only serum HDL-C but also serum non–HDL-C and TG. However, the precise mechanisms remain unknown and need further investigation.
In advancing atherosclerotic lesions, macrophages are responsible for ingesting accumulated apoB-containing lipoproteins and triggering inflammation.37,38 We examined macrophage miR-33b functions for these 2 aspects. First, we found that PEMs from miR-33b+/+Apoe−/− mice are more susceptible to FC-induced apoptosis via repressing ABCA1/G1. This could contribute to the larger necrotic core area and the numbers of apoptotic cells in plaques of miR-33b+/+Apoe−/− mice. Second, we found that thioglycollate-elicited PEMs from miR-33b+/+Apoe−/− mice showed higher expression levels of proinflammatory genes. When macrophages gain their functional phenotypes, both endogenous and exogenous clues are important. Others showed miR-33a inhibition increased oxidative respiration via Prkaa1 derepression and induced M2-macrophage polarization-associated gene expression profiles.30 This work highlighted that miR-33a function in macrophage polarization from the viewpoint of endogenous cellular metabolic cues. However, ABCA1/G1 double-deficient macrophages were reported to have increased proinflammatory responses via augmented lipid raft cholesterol.39,40 Thus, we hypothesized that miR-33a/b regulate lipid raft cholesterol and control the signal transduction from external cues. In fact, the amount of lipid raft labeled with CTB was increased in miR-33b+/+Apoe−/− PEMs. We confirmed that miR-33b–overexpressing THP-1 macrophages had also accelerated proinflammatory responses to LPS stimulation via increased amounts of lipid rafts. Our data indicate that miR-33b affect lipid raft remodeling, which leads to control exogenous cues for reprogramming macrophage functional phenotype. BMT experiments highlighted that hematopoietic miR-33b promoted atherogenesis under the same serum lipid profiles. On the contrary, we could not detect effects of recipient genotypes on atherogenesis. It might be because the absolute values of serum cholesterol and TG were repressed in mice that underwent BMT compared with mice without BMT.
The other abovementioned miR-33b KI model failed to show any impact of hematopoietic miR-33b on atherogenesis.35 We considered that the discrepancy between those results and our current findings may come from the differences in genetic engineering strategies and the lack of appropriate control animal in their experiments. They compared BM cells from wild-type mice that have mouse Srebf1 and those from their KI model that have human SREBF1.35 In addition, the previous report mentioned that one of the causes of their findings was because of dramatically lower expression levels of miR-33b in macrophages than miR-33a. However, the expression levels of miR-33a and miR-33b in macrophages from our miR-33b KI model and FANTOM5 miR atlas data were similar (Figure VIIA and VIIB in the online-only Data Supplement).36 Thus, we concluded miR-33b does have additive proatherogenic effects and contribute to plaque vulnerability.
We recognized several limitations to this study. First, we found hematopoietic miR-33b+/+ accelerated development of atherosclerosis. Because BM cells include a variety of immune cells other than macrophages, miR-33b in these cells also might have important roles in atherosclerosis. Second, although the target genes of miR-33a/b are conserved to some extent between mice and human, they are not completely identical. However, we found the conservation rates are considerably good using Target Scan Human/Mouse release 7.1.25 Furthermore, the pathway analyses showed enriched pathways were concentrated only in conserved target genes (Figure VII in the online-only Data Supplement). These data implied that this KI model is a useful humanized model. We should, of course, beware that there might be some important target genes that exist in only mouse or human. Last, we used male mice for our experiments except for BMT experiment in which we used female mice as recipients.13
In summary, we demonstrated the functions of miR-33b on atherogenesis in vivo act through not only reducing serum HDL-C levels with repressing systemic RCT but also increasing atheroprone small–LDL-C levels and accelerating FC-induced apoptosis and proinflammatory phenotypes of macrophages. Because miR-33b is assumed to be elevated in insulin resistance or chronic inflammatory states with its host SREBFc/1a,41,42 it might play a major role in atherosclerosis development in atheroprone conditions and could be a promising therapeutic target.

Acknowledgments

Experiments using radioisotopes were performed at the Radioisotope Research Center, Kyoto University.

Highlights

MicroRNA (miR)-33a/b expression levels are differentially regulated with their host genes in vivo, and miR-33b is prominent under atheroprone conditions.
Srebf1-miR-33b axis controls overall serum lipoprotein profiles besides previously focused serum high-density lipoprotein cholesterol.
MiR-33b promotes the development of atherosclerotic plaque with more macrophage infiltration, a larger number of apoptotic cells, and less fibrotic area via downregulation of systemic reverse cholesterol transport and skewing macrophage toward proinflammatory phenotype.
MiR-33b may be a promising therapy for treating atherosclerosis; especially, it will give us a chance to stabilize a high-risk vulnerable plaque, which is regarded as causes of plaque ruptures.

Footnote

Nonstandard Abbreviations and Acronyms

ABC
ATP-binding cassette transporter
AcLDL
acetylated low-density lipoprotein
apoB
apolipoprotein B
Apoe−/−
apolipoprotein E–deficient
BM
bone marrow
BMT
bone marrow transplantation
CTB
cholera toxin subunit B
FC
free cholesterol
FITC
fluorescein isothiocyanate
HDL-C
high-density lipoprotein cholesterol
HPLC
high-performance liquid chromatography
KI
knock-in
LDL-C
low-density lipoprotein cholesterol
LPL
lipoprotein lipase
PCR
polymerase chain reaction
PEM
peritoneal macrophage
RCT
reverse cholesterol transport
SREBF
sterol regulatory element-binding factor
SREBP
sterol regulatory element-binding protein
TG
triglyceride
VLDL
very-low-density lipoprotein
WTD
Western-type diet

Supplemental Material

File (atvb_atvb-2018-311409d_supp1.pdf)

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Go to Arteriosclerosis, Thrombosis, and Vascular Biology
Arteriosclerosis, Thrombosis, and Vascular Biology
Pages: 2460 - 2473
PubMed: 30354203

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History

Received: 23 January 2018
Accepted: 13 July 2018
Published online: 26 July 2018
Published in print: October 2018

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Keywords

  1. atherosclerosis
  2. bone marrow transplantation
  3. cholesterol, HDL
  4. lipid metabolism
  5. microRNAs

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Authors

Affiliations

Tomohiro Nishino
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Takahiro Horie [email protected]
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Osamu Baba
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Naoya Sowa
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Ritsuko Hanada
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Yasuhide Kuwabara
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Tetsushi Nakao
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Masataka Nishiga
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Hitoo Nishi
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Yasuhiro Nakashima
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Fumiko Nakazeki
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Yuya Ide
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Satoshi Koyama
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Masahiro Kimura
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
Manabu Nagata
Neurosurgery (M.N., K.Y., Y.T., S.M.), Graduate School of Medicine, Kyoto University, Japan
Kazumichi Yoshida
Neurosurgery (M.N., K.Y., Y.T., S.M.), Graduate School of Medicine, Kyoto University, Japan
Yasushi Takagi
Neurosurgery (M.N., K.Y., Y.T., S.M.), Graduate School of Medicine, Kyoto University, Japan
Tomoyuki Nakamura
Department of Pharmacology, Kansai Medical University, Moriguchi, Japan (T.N.)
Koji Hasegawa
Division of Translational Research, Clinical Research Institute, National Hospital Organization Kyoto Medical Center, Japan (K.H.).
Susumu Miyamoto
Neurosurgery (M.N., K.Y., Y.T., S.M.), Graduate School of Medicine, Kyoto University, Japan
Takeshi Kimura
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan
From the Departments of Cardiovascular Medicine (T.N., T.H., O.B., N.S., R.H., Y.K., T.N., M.N., H.N., Y.N., F.N., Y.I., S.K., M.K., T.K., K.O.), Graduate School of Medicine, Kyoto University, Japan

Notes

The online-only Data Supplement is available with this article at Supplemental Material.
Correspondence to Koh Ono, MD, PhD, Department of Cardiovascular Medicine, Graduate School of Medicine, Kyoto University, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606–8507, Japan, Email [email protected]
Correspondence to Takahiro Horie, MD, PhD, Department of Cardiovascular Medicine, Graduate School of Medicine, Kyoto University, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606–8507, Japan, Email [email protected]

Disclosures

None.

Sources of Funding

This work was supported, in part, by grants from the Ministry of Education, Culture, Sports, Science and Technology of Japan (to T. Nishino, T. Horie, T. Kimura, and K. Ono), by a Japan Heart Foundation & Astellas Grant for Research on Atherosclerosis Update (to T. Nishino), and by a visionary research grant Step from Takeda Science Foundation (to K. Ono).

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  1. miR-33 deletion in hepatocytes attenuates MASLD-MASH-HCC progression, JCI Insight, 9, 19, (2024).https://doi.org/10.1172/jci.insight.168476
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  2. Circulating microRNA-33b levels are associated with the presence and severity of coronary heart disease, Scandinavian Journal of Clinical and Laboratory Investigation, 84, 2, (133-137), (2024).https://doi.org/10.1080/00365513.2024.2340751
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  3. Atherosclerosis is the outcome of adaptive complexity in the Arterial Endothelial Microenvironment, Metabolic Syndrome, (259-277), (2024).https://doi.org/10.1016/B978-0-323-85732-1.00081-5
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  4. MicroRNAs Regulate Function in Atherosclerosis and Clinical Implications, Oxidative Medicine and Cellular Longevity, 2023, (1-12), (2023).https://doi.org/10.1155/2023/2561509
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  5. Inhibition of microRNA-33b in humanized mice ameliorates nonalcoholic steatohepatitis, Life Science Alliance, 6, 8, (e202301902), (2023).https://doi.org/10.26508/lsa.202301902
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  6. Temporal associations between leukocytes DNA methylation and blood lipids: a longitudinal study, Clinical Epigenetics, 14, 1, (2022).https://doi.org/10.1186/s13148-022-01356-x
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  7. Long non-coding RNA HIF1A-AS2 modulates the proliferation, migration, and phenotypic switch of aortic smooth muscle cells in aortic dissection via sponging microRNA-33b, Bioengineered, 13, 3, (6383-6395), (2022).https://doi.org/10.1080/21655979.2022.2041868
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  8. The effects of chemical mixtures on lipid profiles in the Korean adult population: threshold and molecular mechanisms for dyslipidemia involved, Environmental Science and Pollution Research, 29, 26, (39182-39208), (2022).https://doi.org/10.1007/s11356-022-18871-2
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  9. Genomic Variants and Multilevel Regulation of ABCA1, ABCG1, and SCARB1 Expression in Atherogenesis, Journal of Cardiovascular Development and Disease, 8, 12, (170), (2021).https://doi.org/10.3390/jcdd8120170
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  10. MicroRNA-325 facilitates atherosclerosis progression by mediating the SREBF1/LXR axis via KDM1A, Life Sciences, 277, (119464), (2021).https://doi.org/10.1016/j.lfs.2021.119464
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SREBF1/MicroRNA-33b Axis Exhibits Potent Effect on Unstable Atherosclerotic Plaque Formation In Vivo
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