MicroRNA‐143‐3p ameliorates collagen‐induced arthritis by polarizing naive CD4 +T cells into Treg cells

Mei‐Yu Shen; Bao‐Ping Jiang; Ming‐Fei Zhang; Xiang Wang; Hong Zhu; Zhen‐Ning Gu; Xue‐Ping Zhou; Yan Lu; Ling‐Ling Zhou

doi:10.1002/jcla.24845

. 2023 Mar 1;37(5):e24845. doi: 10.1002/jcla.24845

MicroRNA‐143‐3p ameliorates collagen‐induced arthritis by polarizing naive CD4 ⁺T cells into Treg cells

Mei‐Yu Shen ¹, Bao‐Ping Jiang ¹, Ming‐Fei Zhang ¹, Xiang Wang ¹, Hong Zhu ^2,³, Zhen‐Ning Gu ^2,³, Xue‐Ping Zhou ³, Yan Lu ^2,^3,^✉, Ling‐Ling Zhou ^1,^✉

PMCID: PMC10098049 PMID: 36861291

Abstract

Background

Rheumatoid arthritis (RA) is a persistent and systemic autoimmunity disease. The abnormal differentiation of Treg cells is important in pathogenesis. Despite previous studies showed that microRNAs (miRNAs, miR) are pivotal modulators of Treg cells, the effect of miRNAs on Treg cell differentiation and function is not clear. Our study wants to reveal the relationship of miR‐143‐3p with the differentiative ability and biofunction of Treg cells during the development of RA.

Methods

The Expressing level of miR‐143‐3p and cell factor generation in peripheral blood (PB) of RA sufferers were identified by ELISA or RT‐qPCR. The roles of miR‐143‐3p in Treg cell differentiation were studied via ShRNA/lentivirus transfection. Male DBA/1 J mice were separated into control, model, control mimics, and miR‐143‐3p mimics groups to analyze the anti‐arthritis efficacy, the differentiative ability of Treg cells, and the expression level of miR‐143‐3p.

Results

Our team discovered that the Expressing level of miR‐143‐3p was related to RA disease activities in a negative manner, and remarkably related to antiinflammation cell factor IL‐10. In vitro, the expression of miR‐143‐3p in the CD4⁺T cells upregulated the percentage of CD4⁺CD25⁺Fxop3⁺ cells (Tregs) and forkhead box protein 3 (Foxp3) mRNA expression. Evidently, miR‐143‐3p mimic intervention considerably upregulated the content of Treg cells in vivo, validly avoided CIA progression, and remarkably suppressed the inflammatory events of joints in mice.

Conclusion

Our findings indicated that miR‐143‐3p could ameliorate CIA through polarizing naive CD4⁺T cells into Treg cells, which may be a novel strategy to treat autoimmune diseases such as RA.

Keywords: CD4⁺T cells, collagen‐induced arthritis, MiR‐143‐3p, rheumatoid arthritis, Treg cells

The overexpression of miR‐143‐3p markedly induced Treg cell differentiation. And the percentage of Treg cells was notably reduced in the miR‐143‐3p‐knockdown cell population. It indicated that miR‐143‐3p promoted Treg cell differentiation in vitro and in vivo.

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1. INTRODUCTION

Rheumatoid arthritis (RA) is a chronic immune‐mediated inflammatory disease that causes joint disability in 0.5%–1% of the global population. ¹ The disease is characterized by synovial inflammation and formation of pannus. ² , ³ The hallmark of inflamed synovium is the infiltration of inflammatory cells into the joints, including native immunocytes and adaptive immunocytes (B cells and T cells). ⁴ Despite the fact that the etiopathogenesis of RA has not been comprehensively examined, it is cleared that the aberrant activation of CD4⁺T helper (Th) cells has been recognized as a critical component of the onset and development of RA. ⁵ The plasticity of CD4⁺T cells, the capability of differentiating into specific subsets, is essential for sustaining immunity equilibrium. ⁶ Naive CD4⁺T cells could convert into Treg cells in the stimulation of immune regulatory cell factors like TGF‐β and IL‐2. Treg cells are critical for preserving immune tolerance by exerting inhibitory functions on immune effector cells. ⁷ Recently, quantitative and functional defects of Treg cells have been determined in the PB and synovia of RA sufferers. ⁸ , ⁹ Treg cells are famous for the ability to specifically express forkhead box P3 (Foxp3), and can excrete antiinflammation cell factors like TGF‐β, IL‐10, and IL‐35, which inhibit effector T cells differentiation and function. ¹⁰ , ¹¹ The modulation of Treg cell differentiation could be helpful for treating RA.

The role of Treg cells in RA is clear, but the exact mechanisms were still being studied. MicroRNAs (miRNAs), considered as an endogenous, conserved small noncoding RNA, can controls genetic expression via binding to the 3'UTR of the targeted mRNAs. Mounting evidence suggests that aberrant miRNA expression participates in the etiologic of multiple inflammation illnesses. ¹² , ¹³ And they are nonreplaceable regulators of Treg cell differentiative activity and/or biofunction, for example, miR‐146a and miR‐155 were downregulated in Treg cells of RA patients and correlated with joint inflammation. ¹⁴ MiR‐342 was confirmed to control Treg regulatory functions via targeting the mTORC2 component, Rictor. ¹⁵ Simultaneously, miR‐142‐3p was reported to target Tet2 and result in impaired Treg stability in islet autoimmunity. ¹⁶ MiR‐34a could downregulate the expression of Foxp3 via targeting their 3'UTR in collagen‐induced arthritis (CIA) mice. ¹⁷ Nevertheless, whether other miRNAs are involved in regulating Treg cells differentiation and/or function. And how those miRNAs are modulated, requires more research.

Our previous studies have also found abnormally expressed miR‐143‐3p in RA sufferer PB by miRCURYTM LNA Array. ¹⁸ Clinical analysis demonstrated that abnormally expressed miR‐143‐3p was related to RA activities in a negative manner, and related to IL‐10 in RA in a positive manner. In vitro, our team discovered that miR‐143‐3p could remarkably promote Treg cell differentiation. Besides, the results herein suggested that overexpressed miR‐143‐3p markedly ameliorates CIA pathogenesis and joint inflammation by inducing Treg cell differentiation. Overall, we observed the roles of miR‐143‐3p in Treg cell differentiative activity in the pathogenies of RA, which might be a prospective target for RA therapy.

2. MATERIALS AND METHODS

2.1. RA patients and control subjects

Serological and clinical information from 38 RA sufferers meeting the 1987 American College of Rheumatology (ACR)/2010 European League Against Rheumatism (EULAR) categorization standards for RA was acquired with no treatments. Every sufferer had active disease with Disease Activity Score at 28 joints (DAS28) >3.2. They were from Jiangsu Province Hospital of TCM. Our research was accepted by the Ethical Committee of our institution (NO.: 2016NL‐KS14) and this research was finished as per the Declaration of Helsinki. Written partake consent was acquired from all sufferers.

The clinical information of the 38 RA sufferers and the 27 healthy controls (HCs) is displayed in Table 1. No remarkable diversity was observed in sex and age of moderate RA sufferers, serious RA sufferers, and HCs. In contrast to moderate RA sufferers, the tender joint count, swollen joint count, ESR, CRP, DAS28, IgG, and IgA in severe RA patients markedly increased. Blood was collected for ELISA and miRNA analysis.

TABLE 1.

Clinic data of RA sufferers and HCs

	Moderate RA (n = 15)	Severe RA (n = 23)	Healthy Controls (n = 27)
Sex (Female %)	80.00	86.96	79.17
Age (years)	48.94 ± 10.26	55.57 ± 11.98	59.32 ± 1.64
Tender joint count	2.47 ± 1.25	7.65 ± 3.92***	NA
Swollen joint count	2.13 ± 1.13	7.35 ± 4.27***	NA
ESR (mm/h)	35.13 ± 18.78	75.96 ± 31.18***	NA
CRP (mg/L)	17.59 ± 18.20	55.70 ± 55.73**	NA
DAS28	4.26 ± 0.60	6.00 ± 0.56***	NA
RF positivity (%)	73.33	95.65*	NA
IgG (g/L)	13.69 ± 1.35	17.36 ± 8.17*	NA
IgA (g/L)	2.58 ± 0.78	3.54 ± 1.63*	NA
IgM (g/L)	1.49 ± 0.66	1.45 ± 0.57	NA

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Abbreviations: CRP, C reactive protein; DAS28, disease Activity Score at 28 joints; ESR, erythrocyte sedimentation rate; IgA, Immunoglobulin‐A; IgG, Immunoglobulin‐G; IgM, Immunoglobulin‐M; RF, rheumatoid factor.

Note: For Sex (Female %) and RF positivity (%), *p < .05, by Fisher's exact test. For the other data, data were expressed as the average ± SEM. *p < .05, **p < .01, ***p < .001, by one‐way ANOVA with Dunnett's post‐hoc test or Student's t test.

2.2. Acquisition of human PB CD4⁺T cells

For mankind specimens, the separation of PB mononuclear cells (PBMCs) was completed via Ficoll density gradient centrifugal process (TBD science, LTS1077) as per the supplier's protocol. Afterward, cells were cleaned in BD IMag™ buffering solution and cultivated with 50 μl BD IMag™ Anti‐Human CD4 Particulates (BD Bioscience, L200) for every 10⁷ total cells under ambient temperature for 0.5 h. Then, we brought the BD IMag™ particle labeling volume at 10⁷ cells/ml with BD IMag™ buffering solution, and directly put the tube on the magnetic platform for 480 s. The supernate was discreetly removed and we harvested the mankind PB CD4⁺T cells.

2.3. Animals

Male DBA/1 J mice (6–8 weeks old) were provided by Gempharma Technology Company [PRC; NO.: SCXK (Su) 2016–0010], and male C57BL/6 mice were provided by Beijing Vital River Lab Animal Technologies [PRC; NO.: SCXK (Jing) 2016–0006]. The animals were raised in an SPF environment. Our assay was accepted by the Ethical Board of our institution (No. 202005A022).

2.4. Separation, transfection, and differentiation of naive CD4 ⁺T cells

Mouse naive splenic CD4⁺T cells from male C57BL/6 mice were subjected to purification and negatively selected via magnetic cells through a murine naive CD4⁺T‐cell separation tool (Miltenyi Biotechnology, 130–104‐453), as per the supplier's protocol. Cellular samples were treated with plate‐bound antiCD3e (BD Pharmingen, 553,057) (2 μg/ml) and antiCD28 antisubstances (BD Pharmingen, 553,294) (2 μg/ml) in vitro in RPMI 1640, added with 10% thermal inactivation FBS and 100 U/ml penicillin/kyowamycin. ShRNA/lentivirus was provided by Gene Pharma (PRC) to overexpress or remove miR‐143‐3p. Under the stimulation by antiCD3e and antiCD28 antibody, the naive CD4⁺T cells were subjected to transfection by lentiviral‐conditioned media as per the supplier's protocol. To differentiate Treg cells, naïve CD4⁺T cells were supplemented with 5 ng/ml TGF‐β (R&D System, 7666‐MB) and 80 ng/ml IL‐2 (R&D System, 402‐ML) posterior to the 12‐h transfection. ¹⁹ Cells were analyzed via RT‐qPCR and flow cell technique.

2.5. Establishment of CIA model and miR‐143‐3p intervention

The CIA animal model was constructed as delineated in the past. ²⁰ , ²¹ Male DBA/1 J mice utilized were immunized s.c. at the tail bottom using bovine type II collagen (CII) (Chondrex, 20,021) and Freund's adjuvant (CFA) (Sigma‐Aldrich, F5881). CII was blended with CFA in a 1:1 ratio (v/v) and subjected to emulsification under 4°C. The day of the first immunization was identified on day 0. On day 21, 0.1 ml incomplete Freund's adjuvant (IFA)‐emulsified CII (eventual content: 1 mg/ml) was s.c. in the tail, near the original injection spot, to reinforce immunization. Then, the control and model groups were treated with saline injection (1 ml/kg, i.v.). The control mimics group was intravenously administered in the tail with 50 μg control mimics (Engreen Biosystem) in EntransterTM‐in vivo, and the miR‐143‐3p mimics group mice were intravenously injected in the tail with 50 μg miR‐143‐3p mimics (Engreen Biosystem) in EntransterTM‐in vivo. MiR‐143‐3p mimetic substances or the control substances were administered on day 28 and day 35 posterior to the first immunization. ²² The developmental process of illness was recorded on day 22, 26, 30, 34, 38, and 42 via evaluating the thickness of paws and arthritis scoring. Arthritis scoring ranged from 0 to 4. ²³ The maximal scoring per mouse was 16 (4 points × 4 paws). At day 44, every mouse was killed via anaesthetization, the plasma, spleen samples, and keen joints were harvested for analyses.

2.6. Histology analyses

Slices from knee joints fixed in 4% PFA were dyed in H&E and tartrate‐resistant acid phosphatase (TRAP). The scoring of slices was acquired as delineated in the past, ²⁴ , ²⁵ and identified via the semiquantitative score system.

2.7. ELISA analysis

PB was harvested from sufferers, HCs, and animals in heparin sodium to plasma centrifuge. The contents of IFN‐γ (Catalog #EK180HS), IL‐4 (Catalog #EK104HS), IL‐10 (Catalog #EK110HS), and IL‐17A (Catalog #EK117HS) were identified via Mankind Highly Sensitive ELISA tool (MultiSciences), and the contents of IL‐1β (Catalog #EK201BHS), IL‐6 (Catalog #EK206HS), TNF‐α (Catalog #EK282HS), IL‐10 (Catalog #EK210/3), IL‐17A (Catalog #EK217HS) were identified via Murine Highly Sensitive ELISA tools or Murine ELISA tools (MultiSciences). Every ELISA procedure was finished as per the supplier's protocol.

2.8. Acquisition of total RNA and RT‐qPCR

Overall RNA was separated from CD4⁺T cells via TRIzol™ Reagent (Ambion, 15,596,026) as per the supplier's protocol and evaluated for purity and content via the absorptive ratios of 260/280 nm and 260/230 nm by Nano Drop Micro Volume spectral photometer (Thermo). For miRNA analysis, 500 ng of total RNA was performed with miRNA 1st Strand cDNA Synthetic Tools (by stem‐loop) (Vazyme, MR101‐02) to generate cDNA. For other mRNA analysis, cDNA was generated by reverse transcription tool HiScript Q RT Super Mix (Vazyme, R222‐01). We quantified mRNA via RT‐qPCR completed on resulting cDNA via miRNA Universal SYBR qPCR Master Mix (Vazyme, MQ101‐02) or ChamQ Universal SYBR qPCR Master Mix (Vazyme, Q711‐02) and an ABI 7500 thermal cycler (Applied Biosystem, America). Genetic comparative expression was computed via the 2^−ΔΔCt and normalized to a referential control (GAPDH or U6). The primers (Sangon Biotechnology) utilized herein are displayed in Table 2.

TABLE 2.

The primers utilized for RT‐qPCR

Name	Primers	Sequence 5′–3′
Has‐U6	Forward	GCTTCGGCAGCACATATACTAAAAT
Has‐U6	Reverse	CGCTTCACGAATTTGCGTGTCAT
Has‐miR‐143‐3p	Forward	CGCGTGAGATGAAGCACTG
Has‐miR‐143‐3p	Reverse	AGTGCAGGGTCCGAGGTATT
Mmu‐U6	Forward	CTCGCTTCGGCAGCACA
Mmu‐U6	Reverse	AACGCTTCACGAATTTGCGT
Mmu‐miR‐143‐3p	Forward	GGGTGAGATGAAGCACTG
Mmu‐miR‐143‐3p	Reverse	CAGTGCGTGTCGTGGAGT
GAPDH	Forward	AGGTCGGTGTGAACGGATTTG
GAPDH	Reverse	TGTAGACCATGTAGTTGAGGTCA
Foxp3	Forward	CACCTATGCCACCCTTATCCG
Foxp3	Reverse	CATGCGAGTAAACCAATGGTAGA

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2.9. Intracellular staining and flow cytometry

As aforementioned, ²⁶ , ²⁷ spleen cells from CIA animals were washed in PBS. For the analysis of Treg cells, splenocytes were dyed with anti‐CD4‐FITC (Clone. RM4‐5), anti‐CD25‐PE‐CY7 (Clone. PC61), and anti‐Foxp3‐PE (Clone. R16‐715) (BD Bioscience). For analyses and gating, our team utilized ancillary dyeing groups involving no dyeing, single dyeing, isotype dyeing. Eventually, numerical results were obtained via flow cell technique (Beckman, FC‐500) and studied via Kaluza Analysis 2.0 (Beckman, A84174).

2.10. Statistics

Data were performed as average ± SEM and p < .05 had significance on statistics. Statistic contrasts were completed via Student's t test, one‐way ANOVA and Dunnett's post‐hoc test, spearman's rank correlative analysis, and linear regressive analysis via GraphPad Prism 6.

3. RESULTS

3.1. Differentially expressed miR‐143‐3p in the CD4 ⁺T cells was related to RA disease activity in a negative manner

To reveal if miR‐143‐3p was implicated in the etiopathogenesis of RA, the levels of miR‐143‐3p in the CD4⁺T cells from PBMCs of RA sufferers and HCs were studied via RT‐qPCR. As miR‐143‐3p has been discovered to show different expression in different individuals with RA, ¹⁸ , ²⁸ , ²⁹ we speculate whether the difference in disease severity or not affected the Expressing level of miR‐143‐3p. Hence, sufferers were classified according to DAS28. 23 patients had severe illness activities (DAS28 >5.1); 15 sufferers had moderate illness activities (DAS28 3.2–5.1). Intriguingly, our team discovered that in contrast to HCs, the Expressing level of miR‐143‐3p was remarkably elevated in CD4⁺T cells from moderate RA sufferers, while the Expressing level of miR‐143‐3p from severe RA sufferers was dramatically decreased in comparison with moderate RA patients and HCs (Figure 1). Besides, based on Pearson's correlative analyses, the Expressing level of miR‐143‐3p was negatively related to the DAS28 (r = −0.7302; p = .0001) and ESR (r = −0.3586, p = .0238) (Figure 1B,C), which were considered as biomarkers of illness activities in RA.

Differentially expressed miR‐143‐3p in the CD4⁺T cells was related to RA activities in a negative manner. (A) Quantification of miR‐143‐3p mRNA in PB CD4⁺T cells of moderate (n = 15) and severe RA patients (n = 23) and HCs (n = 27). *p < .05, **p < .01 by one‐way ANOVA with Dunnett's post‐hoc test. (B, C) The relation among the Expressing level of miR‐143‐3p and DAS28 (n = 38, r = −0.7302, ***, p = .0001) and ESR levels (n = 38, r = −0.3586, *, p = .0238). The Pearson correlative coefficient was identified. (D) Representative images of the hind paws of each group taken after reinforce immunisation. (E, F) Mean arthritis scoring and the thickness of paws of the controls and CIA animals (n = 6). ***p < .001, by one‐way ANOVA with Dunnett's post‐hoc test. (G) Representative histopathological characteristics of CIA mouse joint. HE dyeing of joints of CIA animals displayed inflammation cell infiltration (black arrow). TRAP staining showed the activation of osteoclasts (black arrow) of mouse joints. Histopathologic indices of synovitis in the knee joints were determined using semiquantitative scoring systems (0–5 for the extent of infiltration by inflammatory cells into the synovium) (n = 6). **p < .01 by Student's t test. (H) The plasma contents of IL‐1β, IL‐6, TNF‐α, IL‐17A in the control and CIA mice were identified via ELISA (n = 6). **p < .01 by Student's t test. (I) The Expressing level of miR‐143‐3p in the spleen CD4⁺T cells of control and CIA animals was detected via RT‐qPCR analyses (n = 6). **p < .01 by Student's t test.

To further confirm our observation, we generated the CIA mice model using CII, which has an alike pathologic causal link in contrast to mankind RA. ²¹ , ³⁰ In contrast to the controls, the arthritis scores, paw thickness, histopathologic scores, TRAP‐positive polykaryocytes, and the contents of plasma inflammation cell factors (IL‐1β, IL‐6, TNF‐α, IL‐17A) in CIA mice were markedly increased (Figure 1D–H), indicating the CIA models were built successfully. Consistent with the results of human patients, we also observed a notable decline of miR‐143‐3p expression in the spleen CD4⁺T cells of CIA animals (Figure 1I). Altogether, our observation suggested that the Expressing level of miR‐143‐3p in CD4⁺T cells was related to RA illness activities in a negative manner, which might have the possible protective efficacy in RA.

3.2. MiR‐143‐3p was essential for reducing joint inflammatory events in CIA mice

To study the treatment potential efficacy of miR‐143‐3p in RA, our team treat CIA mice with 2 mg/kg of miR‐143‐3p mimetic substance at day 28 and day 35 tail vein injection after the first immunization to overexpress miR‐143‐3p and evaluated disease development. In contrast to the control mimics group, the high Expressing level of miR‐143‐3p in miR‐14‐3p mimics‐treated mice were observed, which verified the success transfection (Figure 2A). Our team discovered that miR‐143‐3p mimetic substance dramatically repressed the development of CIA, with a considerable decrease in arthritis scoring, the thickness of paws (Figure 2B–D), and histopathological scores (Figure 2F), in contrast to the control mimic mice. Additionally, the generation of proinflammation cell factors, like IL‐6, IL‐1β, and IL‐17A, remarkably reduced in the miR‐143‐3p mimics mice (Figure 2E). Overall, our data indicated a global anti‐inflammatory efficacy of miR‐143‐3p and confirm the latent function of miR‐143‐3p as a new treatment target for RA.

MiR‐143‐3p was essential for reducing joint inflammatory events in CIA animals. CIA animals were treated at day 28 and day 35 after the first immunization with saline (1 ml/kg) or miR‐143‐3p mimic negative control (2 mg/kg) or miR‐143‐3p mimic (2 mg/kg). (A) The Expressing level of miR‐143‐3p in the spleen CD4⁺T cells of CIA animals with miR‐143‐3p mimetic or control mimetic substances was identified via RT‐qPCR analysis (n = 6). ***p < .001 by Student's t test. (B) Representative images of the hind paws of miR‐143‐3p‐treated CIA mice. (C, D) Mean arthritis scoring and the thickness of paws in CIA animals exposed to control mimic or miR‐143‐3p mimic (n = 6). *p < .05, **p < .01, by one‐way ANOVA with Dunnett's post‐hoc test. (E) The plasma contents of IL‐1β, IL‐6, TNF‐α, IL‐17A in CIA animals with miR‐143‐3p mimetic or control mimetic substances were identified via ELISA (n = 6). *p < .05, **p < .01 by Student's t test. (F) Representative histopathological characteristics and histological scores in the joints of miR‐143‐3p‐treated CIA animals (n = 6). **p < .01 by Student's t test.

3.3. MiR‐143‐3p expression was positively related to antiinflammation signal IL‐10

For the sake of identifying the mechanism of miR‐143‐3p reducing inflammatory response in CIA animals, we collected some inflammatory‐related cytokines in plasma of RA patients by ELISA, like IFN‐γ, IL‐4, IL‐10, and IL‐17A. Compared with HCs, the plasma contents of IFN‐γ and IL‐17A were elevated in RA sufferers in a degree‐dependent manner (Figure 3A,C). And more notably, the plasmatic contents of IL‐4 and IL‐10 were remarkably greater in sufferers with moderate RA in contrast to HC, whereas IL‐4 and IL‐10 concentrations were slightly reduced in serious RA sufferers in comparison with moderate RA (Figure 3B,D), whose changing trend was similar to miR‐143‐3p in CD4⁺T cells. Our team also discovered that IL‐17A contents were associated with DAS28 (r = 0.3061; p = .0308) in a positive manner, and IL‐10 contents were associated with DAS28 of RA patients (r = −0.3782; p = .0096) in a negative manner (Figure 3E–H). It is consistent with the characteristics of IL‐10 as an antiinflammation factor and IL‐17A as a proinflammatory factor in RA pathogenesis. Importantly, the results of further analyses unveiled that the Expressing level of miR‐143‐3p was related to IL‐10 contents (r = 0.3922, p = .0074) in a positive manner (Figure 3I,J), which demonstrated that miR‐143‐3p alleviating joint inflammation in CIA mice might relate to anti‐inflammation signal IL‐10.

Expressing level of miR‐143‐3p was related to antiinflammation signal IL‐10 in a positive manner (A–D) The contents of IFN‐γ, IL‐4, IL‐10 and IL‐17A in plasma of moderate patients (n = 15), severe patients (n = 23) and HCs (n = 27) were detected by ELISA. *p < .05, **p < .01 by one‐way ANOVA with Dunnett's post‐hoc test. (E–H) The correlation between IFN‐γ, IL‐4, IL‐17A (n = 38, r = 0.3061, *p = .0308), IL‐10 (n = 38, r = −0.3782, **p = .0096) and DAS28 levels. (I, J) The correlation between the Expressing level of miR‐143‐3p and IL‐17A, IL‐10 (n = 38, r = 0.3922, **p = .0074). The Pearson correlative coefficient was identified.

3.4. MiR‐143‐3p facilitated the differentiation of Treg cells in vitro and in vivo

The aberrant activation and differentiation of CD4⁺T cells has been considered as one of the crucial causations in the initiation and perpetuation process of RA. Treg cells, a subset polarized from naive CD4⁺T cells, has been considered as a critical regulator of peripheral immune tolerance and homeostasis and mainly secreted antiinflammation cell factor IL‐10. As the above mentioned, the Expressing level of miR‐143‐3p in CD4⁺T cells of RA sufferers was positively related to IL‐10 levels. We assumed that miR‐143‐3p might be related to Treg cell differentiation, which may ameliorate joint inflammatory events in CIA model. Hence, to directly reveal the potential roles of miR‐143‐3p in the differentiative ability of Treg cells, our team cultivated the naive CD4⁺T cells from C57BL/6 mice under induced Treg (iTreg) cell–polarizing conditions in vitro. Th0 cells, which stimulated with antiCD3e/CD28 antisubstances but without the supplementation of differentiation cell factors, were used as control group. Our team discovered that the Expressing level of miR‐143‐3p was regulated upward in Treg cell differentiation in contrast to Th0 cells (Figure 4A). Meanwhile, we constructed miR‐143‐3p knockdown and overexpression lineage cells in Treg cells using the lentivirus‐mediated method. The successful transfection, which significantly altered the Expressing level of the intracellular miR‐143‐3p, was verified via RT‐qPCR (Figure 4B). Intriguingly, the overexpression of miR‐143‐3p considerably elevated the proportion of Treg cells. In contrast, the proportion of Treg cells was notably reduced in the miR‐143‐3p‐knockdown cell population (Figure 4D). The changes in Foxp3 mRNA expression coincided with the proportion of Treg cells (Figure 4C). This result indicated that miR‐143‐3p was capable to facilitate Treg cell differentiation in vitro.

MiR‐143‐3p facilitated the differentiative ability of Treg cells in vitro and in vivo. (A) The Expressing level of miR‐143‐3p in CD4⁺T cells (with or without Treg‐polarization) was identified via RT‐qPCR analyses (n = 3). **p < .01 by Student's t test. (B, C) The Expressing level of miR‐143‐3p and Foxp3 in CD4⁺T cells (with the condition of Treg‐polarization) infected with overexpressed miR‐143‐3p lentiviral vector (miR‐143‐3p) and miR‐143‐3p‐knockdown lentiviral vector (sh‐miR‐143‐3p) were identified via RT‐qPCR analyses (n = 3). ***p < .001 by one‐way ANOVA with Dunnett's post‐hoc test. (D) Representative dot plots and the percentage of Treg cells (CD4⁺CD25⁺Foxp3⁺ cells) (with the condition of Treg‐polarization) infected with overexpressed miR‐143‐3p lentiviral vector (miR‐143‐3p) and miR‐143‐3p‐knockdown lentiviral vector (sh‐miR‐143‐3p) were identified via flow cytometry (n = 3). *p < .05, **p < .01 by one‐way ANOVA with Dunnett's post‐hoc test. (E) Typical dot plots and the content of Treg cells (CD4⁺CD25⁺Foxp3⁺ cells) in spleens of CIA animals with miR‐143‐3p mimetic or control mimetic substances were measured by flow cytometry (n = 6). **p < .01 by one‐way ANOVA with Dunnett's post‐hoc test. (F) Foxp3 mRNA expression in the spleen CD4⁺T cells of CIA animals with miR‐143‐3p mimetic or control mimetic substances was identified via RT‐qPCR analyses (n = 6). ***p < .001 by one‐way ANOVA with Dunnett's post‐hoc test. (G) The plasma level of IL‐10 in CIA mice with miR‐143‐3p mimetic or control mimetic substances were measured by ELISA (n = 6). *p < .05, ***p < .001 by one‐way ANOVA with Dunnett's post‐hoc test.

Indeed, we observed dramatic decline in the content of Treg cells in CIA model animals (Figure 4E). Therefore, we explored the roles of miR‐143‐3p in promoting the differentiative activity of Treg cells in CIA mice. Our team realized the over expression of miR‐143‐3p in CIA mice via miR‐143‐3p mimic transfection. As expected, the decreased percentage of Treg cells and the low Expressing levels of Foxp3 and IL‐10 induced by CIA model was partially reversed by overexpressing miR‐143‐3p (Figure 4E–G), which was in accord with the results in vitro. As above mentioned, overexpressed miR‐143‐3p remarkably alleviated the increase of joint inflammation induced by CIA model (Figure 2E,F), revealing that miR‐143‐3p exerts a protective effect on the progression of CIA through promoting Treg cell differentiation.

4. DISCUSSION

RA is a persistent inflammation autoimmunity illness, which induces non‐reversible damage of joints. The effects of Treg cells on the etiopathogenesis are not entirely clear, as the decrease in the quantity of Treg cells in synovium and PB has been delineated recently. ³¹ , ³² , ³³ The main viewpoint in the functions of Treg cells is that they use different pathways to repress effector T‐cell proliferative ability and immunoresponses, including the secretion of antiinflammation cell factors like IL‐10, TGF‐β, and IL‐35. For instance, depleted IL‐10 reporter (IL‐10R) resulted in the selective aberrant regulation of Th17 immunoresponses. ³⁴ Our FCM data also demonstrated a significant decrease of Treg cells in the spleen from CIA animals. And several studies reported that animals with depleted IL‐10 Treg cells could suffer from autoimmune diseases, such as spontaneous colitis. ³⁵ Our data have validated the inverse correlation between plasma IL‐10 and DAS28 scores in the RA patient cohort, suggesting that targeting Treg cells might be a valid and potential method for RA treatment.

MiRNAs playing a vital regulatory role in RA pathogenesis has been previous demonstrated. ³⁶ , ³⁷ , ³⁸ Furthermore, miRNAs have also been associated with T‐cell differentiation and function. ³⁹ Interestingly, results from emerging studies of the Expressing level of miR‐143‐3p in RA sufferers appear to be conflicting, which has been reported to show different expression in different individuals with RA. ¹⁸ , ²⁸ , ²⁹ Hence, our team completed the study and analysis of the relation between miR‐143‐3p and RA activities and explored that the Expressing level of miR‐143‐3p was associated with DAS28 and ESR in a negative manner. We considered that a comparative miR‐143‐3p deficiency exists in RA sufferers. The Expressing level of miR‐143‐3p was increased in some individuals in response to the pathological alterations and could be decreased in severe RA patients. To further illuminate the function of miR‐143‐3p during the RA progress, the overexpression of miR‐143‐3p was conducted with miR‐143‐3p mimetic substance in vivo. It has been displayed that overexpressing miR‐143‐3p could repress RA pathogenesis and joint inflammation to a certain extent. Meanwhile, Pearson's correlative analyses also showed a positive association between the Expressing level of miR‐143‐3p in CD4⁺T cells and plasma IL‐10 contents of RA patients. A recent research has discovered that miR‐143‐3p is related to plasmatic inflammation cell factors IL‐6 in RA and sepsis in a negative manner, ⁴⁰ , ⁴¹ and IL‐6 functions as a critical switch in inhibiting development of TGF‐β‐induced Treg cells. ⁴² Based on the above analyses, it is rational to hypothesize that miR‐143‐3p facilitated the differentiative ability of Treg cells and treated Treg‐deficiency diseases such as RA.

To further investigate the potential mechanisms related to the protective effect of miR‐143‐3p in RA, we verified Treg cells as the critical node of miR‐143‐3p in this function. The elevated expression of miR‐143‐3p was verified to upregulate the mRNA contents of Foxp3 and the content of CD4⁺CD25⁺Foxp3⁺ cells in vitro, revealing that miR‐143‐3p is capable to facilitate Treg cell differentiation. To further illuminate the function of miR‐143‐3p in the differentiative activity of Treg cells during the RA progress, the overexpressed miR‐143‐3p was conducted with synthetic miR‐143‐3p mimics in vivo. The results in this paper corroborated that miR‐143‐3p mimics intervention induced a greater proportion of Treg cells in spleen, along with the higher levels of plasmatic IL‐10 and Foxp3 mRNA in spleen. Those outcomes unveiled that miR‐143‐3p could upregulate the Expressing level of Foxp3 to promote Treg cell differentiation.

Nevertheless, the molecular causal link of the function of miR‐143‐3p in the differentiative activity of Treg cells is still unclear. To reveal the latent causal link of miR‐143‐3p in Treg‐deficiency of RA, our team studied the miRNA database (miRBase at http://www.mirbase.org), which is a highly dependable miRNA dataset to determine latent targets of miR‐143‐3p. ⁴³ , ⁴⁴ With the Target Scan and miRDB miR target forecast kit, our team revealed that Kras, c‐maf, Mapk7, Bmp5, Etv6 might be the miR‐143‐3p targets. We know that the leucine zipper transcriptional factor (c‐maf) can affect the differentiative ability and biofunction of CD4⁺T cells through its unique regulatory mechanism, especially Treg cells. ⁴⁵ It has been recent discovered that the Expressing level of c‐maf was high in intestinal suppressive effector Treg cells (eTreg cells), ⁴⁶ which were pivotal enforcers of the immune balance. Moreover, Treg‐derived IL‐10 generation was c‐maf dependent. ⁴⁷ These evidence indicated that the roles of miR‐143‐3p in Treg cells might be medicated by c‐maf. Further studies are required for the verification.

In conclusion, our results provided the evidence that the Expressing level of miR‐143‐3p in PBMCs is related to RA disease activities in a negative manner. And miR‐143‐3p could be a key modulator of Treg cell differentiative ability to ameliorate CIA symptoms. These results provide a new method to treat Treg‐depletion autoimmunity illnesses like RA.

AUTHOR CONTRIBUTIONS

MY Shen and BP Jiang designed research, performed experiments, analyzed data, and wrote the paper; P Yang, MF Zhang, X Wang, H Zhu, ZN Gu, and XP Zhou contributed significantly to the experiments and data analysis. LL Zhou and Y Lu designed the research and reviewed the manuscript.

FUNDING INFORMATION

This study was financially supported by the National Natural Science Foundation of China (81673937).

CONFLICT OF INTEREST

The authors declare that they have no conflicts of interest.

Shen M‐Y, Jiang B‐P, Zhang M‐F, et al. MicroRNA‐143‐3p ameliorates collagen‐induced arthritis by polarizing naive CD4 ⁺T cells into Treg cells. J Clin Lab Anal. 2023;37:e24845. doi: 10.1002/jcla.24845

Mei‐yu Shen and Bao‐Ping Jiang contributed equally to this work.

Contributor Information

Yan Lu, Email: luyanpr@qq.com.

Ling‐Ling Zhou, Email: zhoulingling@njucm.edu.cn.

DATA AVAILABILITY STATEMENT

The raw data supporting the conclusions of this article will be made available by the corresponding author, without undue reservation.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the corresponding author, without undue reservation.

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[jcla24845-bib-0002] 2. McInnes IB, Schett G. The pathogenesis of rheumatoid arthritis. N Engl J Med. 2011;365(23):2205‐2219. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0003] 3. Sparks JA. Rheumatoid arthritis. Ann Intern Med. 2019;170(1):ITC1‐ITC16. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0004] 4. Srivastava RK, Dar HY, Mishra PK. Immunoporosis: immunology of osteoporosis‐role of T cells. Front Immunol. 2018;9:00657. [DOI] [PMC free article] [PubMed] [Google Scholar]

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[jcla24845-bib-0007] 7. Scheinecker C, Göschl L, Bonelli M. Treg cells in health and autoimmune diseases: new insights from single cell analysis. J Autoimmun. 2020;110:102376. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0008] 8. Notley CA, Ehrenstein MR. The yin and yang of regulatory T cells and inflammation in RA. Nat Rev Rheumatol. 2010;6(10):572‐577. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0009] 9. Xiao XY, Li YT, Jiang X, et al. EZH2 deficiency attenuates Treg differentiation in rheumatoid arthritis. J Autoimmun. 2020;108:102404. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0010] 10. Rubtsov YP, Rasmussen JP, Chi EY, et al. Regulatory T cell‐derived interleukin‐10 limits inflammation at environmental interfaces. Immunity. 2008;28(4):546‐558. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0011] 11. Hori S, Nomura T, Sakaguchi S. Control of regulatory T cell development by the transcription factor Foxp3. Science. 2003;299(5609):1057‐1061. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0012] 12. Krol J, Loedige I, Filipowicz W. The widespread regulation of microRNA biogenesis, function and decay. Nat Rev Genet. 2010;11(9):597‐610. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0013] 13. Lu TX, Rothenberg ME. MicroRNA. J Allergy Clin Immunol. 2018;141(4):1202‐1207. [DOI] [PMC free article] [PubMed] [Google Scholar]

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[jcla24845-bib-0015] 15. Kim D, Nguyen QT, Lee J, et al. Anti‐inflammatory roles of glucocorticoids are mediated by Foxp3 regulatory T cells via a miR‐342‐dependent mechanism. Immunity. 2020;53(3):581‐596. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0016] 16. Scherm MG, Serr I, Zahm AM, et al. MiRNA142‐3p targets Tet2 and impairs Treg differentiation and stability in models of type 1 diabetes. Nat Commun. 2019;10(1):5697. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0017] 17. Xie M, Wang J, Gong W, et al. NF‐κB‐driven miR‐34a impairs Treg/Th17 balance via targeting Foxp3. J Autoimmun. 2019;102:96‐113. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0018] 18. Zhou LL, Zhu YM, Qian FY, Yuan CC, Yuan DP, Zhou XP. MicroRNA‐143‐3p contributes to the regulation of pain responses in collagen‐induced arthritis. Mol Med Rep. 2018;18(3):3219‐3228. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0019] 19. Hwang SM, Sharma G, Verma R, Byun S, Rudra D, Im SH. Inflammation‐induced Id2 promotes plasticity in regulatory T cells. Nat Commun. 2018;9(1):4736. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0020] 20. Brand DD, Latham KA, Rosloniec EF. Collagen‐induced arthritis. Nat Protoc. 2007;2(5):1269‐1275. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0021] 21. Yang P, Qian F, Zhang M, et al. Zishen Tongluo formula ameliorates collagen‐induced arthritis in mice by modulation of Th17/Treg balance. J Ethnopharmacol. 2020;250:112428. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0022] 22. Yang P, Zhang M, Wang X, et al. MicroRNA let‐7g‐5p alleviates murine collagen‐induced arthritis by inhibiting Th17 cell differentiation. Biochem Pharmacol. 2020;174:113822. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0023] 23. Seeuws S, Jacques P, van Praet J, et al. A multiparameter approach to monitor disease activity in collagen‐induced arthritis. Arthritis Res Ther. 2010;12(4):R160. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0024] 24. de Molon RS, Thurlings RM, Walgreen B, et al. Systemic Resolvin E1 (RvE1) treatment does not ameliorate the severity of collagen‐induced arthritis (CIA) in mice: a randomized, prospective, and controlled proof of concept study. Mediat Inflamm. 2019;2019:5689465. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0025] 25. Kang LJ, Kwon ES, Lee KM, et al. 3'‐Sialyllactose as an inhibitor of p65 phosphorylation ameliorates the progression of experimental rheumatoid arthritis. Br J Pharmacol. 2018;175(23):4295‐4309. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0026] 26. Bai Y, Li Y, Marion T, et al. Resistant starch intake alleviates collagen‐induced arthritis in mice by modulating gut microbiota and promoting concomitant propionate production. J Autoimmun. 2021;116:102564. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0027] 27. Jin S, Sun S, Ling H, et al. Protectin DX restores Treg/T17 cell balance in rheumatoid arthritis by inhibiting NLRP3 inflammasome via miR‐20a. Cell Death Dis. 2021;12(3):280. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0028] 28. Stypinska B, Wajda A, Walczuk E, et al. The serum cell‐free microRNA expression profile in MCTD, SLE, SSc, and RA patients. J Clin Med. 2020;9:9010161. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0029] 29. Yang Z, Wang J, Pan Z, Zhang Y. miR‐143‐3p regulates cell proliferation and apoptosis by targeting IGF1R and IGFBP5 and regulating the Ras/p38 MAPK signaling pathway in rheumatoid arthritis. Exp Ther Med. 2018;15(4):3781‐3790. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0030] 30. Miyoshi M, Liu S. Collagen‐induced arthritis models. Methods Mol Biol. 2018;1868:3‐7. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0031] 31. Sun H, Gao W, Pan W, et al. Tim3 Foxp3 Treg cells are potent inhibitors of effector T cells and are suppressed in rheumatoid arthritis. Inflammation. 2017;40(4):1342‐1350. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0032] 32. Zhang X, Zhang X, Zhuang L, et al. Decreased regulatory T‐cell frequency and interleukin‐35 levels in patients with rheumatoid arthritis. Exp Ther Med. 2018;16(6):5366‐5372. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0033] 33. Vitales‐Noyola M, Layseca‐Espinosa E, Baranda L, et al. Analysis of sodium chloride intake and Treg/Th17 lymphocytes in healthy individuals and patients with rheumatoid arthritis or systemic lupus erythematosus. J Immunol Res. 2018;2018:9627806. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0034] 34. Diefenhardt P, Nosko A, Kluger MA, et al. IL‐10 receptor signaling empowers regulatory T cells to control Th17 responses and protect from GN. J Am Soc Nephrol. 2018;29(7):1825‐1837. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0035] 35. Jofra T, Galvani G, Cosorich I, et al. Experimental colitis in IL‐10‐deficient mice ameliorates in the absence of PTPN22. Clin Exp Immunol. 2019;197(3):263‐275. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0036] 36. Donate PB, Alves de Lima K, Peres RS, et al. Cigarette smoke induces in Th17 cells that enhance osteoclastogenesis in inflammatory arthritis. Proc Natl Acad Sci U S A. 2021;118(1):e2017120118. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0037] 37. Evangelatos G, Fragoulis GE, Koulouri V, Lambrou GI. MicroRNAs in rheumatoid arthritis: from pathogenesis to clinical impact. Autoimmun Rev. 2019;18(11):102391. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0038] 38. Zhang L, Wu H, Zhao M, Chang C, Lu Q. Clinical significance of miRNAs in autoimmunity. J Autoimmun. 2020;109:102438. [DOI] [PubMed] [Google Scholar]

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[jcla24845-bib-0040] 40. Zhou J, Chaudhry H, Zhong Y, et al. Dysregulation in microRNA expression in peripheral blood mononuclear cells of sepsis patients is associated with immunopathology. Cytokine. 2015;71(1):89‐100. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0041] 41. Hong B‐K, You S, Yoo S‐A, et al. MicroRNA‐143 and ‐145 modulate the phenotype of synovial fibroblasts in rheumatoid arthritis. Exp Mol Med. 2017;49(8):e363. [DOI] [PMC free article] [PubMed] [Google Scholar]

[jcla24845-bib-0042] 42. Bettelli E, Carrier Y, Gao W, et al. Reciprocal developmental pathways for the generation of pathogenic effector TH17 and regulatory T cells. Nature. 2006;441(7090):235‐238. [DOI] [PubMed] [Google Scholar]

[jcla24845-bib-0043] 43. Kozomara A, Birgaoanu M, Griffiths‐Jones S. miRBase: from microRNA sequences to function. Nucleic Acids Res. 2019;47(D1):D155‐D162. [DOI] [PMC free article] [PubMed] [Google Scholar]

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