Multiple sclerosis (MS) is a chronic autoimmune disease where activated immune cells can attack oligodendrocytes causing damage to the myelin sheath. Several molecular mechanisms are responsible for the auto-activation of immune cells such as RNA interference (RNAi) through microRNAs (miRNAs or miRs). In the present study, the role of miR-155 in regulating CD8+ T-cell activity in patients with relapsing-remitting multiple sclerosis (RRMS) was investigated, in terms of its migratory functions with regard to intracellular adhesion molecule-1 (ICAM1) and integrin subunit β2 (ITGB2), and its cytotoxic proteins, perforin and granzyme B. Gene expression of miR-155, ICAM1, ITGB2, perforin and granzyme B was evaluated following epigenetic modulations using reverse transcription-quantitative polymerase chain reaction in CD8+ T-cells isolated from blood samples of patients with RRMS and compared to healthy controls. The ectopic expression of miR-155 resulted in a persistent downregulation in all genes of interest related to CD8+ T-cell activation that were positively correlated with the Expanded Disability Status Scale of patients. The present study revealed the interplay between miR-155, ICAM1, and ITGB2, shedding light on their beneficial use as possible therapeutic regulators and diagnostic biomarkers of disease. Moreover, epigenetic modulations enhancing the efficacy of disease-modifying therapies (DMTs) may be employed as personalized therapy, to decrease the side effects of DMTs and improve the outcomes of patients.
Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system (CNS), characterized by recurrent episodes of inflammatory demyelination resulting in damage of axons present in the brain, optic nerve, and spinal cord (
Disease pathogenesis is known to be initiated through the activation of peripheral B and T-cells towards self-antigens resulting in damage to the myelin sheath and nerve block (
Unfortunately, current immunomodulatory approaches have severe side effects and complications for the patients, since they become more prone to infections due to immune response suppression (
A promising therapeutic approach is personalized therapy, that could be achieved through the use of RNA interference, which involves gene silencing at the messenger RNA (mRNA) level mediated by small complementary non-coding RNA species such as small interfering RNAs (siRNAs) or microRNAs (miRNAs or miRs) (
Blood samples were collected from 25 patients with RRMS and 10 healthy controls, according to the inclusion and exclusion criteria. Patients diagnosed with RRMS, without treatment with steroids in the past 3 months, were included in the present study. Patients were recruited from May 2019 to May 2020. The mean age of patients was 39.12 years with an age range of 28-55 years, while the mean age of controls was 30.3 years with an age range of 24-50 years. All subjects involved provided their written informed consent, and the Ethics Review Committee of the German University in Cairo (Cairo, Egypt) approved the study (approval no. PTX-2018-11-HET). The study followed the ethical guidelines of the 1975 Declaration of Helsinki. PBMCs were isolated from whole blood using Ficoll density gradient technique. All samples were stored at -80˚C until further use. The clinical characteristics of patients and controls are presented in
PBMCs were isolated using Ficoll (Greiner Bio-One International GmbH), as per the manufacturer's instructions. Harvested cells were washed twice in Roswell Park Memorial Institute Medium-1640 (RPMI-1640; cat. no. SR263-10L; Serox GmbH) supplemented with L-glutamine, phenol red, 10% fetal bovine serum (FBS; cat. no. 10270098) and 1% penicillin/streptomycin (cat. no. 15140122; both from Applied Biosystems; Thermo Fisher Scientific, Inc.), and viable cells were counted using a hemocytometer. Cells were frozen at -80˚C at a density of 107 cells/ml in 50% v/v supplemented media, 40% v/v FBS and 10% v/v dimethyl sulfoxide (DMSO; cat. no. D12345; Applied Biosystems; Thermo Fisher Scientific, Inc.) for later use. Samples were stored at -80˚C for a maximum of 6 months and after thawing, viability was verified using 0.4% Trypan blue (cat. no. 15250061; Thermo Fisher Scientific, Inc.) with an acceptable viability of >80%.
Frozen PBMCs were thawed at 37˚C and transferred to 10 ml of supplemented media and centrifuged at 300 x g for 5 min at room temperature. Cells were isolated to obtain CD8+ T-cells by negative depletion using MojoSort™ Human CD8+ T-cell Isolation Kit (cat. no 480012), MojoSort Buffer (cat. no 480017) and MojoSort Magnet (cat. no 480019; all Biolegend, Inc.) as per manufacturer's instructions. Collected pure CD8+ T-cells were centrifuged (at 300 x g for 5 min at room temperature) and re-suspended in culture media.
Confirmation of CD8+ T-cell isolation was performed using flow cytometry on the isolated population, and CD8-PE antibody (product no. IM0452U; Beckman Coulter, Inc.) for 30 min at room temperature, followed by a washing step and acquisition. Samples were analyzed by flow cytometry (CytoFLEX benchtop flow cytometer; Beckman Coulter Inc.) gating for the CD8-PE-positive population. Fluorescence data were acquired and analyzed using the CytExpert software (version 2.3.3.84; Beckman Coulter Inc.) to determine the purity of the sample, as shown in
Isolated CD8+ T-cells were incubated in supplemented media at 37˚C with an atmosphere of 5% CO2 and 95% humidity. The cultured cells were then screened for miR-155, ICAM1, ITGB2, perforin, and granzyme B expression.
Before transfection, seeding of 4-7x104 isolated CD8+ T-cells per well of a 96-well plate was performed. The cells were incubated under normal growth conditions (37˚C and 5% CO2). Isolated CD8+ T-cells were transfected for 5-10 min at room temperature, with mimics of miR-155 (syn-hsa-miR-155-5p miScript miRNA mimic; cat. no. MSY0000646) and antagomirs of miR-155 (anti-hsa-miR-155-5p miScript miRNA inhibitor; cat. no. MIN0000646), along with both siRNAs of ICAM1 (Hs_ICAM1_3 FlexiTube siRNA; cat. no. SI00004347) and ITGB2 (Hs_ITGB2_3 FlexiTube siRNA; cat. no. SI00004571; all from Qiagen GmbH), in addition to a negative control. The mass of miR-155 mimics and antagomirs, as well as all siRNAs including all negative controls was 250 ng. The negative controls for miRNA mimics and antagomirs were purchased from Invitrogen; Thermo Fisher Scientific, Inc. (cat. nos. AM17110 and AM17010, respectively) and transfected similar to miR-155 mimics and antagomirs. The negative control for siRNA was purchased from Qiagen GmbH (cat. no. 1022076) and was transfected similarly to ICAM1 and ITGB2 siRNA. All transfection experiments were performed in triplicate using HiPerfect Transfection Reagent (cat. no. 301704; Qiagen GmbH) according to the manufacturer's instructions, and experiments were repeated three times. Cells exposed to transfection reagent only were designated as mock cells, cells transfected with miR-155 mimics and antagomirs were designated as mimics and antagomirs, respectively, and cells transfected with ICAM1 and ITGB2 siRNA were designated as siICAM1 and siITGB2 cells. Negative controls transfected with pre-miR negative control, anti-miR negative control and negative control siRNA were designated as pre-miR NC, anti-miR NC and siRNA NC, respectively. siRNA NC was not utilized in silencing experiments as it is widely interchanged with pre-miRNA negative controls (as they have the same makeup), hence the data obtained from the pre-miRNA were proof enough. This was followed by RNA extraction, screening for miR-155, ICAM1, ITGB2, perforin, and granzyme B expression, and finally, comparison to CD8+ T-cell mock cells, 48 h after transfection.
RNA was isolated from cultured CD8+ T-cells using RNeasy Minikit (cat. no. 74104; Qiagen GmBH) as per the extraction protocol. RNA was stored at -80˚C until further use. RNA concentration was calculated using Nanodrop and RNA purity was evaluated using A260/280 with an acceptable range of 1.9-2.2. Total RNA used per sample was 30-50 ng.
Total RNA extracted was reverse-transcribed into single-stranded cDNA using the high-capacity cDNA reverse transcription kit (cat. no. 4368814; Applied Biosystems; Thermo Fisher Scientific, Inc.). The relative expression of ICAM1, ITGB2, perforin and granzyme B, with β-actin (as a housekeeping gene for normalization), along with miR-155 and RNU6 (as a housekeeping gene for normalization) was quantified and amplified using TaqMan RT-quantitative polymerase chain reaction (qPCR; Assay IDs: Hs00164932_m1, Hs00164957_m1, Hs00169473_m1, Hs00188051_m, and Hs99999903_m1 respectively for genes of interest along with 002623 and 001093 for miR-155 and RNU6, respectively; Applied Biosystems; Thermo Fisher Scientific, Inc.) on a StepOne™ Real-Time PCR instrument (Applied Biosystems; Thermo Fisher Scientific, Inc.). For every sample, a reaction mix was prepared according to the manufacturer's instructions, and 4 µl of the respective cDNA was added. The RT-qPCR run was performed in the standard mode, consisting of two stages: A first 10-min stage at 95˚C where the Taq-polymerase enzyme was activated, followed by a second stage of 40 amplification cycles (15 sec at 95˚C and 60 sec at 60˚C). qPCR runs with negative controls as undetermined were taken into account, relative expression was calculated using the 2-ΔΔCq method (
All data were expressed in relative quantitation (RQ). One Way ANOVA was employed, followed by Dunnett's multiple comparison test to compare the basal expression of two different studied groups. Unpaired t-test was used to compare the effect of manipulations within each group (compared to mock). Data were expressed as the mean ± standard error of the mean (SEM). Correlation analyses were performed using Spearman's correlation coefficient, denoted by a rho value, indicating that when the strength of the correlation approaches 1, the degree of correlation increases. Analysis was performed using GraphPad Prism 6.0 software (GraphPad Software, Inc.). All experiments were performed in triplicate. P<0.05 was considered to indicate a statistically significant difference.
Target prediction was performed using Tools for miRs (
First, to understand the relationship between miR-155 and the genes of interest, bioinformatics studies were performed and interactions between miR-155 and genes of interest were found and reported in
Secondly, to understand the relationship between ICAM1, ITGB2 with miR-155, perforin, and granzyme B, the effect of ICAM1 and ITGB2 knockdown on the expression of miR-155, perforin and granzyme B was investigated. Efficient knockdown of ICAM1 and ITGB2 was confirmed as shown in
In a previous study, correlation analyses revealed a positive correlation between miR-155 and ITGB2 with the EDSS of patients and a negative correlation between ICAM1, perforin, and granzyme B with the EDSS (
MS is a chronic neuroinflammatory disease and considered one of the leading causes of disability worldwide. Due to the heterogeneity of the disease, an optimized targeted therapeutic approach is required to achieve efficient treatments for the diverse subpopulations of the disease. Molecular proteins of interest to regulate are CD8+ T-cell surface receptors, ICAM1 and ITGB2, along with cytotoxic proteins produced by the cells, perforin and granzyme B (
Prior to investigating the role of miR-155 in the regulation of crucial proteins for CD8+ T-cells, a screening step for the basal expression levels of miR-155, ICAM1, ITGB2, perforin, and granzyme B in CD8+ T-cells was performed to identify the endogenous levels of these genes. Significant downregulation of miR-155 was observed in CD8+ T-cells of patients with RRMS (
The role of miR-155 on CD8+ T-cell auto-activity and cytotoxicity was studied by
Furthermore, the role of ICAM1 and ITGB2 in the regulation of cytolytic proteins perforin and granzyme B as well as miR-155, was investigated. The silencing of ICAM1 and ITGB2 induced significant downregulation of miR-155 compared to the mock group in all patients with RRMS and healthy controls (
As aforementioned, ICAM1 expression on antigen-presenting cells or T lymphocytes is crucial for antigen-specific interactions leading to CD8+ T-cell activation, proliferation, and differentiation into effector T-cells (
Interestingly, ICAM1 silencing caused similar changes to miR-155 overexpression and miR-155 overexpression caused a decrease in ICAM1 expression in all treated subtypes which suggests that the modulations observed with miR-155 overexpression could be due to ICAM1 downregulation rather than miR-155 manipulation. This indicates that ICAM1 may have a dominant effect in modulating the aforementioned target genes in CD8+ T-cells of treated patients with MS. For further insight, it was also examined whether the disease state affects the manipulation outcomes, hence the same manipulations on CD8+ T-cells isolated from healthy controls were performed. The genetic and epigenetic manipulations performed caused similar outcomes in all diseased cells and healthy controls cells with two exceptions. First, the upregulation of ICAM1 in untreated naïve patients following miR-155-mimic transfection (
Relating the experimental data obtained to the clinical data of the patients was intriguing, hence, correlation studies between mRNA expression of miR-155, target genes, and the EDSS of the patients were carried out. The positive correlation between miR-155, ITGB2, and EDSS, and the negative one with ICAM1, perforin, and granzyme B, determined in a previous study by the authors, could be further exploited to enhance the use of these molecules as biomarkers for diagnostic and prognostic purposes (
Considering the multi-target influence afforded by a single miRNA, it is reasonable to hypothesize that studies directed at establishing the effect of drugs on miRNA gene expression could disclose possible unrevealed, to date, modes of action of drugs (
In conclusion, the
The authors acknowledge the German University in Cairo (Cairo, Egypt) for providing the required facilities to conduct the research work.
Data is contained within the article or supplementary material. The data presented in this study are available in
AAE carried out all the experiments, analyzed the data and contributed to the writing of the manuscript. DAZ is the clinical neurologist who provided all samples and clinical data, and contributed to the data acquisition and revision of manuscript drafts. HMET is the principal investigator and the main supervisor of this research work, and contributed to the conception and design of the work, revising and approving the drafts and final version of the manuscript. AAE and HMET confirm the authenticity of all the raw data. All authors read and approved the final manuscript.
The present study was conducted according to the guidelines of the Declaration of Helsinki, and approved (approval no. PTX-2018-11-HET) by Ethics Committee of the German University in Cairo (Cairo, Egypt). All subjects involved provided their written informed consent.
Not applicable.
The authors declare that they have no competing interests.
Effect of miR-155 overexpression and knockdown on the mRNA levels of ICAM1, ITGB2, perforin, and granzyme B in CD8+ T-cells isolated from different treatment groups of patients with relapsing-remitting multiple sclerosis and healthy controls. (A-D) Effect of miR-155 overexpression and knockdown on the mRNA levels of (A) ICAM1, (B) ITGB2, (C) perforin and (D) granzyme B compared to the mock group. *P<0.05, **P<0.01 and ***P<0.001. Data are presented as the mean ± standard error of the mean. miR-155, microRNA-155; ICAM1, intracellular adhesion molecule-1; ITGB2, integrin subunit β2; RRMS, relapsing-remitting multiple sclerosis; NC, negative control.
Effect of ICAM1 and ITGB2 knockdown on the mRNA levels of miR-155, ITGB2, perforin, and granzyme in CD8+ T-cells isolated from different treatment groups of patients with relapsing-remitting multiple sclerosis and healthy controls. (A-D) Effect of ICAM1 and ITGB2 knockdown on the mRNA levels of (A) miR-155, (B) ITGB2, (C) perforin and (D) granzyme B compared to the mock groups. *P<0.05, **P<0.01 and ***P<0.001. Data are presented as the mean ± standard error of the mean. ICAM1, intracellular adhesion molecule-1; ITGB2, integrin subunit β2; miR-155, microRNA-155; siRNA or si, small interfering RNA; NC, negative control; RRMS, relapsing-remitting multiple sclerosis; ns, not significant.
Correlation analysis between the relative expression of target genes following miR-155 overexpression, normalized to the mock groups, and the EDSS score of patients, determined using Spearman's correlation coefficient. (A-D) Correlation between the effect of miR-155 overexpression on (A) ICAM1, (B) ITGB2, (C) perforin and (D) granzyme B expression, as the RQ values of each gene normalized to the mock groups in CD8+ T-cells isolated from patients with relapsing-remitting multiple sclerosis, and the EDSS score of patients. Correlation analysis was performed using Spearman's correlation coefficient, and the rho values and P-values are presented in each graph. miR-155, microRNA-155; ICAM1, intracellular adhesion molecule-1; ITGB2, integrin subunit β2; EDSS, Expanded Disability Status Scale.
Summary of the regulatory roles of miR-155 mimics, siICAM1 and siITGB2 on ICAM1, ITGB2, perforin and granzyme B. The inhibitory effect of miR-155 on ICAM1, ITGB2, perforin and granzyme B, as well as that of siICAM1 on miR-155, ITGB2, perforin and granzyme B, and that of siITGB2 on miR-155 and perforin is illustrated. Created by Biorender. miR-155, microRNA-155; si, small interfering RNA; ICAM1, intracellular adhesion molecule-1; ITGB2, integrin subunit β2.
Characteristics of patients and healthy controls.
A, Patients (n=25) | Percentage (%) |
---|---|
Sex | |
Female (17/25) | 68 |
Male (8/25) | 32 |
Age | |
<50 years old (22/25) | 88 |
≥50 years old (3/25) | 12 |
Family history | |
Positive family history (1/25) | 4 |
Negative family history (24/25) | 96 |
Type | |
RRMS (15/25) | 100 |
PRMS (0/25) | 0 |
PPMS (0/25) | 0 |
SPMS (0/25) | 0 |
CSF findings | |
+ve Oligoclonal antibodies (25/25) | 100 |
Protein (0/25) | 0 |
Treatment | |
Untreated (naïve) (3/25) | 12 |
DMT-treated (22/25) | 88 |
IFNβ-1a (6/25) | 24 |
IFNβ-1b (6/25) | 24 |
Fingolimod (10/25) | 40 |
B, Controls (n=10) | Percentage (%) |
Sex | |
Female (7/10) | 70 |
Male (3/10) | 30 |
Age | |
<50 years old (9/10) | 90 |
≥50 years old (1/10) | 10 |