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Open Access

Peer-reviewed

Research Article

Crosstalk between MIR-96 and IRS/PI3K/AKT/VEGF cascade in hRPE cells; A potential target for preventing diabetic retinopathy

  • Zeynab Hosseinpoor,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing – original draft, Writing – review & editing

    Affiliation Department of Molecular Medicine, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran

    ⨯
  • Zahra-Soheila Soheili ,

    Roles Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Writing – review & editing

    soheili@nigeb.ac.ir

    Affiliation Department of Molecular Medicine, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran

    ⨯
  • Maliheh Davari,

    Roles Investigation, Methodology, Writing – review & editing

    Affiliation Department of Molecular Medicine, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran

    ⨯
  • Hamid Latifi-Navid,

    Roles Methodology, Software, Writing – review & editing

    Affiliations Department of Molecular Medicine, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran, Electrophysiology Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran, School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran

    ⨯
  • Shahram Samiee,

    Roles Methodology, Resources, Supervision, Validation

    Affiliation Blood Transfusion Research Center High Institute for Research and Education in Transfusion Medicine, Tehran, Iran

    ⨯
  • Dorsa Samiee

    Roles Software, Writing – review & editing

    Affiliation Department of Computer Science, Royal Holloway University of London, Egham, Surrey, United Kingdom

    ⨯

Abstract

Regulation of visual system function demands precise gene regulation. Dysregulation of miRNAs, as key regulators of gene expression in retinal cells, contributes to different eye disorders such as diabetic retinopathy (DR), macular edema, and glaucoma. MIR-96, a member of the MIR-183 cluster family, is widely expressed in the retina, and its alteration is associated with neovascular eye diseases. MIR-96 regulates protein cascades in inflammatory and insulin signaling pathways, but further investigation is required to understand its potential effects on related genes. For this purpose, we identified a series of key target genes for MIR-96 based on gene and protein interaction networks and utilized text-mining resources. To examine the MIR-96 impact on candidate gene expression, we overexpressed MIR-96 via adeno-associated virus (AAV)-based plasmids in human retinal pigment epithelial (RPE) cells. Based on Real-Time PCR results, the relative expression of the selected genes responded differently to overexpressed MIR-96. While the expression levels of IRS2, FOXO1, and ERK2 (MAPK1) were significantly decreased, the SERPINF1 gene exhibited high expression simultaneously. pAAV-delivered MIR-96 had no adverse effect on the viability of human RPE cells. The data showed that changes in insulin receptor substrate-2 (IRS2) expression play a role in disrupted retinal insulin signaling and contribute to the development of diabetic complications. Considered collectively, our findings suggest that altered MIR-96 and its impact on IRS/PI3K/AKT/VEGF axis regulation contribute to DR progression. Therefore, further investigation of the IRS/PI3K/AKT/VEGF axis is recommended as a potential target for DR treatment.

Citation: Hosseinpoor Z, Soheili Z-S, Davari M, Latifi-Navid H, Samiee S, Samiee D (2024) Crosstalk between MIR-96 and IRS/PI3K/AKT/VEGF cascade in hRPE cells; A potential target for preventing diabetic retinopathy. PLoS ONE 19(9): e0310999. https://doi.org/10.1371/journal.pone.0310999

Editor: Partha Mukhopadhyay, National Institutes of Health, UNITED STATES OF AMERICA

Received: November 13, 2023; Accepted: September 10, 2024; Published: September 30, 2024

Copyright: © 2024 Hosseinpoor et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript.

Funding: The National Institute of Genetic Engineering and Biotechnology has allocated Grant 727 to this research project following proposal evaluation and review. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

microRNAs (miRNAs) are a class of small non-coding RNAs that influence gene expression patterns of cellular pathways and regulate diverse biological processes in this way. Their interaction with specific sequences in target mRNAs mediates post-transcriptional gene regulation. Recent studies have revealed that in addition to gene silencing, miRNAs can also activate gene expression through particular pathways [1, 2]. They play a leading role in developmental, functional, and pathological conditions in the retina [3]. The microRNA-183 cluster is a prominent family among the most frequently reported miRNAs in the retina, comprising MIR-183, MIR-96, and MIR-182. During retinal development, members of the MIR-183 cluster are overexpressed as a single transcript and regulate different target genes involved in cellular pathways [4]. Given their pivotal roles, altered expression of the MIR-183 cluster has been shown to be linked to a variety of human diseases, including diabetes and diabetic vascular complications [5, 6]. miRNA microarray analysis indicated that the MIR-96 level increased in the retinas of streptozotocin-induced diabetic rats [7]. However, the MIR-96 expression level was significantly downregulated in the serum of type 2 diabetes patients compared with normal controls [8]. A few studies have explored the potential involvement of miR-96 in the development and progression of diabetic retinopathy (DR). However, the exact mechanisms by which miR-96 influences the development of DR remain unclear and require further investigation. A recent study has investigated how the target genes regulated by miR-96 are connected to the signaling pathways associated with DR [9]. Diabetic retinopathy, as one of the most common microvascular complications of diabetes, remains a dominant cause of visual impairments in diabetic patients. In the early stages of DR, the hyperglycemic condition contributes to vasodilation and increased retinal metabolism, pericyte apoptosis, microaneurysm, and eventually retinal microvascular damage. Advanced stages of DR, characterized mainly by neovascularization, culminate in severe vision impairments due to vitreous hemorrhage or detachment of the retina [10, 11]. Altered retinal metabolism and elevated levels of inflammatory molecules affect multiple parts of the retina, including the vascular network, neuronal cells, choroid, and retinal pigment epithelium (RPE) [12]. RPE cells secrete several growth factors and cytokines, including vascular endothelial growth factor (VEGF), pigment epithelium-derived factor (PEDF), monocyte chemoattractant protein-1 (MCP-1), interleukin-6 and 8 (IL-6, IL-8), and matrix metalloproteinase (MMPs). Studies have shown that high glucose exposure modifies the RPE proteome and secretome and can cause alterations in cell structure and function [13].

Recent studies have identified signaling pathways involved in DR development and progression. The most known pathways are insulin signaling, VEGF signaling, IL-6 signaling, and PI3K-AKT signaling pathways [14]. According to the latest research, MIR-96, as well as other regulatory factors is involved in the control of signaling molecules. For instance, upregulation of MIR-96 leads to insulin signaling impairment through relevant repressing signaling molecules such as insulin receptor (INSR) and insulin receptor substrate-1 (IRS1) [15, 16]. IRS proteins are cytoplasmic receptors involved in insulin action by activating the phosphoinositide 3-kinase (PI3K)/AKT pathway. Studies showed that IRS2 is implicated in type 2 diabetes, and its expression is upregulated in DR mouse models [17, 18]. A previous study suggested activating the PI3K/AKT pathway upregulates VEGF expression in vascular cells [18, 19]. Moreover, a new study determined that MIR-96 acts as a modulator of multiple angiogenic factors, including VEGF, ANG2, and VEGFR2, during pathological conditions in the retina [20]. These suggest that the IRS/PI3K/AKT axis could be counted as a possible target in DR prevention and control.

Considering the involvement of the MIR-96 target genes in specific signaling pathways, the present study was designed to achieve an understanding of MIR-96’s roles in molecular alterations in the retina. To that end, MIR-96 target genes were provided using four miRNA target prediction online databases, including TargetScanHuman 8.0, miRTarBase 9.0, miRDB, and miRWalk 3. The results of three of these databases include predicted miRNA targets using bioinformatics tools. MiRTarBase 9.0 provides miRNA targets with a higher confidence level validated experimentally by reporter assay, western blot, microarray, and next-generation sequencing experiments. The main signaling pathways linked to MIR-96 were identified using mirPath. By analyzing the data of the marked target genes in enriched KEGG pathway maps provided by DIANA-mirPath, the top co-expressed genes were determined utilizing GeneMANIA. In addition, the functional association network was acquired from the STRING online database. Taken together, the results provided a ranked list of genes to investigate the effects of MIR-96 overexpression in human RPE cells.

Materials and methods

In silico target research

To establish a comprehensive understanding of the target interactions for MIR-96, the in silico target research was conducted using multiple prediction tools and databases. In silico target prediction for MIR-96 was done using TargetScan 8.0 (http://www.targetscan.org/vert_80/) [21], miRDB (http://mirdb.org/) [22], miRTarBase 9.0 (https://mirtarbase.cuhk.edu.cn/) [23], and miRWalk 3 (http://mirwalk.umm.uni-heidelberg.de/) [24]. Top-scored genes were identified and integrated with literature search and text mining results obtained from the EVEX database (http://evexdb.org/) [25]. Subsequently, the resulting gene list was introduced to STRING 11.5 (https://string-db.org/) [26], and the functional interactions among identified proteins were visualized using the Cytoscape stringApp (version 3.9.1) [27].

The miRNA-pathway interactions were predicted using DIANA mirPath v.3 (https://dianalab.e-ce.uth.gr/html/mirpathv3/index.php?r=mirpath) [28], and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enriched terms were identified through Metascape website (http://metascape.org/) [29]. In addition, the DisGeNET database (https://www.disgenet.org/) [30–32] was explored to retrieve DR-associated genes, and the gene-disease associations (GDA) network was visualized using the DisGeNET Cytoscape app [33]. This database covers a wide range of diseases and can be a valuable resource for studies on genes associated with human diseases. Fig 1 illustrates a schematic overview of the bioinformatic tools conducted in this study.

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Fig 1. A schematic overview of the bioinformatic tools conducted in this study.

GDA = Gene-Disease Associations.

https://doi.org/10.1371/journal.pone.0310999.g001

Vector constructs

Following the procedure of the Molecular Cloning Laboratory Manual [34], genomic DNA was isolated from hRPE cells. The MIR-96 sequence was amplified from genomic DNA using polymerase chain reaction (PCR) (primer sequences: 5′- CGGGGTACCACCGAAGGGCCATAAACAGA - 3ˊ (Forward), and 5ˊ- CTAGCTCGAGAGTGTAAGGCGATCTGGCT - 3ˊ (Reverse)). Extra base pairs were added to 5ˊ end of the primers to increase the cleavage efficiency of restriction enzymes. The purified PCR product was digested with XhoI and KpnI restriction enzymes and inserted into the pAAV-MCS (a human AAV-2 vector included in the AAV Helper-Free System designed by ©Agilent Technologies, USA) that had been previously manipulated in our lab to incorporate the enhanced green fluorescent protein (eGFP)-intron cassette [35]. Thereafter, Escherichia coli XL10 bacteria (Agilent, USA) was transformed by the ligation product by the heat shock method. Bacterial clones comprising MIR-96 were identified using plasmid mini-preparation and digestion. Subsequently, the sequences of MIR-96 and eGFP-intron fragments were verified using DNA sequencing analysis (Bioneer Corporation, South Korea). The pAAV-MCS-eGFP-int was also employed as a control vector.

Human RPE cell culture and transfection

The human RPE (hRPE) cell line used in the present study was derived from the previously isolated, characterized, and established HRPE-2S cell line [36]. The cells were cultured in DMEM/F-12 mixture (Gibco, Thermo Fisher Scientific, USA) supplemented with 10% fetal bovine serum (FBS, Biowest, France), penicillin (64 μg/ml), and streptomycin (100 μg/ml) in T25 culture flasks (SPL Life Science, Korea). Cells were incubated in a humidified 37 ˚C incubator with 5% CO2 (Binder, USA). For transfections, hRPE cells were seeded in a six-well plate (SPL Life Science, Korea). After 24 hours (60–70% confluency), the cells were transfected with the MIR-96 expression vector by the calcium phosphate-mediated transfection method. For each well, 5 μg of the desired plasmid was added to sterile ddH2O and CaCl2 2M. The CaCl2/DNA mix was added dropwise to an equal amount of HBS 2X (HEPES Buffered Saline) while vortexing. Twenty minutes post-incubation at room temperature, the transfection mixture, containing calcium phosphate-DNA particles was added dropwise and evenly over the cell culture medium. After 6 hours, the medium was replaced with fresh DMEM/F-12 + 10% FBS, and the cells were harvested 72 hours later for further experiments.

RNA extraction and RT-qPCR analysis

Total RNA was isolated from both transfected and control hRPE cell cultures (which were transfected by pAAV-MIR-96-eGFP-int or pAAV-MCS-eGFP-int cassette as control) using TriPure Isolation Reagent (Roche, Germany). Mature MIR-96 expression was quantified following the stem-loop reverse transcription-quantitative polymerase chain reaction (RT-qPCR) procedure [37]. Initially, RNA samples were reversely transcribed by a specific stem-loop primer using the Moloney murine leukemia virus (MMLV) enzyme (Qiagen Inc., USA), then the synthesized complementary DNA (cDNA) was used as a template to amplify MIR-96 with a specific forward primer and a universal reverse primer. The Real-Time PCR program was as follows: 15 min at 95 ˚C for activation, 15 s at 95 ˚C, and 60 s at 60 ˚C for 45 cycles. The expression level of MIR-96 transcripts was normalized to the expression level of RNU48 as endogenous control. To quantify gene expression in transfected hRPE cells, RNA samples were reversely transcribed to cDNAs, using a mixture of oligo (dT) and random hexamer primers and reverse transcriptase (Qiagen Inc., USA). Real-time PCR was performed with QuantiFast SYBR® Green PCR Kit (Qiagen, Germany, Catalog no. 204143) master mix and specific primer pairs of the genes, using Taq DNA polymerase (Qiagen Inc., USA). The utilized Real-Time PCR program was as follows: 10 min at 95 ˚C for activation, 15 s at 95 ˚C, and 60 s at 60 ˚C for 45 cycles. The expression level of genes was normalized to the expression level of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as a verified housekeeping gene. The 2- ΔΔCT method was used to calculate and analyze relative changes in gene expression for both the control and MIR-96-transfected groups. The relative expression of each gene in the transfected group was reported compared to the control group. The results are representative of at least three independent experiments with three replicates.

Cell viability assay (MTT)

Cellular metabolic activity, an indicator of cell viability, proliferation, and cytotoxicity was assayed in transfected hRPE cells (pAAV-MIR-96-eGFP-int, and control pAAV-MCS-eGFP-int transfected hRPE cells) compared to non-transfected control. Both transfected and non-transfected cells were seeded at a density of 1 × 105 cells per well in 96-well plates (SPL Life Science, Korea). Following overnight incubation at 37 ˚C, the cells were treated with 10 μl 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) (5 mg/ml, Sigma-Aldrich, USA). After 4 hours, the medium containing MTT was gently removed, and 100 μl dimethyl sulfoxide (DMSO) (Sigma-Aldrich, USA) was added to each well to dissolve formazan crystals. Thereafter, cell viability was determined by measuring optical density at 580 nm using a microplate reader. Non-transfected hRPE cells were considered for normalizing absorbance data.

Statistical analysis

All transfections were independently done at least three times. RT-qPCR was performed in three independent experiments with three replicates in each experiment. Significant statistical differences were evaluated by one-way (to compare the relative expression levels among the candidate genes) and two-way (to assess the changes in gene expression at different time points) analysis of variance (ANOVA). Statistical analyses were carried out using GraphPad Prism version 8.0.1 (GraphPad Software, San Diego, California USA, www.graphpad.com). The data were reported as the mean ± standard error of the mean, and P values less than 0.05 were considered statistically significant.

Results

Bioinformatics analysis

We determined overlapping target genes from the four miRNA target prediction databases. The resulting genes were then integrated with text mining outcomes, extended, and visualized using stringApp (Fig 2). The functional enrichment analysis also showed that the target genes are mainly enriched in pathways including type II diabetes mellitus, VEGF signaling pathway, and insulin signaling pathway (Table 1), indicating that these genes could be related to several biological processes underlying diabetic retinopathy.

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Fig 2. KEGG pathway enrichment and PPI network of MIR-96 associated genes.

The thickness of the connecting lines indicates the confidence level. Node borders with different colors present the specific biological pathway. KEGG = Kyoto Encyclopedia of Genes and Genomes; PPI = Protein-Protein Interaction; VEGF = Vascular Endothelial Growth Factor.

https://doi.org/10.1371/journal.pone.0310999.g002

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Table 1. Summary of KEGG enrichment analysis.

https://doi.org/10.1371/journal.pone.0310999.t001

DIANA-mirPath analysis using the Tarbase algorithm with a threshold value of P < 0.05, and false discovery rate (FDR) correction implied that MIR-96 could be involved in the regulation of insulin signaling pathway. Metascape extracted all the protein-protein interactions among the input genes from the PPI data source and formed a PPI network. To identify densely connected proteins, the molecular complex detection (MCODE) algorithm was then applied to this network. Gene ontology (GO) enrichment analysis showed that the MCODE1 network components were significantly enriched in the insulin receptor signaling pathway and type II diabetes mellitus (Fig 3).

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Fig 3. Gene ontology enrichment analysis.

(A) GO and KEGG pathway enriched terms recognized using Metascape website, sorted by -log10. (B) Network layout of representative terms visualized by Cytoscape. Each term was represented by a circle node. The colors describe the clusters’ identities. The thickness of the connecting line represents the similarity score. (C) The most significant MCODE model. GO enrichment analysis was applied to MCODE1, and the term “type II diabetes mellitus” was retained from the top three best p-value terms. GO = Gene ontology; KEGG = Kyoto Encyclopedia of Genes and Genomes; MCODE = Molecular Complex Detection.

https://doi.org/10.1371/journal.pone.0310999.g003

To explore related genes that are likely involved in the molecular mechanisms underlying diabetic retinopathy, DR-associated genes (altered expression) were retrieved from the DisGeNET database (v7.0) and gene-disease associations (GDAs) were visualized by the DisGeNET Cytoscape app (Fig 4).

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Fig 4. Network of differentially expressed genes associated with diabetic retinopathy.

(A) Association of common differentially expressed genes with diabetic retinopathy (DR) according to the DisGeNET database. (B) Top scored DR-associated genes. The enriched signaling pathway interrelated genes were highlighted in yellow, and the score ranges from 0.5 to 1.0.

https://doi.org/10.1371/journal.pone.0310999.g004

Construction of the MIR-96 expressing vector, transfection and analysis of GFP expression

MIR-96 gene was amplified from human genomic DNA. The final PCR product (424 bp) was inserted into a pAAV-MCS-eGFP-int plasmid (5506 bp, control vector) to produce a 5.9-kb recombinant vector (Fig 5A). The 1.3-kb DNA fragment containing MIR-96, eGFP-int, and cloning junction sequences was verified by DNA sequencing. Next, the recombinant plasmids were transfected to hRPE cells. 48 hours post-transfection, the cells were inspected for eGFP protein expression using fluorescence microscopy. As illustrated in Fig 5B and 5C, both hRPE cultures transfected with either pAAV-MIR-96-eGFP-int or pAAV-MCS-eGFP-int display over 90% eGFP-expressing cells.

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Fig 5. Schematic representation of pAAV-MIR-96-eGFP-int construct and hRPE cells’ transfection.

(A) MIR-96 fragment was inserted into pAAV-MCS-eGFP-int cassette (5.5 kb) to construct pAAV-MIR-96-eGFP-int vector (5.9 kb). (B) GFP expressing hRPE cells, 48 h after transfection of the recombinant vector, and (C) GFP expressing hRPE cells, 48 h after transfection of the control vector. The fluorescence microscopy image demonstrates more than 90% of both cultures were GFP positive. hRPE = human Retinal Pigment Epithelium; AmpR = ampicillin resistance gene; CMV = cytomegalovirus; AAV2 = adeno-associated virus-2; ITR = inverted terminal repeats; GFP = green fluorescent protein.

https://doi.org/10.1371/journal.pone.0310999.g005

Overexpression of MIR-96 in the transfected hRPE cells

The result of stem-loop RT-qPCR, when compared with hRPE cells transfected with pAAV-MCS-eGFP-int as control, revealed that MIR-96 was upregulated by more than 82-fold in the transfected hRPE cells 48 and 72 h post-transfection (Fig 6A).

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Fig 6. Effects of MIR-96 on cell viability.

(A) The relative expression level of MIR-96 following hRPE cell transfection (at 48 and 72 hours). (B) Cell viability analysis using MTT assay. Data expressed as mean ± standard error of the mean (SEM). P < 0.05. MTT = 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide; GFP = green fluorescent protein.

https://doi.org/10.1371/journal.pone.0310999.g006

Impact of pAAV-MIR-96-eGFP-int overexpression on hRPE cell viability

We further evaluated the effect of MIR-96 overexpression on the viability of the transfected hRPE cells in a time-dependent manner. MTT assay revealed that overexpression of MIR-96 had no statistically significant effect on cell viability when compared with the control group (P = 0.84, one-way ANOVA, Fig 6B).

Effect of MIR-96 overexpression on target genes’ expression

To explore the possible impacts of MIR-96 overexpression on insulin signaling pathway mediators and DR-related genes, the expression level of the nominated genes was assessed using RT-qPCR. As represented in Fig 7, the expression levels of IRS2, FOXO1, and ERK2 genes were significantly downregulated (by 0.3, 0.8, and 0.4-fold, respectively) 48 hours post-transfection in pAAV-MIR-96-eGFP-int transfected group compared with the control. Furthermore, SERPINF1 which displayed higher expression (2.7- fold) up until 48 h, decreased (0.4-fold) within 72 h after transfection compared with the control group.

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Fig 7. Relative expression of selected genes in transfected hRPE cells.

Error bars represent means ± standard error of the mean (SEM). *P < 0.05, **P < 0.01. IRS1 = Insulin Receptor Substrate 1; IRS2 = Insulin Receptor Substrate 2; FOXO1 = Forkhead box protein O1; ERK2 = Extracellular signal-Regulated Kinase 2; SERPINF1 = Serpin Peptidase Inhibitor, Clade F, Member 1; CCL2 = Chemokine (C-C motif) Ligand 2; IL6 = Interleukin 6; PIK3R1 = Phosphoinositide-3-Kinase Regulatory Subunit 1. The p-values of IRS2, FOXO1, ERK2, and SERPPINF1 are 0.001, 0.001, 0,002, and 0,014, respectively.

https://doi.org/10.1371/journal.pone.0310999.g007

Discussion

Recently, there has been considerable interest in comprehending the diverse molecular mechanisms behind DR to enhance the effectiveness of therapeutic strategies. Anti-VEGF therapy is a reliable and responsive treatment for proliferative diabetic retinopathy (PDR) and can also reduce the severity of DR in non-proliferative diabetic retinopathy (NPDR) patients. Despite its efficacy, reports show that DR lesions often recur quickly and underlying retinal ischemia also remains unchanged. Although anti-VEGF therapy is considered the main treatment option for DR, recent studies focus on the different pathways involved in the development of DR in the retina. Identifying the components of these pathways and designing effective drugs can provide new therapeutic options, whether used alone or in combination with anti-VEGF drugs, may enhance the effectiveness of treatments. Therefore, we need to target new pathophysiological pathways and stabilize drug effects [38, 39]. Regarding the importance of DR-associated signaling pathways in developing new pharmaceutical agents targeting non-VEGF-driven pathways, the current study aimed to identify potent components of the related signaling pathways.

Based on the results of the KEGG pathway enrichment analysis, MIR-96 target genes are predominantly enriched in signaling pathways activated by insulin (phosphoinositide 3-kinase) and VEGF. Integrating the protein-protein interaction (PPI) network of MIR-96 associated genes with an in vitro study of MIR-96 overexpression in hRPE cell culture has shown that IRS2 and FOXO1 levels were significantly decreased after 48 hours in pAAV-MIR-96-eGFP-int transfected hRPE cells.

Insulin signaling requires IRS molecules to regulate glucose metabolism in the cells. Among IRS protein family members, IRS1, along with IRS2 are essential molecules for the insulin signaling pathway. Recent evidence revealed that the IRS2 level has been elevated in mouse models of DR [18]. Differently, IRS2 expression in macrophages was downregulated by hyperinsulinemia which is often associated with type 2 diabetes [40]. To regulate IRS2 expression, FOXO1 binds to the insulin-responsive elements (IRE) of the IRS2 promoter, upregulating IRS2 expression and activating the PI3K/AKT pathway in the process. There is, however, no clear understanding of how IRS2 dysregulation occurs [41, 42].

It has also been demonstrated that insulin regulates VEGF expression in several cell types, including epithelial cells, and thereby contributes to DR progression. VEGF by itself can damage the tight junctions and cause dysfunction in RPE cells [43]. As far as we know, insulin upregulates the expression of VEGF mainly through the PI3K/AKT axis. Data support the idea that the IRS/PI3K/AKT/VEGF axis could be a potential target for the treatment of DR and accordingly, it should be further investigated to find new therapeutic targets [44].

Considering previous research, our findings suggest that the alteration of MIR-96 and its effects on IRS/PI3K/AKT/VEGF axis regulation and therefore the enhancement of VEGF, act as a facilitator in DR progression. According to Ji et al., suppression of IRS2 by MIR-7a inhibits PI3K/AKT cascade proteins in retinal pericytes and endothelial cells of DR mouse models. They suggested that the upregulation of MIR-7a and targeting IRS2 can inhibit VEGF and also the invasion capability of retinal cells [18]. In the current study, we found that the overexpression of MIR-96, contrary to other in vitro experiments [18, 45], can eventually result in the downregulation of PI3K/AKT cascade proteins, such as IRS2. Although the IRS2 expression differs from previous studies, it can nevertheless be argued that there is probably an interconnected system including epigenetic control, upstream genes, and miRNAs that can play a role in the regulation of IRS2 expression in diabetic patients [41, 42]. In addition, our studies were performed on non-diabetic retinal cells in which the MIR-96 was overexpressed. Despite the decline of IRS2, the expression of IRS1 remained unaltered which was in line with the findings from the study reviewed by Pitale et al. [45, 46].

A more recent study by Zolfaghari et al. [9] showed that despite the general similarity of retinal pigment epithelial cells in humans and mice, there are differences that should be considered for developing novel treatments [47]. A comprehensive review of the cellular characteristics suggested significant differences associated with each species. For example, RPE cell proliferation was reduced in mice as a result of MIR-96 overexpression, while it remained unchanged in human retinal cells. Nonetheless, the decrease in the expression level of FOXO1 in human cells concurs well with the previous study on the retina of human donors with DR [9].

FOXO1, which activates through the insulin-stimulated PI3K pathway and contributes to diabetes hyperglycemia, is a direct target of MIR-96 [48, 49]. Moreover, FOXO1 has now been identified as a potential DR-specific diagnostic and therapeutic gene, and its aberrant expression is associated with the pathogenesis of DR. It has been reported that several signaling pathways including MAPK regulate the activity of FOXO proteins in response to hyperglycemic conditions in diabetes [50, 51].

Among autophagy-related genes identified by bioinformatics analysis of mRNA chip of DR samples, ERK2 (MAPK1) was found to be downregulated [52]. In the present study, ERK2 gene expression level showed a significant reduction in pAAV-MIR-96-eGFP-int transfected hRPE cells. Several studies indicate that ERK1/2 plays a critical role in the development of DR [53–55]. It has been suggested that in addition to the PI3K/AKT signaling pathway, the ERK1/2 (p44/42 MAP Kinase) pathway may also contribute to long-term VEGF upregulation. As shown in previous studies, ERK1/2 can regulate VEGF expression by acting at the VEGF promoter. Furthermore, it has been shown that the ERK signaling pathway contributes to VEGF release in the retinas of diabetic rats [56].

Consistent with RT-qPCR results, Gene-disease associations (GDAs) provided by the DisGeNET (v7.0) database showed that among the DR-related genes, there are genes (such as IRS1, PIK3CA, AKT1, and MAPK1) related to the insulin signaling pathway and its downstream pathways whose expression has changed. In addition to these genes, MIR-183, according to a recent study, was also upregulated substantially in the retinas of DR rat models. The upregulation of MIR-183 activated the PI3K/AKT/VEGF signaling pathway promoting angiogenesis and endothelial cell proliferation [57].

Several studies have shown that PEDF (SERPINF1) is highly expressed in RPE cells, which affects retinal vasculature, and sustains retinal function. PEDF is a versatile protein that can inhibit the development of DR due to its antioxidant effect [58–61]. It is important to note that the balance between the expression of VEGF and PEDF in RPE cells has a profound impact on retinal vessels so an increase in VEGF and a decrease in PEDF can lead to the development of retinal neovascularization [62]. Likewise, studies have linked DR pathogenesis to decreased levels of PEDF [63]. In the present study, we observed that SERPINF1 expression started to decline over time after transfection, despite the elevation in the early hours. As the most potent neovascularization inhibitor in the eye, SERPINF1 reduction can affect the protection of retinal cells, thus the RPE becomes defective and unable to digest photoreceptor outer segments, allowing the retina to degenerate [64, 65].

It has been shown that PEDF signals through both MAPK/ERK and AKT signaling pathways to regulate gene expression [66]. It can also provide protection by activating the ERK pathway. Indeed, ERK activation has a protective function in the rescuing of RPE cells in an oxidative environment [67, 68]. In addition, PEDF inhibits endothelial cell proliferation by regulating the MAPK/ERK pathway [69]. Furthermore, there is evidence that PEDF can activate the PI3K/AKT pathway to reduce cytotoxicity in RPE cells that are being exposed to oxidative stress [70]. SERPINF1 is also present in the GDAs network and is one of the top-scored DR-associated genes. Delivering SERPINF1 in order to repress angiogenesis in the retina revealed that this approach was effective at inhibiting intravitreal neovascularization [71, 72].

Studies have shown that the regulation of the MMP2 gene is closely associated with the activation of the PI3K/AKT pathway [73]. Based on recent research [74], the PI3KCA/IRS1/2/AKT1/IL6/MMP2 axis shown in the PPI network of MIR-96 associated genes (Fig 2) contributes to retinal neovascularization by enhancing MMP2 expression through activation of PI3K/AKT signaling.

In summary, this study demonstrated that overexpression of MIR-96 influences the expression of IRS2, FOXO1, ERK2, and SERPINF1, consequently disrupting the PI3K/AKT pathway, which may contribute to retinal neovascularization and dysfunction. However, it is believed that further research is required to unravel the mechanism by which the PI3K/AKT pathway is dysregulated during DR pathogenesis, along with other associated mechanisms. The present study also confirms that the IRS/PI3K/AKT axis plays a prominent role in DR pathogenesis, which can be further investigated as a favorable therapeutic target.

Acknowledgments

We wish to acknowledge staff of Blood Transfusion Research Center for contribution to this work.

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