1. Introduction
Inflammation is the biological reaction of body tissues and a complex protective response mechanism (
Ferrero-Miliani, Nielsen, Andersen, & Girardin, 2007). Inflammation in the nervous system occurs because of various reasons and is the component of the pathogenicity of neurodegenerative diseases, particularly Parkinson disease, multiple sclerosis, and Alzheimer disease (
Fung, Vizcaychipi, M., Lloyd, Wan, & Ma, 2012;
Giovannoni and Quintana 2020). It is necessary to know more about inducing inflammatory responses within the Central Nervous System (CNS) and the mechanisms that eventually lead to pathogenicity (
Zipp and Aktas 2006;
Glass, Saijo, Winner, Marchetto, & Gage 2010).
Sialic acid belongs to the family of 50 naturally monosaccharides that differ from other glycan molecules. It is a sugar with a nine-carbon backbone that can be enzymatically modified inside the cell (
Schauer 2009). This sugar plays an important role in many physiological processes such as protein folding, neural development, cell-cell interactions, and pathological processes like autoimmunity and cancer. Changes in sialic acid concentration are shown in many pathological states that might be a valuable marker for determining the inflammatory process (
Noorbakhsh, Zamani, & Galehdari, (2020); Citil, Gunes, Karapehlivan, Atalan, & Marasli 2004;
Varki 2008;
Büll, Heise, Adema, & Boltje 2016). The biological function of sialic acids exerts through multiple mechanisms that participate directly and indirectly in multiple events at molecular and cellular levels (
Schauer 2009;
Büll, et al. 2016). Sialic acid is a sugar that is frequently located on the cell surface. For unknown reasons, the brain has the highest sialic acid concentration in the body (
Schauer, Srinivasan, Wipfler, Kniep, & Schwartz-Albiez 2011;
Sbardella, Fasciglione, Gioia, Ciaccio, C., Tundo, & Marini 2012;
Wielgat and Braszko 2012; Linnartz-Gerlach, Mathews, & Neumann 2014). These sialic acid features make it a suitable candidate for investigating neuroinflammatory pathways.
MicroRNAs (miRNAs) are a class of single-stranded non-coding RNA molecules with a length of 20-24 nucleotides. Individual miRNA can control the expression of more than one target mRNA and is estimated to regulate up to one-third of all human genes, such as genes involved in immunity, immune cell differentiation, and the correct functioning of CNS (
Fenoglio, Ridolfi, E., Galimberti, & Scarpini2012;
Bhalala, Srikanth, & Kessler2013).
MiRNAs are contributing to several biological processes and human diseases. Their involvement in a broad range of cellular processes makes them a powerful cellular tool in numerous biological processes such as cell development, proliferation, differentiation, inflammation, immunity, metabolism, apoptosis, and angiogenesis (
Coolen and Bally-Cuif 2009;
Eacker, Dawson, & Dawson, 2009).
Dysregulating the miRNAs’ expression and function is associated with several human diseases such as neurodegeneration, autoimmunity, and cancer. Also, miRNAs’ involvement in the pathogenesis of some neurodegenerative diseases such as Alzheimer and Parkinson diseases have been demonstrated. After the CNS damage, the expression pattern of miRNAs is changed and affects the downstream factors of these miRNAs (
Bhalala, et al., 2013). Moreover, new studies emerged for making new tools for diagnosing and treating several human diseases (
Mattes, Collison, et al. 2008;
Hébert and De Strooper 2009;
Guan, et al. 2013;
Liu, et al. 2014).
miRNAs can downregulate gene expression at the post-transcriptional level, leading to degrading or translational inhibition of the target by directing the three prime untranslated region (3’-UTR) of mRNAs through sequence-specific binding. It is essential to know the miRNAs’ targets to understand their functions. Moreover, miRNAs regulate gene expression through post-transcriptional repression by binding to the 3’-UTR of their target mRNA (
Akhtar, Micolucci, et al., 2016).
We previously demonstrated in our laboratory that sialic acid could alter the expression of inflammatory genes like MMP-9 and TIMP-1 in the presence of sialic acid in the human glial cell line. We revealed that the expression of MMP-9 and TIMP-1 genes in all three concentrations (300, 500, and 1000 µg/mL) increased compared to the control group (
Shabani Sadr, Shafiei, Galehdari, & Khirolah, 2020). In this study, we examine two miRNAs (miR-320a and let-7e) that contribute to some neurodegenerative diseases directly and can affect MMP-9 (
Guan, et al., 2013;
Aung, Mouradian, Dhib-Jalbut, Balashov, 2015).
Signaling pathways influencing the expression of miR-320a and let-7e are still incompletely understood, so we aimed to explore the potential roles and molecular mechanisms of miR-320a and let-7e in the glial cells in response to sialic acid because both components are embedded in inflammation regulation.
2. Materials and Methods
Culture of 1321N1 cells for sialic acid treatment
The human glial cell line (1321N1) was obtained from the Pasture Institute of Iran. The glial cells were grown in Dulbecco’s Modified Eagle Medium (DMEM) (Bio Idea Company, Tehran, Iran) supplemented with 10% FBS (Gibco), streptomycin (100% µg/mL), and penicillin (100 U/mL). All cells culture were maintained at 37°C in an incubator containing 95% air and 5% CO2 atmosphere. The glial cell line was treated with sialic acid (300, 500, 1000 µg/mL) for 24h to evaluate the effects of this ligand on miR-320a and let-7e transcript expression.
Cell viability assay
Cell viability in response to different treatments was evaluated using the 3-(4,5-dimethylthiazol-2yl)-2,5-diphenyl (MTT) tetrazolium bromide assay. Cells were seeded in a 96-well plate (7000 cells/well) and 200 µL of culture medium treated with different concentrations (between 20-1500 µL) of sialic acid. Cell viability was evaluated with the control group after 24h using the MTT assay (Autocell) at 570 nm with a wavelength of 630 nm. ELISA reader calculated the optical absorption values for each well plate, and the results were analyzed by Excel software.
Ribonucleic acid extraction, reverse transcriptase, and real-time quantitative reverse transcription
Total RNA of the cocultured cell was extracted by miRNA isolation kit from approximately 10×106 glial cells using TRIzol-Sigma-Aldrich (TRI Reagent®, USA) following the manufacturer’s protocol.
The yield and purity of the extracted RNAs were evaluated by 2% agarose gel electrophoresis and NanoDrop N 1000 spectrophotometer (Thermo Scientific).
Gene expression changes of microRNA were assessed using a BON-miR kit (Bon Yakhteh, Tehran, Iran) according to the manufacturer’s instructions; U6 small nuclear RNA was used to normalize the data. U6 has been commonly used for miRNA normalization due to its RNA stability and abundant expression (
Peltier and Latham 2008).
Five thousand nanograms of total RNA from each sample were used in cDNA according to the ‘manufacturer’s protocol. Real-time detection was performed with the SYBER Green master mix using primers for miR-320a and hsa-let-7e. The primers were purchased from BON-miR Research Center. The sequences of the used forward primers are as follows: miR-320a Forward primer: AAGGCTGGGTTGAGAGG, and let-7e Forward primer: GATGGGCTGTGAGGTAGG. Universal reverse primers were obtained from Bon Yakhteh Company, Tehran, Iran.
Polymerase Chain Reaction (PCR) amplification was performed on the Applied Biosystems 7500 stepOnePlus instrument (Applied Biosystems). Real-time Quantitative PCR (qRT-PCR) conditions were as follows: 95°C for 2 min (1 cycle), 95°C for 5s, and 62°C for 30s (40 cycles). All samples were duplicated and repeated at least in two independent biological repeats.
The specificity of all the primers used in these experiments was confirmed with a single product peak in the melt curve analysis. Data analysis was performed using the 2−ΔΔCT method between the treatment and control groups to compare the expressions of miR-320a and let-7e.
Statistical analysis
The real-time Quantitative Reverse Transcription (qRT-PCR) data were analyzed by SPSS 21.0, and the normalization was conducted with U6 small nuclear RNA. Each reaction was performed in triplicate, then miRNA contents were calculated by the
Equation 1: . Statistical analyses were done by SPSS v. 21 software, and data were expressed as Means±SEM.
1. ΔCtmiRNA=CtmiRNA-CtU6
The significance level of the observed difference between the groups was measured by Analysis of Variance (ANOVA), and then Tukey’s HSD test was used to compare the groups. The graphs were generated by GraphPad Prism v. 7 software (GraphPad Software Inc. La Jolla, CA, USA). The t-test was performed to compare groups, and P<0.05 was considered the statistically significant difference.
Target gene prediction
To investigate the putative targets involved in the miR-320a and Let-7e mediated regulation of inflammation of glial cells, four computational algorithms, including TargetScan (
Agarwal, Bell, Nam, & Bartel 2015), miRDB (
Liu and Wang, 2019), miRWalk database (
Sticht, De La Torre, Parveen, & Gretz 2018), and miRmap (
Vejnar, & Zdobnov, 2012) were used to analyze the possible anti-inflammatory cytokine binding sites of miR-320a and let-7e. The structures of the miRNA-320a-mRNA and let-7e-mRNA are displayed in
Figure 1.
3. Results
The MTT assay results were analyzed by Excel software. Three concentrations of sialic acid (300, 500, and 1000 µg/mL) were utilized for the treatment of cells and the analysis of changes in gene expressions.
By analyzing qRT-PCR data, it was revealed that miR-320a and let-7e expressions were greatly influenced (P<0.0001) in response to different treatments (
Figure 2).
Three different concentrations of sialic acid (300, 500, and 1000 µg/mL) displayed a considerable increase in the expression of miR-320a and let-7e compared to the control group.
Therefore, we reject the hypothesis that miR-320a and let-7e directly affect MMP-9 because by targeting 3’-UTR of mRNAs through sequence-specific binding, miRNAs can downregulate gene expression at the post-transcriptional level and lead to degradation or translational inhibition of the target. We have suggested that miR-320a and let-7e might affect anti-inflammatory cytokine to active cellular inflammation in the glial cells treated by sialic acid.
To test our hypothesis, we utilized TargetScan, miRDB, miRWalk, and miRmap to predict the anti-inflammatory cytokines of miR-320a and let-7e, defined as potential target genes for future studies.
The anti-inflammatory cytokines are immune regulatory molecules, and their physiological functions in pathology in inflammation and inflammatory states are highly recognized. Various anti-inflammatory cytokines have been recognized and these include Interleukin (IL)-1ra, IL-4, IL-6, IL-10, IL-11, IL-13, and Transforming Growth Factor-Beta (TGF-β) (
Opal, & DePalo 2000;
Sultani, Stringer, Bowen, & Gibson 2012).
We analyzed two microRNAs in bioinformatics tools to find potential anti-inflammatory cytokines. The results identified putative binding sites for miR-320a in the IL-4 gene. We furthermore observed that let-7e contains binding for IL-10 and IL-13 (
Table 1).
4. Discussion
Numerous reports suggest that miRNAs are key therapeutic targets because they are involved in multiple essential pathways related to neurological networks and biological processes (
Papagiannakopoulos, Shapiro, & Kosik 2008;
Hébert, & De Strooper 2009). Therefore, any disruption would lead to complex neurological ailments. Hence, it is prudent to speculate on the role of these important molecules as a potential target for therapy and or early diagnosis of neurodegenerative diseases and their associated outcomes.
Here, we investigated the putative effect of sialic acid, as a versatile physiologically active molecule in various body processes, on the expression of two miRNAs, the miR-320a and the let-7e, to identify the network under these miRNAs control (
Figure 3).
5. Conclusion
Sialic acid is an inflammatory factor that facilitates cellular inflammation, particularly in the glial cells. It would be an applicable model for mimicking some neurodegenerative diseases such as Parkinson disease and multiple sclerosis.
This research indicates that selected sialic acid concentrations induced significant changes in the expression of miR-320a and let-7e in treated glial cells compared to nontreated groups. It is observed that miR-320a and let-7e were upregulated in the glial cells treated with sialic acid compared to the control group. This finding approved the potential role of miR-320a and let-7e on molecular pathways related to sialic acid.
Also, previous studies have shown that let-7e has been upregulated in some inflammation processes; for example,
Coskun, Bjerrum, Seidelin, Troelsen, Olsen, & Nielsen (2013) demonstrated that Let-7e acts as a potential biomarker in Ulcerative Colitis (UC) (an inflammatory Bowel Disease (IBD)). They have identified that the expression level of let-7e was significantly upregulated in UC (
Coskun, et al., 2013).
Polikepahad et al. (2010), in their in vivo analysis, suggested the proinflammatory properties of let-7 miRNAs. Their studies indicate a powerful proinflammatory role for the let-7 family of miRNAs in allergic lung disease (
Polikepahad, Knight, et al. 2010). Let-7e is significantly upregulated in multiple sclerosis patients, suggesting an active role for let-7e in MS pathogenesis (
Guan, et al., 2013,
Guan, et al., 2016).
Chen et al. (2015), in their in vivo studies, showed that the overexpression of miR-320a led to an increase in the serum inflammatory cytokines such as IL-6, MCP-1, TNF-α, and fibrinogen. (
Chen, et al. 2015). Some studies have suggested that the miR-320 family is altered in patients with inflammatory bowel disease (
Fasseu, et al., 2010). This evidence suggests the potential role of let-7e and miR-320A as proinflammatory factors in the inflammatory process.
Exploring the target genes and pathways of miR-320a, let-7e, and other differentially expressed miRNAs may contribute to understanding the potential role of miRNAs in this pathway. MicroRNAs perform functions through mediating translational repression or directing cleavage of target genes. Identifying the target genes of miR-320a and let-7e will be the next step toward uncovering their role in this pathway.
The present study has suggested that miR-320a overexpression was involved in the cellular inflammation of the glial cells. Because miR-320a regulates multiple genes, it could play an important role in the regulatory network underlying the inflammation of the glial cells (
Noorbakhsh, et al., 2020).
Bioinformatics tools show that IL-4 is the potential anti-inflammatory cytokine of miR-320a, and IL-4 was selected for further experiments as it ranked the highest amongst the potential target genes. In addition, the association between IL-4 and miR-320a was previously investigated in HTR-8/SVneo cells. The results suggested that IL-4 was a direct target gene of miR-320a and could repress IL-4 expression by binding to its 3’‑UTR (
Xie, Jia, & Li, 2019).
Bioinformatics tools show that IL-10 and IL-13 are the potential anti-inflammatory cytokines of let-7e and were selected for further experiments as they ranked the highest amongst the potential target genes. Furthermore, the links between IL-10, IL-13, and let-7e have previously been analyzed in patients with MS. The results identified that let-7e is directly targeted in IL-10 and IL-13. (
Guan, et al. 2013;
Guan, Singh et al. 2016).
Based on in silico studies, it was determined that let-7e could inhibit IL-10 and IL-13, and miR-320a can inhibit IL-4. Therefore, IL-4, IL-10, and IL-13 were selected for further experiments as they ranked the highest amongst the potential target genes.
Ethical Considerations
Compliance with ethical guidelines
There was no requirement for ethical approval because our work has been limited to cell lines.
Funding
The article was extracted from the MSc thesis of the second author in the Department of Genetics, Faculty of the Science at the Shahid Chamran University of Ahvaz.
Authors' contributions
Conceptualization and supervision: Hamid Galehdari; Methodology, Investigation, Data analysis, writing-original draft, and writing-review & editing: Negar Noorbakhsh; Conceptualization and Writing-Review & Editing: Mohammad Shafiei
Conflict of interest
The authors declared no conflict of interest.
Acknowledgments
The authors would like to acknowledge all the contributors to this study for supporting this analysis, particularly Tahereh Seifi. We acknowledge the Support of Shahid Chamran University of Ahvaz for supporting this work
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