ORIGINAL ARTICLE

Year : 2021  |  Volume : 38  |  Issue : 3  |  Page : 166-172

Antiviral microRNA expression signatures are altered in subacute sclerosing panencephalitis

Kemal Ugur Tufekci¹, Jens Allmer², Kürşat Bora Çarman³, Erhan Bayram⁴, Yasemin Topçu⁴, Semra Hız⁴, Şermin Genç⁵, Uluç Yiş^4
1 Department of Healthcare Services, Vocational School of Health Services, İzmir Democracy University; İzmir Biomedicine and Genome Center; Department of Neuroscience, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
² Department of Molecular Biology and Genetics, İzmir Institute of Technology, Urla, Turkey
³ Division of Child Neurology, Gaziantep Children's Hospital, Gaziantep, Turkey
⁴ Department of Pediatrics, Division of Child Neurology, School of Medicine, Dokuz Eylül University, İzmir, Turkey
⁵ İzmir Biomedicine and Genome Center; Department of Neuroscience, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey

Correspondence Address:
Kemal Ugur Tufekci
M. Ali Akman Mh., 13 Sk., No: 2, Güzelyalı, İzmir
Turkey

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/nsn.nsn_57_21

Background: Subacute sclerosing panencephalitis (SSPE) is a chronic, progressive disease caused by a persistent infection of the measles virus. Despite extensive efforts, the exact neurodegeneration mechanism in SSPE remains unknown. MicroRNAs (miRNAs) have emerged as an essential part of cellular antiviral defense mechanisms and can be modulated by antiviral cytokines Such as interferon-beta (IFN-β). Aims and Objectives: In this study, we aimed to elucidate the role of antiviral miRNAs in the pathogenesis of SSPE and analyze the interaction between host antiviral miRNAs and virus genes. Materials and Methods: Thirty-seven patients who were followed with SSPE and age-matched healthy children were included in the study. Peripheral blood mononuclear cell levels of miR-196b, miR-296, miR-431, and miR-448 were analyzed using quantitative polymerase chain reaction. Target predictions and pathway constructions of deregulated miRNAs were assessed. Results: Here, we showed that IFN-β-modulated miR-196b, miR-296, and miR-431 were significantly upregulated in patients with SSPE compared with healthy controls. Besides, sequence complementarity analysis showed that miR-296 and miR-196b predicted binding regions in measles virus genomic RNA. Conclusion: Our findings suggest that antiviral miRNAs are upregulated in patients with SSPE, which could be a part of the host antiviral defense mechanism.

Keywords: Antiviral microRNA, measles virus, microRNA, subacute sclerosing panencephalitis

Introduction

Subjects and Methods

−ΔΔ^Ct method.^[9]

Pathway construction

The Kyoto Encyclopedia of Genes and Genomes (KEGGs) provides manually curated pathways for human and other organisms.^[10] Such pathways may show any interaction such as regulatory or compositional. KEGG also provides compound pathways, and we downloaded the measles pathway, which contains human pathways and their interactios with the measles genes (http://www.genome.jp/kegg-bin/show_pathway?hsa05162). Unfortunately, the pathway displayed on the KEGG webpage is significantly different from the download that is provided on the same page. To overcome this issue and to add the miRNA-driven regulation to the compound human/measles pathway, we loaded the downloaded pathway into a network editor. This editor, Cytoscape, among other functionalities, allows formatting, layout, and additions to the pathway.^{[1],[12],[13]} Thus, Cytoscape enabled us to establish the pathway similar to how it appeared on the KEGG website and to add the miRNAs analyzed in this study.

The overexpressed miRNAs were investigated in miRBase^[14] and miRTarBase^[15] and their source genes were determined. A total of four source genes lead to six miRNAs that had targets in the measles and or human pathways. Targets were determined using miRTarBase,^[15] TarBase,^[16],[17] and computational target prediction (see below). Targets were either within the measles or associated human pathways or were targeting completely different processes (other targets). The miRNAs, their source genes, and their targets were manually added to the combined human and measles pathways using the Cytoscape editor.

Target prediction

The mature sequences for the miRNAs found in this study were reverse complemented and then compared with the measles genome using BLAST^[18] for small sequences. The first binding of the sequences was forced to be among the first three nucleotides of the reverse complement because the seed sequences are the most important in target binding. The binding of 6–8 nucleotides in the seed sequence was found to be sufficient for target recognition and therefore at least this length of perfect matching was required. The targets were visualized on the National Center for Biotechnology Information (NCBI) measles genome browser using the NCBI facilities (Available at: http://tinyurl.com/po4ko6v).

Statistical analysis

SPSS v.20.0 (IBM Corp., Armonk, NY, USA) was used for statistical analysis. Data are presented as mean ± standard error. Student's t-test was used to compare parametric variables. The Kruskal–Wallis and Mann–Whitney U-tests were used to analyze nonparametric variables (n < 30). Pearson's correlation test was used to determine the correlation between miRNA expression levels and clinical variables. P < 0.05 was considered statistically significant.

Results

Clinical features of subacute sclerosing panencephalitis patients

Thirty-seven patients with SSPE (25 boys and 12 girls; mean age = 14.6 years) and 41 healthy controls (22 girls and 19 boys; mean age = 13.5 years) from the same patient and control cohort^[7] were included in the study. Fifty-four percent of patients with SSPE and 36.6% of healthy control samples were obtained from Gaziantep Children's Hospital (Gaziantep, Turkey) (P = 0.35). The demographic and clinical features of the patients were previously published^[7] [Table 1].

Table 1: Classification of patients with subacute sclerosing panencephalitis with respect to disease stage Click here to view

Antiviral microRNA expression levels are altered in subacute sclerosing panencephalitis

To determine the alterations in antiviral miRNAs expression levels, we used quantitative PCR to analyze hsa-miR-448, hsa-miR-196b, hsa-miR-296, and hsa-miR-431 expression levels. The mean hsa-miR-196b expression in patients with SSPE was 4.9-fold higher compared with the healthy controls (P < 0.001). The mean hsa-miR-431 expression in patients with SSPE was 5.6-fold higher compared with the healthy controls (P < 0.001). The mean miR-296 expression in patients with SSPE was 6.6-fold higher compared with the healthy controls (P = 0.001). The mean miR-448 expression in patients with SSPE was 1.5-fold higher compared with the healthy controls (P = 0.32). Overall, the expression levels of all miRNAs, except hsa-miR-448, were significantly higher in patients with SSPE compared with the healthy controls [Figure 1].

Figure 1: Antiviral microRNA expression levels are altered in subacute sclerosing panencephalitis. Peripheral blood mononuclear cells were isolated from patients with subacute sclerosing panencephalitis (n = 37) and healthy controls (n = 41). Total RNA was isolated from peripheral blood mononuclear cells, and hsa-miR-448, hsa-miR-196b, hsa-miR-296, and hsa-miR-431 expression levels were analyzed using quantitative polymerase chain reaction Click here to view

Given that the majority of the patients (26 of 37 patients) received IFN-β treatment, elevated miRNA expression levels may be a consequence of this treatment. When we grouped the patients concerning IFN-β treatment (treated vs. untreated), we found no significant difference in expression levels of any miRNA (P > 0.05).

Antiviral microRNAs have predicted binding sites in the measles genomic RNA

Our next question was whether the elevated miRNA species would target the measles genome. Previously, Pedersen et al. used a sequence complementarity analysis of several IFN-β-induced miRNAs against HCV genomic RNA and determined that eight IFN-β-induced miRNAs had nearly perfect complementarity in their seed sequences with the HCV RNA genome.^[4] By employing a similar approach, we analyzed the complementarity between the seed sequences of miR-196b, miR-296, and miR-431 and the measles virus RNA genome. We identified that miR-296 and miR-196b targeted the RNA genome of the measles virus, as well as its variants [Table 2] and [Figure 2]. Further analysis of these miRNAs showed that they also targeted different viruses including HCV, influenza virus, and poliovirus. This finding suggests that elevated miRNA expression profiles in patients with SSPE could represent a shared antiviral defense mechanism.

Table 2: hsa-miR-296 and hsa-miR-196b predicted binding regions in the measles genome Click here to view

Figure 2: The transcripts of the measles virus and the predicted targets of the microRNAs. Due to space constraints, the microRNAs were abbreviated as follows: Hsa-miR-196b-3p (t13; dark red), hsa-miR-196b-5p (t15; orange), hsa-miR-296-3p (t23; olive), hsa-miR-296-5p (t25; green), hsa-mir-431 (t41, aquamarine), and hsa-mir-448-3p (t43, blue). Drop lines on the genomic view indicate the locations of the targets of these microRNAs. The horizontal bars art the collapsed features available in full on National Center for Biotechnology information website Click here to view

Pathway analysis

In the next step, we conducted pathway analysis to identify the potential measles genes that were targeted by the antiviral miRNAs. Our pathway analysis confirmed that 196b-5p, 296-5p, and 296-3p had targets within the KEGG measles pathway [Table 2] and [Figure 3]. Furthermore, all miRNAs found in this study predicted targets in the measles genome [Table 3], [Figure 3].

Table 3: In silico prediction of measles virus genes that are targeted by antiviral micro ribonucleic acid Click here to view

Figure 3: hsa-miR-448, hsa-miR-196b, hsa-miR-296, and hsa-miR-431 had targets in the measles Kyoto Encyclopedia of Genes and Genome pathway. The Kyoto Encyclopedia of Genes and Genome measles pathway (Accession: Hsa05162) was amended with the measles genes (khaki rectangles). The microRNAs found in this study and their targets were also added to the pathway (orange rectangles). Gray rectangles with diamond connection to the microRNAs indicate their source genes. Solid lines with perpendicular lines from microRNAs to genes indicate repression. If these lines are dotted, it indicates that the targets are computational predictions. Green rectangles (other targets) indicate the presence of further targets in the human genome Click here to view

Discussion

During the past decade, miRNAs have emerged as important regulators of cellular antiviral defense mechanisms in different viral infections. However, we still do not know which miRNAs play a role in SSPE, or how. In the present study, we report that several antiviral miRNAs are overexpressed in patients with SSPE compared with healthy controls.

One of the pioneering studies on the antiviral role of miRNAs came from Lecellier et al., where the authors showed that cellular miRNA limited the replication of a mammalian virus, thus functioning as a cellular mediator of the antiviral response.^[19] Later, Pedersen et al. reported that IFN-β modulated the expression of different cellular miRNAs, eight of which were predicted to target the HCV genomic RNA.^[4] Subsequent studies indicated that miRNAs were major mediators of antiviral immunity, and analysis of virus-induced miRNA expression represented a rational way of studying virus-host interactions. In a recent study, Hou et al. demonstrated that hepatitis B virus (HBV) promoted miR-146a expression, which in turn suppressed STAT1 expression and led to interferon resistance.^[20] Similarly, in our previous study, we found that miR-146a expression was significantly higher in patients with SSPE compared with healthy controls.^[7] This finding could represent a shared mechanism of virus-induced alteration of miRNA expression. Still, the consequences of elevated miR-146a expression in SSPE are not completely identified.

We previously analyzed expression levels of several miRNAs involved in the immune system and inflammation in patients with SSPE and found that hsa-miR-146a, hsa-miR-181a, and hsa-miR-155 expression was significantly higher in patients with SSPE compared with healthy age-matched controls.^[7] Together with the findings of the present report, these results suggest that miRNAs that are modulated by IFN-β might play a significant role in the pathogenesis of SSPE.

Interferon regulatory factors (IRFs) represent a group of transcription factors that play key roles in the innate immune system, especially during interferon production.^[21] The measles virus nucleocapsid gene (N) activates IRF3,^[22] but hsa-miR-296-5p counteracts that by repressing IKBKE, which also activates IRF3. Hsa-miR-196-5p shares GNB2 L1 as a target with hsa-miR-296-3p. MV-L is targeted by hsa-miR-448, hsa-miR-196 5p and 3p and by hsa-miR-196-3p, which may indicate that the measles polymerase (L) is an important target for human defense mechanisms. All miRNAs identified in our study targeted at least one measles gene, but usually multiple, which led to redundant repression of some virus genes such as L, H/F, and N. However, C, V, and M are also targeted but only by a single miRNA [Figure 3]. The distribution of the targets of these miRNAs is uneven and many target MV-L and MV-F more compared with other genes, which indicates that these two genes are important for defense against MV [Figure 3].

As summarized in [Table 1], the majority of the patients with SSPE had an advanced stage disease and also received IFN-β. This information should be considered when interpreting the antiviral miRNA expression levels. It is likely that IFN-β treatment also contributed to the observed elevation in miRNA expression levels. Determining the actual increase in antiviral miRNA expression levels is possible through analysis of CSF samples and/or CNS cells; however, this approach relies on invasive sample collection procedures.

There are certain limitations of our present study. We were unable to compare miRNA expressions between patients convalescing from measles and those with SSPE; such information would allow us to have an accurate interpretation of the role of these four miRNAs in SSPE pathogenesis. We initially hypothesized that elevated miRNA expression levels were a response to measles infection; hence, it is possible to speculate that miRNAs would show differential expression between patients who recovered from measles infection and patients who progress to SSPE. Unfortunately, we do not have any follow-up information about the patients, and the only available information is the time of admission to the study. Another limitation of our study is that RNA profiles may vary in PBMC samples obtained from blood from different cities. However, in the pilot study, we conducted before our study, miRNA levels were compared by isolating PBMCs from fresh blood samples and from the same blood that was kept in EDTA tubes for 48 h at room temperature. There was no difference between the RNA concentrations, cycle threshold (Ct) values, and ΔCt values we obtained. Hence, our investigation showed that the stability and expression of miRNAs were not affected by external conditions during transportation of blood samples. We were also unable to analyze the potential correlation between the disease stage with measles virus titers because this parameter is not regularly used in routine clinical practice in Turkey. Finally, we were unable to validate in silico predictions due to the lack of a suitable in vitro SSPE model.

To identify the precise contribution of miRNAs to the pathogenesis of SSPE, future studies should focus on functional analyses of miRNA gain and/or loss in an in vitro model of SSPE. Given the lack of an existing model for this disease, this could represent a technical challenge, but the outcomes of such efforts will surely help us to determine the roles of miRNAs in SSPE.

Acknowledgment

The study received financial support from Dokuz Eylul University, Izmir, Turkey (Grant number: BAP 2012.KB.SAG.106).

Financial support and sponsorship

This study has been funded by Dokuz Eylul University (Project number: 2012.KB.SAG.106).

Conflicts of interest

There are no conflicts of interest.



 

References

1.	Mekki M, Eley B, Hardie D, Wilmshurst JM. Subacute sclerosing panencephalitis: Clinical phenotype, epidemiology, and preventive interventions. Dev Med Child Neurol 2019;61:1139-44.
2.	Solomon T, Hart CA, Vinjamuri S, Beeching NJ, Malucci C, Humphrey P. Treatment of subacute sclerosing panencephalitis with interferon-alpha, ribavirin, and inosiplex. J Child Neurol 2002;17:703-5.
3.	Anlar B, Yalaz K, Imir T, Turanli G. The effect of inosiplex in subacute sclerosing panencephalitis: A clinical and laboratory study. Eur Neurol 1994;34:44-7.
4.	Pedersen IM, Cheng G, Wieland S, Volinia S, Croce CM, Chisari FV, et al. Interferon modulation of cellular microRNAs as an antiviral mechanism. Nature 2007;449:919-22.
5.	Nagano I, Nakamura S, Yoshioka M, Onodera J, Kogure K, Itoyama Y. Expression of cytokines in brain lesions in subacute sclerosing panencephalitis. Neurology 1994;44:710-5.
6.	O'Connell RM, Rao DS, Baltimore D. microRNA regulation of inflammatory responses. Ann Rev Immunol 2012;30:295-312.
7.	Yiş U, Tüfekçi UK, Genç Ş, Çarman KB, Bayram E, Topçu Y, et al. Expression patterns of micro-RNAs 146a, 181a, and 155 in subacute sclerosing panencephalitis. J Child Neurol 2015;30:69-74.
8.	Cakmak Genc G, Dursun A, Karakas Celik S, Calik M, Kokturk F, Piskin IE. IL28B, IL29 and micro-RNA 548 in subacute sclerosing panencephalitis as a rare disease. Gene 2018;678:73-8.
9.	Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C (T)) Method. Methods 2001;25:402-8.
10.	Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M. Data, information, knowledge and principle: Back to metabolism in KEGG. Nucleic Acids Res 2014;42:D199-205.
11.	Saito R, Smoot ME, Ono K, Ruscheinski J, Wang PL, Lotia S, et al. A travel guide to Cytoscape plugins. Nat Methods 2012;9:1069-76.
12.	Cline MS, Smoot M, Cerami E, Kuchinsky A, Landys N, Workman C, et al. Integration of biological networks and gene expression data using Cytoscape. Nat Protoc 2007;2:2366-82.
13.	Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res 2003;13:2498-504.
14.	Kozomara A, Griffiths-Jones S. miRBase: Annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 2014;42:D68-73.
15.	Hsu SD, Tseng YT, Shrestha S, Lin YL, Khaleel A, Chou CH, et al. miRTarBase update 2014: An information resource for experimentally validated miRNA-target interactions. Nucleic Acids Res 2014;42:D78-85.
16.	Sethupathy P, Corda B, Hatzigeorgiou AG. TarBase: A comprehensive database of experimentally supported animal microRNA targets. RNA 2006;12:192-7.
17.	Vergoulis T, Vlachos IS, Alexiou P, Georgakilas G, Maragkakis M, Reczko M, et al. TarBase 6.0: Capturing the exponential growth of miRNA targets with experimental support. Nucleic Acids Res 2012;40:D222-9.
18.	Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990;215:403-10.
19.	Lecellier CH, Dunoyer P, Arar K, Lehmann-Che J, Eyquem S, Himber C, et al. A cellular microRNA mediates antiviral defense in human cells. Science 2005;308:557-60.
20.	Hou ZH, Han QJ, Zhang C, Tian ZG, Zhang J. miR146a impairs the IFN-induced anti-HBV immune response by downregulating STAT1 in hepatocytes. Liver Int 2014;34:58-68.
21.	Collins SE, Noyce RS, Mossman KL. Innate cellular response to virus particle entry requires IRF3 but not virus replication. J Virol 2004;78:1706-17.
22.	tenOever BR, Servant MJ, Grandvaux N, Lin R, Hiscott J. Recognition of the measles virus nucleocapsid as a mechanism of IRF-3 activation. J Virol 2002;76:3659-69.

Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 

Tables

  [Table 1], [Table 2], [Table 3]