Browsing by Author "Demirci, Muserref Duygu Sacar"

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Citation - WoS: 24
Citation - Scopus: 24
Circular RNA-MicroRNA Interaction Predictions in SARS-CoV Infection
(Walter de Gruyter Gmbh, 2021) Demirci, Yilmaz Mehmet; Demirci, Muserref Duygu Sacar; Saçar Demirci, Müşerref Duygu
Different types of noncoding RNAs like MicroRNAs (miRNAs) and circular RNAs (circRNAs) have been shown to take part in various cellular processes including post-transcriptional gene regulation during infection. MiRNAs are expressed by more than 200 organisms ranging from viruses to higher eukaryotes. Since miRNAs seem to be involved in host-pathogen interactions, many studies attempted to identify whether human miRNAs could target severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNAs as an antiviral defence mechanism. In this work, a machine learning based miRNA analysis work flow was developed to predict differential expression patterns of human miRNAs during SARS-CoV-2 infection. In order to obtain the graphical representation of miRNA hairpins, 36 features were defined based on the secondary structures. Moreover, potential targeting interactions between human circRNAs and miRNAs as well as human miRNAs and viral mRNAs were investigated.
Citation - WoS: 1
Citation - Scopus: 1
A Comprehensive MicroRNA-seq Transcriptomic Analysis of Tay-Sachs Disease Mice Revealed Distinct miRNA Profiles in Neuroglial Cells
(Springernature, 2025) Kaya, Beyza; Orhan, Mehmet Emin; Yanbul, Selman; Demirci, Muserref Duygu Sacar; Demir, Secil Akyildiz; Seyrantepe, Volkan
Tay-Sachs disease (TSD) is a rare lysosomal storage disorder marked by the progressive buildup of GM2 in the central nervous system (CNS). This condition arises from mutations in the HEXA gene, which encodes the alpha subunit of the enzyme beta-hexosaminidase A. A newly developed mouse model for early-onset TSD (Hexa-/-Neu3-/-) exhibited signs of neurodegeneration and neuroinflammation, evidenced by elevated levels of pro-inflammatory cytokines and chemokines, as well as significant astrogliosis and microgliosis. Identifying disease-specific MicroRNAs (miRNAs) may aid the development of targeted therapies. Although previous small-scale studies have investigated miRNA expression in some regions of GM2 gangliosidosis mouse models, thorough profiling of miRNAs in this innovative TSD model remains to be done. In this study, we employed next-generation sequencing to analyze the complete miRNA profile of neuroglial cells from Hexa-/-Neu3-/- mice. By comparing KEGG and Reactome pathways associated with neurodegeneration, neuroinflammation, and sphingolipid metabolism in Hexa-/-Neu3-/- neuroglial cells, we discovered new MicroRNAs and their targets related to the pathophysiology of GM2 gangliosidosis. For the first time, our findings showed that miR-708-5p, miR-672-5p, miR-204-5p, miR-335-5p, and miR-296-3p were upregulated, while miR-10 b-5p, miR-615-3p, miR-196a-5p, miR-214-5p, and miR-199a-5p were downregulated in Hexa-/-Neu3-/- neuroglial cells in comparison to age-matched wild-type (WT). These specific changes in miRNA expression deepen our understanding of the disease's neuropathological characteristics in Hexa-/-Neu3-/- mice. Our study suggests that miRNA-based therapeutic strategies may improve clinical outcomes for TSD patients.
Comprehensive Prediction of FBN1 Targeting Mirnas: A Systems Biology Approach for Marfan Syndrome
(Galenos Publishing House, 2025) Orhan, M.E.; Demirci, Y.M.; Saçar Demirci, M.D.S.; Demirci, Muserref Duygu Sacar
Objective: Marfan syndrome (MFS) is a genetic connective tissue disorder primarily caused by mutations in the FBN1 gene. Emerging evidence highlights the regulatory role of microRNAs (miRNAs) in modulating gene expression in MFS, but a systematic investigation into miRNAs targeting FBN1 is lacking. This study aimed to comprehensively identify miRNAs interacting with the FBN1 transcript to reveal potential molecular regulators and therapeutic targets. Methods: Human miRNA sequences were retrieved from miRBase (Release 22.1), and the canonical FBN1 transcript (RefSeq: NM_000138.5) was used for target prediction. Computational interaction analysis was conducted using the psRNATarget server with stringent parameters to detect potential miRNA binding sites. Expression profiles and disease associations of the top candidate miRNAs were further investigated through database integration and literature review. Results: Out of 2656 human mature miRNAs analyzed, 251 were predicted to bind FBN1, with the hsa-miR-181 family exhibiting the highest number of predicted interactions. Evidence from the literature highlighted dysregulation of hsa-miR-181 expression in MFS patients, suggesting a functional role in disease pathophysiology. Conclusion: This study identifies key members of the hsa-miR-181 family as post-transcriptional regulators of FBN1, offering new insights into miRNA-driven mechanisms in MFS. These findings support the potential of RNA-based diagnostics and therapeutic strategies targeting miRNA-FBN1 interactions. ©Copyright 2025 The Author.
Citation - WoS: 151
Citation - Scopus: 155
Computational Analysis of MicroRNA-Mediated Interactions in SARS-CoV Infection
(PeerJ Inc, 2020) Demirci, Muserref Duygu Sacar; Adan, Aysun
MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression found in more than 200 diverse organisms. Although it is still not fully established if RNA viruses could generate miRNAs, there are examples of miRNA like sequences from RNA viruses with regulatory functions. In the case of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there are several mechanisms that would make miRNAs impact the virus, like interfering with viral replication, translation and even modulating the host expression. In this study, we performed a machine learning based miRNA prediction analysis for the SARS-CoV-2 genome to identify miRNA-like hairpins and searched for potential miRNA-based interactions between the viral miRNAs and human genes and human miRNAs and viral genes. Overall, 950 hairpin structured sequences were extracted from the virus genome and based on the prediction results, 29 of them could be precursor miRNAs. Targeting analysis showed that 30 viral mature miRNA-like sequences could target 1,367 different human genes. PANTHER gene function analysis results indicated that viral derived miRNA candidates could target various human genes involved in crucial cellular processes including transcription, metabolism, defense system and several signaling pathways such as Wnt and EGFR signalings. Protein class-based grouping of targeted human genes showed that host transcription might be one of the main targets of the virus since 96 genes involved in transcriptional processes were potential targets of predicted viral miRNAs. For instance, basal transcription machinery elements including several components of human mediator complex (MED1, MED9, MED 12L, MED 19), basal transcription factors such as TAF4, TAF5, TAF7L and site-specific transcription factors such as STATI were found to be targeted. In addition, many known human miRNAs appeared to be able to target viral genes involved in viral life cycle such as S, M, N, E proteins and ORF lab, ORF3a, ORF8, ORF7a and ORF10. Considering the fact that miRNA-based therapies have been paid attention, based on the findings of this study, comprehending mode of actions of miRNAs and their possible roles during SARS-CoV-2 infections could create new opportunities for the development and improvement of new therapeutics.
Citation - WoS: 19
Citation - Scopus: 26
Computational Prediction of Functional MicroRNA-mRNA Interactions
(Humana Press Inc, 2019) Demirci, Muserref Duygu Sacar; Yousef, Malik; Allmer, Jens; Saçar Demirci, Müşerref Duygu
Proteins have a strong influence on the phenotype and their aberrant expression leads to diseases. MicroRNAs (miRNAs) are short RNA sequences which posttranscriptionally regulate protein expression. This regulation is driven by miRNAs acting as recognition sequences for their target mRNAs within a larger regulatory machinery. A miRNA can have many target mRNAs and an mRNA can be targeted by many miRNAs which makes it difficult to experimentally discover all miRNA-mRNA interactions. Therefore, computational methods have been developed for miRNA detection and miRNA target prediction. An abundance of available computational tools makes selection difficult. Additionally, interactions are not currently the focus of investigation although they more accurately define the regulation than pre-miRNA detection or target prediction could perform alone. We define an interaction including the miRNA source and the mRNA target. We present computational methods allowing the investigation of these interactions as well as how they can be used to extend regulatory pathways. Finally, we present a list of points that should be taken into account when investigating miRNA-mRNA interactions. In the future, this may lead to better understanding of functional interactions which may pave the way for disease marker discovery and design of miRNA-based drugs.
Integrative Bioinformatics Prediction of West Nile Virus-Derived microRNAs Reveals Potential Host Regulatory Interactions
(Elsevier Sci Ltd, 2026) Demirci, Muserref Duygu Sacar; Orhan, Mehmet Emin; Erginkoc, Altay Nida; Saçar Demirci, Müşerref Duygu
West Nile virus (WNV) is a mosquito-borne flavivirus linked to severe neuroinvasive disease. Although host and vector microRNAs (miRNAs) have been implicated in viral infection, the presence and functional relevance of WNV-encoded miRNAs remain largely unexplored. Here, we developed an integrative bioinformatics pipeline that combines multiple miRNA prediction algorithms with secondary structure screening and host transcriptomic data to identify high-confidence candidate WNV-derived mature miRNAs. Overlap-based confidence scoring and differential expression support from RNA-seq datasets prioritized a small subset of putative miRNA-mRNA interactions with potential roles in infection-associated gene regulation. A competitive endogenous RNA network constructed from predicted mRNA, lncRNA, and circRNA targets highlighted pathways involving innate immunity, GPCR and Wnt signaling, RNA degradation, and viral replication. Together, these findings provide a reproducible computational workflow and nominate testable regulatory interactions for future experimental validation.