WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article 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, VolkanTay-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.Article Citation - WoS: 11Citation - Scopus: 14MicroRNA-155 plays selective cell-intrinsic roles in brain-infiltrating immune cell populations during neuroinflammation(American Association of Immunologists, 2023) Thompson, J.W.; Hu, R.; Huffaker, T.B.; Ramstead, A.G.; Ekiz, Hüseyin Atakan; Bauer, K.M.; Tang, W.W.The proinflammatory microRNA-155 (miR-155) is highly expressed in the serum and CNS lesions of patients with multiple sclerosis (MS). Global knockout (KO) of miR-155 in mice confers resistance to a mouse model of MS, experimental autoimmune encephalomyelitis (EAE), by reducing the encephalogenic potential of CNS-infiltrating Th17 T cells. However, cell-intrinsic roles for miR-155 during EAE have not been formally determined. In this study, we use single-cell RNA sequencing and cell-specific conditional miR-155 KOs to determine the importance of miR-155 expression in distinct immune cell populations. Time-course single-cell sequencing revealed reductions in T cells, macrophages, and dendritic cells (DCs) in global miR-155 KO mice compared with wild-type controls at day 21 after EAE induction. Deletion of miR-155 in T cells, driven by CD4 Cre, significantly reduced disease severity similar to global miR-155 KOs. CD11c Cre-mediated deletion of miR-155 in DCs also resulted in a modest yet significant reduction in the development of EAE, with both T cell- and DC-specific KOs showing a reduction in Th17 T cell infiltration into the CNS. Although miR-155 is highly expressed in infiltrating macrophages during EAE, deletion of miR-155 using LysM Cre did not impact disease severity. Taken together, these data show that although miR-155 is highly expressed in most infiltrating immune cells, miR-155 has distinct roles and requirements depending on the cell type, and we have demonstrated this using the gold standard conditional KO approach. This provides insights into which functionally relevant cell types should be targeted by the next generation of miRNA therapeutics. Copyright © 2023 by The American Association of Immunologists, Inc.Article Citation - WoS: 19Citation - Scopus: 24Intracytoplasmic Re-Localization of Mirisc Complexes(Frontiers Media S.A., 2018) Akgül, Bünyamin; Erdoğan, İpekMicroRNAs (miRNAs) are a conserved class of non-coding RNAs of 22 nucleotides that post-transcriptionally regulate gene expression through translational repression and/or mRNA degradation. A great progress has been made regarding miRNA biogenesis and miRNA-mediated gene regulation. Additionally, an ample amount of information exists with respect to the regulation of miRNAs. However, the cytoplasmic localization of miRNAs and its effect on gene regulatory output is still in progress. We provide a current review of the cytoplasmic miRNA localization in metazoans. We then discuss the dynamic changes in the intracytoplasmic localization of miRNAs as a means to regulate their silencing activity. We then conclude our discussion with the potential molecules that could modulate miRNA localization.Article Citation - WoS: 14Visualization and Analysis of Micrornas Within Kegg Pathways Using Vanesa(Walter de Gruyter GmbH, 2017) Hamzeiy, Hamid; Suluyayla, Rabia; Brinkrolf, Christoph; Janowski, Sebastian Jan; Hofestaedt, Ralf; Allmer, JensMicroRNAs (miRNAs) are small RNA molecules which are known to take part in post-transcriptional regulation of gene expression. Here, VANESA, an existing platform for reconstructing, visualizing, and analysis of large biological networks, has been further expanded to include all experimentally validated human miRNAs available within miRBase, TarBase and miRTarBase. This is done by integrating a custom hybrid miRNA database to DAWIS-M.D., VANESA's main data source, enabling the visualization and analysis of miRNAs within large biological pathways such as those found within the Kyoto Encyclopedia of Genes and Genomes (KEGG). Interestingly, 99.15 % of human KEGG pathways either contain genes which are targeted by miRNAs or harbor them. This is mainly due to the high number of interaction partners that each miRNA could have (e.g.: hsa-miR-335-5p targets 2544 genes and 71 miRNAs target NUFIP2). We demonstrate the usability of our system by analyzing the measles virus KEGG pathway as a proof-of-principle model and further highlight the importance of integrating miRNAs (both experimentally validated and predicted) into biological networks for the elucidation of novel miRNA-mRNA interactions of biological importance.Article Citation - WoS: 4Citation - Scopus: 4Improving the Quality of Positive Datasets for the Establishment of Machine Learning Models for Pre-Microrna Detection(Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.), 2017) Saçar Demirci, Müşerref Duygu; Allmer, JensMicroRNAs (miRNAs) are involved in the post-transcriptional regulation of protein abundance and thus have a great impact on the resulting phenotype. It is, therefore, no wonder that they have been implicated in many diseases ranging from virus infections to cancer. This impact on the phenotype leads to a great interest in establishing the miRNAs of an organism. Experimental methods are complicated which led to the development of computational methods for pre-miRNA detection. Such methods generally employ machine learning to establish models for the discrimination between miRNAs and other sequences. Positive training data for model establishment, for the most part, stems from miRBase, the miRNA registry. The quality of the entries in miRBase has been questioned, though. This unknown quality led to the development of filtering strategies in attempts to produce high quality positive datasets which can lead to a scarcity of positive data. To analyze the quality of filtered data we developed a machine learning model and found it is well able to establish data quality based on intrinsic measures. Additionally, we analyzed which features describing pre-miRNAs could discriminate between low and high quality data. Both models are applicable to data from miRBase and can be used for establishing high quality positive data. This will facilitate the development of better miRNA detection tools which will make the prediction of miRNAs in disease states more accurate. Finally, we applied both models to all miRBase data and provide the list of high quality hairpins.Article Citation - WoS: 11Citation - Scopus: 11The Expressed Microrna-Mrna Interactions of Toxoplasma Gondii(Frontiers Media S.A., 2018) Acar, İlhan Erkin; Saçar Demirci, Müşerref Duygu; Groß, Uwe; Allmer, JensMicroRNAs (miRNAs) are involved in post-transcriptional modulation of gene expression and thereby have a large influence on the resulting phenotype. We have previously shown that miRNAs may be involved in the communication between Toxoplasma gondii and its hosts and further confirmed a number of proposed specific miRNAs. Yet, little is known about the internal regulation via miRNAs in T. gondii. Therefore, we predicted pre-miRNAs directly from the type II ME49 genome and filtered them. For the confident hairpins, we predicted the location of the mature miRNAs and established their target genes. To add further confidence, we evaluated whether the hairpins and their targets were co-expressed. Such co-expressed miRNA and target pairs define a functional interaction. We extracted all such functional interactions and analyzed their differential expression among strains of all three clonal lineages (RH, PLK, and CTG) and between the two stages present in the intermediate host (tachyzoites and bradyzoites). Overall, we found ~65,000 expressed interactions of which ~5,500 are differentially expressed among strains but none are significantly differentially expressed between developmental stages. Since miRNAs and target decoys can be used as therapeutics we believe that the list of interactions we provide will lead to novel approaches in the treatment of toxoplasmosis.Article Citation - WoS: 6Citation - Scopus: 8Deep Sequencing Reveals Two Jurkat Subpopulations With Distinct Mirna Profiles During Camptothecin-Induced Apoptosis(TUBITAK, 2018) Erdoğan, İpek; Coşacak, Mehmet İlyas; Nalbant, Ayten; Akgül, BünyaminMicroRNAs (miRNAs) are small noncoding RNAs of about 19-25 nt that regulate gene expression posttranscriptionally under various cellular conditions, including apoptosis. The miRNAs involved in modulation of apoptotic events in T cells are partially known. However, heterogeneity associated with cell lines makes it difficult to interpret gene expression signatures, especially in cancer-related cell lines. Treatment of the Jurkat T-cell leukemia cell line with the universal apoptotic drug, camptothecin, resulted in identification of two Jurkat subpopulations: one that is sensitive to camptothecin and another that is rather intrinsically resistant. We sorted apoptotic Jurkat cells from nonapoptotic ones prior to profiling miRNAs through deep sequencing. Our data showed that a total of 184 miRNAs were dysregulated. Interestingly, the apoptotic and nonapoptotic subpopulations exhibited distinct miRNA expression profiles. In particular, 6 miRNAs were inversely expressed in these two subpopulations. The pyrosequencing results were validated by real-time qPCR. Altogether, these results suggest that miRNAs modulate apoptotic events in T cells and that cellular heterogeneity requires careful interpretation of miRNA expression profiles obtained from drug-treated cell lines.Article Citation - WoS: 10Citation - Scopus: 11Intersection of Microrna and Gene Regulatory Networks and Their Implication in Cancer(Bentham Science Publishers B.V., 2014) Yousef, Malik; Trinh, Hung V.; Allmer, JensMicroRNAs (miRNAs) have attracted heightened attention for their role as post-transcriptional regulators of gene expression. It has become clear that miRNAs can both up- and downregulate protein expression. According to current estimates, most human genes are harboring miRNAs and/or are regulated by them. Thus miRNAs form a complex network of expression regulation which tightly interacts with known gene regulatory networks. Similar to some transcription factors, some miRNAs can have hundreds of target transcripts whose expression they modulate. Thus miRNAs can form complex regulatory networks by themselves, but because their expression is often tightly coordinated with gene expression, they form an intertwined regulatory network with many possible interactions among gene and miRNA regulatory pathways. In this review we first consider gene regulatory networks. Then we discuss microRNAs and their implication in cancer and how they may form regulatory networks. Finally, we give our perspective and provide an outlook including the aspect of personalized medicine.Article Citation - WoS: 16Citation - Scopus: 18Computational and Bioinformatics Methods for Microrna Gene Prediction(Humana Press, 2014) Allmer, JensMicroRNAs (miRNAs) have attracted ever-increasing interest in recent years. Since experimental approaches for determining miRNAs are nontrivial in their application, computational methods for the prediction of miRNAs have gained popularity. Such methods can be grouped into two broad categories (1) performing ab initio predictions of miRNAs from primary sequence alone and (2) additionally employing phylogenetic conservation. Most methods acknowledge the importance of hairpin or stem-loop structures and employ various methods for the prediction of RNA secondary structure. Machine learning has been employed in both categories with classification being the predominant method. In most cases, positive and negative examples are necessary for performing classification. Since it is currently elusive to experimentally determine all possible miRNAs for an organism, true negative examples are hard to come by, and therefore the accuracy assessment of algorithms is hampered. In this chapter, first RNA secondary structure prediction is introduced since it provides a basis for miRNA prediction. This is followed by an assessment of homology and then ab initio miRNA prediction methods.Article Citation - WoS: 37Citation - Scopus: 46Computational Methods for Microrna Target Prediction(Humana Press, 2014) Hamzeiy, Hamid; Yousef, Malik; Allmer, JensMicroRNAs (miRNAs) are important players in gene regulation. The final and maybe the most important step in their regulatory pathway is the targeting. Targeting is the binding of the miRNA to the mature RNA via the RNA-induced silencing complex. Expression patterns of miRNAs are highly specific in respect to external stimuli, developmental stage, or tissue. This is used to diagnose diseases such as cancer in which the expression levels of miRNAs are known to change considerably. Newly identified miRNAs are increasing in number with every new release of miRBase which is the main online database providing miRNA sequences and annotation. Many of these newly identified miRNAs do not yet have identified targets. This is especially the case in animals where the miRNA does not bind to its target as perfectly as it does in plants. Valid targets need to be identified for miRNAs in order to properly understand their role in cellular pathways. Experimental methods for target validations are difficult, expensive, and time consuming. Having considered all these facts it is of crucial importance to have accurate computational miRNA target predictions. There are many proposed methods and algorithms available for predicting targets for miRNAs, but only a few have been developed to become available as independent tools and software. There are also databases which collect and store information regarding predicted miRNA targets. Current approaches to miRNA target prediction produce a huge amount of false positive and an unknown amount of false negative results, and thus the need for better approaches is evermore evident. This chapter aims to give some detail about the current tools and approaches used for miRNA target prediction, provides some grounds for their comparison, and outlines a possible future.
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