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: 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: 11Citation - Scopus: 14Categorization of Species Based on Their Micrornas Employing Sequence Motifs, Information-Theoretic Sequence Feature Extraction, and K-Mers(Springer Verlag, 2017) Yousef, Malik; Nigatu, Dawit; Levy, Dalit; Allmer, Jens; Henkel, WernerBackground: Diseases like cancer can manifest themselves through changes in protein abundance, and microRNAs (miRNAs) play a key role in the modulation of protein quantity. MicroRNAs are used throughout all kingdoms and have been shown to be exploited by viruses to modulate their host environment. Since the experimental detection of miRNAs is difficult, computational methods have been developed. Many such tools employ machine learning for pre-miRNA detection, and many features for miRNA parameterization have been proposed. To train machine learning models, negative data is of importance yet hard to come by; therefore, we recently started to employ pre-miRNAs from one species as positive data versus another species’ pre-miRNAs as negative examples based on sequence motifs and k-mers. Here, we introduce the additional usage of information-theoretic (IT) features. Results: Pre-miRNAs from one species were used as positive and another species’ pre-miRNAs as negative training data for machine learning. The categorization capability of IT and k-mer features was investigated. Both feature sets and their combinations yielded a very high accuracy, which is as good as the previously suggested sequence motif and k-mer based method. However, for obtaining a high performance, a sufficiently large phylogenetic distance between the species and sufficiently high number of pre-miRNAs in the training set is required. To examine the contribution of the IT and k-mer features, an information gain-based feature ranking was performed. Although the top 3 are IT features, 80% of the top 100 features are k-mers. The comparison of all three individual approaches (motifs, IT, and k-mers) shows that the distinction of species based on their pre-miRNAs k-mers are sufficient. Conclusions: IT sequence feature extraction enables the distinction among species and is less computationally expensive than motif calculations. However, since IT features need larger amounts of data to have enough statistics for producing highly accurate results, future categorization into species can be effectively done using k-mers only. The biological reasoning for this is the existence of a codon bias between species which can, at least, be observed in exonic miRNAs. Future work in this direction will be the ab initio detection of pre-miRNA. In addition, prediction of pre-miRNA from RNA-seq can be done.Article Citation - WoS: 20Citation - Scopus: 25Microrna Categorization Using Sequence Motifs and K-Mers(BioMed Central Ltd., 2017) Yousef, Malik; Khalifa, Waleed; Acar, İlhan Erkin; Allmer, JensBackground: Post-transcriptional gene dysregulation can be a hallmark of diseases like cancer and microRNAs (miRNAs) play a key role in the modulation of translation efficiency. Known pre-miRNAs are listed in miRBase, and they have been discovered in a variety of organisms ranging from viruses and microbes to eukaryotic organisms. The computational detection of pre-miRNAs is of great interest, and such approaches usually employ machine learning to discriminate between miRNAs and other sequences. Many features have been proposed describing pre-miRNAs, and we have previously introduced the use of sequence motifs and k-mers as useful ones. There have been reports of xeno-miRNAs detected via next generation sequencing. However, they may be contaminations and to aid that important decision-making process, we aimed to establish a means to differentiate pre-miRNAs from different species. Results: To achieve distinction into species, we used one species' pre-miRNAs as the positive and another species' pre-miRNAs as the negative training and test data for the establishment of machine learned models based on sequence motifs and k-mers as features. This approach resulted in higher accuracy values between distantly related species while species with closer relation produced lower accuracy values. Conclusions: We were able to differentiate among species with increasing success when the evolutionary distance increases. This conclusion is supported by previous reports of fast evolutionary changes in miRNAs since even in relatively closely related species a fairly good discrimination was possible.Article Citation - WoS: 14Citation - Scopus: 14Polythiophene Derivative on Quartz Resonators for Mirna Capture and Assay(Royal Society of Chemistry, 2015) Palaniappan, Al.; Cheema, Jamal Ahmed; Rajwar, Deepa; Ammanath, Gopal; Xiaohu, Liu; Seng Koon, Lim; Yi, Wang; Yıldız, Ümit Hakan; Liedberg, BoA novel approach for miRNA assay using a cationic polythiophene derivative, poly[3-(3′-N,N,N-triethylamino-1′-propyloxy)-4-methyl-2,5-thiophene hydrobromide] (PT), immobilized on a quartz resonator is proposed. The cationic PT enables capturing of all RNA sequences in the sample matrix via electrostatic interactions, resulting in the formation of PT-RNA duplex structures on quartz resonators. Biotinylated peptide nucleic acid (b-PNA) sequences are subsequently utilized for the RNA assay, upon monitoring the PT-RNA-b-PNA triplex formation. Signal amplification is achieved by anchoring avidin coated nanoparticles to b-PNA in order to yield responses at clinically relevant concentration regimes. Unlike conventional nucleic acid assay methodologies that usually quantify a specific sequence of RNA, the proposed approach enables the assay of any RNA sequence in the sample matrix upon hybridization with a PNA sequence complementary to the RNA of interest. As an illustration, successful detection of mir21, (a miRNA sequence associated with lung cancer) is demonstrated with a limit of detection of 400 pM. Furthermore, precise quantification of mir21 in plasma samples is demonstrated without requiring PCR and sophisticated instrumentation.