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    SARS-CoV-2 isolation and propagation from Turkish COVID-19 patients
    (2004-01-01) Tastan, Cihan; Yurtsever, Bulut; Karakus, Gozde Sir; Kancagi, Derya Dilek; Demir, Sevda; Abanuz, Selen; Seyis, Utku; Yildirim, Mulazim; Kuzay, Recai; Elibol, Omer; Arbak, Serap; Elmas, Merve Acikel; Birdogan, Selcuk; Sezerman, Osman Ugur; Kocagoz, Aye Sesin; Yalcin, Koray; Ovali, Ercument
    The novel coronavirus pneumonia, which was named later as coronavirus disease 2019 (COVID-19), is caused by the severe acute respiratory syndrome coronavirus 2, namely SARS-CoV-2. It is a positive-strand RNA virus that is the seventh coronavirus known to infect humans. The COVID-19 outbreak presents enormous challenges for global health behind the pandemic outbreak. The first diagnosed patient in Turkey has been reported by the Republic of Turkey Ministry of Health on March 11, 2020. In May, over 150,000 cases in Turkey, and 5.5 million cases around the world have been declared. Due to the urgent need for a vaccine and antiviral drug, isolation of the virus is crucial. Here, we report 1 of the first isolation and characterization studies of SARS-CoV-2 from nasopharyngeal and oropharyngeal specimens of diagnosed patients in Turkey. This study provides an isolation and replication methodology,and cell culture tropism of the virus that will be available to the research communities.
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    Adaptive phenotypic modulations lead to therapy resistance in chronic myeloid leukemia cells
    (PUBLIC LIBRARY SCIENCE, 2020-01-01) Baykal-Kose, Seda; Acikgoz, Eda; Yavuz, Ahmet Sinan; Geyik, Oyku Gonul; Ate, Halil; Sezerman, Osman Ugur; Ozsan, Guner Hayri; Yuce, Zeynep
    Tyrosine kinase inhibitor (TKI) resistance is a major problem in chronic myeloid leukemia (CML). We generated a TKI-resistant K562 sub-population, K562-IR, under selective imatinib-mesylate pressure. K562-IR cells are CD34(-)/CD38(-), BCR-Abl-independent, proliferate slowly, highly adherent and form intact tumor spheroids. Loss of CD45 and other hematopoietic markers reveal these cells have diverged from their hematopoietic origin. CD34 negativity, high expression of E-cadherin and CD44
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    Probing the Structural Dynamics of the Catalytic Domain of Human Soluble Guanylate Cyclase
    (NATURE PUBLISHING GROUP, 2020-01-01) Khalid, Rana Rehan; Maryam, Arooma; Sezerman, Osman Ugur; Mylonas, Efstratios; Siddiqi, Abdul Rauf; Kokkinidis, Michael
    In the nitric oxide (NO) signaling pathway, human soluble guanylate cyclase (hsGC) synthesizes cyclic guanosine monophosphate (cGMP)
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    Identification of epilepsy related pathways using genome-wide DNA methylation measures: A trio-based approach
    (PUBLIC LIBRARY SCIENCE, 2019-01-01) Ozdemir, Ozkan; Egemen, Ece; Iseri, Sibel Aylin Ugur; Sezerman, Osman Ugur; Bebek, Nerses; Baykan, Betul; Ozbek, Ugur
    Genetic generalized epilepsies (GGE) are genetically determined, as their name implies and they are clinically characterized by generalized seizures involving both sides of the brain in the absence of detectable brain lesions or other known causes. GGEs are yet complex and are influenced by many different genetic and environmental factors. Methylation specific epigenetic marks are one of the players of the complex epileptogenesis scenario leading to GGE. In this study, we have set out to perform genome-wide methylation profiling to analyze GGE trios each consisting of an affected parent-offspring couple along with an unaffected parent. We have developed a novel scoring scheme within trios to categorize each locus analyzed as hypo or hypermethylated. This stringent approach classified differentially methylated genes in each trio and helped us to produce trio specific and pooled gene lists with inherited and aberrant methylation levels. In order to analyze the methylation differences from a boarder perspective, we performed enrichment analysis with these lists using the PANOGA software. This collective effort has led us to detect pathways associated with the GGE phenotype, including the neurotrophin signaling pathway. We have demonstrated a trio based approach to genome-wide DNA methylation analysis that identified individual and possibly minor changes in methylation marks that could be involved in epileptogenesis leading to GGE.
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    Prediction of neddylation sites from protein sequences and sequence-derived properties
    (BMC, 2015-01-01) Yavuz, Ahmet Sinan; Sozer, Namik Berk; Sezerman, Osman Ugur
    Background: Neddylation is a reversible post-translational modification that plays a vital role in maintaining cellular machinery. It is shown to affect localization, binding partners and structure of target proteins. Disruption of protein neddylation was observed in various diseases such as Alzheimer's and cancer. Therefore, understanding the neddylation mechanism and determining neddylation targets possibly bears a huge importance in further understanding the cellular processes. This study is the first attempt to predict neddylated sites from protein sequences by using several sequence and sequence-based structural features. Results: We have developed a neddylation site prediction method using a support vector machine based on various sequence properties, position-specific scoring matrices, and disorder. Using 21 amino acid long lysinecentred windows, our model was able to predict neddylation sites successfully, with an average 5-fold stratified cross validation performance of 0.91, 0.91, 0.75, 0.44, 0.95 for accuracy, specificity, sensitivity, Matthew's correlation coefficient and area under curve, respectively. Independent test set results validated the robustness of reported new method. Additionally, we observed that neddylation sites are commonly flexible and there is a significant positively charged amino acid presence in neddylation sites. Conclusions: In this study, a neddylation site prediction method was developed for the first time in literature. Common characteristics of neddylation sites and their discriminative properties were explored for further in silico studies on neddylation. Lastly, up-to-date neddylation dataset was provided for researchers working on post-translational modifications in the accompanying supplementary material of this article.
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    A novel analysis strategy for integrating methylation and expression data reveals core pathways for thyroid cancer aetiology
    (BMC, 2015-01-01) Ozer, Bugra; Sezerman, Osman Ugur
    Background: Recently, a wide range of diseases have been associated with changes in DNA methylation levels, which play a vital role in gene expression regulation. With ongoing developments in technology, attempts to understand disease mechanism have benefited greatly from epigenetics and transcriptomics studies. In this work, we have used expression and methylation data of thyroid carcinoma as a case study and explored how to optimally incorporate expression and methylation information into the disease study when both data are available. Moreover, we have also investigated whether there are important post-translational modifiers which could drive critical insights on thyroid cancer genetics. Results: In this study, we have conducted a threshold analysis for varying methylation levels to identify whether setting a methylation level threshold increases the performance of functional enrichment. Moreover, in order to decide on best-performing analysis strategy, we have performed data integration analysis including comparison of 10 different analysis strategies. As a result, combining methylation with expression and using genes with more than 15\% methylation change led to optimal detection rate of thyroid-cancer associated pathways in top 20 functional enrichment results. Furthermore, pooling the data from different experiments increased analysis confidence by improving the data range. Consequently, we have identified 207 transcription factors and 245 post-translational modifiers with more than 15\% methylation change which may be important in understanding underlying mechanisms of thyroid cancer. Conclusion: While only expression or only methylation information would not reveal both primary and secondary mechanisms involved in disease state, combining expression and methylation led to a better detection of thyroid cancer-related genes and pathways that are found in the recent literature. Moreover, focusing on genes that have certain level of methylation change improved the functional enrichment results, revealing the core pathways involved in disease development such as
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    Ligand binding pocket of a novel Allatostatin receptor type C of stick insect, Carausius morosus
    (NATURE PUBLISHING GROUP, 2017-01-01) Sahbaz, Burcin Duan; Sezerman, Osman Ugur; Torun, Hamdi; Iyison, Necla Birgul
    Allatostatins (AST) are neuropeptides with variable function ranging from regulation of developmental processes to the feeding behavior in insects. They exert their effects by binding to cognate GPCRs, called Allatostatin receptors (AlstR), which emerge as promising targets for pesticide design. However, AlstRs are rarely studied. This study is the first reported structural study on AlstR-AST interaction. In this work, the first C type AlstR from the stick insect Carausius morosus (CamAlstR-C) was identified and its interaction with type C AST peptide was shown to be physically consistent with the experimental results. The proposed structure of CamAlstR-C revealed a conserved motif within the third extracellular loop, which, together with the N-terminus is essential for ligand binding. In this work, computational studies were combined with molecular and nano-scale approaches in order to introduce an unknown GPCR-ligand system. Consequently, the data obtained provided a reliable target region for future agonist/inverse agonist studies on AlstRs.
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    Enhancing Enzymatic Properties of Endoglucanase I Enzyme from Trichoderma Reesei via Swapping from Cellobiohydrolase I Enzyme
    (MDPI, 2019-01-01) Yenenler, Asli; Kurt, Hasan; Sezerman, Osman Ugur
    Utilizing plant-based materials as a biofuel source is an increasingly popular attempt to redesign the global energy cycle. This endeavour underlines the potential of cellulase enzymes for green energy production and requires the structural and functional engineering of natural enzymes to enhance their utilization. In this work, we aimed to engineer enzymatic and functional properties of Endoglucanase I (EGI) by swapping the Ala43-Gly83 region of Cellobiohydrolase I (CBHI) from Trichoderma reesei. Herein, we report the enhanced enzymatic activity and improved thermal stability of the engineered enzyme, called EGI\_swapped, compared to EGI. The difference in the enzymatic activity profile of EGI\_swapped and the EGI enzymes became more pronounced upon increasing metal-ion concentrations in the reaction media. Notably, the engineered enzyme retained a considerable level of enzymatic activity after thermal incubation for 90 min at 70 degrees C while EGI completely lost its enzymatic activity. Circular Dichroism spectroscopy studies revealed distinctive conformational and thermal susceptibility differences between EGI\_swapped and EGI enzymes, confirming the improved structural integrity of the swapped enzyme. This study highlights the importance of swapping the metal-ion coordination region in the engineering of EGI enzyme for enhanced structural and thermal stability.
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    pathfindR: An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks
    (FRONTIERS MEDIA SA, 2019-01-01) Ulgen, Ege; Ozisik, Ozan; Sezerman, Osman Ugur
    Pathway analysis is often the first choice for studying the mechanisms underlying a phenotype. However, conventional methods for pathway analysis do not take into account complex protein-protein interaction information, resulting in incomplete conclusions. Previously, numerous approaches that utilize protein-protein interaction information to enhance pathway analysis yielded superior results compared to conventional methods. Hereby, we present pathfindR, another approach exploiting protein-protein interaction information and the first R package for active-subnetwork-oriented pathway enrichment analyses for class comparison omics experiments. Using the list of genes obtained from an omics experiment comparing two groups of samples, pathfindR identifies active subnetworks in a protein-protein interaction network. It then performs pathway enrichment analyses on these identified subnetworks. To further reduce the complexity, it provides functionality for clustering the resulting pathways. Moreover, through a scoring function, the overall activity of each pathway in each sample can be estimated. We illustrate the capabilities of our pathway analysis method on three gene expression datasets and compare our results with those obtained from three popular pathway analysis tools. The results demonstrate that literature-supported disease-related pathways ranked higher in our approach compared to the others. Moreover, pathfindR identified additional pathways relevant to the conditions that were not identified by other tools, including pathways named after the conditions.
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    Design and characterizations of two novel cellulases through single-gene shuffling of Cel12A (EG3) gene from Trichoderma reseei
    (OXFORD UNIV PRESS, 2016-01-01) Yenenler, Asli; Sezerman, Osman Ugur
    Cellulases have great potential to be widely used for industrial applications. In general, naturally occurring cellulases are not optimized and limited to meet the industrial needs. These limitations lead to demand for novel cellulases with enhanced enzymatic properties. Here, we describe the enzymatic and structural properties of two novel enzymes, EG3\_S1 and EG3\_S2, obtained through the single-gene shuffling approach of Cel12A(EG3) gene from Trichoderma reseei. EG3\_S1 and EG3\_S2 shuffled enzymes display 59 and 75\% identity in protein sequence with respect to native, respectively. Toward 4-MUC, the minimum activity of EG3\_S1 was reported as 5.9-fold decrease in native at 35 degrees C, whereas the maximum activity of EG3\_S2 was reported as 15.4-fold increase in native activity at 40 degrees C. Also, the diminished enzyme activity of EG3\_S1 was reported within range of 0.6-to 0.8-fold of native and within range of 0.5-to 0.7-fold of native toward CMC and Na-CMC, respectively. For EG3\_S2 enzyme, the improved enzymatic activities within range of 1.1- to 1.4-fold of native and within range of 1.1-to 1.6-fold of nativewere reported toward CMC and Na-CMC, respectively. Moreover, we have reported 6.5-fold increase in the kcat/Km ratio of EG3\_S2 with respect to native and suggested EG3\_S2 enzyme as more efficient catalysis for hydrolysis reactions than its native counterpart.