Browsing by Author "Sezerman, Osman Ugur"

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A comprehensive study on identifying the structural and functional SNPs of human neuronal membrane glycoprotein M6A (GPM6A)
(TAYLOR \& FRANCIS INC, 2021-01-01) Khalid, Zoya; Sezerman, Osman Ugur
Glycoprotein M6A, a stress related gene, plays an important role in synapse and filopodia formation. Filopodia formation is vital for development, immunity, angiogenesis, wound healing and metastasis. In this study, structural and functional analysis of high-risk SNPs associated with Glycoprotein M6-A were evaluated using six different bioinformatics tools. Results classified T210I, T134I, Y153H, I215T, F156L, T160I, I226T, R247W, R178C, W159R, N157S and P151L as deleterious mutants that are crucial for the structure and function of the protein causing malfunction of M6-a and ultimately leads to disease development. The three-dimensional structure of wild-type M6-a and mutant M6-a were also predicted. Furthermore, the effects of high risk substitutions were also analyzed with interaction with valproic acid. Based on structural models obtained, the binding pocket of ligand bound glycoprotein M6-A structure showed few core interacting residues which are different in the mutant models. Among all substitutions, F156L showed complete loss of binding pocket when interacting with valproic acid as compared to the wild type model. Up to the best of our knowledge this is the first comprehensive study where GPM6A mutations were analyzed. The mechanism of action of GPM6A is still not fully defined which limits the understanding of functional details encoding M6-A. Our results may help enlighten some molecular aspects underlying glycoprotein M6-A. Communicated by Ramaswamy H. Sarma
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
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
Bridging the Bridging Imidazolate in the Bimetallic Center of the Cu/Zn SOD1 and ALS
(FRONTIERS MEDIA SA, 2021-01-01) Timucin, Ahmet Can; Cinaroglu, Suleyman Selim; Sezerman, Osman Ugur; Timucin, Emel
Metallation status of human Cu/Zn superoxide dismutase 1 (SOD1) plays a pivotal role in the pathogenesis of amyotrophic lateral sclerosis (ALS). All of the amino acids found in the bimetallic center have been associated with ALS except for two positions. H63 which forms the bridging imidazolate ion in the bimetallic center and K136 which is not directly involved in coordination but located in the bimetallic center were not reported to be mutated in any of the identified ALS cases. In this study, we investigated the structure and flexibility of five SOD1 variants by using classical molecular dynamics simulations. These variants include three substitutions on the non-ALS-linked positions
CogNet: classification of gene expression data based on ranked active-subnetwork- oriented KEGG pathway enrichment analysis
(PEERJ INC, 2021-01-01) Yousef, Malik; Ulgen, Ege; Sezerman, Osman Ugur
Most of the traditional gene selection approaches are borrowed from other fields such as statistics and computer science, However, they do not prioritize biologically relevant genes since the ultimate goal is to determine features that optimize model performance metrics not to build a biologically meaningful model. Therefore, there is an imminent need for new computational tools that integrate the biological knowledge about the data in the process of gene selection and machine learning. Integrative gene selection enables incorporation of biological domain knowledge from external biological resources. In this study, we propose a new computational approach named CogNet that is an integrative gene selection tool that exploits biological knowledge for grouping the genes for the computational modeling tasks of ranking and classification. In CogNet, the pathfindR serves as the biological grouping tool to allow the main algorithm to rank active-subnetwork-oriented KEGG pathway enrichment analysis results to build a biologically relevant model. CogNet provides a list of significant KEGG pathways that can classify the data with a very high accuracy. The list also provides the genes belonging to these pathways that are differentially expressed that are used as features in the classification problem. The list facilitates deep analysis and better interpretability of the role of KEGG pathways in classification of the data thus better establishing the biological relevance of these differentially expressed genes. Even though the main aim of our study is not to improve the accuracy of any existing tool, the performance of the CogNet outperforms a similar approach called maTE while obtaining similar performance compared to other similar tools including SVM-RCE. CogNet was tested on 13 gene expression datasets concerning a variety of diseases.
Computational analysis of missense filamin-A variants, including the novel p.Arg484Gln variant of two brothers with periventricular nodular heterotopia
(PUBLIC LIBRARY SCIENCE, 2022-01-01) Gerlevik, Umut; Saygi, Ceren; Cangul, Hakan; Kutlu, Asli; Caralan, Erdal Firat; Topcu, Yasemin; Ozoren, Nesrin; Sezerman, Osman Ugur
Background Periventricular nodular heterotopia (PNH) is a cell migration disorder associated with mutations in Filamin-A (FLNA) gene on chromosome X. Majority of the individuals with PNHassociated FLNA mutations are female whereas liveborn males with FLNA mutations are very rare. Fetal viability of the males seems to depend on the severity of the variant. Splicing or severe truncations presumed loss of function of the protein product, lead to male lethality and only partial-loss-of-function variants are reported in surviving males. Those variants mostly manifest milder clinical phenotypes in females and thus avoid detection of the disease in females. Methods We describe a novel p.Arg484Gln variant in the FLNA gene by performing whole exome analysis on the index case, his one affected brother and his healthy non-consanguineous parents. The transmission of PNH from a clinically asymptomatic mother to two sons is reported in a fully penetrant classical X-linked dominant mode. The variant was verified via Sanger sequencing. Additionally, we investigated the impact of missense mutations reported in affected males on the FLNa protein structure, dynamics and interactions by performing molecular dynamics (MD) simulations to examine the disease etiology and possible compensative mechanisms allowing survival of the males. Results We observed that p.Arg484Gln disrupts the FLNa by altering its structural and dynamical properties including the flexibility of certain regions, interactions within the protein, and conformational landscape of FLNa. However, these impacts existed for only a part the MD trajectories and highly similar patterns observed in the other 12 mutations reported in the liveborn males validated this mechanism. Conclusion It is concluded that the variants seen in the liveborn males result in transient pathogenic effects, rather than persistent impairments. By this way, the protein could retain its function occasionally and results in the survival of the males besides causing the disease.
Computational approaches for de novo design and redesign of metal-binding sites on proteins
(PORTLAND PRESS LTD, 2017-01-01) Akcapinar, Gunseli Bayram; Sezerman, Osman Ugur
Metal ions play pivotal roles in protein structure, function and stability. The functional and structural diversity of proteins in nature expanded with the incorporation of metal ions or clusters in proteins. Approximately one-third of these proteins in the databases contain metal ions. Many biological and chemical processes in nature involve metal ion-binding proteins, aka metalloproteins. Many cellular reactions that underpin life require metalloproteins. Most of the remarkable, complex chemical transformations are catalysed by metalloenzymes. Realization of the importance of metal-binding sites in a variety of cellular events led to the advancement of various computational methods for their prediction and characterization. Furthermore, as structural and functional knowledgebase about metalloproteins is expanding with advances in computational and experimental fields, the focus of the research is now shifting towards de novo design and redesign of metalloproteins to extend nature's own diversity beyond its limits. In this review, we will focus on the computational toolbox for prediction of metal ion-binding sites, de novo metalloprotein design and redesign. We will also give examples of tailor-made artificial metalloproteins designed with the computational
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.
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.
Enhancing Reuse of Data and Biological Material in Medical Research: From FAIR to FAIR-Health
(MARY ANN LIEBERT, INC, 2018-01-01) Holub, Petr; Kohlmayer, Florian; Prasser, Fabian; Mayrhofer, Michaela Th.; Schluender, Irene; Martin, Gillian M.; Casati, Sara; Koumakis, Lefteris; Wutte, Andrea; Kozera, Lukasz; Strapagiel, Dominik; Anton, Gabriele; Zanetti, Gianluigi; Sezerman, Osman Ugur; Mendy, Maimuna; Valik, Dalibor; Lavitrano, Marialuisa; Dagher, Georges; Zatloukal, Kurt; van Ommen, GertJan B.; Litton, Jan-Eric
The known challenge of underutilization of data and biological material from biorepositories as potential resources for medical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability-entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)-are likely to address only parts of the problem. In this article, we argue that biological material and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks. We propose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently.
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.
Identifying and elucidating the roles of Y198N and Y204F mutations in the PAH enzyme through molecular dynamic simulations
(TAYLOR \& FRANCIS INC, 2021-01-01) Aslan, Tolga; Yenenler-Kutlu, Asli; Gerlevik, Umut; Aktuglu Zeybek, Ayse Cigdem; Kiykim, Ertugrul; Sezerman, Osman Ugur; Birgul Iyison, Necla
Phenylketonuria is an autosomal recessive disorder caused by mutations in the phenylalanine hydroxylase gene. In phenylketonuria causes various symptoms including severe mental retardation. PAH gene of a classical Phenylketonuria patient was sequenced, and two novel heterozygous mutations, p.Y198N and p.Y204F, were found. This study aimed to reveal the impacts of these variants on the structural stability of the PAH enzyme. In-silico analyses using prediction tools and molecular dynamics simulations were performed. Mutations were introduced to the wild type catalytic monomer and full length tetramer crystal structures. Variant pathogenicity analyses predicted p.Y198N to be damaging, and p.Y204F to be benign by some prediction tools and damaging by others. Simulations suggested p.Y198N mutation cause significant fluctuations in the spatial organization of two catalytic residues in the temperature accelerated MD simulations with the monomer and increased root-mean-square deviations in the tetramer structure. p.Y204F causes noticeable changes in the spatial positioning of T278 suggesting a possible segregation from the catalytic site in temperature accelerated MD simulations with the monomer. This mutation also leads to increased root-mean-square fluctuations in the regulatory domain which may lead to conformational change resulting in inhibition of dimerization and enzyme activation. Our study reports two novel mutations in the PAH gene and gives insight to their effects on the PAH activity. MD simulations did not yield conclusive results that explains the phenotype but gave plausible insight to possible effects which should be investigated further with in-silico and in-vitro studies to assess the roles of these mutations in etiology of PKU. Communicated by Ramaswamy H. Sarma
Investigation of multiple sclerosis-related pathways through the integration of genomic and proteomic data
(PEERJ INC, 2021-01-01) Everest, Elif; Ulgen, Ege; Uygunoglu, Ugur; Tutuncu, Melih; Saip, Sabahattin; Sezerman, Osman Ugur; Siva, Aksel; Turanli, Eda Tahir
Background. Multiple sclerosis (MS) has a complex pathophysiology, variable clinical presentation, and unpredictable prognosis
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.
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.
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.
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)
RACK1 Is an Interaction Partner of ATG5 and a Novel Regulator of Autophagy
(AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC, 2016-01-01) Erbil, Secil; Oral, Ozlem; Mitou, Geraldine; Kig, Cenk; Durmaz-Timucin, Emel; Guven-Maiorov, Emine; Gulacti, Ferah; Gokce, Gokcen; Dengjel, Jorn; Sezerman, Osman Ugur; Gozuacik, Devrim
Autophagy is biological mechanism allowing recycling of long-lived proteins, abnormal protein aggregates, and damaged organelles under cellular stress conditions. Following sequestration in double-or multimembrane autophagic vesicles, the cargo is delivered to lysosomes for degradation. ATG5 is a key component of an E3-like ATG12-ATG5-ATG16 protein complex that catalyzes conjugation of the MAP1LC3 protein to lipids, thus controlling autophagic vesicle formation and expansion. Accumulating data indicate that ATG5 is a convergence point for autophagy regulation. Here, we describe the scaffold protein RACK1 (receptor activated C-kinase 1, GNB2L1) as a novel ATG5 interactor and an autophagy protein. Using several independent techniques, we showed that RACK1 interacted with ATG5. Importantly, classical autophagy inducers (starvation or mammalian target of rapamycin blockage) stimulated RACK1-ATG5 interaction. Knockdown of RACK1 or prevention of its binding to ATG5 using mutagenesis blocked autophagy activation. Therefore, the scaffold protein RACK1 is a new ATG5-interacting protein and an important and novel component of the autophagy pathways.
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.
Structural analysis of M1AP variants associated with severely impaired spermatogenesis causing male infertility
(PEERJ INC, 2022-01-01) Gerlevik, Umut; Ergoren, Mahmut Cerkez; Sezerman, Osman Ugur; Temel, Sehime Gulsun
Background: Impaired meiosis can result in absence of sperm in the seminal fluid. This condition, namely non-obstructive azoospermia (NOA), is one of the reasons of male infertility. Despite the low number of studies on meiosis 1-associated protein (M1AP) in the literature, MIAP is known to be crucial for spermatogenesis. Recently, seven variants (five missense, one frameshift, one splice-site) have been reported in the MIAP gene as associated with NOA, cryptozoospermia and oligozoospermia in two separate studies. However, all missense variants were evaluated as variant of uncertain significance by these studies. Therefore, we aimed to analyze their structural impacts on the M1AP protein that could lead to NOA. Methods: We firstly performed an evolutionary conservation analysis for the variant positions. Afterwards, a comprehensive molecular modelling study was performed for the M1AP structure. By utilizing this model, protein dynamics were sampled for the wild-type and variants by performing molecular dynamics (MD) simulations. Results: All variant positions are highly conserved, indicating that they are potentially important for function. In MD simulations, none of the variants led to a general misfolding or loss of stability in the protein structure, but they did cause severe modifications in the conformational dynamics of M1AP, particularly through changes in local interactions affecting flexibility, hinge and secondary structure. Conclusions: Due to critical perturbations in protein dynamics, we propose that these variants may cause NOA by affecting important interactions regulating meiosis, particularly in wild-type M1AP deficiency since the variants are reported to be homozygous or bi-allelic in the infertile individuals. Our results provided reasonable insights about the MIAP structure and the effects of the variants to the structure and dynamics, which should be further investigated by experimental studies to validate.