Molecular Biology and Genetics / Moleküler Biyoloji ve Genetik
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Book Part Citation - Scopus: 444 Current Challenges in Mirnomics(Humana Press, 2022) Akgül, Bünyamin; Stadler, Peter F.; Hawkins, Liam J.; Hadj-Moussa, Hanane; Storey, Kenneth B.; Ergin, Kemal; Allmer, JensMature microRNAs (miRNAs) are short RNA sequences about 18–24 nucleotide long, which provide the recognition key within RISC for the posttranscriptional regulation of target RNAs. Considering the canonical pathway, mature miRNAs are produced via a multistep process. Their transcription (pri-miRNAs) and first processing step via the microprocessor complex (pre-miRNAs) occur in the nucleus. Then they are exported into the cytosol, processed again by Dicer (dsRNA) and finally a single strand (mature miRNA) is incorporated into RISC (miRISC). The sequence of the incorporated miRNA provides the function of RNA target recognition via hybridization. Following binding of the target, the mRNA is either degraded or translation is inhibited, which ultimately leads to less protein production. Conversely, it has been shown that binding within the 5? UTR of the mRNA can lead to an increase in protein product. Regulation of homeostasis is very important for a cell; therefore, all steps in the miRNA-based regulation pathway, from transcription to the incorporation of the mature miRNA into RISC, are under tight control. While much research effort has been exerted in this area, the knowledgebase is not sufficient for accurately modelling miRNA regulation computationally. The computational prediction of miRNAs is, however, necessary because it is not feasible to investigate all possible pairs of a miRNA and its target, let alone miRNAs and their targets. We here point out open challenges important for computational modelling or for our general understanding of miRNA-based regulation and show how their investigation is beneficial. It is our hope that this collection of challenges will lead to their resolution in the near future. © 2022, Springer Science+Business Media, LLC, part of Springer Nature.Article Citation - WoS: 13Citation - Scopus: 15Cytotoxic Tolerance of Healthy and Cancerous Bone Cells To Anti-Microbial Phenolic Compounds Depend on Culture Conditions(Humana Press, 2019) Karadaş, Özge; Meşe, Gülistan; Özçivici, EnginCarnosol and carnosic acid are polyphenolic compounds found in rosemary and sage with known anti-oxidant, anti-inflammatory, and anti-microbial properties. Here, we addressed the potential use of carnosol and carnosic acid for in vitro bone tissue engineering applications, specifically depending on their cytotoxic effects on bone marrow stromal and stem cells, and osteosarcoma cells in monolayer and 3D cultures. Carnosol and carnosic acid displayed a bacteriostatic effect on Gram-positive bacteria, especially on S. aureus. The viability results indicated that bone marrow stromal cells and bone marrow stem cells were more tolerant to the presence of carnosol compared to osteosarcoma cells. 3D culture conditions increased this tolerance further for healthy cells, while not affecting the cytotoxic potential of carnosol for osteosarcoma cells. Carnosic acid was found to be more cytotoxic for all cell types used in the study. Results suggest that phenolic compounds might have potential use as anti-microbial and anti-carcinogenic agents for bone tissue engineering with further optimization for controlled release.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.Article Citation - Scopus: 18Organogenesis From Transformed Tomato Explants(Humana Press, 2005) Frary, Anne; Van Eck, JoyceTomato was one of the first crops for which a genetic transformation system was reported involving regeneration by organogenesis from Agrobacterium-transformed explants. Since the initial reports, various factors have been studied that affect the efficiency of tomato transformation and the technique has been useful for the isolation and identification of many genes involved in plant disease resistance, morphology and development. In this method, cotyledon explants from in vitro-grown seedlings are precultured overnight on a tobacco suspension feeder layer. The explants are then inoculated with Agrobacterium and returned to the feeder layer for a 2-d period of cocultivation. After cocultivation, the explants are transferred to an MS-based selective regeneration medium containing zeatin. Regenerated shoots are then rooted on a separate selective medium. This protocol has been used with several tomato cultivars and routinely yields transformation efficiencies of 10-15%.Article Citation - WoS: 30Machine Learning Methods for Microrna Gene Prediction(Humana Press, 2014) Saçar, Müşerref Duygu; Allmer, JensMicroRNAs (miRNAs) are single-stranded, small, noncoding RNAs of about 22 nucleotides in length, which control gene expression at the posttranscriptional level through translational inhibition, degradation, adenylation, or destabilization of their target mRNAs. Although hundreds of miRNAs have been identified in various species, many more may still remain unknown. Therefore, discovery of new miRNA genes is an important step for understanding miRNA-mediated posttranscriptional regulation mechanisms. It seems that biological approaches to identify miRNA genes might be limited in their ability to detect rare miRNAs and are further limited to the tissues examined and the developmental stage of the organism under examination. These limitations have led to the development of sophisticated computational approaches attempting to identify possible miRNAs in silico. In this chapter, we discuss computational problems in miRNA prediction studies and review some of the many machine learning methods that have been tried to address the issues.Article Citation - WoS: 4Citation - Scopus: 7Master Regulators of Posttranscriptional Gene Expression Are Subject To Regulation(Humana Press, 2014) Hamid, Syed Muhammad; Akgül, BünyaminMicroRNAs (miRNAs) are small noncoding RNAs of 17-25 nt in length that control gene expression posttranscriptionally. As master regulators of posttranscriptional gene expression, miRNAs themselves are subject to tight regulation at multiple steps. The most common mechanisms include miRNA transcription, processing, and localization. Additionally, intricate feedback loops between miRNAs and transcription factors result in unidirectional, reciprocal, or self-directed elegant control mechanisms. In this chapter, we focus on the posttranscriptional regulatory mechanisms that generate miRNAs whose sequence might be slightly different from the miRNA-coding sequences. Hopefully, this information will be helpful in the discovery of novel miRNAs as well as in the analysis of deep-sequencing data and ab initio prediction of miRNAs. © Springer Science+Business Media New York 2014.Article Citation - WoS: 12Citation - Scopus: 14Gossypol Interferes With Both Type I and Type Ii Topoisomerase Activities Without Generating Strand Breaks(Humana Press, 2013) Şenarısoy, Müge; Cantürk, Pakize; Zencir, Sevil; Baran, Yusuf; Topçu, ZekiA considerable number of agents with chemotherapeutic potentials reported over the past years were shown to interfere with the reactions of DNA topoisomerases, the essential enzymes that regulate conformational changes in DNA topology. Gossypol, a naturally occurring bioactive phytochemical is a chemopreventive agent against various types of cancer cell growth with a reported activity on mammalian topoisomerase II. The compounds targeting topoisomerases vary in their mode of action; class I compounds act by stabilizing covalent topoisomerase-DNA complexes resulting in DNA strand breaks while class II compounds interfere with the catalytic function of topoisomerases without generating strand breaks. In this study, we report Gossypol as the interfering agent with type I topoisomerases as well. We also carried out an extensive set of assays to analyze the type of interference manifested by Gossypol on DNA topoisomerases. Our results strongly suggest that Gossypol is a potential class II inhibitor as it blocked DNA topoisomerase reactions with no consequently formed strand breaks.Other Erratum: Protective Effect of Zinc on Cyclophosphamide-Induced Hematoxicity and Urotoxicity: (biol Trace Elem Res (2008) 126 (186-193) Doi 10.1007/S12011-008-8189-5)(Humana Press, 2009) Ayhancı, Adnan; Uyar, Ruhi; Aral, Erinç; Kabadere, Selda; Appak, SılaThe original version of this article unfortunately contained a mistake. The Materials and Methods section should include last paragraph. Section “Materials and Methods”, inclusion of the last paragraph should read: Only the groups which had CY treatment alone were killed 3 days after the CY injection. For the groups having Cy+ZnCl2 , ZnCl2 administration was started three days earlier than the CY administration and continued till the end of the experiment (6 days). On the fourth day the animals were weighed again, relative doses of CY were estimated and CY+ZnCl2 was administered together. On the seventh day blood samples were collected, bone marrow and the urinary bladders of the animals were resected under anesthesia. Also, the first three affiliations were incorrect. The correct information is given below.Article Citation - WoS: 11Citation - Scopus: 13Protective Effect of Seleno-L on Cyclophosphamide-Induced Urinary Bladder Toxicity in Rats(Humana Press, 2010) Ayhancı, Adnan; Yaman, Suzan; Şahintürk, Varol; Uyar, Ruhi; Bayramoğlu, Gökhan; Şentürk, Hakan; Altuner, Yılmaz; Appak, Sıla; Güneş, SibelCyclophosphamide (CP) is a widely used antineoplastic drug, which could cause toxicity of the normal cells due to its toxic metabolites. Its urotoxicity may cause dose-limiting side effects like hemorrhagic cystitis. Overproduction of reactive oxygen species (ROS) during inflammation is one of the reasons of the urothelial injury. Selenoproteins play crucial roles in regulating ROS and redox status in nearly all tissues; therefore, in this study, the urotoxicity of CP and the possible protective effects of seleno-l-methionine (SLM) on urinary bladder of rats were investigated. Intraperitoneal (i.p.) administration of 50, 100, or 150 mg/kg CP induced cystitis, in a dose-dependent manner, as manifested by marked congestion, edema and extravasation in rat urinary bladder, a marked desquamative damage to the urothelium, severe inflammation in the lamina propria, focal erosions, and polymorphonuclear (PMN) leukocytes associated with occasional lymphocyte infiltration determined by macroscopic and histopathological examination. In rat urinary bladder tissue, a significant decrease in the endogenous antioxidant compound glutathione, and elevation of lipid peroxidation were also noted. Pretreatment with SLM (0.5 or 1 mg/kg) produced a significant decrease in the bladder edema and caused a marked decrease in vascular congestion and hemorrhage and a profound improvement in the histological structure. Moreover, SLM pretreatment decreased lipid peroxide significantly in urinary bladder tissue, and glutathione content was greatly restored. These results suggest that SLM offers protective effects against CP-induced urinary bladder toxicity and could be used as a protective agent against the drug toxicity. © 2009 Humana Press Inc.