Person: KASAVİ, CEYDA
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KASAVİ
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CEYDA
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Publication Metadata only Purification, biochemical characterization and gene sequencing of a thermostable raw starch digesting alpha-amylase from Geobacillus thermoleovorans subsp stromboliensis subsp nov.(SPRINGER, 2011) KASAVİ, CEYDA; Finore, Ilaria; Kasavi, Ceyda; Poli, Annarita; Romano, Ida; Oner, Ebru Toksoy; Kirdar, Betul; Dipasquale, Laura; Nicolaus, Barbara; Lama, LiciaThis study reports the purification and biochemical characterization of a raw starch-digesting alpha-amylase from Geobacillus thermoleovorans subsp. stromboliensis subsp. nov. (strain Pizzo(T)). The molecular weight was estimated to be 58 kDa by SDS-PAGE. The enzyme was highly active over a wide range of pH from 4.0-10.0. The optimum temperature of the enzyme was 70A degrees C. It showed extreme thermostability in the presence of Ca2+, retaining 50% of its initial activity after 90 h at 70A degrees C. The enzyme efficiently hydrolyzed 20% (w/v) of raw starches, concentration normally used in starch industries. The alpha-amylase showed an high stability in presence of many organic solvents. In particular the residual activity was of 73% in presence of 15% (v/v) ethyl alcohol, which corresponds to ethanol yield in yeast fermentation process. By analyzing its complete amyA gene sequence (1,542 bp), the enzyme was proposed to be a new alpha-amylase.Publication Open Access Gene co-expression network analysis revealed novel biomarkers for ovarian cancer(2022-10-01) KASAVİ, CEYDA; KASAVİ C.Ovarian cancer is the second most common gynecologic cancer and remains the leading cause of death of all gynecologic oncologic disease. Therefore, understanding the molecular mechanisms underlying the disease, and the identification of effective and predictive biomarkers are invaluable for the development of diagnostic and treatment strategies. In the present study, a differential co-expression network analysis was performed via meta-analysis of three transcriptome datasets of serous ovarian adenocarcinoma to identify novel candidate biomarker signatures, i.e. genes and miRNAs. We identified 439 common differentially expressed genes (DEGs), and reconstructed differential co-expression networks using common DEGs and considering two conditions, i.e. healthy ovarian surface epithelia samples and serous ovarian adenocarcinoma epithelia samples. The modular analyses of the constructed networks indicated a co-expressed gene module consisting of 17 genes. A total of 11 biomarker candidates were determined through receiver operating characteristic (ROC) curves of gene expression of module genes, and miRNAs targeting these genes were identified. As a result, six genes (CDT1, CNIH4, CRLS1, LIMCH1, POC1A, and SNX13), and two miRNAs (mir-147a, and mir-103a-3p) were suggested as novel candidate prognostic biomarkers for ovarian cancer. Further experimental and clinical validation of the proposed biomarkers could help future development of potential diagnostic and therapeutic innovations in ovarian cancer.Publication Open Access Idiopathic pulmonary arterial hypertension: network-based integration of multi-omics data reveals new molecular signatures and candidate drugs(2023-01-01) KASAVİ, CEYDA; KASAVİ C.Idiopathic pulmonary arterial hypertension (IPAH) is a progressive disease that affects the pulmonary arteries, resulting in increased pulmonary vascular resistance and right ventricular dysfunction, which can ultimately lead to heart failure and death. The molecular substrates of IPAH are poorly understood while diagnostics and therapeutics innovation remain as unmet needs for this debilitating disease. In this study, a network-based methodology was used to uncover the salient molecular mechanisms of IPAH to inform drug and diagnostic discovery, and personalized medicine. Expression profiling datasets associated with IPAH were obtained from the Gene Expression Omnibus database: GSE15197, GSE113439, GSE53408, and GSE67597. The comparative analysis of mRNA and miRNA expression data and the modular analysis of a transcriptome-based weighted gene coexpression network unraveled disease-specific gene and miRNA signatures. DEAD-box helicase 52 (DDx52), ESF1 nucleolar pre-RNA processing protein (ESF1), heterogeneous nuclear ribonuclearprotein A3 (MNRNPA3), Myosin VA (MYO5A), replication factor C subunit 1 (RFC1), and arginine and serine rich coiled coil 1 (RSRC1) were detected as the salient genes for IPAH. In addition, the salient gene-based drug repositioning analysis identified alvespimycin, tanespimycin, geldanamycin, LY294002, cephaeline, digoxigenin, lanatoside C, helveticoside, trichostatin A, phenoxybenzamine, genistein, pioglitazone, and rosiglitazone as potential drug candidates for IPAH. In conclusion, this study provides new molecular signatures in relation to IPAH and attendant potential drug candidates for further experimental and translational clinical research for patients with IPAH.Publication Metadata only Evaluation of industrial Saccharomyces cerevisiae strains for ethanol production from biomass(PERGAMON-ELSEVIER SCIENCE LTD, 2012) KASAVİ, CEYDA; Kasavi, Ceyda; Finore, Ilaria; Lama, Licia; Nicolaus, Barbara; Oliver, Stephen G.; Oner, Ebru Toksoy; Kirdar, BetulFive industrial Saccharomyces cerevisiae strains were evaluated for their suitability for strain improvement for future use in ethanol production processes. Principal components analysis of growth-related and production-related fermentation parameters of the 5 strains grown on glucose demonstrated the superiority of the Y9 strain in terms of its rapid growth and highest ethanol yields on both biomass and glucose. The growth and ethanol production performances of these strains on various agro-industrial wastes (including sugar beet pulp, starch and sugar beet molasses) and biological residues (including carrot, tomato and potato peel) were also determined. Ethanol tolerance studies, using both solid and liquid cultures, revealed the remarkable abilities of the BC187 and Y9 strains to survive and grow at high ethanol concentrations. Suspension cultures were found to be highly tolerant to 78.80 g L-1 ethanol however their growth ability showed a distinct decrease with increasing ethanol concentration such that only (1-2)% of the control growth was observed in media containing 118.20 g L-1 ethanol. The importance of choosing the appropriate S. cerevisiae strain to be used in ethanol production was clearly established with this study. Fermentation performances of the cultures under different cultivation conditions pointed to the fact that the choice of strain will not only depend on the ethanol tolerance but also on the preferential utilization of the carbon resources of biological residues. (c) 2012 Elsevier Ltd. All rights reserved.Publication Open Access Genomic analysis provides new Insights into biotechnological and industrial potential of parageobacillus thermantarcticus M1(2022-06-01) KASAVİ, CEYDA; TOKSOY ÖNER, EBRU; YILDIZ S. Y., Finore I., Leone L., Romano I., Lama L., KASAVİ C., Nicolaus B., TOKSOY ÖNER E., Poli A.Parageobacillus thermantarcticus strain M1 is a Gram-positive, motile, facultative anaerobic, spore forming, and thermophilic bacterium, isolated from geothermal soil of the crater of Mount Melbourne (74 degrees 22 \" S, 164 degrees 40 \" E) during the Italian Antarctic Expedition occurred in Austral summer 1986-1987. Strain M1 demonstrated great biotechnological and industrial potential owing to its ability to produce exopolysaccharides (EPSs), ethanol and thermostable extracellular enzymes, such as an xylanase and a beta-xylosidase, and intracellular ones, such as xylose/glucose isomerase and protease. Furthermore, recent studies revealed its high potential in green chemistry due to its use in residual biomass transformation/valorization and as an appropriate model for microbial astrobiology studies. In the present study, using a systems-based approach, genomic analysis of P. thermantarcticus M1 was carried out to enlighten its functional characteristics. The elucidation of whole-genome organization of this thermophilic cell factory increased our understanding of biological mechanisms and pathways, by providing valuable information on the essential genes related to the biosynthesis of nucleotide sugar precursors, monosaccharide unit assembly, as well as the production of EPSs and ethanol. In addition, gene prediction and genome annotation studies identified genes encoding xylanolytic enzymes that are required for the conversion of lignocellulosic materials to high-value added molecules. Our findings pointed out the significant potential of strain M1 in various biotechnological and industrial applications considering its capacity to produce EPSs, ethanol and thermostable enzymes via the utilization of lignocellulosic waste materials.Publication Open Access Process development for the continuous production of heterologous proteins by the industrial yeast, Komagataella phaffii(WILEY, 2018-12) KASAVİ, CEYDA; Cankorur-Cetinkaya, Ayca; Narraidoo, Nathalie; Kasavi, Ceyda; Slater, Nigel K. H.; Archer, David B.; Oliver, Stephen G.The current trend in industrial biotechnology is to move from batch or fed-batch fermentations to continuous operations. The success of this transition will require the development of genetically stable production strains, the use of strong constitutive promoters, and the development of new medium formulations that allow an appropriate balance between cell growth and product formation. We identified genes that showed high expression in Komagataella phaffii during different steady-state conditions and explored the utility of promoters of these genes (Chr1-4_0586 and FragB_0052) in optimizing the expression of two different r-proteins, human lysozyme (HuLy), and the anti-idiotypic antibody fragment, Fab-3H6, in comparison with the widely used glyceraldehyde-3-phosphate dehydrogenase promoter. Our results showed that the promoter strength was highly dependent on the cultivation conditions and thus constructs should be tested under a range of conditions to determine both the best performing clone and the ideal promoter for the expression of the protein of interest. An important benefit of continuous production is that it facilitates the use of the genome-scale metabolic models in the design of strains and cultivation media. In silico flux distributions showed that production of either protein increased the flux through aromatic amino acid biosynthesis. Tyrosine supplementation increased the productivity for both proteins, whereas tryptophan addition did not cause any significant change and, phenylalanine addition increased the expression of HuLy but decreased that of Fab-3H6. These results showed that a genome-scale metabolic model can be used to assess the metabolic burden imposed by the synthesis of a specific r-protein and then this information can be used to tailor a cultivation medium to increase production.Publication Metadata only An integrative analysis of transcriptomic response of ethanol tolerant strains to ethanol in Saccharomyces cerevisiae(ROYAL SOC CHEMISTRY, 2016) KASAVİ, CEYDA; Kasavi, Ceyda; Eraslan, Serpil; Oner, Ebru Toksoy; Kirdar, BetulThe accumulation of ethanol is one of the main environmental stresses that Saccharomyces cerevisiae cells are exposed to in industrial alcoholic beverage and bioethanol production processes. Despite the known impacts of ethanol, the molecular mechanisms underlying ethanol tolerance are still not fully understood. Novel gene targets leading to ethanol tolerance were previously identified via a network approach and the investigations of the deletions of these genes resulted in the improved ethanol tolerance of pmt7 Delta/pmt7 Delta and yhl042w Delta/yhl042w Delta strains. In the present study, an integrative system based approach was used to investigate the global transcriptional changes in these two ethanol tolerant strains in response to ethanol and hence to elucidate the mechanisms leading to the observed tolerant phenotypes. In addition to strain specific biological processes, a number of common and already reported biological processes were found to be affected in the reference and both ethanol tolerant strains. However, the integrative analysis of the transcriptome with the transcriptional regulatory network and the ethanol tolerance network revealed that each ethanol tolerant strain had a specific organization of the transcriptomic response. Transcription factors around which most important changes occur were determined and active subnetworks in response to ethanol and functional clusters were identified in all strains.Publication Metadata only Analysis of multi-omics data revealed candidate drugs for COVID-19(2023-10-04) KASAVİ, CEYDA; Cig D., KASAVİ C.The infection with severe acute respiratory syndrome coronavirus 2is the cause of COVID-19, which has rapidly spread worldwide through person-to-person transmission. More than 6.5 million people died because of COVID-19. Significant data revealed COVID-19-related cardiovascular complications and endothelial dysfunction leading to increased inflammation in various organs. Novel approaches for the development of therapeutics are required given the lack of reliable prognostic biomarkers, multifactorial effects, and the morbidity and mortality risks in vulnerable groups associated with COVID-19. Therefore, the objective of this study is to identify new molecular signatures for drug development. A comparative analysis of genome-wide expression data obtained from lung tissue samples of COVID-19 patients and healthy controls was performed. Specifically, differentially expressed genes (DEGs) were identified, and functional enrichment analyzes of DEGs were carried out. In addition, hub proteins, reporter regulatory elements (i.e., TF and miRNAs), and reporter metabolites were identified by integrating transcriptome data with protein-protein interaction (PPI), regulatory, and genome-scale metabolic networks, respectively. Moreover, a transcriptionally active subnetwork was identified by mapping transcriptome data to PPI network through KeyPathwayMiner. A total of 884 up- and 608 down-regulated DEGs were identified. Functional enrichment analysis demonstrated alterations in immunity, inflammation, and infection disease-associated pathways in the presence of COVID-19. Furthermore, DEGs encoding hub proteins that were regulated by reporter molecules were considered as key genes, and key gene-based drug repositioning analysis revealed candidate drugs including cardiac glycosides, insulin sensitizers, and drugs with antifibrotic, anti-inflammatory, and antiproliferative effects, for consideration in future clinical drug development.Publication Metadata only Halomonas smyrnensis as a cell factory for co-production of PHB and levan(ELSEVIER SCIENCE BV, 2018) KASAVİ, CEYDA; Tohme, Souha; Haciosmanoglu, Gul Gulenay; Eroglu, Mehmet Sayip; Kasavi, Ceyda; Genc, Seval; Can, Zehra Semra; Oner, Ebru ToksoyLevan is a fructan type polysaccharide that has long been considered as an industrially important biopolymer however its limited availability is mainly due to the bottlenecks associated with its large-scale production. To overcome such bottlenecks in the commercialization of this very promising polysaccharide, co-production of levan with polyhydroxyalkanoates (PHAs) by halophilic Halomonas smyrnensis cultures has been proposed in this study for the first time. After in silico and in vitro assessment of PHA accumulation, fermentation profiles for levan and PHA concentrations were obtained in the presence of sucrose and glucose and the PHA granules observed by TEM were found to be poly(3-hydroxybutyrate) (PHB) after detailed structural characterization by GC-MS, DSC, FTIR and NMR. Six nutrient limitation strategies based on nitrogen (N) and phosphorus (P) were tested but highest levan and PHB yields were obtained under unlimited conditions. H. smyrnensis is proved to co-produce PHB and levan while using inexpensive carbon sources which is a commercially successful microbial cell factory system showing a great potential in lowering manufacturing costs and aiming for a zero waste policy within the biorefinery concept. (C) 2018 Elsevier B.V. All rights reserved.Publication Open Access A system based network approach to ethanol tolerance in Saccharomyces cerevisiae(BMC, 2014-12) KASAVİ, CEYDA; Kasavi, Ceyda; Eraslan, Serpil; Arga, Kazim Yalcin; Oner, Ebru Toksoy; Kirdar, BetulBackground: Saccharomyces cerevisiae has been widely used for bio-ethanol production and development of rational genetic engineering strategies leading both to the improvement of productivity and ethanol tolerance is very important for cost-effective bio-ethanol production. Studies on the identification of the genes that are up-or down-regulated in the presence of ethanol indicated that the genes may be involved to protect the cells against ethanol stress, but not necessarily required for ethanol tolerance. Results: In the present study, a novel network based approach was developed to identify candidate genes involved in ethanol tolerance. Protein-protein interaction (PPI) network associated with ethanol tolerance (tETN) was reconstructed by integrating PPI data with Gene Ontology (GO) terms. Modular analysis of the constructed networks revealed genes with no previously reported experimental evidence related to ethanol tolerance and resulted in the identification of 17 genes with previously unknown biological functions. We have randomly selected four of these genes and deletion strains of two genes (YDR307W and YHL042W) were found to exhibit improved tolerance to ethanol when compared to wild type strain. The genome-wide transcriptomic response of yeast cells to the deletions of YDR307W and YHL042W in the absence of ethanol revealed that the deletion of YDR307W and YHL042W genes resulted in the transcriptional re-programming of the metabolism resulting from a mis-perception of the nutritional environment. Yeast cells perceived an excess amount of glucose and a deficiency of methionine or sulfur in the absence of YDR307W and YHL042W, respectively, possibly resulting from a defect in the nutritional sensing and signaling or transport mechanisms. Mutations leading to an increase in ribosome biogenesis were found to be important for the improvement of ethanol tolerance. Modulations of chronological life span were also identified to contribute to ethanol tolerance in yeast. Conclusions: The system based network approach developed allows the identification of novel gene targets for improved ethanol tolerance and supports the highly complex nature of ethanol tolerance in yeast.