Leukemic cell plasticity as a resistance mechanism towards tyrosine kinase inhibitors

ConferencePoster
Seda Baykal, Halil Ateş, Ahmet Sinan Yavuz, Uğur Sezerman, Eda Açıkgöz, Gülperi Öktem, Zeynep Yüce
The FEBS Journal, 283, S1, pp. 129–417
Publication year: 2016

Abstract

Chronic myelogenous leukemia (CML) is a hematopoietic stem cell disease characterized by the t(9;22)(q34;q11) translocation, which encodes the chimeric tyrosine kinase oncoprotein, Bcr- Abl. The tyrosine kinase inhibitor (TKI) imatinib is the first-line treatment for patients with CML. Unfortunately, drug resistance is one of the main problems observed. While secondary resistance is associated with Bcr-Abl kinase domain mutations, oncogene amplification and mechanisms interfering with intracellular drug concentrations; primary resistance mechanisms haven’t been elucidated. We generated high dose imatinib-resistant K562 sub- clones (K562-Ir) by clonal selection to study primary resistance mechanisms in vitro. Drug resistance was shown by caspase 3 and annexin V/PI assays. We also showed cellular uptake and function of imatinib with Western blot technics. K562-Ir cells are not only resistant to imatinib but also to 2nd, 3rd generation tyrosine kinase inhibitors. We demonstrated that K562-Ir cells have a highly adherent character, proliferate slowly and are resistant to drug-induced senescence. Microarray analysis revealed that K562-Ir cells differentially express tissue/organ development and differentiation genes at high levels. We showed that K562-Ir cells form intact tumor spheroids in 3D cell culture conditions which are a marker of tumor-initiating potential. Cell surface marker analyses and protein analyses of K562-Ir cell population points towards an epithelial-mesenchymal plastic cell capable of adopting different morphologies. We hypothesized that imatinib and other tyrosine kinase inhibitors may cause the gain of phenotypic plasticity potential in leukemic cells, by interfering with signaling pathways; which in itself may lead to therapy resistance.

This poster was presented by S. Baykal at the 41st FEBS Congress, Molecular and Systems Biology for a Better Life, Ephesus/Kuşadası, Turkey, September 3-8, 2016.

Prediction of neddylation sites from protein sequences and sequence-derived properties

ConferenceJournal
Ahmet Sinan Yavuz, Namık Berk Sözer, Osman Uğur Sezerman
BMC Bioinformatics, 16, S18, S9
Publication year: 2015

Abstract

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 lysine-centred 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.

Keywords

Neddylation, NEDD8, machine learning, support vector machines, post-translational modifications

Availability

The standalone version of neddylation site prediction method developed in this article are available in a Bitbucket repository at https://bitbucket.org/asyavuz/neddypreddy. Dataset that has been used to develop this article can be found in the supplementary material of this article.

Multiplex-PCR-Based Screening and Computational Modeling of Virulence Factors and T-Cell Mediated Immunity in Helicobacter pylori Infections for Accurate Clinical Diagnosis

Journal
Sinem Öktem-Okullu, Arzu Tiftikçi, Murat Saruç, Bahattin Çiçek, Eser Vardareli, Nurdan Tözün, Tanıl Kocagöz, Uğur Sezerman, Ahmet Sinan Yavuz, Ayça Sayı-Yazgan
PLoS ONE, 10, 8, e0136212.
Publication year: 2015

Abstract

The outcome of H. pylori infection is closely related with bacteria’s virulence factors and host immune response. The association between T cells and H. pylori infection has been identified, but the effects of the nine major H. pylori specific virulence factors; cagA, vacA, oipA, babA, hpaA, napA, dupA, ureA, ureB on T cell response in H. pylori infected patients have not been fully elucidated. We developed a multiplex- PCR assay to detect nine H. pylori virulence genes with in a three PCR reactions. Also, the expression levels of Th1, Th17 and Treg cell specific cytokines and transcription factors were detected by using qRT-PCR assays. Furthermore, a novel expert derived model is developed to identify set of factors and rules that can distinguish the ulcer patients from gastritis patients. Within all virulence factors that we tested, we identified a correlation between the presence of napA virulence gene and ulcer disease as a first data. Additionally, a positive correlation between the H. pylori dupA virulence factor and IFN-γ, and H. pylori babA virulence factor and IL-17 was detected in gastritis and ulcer patients respectively. By using computer-based models, clinical outcomes of a patients infected with H. pylori can be predicted by screening the patient’s H. pylori vacA m1/m2, ureA and cagA status and IFN-γ (Th1), IL-17 (Th17), and FOXP3 (Treg) expression levels. Herein, we report, for the first time, the relationship between H. pylori virulence factors and host immune responses for diagnostic prediction of gastric diseases using computer—based models.

Investigating DNA methylation susceptibility with a multi-omics strategy

Poster
Ahmet Sinan Yavuz, Osman Uğur Sezerman
STATegra Summer School in -Omics Data Integration, September 7-11, 2015, Benicassim, Spain
Publication year: 2015

Abstract

Aberrant epigenetic variation has been previously identified as a component of many complex diseases, such as various cancers including liver hepatocellular carcinoma. In this context, mostly aberrations in DNA methylation have been extensively studied. However, most research on the common characteristics of regions involved in aberrant DNA methylation (either hyper- and hypo-methylated) were only limited to particular chromosomes and performed mostly on healthy cells. Disease information was only used as a validation step in these studies. Although there are whole-genome approaches present, none of the previous studies investigated the relationship between aberrant DNA methylation and gene expression in the context of DNA methylation susceptibility. We are currently studying methylation susceptibility of DNA regions with different cancer samples and cancer cell lines. We believe that integrating other paired -omics data into DNA methylation analyses will provide further details on the mechanisms of aberrant DNA methylation. Consequently, this analyses will provide invaluable information for targeting cancer progression via DNA methylation.

Predicting sumoylation sites using support vector machines based on various sequence features, conformational flexibility and disorder

ConferenceJournal
Ahmet Sinan Yavuz, Osman Uğur Sezerman
BMC Genomics, 15, S9, S18
Publication year: 2014

Abstract

Background
Sumoylation, which is a reversible and dynamic post-translational modification, is one of the vital processes in a cell. Before a protein matures to perform its function, sumoylation may alter its localization, interactions, and possibly structural conformation. Abberations in protein sumoylation has been linked with a variety of disorders and developmental anomalies. Experimental approaches to identification of sumoylation sites may not be effective due to the dynamic nature of sumoylation, laborsome experiments and their cost. Therefore, computational approaches may guide experimental identification of sumoylation sites and provide insights for further understanding sumoylation mechanism.

Results
In this paper, the effectiveness of using various sequence properties in predicting sumoylation sites was investigated with statistical analyses and machine learning approach employing support vector machines. These sequence properties were derived from windows of size 7 including position-specific amino acid composition, hydrophobicity, estimated sub-window volumes, predicted disorder, and conformational flexibility. 5-fold cross-validation results on experimentally identified sumoylation sites revealed that our method successfully predicts sumoylation sites with a Matthew’s correlation coefficient, sensitivity, specificity, and accuracy equal to 0.66, 73%, 98%, and 97%, respectively. Additionally, we have showed that our method compares favorably to the existing prediction methods and basic regular expressions scanner.

Conclusions
By using support vector machines, a new, robust method for sumoylation site prediction was introduced. Besides, the possible effects of predicted conformational flexibility and disorder on sumoylation site recognition were explored computationally for the first time to our knowledge as an additional parameter that could aid in sumoylation site prediction.

Keywords

Sumoylation, SUMO, machine learning, support vector machines, post-translational modification

Amino acid preferences at neddylation sites

ConferenceProceedings Article
Ahmet Sinan Yavuz, Namık Berk Sözer, Osman Uğur Sezerman
International Conference on Applied Informatics for Health and Life Sciences (AIHLS-2014), October 19-22, 2014, Kusadası, Aydın, Turkey.
Publication year: 2014

Abstract
Neddylation is a dynamic post-translational modification in which NEDD8 proteins are covalently attached to the target site lysine residue. Neddylation may affect a target protein’s localization, binding partners and structure. Targets of this modification have commonly found in nucleus and the most well characterized target family is cullins, which is modulating ubiquitination and proteosomal degradation system in a cell. Disruptions in neddylation pathway implicated in various diseases such as Alzheimer’s, Parkinson’s and cancer. Therefore, understanding neddylation site recognition bears a huge importance in understanding the complete functional mechanism of this post-translational modification and revealing the mechanisms of associated diseases towards a cure. However, there is no study in literature investigating whether a common neddylation site motif exists or not. In this work, we have identified various amino acid preferences and hydrophobicity patterns seen in neddylation sites, differing from not neddylated lysine residues.

Prolonged exposure to tyrosine kinase inhibitors cause phenotypic plasticity in K652 cells, resulting in morphology transition, drug resistance and escape from cellular aging

AbstractConference
Seda Baykal, Ahmet Sinan Yavuz, Halil Ateş, Uğur Sezerman, Hayri Güner Özsan, Hakkı Ogün Sercan, Zeynep Sercan
9th International Conference on Cell and Stem Cell Engineering, September 11-13, 2014, Aachen, Germany
Publication year: 2013

Abstract

Currently there are several approaches for engineering cell fate. The generation of IPSCs as well as direct conversion between two mature cell states are the two major processes used in the field of induced cellular potency. Research so far supports that transcription factors are predominantly responsible for the phenotypic plasticity observed in direct cellular conversion. Transcription factors are end targets of signaling pathways.
We hypothesized that alteration of signal transduction pathways by therapeutic drugs such as tyrosine kinase inhibitors (TKIs) have the potential of inducing phenotypic conversion in a subset of cells; which in turn may have important consequences ranging from drug resistance or inducing senescence to generating dormant cancer cells. TKIs are used as first line therapy in chronic myeloid leukemia (CML). We used the CML cell line K562 to generate a TKI resistant sub-clone. Resistance to 1st, 2nd and 3rd generation TKIs was confirmed by annexin-V staining, caspase activation and MTT assays. ABL kinase domain mutations, BCR-ABL amplification and deficient cellular uptake were ruled out. Prolonged growth in the presence of TKİs resulted in the selection of cells with fibroblastoid morphology and the ability to grow as a monolayer.
Cellular characterization showed enrichment in pluripotent and mesenchymal surface markers in addition to resistance to stress-induced replicative senescence and cellular aging. Our findings have important clinical implications as well as supporting research that aim to induce cellular potency and targeted cell fate decisions by more efficient and less laborious/consuming methodologies.

Pattern Recognition for Subfamily Level Classification of GPCRs Using Motif Distillation and Distinguishing Power Evaluation

ConferenceProceedings Article
Ahmet Sinan Yavuz, Buğra Özer, Osman Uğur Sezerman
Pattern Recognition in Bioinformatics, Lecture Notes in Computer Science, 7632, 2012, pp. 267-276
Publication year: 2012

Abstract
G protein coupled receptors (GPCRs) are one of the most prominent and abundant family of membrane proteins in the human genome. Since they are main targets of many drugs, GPCR research has grown significantly in recent years. However the fact that only few structures of GPCRs are known still remains as an important challenge. Therefore, the classification of GPCRs is a significant problem provoked from increasing gap between orphan GPCR sequences and a small amount of annotated ones. This work employs motif distillation using defined parameters, distinguishing power evaluation method and general weighted set cover problem in order to determine the minimum set of motifs which can cover a particular GPCR subfamily. Our results indicate that in Family A Peptide subfamily, 91% of all proteins listed in GPCRdb can be covered by using only 691 different motifs, which can be employed later as an invaluable source for developing a third level GPCR classification tool.

Keywords
g-protein coupled receptors data mining pattern recognition

Presented in 7th IAPR International Conference, PRIB 2012, Tokyo, Japan, November 8-10, 2012.

The assembly of cell-encapsulating microscale hydrogels using acoustic waves

Journal
Feng Xu, Thomas D. Finley, Müge Turkaydın, Yuree Sung, Umut Atakan Gürkan, Ahmet S. Yavuz, Rasim O. Güldiken, Utkan Demirci
Biomaterials, 32, 31, pp. 7847–7855
Publication year: 2011

Abstract

Microscale hydrogels find widespread applications in medicine and biology, e.g., as building blocks for tissue engineering and regenerative medicine. In these applications, these microgels are assembled to fabricate large complex 3D constructs. The success of this approach requires non-destructive and high throughput assembly of the microgels. Although various assembly methods have been developed based on modifying interfaces, and using microfluidics, so far, none of the available assembly technologies have shown the ability to assemble microgels using non-invasive fields rapidly within seconds in an efficient way. Acoustics has been widely used in biomedical arena to manipulate droplets, cells and biomolecules. In this study, we developed a simple, non-invasive acoustic assembler for cell-encapsulating microgels with maintained cell viability (>93%). We assessed the assembler for both microbeads (with diameter of 50 μm and 100 μm) and microgels of different sizes and shapes (e.g., cubes, lock-and-key shapes, tetris, saw) in microdroplets (with volume of 10 μL, 20 μL, 40 μL, 80 μL). The microgels were assembled in seconds in a non-invasive manner. These results indicate that the developed acoustic approach could become an enabling biotechnology tool for tissue engineering, regenerative medicine, pharmacology studies and high throughput screening applications.

Multiphase Anistropic Tissue Structures by Microdroplet Based Hydrogel Printing

AbstractConference
Umut Atakan Gürkan, Feng Xu, Yuree Sung, Banupriya Sridharan, Ahmet Sinan Yavuz, Utkan Demirci
2011 MRS Spring Meeting, April 26-29, 2011, San Francisco, CA, USA
Publication year: 2011

Background: In this paper we present generation and preliminary assessment of multiphase anisotropic tissue structures by microdroplet based hydrogel printing method. Current cell/tissue scaffolding methods present shortcomings due to the lack of control over the spatial and temporal control over cell seeding and extracellular matrix composition. Microdroplet based hydrogel bioprinting technology can be used to engineer complex tissue anisotropies with multiple phases by producing scaffolds with controlled micro-scale spatial heterogeneity in extracellular, cellular compositions and physical properties. Therefore, we hypothesized that the microdroplet-based hydrogel bioprinting approach developed in our laboratory will successfully facilitate engineering of the complex tissue anisotropies that are composed of multiple phases. In order to test this hypothesis we printed agarose hydrogel bioinks colored with red, green and blue (RGB) high molecular weight (35-38 kDa) fluorescent dyes and assessed the phase transitions via image processing to evaluate the anisotropy of the resulting multiphase structure by measuring the RGB color intensities.

Methods: Microdroplet generation process was performed with multiple ejectors in sterile laminar flow hood under controlled humidity. The inter-droplet distance was determined by the size of the droplets residing on the substrate. The prepared bio-inks (RGB colored hydrogels) were printed in a staggered configuration. The ejector was kept warm (37 degC) to minimize viscosity changes and premature gelation of the hydrogel. Printed staggered phases were gelled by incubation at 4 degC for 5 minutes. The diffusion and integration of the phases was assessed immediately after and 3 hours after printing by taking micographs and analyzing using ImageJ software. RGB color relative intensity values were used analytically to analyze the anisotropic gradient of the phases and phase transitions.

Results and Discussion: The printed multiphase hydrogel structure representing an anisotropic tissue unit displayed sharp RGB boundaries between the phases immediately after printing. These sharp boundaries disappeared and smooth transitions emerged within 3 hours. These results suggest that microdroplet based hydrogel printing technology can be used to create highly anisotropic structures with smooth boundaries mimicking the complex cellular and extracellular gradients in the natural tissues. Our long term goal is to develop effective bioprinting methodologies to engineer micro-scale anisotropic complex tissue structures with multiple phases, which can be incorporated into currently available biomaterials to face the challenges of incompatibility at tissue-biomaterial interfaces.

Living Bacterial Sacrificial Porogens to Engineer Decellularized Porous Scaffolds

Journal
Feng Xu, BanuPriya Sridharan, Naşide Gözde Durmuş, ShuQi Wang, Ahmet Sinan Yavuz, Umut Atakan Gürkan, Utkan Demirci
PLoS ONE, 6, 4, e19344
Publication year: 2011

Abstract
Decellularization and cellularization of organs have emerged as disruptive methods in tissue engineering and regenerative medicine. Porous hydrogel scaffolds have widespread applications in tissue engineering, regenerative medicine and drug discovery as viable tissue mimics. However, the existing hydrogel fabrication techniques suffer from limited control over pore interconnectivity, density and size, which leads to inefficient nutrient and oxygen transport to cells embedded in the scaffolds. Here, we demonstrated an innovative approach to develop a new platform for tissue engineered constructs using live bacteria as sacrificial porogens. E.coli were patterned and cultured in an interconnected three-dimensional (3D) hydrogel network. The growing bacteria created interconnected micropores and microchannels. Then, the scafold was decellularized, and bacteria were eliminated from the scaffold through lysing and washing steps. This 3D porous network method combined with bioprinting has the potential to be broadly applicable and compatible with tissue specific applications allowing seeding of stem cells and other cell types.

Directed Assembly of Microscale Particles by Acoustic Waves for Biomedical Applications

ConferenceProceedings Article
Feng Xu, Umut Atakan Gürkan, Thomas D. Finley, Müge Turkaydın, Ahmet Sinan Yavuz, Onur Hasan, Utkan Demirci
The Society For Biomaterials’ 2011 Annual Meeting, “Animating Materials”, April 13-16, 2011, Orlando, FL, USA
Publication year: 2011

This is a one-page proceedings article without any abstract. Please follow the link, or download the file to view the article.

Acoustics Directed Microparticle Assembly for Biomedical Applications

ConferenceProceedings Article
Feng Xu, Umut Atakan Gürkan, Thomas D. Finley, Müge Turkaydın, Ahmet Sinan Yavuz, Utkan Demirci
TERMIS-EU Meeting 2011, June 7-10, 2011, Granada, Spain.
Publication year: 2011

This is a one-page proceedings article without any abstract. Please download the file to view the article.

SUMOtr: SUMOylation site prediction based on 3D structure and hydrophobicity

ConferenceProceedings Article
Ahmet Sinan Yavuz, Uğur Sezerman
5th International Symposium on Health Informatics and Bioinformatics (HIBIT), April 20-22, 2010, Antalya, Turkey
Publication year: 2010

Abstract
A post translational modification SUMOylation is one of the vital processes of protein maturation and function. Determining a protein’s SUMOylation status is important in the context of determining that protein’s function, nuclear localization, and intra-nuclear spatial association. Many of the predictors currently use a consensus motif, which is ΨKxE (where Ψ is a large aliphatic branched hydrophobic amino acid and x is any amino acid), to predict the location of SUMO modification. However, approximately 23% of the validated SUMOylation sites do not conform to the consensus motif, a phenomenon which makes the prediction of SUMOylation sites complicated. Here we present a new method, SUMOtr, using structure and sequence information. This study investigates the role of protein volume, structural motifs, and hydrophobicity of the amino acids in the vicinity of central Lysine in the prediction of SUMOylation sites with tree classification algorithms. A comparison between SUMOtr and the previous methods show that SUMOtr is higher in correlation coefficient and sensitivity. Decision Stump tree classification has provided the overall performance of the method as 85% accuracy, 75% specificity, 95% sensitivity and 0.72 correlation coefficient.

Bacterial printing for fabricating microfluidic hydrogels

ConferenceProceedings Article
Feng Xu, Ahmet Sinan Yavuz, Banupriya Sridharan, ShuQi Wang, Utkan Demirci
2010 International Conference of Biofabrication, October 4-6, 2010, Philadelphia, PA, USA
Publication year: 2010

This is a one-page proceedings article without any abstract. Please download the file to view the article.