Biology subjects

Konu, O.

Publications and source records attributed to Konu, O..

4 recordsLinked to original sources

bioRxiv2025

TP53-META, a meta-analysis tool for comparative transcriptomics of TP53 dependency: Examples from target silencing and liver fibrosis

BackgroundTP53 is the most frequently mutated transcription factor (TF) in sporadic cancers; and its targets exhibit dysregulation at the level of expression in both cancer and non-cancer pathologies. However, there is not yet a web-based tool that enables meta-analysis and visualization of TP53-related gene expression datasets, although several databases exist to access and annotate TP53 target information. To address this gap, we developed TP53-META, an interactive R Shiny-based web tool that allows users to upload and simultaneously analyze users or integrated public RNA-seq datasets for effects of TP53 depletion and/or induction on the transcriptome. ResultsTP53-META can be used to visualize significant expression clusters as well as TF-TF, pathway-pathway, disease-gene and treatment-gene networks to determine TP53 dependency of selected treatment contrasts. We demonstrated the utility of TP53-META through two case studies. In the first, using an in-house RNA-seq data from MCF7 cells treated with siRNAs against CHRNA5 and TP53, we identified TP53-independent and dependent transcriptomic changes by CHRNA5 depletion by comparing with selected public datasets in TP53-META. In the second, we demonstrated the user data upload functionality of TP53-META before meta-analysis and extracted commonly modulated TP53-related genes in liver fibrosis using public RNA-seq datasets. TP53-META is available at http://konulabapps.bilkent.edu.tr:3838/TP53-Meta1.5/ ConclusionsBy facilitating meta-analysis, clustering, and network-based visualizations, TP53-META enables researchers to efficiently integrate and explore TP53-related transcriptomic datasets from diverse sources, and help uncover robust expression patterns, and investigate context-specific TP53 functions.

bioinformatics↗

bioRxiv2024

Randomization based evaluation of distinct topological and cancer expression characteristics of mutually acting gene pairs

Small scale molecular network patterns and motifs are crucial for systems level understanding of cellular information transduction. A subgroup of such patterns consists of only 2 molecules, which we named as mutually acting pairs. Using randomizations, we statistically explored such gene pair designs, i.e. mutually positive (PP) or negative (NN) and positive-negative (PN) pairs, in two comprehensive and distinct large-scale molecular networks from literature; the human protein signaling network (PSN) and the human gene regulatory network (GRN). While the numbers of NN and PN pairs were significantly higher, the number of PP pairs was significantly lower than randomly expected values. Genes participating in mutual pairs were more connected than other genes. The connectivity of mutual gene pairs differed between the two networks. NN genes were more connected than PP and PN in GRN for all types of degree values, including in, out, positive or negative connections, but less connected for in-degree and more connected for out-degree values in PSN. They also had significantly high number of intersections with each other and PN pairs than randomly expected values, indicating potential cooperative mechanisms. The three mutual interaction designs we examined had distinct RNA and protein expression correlation characteristics. NN protein pairs were uniquely over-represented across normal tissue samples, whose negative correlations were lost across cancer tissue samples. PP and PN pairs showed non-random positive RNA or protein expression correlation across normal or cancer tissue samples. Moreover, we developed an online tool, i.e., MGPNet, for further user specific analysis of mutual gene pairs. For example, we identified SNCA with significantly enriched negatively correlated NN pairs with ubiquitin-proteasome members only in normal tissues. Unique non-random characteristics of mutual gene/protein pairs identified in two different comprehensive human molecular networks could provide valuable information for a better understanding of molecular design principles between normal and cancer states.

systems biology↗

bioRxiv2022

Doxorubicin induces prolonged DNA damage signal in cells overexpressing DEK isoform-2.

DEK has a short isoform (DEK isoform-2; DEK2) that lacks amino acid residues between 49-82. The full-length DEK (DEK isoform-1; DEK1) is ubiquitously expressed and plays a role in different cellular processes but whether DEK2 is involved in these processes remains elusive. We stably overexpressed DEK2 in human bone marrow stromal cell line HS-27A, in which endogenous DEKs were intact or suppressed via short hairpin RNA (sh-RNA). We have found that contrary to ectopic DEK1, DEK2 locates in the nucleus and nucleolus, causes persistent {gamma}H2AX signal upon doxorubicin treatment, and couldnt functionally compensate for the loss of DEK1. In addition, DEK2 overexpressing cells were more sensitive to doxorubicin than DEK1-cells. Expressions of DEK1 and DEK2 in cell lines and primary tumors exhibit tissue specificity. DEK1 is upregulated in cancers of the colon, liver, and lung compared to normal tissues while both DEK1 and DEK2 are downregulated in subsets of kidney, prostate, and thyroid carcinomas. Interestingly, only DEK2 was downregulated in a subset of breast tumors suggesting that DEK2 can be modulated differently than DEK1 in specific cancers. In summary, our findings show distinct expression patterns and subcellular location and suggest non-overlapping functions between the two DEK isoforms.

cell biology↗

bioRxiv2020

ace2 expression is higher in intestines and liver while being tightly regulated in development and disease in zebrafish

Human Angiotensin I Converting Enzyme 2 (ACE2) that acts as a receptor for SARS-CoV-2 entry is highly expressed in human type II pneumocytes and enterocytes and similarly in other mammals and zebrafish (Danio rerio). The zebrafish genome has a highly conserved, one-to-one ortholog of ACE2, i.e., ace2, whose expression profile however has not yet been studied during development or in pathologies relevant to COVID-19. Herein, we identified significant development-, tissue- and gender-specific modulations in ace2 expression based on meta-analysis of zebrafish Affymetrix transcriptomics datasets (ndatasets=107, GPL1319 in GEO database). Co-expression network analysis of ace2 revealed distinct positively correlated (carboxypeptidase activity and fibrin clot formation), and negatively correlated (cilia biogenesis/transport and chromatin modifications) STRING network modules. Using additional transcriptomics datasets, we showed zebrafish embryos before 3 days post fertilization (dpf) exhibited low levels of ace2 that increased significantly until 4 dpf implicating a role for ace2 in organogenesis. Re-analysis of RNA-seq datasets from zebrafish adult tissues demonstrated ace2 was expressed highly in intestines, variably in liver, and at lower levels in other organs. In addition, zebrafish females and males showed significant dimorphism in their age-dependent expression of ace2, and between ovary and testis where the latter had higher levels. Moreover, we demonstrated ace2 expression was significantly modulated under different physiological and pathological conditions associated with development, diet, infection, and inflammation. Our findings implicate a novel translational role for zebrafish ace2 in differentiation and pathologies predominantly found in intestines and liver, in which the effects of SARS-CoV-2 could be detrimental.

molecular biology↗