TY - JOUR A1 - Peindl, Matthias A1 - Göttlich, Claudia A1 - Crouch, Samantha A1 - Hoff, Niklas A1 - Lüttgens, Tamara A1 - Schmitt, Franziska A1 - Pereira, Jesús Guillermo Nieves A1 - May, Celina A1 - Schliermann, Anna A1 - Kronenthaler, Corinna A1 - Cheufou, Danjouma A1 - Reu-Hofer, Simone A1 - Rosenwald, Andreas A1 - Weigl, Elena A1 - Walles, Thorsten A1 - Schüler, Julia A1 - Dandekar, Thomas A1 - Nietzer, Sarah A1 - Dandekar, Gudrun T1 - EMT, stemness, and drug resistance in biological context: a 3D tumor tissue/in silico platform for analysis of combinatorial treatment in NSCLC with aggressive KRAS-biomarker signatures JF - Cancers N2 - Epithelial-to-mesenchymal transition (EMT) is discussed to be centrally involved in invasion, stemness, and drug resistance. Experimental models to evaluate this process in its biological complexity are limited. To shed light on EMT impact and test drug response more reliably, we use a lung tumor test system based on a decellularized intestinal matrix showing more in vivo-like proliferation levels and enhanced expression of clinical markers and carcinogenesis-related genes. In our models, we found evidence for a correlation of EMT with drug resistance in primary and secondary resistant cells harboring KRAS\(^{G12C}\) or EGFR mutations, which was simulated in silico based on an optimized signaling network topology. Notably, drug resistance did not correlate with EMT status in KRAS-mutated patient-derived xenograft (PDX) cell lines, and drug efficacy was not affected by EMT induction via TGF-β. To investigate further determinants of drug response, we tested several drugs in combination with a KRAS\(^{G12C}\) inhibitor in KRAS\(^{G12C}\) mutant HCC44 models, which, besides EMT, display mutations in P53, LKB1, KEAP1, and high c-MYC expression. We identified an aurora-kinase A (AURKA) inhibitor as the most promising candidate. In our network, AURKA is a centrally linked hub to EMT, proliferation, apoptosis, LKB1, and c-MYC. This exemplifies our systemic analysis approach for clinical translation of biomarker signatures. KW - EMT KW - drug resistance KW - invasion KW - stemness KW - 3D lung tumor tissue models KW - KRAS biomarker signatures KW - boolean in silico models KW - targeted combination therapy Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-270744 SN - 2072-6694 VL - 14 IS - 9 ER - TY - JOUR A1 - Sarukhanyan, Edita A1 - Shanmugam, Tipack Ayothyapattanam A1 - Dandekar, Thomas T1 - In silico studies reveal Peramivir and Zanamivir as an optimal drug treatment even if H7N9 avian type influenza virus acquires further resistance JF - Molecules N2 - An epidemic of avian type H7N9 influenza virus, which took place in China in 2013, was enhanced by a naturally occurring R294K mutation resistant against Oseltamivir at the catalytic site of the neuraminidase. To cope with such drug-resistant neuraminidase mutations, we applied the molecular docking technique to evaluate the fitness of the available drugs such as Oseltamivir, Zanamivir, Peramivir, Laninamivir, L-Arginine and Benserazide hydrochloride concerning the N9 enzyme with single (R294K, R119K, R372K), double (R119_294K, R119_372K, R294_372K) and triple (R119_294_372K) mutations in the pocket. We found that the drugs Peramivir and Zanamivir score best amongst the studied compounds, demonstrating their high binding potential towards the pockets with the considered mutations. Despite the fact that mutations changed the shape of the pocket and reduced the binding strength for all drugs, Peramivir was the only drug that formed interactions with the key residues at positions 119, 294 and 372 in the pocket of the triple N9 mutant, while Zanamivir demonstrated the lowest RMSD value (0.7 Å) with respect to the reference structure. KW - H7N9 influenza virus KW - neuraminidase KW - mutation KW - binding pocket KW - molecular docking Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-288240 SN - 1420-3049 VL - 27 IS - 18 ER - TY - JOUR A1 - Gupta, Shishir K. A1 - Minocha, Rashmi A1 - Thapa, Prithivi Jung A1 - Srivastava, Mugdha A1 - Dandekar, Thomas T1 - Role of the pangolin in origin of SARS-CoV-2: an evolutionary perspective JF - International Journal of Molecular Sciences N2 - After the recent emergence of SARS-CoV-2 infection, unanswered questions remain related to its evolutionary history, path of transmission or divergence and role of recombination. There is emerging evidence on amino acid substitutions occurring in key residues of the receptor-binding domain of the spike glycoprotein in coronavirus isolates from bat and pangolins. In this article, we summarize our current knowledge on the origin of SARS-CoV-2. We also analyze the host ACE2-interacting residues of the receptor-binding domain of spike glycoprotein in SARS-CoV-2 isolates from bats, and compare it to pangolin SARS-CoV-2 isolates collected from Guangdong province (GD Pangolin-CoV) and Guangxi autonomous regions (GX Pangolin-CoV) of South China. Based on our comparative analysis, we support the view that the Guangdong Pangolins are the intermediate hosts that adapted the SARS-CoV-2 and represented a significant evolutionary link in the path of transmission of SARS-CoV-2 virus. We also discuss the role of intermediate hosts in the origin of Omicron. KW - COVID-19 KW - SARS-CoV-2 KW - origin KW - evolution KW - intermediate host KW - pangolin KW - mutation KW - recombination KW - adaptation KW - transmission KW - comparative sequence analysis Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-285995 SN - 1422-0067 VL - 23 IS - 16 ER - TY - JOUR A1 - Rackevei, Antonia S. A1 - Borges, Alyssa A1 - Engstler, Markus A1 - Dandekar, Thomas A1 - Wolf, Matthias T1 - About the analysis of 18S rDNA sequence data from trypanosomes in barcoding and phylogenetics: tracing a continuation error occurring in the literature JF - Biology N2 - The variable regions (V1–V9) of the 18S rDNA are routinely used in barcoding and phylogenetics. In handling these data for trypanosomes, we have noticed a misunderstanding that has apparently taken a life of its own in the literature over the years. In particular, in recent years, when studying the phylogenetic relationship of trypanosomes, the use of V7/V8 was systematically established. However, considering the current numbering system for all other organisms (including other Euglenozoa), V7/V8 was never used. In Maia da Silva et al. [Parasitology 2004, 129, 549–561], V7/V8 was promoted for the first time for trypanosome phylogenetics, and since then, more than 70 publications have replicated this nomenclature and even discussed the benefits of the use of this region in comparison to V4. However, the primers used to amplify the variable region of trypanosomes have actually amplified V4 (concerning the current 18S rDNA numbering system). KW - RNA secondary structure KW - variable regions KW - V1–V9 KW - V4 KW - V7/V8 KW - Trypanosoma Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-297562 SN - 2079-7737 VL - 11 IS - 11 ER - TY - JOUR A1 - Fathy, Moustafa A1 - Darwish, Mostafa A. A1 - Abdelhamid, Al-Shaimaa M. A1 - Alrashedy, Gehad M. A1 - Othman, Othman Ali A1 - Naseem, Muhammad A1 - Dandekar, Thomas A1 - Othman, Eman M. T1 - Kinetin ameliorates cisplatin-induced hepatotoxicity and lymphotoxicity via attenuating oxidative damage, cell apoptosis and inflammation in rats JF - Biomedicines N2 - Though several previous studies reported the in vitro and in vivo antioxidant effect of kinetin (Kn), details on its action in cisplatin-induced toxicity are still scarce. In this study we evaluated, for the first time, the effects of kinetin in cisplatin (cp)- induced liver and lymphocyte toxicity in rats. Wistar male albino rats were divided into nine groups: (i) the control (C), (ii) groups 2,3 and 4, which received 0.25, 0.5 and 1 mg/kg kinetin for 10 days; (iii) the cisplatin (cp) group, which received a single intraperitoneal injection of CP (7.0 mg/kg); and (iv) groups 6, 7, 8 and 9, which received, for 10 days, 0.25, 0.5 and 1 mg/kg kinetin or 200 mg/kg vitamin C, respectively, and Cp on the fourth day. CP-injected rats showed a significant impairment in biochemical, oxidative stress and inflammatory parameters in hepatic tissue and lymphocytes. PCR showed a profound increase in caspase-3, and a significant decline in AKT gene expression. Intriguingly, Kn treatment restored the biochemical, redox status and inflammatory parameters. Hepatic AKT and caspase-3 expression as well as CD95 levels in lymphocytes were also restored. In conclusion, Kn mitigated oxidative imbalance, inflammation and apoptosis in CP-induced liver and lymphocyte toxicity; therefore, it can be considered as a promising therapy. KW - cisplatin KW - hepatotoxicity KW - lymphotoxicity KW - oxidative stress KW - AKT KW - CD95 KW - caspase-3 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-281686 SN - 2227-9059 VL - 10 IS - 7 ER - TY - JOUR A1 - Kaltdorf, Martin A1 - Breitenbach, Tim A1 - Karl, Stefan A1 - Fuchs, Maximilian A1 - Kessie, David Komla A1 - Psota, Eric A1 - Prelog, Martina A1 - Sarukhanyan, Edita A1 - Ebert, Regina A1 - Jakob, Franz A1 - Dandekar, Gudrun A1 - Naseem, Muhammad A1 - Liang, Chunguang A1 - Dandekar, Thomas T1 - Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis JF - Scientific Reports N2 - The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors. KW - cellular signalling networks KW - computer modelling Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-313303 VL - 13 ER - TY - JOUR A1 - Han, Chao A1 - Ren, Pengxuan A1 - Mamtimin, Medina A1 - Kruk, Linus A1 - Sarukhanyan, Edita A1 - Li, Chenyu A1 - Anders, Hans-Joachim A1 - Dandekar, Thomas A1 - Krueger, Irena A1 - Elvers, Margitta A1 - Goebel, Silvia A1 - Adler, Kristin A1 - Münch, Götz A1 - Gudermann, Thomas A1 - Braun, Attila A1 - Mammadova-Bach, Elmina T1 - Minimal collagen-binding epitope of glycoprotein VI in human and mouse platelets JF - Biomedicines N2 - Glycoprotein VI (GPVI) is a platelet-specific receptor for collagen and fibrin, regulating important platelet functions such as platelet adhesion and thrombus growth. Although the blockade of GPVI function is widely recognized as a potent anti-thrombotic approach, there are limited studies focused on site-specific targeting of GPVI. Using computational modeling and bioinformatics, we analyzed collagen- and CRP-binding surfaces of GPVI monomers and dimers, and compared the interacting surfaces with other mammalian GPVI isoforms. We could predict a minimal collagen-binding epitope of GPVI dimer and designed an EA-20 antibody that recognizes a linear epitope of this surface. Using platelets and whole blood samples donated from wild-type and humanized GPVI transgenic mice and also humans, our experimental results show that the EA-20 antibody inhibits platelet adhesion and aggregation in response to collagen and CRP, but not to fibrin. The EA-20 antibody also prevents thrombus formation in whole blood, on the collagen-coated surface, in arterial flow conditions. We also show that EA-20 does not influence GPVI clustering or receptor shedding. Therefore, we propose that blockade of this minimal collagen-binding epitope of GPVI with the EA-20 antibody could represent a new anti-thrombotic approach by inhibiting specific interactions between GPVI and the collagen matrix. KW - GPVI KW - collagen KW - blood platelets KW - thrombosis KW - anti-thrombotic therapies Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-304148 SN - 2227-9059 VL - 11 IS - 2 ER - TY - JOUR A1 - Salihoglu, Rana A1 - Srivastava, Mugdha A1 - Liang, Chunguang A1 - Schilling, Klaus A1 - Szalay, Aladar A1 - Bencurova, Elena A1 - Dandekar, Thomas T1 - PRO-Simat: Protein network simulation and design tool JF - Computational and Structural Biotechnology Journal N2 - PRO-Simat is a simulation tool for analysing protein interaction networks, their dynamic change and pathway engineering. It provides GO enrichment, KEGG pathway analyses, and network visualisation from an integrated database of more than 8 million protein-protein interactions across 32 model organisms and the human proteome. We integrated dynamical network simulation using the Jimena framework, which quickly and efficiently simulates Boolean genetic regulatory networks. It enables simulation outputs with in-depth analysis of the type, strength, duration and pathway of the protein interactions on the website. Furthermore, the user can efficiently edit and analyse the effect of network modifications and engineering experiments. In case studies, applications of PRO-Simat are demonstrated: (i) understanding mutually exclusive differentiation pathways in Bacillus subtilis, (ii) making Vaccinia virus oncolytic by switching on its viral replication mainly in cancer cells and triggering cancer cell apoptosis and (iii) optogenetic control of nucleotide processing protein networks to operate DNA storage. Multilevel communication between components is critical for efficient network switching, as demonstrated by a general census on prokaryotic and eukaryotic networks and comparing design with synthetic networks using PRO-Simat. The tool is available at https://prosimat.heinzelab.de/ as a web-based query server. KW - network simulation KW - protein analysis KW - signalling pathways KW - dynamic protein-protein interactions KW - optogenetics KW - oncolytic virus KW - DNA storage Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-350034 SN - 2001-0370 VL - 21 ER - TY - JOUR A1 - Caliskan, Aylin A1 - Caliskan, Deniz A1 - Rasbach, Lauritz A1 - Yu, Weimeng A1 - Dandekar, Thomas A1 - Breitenbach, Tim T1 - Optimized cell type signatures revealed from single-cell data by combining principal feature analysis, mutual information, and machine learning JF - Computational and Structural Biotechnology Journal N2 - Machine learning techniques are excellent to analyze expression data from single cells. These techniques impact all fields ranging from cell annotation and clustering to signature identification. The presented framework evaluates gene selection sets how far they optimally separate defined phenotypes or cell groups. This innovation overcomes the present limitation to objectively and correctly identify a small gene set of high information content regarding separating phenotypes for which corresponding code scripts are provided. The small but meaningful subset of the original genes (or feature space) facilitates human interpretability of the differences of the phenotypes including those found by machine learning results and may even turn correlations between genes and phenotypes into a causal explanation. For the feature selection task, the principal feature analysis is utilized which reduces redundant information while selecting genes that carry the information for separating the phenotypes. In this context, the presented framework shows explainability of unsupervised learning as it reveals cell-type specific signatures. Apart from a Seurat preprocessing tool and the PFA script, the pipeline uses mutual information to balance accuracy and size of the gene set if desired. A validation part to evaluate the gene selection for their information content regarding the separation of the phenotypes is provided as well, binary and multiclass classification of 3 or 4 groups are studied. Results from different single-cell data are presented. In each, only about ten out of more than 30000 genes are identified as carrying the relevant information. The code is provided in a GitHub repository at https://github.com/AC-PHD/Seurat_PFA_pipeline. KW - single cell analysis KW - machine learning KW - explainability of machine learning KW - principal KW - feature analysis KW - model reduction KW - feature selection Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-349989 SN - 2001-0370 VL - 21 ER - TY - JOUR A1 - Caliskan, Aylin A1 - Dangwal, Seema A1 - Dandekar, Thomas T1 - Metadata integrity in bioinformatics: bridging the gap between data and knowledge JF - Computational and Structural Biotechnology Journal N2 - In the fast-evolving landscape of biomedical research, the emergence of big data has presented researchers with extraordinary opportunities to explore biological complexities. In biomedical research, big data imply also a big responsibility. This is not only due to genomics data being sensitive information but also due to genomics data being shared and re-analysed among the scientific community. This saves valuable resources and can even help to find new insights in silico. To fully use these opportunities, detailed and correct metadata are imperative. This includes not only the availability of metadata but also their correctness. Metadata integrity serves as a fundamental determinant of research credibility, supporting the reliability and reproducibility of data-driven findings. Ensuring metadata availability, curation, and accuracy are therefore essential for bioinformatic research. Not only must metadata be readily available, but they must also be meticulously curated and ideally error-free. Motivated by an accidental discovery of a critical metadata error in patient data published in two high-impact journals, we aim to raise awareness for the need of correct, complete, and curated metadata. We describe how the metadata error was found, addressed, and present examples for metadata-related challenges in omics research, along with supporting measures, including tools for checking metadata and software to facilitate various steps from data analysis to published research. Highlights • Data awareness and data integrity underpins the trustworthiness of results and subsequent further analysis. • Big data and bioinformatics enable efficient resource use by repurposing publicly available RNA-Sequencing data. • Manual checks of data quality and integrity are insufficient due to the overwhelming volume and rapidly growing data. • Automation and artificial intelligence provide cost-effective and efficient solutions for data integrity and quality checks. • FAIR data management, various software solutions and analysis tools assist metadata maintenance. KW - meta-data KW - error KW - annotation KW - error-transfer KW - wrong labelling KW - patient data KW - control group KW - tools overview Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-349990 SN - 2001-0370 VL - 21 ER -