@unpublished{Dandekar2019, author = {Dandekar, Thomas}, title = {Biological heuristics applied to cosmology suggests a condensation nucleus as start of our universe and inflation cosmology replaced by a period of rapid Weiss domain-like crystal growth}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-183945}, pages = {24}, year = {2019}, abstract = {Cosmology often uses intricate formulas and mathematics to derive new theories and concepts. We do something different in this paper: We look at biological processes and derive from these heuristics so that the revised cosmology agrees with astronomical observations but does also agree with standard biological observations. We show that we then have to replace any type of singularity at the start of the universe by a condensation nucleus and that the very early period of the universe usually assumed to be inflation has to be replaced by a period of rapid crystal growth as in Weiss magnetization domains. Impressively, these minor modifications agree well with astronomical observations including removing the strong inflation perturbations which were never observed in the recent BICEP2 experiments. Furthermore, looking at biological principles suggests that such a new theory with a condensation nucleus at start and a first rapid phase of magnetization-like growth of the ordered, physical laws obeying lattice we live in is in fact the only convincing theory of the early phases of our universe that also is compatible with current observations. We show in detail in the following that such a process of crystal creation, breaking of new crystal seeds and ultimate evaporation of the present crystal readily leads over several generations to an evolution and selection of better, more stable and more self-organizing crystals. Moreover, this explains the "fine-tuning" question why our universe is fine-tuned to favor life: Our Universe is so self-organizing to have enough offspring and the detailed physics involved is at the same time highly favorable for all self-organizing processes including life. This biological theory contrasts with current standard inflation cosmologies. The latter do not perform well in explaining any phenomena of sophisticated structure creation or self-organization. As proteins can only thermodynamically fold by increasing the entropy in the solution around them we suggest for cosmology a condensation nucleus for a universe can form only in a "chaotic ocean" of string-soup or quantum foam if the entropy outside of the nucleus rapidly increases. We derive an interaction potential for 1 to n-dimensional strings or quantum-foams and show that they allow only 1D, 2D, 4D or octonion interactions. The latter is the richest structure and agrees to the E8 symmetry fundamental to particle physics and also compatible with the ten dimensional string theory E8 which is part of the M-theory. Interestingly, any other interactions of other dimensionality can be ruled out using Hurwitz compositional theorem. Crystallization explains also extremely well why we have only one macroscopic reality and where the worldlines of alternative trajectories exist: They are in other planes of the crystal and for energy reasons they crystallize mostly at the same time, yielding a beautiful and stable crystal. This explains decoherence and allows to determine the size of Planck´s quantum h (very small as separation of crystal layers by energy is extremely strong). Ultimate dissolution of real crystals suggests an explanation for dark energy agreeing with estimates for the "big rip". The halo distribution of dark matter favoring galaxy formation is readily explained by a crystal seed starting with unit cells made of normal and dark matter. That we have only matter and not antimatter can be explained as there may be right handed mattercrystals and left-handed antimatter crystals. Similarly, real crystals are never perfect and we argue that exactly such irregularities allow formation of galaxies, clusters and superclusters. Finally, heuristics from genetics suggest to look for a systems perspective to derive correct vacuum and Higgs Boson energies.}, language = {en} } @article{KaltdorfTheissMarkertetal.2018, author = {Kaltdorf, Kristin Verena and Theiss, Maria and Markert, Sebastian Matthias and Zhen, Mei and Dandekar, Thomas and Stigloher, Christian and Kollmannsberger, Philipp}, title = {Automated classification of synaptic vesicles in electron tomograms of C. elegans using machine learning}, series = {PLoS ONE}, volume = {13}, journal = {PLoS ONE}, number = {10}, doi = {10.1371/journal.pone.0205348}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-176831}, pages = {e0205348}, year = {2018}, abstract = {Synaptic vesicles (SVs) are a key component of neuronal signaling and fulfil different roles depending on their composition. In electron micrograms of neurites, two types of vesicles can be distinguished by morphological criteria, the classical "clear core" vesicles (CCV) and the typically larger "dense core" vesicles (DCV), with differences in electron density due to their diverse cargos. Compared to CCVs, the precise function of DCVs is less defined. DCVs are known to store neuropeptides, which function as neuronal messengers and modulators [1]. In C. elegans, they play a role in locomotion, dauer formation, egg-laying, and mechano- and chemosensation [2]. Another type of DCVs, also referred to as granulated vesicles, are known to transport Bassoon, Piccolo and further constituents of the presynaptic density in the center of the active zone (AZ), and therefore are important for synaptogenesis [3]. To better understand the role of different types of SVs, we present here a new automated approach to classify vesicles. We combine machine learning with an extension of our previously developed vesicle segmentation workflow, the ImageJ macro 3D ART VeSElecT. With that we reliably distinguish CCVs and DCVs in electron tomograms of C. elegans NMJs using image-based features. Analysis of the underlying ground truth data shows an increased fraction of DCVs as well as a higher mean distance between DCVs and AZs in dauer larvae compared to young adult hermaphrodites. Our machine learning based tools are adaptable and can be applied to study properties of different synaptic vesicle pools in electron tomograms of diverse model organisms.}, language = {en} } @article{SarukhanyanShityakovDandekar2018, author = {Sarukhanyan, Edita and Shityakov, Sergey and Dandekar, Thomas}, title = {In silico designed Axl receptor blocking drug candidates against Zika virus infection}, series = {ACS Omega}, volume = {3}, journal = {ACS Omega}, number = {5}, doi = {10.1021/acsomega.8b00223}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-176739}, pages = {5281-5290}, year = {2018}, abstract = {After a large outbreak in Brazil, novel drugs against Zika virus became extremely necessary. Evaluation of virus-based pharmacological strategies concerning essential host factors brought us to the idea that targeting the Axl receptor by blocking its dimerization function could be critical for virus entry. Starting from experimentally validated compounds, such as RU-301, RU-302, warfarin, and R428, we identified a novel compound 2′ (R428 derivative) to be the most potent for this task amongst a number of alternative compounds and leads. The improved affinity of compound 2′ was confirmed by molecular docking as well as molecular dynamics simulation techniques using implicit solvation models. The current study summarizes a new possibility for inhibition of the Axl function as a potential target for future antiviral therapies.}, language = {en} } @article{ShityakovDandekarFoerster2015, author = {Shityakov, Sergey and Dandekar, Thomas and F{\"o}rster, Carola}, title = {Gene expression profiles and protein-protein interaction network analysis in AIDS patients with HIV-associated encephalitis and dementia}, series = {HIV/AIDS: Research and Palliative Care}, volume = {7}, journal = {HIV/AIDS: Research and Palliative Care}, doi = {10.2147/HIV.S88438}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-149494}, pages = {265-276}, year = {2015}, abstract = {Central nervous system dysfunction is an important cause of morbidity and mortality in patients with human immunodeficiency virus type 1 (HIV-1) infection and acquired immunodeficiency virus syndrome (AIDS). Patients with AIDS are usually affected by HIV-associated encephalitis (HIVE) with viral replication limited to cells of monocyte origin. To examine the molecular mechanisms underlying HIVE-induced dementia, the GSE4755 Affymetrix data were obtained from the Gene Expression Omnibus database and the differentially expressed genes (DEGs) between the samples from AIDS patients with and without apparent features of HIVE-induced dementia were identified. In addition, protein-protein interaction networks were constructed by mapping DEGs into protein-protein interaction data to identify the pathways that these DEGs are involved in. The results revealed that the expression of 1,528 DEGs is mainly involved in the immune response, regulation of cell proliferation, cellular response to inflammation, signal transduction, and viral replication cycle. Heat-shock protein alpha, class A member 1 (HSP90AA1), and fibronectin 1 were detected as hub nodes with degree values >130. In conclusion, the results indicate that HSP90A and fibronectin 1 play important roles in HIVE pathogenesis.}, language = {en} } @article{DandekarFieselmannFischeretal.2015, author = {Dandekar, Thomas and Fieselmann, Astrid and Fischer, Eva and Popp, Jasmin and Hensel, Michael and Noster, Janina}, title = {Salmonella - how a metabolic generalist adopts an intracellular lifestyle during infection}, series = {Frontiers in Cellular and Infection Microbiology}, volume = {4}, journal = {Frontiers in Cellular and Infection Microbiology}, number = {191}, doi = {10.3389/fcimb.2014.00191}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-149029}, year = {2015}, abstract = {The human-pathogenic bacterium Salmonella enterica adjusts and adapts to different environments while attempting colonization. In the course of infection nutrient availabilities change drastically. New techniques, "-omics" data and subsequent integration by systems biology improve our understanding of these changes. We review changes in metabolism focusing on amino acid and carbohydrate metabolism. Furthermore, the adaptation process is associated with the activation of genes of the Salmonella pathogenicity islands (SPIs). Anti-infective strategies have to take these insights into account and include metabolic and other strategies. Salmonella infections will remain a challenge for infection biology.}, language = {en} } @article{KarlDandekar2015, author = {Karl, Stefan and Dandekar, Thomas}, title = {Convergence behaviour and control in non-linear biological networks}, series = {Scientific Reports}, volume = {5}, journal = {Scientific Reports}, number = {09746}, doi = {10.1038/srep09746}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-148510}, year = {2015}, abstract = {Control of genetic regulatory networks is challenging to define and quantify. Previous control centrality metrics, which aim to capture the ability of individual nodes to control the system, have been found to suffer from plausibility and applicability problems. Here we present a new approach to control centrality based on network convergence behaviour, implemented as an extension of our genetic regulatory network simulation framework Jimena (http://stefan-karl.de/jimena). We distinguish three types of network control, and show how these mathematical concepts correspond to experimentally verified node functions and signalling pathways in immunity and cell differentiation: Total control centrality quantifies the impact of node mutations and identifies potential pharmacological targets such as genes involved in oncogenesis (e.g. zinc finger protein GLI2 or bone morphogenetic proteins in chondrocytes). Dynamic control centrality describes relaying functions as observed in signalling cascades (e.g. src kinase or Jak/Stat pathways). Value control centrality measures the direct influence of the value of the node on the network (e.g. Indian hedgehog as an essential regulator of proliferation in chondrocytes). Surveying random scale-free networks and biological networks, we find that control of the network resides in few high degree driver nodes and networks can be controlled best if they are sparsely connected.}, language = {en} } @article{RemmeleLutherBalkenholetal.2015, author = {Remmele, Christian W. and Luther, Christian H. and Balkenhol, Johannes and Dandekar, Thomas and M{\"u}ller, Tobias and Dittrich, Marcus T.}, title = {Integrated inference and evaluation of host-fungi interaction networks}, series = {Frontiers in Microbiology}, volume = {6}, journal = {Frontiers in Microbiology}, number = {764}, doi = {10.3389/fmicb.2015.00764}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-148278}, year = {2015}, abstract = {Fungal microorganisms frequently lead to life-threatening infections. Within this group of pathogens, the commensal Candida albicans and the filamentous fungus Aspergillus fumigatus are by far the most important causes of invasive mycoses in Europe. A key capability for host invasion and immune response evasion are specific molecular interactions between the fungal pathogen and its human host. Experimentally validated knowledge about these crucial interactions is rare in literature and even specialized host pathogen databases mainly focus on bacterial and viral interactions whereas information on fungi is still sparse. To establish large-scale host fungi interaction networks on a systems biology scale, we develop an extended inference approach based on protein orthology and data on gene functions. Using human and yeast intraspecies networks as template, we derive a large network of pathogen host interactions (PHI). Rigorous filtering and refinement steps based on cellular localization and pathogenicity information of predicted interactors yield a primary scaffold of fungi human and fungi mouse interaction networks. Specific enrichment of known pathogenicity-relevant genes indicates the biological relevance of the predicted PHI. A detailed inspection of functionally relevant subnetworks reveals novel host fungal interaction candidates such as the Candida virulence factor PLB1 and the anti-fungal host protein APP. Our results demonstrate the applicability of interolog-based prediction methods for host fungi interactions and underline the importance of filtering and refinement steps to attain biologically more relevant interactions. This integrated network framework can serve as a basis for future analyses of high-throughput host fungi transcriptome and proteome data.}, language = {en} } @article{AhmedZeeshanDandekar2016, author = {Ahmed, Zeeshan and Zeeshan, Saman and Dandekar, Thomas}, title = {Mining biomedical images towards valuable information retrieval in biomedical and life sciences}, series = {Database - The Journal of Biological Databases and Curation}, volume = {2016}, journal = {Database - The Journal of Biological Databases and Curation}, doi = {10.1093/database/baw118}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-162697}, pages = {baw118}, year = {2016}, abstract = {Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries.}, language = {en} } @article{WolfKuonenDandekaretal.2015, author = {Wolf, Beat and Kuonen, Pierre and Dandekar, Thomas and Atlan, David}, title = {DNAseq workflow in a diagnostic context and an example of a user friendly implementation}, series = {BioMed Research International}, journal = {BioMed Research International}, number = {403497}, doi = {10.1155/2015/403497}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-144527}, year = {2015}, abstract = {Over recent years next generation sequencing (NGS) technologies evolved from costly tools used by very few, to a much more accessible and economically viable technology. Through this recently gained popularity, its use-cases expanded from research environments into clinical settings. But the technical know-how and infrastructure required to analyze the data remain an obstacle for a wider adoption of this technology, especially in smaller laboratories. We present GensearchNGS, a commercial DNAseq software suite distributed by Phenosystems SA. The focus of GensearchNGS is the optimal usage of already existing infrastructure, while keeping its use simple. This is achieved through the integration of existing tools in a comprehensive software environment, as well as custom algorithms developed with the restrictions of limited infrastructures in mind. This includes the possibility to connect multiple computers to speed up computing intensive parts of the analysis such as sequence alignments. We present a typical DNAseq workflow for NGS data analysis and the approach GensearchNGS takes to implement it. The presented workflow goes from raw data quality control to the final variant report. This includes features such as gene panels and the integration of online databases, like Ensembl for annotations or Cafe Variome for variant sharing.}, language = {en} } @article{KunzGoettlichWallesetal.2017, author = {Kunz, Meik and G{\"o}ttlich, Claudia and Walles, Thorsten and Nietzer, Sarah and Dandekar, Gudrun and Dandekar, Thomas}, title = {MicroRNA-21 versus microRNA-34: Lung cancer promoting and inhibitory microRNAs analysed in silico and in vitro and their clinical impact}, series = {Tumor Biology}, volume = {39}, journal = {Tumor Biology}, number = {7}, doi = {10.1177/1010428317706430}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-158399}, year = {2017}, abstract = {MicroRNAs are well-known strong RNA regulators modulating whole functional units in complex signaling networks. Regarding clinical application, they have potential as biomarkers for prognosis, diagnosis, and therapy. In this review, we focus on two microRNAs centrally involved in lung cancer progression. MicroRNA-21 promotes and microRNA-34 inhibits cancer progression. We elucidate here involved pathways and imbed these antagonistic microRNAs in a network of interactions, stressing their cancer microRNA biology, followed by experimental and bioinformatics analysis of such microRNAs and their targets. This background is then illuminated from a clinical perspective on microRNA-21 and microRNA-34 as general examples for the complex microRNA biology in lung cancer and its diagnostic value. Moreover, we discuss the immense potential that microRNAs such as microRNA-21 and microRNA-34 imply by their broad regulatory effects. These should be explored for novel therapeutic strategies in the clinic.}, language = {en} } @article{AmpattuHagmannLiangetal.2017, author = {Ampattu, Biju Joseph and Hagmann, Laura and Liang, Chunguang and Dittrich, Marcus and Schl{\"u}ter, Andreas and Blom, Jochen and Krol, Elizaveta and Goesmann, Alexander and Becker, Anke and Dandekar, Thomas and M{\"u}ller, Tobias and Schoen, Christoph}, title = {Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence}, series = {BMC Genomics}, volume = {18}, journal = {BMC Genomics}, number = {282}, doi = {10.1186/s12864-017-3616-7}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157534}, year = {2017}, abstract = {Background: Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain α522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence. Results: Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p)ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region. Conclusions: Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis.}, language = {en} } @article{DuehringGermerodtSkerkaetal.2015, author = {D{\"u}hring, Sybille and Germerodt, Sebastian and Skerka, Christine and Zipfel, Peter F. and Dandekar, Thomas and Schuster, Stefan}, title = {Host-pathogen interactions between the human innate immune system and Candida albicans - understanding and modeling defense and evasion strategies}, series = {Frontiers in Microbiology}, volume = {6}, journal = {Frontiers in Microbiology}, number = {625}, doi = {10.3389/fmicb.2015.00625}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-151621}, year = {2015}, abstract = {The diploid, polymorphic yeast Candida albicans is one of the most important human pathogenic fungi. C. albicans can grow, proliferate and coexist as a commensal on or within the human host for a long time. However, alterations in the host environment can render C. albicans virulent. In this review, we describe the immunological cross-talk between C. albicans and the human innate immune system. We give an overview in form of pairs of human defense strategies including immunological mechanisms as well as general stressors such as nutrient limitation, pH, fever etc. and the corresponding fungal response and evasion mechanisms. Furthermore, Computational Systems Biology approaches to model and investigate these complex interactions are highlighted with a special focus on game-theoretical methods and agent-based models. An outlook on interesting questions to be tackled by Systems Biology regarding entangled defense and evasion mechanisms is given.}, language = {en} } @article{SchokraieWarnkenHotzWagenblattetal.2012, author = {Schokraie, Elham and Warnken, Uwe and Hotz-Wagenblatt, Agnes and Grohme, Markus A. and Hengherr, Steffen and F{\"o}rster, Frank and Schill, Ralph O. and Frohme, Marcus and Dandekar, Thomas and Schn{\"o}lzer, Martina}, title = {Comparative proteome analysis of Milnesium tardigradum in early embryonic state versus adults in active and anhydrobiotic state}, series = {PLoS One}, volume = {7}, journal = {PLoS One}, number = {9}, doi = {10.1371/journal.pone.0045682}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-134447}, pages = {e45682}, year = {2012}, abstract = {Tardigrades have fascinated researchers for more than 300 years because of their extraordinary capability to undergo cryptobiosis and survive extreme environmental conditions. However, the survival mechanisms of tardigrades are still poorly understood mainly due to the absence of detailed knowledge about the proteome and genome of these organisms. Our study was intended to provide a basis for the functional characterization of expressed proteins in different states of tardigrades. High-throughput, high-accuracy proteomics in combination with a newly developed tardigrade specific protein database resulted in the identification of more than 3000 proteins in three different states: early embryonic state and adult animals in active and anhydrobiotic state. This comprehensive proteome resource includes protein families such as chaperones, antioxidants, ribosomal proteins, cytoskeletal proteins, transporters, protein channels, nutrient reservoirs, and developmental proteins. A comparative analysis of protein families in the different states was performed by calculating the exponentially modified protein abundance index which classifies proteins in major and minor components. This is the first step to analyzing the proteins involved in early embryonic development, and furthermore proteins which might play an important role in the transition into the anhydrobiotic state.}, language = {en} } @article{KunzWolfSchulzeetal.2016, author = {Kunz, Meik and Wolf, Beat and Schulze, Harald and Atlan, David and Walles, Thorsten and Walles, Heike and Dandekar, Thomas}, title = {Non-Coding RNAs in Lung Cancer: Contribution of Bioinformatics Analysis to the Development of Non-Invasive Diagnostic Tools}, series = {Genes}, volume = {8}, journal = {Genes}, number = {1}, doi = {10.3390/genes8010008}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147990}, pages = {8}, year = {2016}, abstract = {Lung cancer is currently the leading cause of cancer related mortality due to late diagnosis and limited treatment intervention. Non-coding RNAs are not translated into proteins and have emerged as fundamental regulators of gene expression. Recent studies reported that microRNAs and long non-coding RNAs are involved in lung cancer development and progression. Moreover, they appear as new promising non-invasive biomarkers for early lung cancer diagnosis. Here, we highlight their potential as biomarker in lung cancer and present how bioinformatics can contribute to the development of non-invasive diagnostic tools. For this, we discuss several bioinformatics algorithms and software tools for a comprehensive understanding and functional characterization of microRNAs and long non-coding RNAs.}, language = {en} } @article{OthmanNaseemAwadetal.2016, author = {Othman, Eman M. and Naseem, Muhammed and Awad, Eman and Dandekar, Thomas and Stopper, Helga}, title = {The Plant Hormone Cytokinin Confers Protection against Oxidative Stress in Mammalian Cells}, series = {PLoS One}, volume = {11}, journal = {PLoS One}, number = {12}, doi = {10.1371/journal.pone.0168386}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147983}, pages = {e0168386}, year = {2016}, abstract = {Modulating key dynamics of plant growth and development, the effects of the plant hormone cytokinin on animal cells gained much attention recently. Most previous studies on cytokinin effects on mammalian cells have been conducted with elevated cytokinin concentration (in the μM range). However, to examine physiologically relevant dose effects of cytokinins on animal cells, we systematically analyzed the impact of kinetin in cultured cells at low and high concentrations (1nM-10μM) and examined cytotoxic and genotoxic conditions. We furthermore measured the intrinsic antioxidant activity of kinetin in a cell-free system using the Ferric Reducing Antioxidant Power assay and in cells using the dihydroethidium staining method. Monitoring viability, we looked at kinetin effects in mammalian cells such as HL60 cells, HaCaT human keratinocyte cells, NRK rat epithelial kidney cells and human peripheral lymphocytes. Kinetin manifests no antioxidant activity in the cell free system and high doses of kinetin (500 nM and higher) reduce cell viability and mediate DNA damage in vitro. In contrast, low doses (concentrations up to 100 nM) of kinetin confer protection in cells against oxidative stress. Moreover, our results show that pretreatment of the cells with kinetin significantly reduces 4-nitroquinoline 1-oxide mediated reactive oxygen species production. Also, pretreatment with kinetin retains cellular GSH levels when they are also treated with the GSH-depleting agent patulin. Our results explicitly show that low kinetin doses reduce apoptosis and protect cells from oxidative stress mediated cell death. Future studies on the interaction between cytokinins and human cellular pathway targets will be intriguing.}, language = {en} } @article{KaltdorfSrivastavaGuptaetal.2016, author = {Kaltdorf, Martin and Srivastava, Mugdha and Gupta, Shishir K. and Liang, Chunguang and Binder, Jasmin and Dietl, Anna-Maria and Meir, Zohar and Haas, Hubertus and Osherov, Nir and Krappmann, Sven and Dandekar, Thomas}, title = {Systematic Identification of Anti-Fungal Drug Targets by a Metabolic Network Approach}, series = {Frontiers in Molecular Bioscience}, volume = {3}, journal = {Frontiers in Molecular Bioscience}, doi = {10.3389/fmolb.2016.00022}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147396}, pages = {22}, year = {2016}, abstract = {New antimycotic drugs are challenging to find, as potential target proteins may have close human orthologs. We here focus on identifying metabolic targets that are critical for fungal growth and have minimal similarity to targets among human proteins. We compare and combine here: (I) direct metabolic network modeling using elementary mode analysis and flux estimates approximations using expression data, (II) targeting metabolic genes by transcriptome analysis of condition-specific highly expressed enzymes, and (III) analysis of enzyme structure, enzyme interconnectedness ("hubs"), and identification of pathogen-specific enzymes using orthology relations. We have identified 64 targets including metabolic enzymes involved in vitamin synthesis, lipid, and amino acid biosynthesis including 18 targets validated from the literature, two validated and five currently examined in own genetic experiments, and 38 further promising novel target proteins which are non-orthologous to human proteins, involved in metabolism and are highly ranked drug targets from these pipelines.}, language = {en} } @article{KunzLiangNillaetal.2016, author = {Kunz, Meik and Liang, Chunguang and Nilla, Santosh and Cecil, Alexander and Dandekar, Thomas}, title = {The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development}, series = {Database}, volume = {2016}, journal = {Database}, doi = {10.1093/database/baw041}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147369}, pages = {baw041}, year = {2016}, abstract = {The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure-activity relationships.}, language = {en} } @article{NaseemDandekar2012, author = {Naseem, Muhammad and Dandekar, Thomas}, title = {The Role of Auxin-Cytokinin Antagonism in Plant-Pathogen Interactions}, series = {PLOS Pathogens}, volume = {8}, journal = {PLOS Pathogens}, number = {11}, doi = {10.1371/journal.ppat.1003026}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-131901}, pages = {e1003026}, year = {2012}, abstract = {No abstract available.}, language = {en} } @article{BugaScholzKumaretal.2012, author = {Buga, Ana-Maria and Scholz, Claus J{\"u}rgen and Kumar, Senthil and Herndon, James G. and Alexandru, Dragos and Cojocaru, Gabriel Radu and Dandekar, Thomas and Popa-Wagner, Aurel}, title = {Identification of New Therapeutic Targets by Genome-Wide Analysis of Gene Expression in the Ipsilateral Cortex of Aged Rats after Stroke}, series = {PLoS One}, volume = {7}, journal = {PLoS One}, number = {12}, doi = {10.1371/journal.pone.0050985}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-130657}, pages = {e50985}, year = {2012}, abstract = {Background: Because most human stroke victims are elderly, studies of experimental stroke in the aged rather than the young rat model may be optimal for identifying clinically relevant cellular responses, as well for pinpointing beneficial interventions. Methodology/Principal Findings: We employed the Affymetrix platform to analyze the whole-gene transcriptome following temporary ligation of the middle cerebral artery in aged and young rats. The correspondence, heat map, and dendrogram analyses independently suggest a differential, age-group-specific behaviour of major gene clusters after stroke. Overall, the pattern of gene expression strongly suggests that the response of the aged rat brain is qualitatively rather than quantitatively different from the young, i.e. the total number of regulated genes is comparable in the two age groups, but the aged rats had great difficulty in mounting a timely response to stroke. Our study indicates that four genes related to neuropathic syndrome, stress, anxiety disorders and depression (Acvr1c, Cort, Htr2b and Pnoc) may have impaired response to stroke in aged rats. New therapeutic options in aged rats may also include Calcrl, Cyp11b1, Prcp, Cebpa, Cfd, Gpnmb, Fcgr2b, Fcgr3a, Tnfrsf26, Adam 17 and Mmp14. An unexpected target is the enzyme 3-hydroxy-3-methylglutaryl-Coenzyme A synthase 1 in aged rats, a key enzyme in the cholesterol synthesis pathway. Post-stroke axonal growth was compromised in both age groups. Conclusion/Significance: We suggest that a multi-stage, multimodal treatment in aged animals may be more likely to produce positive results. Such a therapeutic approach should be focused on tissue restoration but should also address other aspects of patient post-stroke therapy such as neuropathic syndrome, stress, anxiety disorders, depression, neurotransmission and blood pressure.}, language = {en} } @article{KarlDandekar2013, author = {Karl, Stefan and Dandekar, Thomas}, title = {Jimena: Efficient computing and system state identification for genetic regulatory networks}, series = {BMC Bioinformatics}, volume = {14}, journal = {BMC Bioinformatics}, doi = {10.1186/1471-2105-14-306}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-128671}, year = {2013}, abstract = {Background: Boolean networks capture switching behavior of many naturally occurring regulatory networks. For semi-quantitative modeling, interpolation between ON and OFF states is necessary. The high degree polynomial interpolation of Boolean genetic regulatory networks (GRNs) in cellular processes such as apoptosis or proliferation allows for the modeling of a wider range of node interactions than continuous activator-inhibitor models, but suffers from scaling problems for networks which contain nodes with more than ~10 inputs. Many GRNs from literature or new gene expression experiments exceed those limitations and a new approach was developed. Results: (i) As a part of our new GRN simulation framework Jimena we introduce and setup Boolean-tree-based data structures; (ii) corresponding algorithms greatly expedite the calculation of the polynomial interpolation in almost all cases, thereby expanding the range of networks which can be simulated by this model in reasonable time. (iii) Stable states for discrete models are efficiently counted and identified using binary decision diagrams. As application example, we show how system states can now be sampled efficiently in small up to large scale hormone disease networks (Arabidopsis thaliana development and immunity, pathogen Pseudomonas syringae and modulation by cytokinins and plant hormones). Conclusions: Jimena simulates currently available GRNs about 10-100 times faster than the previous implementation of the polynomial interpolation model and even greater gains are achieved for large scale-free networks. This speed-up also facilitates a much more thorough sampling of continuous state spaces which may lead to the identification of new stable states. Mutants of large networks can be constructed and analyzed very quickly enabling new insights into network robustness and behavior.}, language = {en} }