@article{SbieraKunzWeigandetal.2019,
  author    = {Sbiera, Silviu and Kunz, Meik and Weigand, Isabel and Deutschbein, Timo and Dandekar, Thomas and Fassnacht, Martin},
  title     = {The new genetic landscape of Cushing's disease: deubiquitinases in the spotlight},
  series = {Cancers},
  volume    = {11},
  journal   = {Cancers},
  number    = {11},
  issn      = {2072-6694},
  doi       = {10.3390/cancers11111761},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193194},
  pages     = {1761},
  year      = {2019},
  abstract  = {Cushing's disease (CD) is a rare condition caused by adrenocorticotropic hormone (ACTH)-producing adenomas of the pituitary, which lead to hypercortisolism that is associated with high morbidity and mortality. Treatment options in case of persistent or recurrent disease are limited, but new insights into the pathogenesis of CD are raising hope for new therapeutic avenues. Here, we have performed a meta-analysis of the available sequencing data in CD to create a comprehensive picture of CD's genetics. Our analyses clearly indicate that somatic mutations in the deubiquitinases are the key drivers in CD, namely USP8 (36.5\%) and USP48 (13.3\%). While in USP48 only Met415 is affected by mutations, in USP8 there are 26 different mutations described. However, these different mutations are clustering in the same hotspot region (affecting in 94.5\% of cases Ser718 and Pro720). In contrast, pathogenic variants classically associated with tumorigenesis in genes like TP53 and BRAF are also present in CD but with low incidence (12.5\% and 7\%). Importantly, several of these mutations might have therapeutic potential as there are drugs already investigated in preclinical and clinical setting for other diseases. Furthermore, network and pathway analyses of all somatic mutations in CD suggest a rather unified picture hinting towards converging oncogenic pathways.},
  language  = {en}
}
@article{MergetKoetschanHackletal.2012,
  author    = {Merget, Benjamin and Koetschan, Christian and Hackl, Thomas and F{\"o}rster, Frank and Dandekar, Thomas and M{\"u}ller, Tobias and Schultz, J{\"o}rg and Wolf, Matthias},
  title     = {The ITS2 Database},
  series = {Journal of Visual Expression},
  volume    = {61},
  journal   = {Journal of Visual Expression},
  number    = {e3806},
  doi       = {10.3791/3806},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-124600},
  year      = {2012},
  abstract  = {The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1 and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation. The ITS2 Database presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank accurately reannotated. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold (direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold. The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE and ProfDistS for multiple sequence-structure alignment calculation and Neighbor Joining tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure. In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.},
  language  = {en}
}
@article{VainshteinSanchezBrazmaetal.2010,
  author    = {Vainshtein, Yevhen and Sanchez, Mayka and Brazma, Alvis and Hentze, Matthias W. and Dandekar, Thomas and Muckenthaler, Martina U.},
  title     = {The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-67869},
  year      = {2010},
  abstract  = {Background: Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, production and manipulations are limiting factors, affecting data quality. The use of customized DNA microarrays improves overall data quality in many situations, however, only if for these specifically designed microarrays analysis tools are available. Results: The IronChip Evaluation Package (ICEP) is a collection of Perl utilities and an easy to use data evaluation pipeline for the analysis of microarray data with a focus on data quality of custom-designed microarrays. The package has been developed for the statistical and bioinformatical analysis of the custom cDNA microarray IronChip but can be easily adapted for other cDNA or oligonucleotide-based designed microarray platforms. ICEP uses decision tree-based algorithms to assign quality flags and performs robust analysis based on chip design properties regarding multiple repetitions, ratio cut-off, background and negative controls. Conclusions: ICEP is a stand-alone Windows application to obtain optimal data quality from custom-designed microarrays and is freely available here (see "Additional Files" section) and at: http://www.alice-dsl.net/evgeniy. vainshtein/ICEP/},
  subject      = {Microarray},
  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{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{GrebinykPrylutskaChepurnaetal.2019,
  author    = {Grebinyk, Anna and Prylutska, Svitlana and Chepurna, Oksana and Grebinyk, Sergii and Prylutskyy, Yuriy and Ritter, Uwe and Ohulchanskyy, Tymish Y. and Matyshevska, Olga and Dandekar, Thomas and Frohme, Marcus},
  title     = {Synergy of chemo- and photodynamic therapies with C\(_{60}\) Fullerene-Doxorubicin nanocomplex},
  series = {Nanomaterials},
  volume    = {9},
  journal   = {Nanomaterials},
  number    = {11},
  issn      = {2079-4991},
  doi       = {10.3390/nano9111540},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193140},
  year      = {2019},
  abstract  = {A nanosized drug complex was explored to improve the efficiency of cancer chemotherapy, complementing it with nanodelivery and photodynamic therapy. For this, nanomolar amounts of a non-covalent nanocomplex of Doxorubicin (Dox) with carbon nanoparticle C\(_{60}\) fullerene (C\(_{60}\)) were applied in 1:1 and 2:1 molar ratio, exploiting C\(_{60}\) both as a drug-carrier and as a photosensitizer. The fluorescence microscopy analysis of human leukemic CCRF-CEM cells, in vitro cancer model, treated with nanocomplexes showed Dox's nuclear and C\(_{60}\)'s extranuclear localization. It gave an opportunity to realize a double hit strategy against cancer cells based on Dox's antiproliferative activity and C\(_{60}\)'s photoinduced pro-oxidant activity. When cells were treated with 2:1 C\(_{60}\)-Dox and irradiated at 405 nm the high cytotoxicity of photo-irradiated C\(_{60}\)-Dox enabled a nanomolar concentration of Dox and C\(_{60}\) to efficiently kill cancer cells in vitro. The high pro-oxidant and pro-apoptotic efficiency decreased IC\(_{50}\) 16, 9 and 7 × 10\(^3\)-fold, if compared with the action of Dox, non-irradiated nanocomplex, and C\(_{60}\)'s photodynamic effect, correspondingly. Hereafter, a strong synergy of therapy arising from the combination of C\(_{60}\)-mediated Dox delivery and C\(_{60}\) photoexcitation was revealed. Our data indicate that a combination of chemo- and photodynamic therapies with C\(_{60}\)-Dox nanoformulation provides a promising synergetic approach for cancer treatment.},
  language  = {en}
}
@article{NaseemSrivastavaDandekar2014,
  author    = {Naseem, Muhammad and Srivastava, Mugdha and Dandekar, Thomas},
  title     = {Stem-cell-triggered immunity safeguards cytokinin enriched plant shoot apexes from pathogen infection},
  series = {Frontiers in Plant Science},
  volume    = {5},
  journal   = {Frontiers in Plant Science},
  issn      = {1664-462X},
  doi       = {10.3389/fpls.2014.00588},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-118247},
  pages     = {588},
  year      = {2014},
  abstract  = {Intricate mechanisms discriminate between friends and foes in plants. Plant organs deploy overlapping and distinct protection strategies. Despite vulnerability to a plethora of pathogens, the growing tips of plants grow bacteria free. The shoot apical meristem (SAM) is among three stem cells niches, a self-renewable reservoir for the future organogenesis of leaf, stem, and flowers. How plants safeguard this high value growth target from infections was not known until now. Recent reports find the stem cell secreted 12-amino acid peptide CLV3p (CLAVATA3 peptide) is perceived by FLS2 (FLAGELLIN SENSING 2) receptor and activates the transcription of immunity and defense marker genes. No infection in the SAM of wild type plants and bacterial infection in clv3 and fls2 mutants illustrate this natural protection against infections. Cytokinins (CKs) are enriched in the SAM and regulate meristem activities by their involvement in stem cell signaling networks. Auxin mediates plant susceptibility to pathogen infections while CKs boost plant immunity. Here, in addition to the stem-cell-triggered immunity we also highlight a potential link between CK signaling and CLV3p mediated immune response in the SAM.},
  language  = {en}
}
@article{LiangRiosMiguelJaricketal.2021,
  author    = {Liang, Chunguang and Rios-Miguel, Ana B. and Jarick, Marcel and Neurgaonkar, Priya and Girard, Myriam and Fran{\c{c}}ois, Patrice and Schrenzel, Jacques and Ibrahim, Eslam S. and Ohlsen, Knut and Dandekar, Thomas},
  title     = {Staphylococcus aureus transcriptome data and metabolic modelling investigate the interplay of Ser/Thr kinase PknB, its phosphatase Stp, the glmR/yvcK regulon and the cdaA operon for metabolic adaptation},
  series = {Microorganisms},
  volume    = {9},
  journal   = {Microorganisms},
  number    = {10},
  issn      = {2076-2607},
  doi       = {10.3390/microorganisms9102148},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-248459},
  year      = {2021},
  abstract  = {Serine/threonine kinase PknB and its corresponding phosphatase Stp are important regulators of many cell functions in the pathogen S. aureus. Genome-scale gene expression data of S. aureus strain NewHG (sigB\(^+\)) elucidated their effect on physiological functions. Moreover, metabolic modelling from these data inferred metabolic adaptations. We compared wild-type to deletion strains lacking pknB, stp or both. Ser/Thr phosphorylation of target proteins by PknB switched amino acid catabolism off and gluconeogenesis on to provide the cell with sufficient components. We revealed a significant impact of PknB and Stp on peptidoglycan, nucleotide and aromatic amino acid synthesis, as well as catabolism involving aspartate transaminase. Moreover, pyrimidine synthesis was dramatically impaired by stp deletion but only slightly by functional loss of PknB. In double knockouts, higher activity concerned genes involved in peptidoglycan, purine and aromatic amino acid synthesis from glucose but lower activity of pyrimidine synthesis from glucose compared to the wild type. A second transcriptome dataset from S. aureus NCTC 8325 (sigB\(^-\)) validated the predictions. For this metabolic adaptation, PknB was found to interact with CdaA and the yvcK/glmR regulon. The involved GlmR structure and the GlmS riboswitch were modelled. Furthermore, PknB phosphorylation lowered the expression of many virulence factors, and the study shed light on S. aureus infection processes.},
  language  = {en}
}
@article{DandekarAhmedSamanetal.2013,
  author    = {Dandekar, Thomas and Ahmed, Zeeshan and Saman, Zeeshan and Huber, Claudia and Hensel, Michael and Schomburg, Dietmar and M{\"u}nch, Richard and Eisenreich, Wolfgang},
  title     = {Software LS-MIDA for efficient mass isotopomer distribution analysis in metabolic modelling},
  series = {BMC Bioinformatics},
  journal   = {BMC Bioinformatics},
  doi       = {10.1186/1471-2334-13-266},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-95882},
  year      = {2013},
  abstract  = {Background The knowledge of metabolic pathways and fluxes is important to understand the adaptation of organisms to their biotic and abiotic environment. The specific distribution of stable isotope labelled precursors into metabolic products can be taken as fingerprints of the metabolic events and dynamics through the metabolic networks. An open-source software is required that easily and rapidly calculates from mass spectra of labelled metabolites, derivatives and their fragments global isotope excess and isotopomer distribution. Results The open-source software "Least Square Mass Isotopomer Analyzer" (LS-MIDA) is presented that processes experimental mass spectrometry (MS) data on the basis of metabolite information such as the number of atoms in the compound, mass to charge ratio (m/e or m/z) values of the compounds and fragments under study, and the experimental relative MS intensities reflecting the enrichments of isotopomers in 13C- or 15 N-labelled compounds, in comparison to the natural abundances in the unlabelled molecules. The software uses Brauman's least square method of linear regression. As a result, global isotope enrichments of the metabolite or fragment under study and the molar abundances of each isotopomer are obtained and displayed. Conclusions The new software provides an open-source platform that easily and rapidly converts experimental MS patterns of labelled metabolites into isotopomer enrichments that are the basis for subsequent observation-driven analysis of pathways and fluxes, as well as for model-driven metabolic flux calculations.},
  language  = {en}
}
@article{KaltdorfBreitenbachKarletal.2023,
  author    = {Kaltdorf, Martin and Breitenbach, Tim and Karl, Stefan and Fuchs, Maximilian and Kessie, David Komla and Psota, Eric and Prelog, Martina and Sarukhanyan, Edita and Ebert, Regina and Jakob, Franz and Dandekar, Gudrun and Naseem, Muhammad and Liang, Chunguang and Dandekar, Thomas},
  title     = {Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis},
  series = {Scientific Reports},
  volume    = {13},
  journal   = {Scientific Reports},
  doi       = {10.1038/s41598-022-27098-7},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-313303},
  year      = {2023},
  abstract  = {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.},
  language  = {en}
}