@article{BaurNietzerKunzetal.2020,
  author    = {Baur, Florentin and Nietzer, Sarah L. and Kunz, Meik and Saal, Fabian and Jeromin, Julian and Matschos, Stephanie and Linnebacher, Michael and Walles, Heike and Dandekar, Thomas and Dandekar, Gudrun},
  title     = {Connecting cancer pathways to tumor engines: a stratification tool for colorectal cancer combining human in vitro tissue models with boolean in silico models},
  series = {Cancers},
  volume    = {12},
  journal   = {Cancers},
  number    = {1},
  issn      = {2072-6694},
  doi       = {10.3390/cancers12010028},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193798},
  pages     = {28},
  year      = {2020},
  abstract  = {To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is—in contrast to melanoma—not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification.},
  language  = {en}
}
@article{BeisserGrohmeKopkaetal.2012,
  author    = {Beisser, Daniela and Grohme, Markus A. and Kopka, Joachim and Frohme, Marcus and Schill, Ralph O. and Hengherr, Steffen and Dandekar, Thomas and Klau, Gunnar W. and Dittrich, Marcus and M{\"u}ller, Tobias},
  title     = {Integrated pathway modules using time-course metabolic profiles and EST data from Milnesium tardigradum},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-75241},
  year      = {2012},
  abstract  = {Background: Tardigrades are multicellular organisms, resistant to extreme environmental changes such as heat, drought, radiation and freezing. They outlast these conditions in an inactive form (tun) to escape damage to cellular structures and cell death. Tardigrades are apparently able to prevent or repair such damage and are therefore a crucial model organism for stress tolerance. Cultures of the tardigrade Milnesium tardigradum were dehydrated by removing the surrounding water to induce tun formation. During this process and the subsequent rehydration, metabolites were measured in a time series by GC-MS. Additionally expressed sequence tags are available, especially libraries generated from the active and inactive state. The aim of this integrated analysis is to trace changes in tardigrade metabolism and identify pathways responsible for their extreme resistance against physical stress. Results: In this study we propose a novel integrative approach for the analysis of metabolic networks to identify modules of joint shifts on the transcriptomic and metabolic levels. We derive a tardigrade-specific metabolic network represented as an undirected graph with 3,658 nodes (metabolites) and 4,378 edges (reactions). Time course metabolite profiles are used to score the network nodes showing a significant change over time. The edges are scored according to information on enzymes from the EST data. Using this combined information, we identify a key subnetwork (functional module) of concerted changes in metabolic pathways, specific for de- and rehydration. The module is enriched in reactions showing significant changes in metabolite levels and enzyme abundance during the transition. It resembles the cessation of a measurablemetabolism (e.g. glycolysis and amino acid anabolism) during the tun formation, the production of storage metabolites and bioprotectants, such as DNA stabilizers, and the generation of amino acids and cellular components from monosaccharides as carbon and energy source during rehydration. Conclusions: The functional module identifies relationships among changed metabolites (e.g. spermidine) and reactions and provides first insights into important altered metabolic pathways. With sparse and diverse data available, the presented integrated metabolite network approach is suitable to integrate all existing data and analyse it in a combined manner.},
  subject      = {Milnesium tardigradum},
  language  = {en}
}
@article{BencurovaAkashDobsonetal.2023,
  author    = {Bencurova, Elena and Akash, Aman and Dobson, Renwick C.J. and Dandekar, Thomas},
  title     = {DNA storage-from natural biology to synthetic biology},
  series = {Computational and Structural Biotechnology Journal},
  volume    = {21},
  journal   = {Computational and Structural Biotechnology Journal},
  issn      = {2001-0370},
  doi       = {10.1016/j.csbj.2023.01.045},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-349971},
  pages     = {1227-1235},
  year      = {2023},
  abstract  = {Natural DNA storage allows cellular differentiation, evolution, the growth of our children and controls all our ecosystems. Here, we discuss the fundamental aspects of DNA storage and recent advances in this field, with special emphasis on natural processes and solutions that can be exploited. We point out new ways of efficient DNA and nucleotide storage that are inspired by nature. Within a few years DNA-based information storage may become an attractive and natural complementation to current electronic data storage systems. We discuss rapid and directed access (e.g. DNA elements such as promotors, enhancers), regulatory signals and modulation (e.g. lncRNA) as well as integrated high-density storage and processing modules (e.g. chromosomal territories). There is pragmatic DNA storage for use in biotechnology and human genetics. We examine DNA storage as an approach for synthetic biology (e.g. light-controlled nucleotide processing enzymes). The natural polymers of DNA and RNA offer much for direct storage operations (read-in, read-out, access control). The inbuilt parallelism (many molecules at many places working at the same time) is important for fast processing of information. Using biology concepts from chromosomal storage, nucleic acid processing as well as polymer material sciences such as electronical effects in enzymes, graphene, nanocellulose up to DNA macram{\´e} , DNA wires and DNA-based aptamer field effect transistors will open up new applications gradually replacing classical information storage methods in ever more areas over time (decades).},
  language  = {en}
}
@article{BencurovaGuptaSarukhanyanetal.2018,
  author    = {Bencurova, Elena and Gupta, Shishir K. and Sarukhanyan, Edita and Dandekar, Thomas},
  title     = {Identification of antifungal targets based on computer modeling},
  series = {Journal of Fungi},
  volume    = {4},
  journal   = {Journal of Fungi},
  number    = {3},
  issn      = {2309-608X},
  doi       = {10.3390/jof4030081},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197670},
  pages     = {81},
  year      = {2018},
  abstract  = {Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host-pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools.},
  language  = {en}
}
@article{BencurovaShityakovSchaacketal.2022,
  author    = {Bencurova, Elena and Shityakov, Sergey and Schaack, Dominik and Kaltdorf, Martin and Sarukhanyan, Edita and Hilgarth, Alexander and Rath, Christin and Montenegro, Sergio and Roth, G{\"u}nter and Lopez, Daniel and Dandekar, Thomas},
  title     = {Nanocellulose composites as smart devices with chassis, light-directed DNA Storage, engineered electronic properties, and chip integration},
  series = {Frontiers in Bioengineering and Biotechnology},
  volume    = {10},
  journal   = {Frontiers in Bioengineering and Biotechnology},
  issn      = {2296-4185},
  doi       = {10.3389/fbioe.2022.869111},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-283033},
  year      = {2022},
  abstract  = {The rapid development of green and sustainable materials opens up new possibilities in the field of applied research. Such materials include nanocellulose composites that can integrate many components into composites and provide a good chassis for smart devices. In our study, we evaluate four approaches for turning a nanocellulose composite into an information storage or processing device: 1) nanocellulose can be a suitable carrier material and protect information stored in DNA. 2) Nucleotide-processing enzymes (polymerase and exonuclease) can be controlled by light after fusing them with light-gating domains; nucleotide substrate specificity can be changed by mutation or pH change (read-in and read-out of the information). 3) Semiconductors and electronic capabilities can be achieved: we show that nanocellulose is rendered electronic by iodine treatment replacing silicon including microstructures. Nanocellulose semiconductor properties are measured, and the resulting potential including single-electron transistors (SET) and their properties are modeled. Electric current can also be transported by DNA through G-quadruplex DNA molecules; these as well as classical silicon semiconductors can easily be integrated into the nanocellulose composite. 4) To elaborate upon miniaturization and integration for a smart nanocellulose chip device, we demonstrate pH-sensitive dyes in nanocellulose, nanopore creation, and kinase micropatterning on bacterial membranes as well as digital PCR micro-wells. Future application potential includes nano-3D printing and fast molecular processors (e.g., SETs) integrated with DNA storage and conventional electronics. This would also lead to environment-friendly nanocellulose chips for information processing as well as smart nanocellulose composites for biomedical applications and nano-factories.},
  language  = {en}
}
@article{BrehmHemerKonradetal.2014,
  author    = {Brehm, Klaus and Hemer, Sarah and Konrad, Christian and Spiliotis, Markus and Koziol, Uriel and Schaack, Dominik and F{\"o}rster, Sabine and Gelmedin, Verena and Stadelmann, Britta and Dandekar, Thomas and Hemphill, Andrew},
  title     = {Host insulin stimulates Echinococcus multilocularis insulin signalling pathways and larval development},
  doi       = {10.1186/1741-7007-12-5},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-110357},
  year      = {2014},
  abstract  = {Background The metacestode of the tapeworm Echinococcus multilocularis is the causative agent of alveolar echinococcosis, a lethal zoonosis. Infections are initiated through establishment of parasite larvae within the intermediate host's liver, where high concentrations of insulin are present, followed by tumour-like growth of the metacestode in host organs. The molecular mechanisms determining the organ tropism of E. multilocularis or the influences of host hormones on parasite proliferation are poorly understood. Results Using in vitro cultivation systems for parasite larvae we show that physiological concentrations (10 nM) of human insulin significantly stimulate the formation of metacestode larvae from parasite stem cells and promote asexual growth of the metacestode. Addition of human insulin to parasite larvae led to increased glucose uptake and enhanced phosphorylation of Echinococcus insulin signalling components, including an insulin receptor-like kinase, EmIR1, for which we demonstrate predominant expression in the parasite's glycogen storage cells. We also characterized a second insulin receptor family member, EmIR2, and demonstrated interaction of its ligand binding domain with human insulin in the yeast two-hybrid system. Addition of an insulin receptor inhibitor resulted in metacestode killing, prevented metacestode development from parasite stem cells, and impaired the activation of insulin signalling pathways through host insulin. Conclusions Our data indicate that host insulin acts as a stimulant for parasite development within the host liver and that E. multilocularis senses the host hormone through an evolutionarily conserved insulin signalling pathway. Hormonal host-parasite cross-communication, facilitated by the relatively close phylogenetic relationship between E. multilocularis and its mammalian hosts, thus appears to be important in the pathology of alveolar echinococcosis. This contributes to a closer understanding of organ tropism and parasite persistence in larval cestode infections. Furthermore, our data show that Echinococcus insulin signalling pathways are promising targets for the development of novel drugs.},
  language  = {en}
}
@article{BreitenbachHelfrichFoersterDandekar2021,
  author    = {Breitenbach, Tim and Helfrich-F{\"o}rster, Charlotte and Dandekar, Thomas},
  title     = {An effective model of endogenous clocks and external stimuli determining circadian rhythms},
  series = {Scientific Reports},
  volume    = {11},
  journal   = {Scientific Reports},
  number    = {1},
  doi       = {10.1038/s41598-021-95391-y},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-261655},
  pages     = {16165},
  year      = {2021},
  abstract  = {Circadian endogenous clocks of eukaryotic organisms are an established and rapidly developing research field. To investigate and simulate in an effective model the effect of external stimuli on such clocks and their components we developed a software framework for download and simulation. The application is useful to understand the different involved effects in a mathematical simple and effective model. This concerns the effects of Zeitgebers, feedback loops and further modifying components. We start from a known mathematical oscillator model, which is based on experimental molecular findings. This is extended with an effective framework that includes the impact of external stimuli on the circadian oscillations including high dose pharmacological treatment. In particular, the external stimuli framework defines a systematic procedure by input-output-interfaces to couple different oscillators. The framework is validated by providing phase response curves and ranges of entrainment. Furthermore, Aschoffs rule is computationally investigated. It is shown how the external stimuli framework can be used to study biological effects like points of singularity or oscillators integrating different signals at once. The mathematical framework and formalism is generic and allows to study in general the effect of external stimuli on oscillators and other biological processes. For an easy replication of each numerical experiment presented in this work and an easy implementation of the framework the corresponding Mathematica files are fully made available. They can be downloaded at the following link: https://www.biozentrum.uni-wuerzburg.de/bioinfo/computing/circadian/.},
  language  = {en}
}
@article{BreitenbachLorenzDandekar2019,
  author    = {Breitenbach, Tim and Lorenz, Kristina and Dandekar, Thomas},
  title     = {How to steer and control ERK and the ERK signaling cascade exemplified by looking at cardiac insufficiency},
  series = {International Journal of Molecular Sciences},
  volume    = {20},
  journal   = {International Journal of Molecular Sciences},
  number    = {9},
  issn      = {1422-0067},
  doi       = {10.3390/ijms20092179},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-285164},
  year      = {2019},
  abstract  = {Mathematical optimization framework allows the identification of certain nodes within a signaling network. In this work, we analyzed the complex extracellular-signal-regulated kinase 1 and 2 (ERK1/2) cascade in cardiomyocytes using the framework to find efficient adjustment screws for this cascade that is important for cardiomyocyte survival and maladaptive heart muscle growth. We modeled optimal pharmacological intervention points that are beneficial for the heart, but avoid the occurrence of a maladaptive ERK1/2 modification, the autophosphorylation of ERK at threonine 188 (ERK\(^{Thr188}\) phosphorylation), which causes cardiac hypertrophy. For this purpose, a network of a cardiomyocyte that was fitted to experimental data was equipped with external stimuli that model the pharmacological intervention points. Specifically, two situations were considered. In the first one, the cardiomyocyte was driven to a desired expression level with different treatment strategies. These strategies were quantified with respect to beneficial effects and maleficent side effects and then which one is the best treatment strategy was evaluated. In the second situation, it was shown how to model constitutively activated pathways and how to identify drug targets to obtain a desired activity level that is associated with a healthy state and in contrast to the maleficent expression pattern caused by the constitutively activated pathway. An implementation of the algorithms used for the calculations is also presented in this paper, which simplifies the application of the presented framework for drug targeting, optimal drug combinations and the systematic and automatic search for pharmacological intervention points. The codes were designed such that they can be combined with any mathematical model given by ordinary differential equations.},
  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{CaliskanCaliskanRasbachetal.2023,
  author    = {Caliskan, Aylin and Caliskan, Deniz and Rasbach, Lauritz and Yu, Weimeng and Dandekar, Thomas and Breitenbach, Tim},
  title     = {Optimized cell type signatures revealed from single-cell data by combining principal feature analysis, mutual information, and machine learning},
  series = {Computational and Structural Biotechnology Journal},
  volume    = {21},
  journal   = {Computational and Structural Biotechnology Journal},
  issn      = {2001-0370},
  doi       = {10.1016/j.csbj.2023.06.002},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-349989},
  pages     = {3293-3314},
  year      = {2023},
  abstract  = {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.},
  language  = {en}
}