@article{StaigerCadotKooteretal.2012, author = {Staiger, Christine and Cadot, Sidney and Kooter, Raul and Dittrich, Marcus and M{\"u}ller, Tobias and Klau, Gunnar W. and Wessels, Lodewyk F. A.}, title = {A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer}, series = {PLoS One}, volume = {7}, journal = {PLoS One}, number = {4}, doi = {10.1371/journal.pone.0034796}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-131323}, pages = {e34796}, year = {2012}, abstract = {Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single genes classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single genes classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single genes classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single genes sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single genes classifiers for predicting outcome in breast cancer.}, language = {en} } @article{SchmidSchindelinCardonaetal.2010, author = {Schmid, Benjamin and Schindelin, Johannes and Cardona, Albert and Longair, Martin and Heisenberg, Martin}, title = {A high-level 3D visualization API for Java and ImageJ}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-67851}, year = {2010}, abstract = {Background: Current imaging methods such as Magnetic Resonance Imaging (MRI), Confocal microscopy, Electron Microscopy (EM) or Selective Plane Illumination Microscopy (SPIM) yield three-dimensional (3D) data sets in need of appropriate computational methods for their analysis. The reconstruction, segmentation and registration are best approached from the 3D representation of the data set. Results: Here we present a platform-independent framework based on Java and Java 3D for accelerated rendering of biological images. Our framework is seamlessly integrated into ImageJ, a free image processing package with a vast collection of community-developed biological image analysis tools. Our framework enriches the ImageJ software libraries with methods that greatly reduce the complexity of developing image analysis tools in an interactive 3D visualization environment. In particular, we provide high-level access to volume rendering, volume editing, surface extraction, and image annotation. The ability to rely on a library that removes the low-level details enables concentrating software development efforts on the algorithm implementation parts. Conclusions: Our framework enables biomedical image software development to be built with 3D visualization capabilities with very little effort. We offer the source code and convenient binary packages along with extensive documentation at http://3dviewer.neurofly.de.}, subject = {Visualisierung}, language = {en} } @unpublished{Dandekar2023, author = {Dandekar, Thomas}, title = {Analysing the phase space of the standard model and its basic four forces from a qubit phase transition perspective: implications for large-scale structure generation and early cosmological events}, doi = {10.25972/OPUS-29858}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-298580}, pages = {42}, year = {2023}, abstract = {The phase space for the standard model of the basic four forces for n quanta includes all possible ensemble combinations of their quantum states m, a total of n**m states. Neighbor states reach according to transition possibilities (S-matrix) with emergent time from entropic ensemble gradients. We replace the "big bang" by a condensation event (interacting qubits become decoherent) and inflation by a crystallization event - the crystal unit cell guarantees same symmetries everywhere. Interacting qubits solidify and form a rapidly growing domain where the n**m states become separated ensemble states, rising long-range forces stop ultimately further growth. After that very early events, standard cosmology with the hot fireball model takes over. Our theory agrees well with lack of inflation traces in cosmic background measurements, large-scale structure of voids and filaments, supercluster formation, galaxy formation, dominance of matter and life-friendliness. We prove qubit interactions to be 1,2,4 or 8 dimensional (agrees with E8 symmetry of our universe). Repulsive forces at ultrashort distances result from quantization, long-range forces limit crystal growth. Crystals come and go in the qubit ocean. This selects for the ability to lay seeds for new crystals, for self-organization and life-friendliness. We give energy estimates for free qubits vs bound qubits, misplacements in the qubit crystal and entropy increase during qubit decoherence / crystal formation. Scalar fields for color interaction and gravity derive from the permeating qubit-interaction field. Hence, vacuum energy gets low only inside the qubit crystal. Condensed mathematics may advantageously model free / bound qubits in phase space.}, language = {en} } @article{ZirkelCecilSchaeferetal.2012, author = {Zirkel, J. and Cecil, A. and Sch{\"a}fer, F. and Rahlfs, S. and Ouedraogo, A. and Xiao, K. and Sawadogo, S. and Coulibaly, B. and Becker, K. and Dandekar, T.}, title = {Analyzing Thiol-Dependent Redox Networks in the Presence of Methylene Blue and Other Antimalarial Agents with RT-PCR-Supported in silico Modeling}, series = {Bioinformatics and Biology Insights}, volume = {6}, journal = {Bioinformatics and Biology Insights}, doi = {10.4137/BBI.S10193}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-123751}, pages = {287-302}, year = {2012}, abstract = {BACKGROUND: In the face of growing resistance in malaria parasites to drugs, pharmacological combination therapies are important. There is accumulating evidence that methylene blue (MB) is an effective drug against malaria. Here we explore the biological effects of both MB alone and in combination therapy using modeling and experimental data. RESULTS: We built a model of the central metabolic pathways in P. falciparum. Metabolic flux modes and their changes under MB were calculated by integrating experimental data (RT-PCR data on mRNAs for redox enzymes) as constraints and results from the YANA software package for metabolic pathway calculations. Several different lines of MB attack on Plasmodium redox defense were identified by analysis of the network effects. Next, chloroquine resistance based on pfmdr/and pfcrt transporters, as well as pyrimethamine/sulfadoxine resistance (by mutations in DHF/DHPS), were modeled in silico. Further modeling shows that MB has a favorable synergism on antimalarial network effects with these commonly used antimalarial drugs. CONCLUSIONS: Theoretical and experimental results support that methylene blue should, because of its resistance-breaking potential, be further tested as a key component in drug combination therapy efforts in holoendemic areas.}, language = {en} } @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{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{SchererFleishmanJonesetal.2021, author = {Scherer, Marc and Fleishman, Sarel J. and Jones, Patrik R. and Dandekar, Thomas and Bencurova, Elena}, title = {Computational Enzyme Engineering Pipelines for Optimized Production of Renewable Chemicals}, series = {Frontiers in Bioengineering and Biotechnology}, volume = {9}, journal = {Frontiers in Bioengineering and Biotechnology}, issn = {2296-4185}, doi = {10.3389/fbioe.2021.673005}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-240598}, year = {2021}, abstract = {To enable a sustainable supply of chemicals, novel biotechnological solutions are required that replace the reliance on fossil resources. One potential solution is to utilize tailored biosynthetic modules for the metabolic conversion of CO2 or organic waste to chemicals and fuel by microorganisms. Currently, it is challenging to commercialize biotechnological processes for renewable chemical biomanufacturing because of a lack of highly active and specific biocatalysts. As experimental methods to engineer biocatalysts are time- and cost-intensive, it is important to establish efficient and reliable computational tools that can speed up the identification or optimization of selective, highly active, and stable enzyme variants for utilization in the biotechnological industry. Here, we review and suggest combinations of effective state-of-the-art software and online tools available for computational enzyme engineering pipelines to optimize metabolic pathways for the biosynthesis of renewable chemicals. Using examples relevant for biotechnology, we explain the underlying principles of enzyme engineering and design and illuminate future directions for automated optimization of biocatalysts for the assembly of synthetic metabolic pathways.}, language = {en} } @article{KruegerFriedrichFoersteretal.2012, author = {Krueger, Beate and Friedrich, Torben and F{\"o}rster, Frank and Bernhardt, J{\"o}rg and Gross, Roy and Dandekar, Thomas}, title = {Different evolutionary modifications as a guide to rewire two-component systems}, series = {Bioinformatics and Biology Insights}, volume = {6}, journal = {Bioinformatics and Biology Insights}, doi = {10.4137/BBI.S9356}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-123647}, pages = {97-128}, year = {2012}, abstract = {Two-component systems (TCS) are short signalling pathways generally occurring in prokaryotes. They frequently regulate prokaryotic stimulus responses and thus are also of interest for engineering in biotechnology and synthetic biology. The aim of this study is to better understand and describe rewiring of TCS while investigating different evolutionary scenarios. Based on large-scale screens of TCS in different organisms, this study gives detailed data, concrete alignments, and structure analysis on three general modification scenarios, where TCS were rewired for new responses and functions: (i) exchanges in the sequence within single TCS domains, (ii) exchange of whole TCS domains; (iii) addition of new components modulating TCS function. As a result, the replacement of stimulus and promotor cassettes to rewire TCS is well defined exploiting the alignments given here. The diverged TCS examples are non-trivial and the design is challenging. Designed connector proteins may also be useful to modify TCS in selected cases.}, language = {en} } @article{KaltdorfSchulzeHelmprobstetal.2017, author = {Kaltdorf, Kristin Verena and Schulze, Katja and Helmprobst, Frederik and Kollmannsberger, Philip and Dandekar, Thomas and Stigloher, Christian}, title = {Fiji macro 3D ART VeSElecT: 3D automated reconstruction tool for vesicle structures of electron tomograms}, series = {PLoS Computational Biology}, volume = {13}, journal = {PLoS Computational Biology}, number = {1}, doi = {10.1371/journal.pcbi.1005317}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-172112}, year = {2017}, abstract = {Automatic image reconstruction is critical to cope with steadily increasing data from advanced microscopy. We describe here the Fiji macro 3D ART VeSElecT which we developed to study synaptic vesicles in electron tomograms. We apply this tool to quantify vesicle properties (i) in embryonic Danio rerio 4 and 8 days past fertilization (dpf) and (ii) to compare Caenorhabditis elegans N2 neuromuscular junctions (NMJ) wild-type and its septin mutant (unc-59(e261)). We demonstrate development-specific and mutant-specific changes in synaptic vesicle pools in both models. We confirm the functionality of our macro by applying our 3D ART VeSElecT on zebrafish NMJ showing smaller vesicles in 8 dpf embryos then 4 dpf, which was validated by manual reconstruction of the vesicle pool. Furthermore, we analyze the impact of C. elegans septin mutant unc-59(e261) on vesicle pool formation and vesicle size. Automated vesicle registration and characterization was implemented in Fiji as two macros (registration and measurement). This flexible arrangement allows in particular reducing false positives by an optional manual revision step. Preprocessing and contrast enhancement work on image-stacks of 1nm/pixel in x and y direction. Semi-automated cell selection was integrated. 3D ART VeSElecT removes interfering components, detects vesicles by 3D segmentation and calculates vesicle volume and diameter (spherical approximation, inner/outer diameter). Results are collected in color using the RoiManager plugin including the possibility of manual removal of non-matching confounder vesicles. Detailed evaluation considered performance (detected vesicles) and specificity (true vesicles) as well as precision and recall. We furthermore show gain in segmentation and morphological filtering compared to learning based methods and a large time gain compared to manual segmentation. 3D ART VeSElecT shows small error rates and its speed gain can be up to 68 times faster in comparison to manual annotation. Both automatic and semi-automatic modes are explained including a tutorial.}, language = {en} } @article{AppelScholzMuelleretal.2015, author = {Appel, Mirjam and Scholz, Claus-J{\"u}rgen and M{\"u}ller, Tobias and Dittrich, Marcus and K{\"o}nig, Christian and Bockstaller, Marie and Oguz, Tuba and Khalili, Afshin and Antwi-Adjei, Emmanuel and Schauer, Tamas and Margulies, Carla and Tanimoto, Hiromu and Yarali, Ayse}, title = {Genome-Wide Association Analyses Point to Candidate Genes for Electric Shock Avoidance in Drosophila melanogaster}, series = {PLoS ONE}, volume = {10}, journal = {PLoS ONE}, number = {5}, doi = {10.1371/journal.pone.0126986}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-152006}, pages = {e0126986}, year = {2015}, abstract = {Electric shock is a common stimulus for nociception-research and the most widely used reinforcement in aversive associative learning experiments. Yet, nothing is known about the mechanisms it recruits at the periphery. To help fill this gap, we undertook a genome-wide association analysis using 38 inbred Drosophila melanogaster strains, which avoided shock to varying extents. We identified 514 genes whose expression levels and/or sequences covaried with shock avoidance scores. We independently scrutinized 14 of these genes using mutants, validating the effect of 7 of them on shock avoidance. This emphasizes the value of our candidate gene list as a guide for follow-up research. In addition, by integrating our association results with external protein-protein interaction data we obtained a shock avoidance- associated network of 38 genes. Both this network and the original candidate list contained a substantial number of genes that affect mechanosensory bristles, which are hairlike organs distributed across the fly's body. These results may point to a potential role for mechanosensory bristles in shock sensation. Thus, we not only provide a first list of candidate genes for shock avoidance, but also point to an interesting new hypothesis on nociceptive mechanisms.}, language = {en} } @article{AndronicShirakashiPickeletal.2015, author = {Andronic, Joseph and Shirakashi, Ryo and Pickel, Simone U. and Westerling, Katherine M. and Klein, Teresa and Holm, Thorge and Sauer, Markus and Sukhorukov, Vladimir L.}, title = {Hypotonic Activation of the Myo-Inositol Transporter SLC5A3 in HEK293 Cells Probed by Cell Volumetry, Confocal and Super-Resolution Microscopy}, series = {PLoS One}, volume = {10}, journal = {PLoS One}, number = {3}, doi = {10.1371/journal.pone.0119990}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-126408}, year = {2015}, abstract = {Swelling-activated pathways for myo-inositol, one of the most abundant organic osmolytes in mammalian cells, have not yet been identified. The present study explores the SLC5A3 protein as a possible transporter of myo-inositol in hyponically swollen HEK293 cells. To address this issue, we examined the relationship between the hypotonicity-induced changes in plasma membrane permeability to myo-inositol Pino [m/s] and expression/localization of SLC5A3. Pino values were determined by cell volumetry over a wide tonicity range (100-275 mOsm) in myo-inositol-substituted solutions. While being negligible under mild hypotonicity (200-275 mOsm), Pino grew rapidly at osmolalities below 200 mOsm to reach a maximum of ∼3 nm/s at 100-125 mOsm, as indicated by fast cell swelling due to myo-inositol influx. The increase in Pino resulted most likely from the hypotonicity-mediated incorporation of cytosolic SLC5A3 into the plasma membrane, as revealed by confocal fluorescence microscopy of cells expressing EGFP-tagged SLC5A3 and super-resolution imaging of immunostained SLC5A3 by direct stochastic optical reconstruction microscopy (dSTORM). dSTORM in hypotonic cells revealed a surface density of membrane-associated SLC5A3 proteins of 200-2000 localizations/μm2. Assuming SLC5A3 to be the major path for myo-inositol, a turnover rate of 80-800 myo-inositol molecules per second for a single transporter protein was estimated from combined volumetric and dSTORM data. Hypotonic stress also caused a significant upregulation of SLC5A3 gene expression as detected by semiquantitative RT-PCR and Western blot analysis. In summary, our data provide first evidence for swelling-mediated activation of SLC5A3 thus suggesting a functional role of this transporter in hypotonic volume regulation of mammalian cells.}, language = {en} } @article{WeissSchultz2015, author = {Weiß, Clemens Leonard and Schultz, J{\"o}rg}, title = {Identification of divergent WH2 motifs by HMM-HMM alignments}, series = {BMC Research Notes}, volume = {8}, journal = {BMC Research Notes}, number = {18}, doi = {10.1186/s13104-015-0981-7}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-126413}, year = {2015}, abstract = {Background The actin cytoskeleton is a hallmark of eukaryotic cells. Its regulation as well as its interaction with other proteins is carefully orchestrated by actin interaction domains. One of the key players is the WH2 motif, which enables binding to actin monomers and filaments and is involved in the regulation of actin nucleation. Contrasting conserved domains, the identification of this motif in protein sequences is challenging, as it is short and poorly conserved. Findings To identify divergent members, we combined Hidden-Markov-Model (HMM) to HMM alignments with orthology predictions. Thereby, we identified nearly 500 proteins containing so far not annotated WH2 motifs. This included shootin-1, an actin binding protein involved in neuron polarization. Among others, WH2 motifs of 'proximal to raf' (ptr)-orthologs, which are described in the literature, but not annotated in genome databases, were identified. Conclusion In summary, we increased the number of WH2 motif containing proteins substantially. This identification of candidate regions for actin interaction could steer their experimental characterization. Furthermore, the approach outlined here can easily be adapted to the identification of divergent members of further domain families.}, 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{BuchheimKellerKoetschanetal.2011, author = {Buchheim, Mark A. and Keller, Alexander and Koetschan, Christian and F{\"o}rster, Frank and Merget, Benjamin and Wolf, Matthias}, title = {Internal Transcribed Spacer 2 (nu ITS2 rRNA) Sequence-Structure Phylogenetics: Towards an Automated Reconstruction of the Green Algal Tree of Life}, series = {PLoS ONE}, volume = {6}, journal = {PLoS ONE}, number = {2}, doi = {10.1371/journal.pone.0016931}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-140866}, pages = {e16931}, year = {2011}, abstract = {Background: Chloroplast-encoded genes (matK and rbcL) have been formally proposed for use in DNA barcoding efforts targeting embryophytes. Extending such a protocol to chlorophytan green algae, though, is fraught with problems including non homology (matK) and heterogeneity that prevents the creation of a universal PCR toolkit (rbcL). Some have advocated the use of the nuclear-encoded, internal transcribed spacer two (ITS2) as an alternative to the traditional chloroplast markers. However, the ITS2 is broadly perceived to be insufficiently conserved or to be confounded by introgression or biparental inheritance patterns, precluding its broad use in phylogenetic reconstruction or as a DNA barcode. A growing body of evidence has shown that simultaneous analysis of nucleotide data with secondary structure information can overcome at least some of the limitations of ITS2. The goal of this investigation was to assess the feasibility of an automated, sequence-structure approach for analysis of IT2 data from a large sampling of phylum Chlorophyta. Methodology/Principal Findings: Sequences and secondary structures from 591 chlorophycean, 741 trebouxiophycean and 938 ulvophycean algae, all obtained from the ITS2 Database, were aligned using a sequence structure-specific scoring matrix. Phylogenetic relationships were reconstructed by Profile Neighbor-Joining coupled with a sequence structure-specific, general time reversible substitution model. Results from analyses of the ITS2 data were robust at multiple nodes and showed considerable congruence with results from published phylogenetic analyses. Conclusions/Significance: Our observations on the power of automated, sequence-structure analyses of ITS2 to reconstruct phylum-level phylogenies of the green algae validate this approach to assessing diversity for large sets of chlorophytan taxa. Moreover, our results indicate that objections to the use of ITS2 for DNA barcoding should be weighed against the utility of an automated, data analysis approach with demonstrated power to reconstruct evolutionary patterns for highly divergent lineages.}, 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} } @article{FathyDarwishAbdelhamidetal.2022, author = {Fathy, Moustafa and Darwish, Mostafa A. and Abdelhamid, Al-Shaimaa M. and Alrashedy, Gehad M. and Othman, Othman Ali and Naseem, Muhammad and Dandekar, Thomas and Othman, Eman M.}, title = {Kinetin ameliorates cisplatin-induced hepatotoxicity and lymphotoxicity via attenuating oxidative damage, cell apoptosis and inflammation in rats}, series = {Biomedicines}, volume = {10}, journal = {Biomedicines}, number = {7}, issn = {2227-9059}, doi = {10.3390/biomedicines10071620}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-281686}, year = {2022}, abstract = {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.}, 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{CaliskanCrouchGiddinsetal.2022, author = {Caliskan, Aylin and Crouch, Samantha A. W. and Giddins, Sara and Dandekar, Thomas and Dangwal, Seema}, title = {Progeria and aging — Omics based comparative analysis}, series = {Biomedicines}, volume = {10}, journal = {Biomedicines}, number = {10}, issn = {2227-9059}, doi = {10.3390/biomedicines10102440}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-289868}, year = {2022}, abstract = {Since ancient times aging has also been regarded as a disease, and humankind has always strived to extend the natural lifespan. Analyzing the genes involved in aging and disease allows for finding important indicators and biological markers for pathologies and possible therapeutic targets. An example of the use of omics technologies is the research regarding aging and the rare and fatal premature aging syndrome progeria (Hutchinson-Gilford progeria syndrome, HGPS). In our study, we focused on the in silico analysis of differentially expressed genes (DEGs) in progeria and aging, using a publicly available RNA-Seq dataset (GEO dataset GSE113957) and a variety of bioinformatics tools. Despite the GSE113957 RNA-Seq dataset being well-known and frequently analyzed, the RNA-Seq data shared by Fleischer et al. is far from exhausted and reusing and repurposing the data still reveals new insights. By analyzing the literature citing the use of the dataset and subsequently conducting a comparative analysis comparing the RNA-Seq data analyses of different subsets of the dataset (healthy children, nonagenarians and progeria patients), we identified several genes involved in both natural aging and progeria (KRT8, KRT18, ACKR4, CCL2, UCP2, ADAMTS15, ACTN4P1, WNT16, IGFBP2). Further analyzing these genes and the pathways involved indicated their possible roles in aging, suggesting the need for further in vitro and in vivo research. In this paper, we (1) compare "normal aging" (nonagenarians vs. healthy children) and progeria (HGPS patients vs. healthy children), (2) enlist genes possibly involved in both the natural aging process and progeria, including the first mention of IGFBP2 in progeria, (3) predict miRNAs and interactomes for WNT16 (hsa-mir-181a-5p), UCP2 (hsa-mir-26a-5p and hsa-mir-124-3p), and IGFBP2 (hsa-mir-124-3p, hsa-mir-126-3p, and hsa-mir-27b-3p), (4) demonstrate the compatibility of well-established R packages for RNA-Seq analysis for researchers interested but not yet familiar with this kind of analysis, and (5) present comparative proteomics analyses to show an association between our RNA-Seq data analyses and corresponding changes in protein expression.}, language = {en} } @article{SinghKingstonGuptaetal.2015, author = {Singh, Amit K. and Kingston, Joseph J. and Gupta, Shishir K. and Batra, Harsh V.}, title = {Recombinant Bivalent Fusion Protein rVE Induces CD4+ and CD8+ T-Cell Mediated Memory Immune Response for Protection Against Yersinia enterocolitica Infection}, series = {Frontiers in Microbiology}, volume = {6}, journal = {Frontiers in Microbiology}, number = {1407}, doi = {10.3389/fmicb.2015.01407}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-136114}, year = {2015}, abstract = {Studies investigating the correlates of immune protection against Yersinia infection have established that both humoral and cell mediated immune responses are required for the comprehensive protection. In our previous study, we established that the bivalent fusion protein (rVE) comprising immunologically active regions of Y pestis LcrV (100-270 aa) and YopE (50-213 aa) proteins conferred complete passive and active protection against lethal Y enterocolitica 8081 challenge. In the present study, cohort of BALB/c mice immunized with rVE or its component proteins rV, rE were assessed for cell mediated immune responses and memory immune protection against Y enterocolitica 8081 rVE immunization resulted in extensive proliferation of both CD4 and CD8 T cell subsets; significantly high antibody titer with balanced IgG1: IgG2a/IgG2b isotypes (1:1 ratio) and up regulation of both Th1 (INF-\(\alpha\), IFN-\(\gamma\), IL 2, and IL 12) and Th2 (IL 4) cytokines. On the other hand, rV immunization resulted in Th2 biased IgG response (11:1 ratio) and proliferation of CD4+ T-cell; rE group of mice exhibited considerably lower serum antibody titer with predominant Th1 response (1:3 ratio) and CD8+ T-cell proliferation. Comprehensive protection with superior survival (100\%) was observed among rVE immunized mice when compared to the significantly lower survival rates among rE (37.5\%) and rV (25\%) groups when IP challenged with Y enterocolitica 8081 after 120 days of immunization. Findings in this and our earlier studies define the bivalent fusion protein rVE as a potent candidate vaccine molecule with the capability to concurrently stimulate humoral and cell mediated immune responses and a proof of concept for developing efficient subunit vaccines against Gram negative facultative intracellular bacterial pathogens.}, language = {en} } @article{ReinhardHelmerichBorasetal.2022, author = {Reinhard, Sebastian and Helmerich, Dominic A. and Boras, Dominik and Sauer, Markus and Kollmannsberger, Philip}, title = {ReCSAI: recursive compressed sensing artificial intelligence for confocal lifetime localization microscopy}, series = {BMC Bioinformatics}, volume = {23}, journal = {BMC Bioinformatics}, number = {1}, doi = {10.1186/s12859-022-05071-5}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-299768}, year = {2022}, abstract = {Background Localization-based super-resolution microscopy resolves macromolecular structures down to a few nanometers by computationally reconstructing fluorescent emitter coordinates from diffraction-limited spots. The most commonly used algorithms are based on fitting parametric models of the point spread function (PSF) to a measured photon distribution. These algorithms make assumptions about the symmetry of the PSF and thus, do not work well with irregular, non-linear PSFs that occur for example in confocal lifetime imaging, where a laser is scanned across the sample. An alternative method for reconstructing sparse emitter sets from noisy, diffraction-limited images is compressed sensing, but due to its high computational cost it has not yet been widely adopted. Deep neural network fitters have recently emerged as a new competitive method for localization microscopy. They can learn to fit arbitrary PSFs, but require extensive simulated training data and do not generalize well. A method to efficiently fit the irregular PSFs from confocal lifetime localization microscopy combining the advantages of deep learning and compressed sensing would greatly improve the acquisition speed and throughput of this method. Results Here we introduce ReCSAI, a compressed sensing neural network to reconstruct localizations for confocal dSTORM, together with a simulation tool to generate training data. We implemented and compared different artificial network architectures, aiming to combine the advantages of compressed sensing and deep learning. We found that a U-Net with a recursive structure inspired by iterative compressed sensing showed the best results on realistic simulated datasets with noise, as well as on real experimentally measured confocal lifetime scanning data. Adding a trainable wavelet denoising layer as prior step further improved the reconstruction quality. Conclusions Our deep learning approach can reach a similar reconstruction accuracy for confocal dSTORM as frame binning with traditional fitting without requiring the acquisition of multiple frames. In addition, our work offers generic insights on the reconstruction of sparse measurements from noisy experimental data by combining compressed sensing and deep learning. We provide the trained networks, the code for network training and inference as well as the simulation tool as python code and Jupyter notebooks for easy reproducibility.}, language = {en} }