Surface-Patterned DNA Origami Rulers Reveal Nanoscale Distance Dependency of the Epidermal Growth Factor Receptor Activation.

The nanoscale arrangement of ligands can have a major effect on the activation of membrane receptor proteins and thus cellular communication mechanisms. Here we report on the technological development and use of tailored DNA origami-based molecular rulers to fabricate "Multiscale Origami Structures As Interface for Cells" (MOSAIC), to enable the systematic investigation of the effect of the nanoscale spacing of epidermal growth factor (EGF) ligands on the activation of the EGF receptor (EGFR). MOSAIC-based analyses revealed that EGF distances of about 30-40 nm led to the highest response in EGFR activation of adherent MCF7 and Hela cells. Our study emphasizes the significance of DNA-based platforms for the detailed investigation of the molecular mechanisms of cellular signaling cascades.

Normics: Proteomic Normalization by Variance and Data-Inherent Correlation Structure.

Several algorithms for the normalization of proteomic data are currently available, each based on a priori assumptions. Among these is the extent to which differential expression (DE) can be present in the dataset. This factor is usually unknown in explorative biomarker screens. Simultaneously, the increasing depth of proteomic analyses often requires the selection of subsets with a high probability of being DE to obtain meaningful results in downstream bioinformatical analyses. Based on the relationship of technical variation and (true) biological DE of an unknown share of proteins, we propose the "Normics" algorithm: Proteins are ranked based on their expression level-corrected variance and the mean correlation with all other proteins. The latter serves as a novel indicator of the non-DE likelihood of a protein in a given dataset. Subsequent normalization is based on a subset of non-DE proteins only. No a priori information such as batch, clinical, or replicate group is necessary. Simulation data demonstrated robust and superior performance across a wide range of stochastically chosen parameters. Five publicly available spike-in and biologically variant datasets were reliably and quantitively accurately normalized by Normics with improved performance compared to standard variance stabilization as well as median, quantile, and LOESS normalizations. In complex biological datasets Normics correctly determined proteins as being DE that had been cross-validated by an independent transcriptome analysis of the same samples. In both complex datasets Normics identified the most DE proteins. We demonstrate that combining variance analysis and data-inherent correlation structure to identify non-DE proteins improves data normalization. Standard normalization algorithms can be consolidated against high shares of (one-sided) biological regulation. The statistical power of downstream analyses can be increased by focusing on Normics-selected subsets of high DE likelihood.

The HMG box transcription factors Sox1a and Sox1b specify a new class of glycinergic interneuron in the spinal cord of zebrafish embryos.

Specification of neurons in the spinal cord relies on extrinsic and intrinsic signals, which in turn are interpreted by expression of transcription factors. V2 interneurons develop from the ventral aspects of the spinal cord. We report here a novel neuronal V2 subtype, named V2s, in zebrafish embryos. Formation of these neurons depends on the transcription factors sox1a and sox1b. They develop from common gata2a- and gata3-dependent precursors co-expressing markers of V2b and V2s interneurons. Chemical blockage of Notch signalling causes a decrease in V2s and an increase in V2b cells. Our results are consistent with the existence of at least two types of precursor arranged in a hierarchical manner in the V2 domain. V2s neurons grow long ipsilateral descending axonal projections with a short branch at the ventral midline. They acquire a glycinergic neurotransmitter type during the second day of development. Unilateral ablation of V2s interneurons causes a delay in touch-provoked escape behaviour, suggesting that V2s interneurons are involved in fast motor responses.

[Pilot study examining a profession-oriented rehabilitation concept for nursing professions]. / Pilotstudie zur Evaluation einer medizinisch-beruflich orientierten Rehabilitation für Pflegekräfte.

Pilot study examining a profession-oriented rehabilitation concept for nursing professions Objectives: Nursing professions are associated with high levels of psychological distress, high numbers of absent days and premature retirement. To achieve higher return-to-work rates, psychosomatic rehabilitation is expected to offer treatments tailored to workplace demands. This pilot study is the first to examine the effects of a new workplace-oriented medical rehabilitation program for nursing professions. Methods: A total of N = 145 depressed patients in nursing occupations (86.9 % female; 50.9 ± 7.34 years) took part in a workplace-oriented rehabilitation program for nursing professions. At admission they were compared to N = 147 depressed patients (63.27 % female; 49.36 ± 7.58 years) in non-nursing professions regarding patterns of work-related experience and behaviour (AVEM) using a MANOVA with follow-up ANOVAs for individual subscales. Changes in work-related attitudes among the nursing professions following completion of the intervention were assessed using a MANOVA followed by repeated measures ANOVAs. The effect of the workplace- oriented intervention on depressiveness (BDI-II) was compared to a treatment program for depression using a mixed model after taking potentially confounding variables into account. Results: At entry, depressed patients in nursing professions scored significantly higher on AVEM scale willingness to work to exhaustion and lower on AVEM scale distancing ability compared to depressed patients in other professions. Following completion of the workplace-oriented intervention program for nursing professions, participants showed a significant reduction on AVEM scales subjective importance of work, willingness to work to exhaustion, and striving for perfection. Increasing scores were observed on the distancing ability and life satisfaction scales. Depression scores had significantly improved at discharge in both participants of the work-oriented intervention and the disorder-specific intervention for depressive disorders, whereas neither group differences nor interaction effects were found. Conclusions: The work-oriented intervention for nursing professions successfully induced changes in maladaptive work-related attitudes. Improvements in depressiveness did not significantly differ from an intervention targeting depression specifically.

BeadNet: deep learning-based bead detection and counting in low-resolution microscopy images.

MOTIVATION: An automated counting of beads is required for many high-throughput experiments such as studying mimicked bacterial invasion processes. However, state-of-the-art algorithms under- or overestimate the number of beads in low-resolution images. In addition, expert knowledge is needed to adjust parameters. RESULTS: In combination with our image labeling tool, BeadNet enables biologists to easily annotate and process their data reducing the expertise required in many existing image analysis pipelines. BeadNet outperforms state-of-the-art-algorithms in terms of missing, added and total amount of beads. AVAILABILITY AND IMPLEMENTATION: BeadNet (software, code and dataset) is available at https://bitbucket.org/t_scherr/beadnet. The image labeling tool is available at https://bitbucket.org/abartschat/imagelabelingtool. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Motion prediction enables simulated MR-imaging of freely moving model organisms.

Magnetic resonance tomography typically applies the Fourier transform to k-space signals repeatedly acquired from a frequency encoded spatial region of interest, therefore requiring a stationary object during scanning. Any movement of the object results in phase errors in the recorded signal, leading to deformed images, phantoms, and artifacts, since the encoded information does not originate from the intended region of the object. However, if the type and magnitude of movement is known instantaneously, the scanner or the reconstruction algorithm could be adjusted to compensate for the movement, directly allowing high quality imaging with non-stationary objects. This would be an enormous boon to studies that tie cell metabolomics to spontaneous organism behaviour, eliminating the stress otherwise necessitated by restraining measures such as anesthesia or clamping. In the present theoretical study, we use a phantom of the animal model C. elegans to examine the feasibility to automatically predict its movement and position, and to evaluate the impact of movement prediction, within a sufficiently long time horizon, on image reconstruction. For this purpose, we use automated image processing to annotate body parts in freely moving C. elegans, and predict their path of movement. We further introduce an MRI simulation platform based on bright field videos of the moving worm, combined with a stack of high resolution transmission electron microscope (TEM) slice images as virtual high resolution phantoms. A phantom provides an indication of the spatial distribution of signal-generating nuclei on a particular imaging slice. We show that adjustment of the scanning to the predicted movements strongly reduces distortions in the resulting image, opening the door for implementation in a high-resolution NMR scanner.

Sympathetic innervation controls homeostasis of neuromuscular junctions in health and disease.

The distribution and function of sympathetic innervation in skeletal muscle have largely remained elusive. Here we demonstrate that sympathetic neurons make close contact with neuromuscular junctions and form a network in skeletal muscle that may functionally couple different targets including blood vessels, motor neurons, and muscle fibers. Direct stimulation of sympathetic neurons led to activation of muscle postsynaptic ß2-adrenoreceptor (ADRB2), cAMP production, and import of the transcriptional coactivator peroxisome proliferator-activated receptor γ-coactivator 1α (PPARGC1A) into myonuclei. Electrophysiological and morphological deficits of neuromuscular junctions upon sympathectomy and in myasthenic mice were rescued by sympathicomimetic treatment. In conclusion, this study identifies the neuromuscular junction as a target of the sympathetic nervous system and shows that sympathetic input is crucial for synapse maintenance and function.

[Digital Image Processing and Deep Neural Networks in Ophthalmology - Current Trends]. / Digitale Bildverarbeitung und Tiefe Neuronale Netze in der Augenheilkunde ­ aktuelle Trends.

The use of deep neural networks ("deep learning") creates new possibilities in digital image processing. This approach has been widely applied and successfully used for the evaluation of image data in ophthalmology. In this article, the methodological approach of deep learning is examined and compared to the classical approach for digital image processing. The differences between the approaches are discussed and the increasingly important role of training data for model generation is explained. Furthermore, the approach of transfer learning for deep learning is presented with a representative data set from the field of corneal confocal microscopy. In this context, the advantages of the method and the specific problems when dealing with medical microscope data will be discussed.

Improving short antimicrobial peptides despite elusive rules for activity.

Antimicrobial peptides (AMPs) can effectively kill a broad range of life threatening multidrug-resistant bacteria, a serious threat to public health worldwide. However, despite great hopes novel drugs based on AMPs are still rare. To accelerate drug development we studied different approaches to improve the antibacterial activity of short antimicrobial peptides. Short antimicrobial peptides seem to be ideal drug candidates since they can be synthesized quickly and easily, modified and optimized. In addition, manufacturing a short peptide drug will be more cost efficient than long and structured ones. In contrast to longer and structured peptides short AMPs seem hard to design and predict. Here, we designed, synthesized and screened five different peptide libraries, each consisting of 600 9-mer peptides, against Pseudomonas aeruginosa. Each library is presenting a different approach to investigate effectiveness of an optimization strategy. The data for the 3000 peptides were analyzed using models based on fuzzy logic bioinformatics and plausible descriptors. The rate of active or superior active peptides was improved from 31.0% in a semi-random library from a previous study to 97.8% in the best new designed library. This article is part of a Special Issue entitled: Antimicrobial peptides edited by Karl Lohner and Kai Hilpert.

XPIWIT--an XML pipeline wrapper for the Insight Toolkit.

UNLABELLED: The Insight Toolkit offers plenty of features for multidimensional image analysis. Current implementations, however, often suffer either from a lack of flexibility due to hard-coded C++ pipelines for a certain task or by slow execution times, e.g. caused by inefficient implementations or multiple read/write operations for separate filter execution. We present an XML-based wrapper application for the Insight Toolkit that combines the performance of a pure C++ implementation with an easy-to-use graphical setup of dynamic image analysis pipelines. Created XML pipelines can be interpreted and executed by XPIWIT in console mode either locally or on large clusters. We successfully applied the software tool for the automated analysis of terabyte-scale, time-resolved 3D image data of zebrafish embryos. AVAILABILITY AND IMPLEMENTATION: XPIWIT is implemented in C++ using the Insight Toolkit and the Qt SDK. It has been successfully compiled and tested under Windows and Unix-based systems. Software and documentation are distributed under Apache 2.0 license and are publicly available for download at https://bitbucket.org/jstegmaier/xpiwit/downloads/. CONTACT: johannes.stegmaier@kit.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Clinical and molecular implications of MED15 in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) progression depends on various dysregulated pathways. Regulation of diverse pathways is mediated by the mediator complex. The mediator subunit MED15 is essential for transforming growth factor (TGF)-ß signaling and involved in breast and prostate cancers. We investigated the implication of MED15 in HNSCC. IHC for MED15 was performed on 324 tissue samples, and TGF-ß assessed the use of Ki-67 and pSMAD3 as markers. MED15 knockdown followed by proliferation and migration assays, as well as TGF-ß1 treatment followed by MED15 analysis, was also performed. MED15 was overexpressed in 35% of primary tumors, 30% of lymph node metastases, and 70% of recurrences in contrast to no or low expression in benign tumors. MED15 overexpression in primary tumors from patients who developed recurrences was associated with higher mortality rates and occurred at highest frequency in oral cavity or oropharyngeal tumors. Furthermore, MED15 expression correlated between primary tumors and corresponding lymph node metastases. MED15 correlated with proliferation in tissues, and MED15 knockdown reduced proliferation and migration. We observed an association between MED15 and TGF-ß activity in tissues because TGF-ß activation led to increased MED15 expression and reduced pSMAD3 on MED15 knockdown. Taken together, our results implicate MED15 in HNSCC and hint that MED15 overexpression is a clonal event during HNSCC progression. MED15 may serve as a prognostic marker for recurrence and as a therapeutic target.

Automated prior knowledge-based quantification of neuronal patterns in the spinal cord of zebrafish.

MOTIVATION: To reliably assess the effects of unknown chemicals on the development of fluorescently labeled sensory-, moto- and interneuron populations in the spinal cord of zebrafish, automated data analysis is essential. RESULTS: For the evaluation of a high-throughput screen of a large chemical library, we developed a new method for the automated extraction of quantitative information from green fluorescent protein (eGFP) and red fluorescent protein (RFP) labeled spinal cord neurons in double-transgenic zebrafish embryos. The methodology comprises region of interest detection, intensity profiling with reference comparison and neuron distribution histograms. All methods were validated on a manually evaluated pilot study using a Notch inhibitor dose-response experiment. The automated evaluation showed superior performance to manual investigation regarding time consumption, information detail and reproducibility. AVAILABILITY AND IMPLEMENTATION: Being part of GNU General Public Licence (GNU-GPL) licensed open-source MATLAB toolbox Gait-CAD, an implementation of the presented methods is publicly available for download at http://sourceforge.net/projects/zebrafishimage/.

Genome-wide, whole mount in situ analysis of transcriptional regulators in zebrafish embryos.

Transcription is the primary step in the retrieval of genetic information. A substantial proportion of the protein repertoire of each organism consists of transcriptional regulators (TRs). It is believed that the differential expression and combinatorial action of these TRs is essential for vertebrate development and body homeostasis. We mined the zebrafish genome exhaustively for genes encoding TRs and determined their expression in the zebrafish embryo by sequencing to saturation and in situ hybridisation. At the evolutionary conserved phylotypic stage, 75% of the 3302 TR genes encoded in the genome are already expressed. The number of expressed TR genes increases only marginally in subsequent stages and is maintained during adulthood suggesting important roles of the TR genes in body homeostasis. Fewer than half of the TR genes (45%, n=1711 genes) are expressed in a tissue-restricted manner in the embryo. Transcripts of 207 genes were detected in a single tissue in the 24h embryo, potentially acting as regulators of specific processes. Other TR genes were expressed in multiple tissues. However, with the exception of certain territories in the nervous system, we did not find significant synexpression suggesting that most tissue-restricted TRs act in a freely combinatorial fashion. Our data indicate that elaboration of body pattern and function from the phylotypic stage onward relies mostly on redeployment of TRs and post-transcriptional processes.

Rapsyn mediates subsynaptic anchoring of PKA type I and stabilisation of acetylcholine receptor in vivo.

The stabilisation of acetylcholine receptors (AChRs) at the neuromuscular junction depends on muscle activity and the cooperative action of myosin Va and protein kinase A (PKA) type I. To execute its function, PKA has to be present in a subsynaptic microdomain where it is enriched by anchoring proteins. Here, we show that the AChR-associated protein, rapsyn, interacts with PKA type I in C2C12 and T-REx293 cells as well as in live mouse muscle beneath the neuromuscular junction. Molecular modelling, immunoprecipitation and bimolecular fluorescence complementation approaches identify an α-helical stretch of rapsyn to be crucial for binding to the dimerisation and docking domain of PKA type I. When expressed in live mouse muscle, a peptide encompassing the rapsyn α-helical sequence efficiently delocalises PKA type I from the neuromuscular junction. The same peptide, as well as a rapsyn construct lacking the α-helical domain, induces severe alteration of acetylcholine receptor turnover as well as fragmentation of synapses. This shows that rapsyn anchors PKA type I in close proximity to the postsynaptic membrane and suggests that this function is essential for synapse maintenance.

Image-based recognition of parasitoid wasps using advanced neural networks.

Hymenoptera has some of the highest diversity and number of individuals among insects. Many of these species potentially play key roles as food sources, pest controllers and pollinators. However, little is known about the diversity and biology and ~80% of the species have not yet been described. Classical taxonomy based on morphology is a rather slow process but DNA barcoding has already brought considerable progress in identification. Innovative methods such as image-based identification and automation can further speed up the process. We present a proof of concept for image data recognition of a parasitic wasp family, the Diapriidae (Hymenoptera), obtained as part of the GBOL III project. These tiny (1.2-4.5mm) wasps were photographed and identified using DNA barcoding to provide a solid ground truth for training a neural network. Taxonomic identification was used down to the genus level. Subsequently, three different neural network architectures were trained, evaluated and optimised. As a result, 11 different genera of diaprids and one mixed group of 'other Hymenoptera' can be classified with an average accuracy of 96%. Additionally, the sex of the specimen can be classified automatically with an accuracy of >97%.

TRIM11 expression in non-small cell lung cancer is associated with poor prognosis.

BACKGROUND: Despite promising results of targeted therapy approaches, non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related death. Tripartite motif containing 11 (TRIM11) is part of the TRIM family of proteins, playing crucial roles in tumor progression. TRIM11 serves as an oncogene in various cancer types and has been reported to be associated with a poor prognosis. In this study, we aimed to investigate the protein expression of TRIM11 in a large NSCLC cohort and to correlate its expression with comprehensive clinico-pathological data. METHODS: Immunohistochemical staining of TRIM11 was performed on a European cohort of NSCLC patients (n=275) including 224 adenocarcinomas and 51 squamous cell carcinomas. Protein expression was categorized according to staining intensity as absent, low, moderate and high. To dichotomize samples, absent and low expression was defined as weak and moderate and high expression was defined as high. Results were correlated with clinico-pathological data. RESULTS: TRIM11 was significantly more highly expressed in NSCLC than in normal lung tissue and significantly more highly expressed in squamous cell carcinomas than in adenocarcinomas. We found a significantly worse 5-year overall survival for patients who highly expressed TRIM11 in NSCLC. CONCLUSIONS: High TRIM11 expression is linked with a poor prognosis and might serve as a promising novel prognostic biomarker for NSCLC. Its assessment could be implemented in future routine diagnostic workup.

Using the High-Entropy Approach to Obtain Multimetal Oxide Nanozymes: Library Synthesis, In Silico Structure-Activity, and Immunoassay Performance.

High-entropy nanomaterials exhibit exceptional mechanical, physical, and chemical properties, finding applications in many industries. Peroxidases are metalloenzymes that accelerate the decomposition of hydrogen peroxide. This study uses the high-entropy approach to generate multimetal oxide-based nanozymes with peroxidase-like activity and explores their application as sensors in ex vivo bioassays. A library of 81 materials was produced using a coprecipitation method for rapid synthesis of up to 100 variants in a single plate. The A and B sites of the magnetite structure, (AA')(BB'B'')2O4, were substituted with up to six different cations (Cu/Fe/Zn/Mg/Mn/Cr). Increasing the compositional complexity improved the catalytic performance; however, substitutions of single elements also caused drastic reductions in the peroxidase-like activity. A generalized linear model was developed describing the relationship between material composition and catalytic activity. Binary interactions between elements that acted synergistically or antagonistically were identified, and a single parameter, the mean interaction effect, was observed to correlate highly with catalytic activity, providing a valuable tool for the design of high-entropy-inspired nanozymes.

Targeting Mycobacterium tuberculosis and other microbial pathogens using improved synthetic antibacterial peptides.

The lack of effective therapies for treating tuberculosis (TB) is a global health problem. While Mycobacterium tuberculosis is notoriously resistant to most available antibiotics, we identified synthetic short cationic antimicrobial peptides that were active at low micromolar concentrations (less than 10 µM). These small peptides (averaging 10 amino acids) had remarkably broad spectra of antimicrobial activities against both bacterial and fungal pathogens and an indication of low cytotoxicity. In addition, their antimicrobial activities displayed various degrees of species specificity that were not related to taxonomy. For example, Candida albicans and Staphylococcus aureus were the best surrogates to predict peptide activity against M. tuberculosis, while Mycobacterium smegmatis was a poor surrogate. Principle component analysis of activity spectrum profiles identified unique features associated with activity against M. tuberculosis that reflect their distinctive amino acid composition; active peptides were more hydrophobic and cationic, reflecting increased tryptophan with compensating decreases in valine and other uncharged amino acids and increased lysine. These studies provide foundations for development of cationic antimicrobial peptides as potential new therapeutic agents for TB treatment.

Myosin Va cooperates with PKA RIalpha to mediate maintenance of the endplate in vivo.

Myosin V motor proteins facilitate recycling of synaptic receptors, including AMPA and acetylcholine receptors, in central and peripheral synapses, respectively. To shed light on the regulation of receptor recycling, we employed in vivo imaging of mouse neuromuscular synapses. We found that myosin Va cooperates with PKA on the postsynapse to maintain size and integrity of the synapse; this cooperation also regulated the lifetime of acetylcholine receptors. Myosin Va and PKA colocalized in subsynaptic enrichments. These accumulations were crucial for synaptic integrity and proper cAMP signaling, and were dependent on AKAP function, myosin Va, and an intact actin cytoskeleton. The neuropeptide and cAMP agonist, calcitonin-gene related peptide, rescued fragmentation of synapses upon denervation. We hypothesize that neuronal ligands trigger local activation of PKA, which in turn controls synaptic integrity and turnover of receptors. To this end, myosin Va mediates correct positioning of PKA in a postsynaptic microdomain, presumably by tethering PKA to the actin cytoskeleton.

Self-Supervised Learning for Annotation Efficient Biomedical Image Segmentation.

OBJECTIVE: The scarcity of high-quality annotated data is omnipresent in machine learning. Especially in biomedical segmentation applications, experts need to spend a lot of their time into annotating due to the complexity. Hence, methods to reduce such efforts are desired. METHODS: Self-Supervised Learning (SSL) is an emerging field that increases performance when unannotated data is present. However, profound studies regarding segmentation tasks and small datasets are still absent. A comprehensive qualitative and quantitative evaluation is conducted, examining SSL's applicability with a focus on biomedical imaging. We consider various metrics and introduce multiple novel application-specific measures. All metrics and state-of-the-art methods are provided in a directly applicable software package (https://osf.io/gu2t8/). RESULTS: We show that SSL can lead to performance improvements of up to 10%, which is especially notable for methods designed for segmentation tasks. CONCLUSION: SSL is a sensible approach to data-efficient learning, especially for biomedical applications, where generating annotations requires much effort. Additionally, our extensive evaluation pipeline is vital since there are significant differences between the various approaches. SIGNIFICANCE: We provide biomedical practitioners with an overview of innovative data-efficient solutions and a novel toolbox for their own application of new approaches. Our pipeline for analyzing SSL methods is provided as a ready-to-use software package.