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Schriftenreihe
Sonstige beteiligte Institutionen
- Helmholtz Institute for RNA-based Infection Research (HIRI) (2)
- Interdisziplinäres Zentrum für Klinische Forschung (IZKF) (2)
- Klinische Studienzentrale (Universitätsklinikum) (2)
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg (2)
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- DATE Lab, KITE Research Insititute, University Health Network, Toronto, Canada (1)
The phylogeny of Euglenophyceae (Euglenozoa, Euglenida) has been discussed for decades with new genera being described in the last few years. In this study, we reconstruct a phylogeny using 18S rDNA sequence and structural data simultaneously. Using homology modeling, individual secondary structures were predicted. Sequence–structure data are encoded and automatically aligned. Here, we present a sequence–structure neighbor‐joining tree of more than 300 taxa classified as Euglenophyceae. Profile neighbor‐joining was used to resolve the basal branching pattern. Neighbor‐joining, maximum parsimony, and maximum likelihood analyses were performed using sequence–structure information for manually chosen subsets. All analyses supported the monophyly of Eutreptiella, Discoplastis, Lepocinclis, Strombomonas, Cryptoglena, Monomorphina, Euglenaria, and Colacium. Well‐supported topologies were generally consistent with previous studies using a combined dataset of genetic markers. Our study supports the simultaneous use of sequence and structural data to reconstruct more accurate and robust trees. The average bootstrap value is significantly higher than the average bootstrap value obtained from sequence‐only analyses, which is promising for resolving relationships between more closely related taxa.
Merkel cell carcinoma (MCC) is frequently caused by the Merkel cell polyomavirus (MCPyV), and MCPyV-positive tumor cells depend on expression of the virus-encoded T antigens (TA). Here, we identify 4-[(5-methyl-1H-pyrazol-3-yl)amino]-2H-phenyl-1-phthalazinone (PHT) — a reported inhibitor of Aurora kinase A — as a compound inhibiting growth of MCC cells by repressing noncoding control region (NCCR)-controlled TA transcription. Surprisingly, we find that TA repression is not caused by inhibition of Aurora kinase A. However, we demonstrate that β-catenin — a transcription factor repressed by active glycogen synthase kinase 3 (GSK3) — is activated by PHT, suggesting that PHT bears a hitherto unreported inhibitory activity against GSK3, a kinase known to function in promoting TA transcription. Indeed, applying an in vitro kinase assay, we demonstrate that PHT directly targets GSK3. Finally, we demonstrate that PHT exhibits in vivo antitumor activity in an MCC xenograft mouse model, suggesting a potential use in future therapeutic settings for MCC.
Plexus injury often occurs after motor vehicle accidents and results in lifelong disability with severe neuropathic pain. Surgical treatment can partially restore motor functions, but sensory loss and neuropathic pain persist. Regenerative medicine concepts, such as cell replacement therapies for restoring dorsal root ganglia (DRG) function, set high expectations. However, up to now, it is unclear which DRG cell types are affected by nerve injury and can be targeted in regenerative medicine approaches.
This study followed the hypothesis that satellite glial cells (SGCs) might be a suitable endogenous cell source for regenerative medicine concepts in the DRG. SGCs originate from the same neural crest-derived cell lineage as sensory neurons, making them attractive for neural repair strategies in the peripheral nervous system. Our hypothesis was investigated on three levels of experimentation. First, we asked whether adult SGCs have the potential of sensory neuron precursors and can be reprogrammed into sensory neurons in vitro. We found that adult mouse DRG harbor SGC-like cells that can still dedifferentiate into progenitor-like cells. Surprisingly, expression of the early developmental transcription factors Neurog1 and Neurog2 was sufficient to induce neuronal and glial cell phenotypes. In the presence of nerve growth factor, induced neurons developed a nociceptor-like phenotype expressing functional nociceptor markers, such as the ion channels TrpA1, TrpV1 and NaV1.9. In a second set of experiments, we used a rat model for peripheral nerve injury to look for changes in the DRG cell composition. Using an unbiased deep learning-based approach for cell analysis, we found that cellular plasticity responses after nerve injury activate SGCs in the whole DRG. However, neither injury-induced neuronal death nor gliosis was observed. Finally, we asked whether a severe nerve injury changed the cell composition in the human DRG. For this, a cohort of 13 patients with brachial plexus injury was investigated. Surprisingly, in about half of all patients, the injury-affected DRG showed no characteristic DRG tissue. The complete entity of neurons, satellite cells, and axons was lost and fully replaced by mesodermal/connective tissue. In the other half of the patients, the basic cellular entity of the DRG was well preserved. Objective deep learning-based analysis of large-scale bioimages of the “intact” DRG showed no loss of neurons and no signs of gliosis.
This study suggests that concepts for regenerative medicine for restoring DRG function need at least two translational research directions: reafferentation of existing DRG units or full replacement of the entire multicellular DRG structure. For DRG replacement, SGCs of the adult DRG are an attractive endogenous cell source, as the multicellular DRG units could possibly be rebuilt by transdifferentiating neural crest-derived sensory progenitor cells into peripheral sensory neurons and glial cells using Neurog1 and Neurog2.
The signals that coordinate and control movement in vertebrates are transmitted from motoneurons (MNs) to their target muscle cells at neuromuscular junctions (NMJs). Human NMJs display unique structural and physiological features, which make them vulnerable to pathological processes. NMJs are an early target in the pathology of motoneuron diseases (MND). Synaptic dysfunction and synapse elimination precede MN loss suggesting that the NMJ is the starting point of the pathophysiological cascade leading to MN death. Therefore, the study of human MNs in health and disease requires cell culture systems that enable the connection to their target muscle cells for NMJ formation. Here, we present a human neuromuscular co-culture system consisting of induced pluripotent stem cell (iPSC)-derived MNs and 3D skeletal muscle tissue derived from myoblasts. We used self-microfabricated silicone dishes combined with Velcro hooks to support the formation of 3D muscle tissue in a defined extracellular matrix, which enhances NMJ function and maturity. Using a combination of immunohistochemistry, calcium imaging, and pharmacological stimulations, we characterized and confirmed the function of the 3D muscle tissue and the 3D neuromuscular co-cultures. Finally, we applied this system as an in vitro model to study the pathophysiology of Amyotrophic Lateral Sclerosis (ALS) and found a decrease in neuromuscular coupling and muscle contraction in co-cultures with MNs harboring ALS-linked SOD1 mutation. In summary, the human 3D neuromuscular cell culture system presented here recapitulates aspects of human physiology in a controlled in vitro setting and is suitable for modeling of MND.
A circum-Arctic monitoring framework for quantifying annual erosion rates of permafrost coasts
(2023)
This study demonstrates a circum-Arctic monitoring framework for quantifying annual change of permafrost-affected coasts at a spatial resolution of 10 m. Frequent cloud coverage and challenging lighting conditions, including polar night, limit the usability of optical data in Arctic regions. For this reason, Synthetic Aperture RADAR (SAR) data in the form of annual median and standard deviation (sd) Sentinel-1 (S1) backscatter images covering the months June–September for the years 2017–2021 were computed. Annual composites for the year 2020 were hereby utilized as input for the generation of a high-quality coastline product via a Deep Learning (DL) workflow, covering 161,600 km of the Arctic coastline. The previously computed annual S1 composites for the years 2017 and 2021 were employed as input data for the Change Vector Analysis (CVA)-based coastal change investigation. The generated DL coastline product served hereby as a reference. Maximum erosion rates of up to 67 m per year could be observed based on 400 m coastline segments. Overall highest average annual erosion can be reported for the United States (Alaska) with 0.75 m per year, followed by Russia with 0.62 m per year. Out of all seas covered in this study, the Beaufort Sea featured the overall strongest average annual coastal erosion of 1.12 m. Several quality layers are provided for both the DL coastline product and the CVA-based coastal change analysis to assess the applicability and accuracy of the output products. The predicted coastal change rates show good agreement with findings published in previous literature. The proposed methods and data may act as a valuable tool for future analysis of permafrost loss and carbon emissions in Arctic coastal environments.
A closer look at long-established drugs: enantioselective protein binding and stability studies
(2023)
The aim of this work was to investigate older, established drugs. The extent of the protein binding of chiral ephedra alkaloids to AGP and of ketamine to albumin was determined. Since enantiomers of these drugs are individual available, the focus was on possible enantioselective binding and structural moieties involved in the binding.
Previously published work suggested that ephedrine and pseudoephedrine can bind stereoselectively to proteins other than albumin in serum. For the determination of the extent of protein binding, the established ultrafiltration with subsequent chiral CE analysis was used. To determine the influence of basicity on binding, the drugs methylephedrine and norephedrine were also analyzed. Drug binding to AGP increased with increasing basicity as follows: norephedrine < methylephedrine < ephedrine < pseudoephedrine. pKaff was determined both graphically using the Klotz plot and mathematical indicating a low affinity of the ephedra alkaloids to AGP. Using STD-NMR spectroscopy experiments the aromatic protons and the C-CH3 side chain were shown to be most strongly involved in binding, which could be confirmed by molecular docking experiments in more detail. For all drugs, van der Waals-, π π , cationic interactions, hydrogen bonds, and a formation of a salt bridge were observed. The individual enantiomers showed no significant differences and thus the binding of ephedra alkaloids to AGP is not significant.
In contrast to the ephedra alkaloids, the possible enantioselective binding to albumin was investigated for R and S ketamine. Again, ultrafiltration followed by CE analysis was performed. The binding of ketamine to one main binding site could be identified. A non-linear fit was used for the determination of pKaff. Using the NMR methods STD-NMR, waterLOGSY-NMR, and CPMG-NMRspectroscopy: the aromatic protons as well as the protons of the NCH3 methyl group showed the largest signal intensity changes, while the cyclohexanone protons showed the smallest changes. pKaff was also determined by the change in the chemical shift at different drug-protein ratios. These obtained values confirm the values obtained from ultrafiltration. Based on this, ketamine is classified as a low-affinity ligand to albumin. There were no significant differences between the individual enantiomers and thus the binding of ketamine to albumin is not a stereoselective process.
Using statistical design of experiments an efficient chiral CE method for determining the extent of protein binding of R and S ketamine to albumin was developed and validated according to ICH Q2 (R1) guideline.
The stability of ketamine was also investigated because a yellowish discoloration of an aqueous solution of ketamine developed under heat. XRPD investigations showed the same crystal structure for all batches examined. An untargeted screening using LC HRMS as well as LC UV measurements showed no degradation of ketamine or the presence of impurities in stress and non-stressed ketamine solutions, confirming the stability of ketamine under the stress conditions investigated. The lower the quality of the water used in the stress tests, the more intense the yellow discoloration occurred. The impurity or the mechanism that causes the yellow discoloration could not be identified.
The increasing loss of pollinators over the last decades has become more and more evident. Intensive use of plant protection products is one key factor contributing to this decline. Especially the mixture of different plant protection products can pose an increased risk for pollinators as synergistic effects may occur. In this study we investigated the effect of the fungicide Cantus® Gold (boscalid/dimoxystrobin), the neonicotinoid insecticide Mospilan® (acetamiprid) and their mixture on honeybees. Since both plant protection products are frequently applied sequentially to the same plants (e.g. oilseed rape), their combination is a realistic scenario for honeybees. We investigated the mortality, the sucrose responsiveness and the differential olfactory learning performance of honeybees under controlled conditions in the laboratory to reduce environmental noise. Intact sucrose responsiveness and learning performance are of pivotal importance for the survival of individual honeybees as well as for the functioning of the entire colony. Treatment with two sublethal and field relevant concentrations of each plant protection product did not lead to any significant effects on these behaviors but affected the mortality rate. However, our study cannot exclude possible negative sublethal effects of these substances in higher concentrations. In addition, the honeybee seems to be quite robust when it comes to effects of plant protection products, while wild bees might be more sensitive.
Highlights
• Mix of SBI fungicides and neonicotinoids can lead to synergistic effects for bees.
• Combination of non-SBI fungicide and neonicotinoid in field-realistic doses tested.
• Synergistic effect on mortality of honeybees.
• No effects on sucrose responsiveness and learning performance of honeybees.
• Synergistic effects by other pesticide mixtures or on wild bees cannot be excluded.
The steadily increasing usage of smart meters generates a valuable amount of high-resolution data about the individual energy consumption and production of local energy systems. Private households install more and more photovoltaic systems, battery storage and big consumers like heat pumps. Thus, our vision is to augment these collected smart meter time series of a complete system (e.g., a city, town or complex institutions like airports) with simulatively added previously named components. We, therefore, propose a novel digital twin of such an energy system based solely on a complete set of smart meter data including additional building data. Based on the additional geospatial data, the twin is intended to represent the addition of the abovementioned components as realistically as possible. Outputs of the twin can be used as a decision support for either system operators where to strengthen the system or for individual households where and how to install photovoltaic systems and batteries. Meanwhile, the first local energy system operators had such smart meter data of almost all residential consumers for several years. We acquire those of an exemplary operator and discuss a case study presenting some features of our digital twin and highlighting the value of the combination of smart meter and geospatial data.
Butyrophilin (BTN)–3A and BTN2A1 molecules control the activation of human Vγ9Vδ2 T cells during T cell receptor (TCR)-mediated sensing of phosphoantigens (PAg) derived from microbes and tumors. However, the molecular rules governing PAg sensing remain largely unknown. Here, we establish three mechanistic principles of PAg-mediated γδ T cell activation. First, in humans, following PAg binding to the intracellular BTN3A1-B30.2 domain, Vγ9Vδ2 TCR triggering involves the extracellular V-domain of BTN3A2/BTN3A3. Moreover, the localization of both protein domains on different chains of the BTN3A homo-or heteromers is essential for efficient PAg-mediated activation. Second, the formation of BTN3A homo-or heteromers, which differ in intracellular trafficking and conformation, is controlled by molecular interactions between the juxtamembrane regions of the BTN3A chains. Finally, the ability of PAg not simply to bind BTN3A-B30.2, but to promote its subsequent interaction with the BTN2A1-B30.2 domain, is essential for T-cell activation. Defining these determinants of cooperation and the division of labor in BTN proteins improves our understanding of PAg sensing and elucidates a mode of action that may apply to other BTN family members.
Robotic process automation is a disruptive technology to automate already digital yet manual tasks and subprocesses as well as whole business processes rapidly. In contrast to other process automation technologies, robotic process automation is lightweight and only accesses the presentation layer of IT systems to mimic human behavior. Due to the novelty of robotic process automation and the varying approaches when implementing the technology, there are reports that up to 50% of robotic process automation projects fail. To tackle this issue, we use a design science research approach to develop a framework for the implementation of robotic process automation projects. We analyzed 35 reports on real-life projects to derive a preliminary sequential model. Then, we performed multiple expert interviews and workshops to validate and refine our model. The result is a framework with variable stages that offers guidelines with enough flexibility to be applicable in complex and heterogeneous corporate environments as well as for small and medium-sized companies. It is structured by the three phases of initialization, implementation, and scaling. They comprise eleven stages relevant during a project and as a continuous cycle spanning individual projects. Together they structure how to manage knowledge and support processes for the execution of robotic process automation implementation projects.