A biochemical approach

0 Titelblatt 1 1 Zusammenfassung 9 2 Abstract 10 3 Einleitung 11 3.1 Biologische Funktion der Neurotrophine 11 3.2 Struktur der Neurotrophine 13 3.3 Die Rezeptoren der Neurotrophine 14 3.3.1 Die Trk Rezeptoren 15 3.3.2 Der Neurotrophinrezeptor p75NTR 16 4 Zielsetzung der Arbeit 21 4.1 Reinigung von intrazellulären Interaktoren 21 4.1.1 Experimentelle Ansätze zur Identifikation von intrazellulären Interaktoren 21 4.2 Suche nach p75NTR-ähnlichen Molekülen 23 5 Material und Methoden 25 5.1 Material 25 5.1.1 Antikörper 25 5.1.2 Tiere 26 5.1.3 Zelllinien 26 5.1.4 Modifizierte Lambda Phosphatase 26 5.1.5 Neurotrophine 27 5.1.6 Plasmide 27 5.1.7 Medien 27 5.1.8 Adjuvantien 27 5.1.9 Chemikalien und Zubehör 28 5.1.10 Geräte 29 5.1.11 Puffer 30 5.2 Methoden 34 5.2.1 Aufreinigung intrazellulärer Interaktoren von p75NTR 34 5.2.1.1 P75NTR Konzentrationsbestimmung in Gehirnhomogenat 34 5.2.1.2 Expression und Aufreinigung des p75NTR-IZD Plasmids 34 5.2.1.3 Verwendung der BIAcore Maschine 35 5.2.1.4 Iodierung von Neurotrophinen 36 5.2.1.5 Dissoziation von Spinalganglien 37 5.2.1.6 Overlayblots 38 5.2.1.7 In vitro Translation der intrazellulären Domäne von p75NTR 38 5.2.1.8 Kopplung von 125I-Neurotrophin an p75NTR für Overlayblots 39 5.2.1.9 Bindungsstudien an dissoziierten Spinalganglien Neuronen 39 5.2.1.10 Präparation von Caveolae mit Triton X-100 40 5.2.1.11 Präparation von Caveolae mit NaCO3 40 5.2.1.12 Präparation von ?Postsynatic Densities? (PSDs) 41 5.2.2 Charakterisierung, Reinigung und Identifizierung von p75NTR-ähnlichen Proteinen 42 5.2.2.1 Herstellung polyklonaler Seren gegen die intrazelluläre Domäne von p75NTR 42 5.2.2.2 Organpräparation 42 5.2.2.3 Dephosphorylierung der FreundI Antigene 42 5.2.2.4 Bindungsassay an Spinalganglien 43 5.2.2.5 Reinigung des FreundI Antigens 43 5.2.2.6 Sequenzvergleich und Phosphorylierungsvorhersagen 44 5.2.2.7 Peptidkompetition im Westernblot 44 5.2.2.8 Präparation von Körnerzellen 45 5.2.2.9 Immunhistochemie 45 5.2.3 Vermischtes 46 5.2.3.1 NGF-ELISA 46 5.2.3.2 Herstellung einer stabilen Zelllinie 46 5.2.3.3 Biologischer Überlebensassay 47 5.2.3.4 Anzucht und Lagerung von E. coli-Bakterien 48 5.2.3.5 SDS-Polyacrylamid Gelelektrophorese (PAGE) 48 5.2.3.6 Semi-dry Westernblot 49 5.2.3.7 Entfernung von Antikörpern von Blotmembranen (?Strippen des Blots?) 49 5.2.3.8 Coomassie Färbung von Gelen 49 5.2.3.9 Silberfärbung von SDS-PAGE Gelen 50 5.2.3.10 Kolloidal Coomassie Färbung von SDS-PAGE Gelen 50 5.2.3.11 Konzentrationsbestimmung von Proteinen 50 6 Ergebnisse 51 6.1 Biochemischen Aufreinigung intrazellulärer Interaktoren von p75NTR 51 6.1.1 Affinitätsreinigung in Gegenwart des extrazellulären Liganden 51 6.1.2 Affinitätsreinigung über die intrazelluläre Domäne von p75NTR 52 6.1.2.1 Protein Interaktionsmessungen mit der BIAcoremaschine 52 6.1.2.2 Interaktorendetektion mit Overlayblots 55 6.1.3 Anreicherung von Interaktoren in funktionell charakterisierten, subzellulären Fraktionen 57 6.1.3.1 Präparation von Caveolae 57 6.1.3.2 Präparation von Postsynaptischen Dichten (PSDs) 58 6.2 Charakterisierung, Reinigung und Identifizierung von p75NTR-ähnlichen Proteinen 60 6.2.1 P75NTR Antiserum zeigt Westernblotsignal auch in p75NTR -/- Mäusen 60 6.2.2 FreundI Antigene sind nur im ZNS exprimiert 62 6.2.3 FreundI Antigene werden postnatal herunterreguliert 63 6.2.4 FreundI Antigen Westernblotsignal ist kalziumabhängig 63 6.2.5 FreundI Antigene wechseln die Zentrifugationsfraktion nach Inkubation 64 6.2.6 p75NTR Seren detektieren FreundI Antigene in dephosphoryliertem Gehirn- homogenat 65 6.2.7 P75NTR-ähnliche Immunfärbung in p75NTR -/- Basal Ganglien 67 6.2.8 P75NTR-ähnliche Bindung an dissoziierten Spinalganglien von p75NTR-/- Tieren 67 6.2.9 Reinigung der FreundI Antigene 68 6.2.10 Identifikation der FreundI Antigene als N-Terminus von MAP1B 73 6.2.11 Die FreundI Antigene werden von einem MAP1B Antiserum detektiert 74 7 Diskussion 8 Abkürzungen und Begriffe 10 Danksagung 11 LiteraturverzeichnisNeurotrophine sind Wachstumsfaktoren. In Säugern modulieren sie nicht nur weitreichende Aspekte der Entwicklung sondern auch Funktionen des erwachsenen Nervensystems. Die Signaltransduktion erfolgt einerseits über den Rezeptor p75NTR andererseits über die Rezeptor-Tyrosinkinasen TrkA, TrkB und TrkC. Während die Signalkaskaden der Trk Rezeptoren weitgehend aufgeklärt wurden, entwickelte sich das Wissen über p75NTR ebenso wie das über die verwandten Mitglieder der ?Tumor Necrosis Factor Rezeptor? (TNFR)-Superfamilie nur langsam. 10 Jahre nach der Klonierung sollten mit dieser Arbeit daher die intrazellulären Interaktoren von p75NTR identifiziert werden. Ebenso wie zur Aufklärung der Signalwege anderer Mitglieder der TNFR-Superfamilie wurden biochemische Reinigungsansätze unternommen. Sowohl die Reinigung des p75NTR- Interaktorkomplexes in Gegenwart extrazellulärer Liganden, als auch die Affinitätsreinigung über die intrazelluläre Domäne sowie die Anreicherung des p75NTR-Interaktorkomplexes in charakterisierten subzellulären Fraktionen wurde vorgenommen. Im Rahmen dieser Arbeit wurden zudem neue Antiseren gegen p75NTR hergestellt. Eines dieser Seren zeigte zusätzliche p75NTR-ähnliche Westernblotsignale. Überraschenderweise konnten diese Signale auch in Gehirnhomogenaten des 1992 hergestellten p75NTR-Teil-Knockout sowie in dem bis dahin nur in unserem Labor zugänglichen ersten vollständigen p75NTR-Knockout detektiert werden. Die Expression der p75NTR-ähnlichen Proteine war auf das Gehirn beschränkt, wurde postnatal stark herunterreguliert und zeigte in differenzieller Zentrifugation starke Kalziumabhängigkeit. Zusätzlich konnte in p75NTR-Knockout-Tieren eine p75NTRähnliche Bindungsstelle identifiziert werden. Die p75NTR-ähnlichen Proteine wurden gereinigt, als N-Terminus von des Mikrotubuli Assoziierten Proteins 1B (MAP1B) identifiziert und die Homologie zu p75NTR untersucht.Neurotrophins are growth factors. In mammals, they exert a broad range of modulatory effects on developing as well as on mature neurons. Neurotrophinmediated signals are transduced by either the neurotrophin receptor p75NRT or the receptor tyrosine kinases TrkA, TrkB and TrkC. Whereas signaling via the Trkreceptors is quite well understood, even 10 years after its identification there was little known about the function and signaling pathways of p75NTR. The aim of this work was therefore to identify intracellular interactors of p75NTR. A biochemical approach was chosen, as was previously applied to related proteins of the TNFR-family. Three different purification strategies were used: 1) purification of the p75NTR-interactor complex in the presence of its extracellular ligands, 2) affinity purification via the intracellular domain of p75NTR and 3) enrichment of the p75NTR- interactor complex in characterized subcellular fractions. In addition, new antisera against p75NTR were generated and characterized. One antiserum recognized additional p75NTR-like signals on Western blot. Surprisingly, these signals remained strongly detectable in brain homogenates of a partial as well as a complete p75NTR-/- knock out mouse. The p75NTR-like antigens were expressed exclusively in the central nervous system, were strongly downregulated during postnatal development and showed calcium-dependent segregation during centrifugation. In addition, a p75NTR-like binding site was detected in dissociated dorsal root ganglia of the complete p75NTR knock out mouse. The p75NTR?like antigens were purified, identified as the N-terminus of the microtubule associated protein MAP1B and the homology to p75NTR was investigated

Quantitative automated microscopy (QuAM) elucidates growth factor specific signalling in pain sensitization

<p>Abstract</p> <p>Background</p> <p>Dorsal root ganglia (DRG)-neurons are commonly characterized immunocytochemically. Cells are mostly grouped by the experimenter's eye as "marker-positive" and "marker-negative" according to their immunofluorescence intensity. Classification criteria remain largely undefined. Overcoming this shortfall, we established a quantitative automated microscopy (QuAM) for a defined and multiparametric analysis of adherent heterogeneous primary neurons on a single cell base.</p> <p>The growth factors NGF, GDNF and EGF activate the MAP-kinase Erk1/2 via receptor tyrosine kinase signalling. NGF and GDNF are established factors in regeneration and sensitization of nociceptive neurons. If also the tissue regenerating growth factor, EGF, influences nociceptors is so far unknown. We asked, if EGF can act on nociceptors, and if QuAM can elucidate differences between NGF, GDNF and EGF induced Erk1/2 activation kinetics. Finally, we evaluated, if the investigation of one signalling component allows prediction of the behavioral response to a reagent not tested on nociceptors such as EGF.</p> <p>Results</p> <p>We established a software-based neuron identification, described quantitatively DRG-neuron heterogeneity and correlated measured sample sizes and corresponding assay sensitivity. Analysing more than 70,000 individual neurons we defined neuronal subgroups based on differential Erk1/2 activation status in sensory neurons. Baseline activity levels varied strongly already in untreated neurons. NGF and GDNF subgroup responsiveness correlated with their subgroup specificity on IB4(+)- and IB4(-)-neurons, respectively. We confirmed expression of EGF-receptors in all sensory neurons. EGF treatment induced STAT3 translocation into the nucleus. Nevertheless, we could not detect any EGF induced Erk1/2 phosphorylation. Accordingly, intradermal injection of EGF resulted in a fundamentally different outcome than NGF/GDNF. EGF did not induce mechanical hyperalgesia, but blocked PGE₂-induced sensitization.</p> <p>Conclusions</p> <p>QuAM is a suitable if not necessary tool to analyze activation of endogenous signalling in heterogeneous cultures. NGF, GDNF and EGF stimulation of DRG-neurons shows differential Erk1/2 activation responses and a corresponding differential behavioral phenotype. Thus, in addition to expression-markers also signalling-activity can be taken for functional subgroup differentiation and as predictor of behavioral outcome. The anti-nociceptive function of EGF is an intriguing result in the context of tissue damage but also for understanding pain resulting from EGF-receptor block during cancer therapy.</p

Threshold-Free Population Analysis Identifies Larger DRG Neurons to Respond Stronger to NGF Stimulation

Sensory neurons in dorsal root ganglia (DRG) are highly heterogeneous in terms of cell size, protein expression, and signaling activity. To analyze their heterogeneity, threshold-based methods are commonly used, which often yield highly variable results due to the subjectivity of the individual investigator. In this work, we introduce a threshold-free analysis approach for sparse and highly heterogeneous datasets obtained from cultures of sensory neurons. This approach is based on population estimates and completely free of investigator-set parameters. With a quantitative automated microscope we measured the signaling state of single DRG neurons by immunofluorescently labeling phosphorylated, i.e., activated Erk1/2. The population density of sensory neurons with and without pain-sensitizing nerve growth factor (NGF) treatment was estimated using a kernel density estimator (KDE). By subtraction of both densities and integration of the positive part, a robust estimate for the size of the responsive subpopulations was obtained. To assure sufficiently large datasets, we determined the number of cells required for reliable estimates using a bootstrapping approach. The proposed methods were employed to analyze response kinetics and response amplitude of DRG neurons after NGF stimulation. We thereby determined the portion of NGF responsive cells on a true population basis. The analysis of the dose dependent NGF response unraveled a biphasic behavior, while the study of its time dependence showed a rapid response, which approached a steady state after less than five minutes. Analyzing two parameter correlations, we found that not only the number of responsive small-sized neurons exceeds the number of responsive large-sized neurons—which is commonly reported and could be explained by the excess of small-sized cells—but also the probability that small-sized cells respond to NGF is higher. In contrast, medium-sized and large-sized neurons showed a larger response amplitude in their mean Erk1/2 activity

Modern venomics--Current insights, novel methods, and future perspectives in biological and applied animal venom research

Venoms have evolved >100 times in all major animal groups, and their components, known as toxins, have been fine-tuned over millions of years into highly effective biochemical weapons. There are many outstanding questions on the evolution of toxin arsenals, such as how venom genes originate, how venom contributes to the fitness of venomous species, and which modifications at the genomic, transcriptomic, and protein level drive their evolution. These questions have received particularly little attention outside of snakes, cone snails, spiders, and scorpions. Venom compounds have further become a source of inspiration for translational research using their diverse bioactivities for various applications. We highlight here recent advances and new strategies in modern venomics and discuss how recent technological innovations and multi-omic methods dramatically improve research on venomous animals. The study of genomes and their modifications through CRISPR and knockdown technologies will increase our understanding of how toxins evolve and which functions they have in the different ontogenetic stages during the development of venomous animals. Mass spectrometry imaging combined with spatial transcriptomics, in situ hybridization techniques, and modern computer tomography gives us further insights into the spatial distribution of toxins in the venom system and the function of the venom apparatus. All these evolutionary and biological insights contribute to more efficiently identify venom compounds, which can then be synthesized or produced in adapted expression systems to test their bioactivity. Finally, we critically discuss recent agrochemical, pharmaceutical, therapeutic, and diagnostic (so-called translational) aspects of venoms from which humans benefit.This work is funded by the European Cooperation in Science and Technology (COST, www.cost.eu) and based upon work from the COST Action CA19144 – European Venom Network (EUVEN, see https://euven-network.eu/). This review is an outcome of EUVEN Working Group 2 (“Best practices and innovative tools in venomics”) led by B.M.v.R. As coordinator of the group Animal Venomics until end 2021 at the Institute for Insectbiotechnology, JLU Giessen, B.M.v.R. acknowledges the Centre for Translational Biodiversity Genomics (LOEWE-TBG) in the programme “LOEWE – Landes-Offensive zur Entwicklung Wissenschaftlich-ökonomischer Exzellenz” of Hesse's Ministry of Higher Education, Research, and the Arts. B.M.v.R. and I.K. further acknowledge funding on venom research by the German Science Foundation to B.M.v.R. (DFG RE3454/6-1). A.C., A.V., and G.Z. were supported by the European Union's Horizon 2020 Research and Innovation program through Marie Sklodowska-Curie Individual Fellowships (grant agreements No. A.C.: 896849, A.V.: 841576, and G.Z.: 845674). M.P.I. is supported by the TALENTO Program by the Regional Madrid Government (2018-T1/BIO-11262). T.H.'s venom research is funded by the DFG projects 271522021 and 413120531. L.E. was supported by grant No. 7017-00288 from the Danish Council for Independent Research (Technology and Production Sciences). N.I. acknowledges funding on venom research by the Research Fund of Nevsehir Haci Bektas Veli University (project Nos. ABAP20F28, BAP18F26). M.I.K. and A.P. acknowledge support from GSRT National Research Infrastructure structural funding project INSPIRED (MIS 5002550). G.A. acknowledges support from the Slovenian Research Agency grants P1-0391, J4-8225, and J4-2547. G.G. acknowledges support from the Institute for Medical Research and Occupational Health, Zagreb, Croatia. E.A.B.U. is supported by a Norwegian Research Council FRIPRO-YRT Fellowship No. 287462

Importance of Non-Selective Cation Channel TRPV4 Interaction with Cytoskeleton and Their Reciprocal Regulations in Cultured Cells

BACKGROUND: TRPV4 and the cellular cytoskeleton have each been reported to influence cellular mechanosensitive processes as well as the development of mechanical hyperalgesia. If and how TRPV4 interacts with the microtubule and actin cytoskeleton at a molecular and functional level is not known. METHODOLOGY AND PRINCIPAL FINDINGS: We investigated the interaction of TRPV4 with cytoskeletal components biochemically, cell biologically by observing morphological changes of DRG-neurons and DRG-neuron-derived F-11 cells, as well as functionally with calcium imaging. We find that TRPV4 physically interacts with tubulin, actin and neurofilament proteins as well as the nociceptive molecules PKCepsilon and CamKII. The C-terminus of TRPV4 is sufficient for the direct interaction with tubulin and actin, both with their soluble and their polymeric forms. Actin and tubulin compete for binding. The interaction with TRPV4 stabilizes microtubules even under depolymerizing conditions in vitro. Accordingly, in cellular systems TRPV4 colocalizes with actin and microtubules enriched structures at submembranous regions. Both expression and activation of TRPV4 induces striking morphological changes affecting lamellipodial, filopodial, growth cone, and neurite structures in non-neuronal cells, in DRG-neuron derived F11 cells, and also in IB4-positive DRG neurons. The functional interaction of TRPV4 and the cytoskeleton is mutual as Taxol, a microtubule stabilizer, reduces the Ca2+-influx via TRPV4. CONCLUSIONS AND SIGNIFICANCE: TRPV4 acts as a regulator for both, the microtubule and the actin. In turn, we describe that microtubule dynamics are an important regulator of TRPV4 activity. TRPV4 forms a supra-molecular complex containing cytoskeletal proteins and regulatory kinases. Thereby it can integrate signaling of various intracellular second messengers and signaling cascades, as well as cytoskeletal dynamics. This study points out the existence of cross-talks between non-selective cation channels and cytoskeleton at multiple levels. These cross talks may help us to understand the molecular basis of the Taxol-induced neuropathic pain development commonly observed in cancer patients

Crosstalk from cAMP to ERK1/2 emerges during postnatal maturation of nociceptive neurons and is maintained during aging

Maturation of nociceptive neurons depends on changes in transcription factors, ion channels and neuropeptides. Mature nociceptors initiate pain in part by drastically reducing the activation threshold via intracellular sensitization signaling. Whether sensitization signaling also changes during development and aging remains so far unknown. Using a novel automated microscopy approach, we quantified changes in intracellular signaling protein expression and in their signaling dynamics, as well as changes in intracellular signaling cascade wiring, in sensory neurons from newborn to senescent (24 months of age) rats. We found that nociceptive subgroups defined by the signaling components protein kinase A (PKA)-RII beta (also known as PRKAR2B) and CaMKIIa (also known as CAMK2A) developed at around postnatal day 10, the time of nociceptor maturation. The integrative nociceptor marker, PKARII beta, allowed subgroup segregation earlier than could be achieved by assessing the classical markers TRPV1 and Na(v)1.8 (also known as SCN10A). Signaling kinetics remained constant over lifetime despite in part strong changes in the expression levels. Strikingly, we found a mechanism important for neuronal memory -i.e. the crosstalk from cAMP and PKA to ERK1 and ERK2 (ERK1/2, also known as MAPK3 and MAPK1, respectively) -to emerge postnatally. Thus, maturation of nociceptors is closely accompanied by altered expression, activation and connectivity of signaling pathways known to be central for pain sensitization and neuronal memory formation

ODE Constrained Mixture Modelling: A Method for Unraveling Subpopulation Structures and Dynamics

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e. g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity

Prostate-Specific Membrane Antigen Uptake in a Peripheral Nerve and Respective Ganglia on Ga-68-Prostate-Specific Membrane Antigen-HBED-CC PET/CT

A 74-year-old man with a history of prostate cancer with proven osseous metastatic disease underwent Ga-68-prostate-specific membrane antigen (PSMA) PET/CT under antiandrogen therapy. The scan revealed a long segment of increased PSMA tracer uptake within the right sciatic nerve, which appeared edematous and swollen, and the respective ganglia. Clinically, the patient suffered from pain and paresis in the right leg. As infiltration of a long segment of a single nerve seems unlikely, primarily neuronal disease such as neuritis (induced by metastases or radiotherapy) was considered. The observed uptake of PSMA-targeting PET tracers may then represent a peripheral nerve disorder