Theodor-Boveri-Institut für Biowissenschaften
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Rhodopsin-cyclases for photocontrol of cGMP/cAMP and 2.3 Å structure of the adenylyl cyclase domain
(2018)
The cyclic nucleotides cAMP and cGMP are important second messengers that orchestrate fundamental cellular responses. Here, we present the characterization of the rhodopsinguanylyl cyclase from Catenaria anguillulae (CaRhGC), which produces cGMP in response to green light with a light to dark activity ratio > 1000. After light excitation the putative signaling state forms with tau = 31 ms and decays with tau = 570 ms. Mutations (up to 6) within the nucleotide binding site generate rhodopsin-adenylyl cyclases (CaRhACs) of which the double mutated YFP-CaRhAC (E497K/C566D) is the most suitable for rapid cAMP production in neurons. Furthermore, the crystal structure of the ligand-bound AC domain (2.25 angstrom) reveals detailed information about the nucleotide binding mode within this recently discovered class of enzyme rhodopsin. Both YFP-CaRhGC and YFP-CaRhAC are favorable optogenetic tools for non-invasive, cell-selective, and spatio-temporally precise modulation of cAMP/cGMP with light.
The fast and accurate yield estimates with the increasing availability and variety of global satellite products and the rapid development of new algorithms remain a goal for precision agriculture and food security. However, the consistency and reliability of suitable methodologies that provide accurate crop yield outcomes still need to be explored. The study investigates the coupling of crop modeling and machine learning (ML) to improve the yield prediction of winter wheat (WW) and oil seed rape (OSR) and provides examples for the Free State of Bavaria (70,550 km2), Germany, in 2019. The main objectives are to find whether a coupling approach [Light Use Efficiency (LUE) + Random Forest (RF)] would result in better and more accurate yield predictions compared to results provided with other models not using the LUE. Four different RF models [RF1 (input: Normalized Difference Vegetation Index (NDVI)), RF2 (input: climate variables), RF3 (input: NDVI + climate variables), RF4 (input: LUE generated biomass + climate variables)], and one semi-empiric LUE model were designed with different input requirements to find the best predictors of crop monitoring. The results indicate that the individual use of the NDVI (in RF1) and the climate variables (in RF2) could not be the most accurate, reliable, and precise solution for crop monitoring; however, their combined use (in RF3) resulted in higher accuracies. Notably, the study suggested the coupling of the LUE model variables to the RF4 model can reduce the relative root mean square error (RRMSE) from −8% (WW) and −1.6% (OSR) and increase the R
2 by 14.3% (for both WW and OSR), compared to results just relying on LUE. Moreover, the research compares models yield outputs by inputting three different spatial inputs: Sentinel-2(S)-MOD13Q1 (10 m), Landsat (L)-MOD13Q1 (30 m), and MOD13Q1 (MODIS) (250 m). The S-MOD13Q1 data has relatively improved the performance of models with higher mean R
2 [0.80 (WW), 0.69 (OSR)], and lower RRMSE (%) (9.18, 10.21) compared to L-MOD13Q1 (30 m) and MOD13Q1 (250 m). Satellite-based crop biomass, solar radiation, and temperature are found to be the most influential variables in the yield prediction of both crops.
Neisseria gonorrhoeae is a human-specific pathogen that causes gonorrhea, the second most common sexually transmitted infection worldwide. Disease progression, drug discovery, and basic host-pathogen interactions are studied using different approaches, which rely on models ranging from 2D cell culture to complex 3D tissues and animals. In this review, we discuss the models used in N. gonorrhoeae research. We address both in vivo (animal) and in vitro cell culture models, discussing the pros and cons of each and outlining the recent advancements in the field of three-dimensional tissue models. From simple 2D monoculture to complex advanced 3D tissue models, we provide an overview of the relevant methodology and its application. Finally, we discuss future directions in the exciting field of 3D tissue models and how they can be applied for studying the interaction of N. gonorrhoeae with host cells under conditions closely resembling those found at the native sites of infection.
Einflüsse der Photophysik und Photochemie von Cyaninfarbstoffen auf die Lokalisationsmikroskopie
(2023)
In den letzten Jahren haben sich hochauflösende Fluoreszenzmikroskopiemethoden, basierend auf der Lokalisation einzelner Fluorophore, zu einem leistungsstarken Werkzeug etabliert, um Fluoreszenzbilder weit unterhalb der Auflösungsgrenze zu generieren. Hiermit können räumliche Auflösungen von ~ 20 nm erzielt werden, was weit unterhalb der Beugungsgrenze liegt. Dabei haben zahlreiche Optimierungen und Entwicklungen neuer Methoden in der Einzelmolekül-Lokalisationsmikroskopie die Genauigkeit der orstspezifischen Bestimmung einzelner Fluorophore auf bis zu ~ 1 – 3 nm erhöht. Eine Auflösung im molekularen Bereich, weit unterhalb von ~ 10 nm bleibt allerdings herausfordernd, da die Lokalisationsgenauigkeit nur ein Kriterium hierfür ist. Allerdings wurde sich in den letzten Jahren überwiegend auf die Verbesserung dieses Parameters konzentriert. Weitere Kriterien für die fluoreszenzmikroskopische Auflösung sind dabei unter anderem die Markierungsdichte und die Kopplungseffizienz der Zielstruktur, sowie der Kopplungsfehler (Abstand zur Zielstruktur nach Farbstoffkopplung), die sich herausfordernd für eine molekulare Auflösung darstellen. Auch wenn die Kopplungseffizienz und -dichte hoch und der Kopplungsfehler gering ist, steigt bei Interfluorophordistanzen < 5nm, abhängig von den Farbstoffen, die Wahrscheinlichkeit von starken und schwachen Farbstoffwechselwirkungen und damit von Energieübertragungsprozessen zwischen den Farbstoffen, stark an. Daneben sollten Farbstoffe, abhänging von der Lokalisationsmikroskopiemethode, spezifische Kriterien, wie beispielsweise die Photoschaltbarkeit bei dSTORM, erfüllen, was dazu führt, dass diese Methoden häufig nur auf einzelne Farbstoffe beschränkt sind. In dieser Arbeit konnte mithilfe von definierten DNA-Origami Konstrukten gezeigt werden, dass das Blinkverhalten von Cyaninfarbstoffen unter dSTORM-Bedingungen einer Abstandsabhängigkeit aufgrund von spezifischen Energieübertragungsprozessen folgt, womit Farbstoffabstände im sub-10 nm Bereich charakterisiert werden konnten. Darüber hinaus konnte diese Abstandsabhängigkeit an biologischen Proben gezeigt werden. Hierbei konnten verschiedene zelluläre Rezeptoren effizient und mit geringem Abstandsfehler zur Zielstruktur mit Cyaninfarbstoffen gekoppelt werden. Diese abstandsabhänigen Prozesse und damit Charakterisierungen könnten dabei nicht nur spezifisch für die häufig unter dSTORM-Bedingungen verwendeten Cyaninfarbstoffen gültig sein, sondern auch auf andere Farbstoffklassen, die einen Auszustand zeigen, übertragbar sein. Darüber hinaus konnte gezeigt werden, dass hochauflösende dSTORM Aufnahmen unabhängig vom Farbstoffkopplungsgrad der Antikörpern sind, welche häufig für Standardfärbungen von zellulären Strukturen verwendet werden. Dabei konnte durch Photonenkoinzidenzmessungen dargelegt werden, dass aufgrund komplexer Farbstoffwechselwirkungen im Mittel nur ein Farbstoff aktiv ist, wobei höhere Kopplungsgrade ein komplexes Blinkverhalten zu Beginn der Messung zeigen. Durch die undefinierten Farbstoffabstände an Antikörpern konnte hier kein eindeutiger Energieübertragungsmechanismus entschlüsselt werden. Dennoch konnte gezeigt werden, dass Farbstoffaggregate bzw. H-Dimere unter dSTORM-Bedingungen destabilisiert werden. Durch die zuvor erwähnten DNA-Origami Konstrukte definierter Interfluorophordistanzen konnten Energieübertragungsmechanismen entschlüsselt werden, die auch für die Antikörper diverser Kopplungsgrade gültig sind. Des Weiteren konnten, ausgelöst durch komplexe Energieübertragungsprozesse höherer Kopplungsgrade am Antikörper, Mehrfarbenaufnahmen zellulärer Strukturen generiert werden, die über die spezifische Fluoreszenzlebenszeit separiert werden konnten. Dies stellt hier eine weitere Möglichkeit dar, unter einfachen Bedingungen, schnelle Mehrfarbenaufnahmen zellulärer Strukturen zu generieren. Durch die Verwendung des selben Farbstoffes unterschiedlicher Kopplungsgrade kann hier nur mit einer Anregungswellenlänge und frei von chromatischer Aberration gearbeitet werden. Neben den photophysikalischen Untersuchungen der Cyaninfarbstoffe Cy5 und Alexa Fluor 647 wurden diese ebenso photochemisch näher betrachtet. Dabei konnte ein neuartiger chemischer Mechanismus entschlüsselt werden. Dieser Mechanismus führt, ausgelöst durch Singulett-Sauerstoff (1O2), zu einer Photozerschneidung des konjugierten Doppelbindungssystems um zwei Kohlenstoffatome, was zu strukturellen und spektroskopischen Veränderungen dieser Farbstoffe führt. Auf Grundlage dieses Mechanismus konnte eine neue DNA-PAINT Methode entwickelt werden, die zu einer Beschleunigung der Aufnahmezeit führt.
Conventional anticancer chemotherapy is limited because of severe side effects as well as a quickly evolving multidrug resistance of the tumor cells. To address this problem, we have explored a C\(_{60}\) fullerene-based nanosized system as a carrier for anticancer drugs for an optimized drug delivery to leukemic cells.Here, we studied the physicochemical properties and anticancer activity of C\(_{60}\) fullerene noncovalent complexes with the commonly used anticancer drug doxorubicin. C\(_{60}\)-Doxorubicin complexes in a ratio 1:1 and 2:1 were characterized with UV/Vis spectrometry, dynamic light scattering, and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The obtained analytical data indicated that the 140-nm complexes were stable and could be used for biological applications. In leukemic cell lines (CCRF-CEM, Jurkat, THP1 and Molt-16), the nanocomplexes revealed 3.5 higher cytotoxic potential in comparison with the free drug in a range of nanomolar concentrations. Also, the intracellular drug's level evidenced C\(_{60}\) fullerene considerable nanocarrier function.The results of this study indicated that C\(_{60}\) fullerene-based delivery nanocomplexes had a potential value for optimization of doxorubicin efficiency against leukemic cells.
Disturbances alter biodiversity via their specific characteristics, including severity and extent in the landscape, which act at different temporal and spatial scales. Biodiversity response to disturbance also depends on the community characteristics and habitat requirements of species. Untangling the mechanistic interplay of these factors has guided disturbance ecology for decades, generating mixed scientific evidence of biodiversity responses to disturbance. Understanding the impact of natural disturbances on biodiversity is increasingly important due to human‐induced changes in natural disturbance regimes. In many areas, major natural forest disturbances, such as wildfires, windstorms, and insect outbreaks, are becoming more frequent, intense, severe, and widespread due to climate change and land‐use change. Conversely, the suppression of natural disturbances threatens disturbance‐dependent biota. Using a meta‐analytic approach, we analysed a global data set (with most sampling concentrated in temperate and boreal secondary forests) of species assemblages of 26 taxonomic groups, including plants, animals, and fungi collected from forests affected by wildfires, windstorms, and insect outbreaks. The overall effect of natural disturbances on α‐diversity did not differ significantly from zero, but some taxonomic groups responded positively to disturbance, while others tended to respond negatively. Disturbance was beneficial for taxonomic groups preferring conditions associated with open canopies (e.g. hymenopterans and hoverflies), whereas ground‐dwelling groups and/or groups typically associated with shady conditions (e.g. epigeic lichens and mycorrhizal fungi) were more likely to be negatively impacted by disturbance. Across all taxonomic groups, the highest α‐diversity in disturbed forest patches occurred under moderate disturbance severity, i.e. with approximately 55% of trees killed by disturbance. We further extended our meta‐analysis by applying a unified diversity concept based on Hill numbers to estimate α‐diversity changes in different taxonomic groups across a gradient of disturbance severity measured at the stand scale and incorporating other disturbance features. We found that disturbance severity negatively affected diversity for Hill number q = 0 but not for q = 1 and q = 2, indicating that diversity–disturbance relationships are shaped by species relative abundances. Our synthesis of α‐diversity was extended by a synthesis of disturbance‐induced change in species assemblages, and revealed that disturbance changes the β‐diversity of multiple taxonomic groups, including some groups that were not affected at the α‐diversity level (birds and woody plants). Finally, we used mixed rarefaction/extrapolation to estimate biodiversity change as a function of the proportion of forests that were disturbed, i.e. the disturbance extent measured at the landscape scale. The comparison of intact and naturally disturbed forests revealed that both types of forests provide habitat for unique species assemblages, whereas species diversity in the mixture of disturbed and undisturbed forests peaked at intermediate values of disturbance extent in the simulated landscape. Hence, the relationship between α‐diversity and disturbance severity in disturbed forest stands was strikingly similar to the relationship between species richness and disturbance extent in a landscape consisting of both disturbed and undisturbed forest habitats. This result suggests that both moderate disturbance severity and moderate disturbance extent support the highest levels of biodiversity in contemporary forest landscapes.
Overwintering temperature and body condition shift emergence dates of spring-emerging solitary bees
(2018)
Solitary bees in seasonal environments must align their life-cycles with favorable environmental conditions and resources; the timing of their emergence is highly fitness relevant. In several bee species, overwintering temperature influences both emergence date and body weight at emergence. High variability in emergence dates among specimens overwintering at the same temperatures suggests that the timing of emergence also depends on individual body conditions. However, possible causes for this variability, such as individual differences in body size or weight, have been rarely studied. In a climate chamber experiment using two spring-emerging mason bees (Osmia cornuta and O. bicornis), we investigated the relationship between temperature, emergence date, body weight, and body size, the last of which is not affected by overwintering temperature. Our study showed that body weight declined during hibernation more strongly in warm than in cold overwintering temperatures. Although bees emerged earlier in warm than in cold overwintering temperatures, at the time of emergence, bees in warm overwintering temperatures had lower body weights than bees in cold overwintering temperatures (exception of male O. cornuta). Among specimens that experienced the same overwintering temperatures, small and light bees emerged later than their larger and heavier conspecifics. Using a simple mechanistic model we demonstrated that spring-emerging solitary bees use a strategic approach and emerge at a date that is most promising for their individual fitness expectations. Our results suggest that warmer overwintering temperatures reduce bee fitness by causing a decrease in body weight at emergence. We showed furthermore that in order to adjust their emergence dates, bees use not only temperature but also their individual body condition as triggers. This may explain differing responses to climate warming within and among bee populations and may have consequences for bee-plant interactions as well as for the persistence of bee populations under climate change.
The composition and richness of herbivore and plant assemblages change along climatic gradients, but knowledge about associated shifts in specialization is scarce and lacks controlling for the abundance and phylogeny of interaction partners. Thus, we aimed to test whether the specialization of phytophagous insects in insect‐plant interaction networks decreases toward cold habitats as predicted by the ‘altitude niche‐breadth hypothesis’ to forecast possible consequences of interaction rewiring under climate change. We used a non‐invasive, standardized metabarcoding approach to reconstruct dietary relationships of Orthoptera species as a major insect herbivore taxon along a broad temperature gradient (~12°C) in Southern Germany. Based on Orthoptera surveys, feeding observations, collection of fecal pellets from >3,000 individuals of 54 species, and parallel vegetation surveys on 41 grassland sites, we quantified plant resource availability and its use by herbivores. Herbivore assemblages were richer in species and individuals at sites with high summer temperatures, while plant richness peaked at intermediate temperatures. Corresponding interaction networks were most specialized in warm habitats. Considering phylogenetic relationships of plant resources, however, the specialization pattern was not linear but peaked at intermediate temperatures, mediated by herbivores feeding on a narrow range of phylogenetically related resources. Our study provides empirical evidence of resource specialization of insect herbivores along a climatic gradient, demonstrating that resource phylogeny, availability, and temperature interactively shape the specialization of herbivore assemblages. Instead of low specialization levels only in cold, harsh habitats, our results suggest increased generalist feeding due to intraspecific changes and compositional differences at both ends of the microclimatic gradient. We conclude that this nonlinear change of phylogeny‐based resource specialization questions predictions derived from the ‘altitude‐niche breadth hypothesis’ and highlights the currently limited understanding of how plant‐herbivore interactions will change under future climatic conditions.
Drosophila’s lateral posterior neurons (LPNs) belong to a small group of circadian clock neurons that is so far not characterized in detail. Thanks to a new highly specific split‐Gal4 line, here we describe LPNs’ morphology in fine detail, their synaptic connections, daily bimodal expression of neuropeptides, and propose a putative role of this cluster in controlling daily activity and sleep patterns. We found that the three LPNs are heterogeneous. Two of the neurons with similar morphology arborize in the superior medial and lateral protocerebrum and most likely promote sleep. One unique, possibly wakefulness‐promoting, neuron with wider arborizations extends from the superior lateral protocerebrum toward the anterior optic tubercle. Both LPN types exhibit manifold connections with the other circadian clock neurons, especially with those that control the flies’ morning and evening activity (M‐ and E‐neurons, respectively). In addition, they form synaptic connections with neurons of the mushroom bodies, the fan‐shaped body, and with many additional still unidentified neurons. We found that both LPN types rhythmically express three neuropeptides, Allostatin A, Allostatin C, and Diuretic Hormone 31 with maxima in the morning and the evening. The three LPN neuropeptides may, furthermore, signal to the insect hormonal center in the pars intercerebralis and contribute to rhythmic modulation of metabolism, feeding, and reproduction. We discuss our findings in the light of anatomical details gained by the recently published hemibrain of a single female fly on the electron microscopic level and of previous functional studies concerning the LPN.
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.