Theodor-Boveri-Institut für Biowissenschaften
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Institute
- Theodor-Boveri-Institut für Biowissenschaften (1953)
- Graduate School of Life Sciences (90)
- Institut für Humangenetik (46)
- Institut für Virologie und Immunbiologie (27)
- Julius-von-Sachs-Institut für Biowissenschaften (25)
- Medizinische Klinik und Poliklinik II (25)
- Rudolf-Virchow-Zentrum (22)
- Center for Computational and Theoretical Biology (19)
- Institut für Pharmakologie und Toxikologie (18)
- Lehrstuhl für Tissue Engineering und Regenerative Medizin (18)
Sonstige beteiligte Institutionen
- Institut für Tierökologie und Tropenbiologie (2)
- Ökologische Station Fabrikschleichach (2)
- Albert-Ludwigs-Universität Freiburg (1)
- Boehringer Ingelheim Pharma GmbH & Co. KG (1)
- Boston Children's Hospital (1)
- Center for Computational and Theoretical Biology (CCTB), Universität Würzburg (1)
- Chemical Biology Laboratory, National Cancer Institue, Frederick (USA) (1)
- Core Unit Systemmedizin (1)
- DNA Analytics Core Facility, Biocenter, University of Wuerzburg, Wuerzburg, Germany (1)
- DNA Analytics Core Facility, Biocenter, University of Würzburg, Würzburg, Germany (1)
ResearcherID
- D-1221-2009 (1)
- J-8841-2015 (1)
- N-2030-2015 (1)
Salt stress is a major abiotic stress, responsible for declining agricultural productivity. Roots are regarded as hubs for salt detoxification, however, leaf salt concentrations may exceed those of roots. How mature leaves manage acute sodium chloride (NaCl) stress is mostly unknown.
To analyze the mechanisms for NaCl redistribution in leaves, salt was infiltrated into intact tobacco leaves. It initiated pronounced osmotically‐driven leaf movements. Leaf downward movement caused by hydro‐passive turgor loss reached a maximum within 2 h.
Salt‐driven cellular water release was accompanied by a transient change in membrane depolarization but not an increase in cytosolic calcium ion (Ca\(^{2+}\)) level. Nonetheless, only half an hour later, the leaves had completely regained turgor. This recovery phase was characterized by an increase in mesophyll cell plasma membrane hydrogen ion (H\(^{+}\)) pumping, a salt uptake‐dependent cytosolic alkalization, and a return of the apoplast osmolality to pre‐stress levels. Although, transcript numbers of abscisic acid‐ and Salt Overly Sensitive pathway elements remained unchanged, salt adaptation depended on the vacuolar H\(^{+}\)/Na\(^{+}\)‐exchanger NHX1.
Altogether, tobacco leaves can detoxify sodium ions (Na\(^{+}\)) rapidly even under massive salt loads, based on pre‐established posttranslational settings and NHX1 cation/H+ antiport activity. Unlike roots, signaling and processing of salt stress in tobacco leaves does not depend on Ca\(^{2+}\) signaling.
Green plants are equipped with photoreceptors that are capable of sensing radiation in the ultraviolet‐to‐blue and the red‐to‐far‐red parts of the light spectrum. However, plant cells are not particularly sensitive to green light (GL), and light which lies within this part of the spectrum does not efficiently trigger the opening of stomatal pores. Here, we discuss the current knowledge of stomatal responses to light, which are either provoked via photosynthetically active radiation or by specific blue light (BL) signaling pathways. The limited impact of GL on stomatal movements provides a unique option to use this light quality to control optogenetic tools. Recently, several of these tools have been optimized for use in plant biological research, either to control gene expression, or to provoke ion fluxes. Initial studies with the BL‐activated potassium channel BLINK1 showed that this tool can speed up stomatal movements. Moreover, the GL‐sensitive anion channel GtACR1 can induce stomatal closure, even at conditions that provoke stomatal opening in wild‐type plants. Given that crop plants in controlled‐environment agriculture and horticulture are often cultivated with artificial light sources (i.e. a combination of blue and red light from light‐emitting diodes), GL signals can be used as a remote‐control signal that controls stomatal transpiration and water consumption.
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.
Recent reports on insect decline have highlighted the need for long‐term data on insect communities towards identifying their trends and drivers.
With the launch of many new insect monitoring schemes to investigate insect communities over large spatial and temporal scales, Malaise traps have become one of the most important tools due to the broad spectrum of species collected and reduced capture bias through passive sampling of insects day and night. However, Malaise traps can vary in size, shape, and colour, and it is unknown how these differences affect biomass, species richness, and composition of trap catch, making it difficult to compare results between studies.
We compared five Malaise trap types (three variations of the Townes and two variations of the Bartak Malaise trap) to determine their effects on biomass and species richness as identified by metabarcoding.
Insect biomass varied by 20%–55%, not strictly following trap size but varying with trap type. Total species richness was 20%–38% higher in the three Townes trap models compared to the Bartak traps. Bartak traps captured lower richness of highly mobile taxa but increased richness of ground‐dwelling taxa. The white roofed Townes trap captured a higher richness of pollinators.
We find that biomass, total richness, and taxa group specific richness are all sensitive to Malaise trap type. Trap type should be carefully considered and aligned to match monitoring and research questions. Additionally, our estimates of trap type effects can be used to adjust results to facilitate comparisons across studies.
Earlier flowering of winter oilseed rape compensates for higher pest pressure in warmer climates
(2023)
Global warming can increase insect pest pressure by enhancing reproductive rates. Whether this translates into yield losses depends on phenological synchronisation of pests with their host plants and natural enemies. Simultaneously, landscape composition may mitigate climate effects by shaping the resource availability for pests and their antagonists. Here, we study the combined effects of temperature and landscape composition on pest abundances, larval parasitism, crop damage and yield, while also considering crop phenology, to identify strategies for sustainable management of oilseed rape (OSR) pests under warming climates.
In all, 29 winter OSR crop fields were investigated in different climates (defined by multi‐annual mean temperature, MAT) and landscape contexts in Bavaria, Germany. We measured abundances of adult pollen beetles and stem weevil larvae, pollen beetle larval parasitism, bud loss, stem damage and seed yield, and calculated the flowering date from growth stage observations. Landscape parameters (proportion of non‐crop and OSR area, change in OSR area relative to the previous year) were calculated at six spatial scales (0.6–5 km).
Pollen beetle abundance increased with MAT but to different degrees depending on the landscape context, that is, increased less strongly when OSR proportions were high (1‐km scale), interannually constant (5‐km scale) or both. In contrast, stem weevil abundance and stem damage did not respond to landscape composition nor MAT. Pollen beetle larval parasitism was overall low, but occasionally exceeded 30% under both low and high MAT and with reduced OSR area (0.6‐km scale).
Despite high pollen beetle abundance in warm climates, yields were high when OSR flowered early. Thereby, higher temperatures favoured early flowering. Only among late‐flowering OSR crop fields yield was higher in cooler than warmer climates. Bud loss responded analogously. Landscape composition did not substantially affect bud loss and yield.
Synthesis and applications: Earlier flowering of winter OSR compensates for higher pollen beetle abundance in warmer climates, while interannual continuity of OSR area prevents high pollen beetle abundance in the first place. Thus, regional coordination of crop rotation and crop management promoting early flowering may contribute to sustainable pest management in OSR under current and future climatic conditions.
The exponential increase in the human population in tandem with increased food demand has caused agriculture to be the global‐dominant form of land use. Afrotropical drylands are currently facing the loss of natural savannah habitats and agricultural intensification with largely unknown consequences for bees. Here we investigate the effects of agricultural intensification on bee assemblages in the Afrotropical drylands of northern Tanzania. We disentangled the direct effects of agricultural intensification and temperature on bee richness from indirect effects mediated by changes in floral resources.
We collected data from 24 study sites representing three levels of management intensity (natural savannah, moderate intensive and highly intensive agriculture) spanning an extensive gradient of mean annual temperature (MAT) in northern Tanzania. We used ordinary linear models and path analysis to test the effects of agricultural intensity and MAT on bee species richness, bee species composition and body‐size variation of bee communities.
We found that bee species richness increased with agricultural intensity and with increasing temperature. The effects of agricultural intensity and temperature on bee species richness were mediated by the positive effects of agriculture and temperature on the richness of floral resources used by bees. During the off‐growing season, agricultural land was characterized by an extensive period of fallow land holding a very high density of flowering plants with unique bee species composition. The increase in bee diversity in agricultural habitats paralleled an increasing variation of bee body sizes with agricultural intensification that, however, diminished in environments with higher temperatures.
Synthesis and applications. Our study reveals that bee assemblages in Afrotropical drylands benefit from agricultural intensification in the way it is currently practiced. However, further land‐use intensification, including year‐round irrigated crop monocultures and excessive use of agrochemicals, is likely to exert a negative impact on bee diversity and pollination services, as reported in temperate regions. Moreover, several bee species were restricted to natural savannah habitats. To conserve bee communities and guarantee pollination services in the region, a mixture of savannah and agriculture, with long periods of fallow land should be maintained.
The mechanisms by which climatic changes influence ecosystem functions, that is, by a direct climatic control of ecosystem processes or by modifying richness and trait compositions of species communities, remain unresolved.
This study is a contribution to this discourse by elucidating the linkages between climate, land use, biodiversity, body size and ecosystem functions.
We disentangled direct climatic from biodiversity‐mediated effects by using dung removal by dung beetles as a model system and by combining correlative field data and exclosure experiments along an extensive elevational gradient on Mt. Kilimanjaro, Tanzania.
Dung removal declined with increasing elevation, being associated with a strong reduction in the richness and body size traits of dung beetle communities. Climate influenced dung removal rates by modifying biodiversity rather than by direct effects. The biodiversity–ecosystem effect was driven by a change in the mean body size of dung beetles. Dung removal rates were strongly reduced when large dung beetles were experimentally excluded.
This study underscores that climate influences ecosystem functions mainly by modifying biodiversity and underpins the important role of body size for dung removal.
Despite sometimes strong codependencies of insect herbivores and plants, the responses of individual taxa to accelerating climate change are typically studied in isolation. For this reason, biotic interactions that potentially limit species in tracking their preferred climatic niches are ignored. Here, we chose butterflies as a prominent representative of herbivorous insects to investigate the impacts of temperature changes and their larval host plant distributions along a 1.4‐km elevational gradient in the German Alps. Following a sampling protocol of 2009, we revisited 33 grassland plots in 2019 over an entire growing season. We quantified changes in butterfly abundance and richness by repeated transect walks on each plot and disentangled the direct and indirect effects of locally assessed temperature, site management, and larval and adult food resource availability on these patterns. Additionally, we determined elevational range shifts of butterflies and host plants at both the community and species level. Comparing the two sampled years (2009 and 2019), we found a severe decline in butterfly abundance and a clear upward shift of butterflies along the elevational gradient. We detected shifts in the peak of species richness, community composition, and at the species level, whereby mountainous species shifted particularly strongly. In contrast, host plants showed barely any change, neither in connection with species richness nor individual species shifts. Further, temperature and host plant richness were the main drivers of butterfly richness, with change in temperature best explaining the change in richness over time. We concluded that host plants were not yet hindering butterfly species and communities from shifting upwards. However, the mismatch between butterfly and host plant shifts might become a problem for this very close plant–herbivore relationship, especially toward higher elevations, if butterflies fail to adapt to new host plants. Further, our results support the value of conserving traditional extensive pasture use as a promoter of host plant and, hence, butterfly richness.
Environmental gradients generate and maintain biodiversity on Earth. Mountain slopes are among the most pronounced terrestrial environmental gradients, and the elevational structure of species and their interactions can provide unique insight into the processes that govern community assembly and function in mountain ecosystems. We recorded bumble bee–flower interactions over 3 years along a 1400‐m elevational gradient in the German Alps. Using nonlinear modeling techniques, we analyzed elevational patterns at the levels of abundance, species richness, species β‐diversity, and interaction β‐diversity. Though floral richness exhibited a midelevation peak, bumble bee richness increased with elevation before leveling off at the highest sites, demonstrating the exceptional adaptation of these bees to cold temperatures and short growing seasons. In terms of abundance, though, bumble bees exhibited divergent species‐level responses to elevation, with a clear separation between species preferring low versus high elevations. Overall interaction β‐diversity was mainly caused by strong turnover in the floral community, which exhibited a well‐defined threshold of β‐diversity rate at the tree line ecotone. Interaction β‐diversity increased sharply at the upper extreme of the elevation gradient (1800–2000 m), an interval over which we also saw steep decline in floral richness and abundance. Turnover of bumble bees along the elevation gradient was modest, with the highest rate of β‐diversity occurring over the interval from low‐ to mid‐elevation sites. The contrast between the relative robustness bumble bee communities and sensitivity of plant communities to the elevational gradient in our study suggests that the strongest effects of climate change on mountain bumble bees may be indirect effects mediated by the responses of their floral hosts, though bumble bee species that specialize in high‐elevation habitats may also experience significant direct effects of warming.
Arthropod dark taxa provide new insights into diversity responses to bark beetle infestations
(2022)
Natural disturbances are increasing around the globe, also impacting protected areas. Although previous studies have indicated that natural disturbances result in mainly positive effects on biodiversity, these analyses mostly focused on a few well established taxonomic groups, and thus uncertainty remains regarding the comprehensive impact of natural disturbances on biodiversity. Using Malaise traps and meta‐barcoding, we studied a broad range of arthropod taxa, including dark and cryptic taxa, along a gradient of bark beetle disturbance severities in five European national parks. We identified order‐level community thresholds of disturbance severity and classified barcode index numbers (BINs; a cluster system for DNA sequences, where each cluster corresponds to a species) as negative or positive disturbance indicators. Negative indicator BINs decreased above thresholds of low to medium disturbance severity (20%–30% of trees killed), whereas positive indicator BINs benefited from high disturbance severity (76%–98%). BINs allocated to a species name contained nearly as many positive as negative disturbance indicators, but dark and cryptic taxa, particularly Diptera and Hymenoptera in our data, contained higher numbers of negative disturbance indicator BINs. Analyses of changes in the richness of BINs showed variable responses of arthropods to disturbance severity at lower taxonomic levels, whereas no significant signal was detected at the order level due to the compensatory responses of the underlying taxa. We conclude that the analyses of dark taxa can offer new insights into biodiversity responses to disturbances. Our results suggest considerable potential for forest management to foster arthropod diversity, for example by maintaining both closed‐canopy forests (>70% cover) and open forests (<30% cover) on the landscape.
The growing tips of plants grow sterile; therefore, disease-free plants can be generated from them. How plants safeguard growing apices from pathogen infection is still a mystery. The shoot apical meristem (SAM) is one of the three stem cells niches that give rise to the above ground plant organs. This is very well explored; however, how signaling networks orchestrate immune responses against pathogen infections in the SAM remains unclear. To reconstruct a transcriptional framework of the differentially expressed genes (DEGs) pertaining to various SAM cellular populations, we acquired large-scale transcriptome datasets from the public repository Gene Expression Omnibus (GEO). We identify here distinct sets of genes for various SAM cellular populations that are enriched in immune functions, such as immune defense, pathogen infection, biotic stress, and response to salicylic acid and jasmonic acid and their biosynthetic pathways in the SAM. We further linked those immune genes to their respective proteins and identify interactions among them by mapping a transcriptome-guided SAM-interactome. Furthermore, we compared stem-cells regulated transcriptome with innate immune responses in plants showing transcriptional separation among their DEGs in Arabidopsis. Besides unleashing a repertoire of immune-related genes in the SAM, our analysis provides a SAM-interactome that will help the community in designing functional experiments to study the specific defense dynamics of the SAM-cellular populations. Moreover, our study promotes the essence of large-scale omics data re-analysis, allowing a fresh look at the SAM-cellular transcriptome repurposing data-sets for new questions.
Animal-microbe mutualisms are typically maintained by vertical symbiont transmission or partner choice. A third mechanism, screening of high-quality symbionts, has been predicted in theory, but empirical examples are rare. Here we demonstrate that ambrosia beetles rely on ethanol within host trees for promoting gardens of their fungal symbiont and producing offspring. Ethanol has long been known as the main attractant for many of these fungus-farming beetles as they select host trees in which they excavate tunnels and cultivate fungal gardens. More than 300 attacks by Xylosandrus germanus and other species were triggered by baiting trees with ethanol lures, but none of the foundresses established fungal gardens or produced broods unless tree tissues contained in vivo ethanol resulting from irrigation with ethanol solutions. More X. germanus brood were also produced in a rearing substrate containing ethanol. These benefits are a result of increased food supply via the positive effects of ethanol on food-fungus biomass. Selected Ambrosiella and Raffaelea fungal isolates from ethanol-responsive ambrosia beetles profited directly and indirectly by (i) a higher biomass on medium containing ethanol, (ii) strong alcohol dehydrogenase enzymatic activity, and (iii) a competitive advantage over weedy fungal garden competitors (Aspergillus, Penicillium) that are inhibited by ethanol. As ambrosia fungi both detoxify and produce ethanol, they may maintain the selectivity of their alcohol-rich habitat for their own purpose and that of other ethanol-resistant/producing microbes. This resembles biological screening of beneficial symbionts and a potentially widespread, unstudied benefit of alcohol-producing symbionts (e.g., yeasts) in other microbial symbioses.
Comprehensive bioinformatics identifies key microRNA players in ATG7-deficient lung fibroblasts
(2020)
Background: Deficient autophagy has been recently implicated as a driver of pulmonary fibrosis, yet bioinformatics approaches to study this cellular process are lacking. Autophagy-related 5 and 7 (ATG5/ATG7) are critical elements of macro-autophagy. However, an alternative ATG5/ATG7-independent macro-autophagy pathway was recently discovered, its regulation being unknown. Using a bioinformatics proteome profiling analysis of ATG7-deficient human fibroblasts, we aimed to identify key microRNA (miR) regulators in autophagy. Method: We have generated ATG7-knockout MRC-5 fibroblasts and performed mass spectrometry to generate a large-scale proteomics dataset. We further quantified the interactions between various proteins combining bioinformatics molecular network reconstruction and functional enrichment analysis. The predicted key regulatory miRs were validated via quantitative polymerase chain reaction. Results: The functional enrichment analysis of the 26 deregulated proteins showed decreased cellular trafficking, increased mitophagy and senescence as the major overarching processes in ATG7-deficient lung fibroblasts. The 26 proteins reconstitute a protein interactome of 46 nodes and miR-regulated interactome of 834 nodes. The miR network shows three functional cluster modules around miR-16-5p, miR-17-5p and let-7a-5p related to multiple deregulated proteins. Confirming these results in a biological setting, serially passaged wild-type and autophagy-deficient fibroblasts displayed senescence-dependent expression profiles of miR-16-5p and miR-17-5p. Conclusions: We have developed a bioinformatics proteome profiling approach that successfully identifies biologically relevant miR regulators from a proteomics dataset of the ATG-7-deficient milieu in lung fibroblasts, and thus may be used to elucidate key molecular players in complex fibrotic pathological processes. The approach is not limited to a specific cell-type and disease, thus highlighting its high relevance in proteome and non-coding RNA research.
CDC14A encodes the Cell Division Cycle 14A protein and has been associated with autosomal recessive non-syndromic hearing loss (DFNB32), as well as hearing impairment and infertile male syndrome (HIIMS) since 2016. To date, only nine variants have been associated in patients whose initial symptoms included moderate-to-profound hearing impairment. Exome analysis of Iranian and Pakistani probands who both showed bilateral, sensorineural hearing loss revealed a novel splice site variant (c.1421+2T>C, p.?) that disrupts the splice donor site and a novel frameshift variant (c.1041dup, p.Ser348Glnfs*2) in the gene CDC14A, respectively. To evaluate the pathogenicity of both loss-of-function variants, we analyzed the effects of both variants on the RNA-level. The splice variant was characterized using a minigene assay. Altered expression levels due to the c.1041dup variant were assessed using RT-qPCR. In summary, cDNA analysis confirmed that the c.1421+2T>C variant activates a cryptic splice site, resulting in a truncated transcript (c.1414_1421del, p.Val472Leufs*20) and the c.1041dup variant results in a defective transcript that is likely degraded by nonsense-mediated mRNA decay. The present study functionally characterizes two variants and provides further confirmatory evidence that CDC14A is associated with a rare form of hereditary hearing loss.
Mathematical optimization framework allows the identification of certain nodes within a signaling network. In this work, we analyzed the complex extracellular-signal-regulated kinase 1 and 2 (ERK1/2) cascade in cardiomyocytes using the framework to find efficient adjustment screws for this cascade that is important for cardiomyocyte survival and maladaptive heart muscle growth. We modeled optimal pharmacological intervention points that are beneficial for the heart, but avoid the occurrence of a maladaptive ERK1/2 modification, the autophosphorylation of ERK at threonine 188 (ERK\(^{Thr188}\) phosphorylation), which causes cardiac hypertrophy. For this purpose, a network of a cardiomyocyte that was fitted to experimental data was equipped with external stimuli that model the pharmacological intervention points. Specifically, two situations were considered. In the first one, the cardiomyocyte was driven to a desired expression level with different treatment strategies. These strategies were quantified with respect to beneficial effects and maleficent side effects and then which one is the best treatment strategy was evaluated. In the second situation, it was shown how to model constitutively activated pathways and how to identify drug targets to obtain a desired activity level that is associated with a healthy state and in contrast to the maleficent expression pattern caused by the constitutively activated pathway. An implementation of the algorithms used for the calculations is also presented in this paper, which simplifies the application of the presented framework for drug targeting, optimal drug combinations and the systematic and automatic search for pharmacological intervention points. The codes were designed such that they can be combined with any mathematical model given by ordinary differential equations.
For all animals the cold represents a dreadful danger. In the event of severe heat loss, animals
fall into a chill coma. If this state persists, it is inevitably followed by death. In poikilotherms
(e.g. insects), the optimal temperature range is narrow compared to homeotherms
(e.g. mammals), resulting in a critical core temperature being reached more quickly. As a
consequence, poikilotherms either had to develop survival strategies, migrate or die. Unlike
the majority of insects, the Western honeybee (Apis mellifera) is able to organize itself into
a superorganism. In this process, worker bees warm and cool the colony by coordinated
use of their flight muscles. This enables precise control of the core temperature in the hive,
analogous to the core body temperature in homeothermic animals. However, to survive the
harsh temperatures in the northern hemisphere, the thermogenic mechanism of honeybees
must be in constant readiness. This mechanism is called shivering thermogenesis, in which
honeybees generate heat using their flight muscles.
My thesis presents the molecular and neurochemical background underlying shivering thermogenesis
in worker honeybees. In this context, I investigated biogenic amine signaling.
I found that the depletion of vesicular monoamines impairs thermogenesis, resulting in
a decrease in thoracic temperature. Subsequent investigations involving various biogenic
amines showed that octopamine can reverse this effect. This clearly indicates the involvement
of the octopaminergic system. Proceeding from these results, the next step was to elucidate
the honeybee thoracic octopaminergic system. This required a multidisciplinary approach to
ultimately provide profound insights into the function and action of octopamine at the flight
muscles. This led to the identification of octopaminergic flight muscle controlling neurons,
which presumably transport octopamine to the flight muscle release sites. These neurons
most likely innervate octopamine β receptors and their activation may stimulate intracellular
glycolytic pathways, which ensure sufficient energy supply to the muscles.
Next, I examined the response of the thoracic octopaminergic system to cold stress conditions.
I found that the thoracic octopaminergic system tends towards an equilibrium,
even though the initial stress response leads to fluctuations of octopamine signaling. My
results indicate the importance of the neuro-muscular octopaminergic system and thus the need for its robustness. Moreover, cold sensitivity was observed for the expression of one
transcript of the octopamine receptor gene AmOARβ2. Furthermore, I found that honeybees
without colony context show a physiological disruption within the octopaminergic system.
This disruption has profound effects on the honeybees protection against the cold.
I could show how important the neuro-muscular octopaminergic system is for thermogenesis
in honeybees. In this context, the previously unknown neurochemical modulation of the
honeybee thorax has now been revealed. I also provide a broad basis to conduct further
experiments regarding honeybee thermogenesis and muscle physiology.
Alterations to the gene encoding the EZH2 (KMT6A) methyltransferase, including both gain-of-function and loss-of-function, have been linked to a variety of haematological malignancies and solid tumours, suggesting a complex, context-dependent role of this methyltransferase. The successful implementation of molecularly targeted therapies against EZH2 requires a greater understanding of the potential mechanisms by which EZH2 contributes to cancer. One aspect of this effort is the mapping of EZH2 partner proteins and cellular targets. To this end we performed affinity-purification mass spectrometry in the FAB-M2 HL-60 acute myeloid leukaemia (AML) cell line before and after all-trans retinoic acid-induced differentiation. These studies identified new EZH2 interaction partners and potential non-histone substrates for EZH2-mediated methylation. Our results suggest that EZH2 is involved in the regulation of translation through interactions with a number of RNA binding proteins and by methylating key components of protein synthesis such as eEF1A1. Given that deregulated mRNA translation is a frequent feature of cancer and that eEF1A1 is highly expressed in many human tumours, these findings present new possibilities for the therapeutic targeting of EZH2 in AML.
Fungi possess diverse photosensory proteins that allow them to perceive different light wavelengths and to adapt to changing light conditions in their environment. The biological and physiological roles of the green light-sensing rhodopsins in fungi are not yet resolved. The rice plant pathogen Fusarium fujikuroi exhibits two different rhodopsins, CarO and OpsA. CarO was previously characterized as a light-driven proton pump. We further analyzed the pumping behavior of CarO by patch-clamp experiments. Our data show that CarO pumping activity is strongly augmented in the presence of the plant hormone indole-3-acetic acid and in sodium acetate, in a dose-dependent manner under slightly acidic conditions. By contrast, under these and other tested conditions, the Neurospora rhodopsin (NR)-like rhodopsin OpsA did not exhibit any pump activity. Basic local alignment search tool (BLAST) searches in the genomes of ascomycetes revealed the occurrence of rhodopsin-encoding genes mainly in phyto-associated or phytopathogenic fungi, suggesting a possible correlation of the presence of rhodopsins with fungal ecology. In accordance, rice plants infected with a CarO-deficient F. fujikuroi strain showed more severe bakanae symptoms than the reference strain, indicating a potential role of the CarO rhodopsin in the regulation of plant infection by this fungus.
The fusion of methods from several disciplines is a crucial component of scientific development. Artificial Neural Networks, based on the principle of biological neuronal networks, demonstrate how nature provides the best templates for technological advancement. These innovations can then be employed to solve the remaining mysteries of biology, including, in particular, processes that take place on microscopic scales and can only be studied with sophisticated techniques. For instance, direct Stochastic Optical Reconstruction Microscopy combines tools from chemistry, physics, and computer science to visualize biological processes at the molecular level. One of the key components is the computer-aided reconstruction of super-resolved images. Improving the corresponding algorithms increases the quality of the generated data, providing further insights into our biology. It is important, however, to ensure that the heavily processed images are still a reflection of reality and do not originate in random artefacts.
Expansion microscopy is expanding the sample by embedding it in a swellable hydrogel. The method can be combined with other super-resolution techniques to gain additional resolution. We tested this approach on microtubules, a well-known filamentous reference structure, to evaluate the performance of different protocols and labelling techniques.
We developed LineProfiler an objective tool for data collection. Instead of collecting perpendicular profiles in small areas, the software gathers line profiles from filamentous structures of the entire image. This improves data quantity, quality and prevents a biased choice of the evaluated regions. On the basis of the collected data, we deployed theoretical models of the expected intensity distribution across the filaments. This led to the conclusion that post-expansion labelling significantly reduces the labelling error and thus, improves the data quality. The software was further used to determine the expansion factor and arrangement of synaptonemal complex data.
Automated Simple Elastix uses state-of-the-art image alignment to compare pre- and post-expansion images. It corrects linear distortions occurring under isotropic expansion, calculates a structural expansion factor and highlights structural mismatches in a distortion map. We used the software to evaluate expanded fungi and NK cells. We found that the expansion factor differs for the two structures and is lower than the overall expansion of the hydrogel.
Assessing the fluorescence lifetime of emitters used for direct Stochastic Optical Reconstruction Microscopy can reveal additional information about the molecular environment or distinguish dyes emitting with a similar wavelength. The corresponding measurements require a confocal scanning of the sample in combination with the fluorescent switching of the underlying emitters. This leads to non-linear, interrupted Point Spread Functions. The software ReCSAI targets this problem by combining the classical algorithm of compressed sensing with modern methods of artificial intelligence. We evaluated several different approaches to combine these components and found, that unrolling compressed sensing into the network architecture yields the best performance in terms of reconstruction speed and accuracy.
In addition to a deep insight into the functioning and learning of artificial intelligence in combination with classical algorithms, we were able to reconstruct the described non-linearities with significantly improved resolution, in comparison to other state-of-the-art architectures.
Automatic image reconstruction is critical to cope with steadily increasing data from advanced microscopy. We describe here the Fiji macro 3D ART VeSElecT which we developed to study synaptic vesicles in electron tomograms. We apply this tool to quantify vesicle properties (i) in embryonic Danio rerio 4 and 8 days past fertilization (dpf) and (ii) to compare Caenorhabditis elegans N2 neuromuscular junctions (NMJ) wild-type and its septin mutant (unc-59(e261)). We demonstrate development-specific and mutant-specific changes in synaptic vesicle pools in both models. We confirm the functionality of our macro by applying our 3D ART VeSElecT on zebrafish NMJ showing smaller vesicles in 8 dpf embryos then 4 dpf, which was validated by manual reconstruction of the vesicle pool. Furthermore, we analyze the impact of C. elegans septin mutant unc-59(e261) on vesicle pool formation and vesicle size. Automated vesicle registration and characterization was implemented in Fiji as two macros (registration and measurement). This flexible arrangement allows in particular reducing false positives by an optional manual revision step. Preprocessing and contrast enhancement work on image-stacks of 1nm/pixel in x and y direction. Semi-automated cell selection was integrated. 3D ART VeSElecT removes interfering components, detects vesicles by 3D segmentation and calculates vesicle volume and diameter (spherical approximation, inner/outer diameter). Results are collected in color using the RoiManager plugin including the possibility of manual removal of non-matching confounder vesicles. Detailed evaluation considered performance (detected vesicles) and specificity (true vesicles) as well as precision and recall. We furthermore show gain in segmentation and morphological filtering compared to learning based methods and a large time gain compared to manual segmentation. 3D ART VeSElecT shows small error rates and its speed gain can be up to 68 times faster in comparison to manual annotation. Both automatic and semi-automatic modes are explained including a tutorial.