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PRO-Simat is a simulation tool for analysing protein interaction networks, their dynamic change and pathway engineering. It provides GO enrichment, KEGG pathway analyses, and network visualisation from an integrated database of more than 8 million protein-protein interactions across 32 model organisms and the human proteome. We integrated dynamical network simulation using the Jimena framework, which quickly and efficiently simulates Boolean genetic regulatory networks. It enables simulation outputs with in-depth analysis of the type, strength, duration and pathway of the protein interactions on the website. Furthermore, the user can efficiently edit and analyse the effect of network modifications and engineering experiments. In case studies, applications of PRO-Simat are demonstrated: (i) understanding mutually exclusive differentiation pathways in Bacillus subtilis, (ii) making Vaccinia virus oncolytic by switching on its viral replication mainly in cancer cells and triggering cancer cell apoptosis and (iii) optogenetic control of nucleotide processing protein networks to operate DNA storage. Multilevel communication between components is critical for efficient network switching, as demonstrated by a general census on prokaryotic and eukaryotic networks and comparing design with synthetic networks using PRO-Simat. The tool is available at https://prosimat.heinzelab.de/ as a web-based query server.
Formic acid is the main component of the ant’s major weapon against enemies. Being mainly used as a chemical defense, the acid is also exploited for recruitment and trail marking. The repelling effect of the organic acid is used by some mammals and birds which rub themselves in the acid to eliminate ectoparasites. Beekeepers across the world rely on this effect to control the parasitic mite Varroa destructor. Varroa mites are considered the most destructive pest of honey bees worldwide and can lead to the loss of entire colonies. Formic acid is highly effective against Varroa mites but can also kill the honeybee queen and worker brood. Whether formic acid can also affect the behavior of honey bees is unknown. We here study the effect of formic acid on sucrose responsiveness and cognition of honey bees treated at different live stages in field-relevant doses. Both behaviors are essential for survival of the honey bee colony. Rather unexpectedly, formic acid clearly improved the learning performance of the bees in appetitive olfactory conditioning, while not affecting sucrose responsiveness. This exciting side effect of formic acid certainly deserves further detailed investigations.
Immune checkpoint blockade therapy is beneficial and even curative for some cancer patients. However, the majority don’t respond to immune therapy. Across different tumor types, pre-existing T cell infiltrates predict response to checkpoint-based immunotherapy. Based on in vitro pharmacological studies, mouse models and analyses of human melanoma patients, we show that the cytokine GDF-15 impairs LFA-1/β2-integrin-mediated adhesion of T cells to activated endothelial cells, which is a pre-requisite of T cell extravasation. In melanoma patients, GDF-15 serum levels strongly correlate with failure of PD-1-based immune checkpoint blockade therapy. Neutralization of GDF-15 improves both T cell trafficking and therapy efficiency in murine tumor models. Thus GDF-15, beside its known role in cancer-related anorexia and cachexia, emerges as a regulator of T cell extravasation into the tumor microenvironment, which provides an even stronger rationale for therapeutic anti-GDF-15 antibody development.
The neuronal RNA-binding protein Ptbp2 regulates neuronal differentiation by modulating alternative splicing programs in the nucleus. Such programs contribute to axonogenesis by adjusting the levels of protein isoforms involved in axon growth and branching. While its functions in alternative splicing have been described in detail, cytosolic roles of Ptbp2 for axon growth have remained elusive. Here, we show that Ptbp2 is located in the cytosol including axons and growth cones of motoneurons, and that depletion of cytosolic Ptbp2 affects axon growth. We identify Ptbp2 as a major interactor of the 3’ UTR of Hnrnpr mRNA encoding the RNA-binding protein hnRNP R. Axonal localization of Hnrnpr mRNA and local synthesis of hnRNP R protein are strongly reduced when Ptbp2 is depleted, leading to defective axon growth. Ptbp2 regulates hnRNP R translation by mediating the association of Hnrnpr with ribosomes in a manner dependent on the translation factor eIF5A2. Our data thus suggest a mechanism whereby cytosolic Ptbp2 modulates axon growth by fine-tuning the mRNA transport and local synthesis of an RNA-binding protein.
Herpes simplex virus 1 (HSV-1) infection and stress responses disrupt transcription termination by RNA Polymerase II (Pol II). In HSV-1 infection, but not upon salt or heat stress, this is accompanied by a dramatic increase in chromatin accessibility downstream of genes. Here, we show that the HSV-1 immediate-early protein ICP22 is both necessary and sufficient to induce downstream open chromatin regions (dOCRs) when transcription termination is disrupted by the viral ICP27 protein. This is accompanied by a marked ICP22-dependent loss of histones downstream of affected genes consistent with impaired histone repositioning in the wake of Pol II. Efficient knock-down of the ICP22-interacting histone chaperone FACT is not sufficient to induce dOCRs in ΔICP22 infection but increases dOCR induction in wild-type HSV-1 infection. Interestingly, this is accompanied by a marked increase in chromatin accessibility within gene bodies. We propose a model in which allosteric changes in Pol II composition downstream of genes and ICP22-mediated interference with FACT activity explain the differential impairment of histone repositioning downstream of genes in the wake of Pol II in HSV-1 infection.
Tropical forest recovery is fundamental to addressing the intertwined climate and biodiversity loss crises. While regenerating trees sequester carbon relatively quickly, the pace of biodiversity recovery remains contentious. Here, we use bioacoustics and metabarcoding to measure forest recovery post-agriculture in a global biodiversity hotspot in Ecuador. We show that the community composition, and not species richness, of vocalizing vertebrates identified by experts reflects the restoration gradient. Two automated measures – an acoustic index model and a bird community composition derived from an independently developed Convolutional Neural Network - correlated well with restoration (adj-R² = 0.62 and 0.69, respectively). Importantly, both measures reflected composition of non-vocalizing nocturnal insects identified via metabarcoding. We show that such automated monitoring tools, based on new technologies, can effectively monitor the success of forest recovery, using robust and reproducible data.
Neural processing of a desired moving direction requires the continuous comparison between the current heading and the goal direction. While the neural basis underlying the current heading is well-studied, the coding of the goal direction remains unclear in insects. Here, we used tetrode recordings in tethered flying monarch butterflies to unravel how a goal direction is represented in the insect brain. While recording, the butterflies maintained robust goal directions relative to a virtual sun. By resetting their goal directions, we found neurons whose spatial tuning was tightly linked to the goal directions. Importantly, their tuning was unaffected when the butterflies changed their heading after compass perturbations, showing that these neurons specifically encode the goal direction. Overall, we here discovered invertebrate goal-direction neurons that share functional similarities to goal-direction cells reported in mammals. Our results give insights into the evolutionarily conserved principles of goal-directed spatial orientation in animals.
Rapid and accurate yield estimates at both field and regional levels remain the goal of sustainable agriculture and food security. Hereby, the identification of consistent and reliable methodologies providing accurate yield predictions is one of the hot topics in agricultural research. This study investigated the relationship of spatiotemporal fusion modelling using STRAFM on crop yield prediction for winter wheat (WW) and oil-seed rape (OSR) using a semi-empirical light use efficiency (LUE) model for the Free State of Bavaria (70,550 km\(^2\)), Germany, from 2001 to 2019. A synthetic normalised difference vegetation index (NDVI) time series was generated and validated by fusing the high spatial resolution (30 m, 16 days) Landsat 5 Thematic Mapper (TM) (2001 to 2012), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) (2012), and Landsat 8 Operational Land Imager (OLI) (2013 to 2019) with the coarse resolution of MOD13Q1 (250 m, 16 days) from 2001 to 2019. Except for some temporal periods (i.e., 2001, 2002, and 2012), the study obtained an R\(^2\) of more than 0.65 and a RMSE of less than 0.11, which proves that the Landsat 8 OLI fused products are of higher accuracy than the Landsat 5 TM products. Moreover, the accuracies of the NDVI fusion data have been found to correlate with the total number of available Landsat scenes every year (N), with a correlation coefficient (R) of +0.83 (between R\(^2\) of yearly synthetic NDVIs and N) and −0.84 (between RMSEs and N). For crop yield prediction, the synthetic NDVI time series and climate elements (such as minimum temperature, maximum temperature, relative humidity, evaporation, transpiration, and solar radiation) are inputted to the LUE model, resulting in an average R\(^2\) of 0.75 (WW) and 0.73 (OSR), and RMSEs of 4.33 dt/ha and 2.19 dt/ha. The yield prediction results prove the consistency and stability of the LUE model for yield estimation. Using the LUE model, accurate crop yield predictions were obtained for WW (R\(^2\) = 0.88) and OSR (R\(^2\) = 0.74). Lastly, the study observed a high positive correlation of R = 0.81 and R = 0.77 between the yearly R\(^2\) of synthetic accuracy and modelled yield accuracy for WW and OSR, respectively.
Recently, we have shown that C6-ceramides efficiently suppress viral replication by trapping the virus in lysosomes. Here, we use antiviral assays to evaluate a synthetic ceramide derivative α-NH2-ω-N3-C6-ceramide (AKS461) and to confirm the biological activity of C6-ceramides inhibiting SARS-CoV-2. Click-labeling with a fluorophore demonstrated that AKS461 accumulates in lysosomes. Previously, it has been shown that suppression of SARS-CoV-2 replication can be cell-type specific. Thus, AKS461 inhibited SARS-CoV-2 replication in Huh-7, Vero, and Calu-3 cells up to 2.5 orders of magnitude. The results were confirmed by CoronaFISH, indicating that AKS461 acts comparable to the unmodified C6-ceramide. Thus, AKS461 serves as a tool to study ceramide-associated cellular and viral pathways, such as SARS-CoV-2 infections, and it helped to identify lysosomes as the central organelle of C6-ceramides to inhibit viral replication.
Infected wounds pose a major mortality risk in animals. Injuries are common in the ant Megaponera analis, which raids pugnacious prey. Here we show that M. analis can determine when wounds are infected and treat them accordingly. By applying a variety of antimicrobial compounds and proteins secreted from the metapleural gland to infected wounds, workers reduce the mortality of infected individuals by 90%. Chemical analyses showed that wound infection is associated with specific changes in the cuticular hydrocarbon profile, thereby likely allowing nestmates to diagnose the infection state of injured individuals and apply the appropriate antimicrobial treatment. This study demonstrates that M. analis ant societies use antimicrobial compounds produced in the metapleural glands to treat infected wounds and reduce nestmate mortality.
Seasonal plasticity in insects is often triggered by temperature and photoperiod changes. When climatic conditions become sub-optimal, insects might undergo reproductive diapause, a form of seasonal plasticity delaying the development of reproductive organs and activities. During the reproductive diapause, the cuticular hydrocarbon (CHC) profile, which covers the insect body surface, might also change to protect insects from desiccation and cold temperature. However, CHCs are often important cues and signals for mate recognition and changes in CHC composition might affect mate recognition. In the present study, we investigated the CHC profile composition and the mating success of Drosophila suzukii in 1- and 5-day-old males and females of summer and winter morphs. CHC compositions differed with age and morphs. However, no significant differences were found between the sexes of the same age and morph. The results of the behavioral assays show that summer morph pairs start to mate earlier in their life, have a shorter mating duration, and have more offspring compared to winter morph pairs. We hypothesize that CHC profiles of winter morphs are adapted to survive winter conditions, potentially at the cost of reduced mate recognition cues.
T cell exhaustion is a hallmark of cancer and persistent infections, marked by inhibitory receptor upregulation, diminished cytokine secretion, and impaired cytolytic activity. Terminally exhausted T cells are steadily replenished by a precursor population (Tpex), but the metabolic principles governing Tpex maintenance and the regulatory circuits that control their exhaustion remain incompletely understood. Using a combination of gene-deficient mice, single-cell transcriptomics, and metabolomic analyses, we show that mitochondrial insufficiency is a cell-intrinsic trigger that initiates the functional exhaustion of T cells. At the molecular level, we find that mitochondrial dysfunction causes redox stress, which inhibits the proteasomal degradation of hypoxia-inducible factor 1α (HIF-1α) and promotes the transcriptional and metabolic reprogramming of Tpex cells into terminally exhausted T cells. Our findings also bear clinical significance, as metabolic engineering of chimeric antigen receptor (CAR) T cells is a promising strategy to enhance the stemness and functionality of Tpex cells for cancer immunotherapy.
Machine learning techniques are excellent to analyze expression data from single cells. These techniques impact all fields ranging from cell annotation and clustering to signature identification. The presented framework evaluates gene selection sets how far they optimally separate defined phenotypes or cell groups. This innovation overcomes the present limitation to objectively and correctly identify a small gene set of high information content regarding separating phenotypes for which corresponding code scripts are provided. The small but meaningful subset of the original genes (or feature space) facilitates human interpretability of the differences of the phenotypes including those found by machine learning results and may even turn correlations between genes and phenotypes into a causal explanation. For the feature selection task, the principal feature analysis is utilized which reduces redundant information while selecting genes that carry the information for separating the phenotypes. In this context, the presented framework shows explainability of unsupervised learning as it reveals cell-type specific signatures. Apart from a Seurat preprocessing tool and the PFA script, the pipeline uses mutual information to balance accuracy and size of the gene set if desired. A validation part to evaluate the gene selection for their information content regarding the separation of the phenotypes is provided as well, binary and multiclass classification of 3 or 4 groups are studied. Results from different single-cell data are presented. In each, only about ten out of more than 30000 genes are identified as carrying the relevant information. The code is provided in a GitHub repository at https://github.com/AC-PHD/Seurat_PFA_pipeline.
In the fast-evolving landscape of biomedical research, the emergence of big data has presented researchers with extraordinary opportunities to explore biological complexities. In biomedical research, big data imply also a big responsibility. This is not only due to genomics data being sensitive information but also due to genomics data being shared and re-analysed among the scientific community. This saves valuable resources and can even help to find new insights in silico. To fully use these opportunities, detailed and correct metadata are imperative. This includes not only the availability of metadata but also their correctness. Metadata integrity serves as a fundamental determinant of research credibility, supporting the reliability and reproducibility of data-driven findings. Ensuring metadata availability, curation, and accuracy are therefore essential for bioinformatic research. Not only must metadata be readily available, but they must also be meticulously curated and ideally error-free. Motivated by an accidental discovery of a critical metadata error in patient data published in two high-impact journals, we aim to raise awareness for the need of correct, complete, and curated metadata. We describe how the metadata error was found, addressed, and present examples for metadata-related challenges in omics research, along with supporting measures, including tools for checking metadata and software to facilitate various steps from data analysis to published research.
Highlights
• Data awareness and data integrity underpins the trustworthiness of results and subsequent further analysis.
• Big data and bioinformatics enable efficient resource use by repurposing publicly available RNA-Sequencing data.
• Manual checks of data quality and integrity are insufficient due to the overwhelming volume and rapidly growing data.
• Automation and artificial intelligence provide cost-effective and efficient solutions for data integrity and quality checks.
• FAIR data management, various software solutions and analysis tools assist metadata maintenance.
Infection research largely relies on classical cell culture or mouse models. Despite having delivered invaluable insights into host-pathogen interactions, both have limitations in translating mechanistic principles to human pathologies. Alternatives can be derived from modern Tissue Engineering approaches, allowing the reconstruction of functional tissue models in vitro. Here, we combined a biological extracellular matrix with primary tissue-derived enteroids to establish an in vitro model of the human small intestinal epithelium exhibiting in vivo-like characteristics. Using the foodborne pathogen Salmonella enterica serovar Typhimurium, we demonstrated the applicability of our model to enteric infection research in the human context. Infection assays coupled to spatio-temporal readouts recapitulated the established key steps of epithelial infection by this pathogen in our model. Besides, we detected the upregulation of olfactomedin 4 in infected cells, a hitherto unrecognized aspect of the host response to Salmonella infection. Together, this primary human small intestinal tissue model fills the gap between simplistic cell culture and animal models of infection, and shall prove valuable in uncovering human-specific features of host-pathogen interplay.
CRISPR/Cas9 gene editing has revolutionised loss-of-function experiments in Leishmania, the causative agent of leishmaniasis. As Leishmania lack a functional non-homologous DNA end joining pathway however, obtaining null mutants typically requires additional donor DNA, selection of drug resistance-associated edits or time-consuming isolation of clones. Genome-wide loss-of-function screens across different conditions and across multiple Leishmania species are therefore unfeasible at present. Here, we report a CRISPR/Cas9 cytosine base editor (CBE) toolbox that overcomes these limitations. We employed CBEs in Leishmania to introduce STOP codons by converting cytosine into thymine and created http://www.leishbaseedit.net/ for CBE primer design in kinetoplastids. Through reporter assays and by targeting single- and multi-copy genes in L. mexicana, L. major, L. donovani, and L. infantum, we demonstrate how this tool can efficiently generate functional null mutants by expressing just one single-guide RNA, reaching up to 100% editing rate in non-clonal populations. We then generated a Leishmania-optimised CBE and successfully targeted an essential gene in a plasmid library delivered loss-of-function screen in L. mexicana. Since our method does not require DNA double-strand breaks, homologous recombination, donor DNA, or isolation of clones, we believe that this enables for the first time functional genetic screens in Leishmania via delivery of plasmid libraries.
Alpine bumble bees are the most important pollinators in temperate mountain ecosystems. Although they are used to encounter small-scale successions of very different climates in the mountains, many species respond sensitively to climatic changes, reflected in spatial range shifts and declining populations worldwide. Cuticular hydrocarbons (CHCs) mediate climate adaptation in some insects. However, whether they predict the elevational niche of bumble bees or their responses to climatic changes remains poorly understood. Here, we used three different approaches to study the role of bumble bees’ CHCs in the context of climate adaptation: using a 1,300 m elevational gradient, we first investigated whether the overall composition of CHCs, and two potentially climate-associated chemical traits (proportion of saturated components, mean chain length) on the cuticle of six bumble bee species were linked to the species’ elevational niches. We then analyzed intraspecific variation in CHCs of Bombus pascuorum along the elevational gradient and tested whether these traits respond to temperature. Finally, we used a field translocation experiment to test whether CHCs of Bombus lucorum workers change, when translocated from the foothill of a cool and wet mountain region to (a) higher elevations, and (b) a warm and dry region. Overall, the six species showed distinctive, species-specific CHC profiles. We found inter- and intraspecific variation in the composition of CHCs and in chemical traits along the elevational gradient, but no link to the elevational distribution of species and individuals. According to our expectations, bumble bees translocated to a warm and dry region tended to express longer CHC chains than bumble bees translocated to cool and wet foothills, which could reflect an acclimatization to regional climate. However, chain lengths did not further decrease systematically along the elevational gradient, suggesting that other factors than temperature also shape chain lengths in CHC profiles. We conclude that in alpine bumble bees, CHC profiles and traits respond at best secondarily to the climate conditions tested in this study. While the functional role of species-specific CHC profiles in bumble bees remains elusive, limited plasticity in this trait could restrict species’ ability to adapt to climatic changes.
Xiphophorus fish exhibit a clear phenotypic polymorphism in puberty onset and reproductive strategies of males. In X. nigrensis and X. multilineatus, puberty onset is genetically determined and linked to a melanocortin 4 receptor (Mc4r) polymorphism of wild-type and mutant alleles on the sex chromosomes. We hypothesized that Mc4r mutant alleles act on wild-type alleles by a dominant negative effect through receptor dimerization, leading to differential intracellular signaling and effector gene activation. Depending on signaling strength, the onset of puberty either occurs early or is delayed. Here, we show by Förster Resonance Energy Transfer (FRET) that wild-type Xiphophorus Mc4r monomers can form homodimers, but also heterodimers with mutant receptors resulting in compromised signaling which explains the reduced Mc4r signaling in large males. Thus, hetero- vs. homo- dimerization seems to be the key molecular mechanism for the polymorphism in puberty onset and body size in male fish.
Fungal infections are a major global health burden where Candida albicans is among the most common fungal pathogen in humans and is a common cause of invasive candidiasis. Fungal phenotypes, such as those related to morphology, proliferation and virulence are mainly driven by gene expression, which is primarily regulated by kinase signaling cascades. Serine-arginine (SR) protein kinases are highly conserved among eukaryotes and are involved in major transcriptional processes in human and S. cerevisiae. Candida albicans harbors two SR protein kinases, while Sky2 is important for metabolic adaptation, Sky1 has similar functions as in S. cerevisiae. To investigate the role of these SR kinases for the regulation of transcriptional responses in C. albicans, we performed RNA sequencing of sky1Δ and sky2Δ and integrated a comprehensive phosphoproteome dataset of these mutants. Using a Systems Biology approach, we study transcriptional regulation in the context of kinase signaling networks. Transcriptomic enrichment analysis indicates that pathways involved in the regulation of gene expression are downregulated and mitochondrial processes are upregulated in sky1Δ. In sky2Δ, primarily metabolic processes are affected, especially for arginine, and we observed that arginine-induced hyphae formation is impaired in sky2Δ. In addition, our analysis identifies several transcription factors as potential drivers of the transcriptional response. Among these, a core set is shared between both kinase knockouts, but it appears to regulate different subsets of target genes. To elucidate these diverse regulatory patterns, we created network modules by integrating the data of site-specific protein phosphorylation and gene expression with kinase-substrate predictions and protein-protein interactions. These integrated signaling modules reveal shared parts but also highlight specific patterns characteristic for each kinase. Interestingly, the modules contain many proteins involved in fungal morphogenesis and stress response. Accordingly, experimental phenotyping shows a higher resistance to Hygromycin B for sky1Δ. Thus, our study demonstrates that a combination of computational approaches with integration of experimental data can offer a new systems biological perspective on the complex network of signaling and transcription. With that, the investigation of the interface between signaling and transcriptional regulation in C. albicans provides a deeper insight into how cellular mechanisms can shape the phenotype.
Highlights
• The integrated stress response leads to a general ATF4-dependent activation of NRF2
• ATF4 causes a CHAC1-dependent GSH depletion, resulting in NRF2 stabilization
• An elevation of NRF2 transcript levels fosters this effect
• NRF2 supports the ISR/ATF4 pathway by improving cystine and antioxidant supply
Summary
The redox regulator NRF2 becomes activated upon oxidative and electrophilic stress and orchestrates a response program associated with redox regulation, metabolism, tumor therapy resistance, and immune suppression. Here, we describe an unrecognized link between the integrated stress response (ISR) and NRF2 mediated by the ISR effector ATF4. The ISR is commonly activated after starvation or ER stress and plays a central role in tissue homeostasis and cancer plasticity. ATF4 increases NRF2 transcription and induces the glutathione-degrading enzyme CHAC1, which we now show to be critically important for maintaining NRF2 activation. In-depth analyses reveal that NRF2 supports ATF4-induced cells by increasing cystine uptake via the glutamate-cystine antiporter xCT. In addition, NRF2 upregulates genes mediating thioredoxin usage and regeneration, thus balancing the glutathione decrease. In conclusion, we demonstrate that the NRF2 response serves as second layer of the ISR, an observation highly relevant for the understanding of cellular resilience in health and disease.
Small bacterial regulatory RNAs (sRNAs) have been implicated in the regulation of numerous metabolic pathways. In most of these studies, sRNA-dependent regulation of mRNAs or proteins of enzymes in metabolic pathways has been predicted to affect the metabolism of these bacteria. However, only in a very few cases has the role in metabolism been demonstrated. Here, we performed a combined transcriptome and metabolome analysis to define the regulon of the sibling sRNAs NgncR_162 and NgncR_163 (NgncR_162/163) and their impact on the metabolism of Neisseria gonorrhoeae. These sRNAs have been reported to control genes of the citric acid and methylcitric acid cycles by posttranscriptional negative regulation. By transcriptome analysis, we now expand the NgncR_162/163 regulon by several new members and provide evidence that the sibling sRNAs act as both negative and positive regulators of target gene expression. Newly identified NgncR_162/163 targets are mostly involved in transport processes, especially in the uptake of glycine, phenylalanine, and branched-chain amino acids. NgncR_162/163 also play key roles in the control of serine-glycine metabolism and, hence, probably affect biosyntheses of nucleotides, vitamins, and other amino acids via the supply of one-carbon (C\(_1\)) units. Indeed, these roles were confirmed by metabolomics and metabolic flux analysis, which revealed a bipartite metabolic network with glucose degradation for the supply of anabolic pathways and the usage of amino acids via the citric acid cycle for energy metabolism. Thus, by combined deep RNA sequencing (RNA-seq) and metabolomics, we significantly extended the regulon of NgncR_162/163 and demonstrated the role of NgncR_162/163 in the regulation of central metabolic pathways of the gonococcus.
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.
Aim
Global warming is assumed to restructure mountain insect communities in space and time. Theory and observations along climate gradients predict that insect abundance and richness, especially of small‐bodied species, will increase with increasing temperature. However, the specific responses of single species to rising temperatures, such as spatial range shifts, also alter communities, calling for intensive monitoring of real‐world communities over time.
Location
German Alps and pre‐alpine forests in south‐east Germany.
Methods
We empirically examined the temporal and spatial change in wild bee communities and its drivers along two largely well‐protected elevational gradients (alpine grassland vs. pre‐alpine forest), each sampled twice within the last decade.
Results
We detected clear abundance‐based upward shifts in bee communities, particularly in cold‐adapted bumble bee species, demonstrating the speed with which mobile organisms can respond to climatic changes. Mean annual temperature was identified as the main driver of species richness in both regions. Accordingly, and in large overlap with expectations under climate warming, we detected an increase in bee richness and abundance, and an increase in small‐bodied species in low‐ and mid‐elevations along the grassland gradient. Community responses in the pre‐alpine forest gradient were only partly consistent with community responses in alpine grasslands.
Main Conclusion
In well‐protected temperate mountain regions, small‐bodied bees may initially profit from warming temperatures, by getting more abundant and diverse. Less severe warming, and differences in habitat openness along the forested gradient, however, might moderate species responses. Our study further highlights the utility of standardized abundance data for revealing rapid changes in bee communities over only one decade.
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.
Cancer is one of the leading causes of death worldwide. The underlying tumorigenesis is driven by the accumulation of alterations in the genome, eventually disabling tumor suppressors and activating proto-oncogenes.
The MYC family of proto-oncogenes shows a strong deregulation in the majority of tumor entities. However, the exact mechanisms that contribute to MYC-driven oncogenesis remain largely unknown. Over the past decades, the influence of the MYC protein on transcription became increasingly apparent and was thoroughly investigated. Additionally, in recent years several publications provided evidence for so far unreported functions of MYC that are independent of a mere regulation of target genes. These findings suggest an additional role of MYC in the maintenance of genomic stability and this role is strengthened by key findings presented in this thesis.
In the first part, I present data revealing a pathway that allows MYC to couple transcription elongation and DNA double-strand break repair, preventing genomic instability of MYC-driven tumor cells. This pathway is driven by a rapid transfer of the PAF1 complex from MYC onto RNAPII, a process that is mediated by HUWE1. The transfer controls MYC-dependent transcription elongation and, simultaneously, the remodeling of chromatin structure by ubiquitylation of histone H2B. These regions of open chromatin favor not only elongation but also DNA double-strand break repair.
In the second part, I analyze the ability of MYC proteins to form multimeric structures in response to perturbation of transcription and replication. The process of multimerization is also referred to as phase transition. The observed multimeric structures are located proximal to stalled replication forks and recruit factors of the DNA-damage response and transcription termination machinery. Further, I identified the HUWE1-dependent ubiquitylation of MYC as an essential step in this phase transition. Cells lacking the ability to form multimers display genomic instability and ultimately undergo apoptosis in response to replication stress.
Both mechanisms present MYC as a stress resilience factor under conditions that are characterized by a high level of transcriptional and replicational stress. This increased resilience ensures oncogenic proliferation.
Therefore, targeting MYC’s ability to limit genomic instability by uncoupling transcription elongation and DNA repair or disrupting its ability to multimerize presents a therapeutic window in MYC-dependent tumors.
Since the advent of high-throughput sequencing technologies in the mid-2010s, RNA se-
quencing (RNA-seq) has been established as the method of choice for studying gene
expression. In comparison to microarray-based methods, which have mainly been used to
study gene expression before the rise of RNA-seq, RNA-seq is able to profile the entire
transcriptome of an organism without the need to predefine genes of interest. Today,
a wide variety of RNA-seq methods and protocols exist, including dual RNA sequenc-
ing (dual RNA-seq) and multi RNA sequencing (multi RNA-seq). Dual RNA-seq and
multi RNA-seq simultaneously investigate the transcriptomes of two or more species, re-
spectively. Therefore, the total RNA of all interacting species is sequenced together and
only separated in silico. Compared to conventional RNA-seq, which can only investi-
gate one species at a time, dual RNA-seq and multi RNA-seq analyses can connect the
transcriptome changes of the species being investigated and thus give a clearer picture of
the interspecies interactions. Dual RNA-seq and multi RNA-seq have been applied to a
variety of host-pathogen, mutualistic and commensal interaction systems.
We applied dual RNA-seq to a host-pathogen system of human mast cells and Staphylo-
coccus aureus (S. aureus). S. aureus, a commensal gram-positive bacterium, can become
an opportunistic pathogen and infect skin lesions of atopic dermatitis (AD) patients.
Among the first immune cells S. aureus encounters are mast cells, which have previously
been shown to be able to kill the bacteria by discharging antimicrobial products and re-
leasing extracellular traps made of protein and deoxyribonucleic acid (DNA). However,
S. aureus is known to evade the host’s immune response by internalizing within mast
cells. Our dual RNA-seq analysis of different infection settings revealed that mast cells
and S. aureus need physical contact to influence each other’s gene expression. We could
show that S. aureus cells internalizing within mast cells undergo profound transcriptome
changes to adjust their metabolism to survive in the intracellular niche. On the host side,
we found out that infected mast cells elicit a type-I interferon (IFN-I) response in an
autocrine manner and in a paracrine manner to non-infected bystander-cells. Our study
provides the first evidence that mast cells are capable to produce IFN-I upon infection
with a bacterial pathogen.
DNA methylation acts as a major epigenetic modification in mammals, characterized by the transfer of a methyl group to a cytosine. DNA methylation plays a pivotal role in regulating normal development, and misregulation in cells leads to an abnormal phenotype as is seen in several cancers. Any mutations or expression anomalies of genes encoding regulators of DNA methylation may lead to abnormal expression of critical molecules. A comprehensive genomic study encompassing all the genes related to DNA methylation regulation in relation to breast cancer is lacking. We used genomic and transcriptomic datasets from the Cancer Genome Atlas (TGCA) Pan-Cancer Atlas, Genotype-Tissue Expression (GTEx) and microarray platforms and conducted in silico analysis of all the genes related to DNA methylation with respect to writing, reading and erasing this epigenetic mark. Analysis of mutations was conducted using cBioportal, while Xena and KMPlot were utilized for expression changes and patient survival, respectively. Our study identified multiple mutations in the genes encoding regulators of DNA methylation. The expression profiling of these showed significant differences between normal and disease tissues. Moreover, deregulated expression of some of the genes, namely DNMT3B, MBD1, MBD6, BAZ2B, ZBTB38, KLF4, TET2 and TDG, was correlated with patient prognosis. The current study, to our best knowledge, is the first to provide a comprehensive molecular and genetic profile of DNA methylation machinery genes in breast cancer and identifies DNA methylation machinery as an important determinant of the disease progression. The findings of this study will advance our understanding of the etiology of the disease and may serve to identify alternative targets for novel therapeutic strategies in cancer.
Spontaneous brain activity builds the foundation for human cognitive processing during external demands. Neuroimaging studies based on functional magnetic resonance imaging (fMRI) identified specific characteristics of spontaneous (intrinsic) brain dynamics to be associated with individual differences in general cognitive ability, i.e., intelligence. However, fMRI research is inherently limited by low temporal resolution, thus, preventing conclusions about neural fluctuations within the range of milliseconds. Here, we used resting-state electroencephalographical (EEG) recordings from 144 healthy adults to test whether individual differences in intelligence (Raven’s Advanced Progressive Matrices scores) can be predicted from the complexity of temporally highly resolved intrinsic brain signals. We compared different operationalizations of brain signal complexity (multiscale entropy, Shannon entropy, Fuzzy entropy, and specific characteristics of microstates) regarding their relation to intelligence. The results indicate that associations between brain signal complexity measures and intelligence are of small effect sizes (r ∼ 0.20) and vary across different spatial and temporal scales. Specifically, higher intelligence scores were associated with lower complexity in local aspects of neural processing, and less activity in task-negative brain regions belonging to the default-mode network. Finally, we combined multiple measures of brain signal complexity to show that individual intelligence scores can be significantly predicted with a multimodal model within the sample (10-fold cross-validation) as well as in an independent sample (external replication, N = 57). In sum, our results highlight the temporal and spatial dependency of associations between intelligence and intrinsic brain dynamics, proposing multimodal approaches as promising means for future neuroscientific research on complex human traits.
Mammalian embryonic development is subject to complex biological relationships that need to be understood. However, before the whole structure of development can be put together, the individual building blocks must first be understood in more detail. One of these building blocks is the second cell fate decision and describes the differentiation of cells of the inner cell mass of the embryo into epiblast and primitive endoderm cells. These cells then spatially segregate and form the subsequent bases for the embryo and yolk sac, respectively. In organoids of the inner cell mass, these two types of progenitor cells are also observed to form, and to some extent to spatially separate. This work has been devoted to these phenomena over the past three years. Plenty of studies already provide some insights into the basic mechanics of this cell differentiation, such that the first signs of epiblast and primitive endoderm differentiation, are the expression levels of transcription factors NANOG and GATA6. Here, cells with low expression of GATA6 and high expression of NANOG adopt the epiblast fate. If the expressions are reversed, a primitive endoderm cell is formed. Regarding the spatial segregation of the two cell types, it is not yet clear what mechanism leads to this. A common hypothesis suggests the differential adhesion of cell as the cause for the spatial rearrangement of cells. In this thesis however, the possibility of a global cell-cell communication is investigated. The approach chosen to study these phenomena follows the motto "mathematics is biology's next microscope". Mathematical modeling is used to transform the central gene regulatory network at the heart of this work into a system of equations that allows us to describe the temporal evolution of NANOG and GATA6 under the influence of an external signal. Special attention is paid to the derivation of new models using methods of statistical mechanics, as well as the comparison with existing models. After a detailed stability analysis the advantages of the derived model become clear by the fact that an exact relationship of the model parameters and the formation of heterogeneous mixtures of two cell types was found. Thus, the model can be easily controlled and the proportions of the resulting cell types can be estimated in advance. This mathematical model is also combined with a mechanism for global cell-cell communication, as well as a model for the growth of an organoid. It is shown that the global cell-cell communication is able to unify the formation of checkerboard patterns as well as engulfing patterns based on differently propagating signals. In addition, the influence of cell division and thus organoid growth on pattern formation is studied in detail. It is shown that this is able to contribute to the formation of clusters and, as a consequence, to breathe some randomness into otherwise perfectly sorted patterns.
Various types of cancer involve aberrant cell cycle regulation. Among the pathways responsible for tumor growth, the YAP oncogene, a key downstream effector of the Hippo pathway, is responsible for oncogenic processes including cell proliferation, and metastasis by controlling the expression of cell cycle genes. In turn, the MMB multiprotein complex (which is formed when B-MYB binds to the MuvB core) is a master regulator of mitotic gene expression, which has also been associated with cancer. Previously, our laboratory identified a novel crosstalk between the MMB-complex and YAP. By binding to enhancers of MMB target genes and promoting B-MYB binding to promoters, YAP and MMB co-regulate a set of mitotic and cytokinetic target genes which promote cell proliferation. This doctoral thesis addresses the mechanisms of YAP and MMB mediated transcription, and it characterizes the role of YAP regulated enhancers in transcription of cell cycle genes.
The results reported in this thesis indicate that expression of constitutively active, oncogenic YAP5SA leads to widespread changes in chromatin accessibility in untransformed human MCF10A cells. ATAC-seq identified that newly accessible and active regions include YAP-bound enhancers, while the MMB-bound promoters were found to be already accessible and remain open during YAP induction. By means of CRISPR-interference (CRISPRi) and chromatin immuniprecipitation (ChIP), we identified a role of YAP-bound enhancers in recruitment of CDK7 to MMB-regulated promoters and in RNA Pol II driven transcriptional initiation and elongation of G2/M genes. Moreover, by interfering with the YAP-B-MYB protein interaction, we can show that binding of YAP to B-MYB is also critical for the initiation of transcription at MMB-regulated genes. Unexpectedly, overexpression of YAP5SA also leads to less accessible chromatin regions or chromatin closing. Motif analysis revealed that the newly closed regions contain binding motifs for the p53 family of transcription factors. Interestingly, chromatin closing by YAP is linked to the reduced expression and loss of chromatin-binding of the p53 family member Np63. Furthermore, I demonstrate that downregulation of Np63 following expression of YAP is a key step in driving cellular migration.
Together, the findings of this thesis provide insights into the role of YAP in the chromatin changes that contribute to the oncogenic activities of YAP. The overexpression of YAP5SA not only leads to the opening of chromatin at YAP-bound enhancers which together with the MMB complex stimulate the expression of G2/M genes, but also promotes the closing of chromatin at ∆Np63 -bound regions in order to lead to cell migration.
Coxiella burnetii, a Gram negative obligate intracellular bacterium, is the causative
agent of Q fever. It has a world wide distribution and has been documented to
be capable of causing infections in several domestic animals, livestock species,
and human beings. Outbreaks of Q fever are still being observed in livestock
across animal farms in Europe, and primary transmission to humans still oc-
curs especially in animal handlers. Public health authorities in some countries
like Germany are required by law to report human acute cases denoting the
significance of the challenge posed by C. burnetii to public health.
In this thesis, I have developed a platform alongside methods to address the
challenges of genomic analyses of C. burnetii for typing purposes. Identification
of C. burnetii isolates is an important task in the laboratory as well as in the
clinics and genotyping is a reliable method to identify and characterize known
and novel isolates. Therefore, I designed and implemented several methods
to facilitate the genotyping analyses of C. burnetii genomes in silico via a web
platform. As genotyping is a data intensive process, I also included additional
features such as visualization methods and databases for interpretation and
storage of obtained results. I also developed a method to profile the resistome
of C. burnetii isolates using a machine learning approach. Data about antibiotic
resistance in C. burnetii are scarce majorly due to its lifestyle and the difficulty
of cultivation in laboratory media. Alternative methods that rely on homology
identification of resistance genes are also inefficient in C. burnetii, hence, I
opted for a novel approach that has been shown to be promising in other
bacteria species. The applied method relied on an artificial neural network as
well as amino acid composition of position specific scoring matrix profile for
feature extraction. The resulting model achieved an accuracy of ≈ 0.96 on test
data and the overall performance was significantly higher in comparison to
existing models. Finally, I analyzed two new C. burnetii isolates obtained from
an outbreak in Germany, I compared the genome to the RSA 493 reference
isolate and found extensive deletions across the genome landscape.
This work has provided a new digital infrastructure to analyze and character-
ize C. burnetii genomes that was not in existence before and it has also made a
significant contribution to the existing information about antibiotic resistance
genes in C. burnetii.
The original habitat of native European honey bees (\(Apis\) \(mellifera\)) is forest, but currently there is a lack of data about the occurrence of wild honey bee populations in Europe. Prior to being kept by humans in hives, honey bees nested as wild species in hollow trees in temperate forests. However, in the 20th century, intensification of silviculture and agriculture with accompanying losses of nesting sites and depletion of food resources caused population declines in Europe. When the varroa mite (Varroa destructor), an invasive ectoparasite from Asia, was introduced in the late 1970s, wild honey bees were thought to be eradicated in Europe. Nevertheless, sporadic, mostly anecdotal, reports from ornithologists or forest ecologists indicated that honey bee colonies still occupy European forest areas. In my thesis I hypothesize that near-natural deciduous forests may provide sufficient large networks of nesting sites representing refugia for wild-living honey bees. Using two special search techniques, i.e. the tracking of flight routes of honey bee foragers (the “beelining” method) and the inspection of known cavity trees, I collected for the first time data on the occurrence and density of wild-living honey bees in forest areas in Germany (CHAPTER 3). I found wild-living honey bee colonies in the Hainich national park at low densities in two succeeding years. In another forest region, I checked known habitat trees containing black woodpecker cavities for occupation by wild-living honey bee colonies. It turned out that honey bees regularly use these cavities and occur in similar densities in both studied forest regions, independent of the applied detection method. Extrapolating these densities to all German forest areas, I estimate several thousand wild-living colonies in Germany that potentially interact in different ways with the forest environment. I conclude that honey bees regularly colonize forest areas in Germany and that networks of mapped woodpecker cavities offer unique possibilities to study the ecology of wild-living honey bees over several years.
While their population status is ambiguous and the density of colonies low, the fact that honey bees can still be found in forests poses questions about food supply in forest environments. Consequently, I investigated the suitability of woodlands as a honey bee foraging habitat (CHAPTER 4). As their native habitat, forests are assumed to provide important pollen and nectar sources for honey bee colonies. However, resource supply might be spatially and temporally restricted and landscape-scale studies in European forest regions are lacking. Therefore, I set up twelve honey bee colonies in observation hives at locations with varying degree of forest cover. Capitalizing on the unique communication behaviour, the waggle dance, I examined the foraging distances and habitat preferences of honey bees over almost an entire foraging season. Moreover, by connecting this decoded dance information with colony weight recordings, I could draw conclusions about the contribution of the different habitat types to honey yield. Foraging distances generally increased with the amount of forest in the surrounding landscape. Yet, forest cover did not have an effect on colony weight. Compared to expectations based on the proportions of different habitats in the surroundings, colonies foraged more frequently in cropland and grasslands than in deciduous and coniferous forests, especially in late summer when pollen foraging in the forest is most difficult. In contrast, colonies used forests for nectar/honeydew foraging in early summer during times of colony weight gain emphasizing forests as a temporarily significant source of carbohydrates. Importantly, my study shows that the ecological and economic value of managed forest as habitat for honey bees and other wild pollinators can be significantly increased by the continuous provision of floral resources, especially for pollen foraging.
The density of these wild-living honey bee colonies and their survival is driven by several factors that vary locally, making it crucial to compare results in different regions. Therefore, I investigated a wild-living honey bee population in Galicia in north-western Spain, where colonies were observed to reside in hollow electric poles (CHAPTER 5). The observed colony density only in these poles was almost twice as high as in German forest areas, suggesting generally more suitable resource conditions for the bees in Galicia. Based on morphometric analyses of their wing venation patterns, I assigned the colonies to the native evolutionary lineage (M-lineage) where the particularly threatened subspecies \(Apis\) \(mellifera\) \(iberiensis\) also belongs to. Averaged over two consecutive years, almost half of the colonies survived winter (23 out of 52). Interestingly, semi-natural areas both increased abundance and subsequent colony survival. Colonies surrounded by more semi-natural habitat (and therefore less intensive cropland) had an elevated overwintering probability, indicating that colonies need a certain amount of semi-natural habitat in the landscape to survive. Due to their ease of access these power poles in Galicia are, ideally suited to assess the population demography of wild-living Galician honey bee colonies through a long-term monitoring.
In a nutshell, my thesis indicates that honey bees in Europe always existed in the wild. I performed the first survey of wild-living bee density yet done in Germany and Spain. My thesis identifies the landscape as a major factor that compromises winter survival and reports the first data on overwintering rates of wild-living honey bees in Europe. Besides, I established methods to efficiently detect wild-living honey bees in different habitat. While colonies can be found all over Europe, their survival and viability depend on unpolluted, flower rich habitats. The protection of near-natural habitat and of nesting sites is of paramount importance for the conservation of wild-living honey bees in Europe.
The monarch butterfly (Danaus plexippus) performs one of the most astonishing behaviors in the animal kingdom: every fall millions of these butterflies leave their breeding grounds in North Amerika and migrate more than 4.000 km southwards until they reach their overwintering habitat in Central Mexico. To maintain their migratory direction over this enormous distance, the butterflies use a time-compensated sun compass. Beside this, skylight polarization, the Earth’s magnetic field and specific mountain ranges seem to guide the butterflies as well the south. In contrast to this fascinating orientation ability, the behavior of the butterflies in their non-migratory state received less attention. Although they do not travel long distances, they still need to orient themselves to find food, mating partners or get away from competitors. The aim of the present doctoral thesis was to investigate use of visual cues for orientation in migrating as well as non-migrating monarch butterflies. For this, field experiments investigating the migration of the butterflies in Texas (USA) were combined with experiments testing the orientation performance of non-migratory butterflies in Germany.
In the first project, I recorded the heading directions of tethered butterflies during their annual fall migration. In an outdoor flight simulator, the butterflies maintained a southwards direction as long as they had a view of the sun’s position. Relocating the position of the sun by 180° using a mirror, revealed that the sun is the animals’ main orientation reference. Furthermore, I demonstrated that when the sun is blocked and a green light stimulus (simulated sun) is introduced, the animals interpreted this stimulus as the ‘real’ sun. However, this cue was not sufficient to set the migratory direction when simulated as the only visual cue in indoor experiments. When I presented the butterflies a linear polarization pattern additionally to the simulated sun, the animals headed in the correct southerly direction showing that multiple skylight cues are required to guide the butterflies during their migration.
In the second project, I, furthermore, demonstrated that non-migrating butterflies are able to maintain a constant direction with respect to a simulated sun. Interestingly, they ignored the spectral component of the stimulus and relied on the intensity instead. When a panoramic skyline was presented as the only orientation reference, the butterflies maintained their direction only for short time windows probably trying to stabilize their flight based on optic-flow information. Next, I investigated whether the butterflies combine celestial with local cues by simulating a sun stimulus together with a panoramic skyline. Under this conditions, the animals’ directedness was increased demonstrating that they combine multiple visual cues for spatial orientation.
Following up on the observation that a sun stimulus resulted in a different behavior than the panoramic skyline, I investigated in my third project which orientation strategies the butterflies use by presenting different simulated cues to them. While a bright stripe on a dark background elicited a strong attraction of the butterflies steering in the direction of the stimulus, the inverted version of the stimulus was used for flight stabilization. In contrast to this, the butterflies maintained arbitrary directions with a high directedness with respect to a simulated sun. In an ambiguous scenery with two identical stimuli (two bright stripes, two dark stripes, or two sun stimuli) set 180° apart, a constant flight course was only achieved when two sun stimuli were displayed suggesting an involvement of the animals’ internal compass. In contrast, the butterflies used two dark stripes for flight stabilization and were alternatingly attracted by two bright stripes. This shows that monarch butterflies use stimulus-dependent orientation strategies and gives the first evidence for different neuronal pathways controlling the output behavior.
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.
Die Fanconi-Anämie (FA) ist eine seltene, heterogene Erbkrankheit. Sie weist ein sehr variables klinisches Erscheinungsbild auf, das sich aus angeborenen Fehlbildungen, hämatologischen Funktionsstörungen, einem erhöhten Risiko für Tumorentwicklung und endokrinen Pathologien zusammensetzt. Die Erkrankung zählt zu den genomischen Instabilitätssyndromen, welche durch eine fehlerhafte DNA-Schadensreparatur gekennzeichnet sind. Bei der FA zeigt sich dies vor allem in einer charakteristischen Hypersensitivität gegenüber DNA-quervernetzenden Substanzen (z. B. Mitomycin C, Cisplatin). Der zelluläre FA-Phänotyp zeichnet sich durch eine erhöhte Chromosomenbrüchigkeit und einen Zellzyklusarrest in der G2-Phase aus. Diese Charakteristika sind bereits spontan vorhanden und werden durch Induktion mit DNA-quervernetzenden Substanzen verstärkt. Der Gendefekt ist dabei in einem der 22 bekannten FA-Gene (FANCA, -B, -C, -D1, -D2, -E, -F, -G, -I, -J, -L, -M, -N, -O, -P, -Q, -R, -S, -T, -U, -V, -W) oder in noch unbekannten FA-Genen zu finden. Die FA-Gendefekte werden mit Ausnahme von FANCR (dominant-negative de novo Mutationen) und FANCB (X-chromosomal) autosomal rezessiv vererbt. Die FA-Genprodukte bilden zusammen mit weiteren Proteinen den FA/BRCA-Signalweg. Das Schlüsselereignis dieses Signalwegs stellt die Monoubiquitinierung von FANCD2 und FANCI (ID2-Komplex) dar. Ausgehend davon lässt sich zwischen upstream- und downstream-gelegenen FA-Proteinen unterscheiden. Letztere sind direkt an der DNA-Schadensreparatur beteiligt. Zu den upstream-gelegenen Proteinen zählt der FA-Kernkomplex, der sich aus bekannten FA-Proteinen und aus FA-assoziierten-Proteinen (FAAPs) zusammensetzt und für die Monoubiquitinierung des ID2-Komplexes verantwortlich ist. Für FAAPs wurden bisher keine pathogenen humanen Mutationen beschrieben. Zu diesen Proteinen gehört auch FAAP100, das mit FANCB und FANCL innerhalb des FA-Kernkomplexes den Subkomplex LBP100 bildet.
Durch die vorliegende Arbeit wurde eine nähere Charakterisierung dieses Proteins erreicht. In einer Amnion-Zelllinie konnte eine homozygote Missense-Mutation identifiziert werden. Der Fetus zeigte einen typischen FA-Phänotyp und auch seine Zellen wiesen charakteristische FA-Merkmale auf. Der zelluläre Phänotyp ließ sich durch FAAP100WT komplementieren, sodass die Pathogenität der Mutation bewiesen war. Unterstützend dazu wurden mithilfe des CRISPR/Cas9-Systems weitere FAAP100-defiziente Zelllinien generiert. Diese zeigten ebenfalls einen typischen FA-Phänotyp, welcher sich durch FAAP100WT komplementieren ließ. Die in vitro-Modelle dienten als Grundlage dafür, die Funktion des FA-Kernkomplexes im Allgemeinen und die des Subkomplexes LBP100 im Besonderen besser zu verstehen. Dabei kann nur durch intaktes FAAP100 das LBP100-Modul gebildet und dieses an die DNA-Schadensstelle transportiert werden. Dort leistet FAAP100 einen essentiellen Beitrag für den FANCD2-Monoubiquitinierungsprozess und somit für die Aktivierung der FA-abhängigen DNA-Schadensreparatur. Um die Funktion von FAAP100 auch in vivo zu untersuchen, wurde ein Faap100-/--Mausmodell generiert, das einen mit anderen FA-Mausmodellen vergleichbaren, relativ schweren FA-Phänotyp aufwies. Aufgrund der Ergebnisse lässt sich FAAP100 als neues FA-Gen klassifizieren. Zudem wurde die Rolle des Subkomplexes LBP100 innerhalb des FA-Kernkomplexes weiter aufgeklärt. Beides trägt zu einem besseren Verständnis des FA/BRCA-Signalweges bei. Ein weiterer Teil der vorliegenden Arbeit beschäftigt sich mit der Charakterisierung von FAAP100138, einer bisher nicht validierten Isoform von FAAP100. Durch dieses Protein konnte der zelluläre FA-Phänotyp von FAAP100-defizienten Zelllinien nicht komplementiert werden, jedoch wurden Hinweise auf einen dominant-negativen Effekt von FAAP100138 auf den FA/BRCA-Signalweg gefunden. Dies könnte zu der Erklärung beitragen, warum und wie der Signalweg, beispielsweise in bestimmtem Gewebearten, herunterreguliert wird. Zudem wäre eine Verwendung in der Krebstherapie denkbar.
Forests are multi-functional system, which have to fulfil different objectives at the same time. The main functions include the production of wood, storage of carbon, the promotion of biological diversity and the provision of recreational space. Yet, global forests are affected by large and intense natural disturbances, like bark beetle infestations. While natural disturbances threaten wood production and are perceived as ‘catastrophe’ diminishing recreational value, biodiversity can benefit from the disturbance-induced changes in forest structures. This trade-off poses a dilemma to managers of bark beetle affected stands, particularly in protected areas designated to both nature conservation and recreation. Forest landscapes need a sustainable management concept aligning these different objectives. In order to support this goal with scientific knowledge, the aim of this work is to analyse ecological and social effects along a gradient of different disturbance severities. In this context, I studied the effects of a disturbance severity gradient on the diversity of different taxonomic groups including vascular plants, mosses, lichens, fungi, arthropods and birds in five national parks in Central Europe. To analyse the recreational value of the landscape I conducted visitor surveys in the same study areas in which the biodiversity surveys were performed. To analyse possible psychological or demographic effects on preferences for certain disturbance intensities, an additional online survey was carried out.
The synaptic cleft is of central importance for synaptic transmission, neuronal plasticity and memory and thus well studied in neurobiology. To target proteins of interest with high specificity and strong signal to noise conventional immunohistochemistry relies on the use of fluorescently labeled antibodies. However, investigations on synaptic receptors remain challenging due to the defined size of the synaptic cleft of ~20 nm between opposing pre- and postsynaptic membranes. At this limited space, antibodies bear unwanted side effects such as crosslinking, accessibility issues and a considerable linkage error between fluorophore and target of ~10 nm. With recent single molecule localization microscopy (SMLM) methods enabling localization precisions of a few nanometers, the demand for labeling approaches with minimal linkage error and reliable recognition of the target molecules rises.
Within the scope of this work, different labeling techniques for super-resolution fluorescence microscopy were utilized allowing site-specific labeling of a single amino acid in synaptic proteins like kainate receptors (KARs), transmembrane α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor regulatory proteins (TARPs), γ-aminobutyric acid type A receptors (GABA-ARs) and neuroligin 2 (NL2). The method exploits the incorporation of unnatural amino acids (uAAs) in the protein of interest using genetic code expansion (GCE) via amber suppression technology and subsequent labeling with tetrazine functionalized fluorophores. Implementing this technique, hard-to-target proteins such as KARs, TARPs and GABA-ARs could be labeled successfully, which could only be imaged insufficiently with conventional labeling approaches. Furthermore, functional studies involving electrophysiological characterization, as well as FRAP and FRET experiments validated that incorporation of uAAs maintains the native character of the targeted proteins. Next, the method was transferred into primary hippocampal neurons and in combination with super-resolution microscopy it was possible to resolve the nanoscale organization of γ2 and γ8 TARPs. Cluster analysis of dSTORM localization data verified synaptic accumulation of γ2, while γ8 was homogenously distributed along the neuron. Additionally, GCE and bioorthogonal labeling allowed visualization of clickable GABA-A receptors located at postsynaptic compartments in dissociated hippocampal neurons. Moreover, saturation experiments and FRET imaging of clickable multimeric receptors revealed successful binding of multiple tetrazine functionalized fluorophores to uAA-modified dimeric GABA-AR α2 subunits in close proximity (~5 nm). Further utilization of tetrazine-dyes via super-resolution microscopy methods such as dSTORM and click-ExM will provide insights to subunit arrangement in receptors in the future.
This work investigated the nanoscale organization of synaptic proteins with minimal linkage error enabling new insights into receptor assembly, trafficking and recycling, as well as protein-protein interactions at synapses. Ultimately, bioorthogonal labeling can help to understand pathologies such as the limbic encephalitis associated with GABA-AR autoantibodies and is already in application for cancer therapies.
Summary
Chapters I & II: General Introduction & General Methods
Agriculture is confronted with a rampant loss of biodiversity potentially eroding ecosystem service potentials and adding up to other stressors like climate change or the consequences of land-use change and intensive management. To counter this ‘biodiversity crisis’, agri-environment schemes (AES) have been introduced as part of ecological intensification efforts. These AES combine special management regimes with the establishment of tailored habitats to create refuges for biodiversity in agricultural landscapes and thus ensure biodiversity mediated ecosystem services such as pest control. However, little is known about how well different AES habitats fulfil this purpose and whether they benefit ecosystem services in adjacent crop fields. Here I investigated how effective different AES habitats are for restoring biodiversity in different agricultural landscapes (Chapter V) and whether they benefit natural pest control in adjacent oilseed rape (Chapter VI) and winter cereal fields (Chapter VII). I recorded biodiversity and pest control potentials using a variety of different methods (Chapters II, V, VI & VII). Moreover, I validated the methodology I used to assess predator assemblages and predation rates (Chapters III & IV).
Chapter III: How to record ground dwelling predators?
Testing methodology is critical as it ensures scientific standards and trustworthy results. Pitfall traps are widely used to record ground dwelling predators, but little is known about how different trap types affect catches. I compared different types of pitfall traps that had been used in previous studies in respect to resulting carabid beetle assemblages. While barrier traps collected more species and deliver more complete species inventories, conventional simple pitfall traps provide reliable results with comparatively little handling effort. Placing several simple pitfall traps in the field can compensate the difference while still saving handling effort.
Chapter IV: How to record predation rates?
A plethora of methods has been proposed and used for recording predation rates, but these have rarely been validated before use. I assessed whether a novel approach to record predation, the use of sentinel prey cards with glued on aphids, delivers realistic results. I compared different sampling efforts and showed that obtained predation rates were similar and could be linked to predator (carabid beetle) densities and body-sizes (a proxy often used for food intake rates). Thus, the method delivers reliable and meaningful predation rates.
Chapter V: Do AES habitats benefit multi-taxa biodiversity?
The main goal of AES is the conservation of biodiversity in agricultural landscapes. I investigated how effectively AES habitats with different temporal continuity fulfil this goal in differently structured landscapes. The different AES habitats investigated had variable effects on local biodiversity. Temporal continuity of AES habitats was the most important predictor with older, more temporally continuous habitats harbouring higher overall biodiversity and different species assemblages in most taxonomic groups than younger AES habitats. Results however varied among taxonomic groups and natural enemies were equally supported by younger habitats. Semi-natural habitats in the surrounding landscape and AES habitat size were of minor importance for local biodiversity and had limited effects. This stresses that newly established AES habitats alone cannot restore farmland biodiversity. Both AES habitats as well as more continuous semi-natural habitats synergistically increase overall biodiversity in agricultural landscapes.
Chapter VI: The effects of AES habitats on predators in adjacent oilseed rape fields
Apart from biodiversity conservation, ensuring ecosystem service delivery in agricultural landscapes is a crucial goal of AES. I therefore investigated the effects of adjacent AES habitats on ground dwelling predator assemblages in oilseed rape fields. I found clear distance decay effects from the field edges into the field centres on both richness and densities of ground dwelling predators. Direct effects of adjacent AES habitats on assemblages in oilseed rape fields however were limited and only visible in functional traits of carabid beetle assemblages. Adjacent AES habitats doubled the proportion of predatory carabid beetles indicating a beneficial role for pest control. My results show that pest control potentials are largest close to the field edges and beneficial effects are comparably short ranged.
Chapter VII: The effects of AES habitats on pest control in adjacent cereal fields
Whether distance functions and potential effects of AES habitats are universal across crops is unknown. Therefore, I assessed distance functions of predators, pests, predation rates and yields after crop rotation in winter cereals using the same study design as in the previous year. Resulting distance functions were not uniform and differed from those found in oilseed rape in the previous year, indicating that the interactions between certain adjacent habitats vary with habitat and crop types. Distance functions of cereal-leaf beetles (important cereal pests) and parasitoid wasps were moreover modulated by semi-natural habitat proportion in the surrounding landscapes. Field edges buffered assemblage changes in carabid beetle assemblages over crop rotation confirming their important function as refuges for natural enemies. My results emphasize the beneficial role of field edges for pest control potentials. These findings back the calls for smaller field sizes and more diverse, more heterogeneously structured agricultural landscapes.
Chapter VIII: General Discussion
Countering biodiversity loss and ensuring ecosystem service provision in agricultural landscapes is intricate and requires strategic planning and restructuring of these landscapes. I showed that agricultural landscapes could benefit maximally from (i) a mixture of AES habitats and semi-natural habitats to support high levels of overall biodiversity and from (ii) smaller continuously managed agricultural areas (i.e. smaller field sizes or the insertion of AES elements within large fields) to maximize natural pest control potentials in crop fields. I propose a mosaic of younger AES habitats and semi-natural habitats to support ecosystem service providers and increase edge density for ecosystem service spillover into adjacent crops. The optimal extent and density of this network as well as the location in which AES and semi-natural habitats interact most beneficially with adjacent crops need further investigation. My results provide a further step towards more sustainable agricultural landscapes that simultaneously allow biodiversity to persist and maintain agricultural production under the framework of ecological intensification.
New insights into the histone variant H2A.Z incorporation pathway in \(Trypanosoma\) \(brucei\)
(2022)
The histone variant H2A.Z is a key player in transcription regulation in eukaryotes. Histone acetylations by the NuA4/TIP60 complex are required to enable proper incorporation of the histone variant and to promote the recruitment of other complexes and proteins required for transcription initiation. The second key player in H2A.Z-mediated transcription is the chromatin remodelling complex SWR1, which replaces the canonical histone H2A with its variant. By the time this project started little was known about H2A.Z in the unicellular parasite Trypanosoma brucei. Like in other eukaryotes H2A.Z was exclusively found in the transcription start sites of the polycistronic transcription units where it keeps the chromatin in an open conformation to enable RNA-polymerase II-mediated transcription. Previous studies showed the variant colocalizing with an acetylation of lysine on histone H4 and a methylation of lysine 4 on histone H3. Data indicated that HAT2 is linked to H2A.Z since it is required for acetylation of lyinse 10 on histone H4. A SWR1-like complex and a complex homologous to the NuA4/TIP60 could not be identified yet. This study aimed at identifying a SWR1-like remodelling complex in T. brucei and at identifying a protein complex orthologous to NuA4/TIP60 as well as at answering the question whether HAT2 is part of this complex or not. To this end, I performed multiple mass spectrometry-coupled co-Immunoprecipitation assays with potential subunits of a SWR1 complex, HAT2 and a putative homolog of a NuA4/TIP60 subunit. In the course of these experiments, I was able to identify the TbSWR1 complex. Subsequent cell fractionation and chromatin immunoprecipitation-coupled sequencing analysis experiments confirmed, that this complex is responsible for the incorporation of the histone variant H2A.Z in T. brucei. In addition to this chromatin remodelling complex, I was also able to identify two histone acetyltransferase complexes assembled around HAT1 and HAT2. In the course of my study data were published by the research group of Nicolai Siegel that identified the histone acetyltransferase HAT2 as being responsible for histone H4 acetylation, in preparation to promote H2A.Z incorporation. The data also indicated that HAT1 is responsible for acetylation of H2A.Z. According to the literature, this acetylation is required for proper transcription initiation. Experimental data generated in this study indicated, that H2A.Z and therefore TbSWR1 is involved in the DNA double strand break response of T. brucei. The identification of the specific complex composition of all three complexes provided some hints about how they could interact with each other in the course of transcription regulation and the DNA double strand break response. A proximity labelling approach performed with one of the subunits of the TbSWR1 complex identified multiple transcription factors, PTM writers and proteins potentially involved in chromatin maintenance. Overall, this work will provide some interesting insights about the composition of the complexes involved in H2A.Z incorporation in T. brucei. Furthermore, it is providing valuable information to set up experiments that could shed some light on RNA-polymerase II-mediated transcription and chromatin remodelling in T. brucei in particular and Kinetoplastids in general.
One of the pronounced global challenges facing ecologists is how to feed the current growing human population while sustaining biodiversity and ecosystem services. To shed light on this, I investigated the impact of human land use on bee diversity and plant-pollinator interactions in Tanzania Savannah ecosystems. The thesis comprises the following chapters:
Chapter I: General Introduction
This chapter provides the background information including the study objectives and hypotheses. It highlights the ecological importance of bees and the main threats facing bee pollinators with a focus on two land-use practices namely livestock grazing and agriculture. It also highlights the diversity and global distribution of bees. It further introduces the tropical savannah ecosystem, its climate, and vegetation characteristics and explains spectacular megafauna species of the system that form centers of wildlife tourism and inadequacy knowledge on pollinators diversity of the system. Finally, this chapter describes the study methodology including, the description of the study area, study design, and data collection.
Chapter II: Positive effects of low livestock grazing intensity on East African bee assemblages mediated by increases in floral resources
The impact of livestock grazing intensity on bee assemblage has been subjected to research over decades. Moreover, most of these studies have been conducted in temperate Europe and America leaving the huge tropical savannah of East Africa less studied. Using sweep netting and pan traps, a total of 183 species (from 2,691 individuals) representing 55 genera and five families were collected from 24 study sites representing three levels of livestock grazing intensity in savannah ecosystem of northern Tanzania. Results have shown that moderate livestock grazing slightly increased bee species richness. However, high livestock grazing intensity led to a strong decline. Besides, results revealed a unimodal distribution pattern of bee species richness and mean annual temperature. It was also found that the effect of livestock grazing and environmental temperature on bee species richness was mediated by a positive effect of moderate grazing on floral resource richness. The study, therefore, reveals that bee communities of the African savannah zone may benefit from low levels of livestock grazing as this favors the growth of flowering plant species. A high level of livestock grazing intensity will cause significant species losses, an effect that may increase with climatic warming.
Chapter III: Agricultural intensification with seasonal fallow land promotes high bee diversity in Afrotropical drylands
This study investigated the impact of local agriculture intensification on bee diversity in the Afro tropical drylands of northern Tanzania. Using sweep netting and pan traps, a total of 219 species (from 3,428 individuals) representing 58 genera and six families were collected from 24 study sites (distributed from 702 to 1708 m. asl) representing three levels of agriculture intensity spanning an extensive gradient of mean annual temperature. Results showed that bee species richness increased with agricultural intensity and with increasing temperature. However, the effects of agriculture intensity and temperature on bee species richness were mediated by the positive effects of agriculture and temperature on floral resource richness used by bee pollinators. Moreover, results showed that variation of bee body sizes increases with agricultural intensification, “that effect”, however, diminished in environments with higher temperatures. This study reveals that bee assemblages in Afrotropical drylands benefit from agriculture intensification in the way it is currently practiced. Further intensification, including year-round irrigated crop monocultures and extensive 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. Therefore, to conserve bee communities in Afro tropical drylands and guarantee pollination services, a mixture of savannah and agriculture, with long periods of fallow land should be maintained.
Chapter IV: Impact of land use intensification and local features on plants and pollinators in Sub-Saharan smallholder farms
For the first time in the region, this study explores the impact of land-use intensification on plants and pollinators in Sub-Saharan smallholder farms. The study complemented field surveys of bees with a modern DNA metabarcoding approach to characterize the foraged plants and thus built networks describing plant-pollinator interactions at the individual insect level. This information was coupled with quantitative traits of landscape composition and floral availability surrounding each farm. The study found that pollinator richness decreased with increasing impervious and agricultural cover in the landscape, whereas the flower density at each farm correlated with pollinator richness. The intensification of agricultural land use and urbanization correlated with a higher foraging niche overlap among pollinators due to the convergence of individuals' flower-visiting strategies. Furthermore, within farms, the higher availability of floral resources drove lower niche overlap among individuals, greater abundance of flower visitors shaped higher generalization at the networks level (H2I), possibly due to increased competition. These mechanistic understandings leading to individuals’ foraging niche overlap and generalism at the network level, could imply stability of interactions and the pollination ecosystem service. The integrative survey proved that plant-pollinator systems are largely affected by land use intensification and by local factors in smallholder farms of Sub-Saharan Africa. Thus, policies promoting nature-based solutions, among which the introduction of more pollinator-friendly practices by smallholder farmers, could be effective in mitigating the intensification of both urban and rural landscapes in this region, as well as in similar Sub-Saharan contexts.
Chapter V: A synopsis of the Bee occurrence data of northern Tanzania
This study represents a synopsis of the bee occurrence data of northern Tanzania obtained from a survey in the Kilimanjaro, Arusha, and Manyara regions. Bees were sampled using two standardized methods, sweep netting and colored pan traps. The study summed up 953 species occurrences of 45 species belonging to 20 genera and four families (Halictidae, Apidae, Megachilidae, and andrenidae) A. This study serves as the baseline information in understanding the diversity and distribution of bees in the northern parts of the country. Understanding the richness and distribution of bees is a critical step in devising robust conservation and monitoring strategies for their populations since limited taxonomic information of the existing and unidentified bee species makes their conservation haphazard.
Chapter VI: General discussion
In general, findings obtained in these studies suggest that livestock grazing and agriculture intensification affects bee assemblages and floral resources used by bee pollinators. Results have shown that moderate livestock grazing intensity may be important in preserving bee diversity. However, high level of livestock grazing intensity may result in a strong decline in bee species richness and abundance. Moreover, findings indicate that agriculture intensification with seasonal fallow lands supports high floral resource richness promoting high bee diversity in Afrotropical drylands. Nonetheless, natural savannahs were found to contain unique bee species. Therefore, agriculture intensification with seasonal fallow should go in hand with conserving remnant savannah in the landscapes to increase bee diversity and ensure pollination services. Likewise, findings suggest that increasing urbanization and agriculture cover at the landscape level reduce plant and pollinator biodiversity with negative impacts on their complex interactions with plants. Conversely, local scale availability of floral resources has shown the positive effects in buffering pollinators decline and mitigating all detrimental effects induced by land-use intensification. Moreover, findings suggest that the impact of human land use (livestock grazing and agriculture) do not act in isolation but synergistically interacts with climatic factors such as mean annual temperature, MAT. The impact of MAT on bee species richness in grazing gradient showed to be more detrimental than in agriculture habitats. This could probably be explained by the remaining vegetation cover following anthropogenic disturbance. Meaning that the remaining vegetation cover in the agricultural gradient probably absorbs the solar radiations hence reducing detrimental effect of mean annual temperature on bee species richness. This one is not the case in grazing gradient since the impact of livestock grazing is severe, leaving the bare land with no vegetation cover. Finally, our findings conclude that understanding the interplay of multiple anthropogenic activities and their interaction with MAT as a consequence of ongoing climate change is necessary for mitigating their potential consequences on bee assemblages and the provision of ecosystem services. Morever, future increases in livestock grazing and agriculture intensification (including year-round crop irrigated monocultures and excessive use of agrochemicals) may lead to undesirable consequences such as species loss and impair provision of pollination services.
Usher syndrome, the most prevalent cause of combined hereditary vision and hearing impairment, is clinically and genetically heterogeneous. Moreover, several conditions with phenotypes overlapping Usher syndrome have been described. This makes the molecular diagnosis of hereditary deaf-blindness challenging. Here, we performed exome sequencing and analysis on 7 Mexican and 52 Iranian probands with combined retinal degeneration and hearing impairment (without intellectual disability). Clinical assessment involved ophthalmological examination and hearing loss questionnaire. Usher syndrome, most frequently due to biallelic variants in MYO7A (USH1B in 16 probands), USH2A (17 probands), and ADGRV1 (USH2C in 7 probands), was diagnosed in 44 of 59 (75%) unrelated probands. Almost half of the identified variants were novel. Nine of 59 (15%) probands displayed other genetic entities with dual sensory impairment, including Alström syndrome (3 patients), cone-rod dystrophy and hearing loss 1 (2 probands), and Heimler syndrome (1 patient). Unexpected findings included one proband each with Scheie syndrome, coenzyme Q10 deficiency, and pseudoxanthoma elasticum. In four probands, including three Usher cases, dual sensory impairment was either modified/aggravated or caused by variants in distinct genes associated with retinal degeneration and/or hearing loss. The overall diagnostic yield of whole exome analysis in our deaf-blind cohort was 92%. Two (3%) probands were partially solved and only 3 (5%) remained without any molecular diagnosis. In many cases, the molecular diagnosis is important to guide genetic counseling, to support prognostic outcomes and decisions with currently available and evolving treatment modalities.
Die Fluoreszenzmikroskopie ist eine vielseitig einsetzbare Untersuchungsmethode für biologische Proben, bei der Biomoleküle selektiv mit Fluoreszenzfarbstoffen markiert werden, um sie dann mit sehr gutem Kontrast abzubilden. Dies ist auch mit mehreren verschiedenartigen Zielmolekülen gleichzeitig möglich, wobei üblicherweise verschiedene Farbstoffe eingesetzt werden, die über ihre Spektren unterschieden werden können.
Um die Anzahl gleichzeitig verwendbarer Färbungen zu maximieren, wird in dieser Arbeit zusätzlich zur spektralen Information auch das zeitliche Abklingverhalten der Fluoreszenzfarbstoffe mittels spektral aufgelöster Fluoreszenzlebensdauer-Mikroskopie (spectrally resolved fluorescence lifetime imaging microscopy, sFLIM) vermessen. Dazu wird die Probe in einem Konfokalmikroskop von drei abwechselnd gepulsten Lasern mit Wellenlängen von 485 nm, 532nm und 640nm angeregt. Die Detektion des Fluoreszenzlichtes erfolgt mit einer hohen spektralen Auflösung von 32 Kanälen und gleichzeitig mit sehr hoher zeitlicher Auflösung von einigen Picosekunden. Damit wird zu jedem detektierten Fluoreszenzphoton der Anregungslaser, der spektrale Kanal und die Ankunftszeit registriert. Diese detaillierte multidimensionale Information wird von einem Pattern-Matching-Algorithmus ausgewertet, der das Fluoreszenzsignal mit zuvor erstellten Referenzpattern der einzelnen Farbstoffe vergleicht. Der Algorithmus bestimmt so für jedes Pixel die Beiträge der einzelnen Farbstoffe.
Mit dieser Technik konnten pro Anregungslaser fünf verschiedene Färbungen gleichzeitig dargestellt werden, also theoretisch insgesamt 15 Färbungen. In der Praxis konnten mit allen drei Lasern zusammen insgesamt neun Färbungen abgebildet werden, wobei die Anzahl der Farben vor allem durch die anspruchsvolle Probenvorbereitung limitiert war. In anderen Versuchen konnte die sehr hohe Sensitivität des sFLIM-Systems genutzt werden, um verschiedene Zielmoleküle voneinander zu unterscheiden, obwohl sie alle mit demselben Farbstoff markiert waren. Dies war möglich, weil sich die Fluoreszenzeigenschaften eines Farbstoffmoleküls geringfügig in Abhängigkeit von seiner Umgebung ändern. Weiterhin konnte die sFLIM-Technik mit der hochauflösenden STED-Mikroskopie (STED: stimulated emission depletion) kombiniert werden, um so hochaufgelöste zweifarbige Bilder zu erzeugen, wobei nur ein einziger gemeinsamer STED-Laser benötigt wurde.
Die gleichzeitige Erfassung von mehreren photophysikalischen Messgrößen sowie deren Auswertung durch den Pattern-Matching-Algorithmus ermöglichten somit die Entwicklung von neuen Methoden der Fluoreszenzmikroskopie für Mehrfachfärbungen.
Ultrastructural analysis of wild-type and RIM1α knockout active zones in a large cortical synapse
(2022)
Rab3A-interacting molecule (RIM) is crucial for fast Ca\(^{2+}\)-triggered synaptic vesicle (SV) release in presynaptic active zones (AZs). We investigated hippocampal giant mossy fiber bouton (MFB) AZ architecture in 3D using electron tomography of rapid cryo-immobilized acute brain slices in RIM1α\(^{−/−}\) and wild-type mice. In RIM1α\(^{−/−}\), AZs are larger with increased synaptic cleft widths and a 3-fold reduced number of tightly docked SVs (0–2 nm). The distance of tightly docked SVs to the AZ center is increased from 110 to 195 nm, and the width of their electron-dense material between outer SV membrane and AZ membrane is reduced. Furthermore, the SV pool in RIM1α\(^{−/−}\) is more heterogeneous. Thus, RIM1α, besides its role in tight SV docking, is crucial for synaptic architecture and vesicle pool organization in MFBs.
Targeting the intrinsic metabolism of immune or tumor cells is a therapeutic strategy in autoimmunity, chronic inflammation or cancer. Metabolite repair enzymes may represent an alternative target class for selective metabolic inhibition, but pharmacological tools to test this concept are needed. Here, we demonstrate that phosphoglycolate phosphatase (PGP), a prototypical metabolite repair enzyme in glycolysis, is a pharmacologically actionable target. Using a combination of small molecule screening, protein crystallography, molecular dynamics simulations and NMR metabolomics, we discover and analyze a compound (CP1) that inhibits PGP with high selectivity and submicromolar potency. CP1 locks the phosphatase in a catalytically inactive conformation, dampens glycolytic flux, and phenocopies effects of cellular PGP-deficiency. This study provides key insights into effective and precise PGP targeting, at the same time validating an allosteric approach to control glycolysis that could advance discoveries of innovative therapeutic candidates.
In times of environmental change species have two options to survive: they either relocate to a new habitat or they adapt to the altered environment. Adaptation requires physiological plasticity and provides a selection benefit. In this regard, the Western honeybee (Apis mellifera) protrudes with its thermoregulatory capabilities, which enables a nearly worldwide distribution. Especially in the cold, shivering thermogenesis enables foraging as well as proper brood development and thus survival. In this study, we present octopamine signaling as a neurochemical prerequisite for honeybee thermogenesis: we were able to induce hypothermia by depleting octopamine in the flight muscles. Additionally, we could restore the ability to increase body temperature by administering octopamine. Thus, we conclude that octopamine signaling in the flight muscles is necessary for thermogenesis. Moreover, we show that these effects are mediated by β octopamine receptors. The significance of our results is highlighted by the fact the respective receptor genes underlie enormous selective pressure due to adaptation to cold climates. Finally, octopamine signaling in the service of thermogenesis might be a key strategy to survive in a changing environment.
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 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.
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.
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.