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Branching allows neurons to make synaptic contacts with large numbers of other neurons, facilitating the high connectivity of nervous systems. Neuronal arbors have geometric properties such as branch lengths and diameters that are optimal in that they maximize signaling speeds while minimizing construction costs. In this work, we asked whether neuronal arbors have topological properties that may also optimize their growth or function. We discovered that for a wide range of invertebrate and vertebrate neurons the distributions of their subtree sizes follow power laws, implying that they are scale invariant. The power-law exponent distinguishes different neuronal cell types. Postsynaptic spines and branchlets perturb scale invariance. Through simulations, we show that the subtree-size distribution depends on the symmetry of the branching rules governing arbor growth and that optimal morphologies are scale invariant. Thus, the subtree-size distribution is a topological property that recapitulates the functional morphology of dendrites.
The establishment and maintenance of protected areas (PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation, but available land and conservation funding is limited. Therefore, optimizing resources by selecting the most beneficial PAs is vital. Here, we advocate for a flexible and transparent approach to selecting protected areas based on multiple objectives, and illustrate this with a decision support tool on a global scale. The tool allows weighting and prioritization of different conservation objectives according to user-specified preferences, as well as real-time comparison of the selected areas that result from such different priorities. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between species protection and ecosystem integrity. Outputs indicate that decision makers frequently face trade-offs among conflicting objectives. Nevertheless, we show that transparent decision-support tools can reveal synergies and trade-offs associated with PA selection, thereby helping to illuminate and resolve land-use conflicts embedded in divergent societal and political demands and values.
The toxicity of microplastics on Daphnia magna as a key model for freshwater zooplankton is well described. While several studies predict population-level effects based on short-term, individual-level responses, only very few have validated these predictions experimentally. Thus, we exposed D. magna populations to irregular polystyrene microplastics and diatomite as natural particle (both ≤ 63 μm) over 50 days. We used mixtures of both particle types at fixed particle concentrations (50,000 particles mL-1) and recorded the effects on overall population size and structure, the size of the individual animals, and resting egg production. Particle exposure adversely affected the population size and structure and induced resting egg production. The terminal population size was 28–42% lower in exposed compared to control populations. Interestingly, mixtures containing diatomite induced stronger effects than microplastics alone, highlighting that natural particles are not per se less toxic than microplastics. Our results demonstrate that an exposure to synthetic and natural particles has negative population-level effects on zooplankton. Understanding the mixture toxicity of microplastics and natural particles is important given that aquatic organisms will experience exposure to both. Just as for chemical pollutants, better knowledge of such joint effects is essential to fully understand the environmental impacts of complex particle mixtures.
Environmental Implications While microplastics are commonly considered hazardous based on individual-level effects, there is a dearth of information on how they affect populations. Since the latter is key for understanding the environmental impacts of microplastics, we investigated how particle exposures affect the population size and structure of Daphnia magna. In addition, we used mixtures of microplastics and natural particles because neither occurs alone in nature and joint effects can be expected in an environmentally realistic scenario. We show that such mixtures adversely affect daphnid populations and highlight that population-level and mixture-toxicity designs are one important step towards more environmental realism in microplastics research.
Bacterial biosynthetic assembly lines, such as non-ribosomal peptide synthetases (NRPS) and polyketide synthases, are often subject of synthetic biology – because they produce a variety of natural products invaluable for modern pharmacotherapy. Acquiring the ability to engineer these biosynthetic assembly lines allows the production of artificial non-ribosomal peptides (NRP), polyketides, and hybrids thereof with new or improved properties. However, traditional bioengineering approaches have suffered for decades from their very limited applicability and, unlike combinatorial chemistry, are stigmatized as inefficient because they cannot be linked to the high-throughput screening platforms of the pharmaceutical industry. Although combinatorial chemistry can generate new molecules cheaper, faster, and in greater numbers than traditional natural product discovery and bioengineering approaches, it does not meet current medical needs because it covers only a limited biologically relevant chemical space. Hence, methods for high-throughput generation of new natural product-like compound libraries could provide a new avenue towards the identification of new lead compounds. To this end, prior to this work, we introduced an artificial synthetic NRPS type, referred to as type S NRPS, to provide a first-of-its-kind bicombinatorial approach to parallelized high-throughput NRP library generation. However, a bottleneck of these first two generations of type S NRPS was a significant drop in production yields. To address this issue, we applied an iterative optimization process that enabled titer increases of up to 55-fold compared to the non-optimized equivalents, restoring them to wild-type levels and beyond.
In humans, screams have strong amplitude modulations (AM) at 30 to 150 Hz. These AM correspond to the acoustic correlate of perceptual roughness. In bats, distress calls can carry AMs, which elicit heart rate increases in playback experiments. Whether amplitude modulation occurs in fearful vocalisations of other animal species beyond humans and bats remains unknown. Here we analysed the AM pattern of rats’ 22-kHz ultrasonic vocalisations emitted in a fear conditioning task. We found that the number of vocalisations decreases during the presentation of conditioned stimuli. We also observed that AMs do occur in rat 22-kHz vocalisations. AMs are stronger during the presentation of conditioned stimuli, and during escape behaviour compared to freezing. Our results suggest that the presence of AMs in vocalisations emitted could reflect the animal’s internal state of fear related to avoidance behaviour.
Engineering of thioesterase YciA from Haemophilus influenzae for production of carboxylic acids
(2023)
Acyl-CoA-thioesterases, which hydrolyze acyl-CoA-esters and thereby release the respective acid, have essential functions in cellular metabolism and have also been used to produce valuable compounds in biotechnological processes. Thioesterase YciA originating from Haemophilus influenzae has been previously used to produce specific dicarboxylic acids from CoA-bound intermediates of the ethylmalonyl CoA pathway (EMCP) in Methylorubrum extorquens. In order to identify variants of the YciA enzyme with the capability to hydrolyze so far inaccessible CoA-esters of the EMCP or with improved productivity, we engineered the substrate-binding region of the enzyme. Screening a small semi-rational mutant library directly in M. extorquens yielded the F35L variant which showed a drastic product level increase for mesaconic acid (6.4-fold) and 2-methylsuccinic acid (4.4-fold) compared to the unaltered YciA enzyme. Unexpectedly, in vitro enzyme assays using respective M. extorquens cell extracts or recombinantly produced thioesterases could not deliver congruent data, as the F35L variant showed strongly reduced activity in these experiments. However, applied in an Escherichia coli production strain, the protein variant again outperformed the wild-type enzyme by allowing threefold increased 3-hydroxybutyric acid product titers. Saturation mutagenesis of the codon for position 35 led to the identification of another highly efficient YciA variant and enabled structure-function interpretations. Our work describes an important module for dicarboxylic acid production with M. extorquens and can guide future thioesterase improvement approaches.
Anthropogenic interventions have altered all ecosystems around the world. One of those ecosystems are forests, the main resource for timber. They have been strongly transformed in their structure with large consequences on forest biodiversity. Especially the decrease in dead-wood volume due to the timber extraction and alternation of natural forest structures with even-aged stands of less diverse tree species composition has put especially saproxylic, i.e., dead-wood dependent species, under threat, which comprise about 20% of all forest species. Beetles, fungi and bacteria are three functional important groups for decomposition processes but we still lack much information about their sampling and the drivers of their diversity, thus it is difficult to comprehensively protect their diversity. Saproxylic fungi are a highly diverse species group and the main drivers of dead-wood decomposition; hence they play a major role in the global carbon cycle. Due to their cryptic lifestyle, many species are still unknown, but the recent advances in environmental DNA barcoding methods (metabarcoding) shed light on the formerly underestimated diversity. Yet, this method's accuracy and suitability in detecting specific species have not been assessed so far, limiting its current usefulness for species conservation. On the other hand, these methods are a convenient tool to study highly diverse areas with high numbers of unknown species, enabling the study of global diversity and its drivers, which are unknown for saproxylic fungi, but important to assess to predict the future impacts of global change. Since nature conservation concepts are usually not applied on a global scale, the drivers of diversity must also be assessed on smaller scales. Besides understanding the drivers of diversity, to identify focus scales to create comprehensive, evidence-based conservation concepts must utilize multi-taxonomic studies since saproxylic species are differently sensitive towards environmental variables and closely interact with each other. Filling these knowledge gaps is utterly needed to protect the high saproxylic diversity and ensure the functional continuity of decomposition processes, especially regarding the global change.
To address the usefulness of metabarcoding for fungal species conservation, I compared the traditional method of fruit body sampling with metabarcoding and their efficiency in detecting threatened fungal species in the first chapter of this thesis. Both methods have advantages and disadvantages. Their ability to detect threatened saproxylic fungal species and their dependencies on detecting specific fungal groups have not been compared, albeit they are important to inform species conservation like Red Lists properly. I found metabarcoding to generally detect more threatened fungal species than fruit body sampling with a higher frequency than fruit body sampling. Moreover, fruit body sampling detected a unique set of species, while fruit body sampling missed large parts of fungal diversity due to species-specific fruiting characteristics. Metabarcoding with high sampling intensity is thus a viable method to assess threatened saproxylic fungal diversity and inform nature conservation like Red Lists about distribution and abundances. Nevertheless, a complementary approach with fruit body sampling is indispensable for assessing all threatened fungal species.
In order to analyse the global diversity of saproxylic fungi and its drivers, I examined whether fungal species richness increases from the poles towards the equator and thus follows the latitudinal diversity gradient already found in many other species groups. I further investigated whether such an increase is caused by increasing ecological specialisation, i.e., niche partitioning, or local tree diversity, i.e., niche space. Gamma diversity per biome increased from the boreal, over the temperate to the tropics and thus confirmed the latitudinal diversity for saproxylic fungi. Contrastingly, alpha diversity at the log level did not significantly increase towards the tropics, suggesting a grain size dependency of the observed pattern and an equal niche space within dead-wood across latitudes. Ecological specialisation on the plot level was globally on a high level but did not increase significantly towards the equator. Additionally, I found local tree species richness to drive plot-based fungal diversity. Further analysis of gamma diversity against the total number of sampled tree species strengthened the assumption that tree species diversity and not increased ecological specialisation was the main driver of the latitudinal diversity gradient, as there was no significant difference between the gamma diversity of the temperate and tropical biome. Nonetheless, as the gamma diversity of the boreal biome was still significantly smaller, my results do not allow a complete neglection of the ecological specialisation hypothesis. The overall results indicate a strong dependency of saproxylic fungi diversity with host tree species diversity and that the global loss of tree species threatens saproxylic fungi with an unpredictable impact on carbon and nutrient cycling.
To support saproxylic conservation, I conducted two analyses. First, I compared the beta diversity of the three main decomposer groups (beetles, fungal fruit bodies, mycelial fungi (metabarcoding), and bacteria (metabarcoding)) across different scales to assess the impact of different environmental variables on their overall diversity. I used an experimental design to disentangle two different spatial scales, influenced by differences in macroclimate, forest microclimate and spatial distance, and two host scales, driven by differences between tree lineages and tree species. I set these beta diversities in relation to the gamma diversity of the three main decomposer groups to identify whether a unified conservation concept could be applied to one scale to optimally protect the diversity of all three species groups. Second, I identified whether diversity and community composition of fungi and bacteria differed among climate and land use gradients. Further I explored whether specialisation and niche packing could explain the expected pattern. To do so I used an experimental design disentangling climate and land use across a large gradient in Germany. The results differed among the species groups, denying a unified conservation concept focusing on one scale. Saproxylic beetle and fruit body beta diversity was equally high on each scale, as they are more sensitive towards environmental factors like macro- and microclimate. On the other hand, mycelial fungi and bacteria beta diversity was highest on the host scale, especially the host tree scale, indicating a high host specificity of the two groups. The second study also identified tree species as the main driver of diversity and community composition of these two study groups. Specialisation of fungi was not influenced by land use or climate. Bacterial specialisation and diversity were under a strong influence of mean precipitation. Comprehensive conservation of multi-taxonomic diversity across regions thus requires the integration of several scales. Within different macroclimatic regions, forests of varying microclimates, i.e., forest management, must be implemented. In these forests, dead-wood of different tree lineages, i.e., angio- and gymnosperms and tree species, must be provided.
Taken together, I could demonstrate that metabarcoding is an efficient method to sample threatened fungal species and identify differing drivers of fungal diversity present as fruit bodies or mycelium. Its usefulness will further increase due to the ongoing improvement of sequencing databases and thus better inform conservation concepts. Using metabarcoding, I could demonstrate that high host specialisation of saproxylic fungi is not a European but a global phenomenon and identify tree species loss under global change as one major concern for saproxylic diversity. My dissertation further highlighted the importance of multi-taxonomic studies for evidence-based nature conservation, as different species groups require varying concepts. These results were especially important for saproxylic bacteria as the drivers of their diversity are still largely unknown. Howbeit, large research gaps still exist regarding the impacts of global change on species and processes. Moreover, the spatial coverage of studies is needed to confirm or neglect the generality of current research especially concerning the highly diverse tropical areas. An increased focus on the drivers of diversity in these areas is crucial to ensure a globally comprehensive saproxylic conservation and the various ecosystem functions they control.
Influenza is a contagious respiratory disease caused by influenza A and influenza B viruses. The World Health Organisation (WHO) reports that annual influenza epidemics result in approximately 1 billion infections, 3 to 5 million severe cases, and 300 to 650 thousand deaths. Understanding hidden mechanisms that lead to optimal vaccine efficacy and improvement antiviral treatment strategies remain continuous and central tasks. First, regarding the immune response to vaccines and natural infections, the antibody response echoes the dynamics of diverse immune elements such as B-cells, and plasma cells. Also, responses reflect the processes for B-cells to gain and adapt affinity for the virus. Antibodies (Abs) that respond to the virus surface proteins, particularly to the hemagglutinin (HA), have been identified to protect against infection. The Abs responses binding to HA can be broadly protective as this protein is considerably accessible on the virion. When following sequential infections with similar influenza strains, i.e. two infections with different strains of a subtype, an enhanced breadth and magnitude of Abs response is developed, mainly after the second infection. The effect of being effective to new strains is called Abs cross-reaction.
On the other hand, as for antiviral treatment, the WHO currently approves the use of neuraminidase inhibitors (NIs) such as zanamivir and oseltamivir. Diverse research areas such as system biology, learning-based methods, control theory, and systems pharmacology have guided the development of modern treatment schemes. To do so, mathematical models are used to describe a wide range of phenomena such as viral pathogenesis, immune responses, and the drug's dynamics in the body. Drug dynamics are usually expressed in two phases, pharmacokinetics (PK) and pharmacodynamics (PD) - the PK/PD approach. These schemes leverage pre-clinical and clinical data through modeling and simulation of infection and drug effects at diverse levels. Under such a framework, control-based scheduling systems seek to tailor optimal antiviral treatment for infectious diseases. Thus, influenza treatment can be theoretically studied as a control-based optimization duty (about systems stability, bounded inputs, and optimality). Finally, towards real-world implementation, learning-based methods such as neural networks (NNs) can guide solving issues on the control-based performance. Using NNs as identifiers provide a setting to deal with infrequent measures and uncertain parameters for the control systems.
This thesis theoretically explores central mechanisms in influenza infection via modeling and control approaches. In the first project, we explore how and to what extent antibody-antigen affinity flexibility could guide the Abs cross-reaction in two sequential infections using a hypothetical family of antigens. The set of antigens generally represent strains of influenza, such as those of a subtype. Each antigen is composed of a variable and a conserved area, generically representing the structures of the HA, head, and stalk, respectively. We test diverse scenarios of affinity thresholds in the conserved and variable areas of the antigens. The Abs response reaches a high magnitude when using equivalent affinity thresholds in the conserved and variable areas during the first infection. However, improved cross-reaction is developed when slightly increasing the affinity threshold of the variable area for the second infection. Key mutations via affinity maturation is a feature that, together with affinity flexibility between infections, guides Abs cross-reaction in the model outcome. These results could correlate with studies pointing out that broad responses might be dependent on reaching specific mutations for getting affinity to a newly presented antigen while broadly reaching related antigens. The general platform may serve as a proof-of-concept for exploring fundamental mechanisms that favor the Abs cross-reaction.
In a second project, theoretical schemes are developed to combine impulsive and inverse optimal control strategies to address antiviral treatment scheduling. We present results regarding stability, passivity, bounded inputs, and optimality using impulsive action. The study is founded on mathematical models of the influenza virus (target-cell limited model) adjusted to data from clinical trials. In these studies, participants were experimentally infected with influenza H1N1 and treated with NIs. Results show that control-based strategies could tailor dosage and reduce the amount of medication by up to 44%. Also, control-based treatment reaches the efficacy (98%) of the current treatment recommendations by the WHO. Monte Carlo simulations (MCS) disclose the robustness of the proposed control-based techniques. Using MCS, we also explore the applicability to the individualized treatment of infectious diseases through virtual clinical trials. Furthermore, bounded control strategies are applied directly in drug dose estimation accounting for overdose prevention. Finally, due to the limitations of the available technology intended for clinical practice, we emphasize the necessity of developing system identifiers and observers for real-world applications.
In the third project, the problem of data scarcity and infrequent measures in the real world is handled by means of learning-based methods. System identification is derived using a Recurrent High Order Neural Network (RHONN) trained with the Extended Kalman filter (EKF). Lessons learned from impulsive control frameworks are taken to develop a neural inverse optimal impulsive control --neurocontrol. The treatment efficacy is tested for early (one day post-infection) and late (2 to 3 days post-infection) treatment initiation. The neurocontrol reaches an efficacy of up to 95% while saving almost 40% of the total drug in the early treatment. Robustness is tested via virtual clinical trials using MCS.
Lastly, taking all together, the schemes developed in this thesis for modeling the Abs cross-reaction and control-based treatment tailoring can be extended and adapted to explore similar phenomena in different respiratory pathogens, such as SARS-CoV-2.
In order to effectively address global environmental problems, it is important that future decision-makers in society are aware of the safe operation space for humans, which is limited by the planetary boundaries. Until now, however, there has been a lack of international studies examining how the planet's boundaries are perceived. In this study, we investigated how students of environmental and sustainability studies in 35 countries (n = 4140) assess the planetary boundaries. Based on the rating, using spectral clustering, the 35 countries were assigned to five different clusters. Four indicators (Human Development Index, Legatum Prosperity Index, Natural Resources Income and Forest Area) were used to provide explanations for the clustering result. The indices allow a distinction between the clusters and provide initial explanations for the clustering. The results provide important insights for today's decision-makers, as possible measures for action in the individual countries can be derived from the findings.
Unter den weltweit in ständigem Gebrauch befindlichen Chemikalien befinden sich nicht nur Verbindungen mit akuter toxischer Wirkung, sondern auch solche mit Wirkung auf das endokrine System. Eine große Rolle spielt hier vor allem die Störung der Geschlechtsdifferenzierung und der Reproduktion, ausgelöst durch natürliche oder synthetische Chemikalien mit endokrinem Potential, sogenannte endokrine Disruptoren (ED). Diese Chemikalien können über unterschiedliche Eintragspfade in die Umwelt gelangen. Seit Mitte des 20. Jahrhunderts werden mehr und mehr Fälle bekannt, in denen anthropogene Chemikalien die Pflanzen- und Tierwelt belasten, darunter zahlreiche Befunde zu Störungen des Hormonsystems von Mensch und Tier.
Im Rahmen der Gefahren- und Risikobewertung steht bereits eine Vielzahl harmonisierter Prüfrichtlinien für die Identifizierung und Evaluierung der Effekte von (potentiellen) ED zur Verfügung. Um die Gesamtheit aller potentiellen Interaktionen von ED mit dem Hormonsystem detektieren zu können, ist die In-vivo-Untersuchung an Vertebraten in der Chemikalienregistrierung bisher unabdingbar. Bei der Untersuchung endokriner Potentiale in höheren Vertebraten spielen vor allem nager- und vogelbasierte Testsysteme eine wichtige Rolle. Diese bergen jedoch einen hohen zeitlichen, personellen und finanziellen Aufwand und erfordern eine massive Zahl an Versuchstieren, die für diese Tests benötigt werden. Darüber hinaus beinhalten Tierversuche eine Vielzahl von Problemen einschließlich ethischer Bedenken, die sich als Konsequenz der Tierhaltung unter Versuchsbedingungen ergeben. Ein sehr interessanter und vielversprechender Ansatz zur Reduktion von Tierversuchen ist die Entwicklung eines standardisierten Verfahrens für die Untersuchung potentieller ED in Vogelembryonen. Auf Vogelembryonen basierende In-ovo-Modelle stellen einen Mittelweg zwischen In-vitro- und In-vivo-Testsystemen dar. Mit dem Vogeleitest wird der sich entwickelnde Embryo, das für ED sensitivste Entwicklungsstadium im Leben eines Organismus, berücksichtigt.
Das Ziel der vorliegenden Arbeit war die Entwicklung und Eignungsuntersuchung eines auf dem Embryo des Haushuhns (Gallus gallus domesticus) basierenden Testsystems für den Nachweis von ED. Das resultierende Testsystem soll als Alternativmethode zu bisher etablierten nager- und vogelbasierten Testsystemen für die Untersuchung der Effekte hormonell aktiver Substanzen auf die Geschlechtsdifferenzierung in höheren Wirbeltieren eingesetzt werden.
Die im Rahmen der vorliegenden Dissertation durchgeführten Arbeiten umfassten sowohl die Charakterisierung der Normalentwicklung des Hühnerembryos, unbeeinflusst durch ED, als auch die morphologisch-histologischen Veränderungen der Gonaden von substanzexponierten Embryonen. Für die Untersuchung substanzbedingter Effekte, welche den Schwerpunkt der vorliegenden Arbeit darstellen, wurden die Embryonen gegenüber verschiedenen (anti)estrogenen und (anti)androgenen Substanzen exponiert. Unter Einfluss der Estrogene Bisphenol A (BPA) und 17α-Ethinylestradiol (EE2) entwickelten sich die Keimdrüsen der Männchen zu Ovotestes, während Weibchen ein Ovar mit deutlich schmalerem Cortex ausbildeten. Unter Einfluss der Antiestrogene Fulvestrant und Tamoxifen blieben Effekte auf die Gonaden männlicher Embryonen aus, eine durch das potente Estrogen EE2 hervorgerufene Feminisierung männlicher Gonaden konnte durch beide Substanzen jedoch effektiv antagonisiert werden. Weibchen bilden unter Einfluss von Tamoxifen deutlich schmalere linke Gonaden mit einem missgebildeten Cortex aus. Unter Einfluss der Androgene Tributylzinn (TBT) und 17α-Methyltestosteron (MT) blieben die Effekte auf männliche Embryonen aus, während die Weibchen anatomisch virilisierte Gonaden und eine Reduktion des linken gonadalen Cortex aufwiesen. Allein die untersuchten antiandrogenen Versuchssubstanzen Cyproteronacetat (CPA), Flutamid und p,p´-Dichlorodiphenyldichloroethen (p,p´-DDE) hatten keinen Effekt auf die gonadale Geschlechtsdifferenzierung männlicher und weiblicher Hühnerembryonen.
Es konnte gezeigt werden, dass der Embryo von G. gallus domesticus einen sensitiven Organismus innerhalb des Tierreichs darstellt und hinreichend sensitiv auf eine Reihe von endokrin wirksamen und reproduktionstoxischen Chemikalien reagiert. Anatomische und histologische Änderungen der Gonaden können daher als Biomarker für die Wirkung von ED bei Vögeln nützlich sein. Die untersuchten Endpunkte beziehen sich jedoch auf apikale Effekte und liefern keine mechanistischen Informationen zu den untersuchten Substanzen. Der
Hühnereitest ist eine sinnvolle Ergänzung zur bestehenden OECD-Testbatterie und zeichnet sich besonders durch seine kostengünstige und einfache Handhabung im Labor sowie einfach durchzuführende Tests aus. Durch die vergleichsweise kurze Versuchsdauer von nur 19 Tagen ist ein schnelles Substanzscreening möglich, welches zeitlich deutliche Vorteile gegenüber den etablierten nager- und vogelbasierten Testsystemen hat. Als Alternative zu bisherigen Assays könnte der vorgeschlagene Hühnereitest dazu beitragen, im Rahmen der (öko)toxikologischen Gefährdungs- und Risikobewertung von Chemikalien künftig weniger Versuchstiere zu verwenden.