Open Access

Age is the single biggest risk factor for most major human diseases. As such, understanding the intricate molecular changes that drive biological aging holds great promise in attempting to slow the onset of systemic diseases and thereby increase the effective health-span in modern societies. This thesis explores several computational approaches to capture and analyze the molecular biological alterations triggered by intrinsic and extrinsic aging using skin as a model tissue to deliver genes and pathways as potential targets for intervention strategies. Publication 1 demonstrates the utility of multi-omics data integration strategies for aging research, leading to the identification of four latent aging phases in skin tissue through an integrated cluster analysis of gene expression and DNA methylation data. The four phases improved the detection of molecular aging signals and were shown to be associated with sunbathing habits of the test subjects. Deeper analysis revealed extensive non-linear alterations in various biological pathways particularly at the transition into the fourth aging phase, coinciding with menopause, with potentially wide-reaching functional implications. Publication 2 describes the development of a novel type of age clock, that provides a new level of interpretability by embedding biological pathway information in the architecture of an artificial neural network. The clock not only generates meaningful biological age estimates from gene expression data, but further allows simultaneous monitoring of the aging states of various biological processes through the activations of intermediate neurons. Analyses of the inner workings of the clock revealed a wide-spread impact of aging on the global pathway landscape. Simulation experiments using the transcriptomic clock recapitulated known functional aging gene associations and allowed deciphering of the pathways by which accelerated aging conditions such as chronic sun exposure and Hutchinson-Gilford progeria syndrome exert their effects. Publication 3 further explores the molecular alterations caused by the pro-aging effector UV irradiation in the skin. The multi-omics data analysis of repetitively irradiated skin revealed signs of the immediate acquisition of aging- and cancer-related epigenetic signatures and concurrent wide-spread transcriptional changes across various biological processes. Investigations into the varying resilience to irradiation between subjects revealed prognostic biomarker signatures capable of predicting individual UV tolerances, with accuracies far surpassing the traditional Fitzpatrick classification scheme. Further analysis of the transcripts and pathways associated with UV tolerance identified a form of melanin-independent DNA damage protection in individuals with higher innate UV resilience. Together, the approaches and findings described in this thesis explore several new angles to advance our understanding of aging processes and external drivers of aging such as UV irradiation in the human skin and deliver new insight on target genes and pathways involved.

Many viral structural proteins can self-assemble into virus-like particles (VLPs). VLPs can serve as an effective vaccine or be used as a vaccine platform. One of these structural proteins is the hepatitis B virus core antigen (HBcAg), which appears to be suitable as an antigen carrier due to its high immunogenicity. HBcAg has a major immunodominant region (MIR) that is presented on the surface of the VLPs after self-assembly. Foreign antigens can be inserted into this region. Since HBcAg VLPs, unlike the Hepatitis B virus (HBV), do not have an envelope, they are not able to penetrate cell membranes efficiently. As an extracellular antigen, HBcAg VLPs primarily induce a strong humoral immune response. In the present study, we investigated the extent to which HBcAg can be modified to also elicit an enhanced cellular, particularly a cytotoxic, immune response. A cytotoxic CD8+ T cell response is predominantly induced by intracellular antigens. Therefore, our goal was to increase the cell penetration capacity of VLPs. We aimed to achieve this by fusing cell-penetrating peptides (CPPs) to HBcAg. CPPs can spontaneously penetrate cell membranes to enter the cytoplasm of cells. To guarantee that the CCPs were localized to the surface of the VLPs, we fused CPPs to the N-terminus of HBcAg. The CCPs were followed by a tag to allow the purification of VLPs. The T cell epitopes, against which the induced CTL should be directed, were derived from the Large T antigen and inserted into the MIR of HBcAg. Finally, we fused fluorescent proteins to the C-terminus of HBcAg to track the entry of VLPs into cells. Modifications of HBcAg may lead to reduced stability or altered structure of VLPs. To analyze the stability of VLPs, we used nanoscale differential scanning fluorimetry (nanoDSF) analysis. This revealed that the N-terminal fusion of CPPs or the tag to HBcAg does not reduce VLP stability. However, some peptides incorporated into the MIR had a significant effect on the structure and stability of the VLPs. While the incorporation of a Flag-tag or a peptide from ovalbumin had no negative effect on VLP stability, the incorporation of peptides representing T cell epitopes of Large T antigen interfered with VLP formation. Denaturation and reassembly of the aggregates significantly improved the homogeneity of the VLPs, and the C-terminal addition of arginine-rich domains enhanced stability. Using live cell imaging and flow cytometry, we demonstrated that HBcAg VLPs functionalized with CPP exhibited up to 40% more efficient penetration into professional antigen-presenting cells (JAWS II) than HBcAg VLPs without CPP. This resulted in the increased presentation of integrated T cell epitopes by dendritic cells. In vivo, we detected significantly increased induction of SV40 Large T antigen-specific CTL in mice immunized with CPP-conjugated VLPs compared to unconjugated VLPs. In this study, we demonstrated that a stronger cellular immune response can be induced by CPP-functionalized HBcAg VLPs than with the unmodified HBcAg VLPs in vitro as well as in vivo. This discovery may have positive implications for future vaccine development where an enhanced cellular component of the immune response is desirable.

Emerging infectious diseases are among the greatest threats to human, animal and plant health as well as to global biodiversity. They often arise following the human-mediated transport of a pathogen beyond its natural geographic range, where host species are typically not well adapted due to a lack of co-evolutionary host-pathogen dynamics. One such pathogen is the fungus Pseudogymnoascus destructans (Pd), which causes White-Nose disease in hibernating bats. While Pd was first observed in North America where it has led to mass-mortalities in some bat species, the pathogen originates from Eurasia where infection is not associated with mortality. Most of the Pd research has focused on the invasive North American range, which likely underestimated the genetic structure of the pathogen and the role it might play in the disease dynamics. In my work, I therefore evaluated the genetic structure of Pd in its native range with the aim of uncovering cryptic diversity and further use population genetic data to address some key ecological aspects of the disease dynamics. With an extensive reference collection of more than 5,000 isolates from 27 countries I first demonstrated strong differentiation between two monophyletic clades across several genetic measures (multi-locus genotypes, full genome long-read sequencing and Illumina NovaSeq on isolate pools). These findings are consistent with the presence of two cryptic species which are both causative agents of bat White-Nose disease (‘Pd-1’, which corresponds to P. destructans sensu stricto, and ‘Pd-2’). Both species exist in the same geographic range and co-occur in the same hibernacula (i.e., in sympatry), though with specialised host preferences. I further described the fine-scale population structure in Eurasia which revealed that most genotypes are unique to single hibernacula (more than 95% of genotypes). The associated differences in microsatellite allele frequencies among hibernacula allowed the use of assignment methods to assign the North American isolates (exclusively Pd-1) to regions in Eurasia. Hence, a region in Ukraine (Podilia) is the most likely origin of the North American introduction. To gain further insights into the spatial and temporal dynamics of White-Nose disease on a localised scale, several hibernacula were sampled with high intensity (artificial hibernaculum in Germany and natural karst caves in Bulgaria). Low rates of Pd gene flow were observed even among closely situated hibernacula. This indicates that Pd does not remain viable on bats over summer or it would be frequently exchanged among bats (and hence hibernacula) resulting in a homogenous distribution of genotypes. Instead, bats need to become re-infected each hibernation season to explain the yearly re-occurrence of White-Nose disease. Given the distribution and richness of Pd genotypes on hibrnacula walls and infected bats of the same hibernacula, bats become infected from the hibernacula walls when they return after summer. This means that environmental reservoirs exist within hibernacula (i.e., the walls) on which Pd spores persist during bat absence and which drive the yearly re-occurrence of White-Nose disease. In an experimental setup, I confirmed the long-term viability of Pd spores on abiotic substrate for at least two years and furthermore discovered temporal variations in Pd spores’ ability to germinate. In fact, these variations followed a seasonal pattern consistent with the timing of bats absence (reduced germination) and presence (increased germination) and could indicate adaptations of Pd to the bats’ life-cycle. The infection of bats from environmental reservoirs hence seems to be a central aspect of White-Nose disease dynamics and Pd biology. Pds ability to remain viable for extended periods outside the host increases its risk of being anthropogenically transported and might have played a role in the emergence of White-Nose disease in North America. The existence of a second species (Pd-2) poses a great additional danger to North American bats considering that its introduction there could lead to deaths and associated population declines in so-far unaffected species given what is known about differing host species preferences in Eurasian bats. Even within the native range of Pd, the movement of Pd between differentiated fungal populations could facilitate genetic exchanges (e.g., through sexual reproduction) between genetically distant genotypes. Such genetic exchanges could lead to phenotypic jumps in pathogenicity or host-species preferences and should hence be prevented. The native range of a pathogen holds great potential to better understand the genetic and ecological basis of a (wildlife) disease. My work informs about the dangers associated with the accidental transport of Pd (and other pathogens) and highlights the need for ‘prezootic’ biosecurity-oriented strategies to prevent disease outbreaks globally. Once a pathogen has arrived in a new geographic range, and particularly if it has environmentally durable spores (as demonstrated for Pd), it will be difficult/impossible to eradicate. Furthermore, a pathogen’s ability to remain viable outside the host and infect them from environmental reservoirs has been associated with an increased risk of species extinctions and needs to be considered when designing management strategies to mitigate disease impact.

Zerebrale kavernöse Malformationen (CCMs) sind Gefäßfehlbildungen im Gehirn oder Rückenmark und können sich klinisch aufgrund einer erhöhten Blutungsbereitschaft mit Kopfschmerzen, Gefühls- und Sprachstörungen bis hin zu Krampfanfällen äußern. Sie treten sporadisch oder im Rahmen einer autosomal-dominant erblichen Form auf. Kausale Sequenzveränderungen sind dabei in den drei Genen CCM1, CCM2 und CCM3 bekannt. Die Detektionsrate für pathogene Varianten ist mit bis zu 60 % für sporadische Fälle und mit weit über 90 % für familiäre Fälle sehr hoch. Während Genpanel-Analysen sehr verlässlich Einzelnukleotidveränderungen, kleine Insertions- und Deletionsvarianten sowie Kopienzahlveränderungen detektieren können, werden komplexe Strukturvarianten oder Veränderungen in nicht-kodierenden Regionen kaum erfasst. Diese rücken jedoch für die bisher genetisch unaufgeklärten Fälle immer mehr in den Fokus des Interesses. Diese Arbeit adressiert daher zum einen die Identifizierung neuer Strukturvarianten und deren funktionale Interpretation im Kontext der CCM-Erkrankung. Im Rahmen der vorliegenden Arbeit ist der erstmalige Nachweis einer interchromosomalen Insertion bei einem CCM-Patienten gelungen. Die unbalancierte Insertion genomischen Materials von Chromosom 1 in die kodierende Region des CCM2-Gens konnte durch die Verbindung von bioinformatischen Auswertestrategien der Next Generation Sequencing-Genpanel-Daten, molekularzytogenetischen Analysen und einer molekularen Bruchpunktkartierung genau charakterisiert werden. Die Identifikation einer weiteren Strukturvariante, einer Deletion des Transkriptionsstarts von CCM1, verdeutlichte die Herausforderungen bei der Bewertung von Veränderungen in nicht-kodierenden Genbereichen. Für eine eindeutige Klassifikation der Variante wurden daher funktionale Analysen durchgeführt, die auf einer CRISPR/Cas9-vermittelten Nachbildung der Deletion in iPSCs und der anschließenden Differenzierung in Endothelzellen beruhte. Damit konnte gezeigt werden, dass die Deletion zu einem Verlust der CCM1 mRNA- und Proteinexpression führt. Zudem wurde in den differenzierten Endothelzellen eine für die CCM-Pathogenese charakteristische Deregulation von KLF2, THBS1, NOS3 und HEY2 beobachtet. Schließlich war es auf Basis dieser in vitro-Analysen möglich, die Variante entsprechend den ACMG-Richtlinien als wahrscheinlich pathogen zu bewerten und somit die molekulare CCM-Diagnose zu sichern. Die Verbindung des CRISPR/Cas9-Systems mit iPSCs ist nicht nur für die Variantenbewertung von großem Nutzen, sondern bietet auch das Potential zum besseren Verständnis von Krankheitsmechanismen. Ein weiterer Fokus der vorliegenden Arbeit lag daher auf der Etablierung und Verwendung iPSC-basierter Zellkulturmodelle für die CCM-Modellierung. Zunächst ist es gelungen, mehrere iPSC-Linien mit einer kompletten CRISPR/Cas9-vermittelten CCM1-, CCM2- oder CCM3-Inaktivierung zu generieren. Diese wurden anschließend für die Differenzierung in hBMEC-ähnliche Zellen und innovative dreidimensionale vaskuläre Organoide verwendet. In diesen Systemen konnte beispielsweise eindrücklich eine tumorähnliche Proliferation CCM3-defizienter Endothelzellen nachvollzogen werden, die nur in Kontakt mit Wildtyp-Zellen auftrat. RNA-Sequenzierungen in einem CCM1-basierten Knockout-Modell konnten darüber hinaus die Rolle von CCM1 als Endothel-spezifisches Suppressorgen stärken. Die im Rahmen der Arbeit etablierten Systeme werden zukünftig für weitere Fragestellungen der CCM-Pathogenese wie der endothelialen Barrierestörung eingesetzt und stellen darüber hinaus sehr gut geeignete Plattformen für die effektive Entwicklung dringend benötigter therapeutischer Ansätze dar.

Amid the current global biodiversity crisis, being able to accurately monitor the changing state of biodiversity is essential for successful conservation actions and policy. Despite the pressing need for reliable and cost-effective monitoring methods, collecting such data remains extremely difficult for elusive species, such as temperate zone bats. Although bats are important indicators of environmental changes, monitoring bat populations is challenging because they are nocturnal, volant, small, and highly sensitive to human activities and disturbance. Thus far, population trends of temperate zone bats have been mainly based on visual surveys, including winter hibernation counts at underground sites. However, as bats may not always be roosting in visible locations within the hibernacula, it is currently unknown how these estimates relate to actual population sizes. Infrared light barriers combined with camera traps are a novel method to monitor bats at underground sites. When installed at the entrance of hibernacula, infrared light barriers have the potential to estimate site-level population sizes more accurately than visual surveys, by counting all bats flying in and out of the site. Moreover, camera traps, consisting of a digital camera and white flash, can be used for species-level identification. However, for this new method to be applicable as a large-scale bat monitoring technique, it is important to characterize it with regard to three main criteria: is the method minimally invasive, is it accurate, and is it scalable in terms of spatial and temporal resolution? Therefore, the purpose of this thesis was to investigate the invasiveness and accuracy of this novel bat monitoring method, and to develop standardized and automated data analysis pipelines, both for the light barrier and camera trap data, to support the deployment of this method at scale. In Publication I, we used light barrier data, infrared video recordings and acoustic data from an experimental field study to investigate whether the white flash of the camera trap has any measurable short- or long-term effect on bat activity and behavior. The flash of the camera trap was turned on and off every week at each site, which allowed us to compare the activity and behavior of bats between flash-on and flash-off nights. We found that despite the high sensitivity of bats to disturbance, they did not change their nightly activity patterns, flight direction, echolocation behavior, or long-term site use in response to the white flash of the camera trap. Based on these results, we concluded that camera traps using a white flash are a minimally invasive method for monitoring bat populations at hibernacula, providing high quality images that allows species-level identification. In Publication II, we used infrared video surveillance to quantify the accuracy of infrared light barriers, and we described a standardized methodology to estimate population sizes and trends of hibernating bat assemblages using light barrier data. We showed that light barrier accuracy varies based on the model and location of the installation relative to the entrance, with the best combination achieving nearly perfect accuracy over the spring emergence phase. When compared to light barrier-based estimates, we found that visual counts markedly underestimated population sizes, recovering less than 10% of the bats at the most complex hibernacula. Moreover, light barrier-based population trends showed regional patterns of growth and decline that were not detectable using the visual count data. Overall, we established that the light barrier data can be used to estimate the population size and trends of hibernating bat assemblages with unprecedented accuracy and in a standardized way. In Publication III, we described a deep learning-based tool, BatNet, that can accurately and efficiently identify bat species from camera trap images. The baseline model was trained to identify 13 European bat species or species complexes using camera trap images collected at 32 hibernation sites (i.e., trained sites). We showed that the baseline model performance was very high across all 13 bat species on trained sites, as well as on untrained sites when the camera angle and distance from the entrance were comparable to the training images. At untrained sites with more atypical camera placements, we demonstrated the ability to retrain the baseline model and achieve an accuracy comparable to the trained sites. Additionally, we showed that the model can learn to identify a new species, while maintaining high classification accuracy for all original species. Finally, we established that BatNet can be used to accurately describe ecological metrics from camera trap images (i.e., species diversity, relative abundance, and species-specific phenology) that are relevant for bat conservation. We conclude that infrared light barriers and camera traps offer a minimally invasive and accurate method to monitor site-level bat population trends and species-specific phenological estimates at underground sites. Such remote data collection approaches are particularly relevant for monitoring large, complex hibernation sites, where traditional visual surveys are not feasible or account only for a small fraction of the actual population. Combining this automated monitoring method with a deep learning-based species identification tool, BatNet, allows us quickly and accurately analyze millions of camera trap images resulting from large-scale, long-term camera trap studies. As a result, we can gain unprecedented insights into the behavior and population dynamics of these enigmatic species, drastically improving our ability to support data-driven bat conservation.