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Generation of an efficient agent-based framework for the simulation of 3D multicellular systems
(2024)
In developmental biology, the focus has shifted from mainly considering genetic and molecular aspects to considering mechanical aspects, as it has become evident in recent years that mechanical forces, tensions, and physical interactions play a significant role alongside molecular mechanisms in developmental biology. Computational models provide a useful tool for the investigation of the complex cell choreography in tissue and organ development. In particular, they allow the identification of principles governing complex behaviours and greatly contribute to understanding self-organising systems. Agent-based models act as a ”virtual laboratory”, facilitating the formulation and testing of biological hypotheses.
In this work, a mathematical model is formulated to describe the dynamics and interactions of multicellular systems. This model formulation results in a large system of coupled stochastic differential equations. Furthermore, a simulation framework is introduced to solve the system of coupled stochastic differential equations numerically. In particular, mechanical processes such as cell-cell interactions, cell growth and division, cell polarity, and active migration are considered. Firstly, a CPU-based version of the simulation framework, implemented in Python and MATLAB, is presented. This version also provides scientists with limited programming experience the abil- ity to simulate systems involving several thousand cells. Additionally, a GPU-based framework version, implemented in CUDA and C++, is introduced. This version primarily targets modellers with advanced programming knowledge. It significantly reduces simulation runtime, allows for the simulation of very large systems, and incorporates additional extensions.
The implemented CPU-based simulation framework was applied to two different biological systems. The first application concerned inner cell mass organoids (ICM organoids), which serve as an experimental model system to study early embryogenesis. In particular, ICM organoids reflect the second cell fate decision, i.e., the differentiation into embryonic tissue and yolk sac, as well as subsequent cell sorting. Using the presented simulation framework, it was demonstrated that the experimentally observed local clustering of cell types can be attributed to mechanical processes, specifically cell growth, cell division, and cell fate inheritance. These results provide evidence that molecular cell fate determination occurs within a short period during the early development of ICM organoids, and that mechanical processes and interactions predominantly characterise subsequent processes. Furthermore, it was shown that differential adhesion and undirected cell movement in a three-dimensional system are sufficient to drive the segregation of different cell types.
The second biological application focused on pancreas-derived organoids, which simulate organ development, in this case, pancreas development. These organoids exhibit high variability in their qualitative behaviour, including volume oscillations, rotation and migration, fusions, and the formation of internal structures. The presented simulation framework was applied to the volume oscillations of the organoids. It was demonstrated that these oscillations depend significantly on the cell division dynamics and size of the organoids, as well as the elasticity and adhesion strength of the cells.
Both biological applications of the framework illustrate its modular structure and, thus, its adaptability to various biological systems. They also emphasise that mechanical processes play a fundamental role in the self-organisation of complex systems. The presented framework en- ables the efficient modelling of multicellular systems and serves as an effective tool for explaining complex behaviour by coupling simple underlying mechanisms.
The study of animal behavior is essential for gaining a better understanding of the behavior, patterns, and needs of animals. A better understanding not only serves scientific progress, but also plays an important role in improving husbandry conditions in zoos, which can help to improve animal welfare (Berger, 2010; Brando and Buchanan-Smith, 2018; Walsh et al., 2019; Rose and Riley, 2021).
The behavior of large herbivores differs significantly between day and night, and most ungulates are diurnal or crepuscular (Bennie et al., 2014; Gravett et al., 2017; Davimes et al., 2018; Wu et al., 2018). In contrast, many studies examine animal behavior during the day, and unfortunately there is little information on nocturnal behavior, including sleep behavior (Berger, 2010; Rose and Robert, 2013). However, sleep behavior, especially the proportion of REM sleep, is of great importance for the well-being of an individual (Hänninen et al., 2008; Fukasawa et al., 2018; Northeast et al., 2020).
To gain more insight into the behavior of ungulates in general, studies based on large samples of different species with a long recording period are useful. This is difficult to achieve with manual data analysis, as data collection and analysis in behavioral biology is time consuming and costly. Therefore, modern methods such as automated analysis are helpful in the field of behavioral biology (Norouzzadeh et al., 2018; Beery et al., 2020; Lürig et al., 2021).
Hence, the development of a software tool for the automated assessment of nocturnal behavior of ungulates in zoos is part of this dissertation. The resulting software tool is called BOVIDS (Behavioral Observations by Videos and Images using Deep-Learning Software) and allows the automatic evaluation of video material in three steps. In the first step, object detection, the individuals on the images are recognized and cut out in order to classify the behavior in the following step, action classification. In the final step, post-processing, errors of the automated analysis are corrected and the data is prepared for further use (Hahn-Klimroth et al., 2021; Gübert et al., 2022). To create such a system, it must first be trained. Typically, two nights per individual were manually annotated, resulting in a total of 594 manually annotated nights. In addition, 224,922 images were used to evaluate whether the system was already correctly recognizing the animals' behavior. Bounding boxes were either manually drawn or evaluated on a total of 201,827 images to train the object detection network.
The software package BOVIDS was used to analyze data from a total of 196 individuals from 19 different ungulate species over a period of 101,629 hours of video material from 9,239 nights. A night is defined as the period from 7 pm to 6 am. The species studied belong to the two orders of odd-toed ungulates (Perissodactyla) and even-toed ungulates (Artiodactyla). The focus is on the behavioral categories of standing, moving, lying – head up, and lying – head down, the latter corresponding to the typical REM sleep position of ungulates. Based on the analyzed data, several biological questions were discussed in this thesis. In addition to the activity budgets and rhythms underlying the night, factors influencing behavior are also investigated. In addition, the enclosure use by the animals is evaluated.
Zebras as representatives of the Perissodactyla spend about 25% of the night lying, while the average for the Artiodactyla studied is 77%. All species studied spend an average of 8.8% of the night in REM sleep (Gübert et al., 2023a), with a typical REM sleep phase lasting between 2.2 and 7.6 minutes (Gübert et al., 2023b). Only 0.7% of time during the night is spent with movement by the animals (Gübert and Dierkes). While the number of lying phases within the Artiodactyla is very constant with an average of five phases, the number of phases in the REM sleep position varies. Age, average species size and taxonomy were found to be influencing factors (Gübert et al., 2023a). With regard to rhythmicity, it is striking that most of the species studied show an increase in lying during the night and that a strong rhythmicity of behavior can be observed. The time between two lying events is very constant and is about two hours for most animals (Gübert et al., 2023b). With regard to enclosure use, it is striking that only a small part of the enclosure is used regularly. All individuals prefer to lie down on the bedding and most individuals prefer one or two different resting places (Gübert and Dierkes).
The data created as part of this thesis can contribute to a better overall understanding of ungulate behavior. The newly developed software package BOVIDS makes it relatively easy to analyze further data on this topic. Long-term studies can now be carried out more cost-effectively, making it easier to answer many questions in the future, such as investigating other influencing factors or responses to changes in husbandry conditions.
Biodiversity post-2020: Closing the gap between global targets and national-level implementation
(2021)
National and local governments need to step up efforts to effectively implement the post-2020 global biodiversity framework of the Convention on Biological Diversity to halt and reverse worsening biodiversity trends. Drawing on recent advances in interdisciplinary biodiversity science, we propose a framework for improved implementation by national and subnational governments. First, the identification of actions and the promotion of ownership across stakeholders need to recognize the multiple values of biodiversity and account for remote responsibility. Second, cross-sectorial implementation and mainstreaming should adopt scalable and multifunctional ecosystem restoration approaches and target positive futures for nature and people. Third, assessment of progress and adaptive management can be informed by novel biodiversity monitoring and modeling approaches handling the multidimensionality of biodiversity change.
Plants and insects often use the same compounds for chemical communication, but not much is known about the genetics of convergent evolution of chemical signals. The terpene (E)-β-ocimene is a common component of floral scent and is also used by the butterfly Heliconius melpomene as an anti-aphrodisiac pheromone. While the biosynthesis of terpenes has been described in plants and microorganisms, few terpene synthases (TPSs) have been identified in insects. Here, we study the recent divergence of 2 species, H. melpomene and Heliconius cydno, which differ in the presence of (E)-β-ocimene; combining linkage mapping, gene expression, and functional analyses, we identify 2 novel TPSs. Furthermore, we demonstrate that one, HmelOS, is able to synthesise (E)-β-ocimene in vitro. We find no evidence for TPS activity in HcydOS (HmelOS ortholog of H. cydno), suggesting that the loss of (E)-β-ocimene in this species is the result of coding, not regulatory, differences. The TPS enzymes we discovered are unrelated to previously described plant and insect TPSs, demonstrating that chemical convergence has independent evolutionary origins.
The main goal of this work is to contribute to the existing knowledge of soil micro-fungi in Panama and Germany. Studies about soil degradation and its influents in the soil fungi diversity have not been investigated as extensively in these countries. This is an extensive and challenging topic to examine since there is an immense phenotypic and genetic diversity in the soil fungal community and relating this community together with factors of soil degradation is an extensive task. For this reason, the present thesis studies the species identified in the study areas, in other words, the soil fungal diversity in relation to environmental factors in the Taunus Mountain range in Frankfurt, Germany, and in the Majagua valley in Chiriquí, Panama. Two complementary objectives were achieved, the first was the development of a theoretical irrigation model for degraded soils. The second was the development of a mobile application to facilitate laboratory work in the cultivation of soil micro-fungi.
The design of the methodology was based on identifying the species and relating the diversity found to soil factors. Soil samples were taken in both countries: the Taunus Mountain range was sampled eight times from January to November 2012 and the Majagua valley was sampled on three occasions between February and July 2012. In both studies, the areas included three different vegetation types (forest, grassland, and bare soil). Samples were separated for two purposes: the assessment of fungal diversity by molecular and morphological methods and soil characterization.
Soil samples used in the methodology of pyrosequencing were related to global climatic factors. Morphological identification was achieved with identification keys. Micro-fungi were cultivated in different media until obtaining pure cultures. Molecular identification was performed by getting the DNA sequences using the ITS1 and ITS4 primers and comparing the sequences with other reference sequences from GenBank. This was done considering the BLAST algorithm, which considered sequences that matched 98 % or more of maximum identity as reliable identifications.
Soil characterization was carried out to measure the soil's Physico-chemical properties; those abiotic factors were compaction, temperature, pH, moisture, and soil composition.
Species richness was calculated in each study area with the estimators Chao, Jackknife, and Bootstrap. Furthermore, the species accumulation curves were performed to observe the species discovery rate and estimate sample completeness. Estimate linear regression models correlated the influence between the soil factors (temperature, moisture, pH, soil compaction, and soil composition) and the species richness. In the same way, an analysis of ecological distance was undertaken based on the similarity in the species composition, compared across samples, and correlated with soil factors, using non-metric multidimensional scaling (NMDs).
Study of abundance showed differences between the bare soil abundances and the forest abundances in Germany and Panama; the grasslands in both countries work as transitional areas in the fungi abundance. The key stone species in Germany were Penicillium daleae, and Pochonia bulbillosa, whereas in Panama were Purpureocillium lilacinum and Trichoderma harzianum. Based on Pareto analysis, a theoretical irrigation model was developed to counteract the degradation effects on the abundance of micro-fungi in the soil.
Applications for mobile devices dealing with the cultivation of soil micro fungi were sought. Due to the small number of existing applications, a new App called Soil-Fungi-Cultures (SFC) was developed to facilitate data collection of cultivated soil micro fungi. App Inventor was the program used to design, program, test, and publish the application developed. The developed application was compared with other applications used in identifying bacteria cultures. The results showed that the new application needed more time to capture the records because it saves more information, the navigation flow was acceptable, the number of clicks was high, but it is due to the usefulness in data capture, and finally, the users rated it as a good application with an eight out of ten rating.
Pyrosequencing resulted in 204 Operational Taxonomic Units (OTUs) considering the two study areas (the Taunus Mountain range and the Majagua valley). The Pyrosequencing database was used to contribute to the most important study of fungal diversity globally based on OTUs, which surpasses any study of molecular and taxonomic diversity previously conducted. The principal result in this study was that the climatic factor is the best predictor of fungal richness and community composition on a global scale. However, the part of the research that focused on the local scale, that is to say, on the correlation patterns between the distribution of fungal species and abiotic factors, showed that the soil properties and degradation levels were not associated with fungal richness, diversity or soil composition in the study areas in Germany or Panama. The above confirms that there are exceptions to the way relationships between soil factors with fungal diversity are established at the local level.
In the case of soil samples used for morphological identification, 71 fungal species were obtained, 47 from Germany, and 32 from Panama.
RNA modification is a dynamic and complex process that involves the addition of various chemical groups to RNA molecules, contributing to their diversity and functional complexity. Among all the RNA modifications, N6-methyladenosine (m6A) is the most common post-transcriptional modification found in mRNA molecules, particularly in eukaryotic mRNA. It involves methylation of the adenosine base at the nitrogen-6 position. This modification plays a crucial role in many aspects of RNA metabolism, including splicing, stability, translation, and the cellular response to stress. With the development of m6A sequencing technologies, our knowledge of m6A has evolved rapidly over the past two decades. However, one of the most widely used m6A profiling techniques termed “m6A individual-nucleotide resolution UV cross-linking and immunoprecipitation (miCLIP)” suffers from a high unspecific background signal due to the limited antibody binding specificity.
To accurately discriminate m6A sites from the background signal in miCLIP data, in Chapter 4, I first developed different strategies to identify the true miCLIP2 signal changes that are corrected for the underlying transcript abundance changes. I performed this analysis on data that generated with an improved experiment protocol, named miCLIP2. With the best performing strategy, the Bin-based method, I detected more than 10,000 genuine m6A sites. I then used the information embedded in the genuine m6A sites to train a machine learning model - named "m6Aboost" - to enable accurate m6A site detection from the miCLIP2 data without a control dataset from an m6A depletion cell line. To allow an easy access for future users, I packaged the m6Aboost model into an R package that is available on Bioconductor.
Although previous studies have reported that m6A is involved in three different RNA decay pathways, it remains unclear how a pathway is selected for a specific transcript or m6A site. In Chapter 5, I reveal that m6A sites in the coding sequence (CDS) induce a stronger and faster RNA decay than the m6A sites in the 3’ untranslated region (3’UTR). Through an in-depth investigation, I found that m6A sites in CDS trigger a novel mRNA decay pathway, which I termed CDS-m6A decay (CMD). Importantly, CMD is distinct from the three previously reported m6A-mediated decay pathways. In terms of its mechanism, CMD relies on translation, where m6A sites in the CDS lead to ribosome pausing and subsequent destabilization of the transcript. The transcripts targeted by CMD are identified by the m6A reader protein YTHDF2, preferentially localized to processing bodies (P-bodies), and undergo degradation facilitated by the decapping factor DCP2. CMD provides a flexible way to control the expression of CDS m6A-containing transcripts which include many developmental regulators and retrogenes.
In summary, this PhD thesis introduces a novel workflow for identifying m6A sites in miCLIP data through the implementation of the m6Aboost machine learning model. Using the m6A sites identified by m6Aboost and additional data, a newly uncovered m6A-mediated mRNA decay pathway, CMD, is elucidated, providing valuable insights into m6A-mediated decay processes.
Terpene bilden mit mehr als 81.000 Verbindungen die größte Klasse der Naturstoffe. Nichtsdestotrotz wird ihre strukturelle Vielfalt durch die Isoprenregel begrenzt. Diese besagt, dass alle primären Terpensynthaseprodukte aus Bausteinen mit fünf Kohlenstoffatomen hervorgehen. Ihre Produkte sind somit kanonisch, da sie durch ein Vielfaches von fünf Kohlenstoffatomen dargestellt sind. In dieser kumulativen Arbeit wird die mikrobielle Produktion einer Vielzahl neuartiger nicht-kanonischer Terpene beschrieben und somit der chemische Strukturraum von Terpenoiden über die Grenzen der Isoprenregel hinaus erweitert. Um dies zu erreichen, wurden in verschiedenen Ansätzen die Gene des Mevalonatwege, einschließlich einer IPP-Isomerase gemeinsam mit verschiedenen Prenylpyrosphosphat-Methyltransferasen und Terpensynthasen in E. coli exprimiert und die Produktspektren der Biosynthesewege detailliert untersucht.
Ein breites Spektrum neuer C11-Terpene wurde als Nebenprodukt der bakteriellen 2-Methylisoborneol- oder 2-Methylenbornansynthasen entdeckt. Neben elf bekannten konnten 24 neuartige C11-Terpene nachgewiesen werden, die bisher noch nicht als Terpensynthase-Produkte beschrieben wurden. Vier davon, 3,4-Dimethylcumol, 2-Methylborneol und die beiden Diastereomere von 2-Methylcitronellol, konnten identifiziert werden. Außerdem wurde das C16-Terpen 6-Methylfarnesol als Produkt identifiziert.
Die Produktselektivität einer C11-Terpensynthasen, die 2 Methylenbornansynthase aus Pseudomonas fluorescens, wurde durch einen semirationalen Protein-Engineering-Ansatz verändert. Aminosäuren des aktiven Zentrums mit Einfluss auf die Produktselektivität wurden identifiziert. Entsprechende Varianten des Enzyms führen zu gänzlich veränderten Produktspektren. So wurden neue Einblicke in die Struktur-Funktions-Beziehung für C11-Terpensynthasen gewonnen und bisher unzugängliche nicht-kanonische Terpene produziert.
Eine IPP-Methyltranferase wurde identifiziert und charakterisiert, die den C5-Baustein der Terpenbiosynthese in eine Vielzahl von C6- und C7-Prenylpyrophosphate umwandelt. Die heterologe Expression in E. coli gemeinsam mit anderen Genen der Terpenbiosynthese erweitert das potenzielle Terpensynthase-Substratspektrum außerdem um C11-, C12-, C16- und C17 Prenylpyrosphopshate. Darüber hinaus konnten polymethylierte C41-, C42-und C43-Carotinoide synthetisiert werden. So wurde die Terpenbiosynthese durch die Modifikation ihrer Bausteine erweitert und neue ungewöhnliche Terpene produziert.
Diurnal and nocturnal behaviour of cheetahs (Acinonyx jubatus) and lions (Panthera leo) in zoos
(2022)
Mammals are constantly exposed to exogenous and endogenous influences that affect their behaviour and daily activity. Light and temperature, as well as anthropogenic factors such as husbandry routines, visitors, and feeding schedules are potential influences on animals in zoological gardens. In order to investigate the effects of some of these factors on animal behaviour, observational studies based on the analyses of activity budgets can be used. In this study, the daily and nightly activity budgets of six lions (Panthera leo) and five cheetahs (Acinonyx jubatus) from four EAZA institutions were investigated. Focused on the influencing factor light and feeding, we analysed these activity budgets descriptively. Behaviour was recorded and analysed during the winter months over an observation period of 14 days and 14 nights using infrared-sensitive cameras. Our results show that lions and cheetahs exhibit activity peaks at crepuscular and feeding times, regardless of husbandry. Thus, lions in captivity shift nocturnal behaviour familiar from the wild to crepuscular and diurnal times. In cheetahs, in contrast, captive and wild individuals show similar 24 h behavioural rhythms. The resting behaviour of both species is more pronounced at night, with cheetahs having a shorter overall sleep duration than lions. This study describes the results of the examined animals and is not predictive. Nevertheless, the results of this study make an important contribution to gaining knowledge about possible factors influencing the behaviour of lions and cheetahs in zoos and offer implications that could be useful for improving husbandry and management.
The success of the increasing use of technology in education is highly dependent on learner acceptance. Although the Technology Acceptance Model (TAM) is dominant in research for surveying acceptance of technology, it does not allow the prediction of a successful first time use of technology. The successful first time use can be determined with the survey of technology affinity, as it corresponds to the expression of certain personality traits of users and is thus detached from the specific technology. Since there are no measurement instruments for the educational sector so far and existing instruments for measuring technology affinity do not meet the specific requirements for use in the educational context (e.g., limited time for questioning), we present the single item Inclusion of Technology Affinity in Self-Scale (ITAS). In study 1 we provide evidence of convergent and discriminant validity within the general population so that a generalization of its applicability is possible. In study 2 we subsequently tested ITAS in the actual target group, the educational sector. The high correlations of the ITAS with the ATI and the control instrument TA-EG (ranging from rs = 0.679 to rs = 0.440) show that ITAS is suitable for use in research. Furthermore, the newly developed instrument convinces with its low complexity, the graphical component, which requires little text understanding and the high time saving. This research thus can contribute to the investigation of technology affinity in the educational sector helping educators to conduct technical activities with their learning group, to predict possible difficulties and adjust their planning accordingly.