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Exploring strategies to improve the reverse beta-oxidation pathway in Saccharomyces cerevisiae
(2024)
Microbes are the most diverse living organisms on Earth, with various metabolic adaptations that allow them to live in different conditions and produce compounds with different chemical complexity. Microbial biotechnology exploits the metabolic diversity of microorganisms to manufacture products for different industries. Today, the chemical industry is a significant energy consumer and carbon dioxide emitter, with processes that harm natural ecosystems, like the extraction of medium-chain fatty acids (MCFAs). MCFAs are used as precursors for biofuels, volatile esters, surfactants, or polymers in materials with enhanced properties.
However, their current extraction process uses large, non-sustainable monocultures of coconut and palm trees. Therefore, the microbial production of MCFAs can help reduce the current environmental impact of obtaining these products and their derivatives.
In nature, fatty acids are mostly produced via fatty acid biosynthesis (FAB). However, the reverse β-oxidation (rBOX) is a more energy-efficient pathway compared to FAB. The rBOX pathway consists of four reactions, which result in the elongation of an acyl-CoA molecule by two carbon units from acetyl-CoA in each cycle. In this work we used Saccharomyces cerevisiae, an organism with a high tolerance towards toxic compounds, as the expression host of the rBOX pathway to produce MCFAs and medium-chain fatty alcohols (MCFOHs).
In the first part of this work, we expanded the length of the products from expressing the rBOX in the cytosol and increased the MCFAs titres. First, we deleted the major glycerol-3-phosphate dehydrogenase (GPD2). This resulted in a platform strain with significantly reduced glycerol fermentation and increased rBOX pathway activity, probably due to an increased availability of NADH. Then, we tested different combinations of rBOX enzymes to increase the length and titres of MCFA. Expressing the thiolase CnbktB and β-hydroxyacyl-CoA dehydrogenase CnpaaH1 from Cupriavidus necator, Cacrt from Clostridium acetobutylicum and the trans-enoyl-CoA reductase Tdter (Treponema denticola) resulted in hexanoic acid as the main product.
Expressing Cncrt2 (C. necator) or YlECH (Y. lipolytica) as enoyl-CoA hydratases resulted in octanoic acid as the main product. Then, we integrated the octanoic (Cncrt2 or YlECH) and the hexanoic acid (Cacrt)-producing variants in the genome of the platform strain and we achieved titers of ≈75 mg/L (hexanoic acid) and ≈ 60 mg/L (octanoic acid) when growing these strains in a complex, highly buffered medium. These are the highest titers of octanoic and hexanoic acid obtained in S. cerevisiae with the rBOX. Additionally, we deleted TES1 and FAA2 to prevent competition for butyryl-CoA and degradation of the produced fatty acids, respectively.
However, these deletions did not improve MCFA titers. In addition, we tested two dual acyl-CoA reductase/alcohol dehydrogenases (ACR/ADH), CaadhE2 from C. acetobutylicum and the putative ACR/ADH EceutE from Escherichia coli, in an octanoyl-CoA-producing strain to produce MCFOH. As a result, we produced 1-hexanol and 1-octanol for the first time in S. cerevisiae with these two enzymes. Nonetheless, the titres were low (<10 mg/L and <2 mg/L, respectively), and four-carbon 1-butanol was the main product in both cases (>80 mg/L). This showed the preference of these two enzymes for butyryl-CoA.
In the second part of this work, we expressed the rBOX in the mitochondria of S. cerevisiae to benefit from the high levels of acetyl-CoA and the reducing environment in that organelle. First, in an adh-deficient strain, we mutated MTH1, a transcription factor regulating the expression of hexose transporters, and deleted GPD2. This resulted in a strain with a reduced Crabtree effect and, therefore, an increased carbon flux to the mitochondria. We partially validated the increased flux to the mitochondria by expressing the ethanol-acetyltransferase EAT1 from Kluyveromyces marxianus in this organelle. This resulted in a higher isoamyl acetate production in the MTH1-mutant strain. Isoamyl acetate is synthesised by Eat1 from acetyl-CoA and isoamyl alcohol, a product of the metabolism of amino acids in the mitochondria. Then, we targeted different butyryl-CoA-producing rBOX variants to the mitochondria, and we used the production of 1-butanol and butyric acid as a proof-of-concept. The strong expression of all the enzymes was toxic for the cell, and the highest butyric acid titres (≈ 50 mg/L) in the mitochondria from the rBOX were obtained from the weak expression of the pathway. The highest 1-butanol titers (≈ 5 mg/L) were obtained with the downregulation of the mitochondrial NADH-oxidase NDI1. However, this downregulation led to a non-desirable petite phenotype.
In summary, we produced hexanoic and octanoic acid for the first time in S. cerevisiae using the rBOX and achieved the highest reported titers of hexanoic and octanoic acid so far using this pathway in S. cerevisiae. In addition, we successfully compartmentalised the rBOX in the mitochondria. However, competing reactions, some of them essential for the viability of the cell, limit the use of this organelle for the rBOX.
Research on the human and animal microbiome has become increasingly important in recent years. It is now widely accepted the gut microbiome is of crucial importance to health, as it is involved in a large number of physiological processes. The term ‘microbiome’ refers to the all living microorganisms including their genes and metabolites in a defined environment, while the specific composition of microorganisms consisting of bacteria, archaea and protozoa is referred to as the ‘microbiota’ (Lane-Petter, 1962; Lederberg and McCray, 2001).
In recent years, research has focused on various of these communities in the soil (Fierer, 2017), water (Sunagawa et al., 2015), air (Leung et al., 2014) and especially in the human gut. However, this topic is also becoming increasingly relevant for the conservation of endangered species. In the face of global mass extinctions and the listing of over 42,000 animal species as ‘critically endangered’, conservation breeding programmes are more important than ever (Díaz et al., 2019; IUCN, 2022). The responsibility for these tasks lies with zoological institutions, which are dedicated to animal conservation and the continuous monitoring of animal welfare. Microbiome research offers a non-invasive method to support species conservation. By analysing faecal samples, microbial markers can be identified that provide important information about the health status and reproductive cycle of animals (Weingrill et al., 2004; Antwis et al., 2019). Zoological facilities also provide an ideal research environment for comparing individuals from different habitats. In addition, all necessary metadata such as age, sex, kinship or medical treatment are documented and can be used for the analysis.
This is the starting point for this thesis. In order to identify such microbial markers, it is necessary to understand the microbiome of a variety of animal species. The first aim is therefore to characterise the faecal microbiota of 31 mammalian species, focusing on herbivores and carnivores. It could be shown that they differ significantly in terms of both microbial diversity and microbiota composition. Herbivorous species express a very diverse microbial composition, consisting mainly of cellulose-degrading taxa of the families Fibrobacteraceae or Spirochaetaceae. In contrast, the microbiota of carnivorous species is less diverse and is dominated by protein-degrading Fusobacteriaceae and Clostridiaceae. In addition, this thesis proves that the microbiota of herbivorous species is highly consistent, whereas the microbiota of carnivorous species is highly variable. The results of this study provide important insights for the sampling scheme of future projects. Especially when analysing carnivorous species, single samples are not sufficient to capture the full variability of the microbiome.
These results lead to the question of whether this variability can be explained by daily fluctuations in the individual microbiome and whether this can be used to distinguish between species or individuals. Using individual longitudinal data and a combined approach of clustering algorithms and dynamic time warping, it is shown that such a distinction is possible at the species and individual level. This was confirmed for both a carnivorous (Panthera tigris) and a herbivorous (Connochaetes taurinus) species. These results confirm the influence of the host individual on the faecal microbiota, in addition to the often described influence of diet (Ley et al., 2008a; Kartzinel et al., 2019).
Based on the knowledge gained from these studies, a methodology has been developed that will enable the conservation of species in the field to be supported by microbiome research in the future. The focus here lays on the identification of host-specific metadata based on the faecal microbiota. The developed regression model is able to distinguish between carnivorous, herbivorous and omnivorous hosts with up to 99% accuracy. In addition, a more accurate phylogenetic classification of the family (Canidae, Felidae, Ursidae, Herpestidae) can be made for carnivorous hosts. For herbivorous hosts, the model can predict the respective digestive system with up to 100% accuracy, distinguishing between ruminants, hindgut fermenters and a simple digestive system. The acquisition of host-specific metadata from an unknown faecal sample is an important step towards establishing microbiome research in species conservation. Field studies in particular will benefit from such new methods. Usually, costly microsatellite analysis and high-quality host DNA are required to obtain host-specific information from faecal samples. The newly developed method offers a less costly and labour-intensive alternative to conventional techniques and opens up a more accessible field for microbiome research in the field.
Trait-dependent effects of biotic and abiotic filters on plant regeneration in Southern Ecuador
(2024)
Tropical forests have always fascinated scientists due to their unique biodiversity. However, our understanding of ecological processes shaping the complexity of tropical rainforests is still relatively poor. Plant regeneration is one of the processes that remain understudied in the tropics although this is a key process defining the structure, diversity and assembly of tropical plant communities. In my dissertation, I combine experimental, observational and trait-based approaches to identify processes shaping the assembly of seedling communities and compare associations between environmental conditions and plant traits across plant life stages. By working along a steep environmental gradient in the tropical mountains of Southern Ecuador, I was able to investigate how processes of plant regeneration vary in response to biotic and abiotic factors in tropical montane forests.
My dissertation comprises three complementary chapters, each addressing an individual research question. First, I studied how trait composition in plant communities varies in relation to the broad- and local-scale environmental conditions and across the plant life cycle. I measured key traits reflecting different ecological strategies of plants that correspond to three stages of the plant life cycle (i.e., adult trees, seed rain and recruiting seedlings). I worked on 81 subplots along an elevational gradient covering a large climatic gradient at three different elevations (1000, 2000 and 3000 m a.s.l.). In addition, I measured soil and light conditions at the local spatial scale within each subplot. My findings show that the trait composition of leaves, seeds and seedlings changed similarly across the elevational gradient, but that the different life stages responded differently to the local gradients in soil nutrients and light availability. Consequently, my findings highlight that trait-environment associations in plant communities differ between large and small spatial scales and across plant life stages.
Second, I investigated how seed size affects seedling recruitment in natural forests and in pastures in relation to abiotic and biotic factors. I set up a seed sowing experiment in both habitat types and sowed over 8,000 seeds belonging to seven tree species differing in seed size. I found that large-seeded species had higher proportions of recruitment in the forests compared to small-seeded species. However, small-seeded species tended to recruit better in pastures compared to large-seeded species. I showed that high surface temperature was the main driver of differences in seedling recruitment between habitats, because it limited seedling recruitment of large-seeded species. The results from this experiment show that pasture restoration requires seed addition of large-seeded species and active protection of recruiting seedlings in order to mitigate harmful conditions associated with high temperatures in deforested areas.
Third, I examined the associations between seedling beta-diversity and different abiotic and biotic factors between and within elevations. I applied beta-diversity partitioning to obtain two components of beta-diversity: species turnover and species richness differences. I associated these components of beta-diversity with biotic pressures by herbivores and fungal pathogens and environmental heterogeneity in light and soil conditions. I found that species turnover in seedling communities was positively associated with the dissimilarity in biotic pressures within elevations and with environmental heterogeneity between elevations. Further, I found that species richness differences increased primarily with increasing environmental heterogeneity within elevations. My findings show that the associations between beta-diversity of seedling communities and abiotic and biotic factors are scale-dependent, most likely due to differences in species sorting in response to biotic pressures and species coexistence in response to environmental heterogeneity.
My dissertation reveals that studying processes of community assembly at different plant life stages and spatial scales can yield new insights into patterns and processes of plant regeneration in tropical forests. I investigated how community assembly processes are governed by abiotic and biotic filtering across and within elevations. I also experimentally explored how the process of seedling recruitment depends on seed size-dependent interactions, and verified how these effects are associated with abiotic and biotic filtering. Identifying such processes is crucial to inform predictive models of environmental change on plant regeneration and successful forest restoration. Further exploration of plant functional traits and their associations with local-scale environmental conditions could effectively support local conservation efforts needed to enhance forest cover in the future and halt the accelerating loss of biodiversity.
Neurodevelopmental psychiatric disorders (NPDs) like attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and schizophrenia, affect millions of people worldwide. Despite recent progress in NPD research, much remains to be discovered about their underpinnings, therapeutic targets, effects of biological sex and age. Risk factors influencing brain development and signalling include prenatal inflammation and genetic variation. This dissertation aimed to build upon these findings by combining behavioural, molecular, and neuromorphological investigations in mouse models of such risk factors, i.e. maternal immune activation (MIA), neuron-specific overexpression (OE) of the cytoplasmatic isoforms of the RNA-binding protein RBFOX1, and neuronal deletion of the small Ras GTPase DIRAS2.
Maternal infections during pregnancy pose an increased risk for NPDs in the offspring. While viral-like MIA has been previously established elsewhere, this study was the first in our institution to implement the model. I validated NPD-relevant deficits in anxiety- and depression-like behaviours, as well as dose- and sex-specific social deficits in mouse offspring following MIA in early gestation. Proteomic analyses in embryonic and adult hippocampal (HPC) synaptoneurosomes highlighted novel and known targets affected by MIA. Analysis of the embryonic dataset implicated neurodevelopmental disruptions of the lipid, polysaccharide, and glycoprotein metabolism, important for proper membrane function, signalling, and myelination, for NPD-pertinent sequelae. In adulthood, the observed changes encompassed transmembrane trafficking and intracellular signalling, apoptosis, and cytoskeletal organisation pathways. Importantly, 50 proteins altered by MIA in embryonic and adult HPC were enriched in the NPD-relevant synaptic vesicle cycle. A persistently upregulated protein cluster formed a functional network involved in presynaptic signalling and proteins downregulated in embryos but upregulated in adults by MIA were correlated with observed social deficits. 49/50 genes encoding these proteins were significantly associated with NPD- and comorbidity-relevant traits in human phenome-wise association study data for psychiatric phenotypes. These findings highlight NPD-relevant targets for future study and early intervention in at-risk individuals. MIA-evoked changes in the neuroarchitecture of the NPD-relevant HPC and prefrontal cortex (PFC) of male and female mice highlighted sex- and region-specific alterations in dendritic and spine morphology, possibly underlining behavioural phenotypes.
To further investigate genetic risk factors of NPDs, I performed a study based on the implications of RBFOX1’s pleiotropic role in neuropsychiatric disorders and previous preclinical findings. Cytoplasmatic OE of RBFOX1, which affects the stability and translation of thousands of targets, was used to disseminate its role in morphology and behaviour. RBFOX1 OE affected dendritic length and branching in the male PFC and led to spine alterations in both PFC and HPC. Due to previously observed ASD-like endophenotypes in our Rbfox1 KO mice and the importance of gene × environment effects on NPD susceptibility, I probed the interaction of cytoplasmatic OE and a low-dose MIA on offspring. Both RBFOX1 OE alone and with MIA led to increased offspring loss during the perinatal period. Preliminary data suggested that RBFOX1 OE × MIA might increase anxiety- and anhedonia-like behaviours. Morphological changes in the adult male OE HPC and PFC suggested increased spine density and reduced dendritic complexity. A small post-mortem study in human dorsolateral PFC of older adults did not reveal significant effects of a common risk variant on RBFOX1 abundance.
To expand upon NPD genetic risks, I evaluated the effects of a homo- (KO) or heterozygous (HET) Diras2 deletion in a novel, neuron-specific mouse model. DIRAS2’s function is largely unknown, but it has been associated with ADHD in humans and neurodevelopment in vitro. In adult mice, there were subtle sex-specific effects on behaviour, i.e. more pronounced NPD-relevant deficits in males, in keeping with human data. KO mice had subtly improved cognitive performance, while HET mice exhibited behaviours in line with core ADHD symptoms, e.g. earning difficulties (females), response inhibition deficits and hyperactivity (males), suggesting Diras2 dose-sensitivity and sex-specificity. The morphological findings revealed multiple aberrations in dendritic and spine morphology in the adult PFC, HPC, and amygdala of HET males. KOs changes in spine and dendritic morphology were exclusively in the PFC and largely opposite to those in HETs and NPD-like phenotypes. Region- and genotype-specific expression changes in Diras2 and Diras1 were observed in six relevant brain regions of adult HET and KO females, also revealing differences in the survival and morphology regulator mTOR, which might underlie observed differences.
In conclusion, the effects of MIA and partial Diras2 knockdown resembled each other in core, NPD-associated behavioural and morphological phenotypes, while cytoplasmatic RBFOX1 OE and full Diras2 KO differed from those. My findings suggest complex dose- and sex-dependent relationships between these prenatal and genetic interventions, whose NPD-relevant influences might converge onto neurodevelopmental molecular pathways. An assessment of such putative overlap, based on available data from the MIA proteomic analyses of embryonic and adult HPC, suggested the three models might be linked via downstream targets, interactions, and upstream regulators. Future studies should disseminate both distinct and shared aspects of MIA, RBFOX1, and DIRAS2 relevant to NPDs and build upon these findings.
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.
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.
Precise regulation of gene expression networks is required to develop and maintain a healthy organism before and after birth and throughout adulthood. Such networks are mostly comprised of regulatory proteins, but meanwhile many long non-coding transcripts (lncRNAs) are shown to participate in these regulatory processes. The functions and mechanisms of these lncRNAs vary greatly, however they are often associated with transcriptional regulation. Three lncRNAs, namely Sweetheart RNA (Swhtr), Fetal-lethal noncoding developmental regulatory RNA / Foxf1 adjacent non-Coding developmental regulatory RNA (Fendrr) and lncFsd2, were studied in this work to demonstrate the variety of cellular and biological processes that require lncRNA-mediated fine-tuning, in regard to the cardiopulmonary system.
Swhtr was found to be expressed exclusively in cardiomyocytes and became critical for regeneration after myocardial injury. Mice lacking Swhtr did not show issues under normal conditions, but failed to undergo compensatory hypertrophic remodeling after injury, leading to increased mortality. This effect was rescued by re-expressing Swhtr, demonstrating importance of the RNA. Genes dependent on Swhtr during cardiac stress were found to likely be regulated by NKX2-5 through physical interaction with Swhtr. Fendrr was found to be expressed in lung and interacted with target promoters through its RNA:dsDNA binding domain, the FendrrBox, which was partially required for Fendrr function. Fendrr, together with activated WNT signaling, regulated fibrosis related target genes via the FendrrBox in fibroblasts. LncFsd2, an ubiquitously expressed lncRNA, showed possible interaction with the striated muscle specific Fsd2, but its exact function and regulatory role remain unclear in muscle physiology. Immunoprecipitation and subcellular fractionation experiments suggest that lncFsd2 might be involved in nuclear retention of Fsd2 mRNA, thus fine-tuning FSD2 protein expression. These investigations have shed light on the roles of these lncRNAs in stress responses, fibrosis-related gene regulation, and localization processes, advancing our understanding of cardiovascular and pulmonary maintenance, reaction to injury, and diseases. The diverse and intricate roles of these three lncRNAs highlight how they influence various cellular processes and disease states, offering avenues for exploring lncRNA functions in different biological contexts.
The attention on the protein PURA has increased recently following the discovery of the rare PURA Syndrome. This neurodevelopmental disorder is caused by de novo mutations in the PURA gene. Notably, our collaborators could show that the protein PURA can bind DNA and RNA in vitro. As a result, I was motivated to explore PURA's cellular RNAbinding activity. Furthermore, I inquired on the connection of PURA-RNA binding to the cellular effect of a reduction of functional PURA as present in PURA Syndrome patients.
To investigate the binding of PURA and the impact of PURA de ciency on cellular RNA and protein expression, I performed an integrative computational analysis of multimodal data from complementary high-throughput experiments. An essential component was the examination of UV Crosslinking and immunoprecipitation (CLIP) experiments, which can query the global RNA-binding behaviour of a given protein in a cellular context. As the processing and analysis of CLIP data are rather complex, I introduce an automated command line tool for the processing of CLIP data named racoon_clip as part of this dissertation. Therefore, this dissertation comprises two major segments. Firstly, I describe the implementation and usage of racoon clip for CLIP data analysis. Secondly, I discuss my research on the protein PURA, demonstrating its global RNA-binding properties, the effects of PURA depletion and its association with neuronal functions and P-bodies, among others.
racoon_clip is a command line application that I have developed for processing of individualnucleotide resolution CLIP (iCLIP) and enhanced CLIP (eCLIP) experiments - two of the most commonly used types of CLIP experiments - in a comparable and user-friendly way.
For this, I built racoon_clip as an automated work how that encompasses all CLIP processing steps from raw data to single-nucleotide resolution crosslink events. racoon_clip is available as a command line tool that users can run with a single command. The work how is implemented with Snakemake work how management providing computational advantage tages including parallelisation, scalability and portability of the work how. The main task of racoon_clip is to extract single-nucleotide crosslink events from iCLIP, iCLIP2, eCLIP and similar data types. To strike a balance between being highly customisable and easy to use, racoon_clip supplies pre-set options for the most common types of experiments.
Additionally, it is possible for users to create a custom setup of barcode and adapter architectures, which allows them to use the software for other types of CLIP data. While accounting for the different architectures in the reads, the performed central processing steps remain the same. This leads to a high degree of comparability between the different experiment types, which I demonstrate in the exemplary processing of U2AF2 iCLIP and eCLIP data. Taken together, I am confident that racoon_clip will be beneficial to numerous researchers interested in RNA-Protein interactions as it offers easily accessible processing for CLIP data and enhances the comparability of multiple CLIP datasets across di erent experiment types.
In the second part of this dissertation, I focus on the cellular function of the RNAbinding protein PURA. Through in-depth computational analysis of one iCLIP data set of endogenous PURA and two iCLIP data sets of overexpressed PURA in HeLa cells, I establish that PURA is a global RNA-binding protein. It preferentially binds RNAs in either the coding sequence (CDS) or the 3' untranslated region (3'UTR) of mature protein-coding transcripts by recognising a Purine-rich degenerated sequence motif. Even though overexpression of PURA results in less specific binding behaviour, the same overall binding patterns as from endogenous PURA persist. Overall characteristics of PURA binding remain similar in three distinct PURA iCLIP data sets with and without PURA overexpression.
To learn about the molecular consequences of a depletion of functional PURA in a cellular context, I used a 50% reduction of PURA in HeLa cells as a model for the heterozygous loss of PURA in PURA Syndrome and evaluated its impact on global RNA and protein expression. The results demonstrate that PURA depletion globally a ects RNA and protein expression. Additionally, I integrate PURA RNA binding with the changes in expression of RNAs and proteins in the context of PURA depletion. This reveals 234 targets of PURA that are bound by PURA and are impacted at both RNA and protein levels by the PURA protein. RNAs that are bound by PURA or change in abundance upon PURA depletion are enriched in neuronal development factors, RNA lifecycle regulators, and mitochondrial factors, among others. Consistent with a possible role of PURA in neuronal transport, there is considerable overlap between PURA bound transcripts and transcripts, that are transported to the dendritic end of neurons.
Notably, there is a link between PURA and P-bodies, as documented by the enrichment of PURA-bound RNAs in both the P-body and stress granule transcriptome. Further, PURA was found by our collaborators to be localised within P-bodies and P-body numbers were strongly reduced in cells that are depleted of PURA. This absence might be attributed to the downregulation of the proteins encoded by the PURA targets LSM14A and DDX6 as both of them were previously identified as essential for P-body formation.
Overall, the reduction of P-body numbers in PURA depletion, the neuronal function of PURA, and its association with mitochondria and RNA lifecycle regulation may indicate the cellular foundation of both PURA Syndrome and related neuronal diseases.
In summary, I present a versatile and user-friendly computational tool for the analysis of CLIP data. Subsequently, I conduct a thorough computational analysis of CLIP and other high-throughput data in the context of the RNA-binding protein PURA, which offers valuable insights into the cellular functions of PURA. These insights advance our understanding of the impact of PURA loss in PURA Syndrome and other disease contexts.
Anthropogenic activities have a major impact on our planet and rapidly drive biodiversity loss in ecosystems at a global scale. Particularly over the last century, rising CO2 emissions significantly raised global temperatures and increased the intensity and frequency of droughts and heatwaves. Additionally, agricultural land use and fossil fuel combustion contribute to the continuous release of nitrogen (N) and phosphorus (P) into ecosystems worldwide through extensive fertilization and deposition from the atmosphere. It is important to understand how these rapid changes affect the evolution of plant populations and their adaptive potential. Adaptation by natural selection (i.e., adaptive evolution) within a few generations is an essential process as a response to rapid environmental changes. Rapid evolution of plant populations can be detected by using the so-called resurrection approach. Here, diaspores (i.e., seeds) from a population are collected before (ancestors) and after (descendants) a potential selection pressure (e.g., consecutive years of drought or changes in nutrient supply). Comparing phenotypes of ancestors and descendants in a common environment such as an outside garden, greenhouse, or climate chamber, may then reveal evolutionary changes. Ideally, plants are first grown in a common environment for an intermediate refresher generation to reduce parental and storage effects.
The aim of this thesis was to investigate the occurrence of adaptive evolution in natural plant populations in response to rapidly changing environments over the past three decades. I conducted three experiments using the resurrection approach to generate comprehensive data on the adaptive processes that acted on three plant populations from three different species over the last three decades. Furthermore, I filled knowledge gaps in plant evolutionary ecology and conceptually developed the resurrection approach further.
In Chapter I, I performed a novel approach by testing for adaptive evolution in natural plant populations using the resurrection approach in combination with in-situ transplantations. I cultivated seedlings from ancestors (23 – 26 years old) and contemporary descendants of three perennial species (Melica ciliata, Leontodon hispidus and Clinopodium vulgare) from calcareous grasslands in the greenhouse and In Chapter III, I assessed the reproducibility of phenotypic differences between genotypes among three different growth facilities (climate chamber, greenhouse, and outdoor garden). I also evaluated differences in phenotypic expression between plants grown after one vs. two intermediate generations (i.e., refresher generations). I performed this experiment within the framework of the resurrection approach and compared ancestors and descendants of the same population of Leontodon hispidus.
I observed very strong differences among plants growing in the different growth facilities. I found a significant interaction between the growth facility and the temporal origin (ancestors vs. descendants): descendants had significantly larger rosettes than ancestors only in the greenhouse and they flowered significantly later than ancestors exclusively in the climate chamber. I did not find significant differences between intermediate generations within the growth facilities. Overall, Chapter III shows that the use of a particular experimental system can dictate the presence and magnitude of phenotypic differences. This implies that absence of evidence is not evidence of absence when it comes to investigating genetically based trait differentiation among plant origins (in space or time). Experimental systems should be carefully designed to provide meaningful conditions, ideally mimicking the environmental conditions of the population’s origins. Finally, growing a second intermediate generation did not impact the genetic differences of ancestors and descendants within the environments, supporting the idea that only one intermediate generation may be sufficient to reduce detectable parental and storage effects.
The resurrection approach allows a better understanding of rapid plant adaptation, but some limitations deserve to be highlighted. I only studied one population per species, and Chapters II and III only focus on one population of L. hispidus, which is also hampering generalizations, as adaptive potential can vary greatly among populations of the same species. I only compared the ancestral genotypes to one descendant sample with a long time span in between (26 – 28 years), which makes it hard to pinpoint the selection agents that caused the genetic differentiation among the sampling years. Hence, closely monitoring biotic and abiotic factors of the studied populations between the ancestral and descendant sampling in future studies, would make identifying the responsible selection pressures more precise. I also recommend sampling multiple populations over consecutive years to improve the robustness of results and make generalizations more approachable.Furthermore, combining the resurrection approach with other methods such as in-situ transplantations will be valuable to offset the limitation that adaptations cannot be proven under artificial conditions (e.g., in the greenhouse).