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Background: In addition to controlled post-translational modifications proteins can be modified with highly reactive compounds. Usually this leads to a compromised functionality of the protein. Methylglyoxal is one of the most common agents that attack arginine residues. Methylglyoxal is also regarded as a pro-oxidant that affects cellular redox homeostasis by contributing to the formation of reactive oxygen species. Antioxidant enzymes like catalase are required to protect the cell from oxidative damage. These enzymes are also targets for methylglyoxal-mediated modification which could severely affect their catalytic activity in breaking down reactive oxygen species to less reactive or inert compounds.
Results: Here, bovine liver catalase was incubated with high levels of methylglyoxal to induce its glycation. This treatment did not lead to a pronounced reduction of enzymatic activity. Subsequently methylglyoxal-mediated arginine modifications (hydroimidazolone and dihydroxyimidazolidine) were quantitatively analysed by sensitive nano high performance liquid chromatography/electron spray ionisation/tandem mass spectrometry. Whereas several arginine residues displayed low to moderate levels of glycation (e.g., Arg93, Arg365, Arg444) Arg354 in the active centre of catalase was never found to be modified.
Conclusions: Bovine liver catalase is able to tolerate very high levels of the modifying α-oxoaldehyde methylglyoxal so that its essential enzymatic function is not impaired.
Electronic supplementary material: The online version of this article (doi:10.1186/s13104-015-1793-5) contains supplementary material, which is available to authorized users.
Abstract: Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they linked their receptive fields to the statistics of visual stimuli. However, a salient feature of image statistics, occlusions of image components, is not considered by these models. Here we ask if occlusions have an effect on the predicted shapes of simple cell receptive fields. We use a comparative approach to answer this question and investigate two models for simple cells: a standard linear model and an occlusive model. For both models we simultaneously estimate optimal receptive fields, sparsity and stimulus noise. The two models are identical except for their component superposition assumption. We find the image encoding and receptive fields predicted by the models to differ significantly. While both models predict many Gabor-like fields, the occlusive model predicts a much sparser encoding and high percentages of ‘globular’ receptive fields. This relatively new center-surround type of simple cell response is observed since reverse correlation is used in experimental studies. While high percentages of ‘globular’ fields can be obtained using specific choices of sparsity and overcompleteness in linear sparse coding, no or only low proportions are reported in the vast majority of studies on linear models (including all ICA models). Likewise, for the here investigated linear model and optimal sparsity, only low proportions of ‘globular’ fields are observed. In comparison, the occlusive model robustly infers high proportions and can match the experimentally observed high proportions of ‘globular’ fields well. Our computational study, therefore, suggests that ‘globular’ fields may be evidence for an optimal encoding of visual occlusions in primary visual cortex.
Author Summary: The statistics of our visual world is dominated by occlusions. Almost every image processed by our brain consists of mutually occluding objects, animals and plants. Our visual cortex is optimized through evolution and throughout our lifespan for such stimuli. Yet, the standard computational models of primary visual processing do not consider occlusions. In this study, we ask what effects visual occlusions may have on predicted response properties of simple cells which are the first cortical processing units for images. Our results suggest that recently observed differences between experiments and predictions of the standard simple cell models can be attributed to occlusions. The most significant consequence of occlusions is the prediction of many cells sensitive to center-surround stimuli. Experimentally, large quantities of such cells are observed since new techniques (reverse correlation) are used. Without occlusions, they are only obtained for specific settings and none of the seminal studies (sparse coding, ICA) predicted such fields. In contrast, the new type of response naturally emerges as soon as occlusions are considered. In comparison with recent in vivo experiments we find that occlusive models are consistent with the high percentages of center-surround simple cells observed in macaque monkeys, ferrets and mice.
Many studies about endocrine pollution in the aquatic environment reveal changes in the reproduction system of biota. We analysed endocrine activities in two rivers in Southern Germany using three approaches: (1) chemical analyses, (2) in vitro bioassays, and (3) in vivo investigations in fish and snails. Chemical analyses were based on gas chromatography coupled with mass spectrometry. For in vitro analyses of endocrine potentials in water, sediment, and waste water samples, we used the E-screen assay (human breast cancer cells MCF-7) and reporter gene assays (human cell line HeLa-9903 and MDA-kb2). In addition, we performed reproduction tests with the freshwater mudsnail Potamopyrgus antipodarum to analyse water and sediment samples. We exposed juvenile brown trout (Salmo trutta f. fario) to water downstream of a wastewater outfall (Schussen River) or to water from a reference site (Argen River) to investigate the vitellogenin production. Furthermore, two feral fish species, chub (Leuciscus cephalus) and spirlin (Alburnoides bipunctatus), were caught in both rivers to determine their gonadal maturity and the gonadosomatic index. Chemical analyses provided only little information about endocrine active substances, whereas the in vitro assays revealed endocrine potentials in most of the samples. In addition to endocrine potentials, we also observed toxic potentials (E-screen/reproduction test) in waste water samples, which could interfere with and camouflage endocrine effects. The results of our in vivo tests were mostly in line with the results of the in vitro assays and revealed a consistent reproduction-disrupting (reproduction tests) and an occasional endocrine action (vitellogenin levels) in both investigated rivers, with more pronounced effects for the Schussen river (e.g. a lower gonadosomatic index). We were able to show that biological in vitro assays for endocrine potentials in natural stream water reasonably reflect reproduction and endocrine disruption observed in snails and field-exposed fish, respectively.
Cockchafers of the genus Melolontha (Coleoptera: Scarabaeidae) can be severe pests in forestry, agriculture and horticulture. Gradation of the two most important species, the forest cockchafer M. hippocastani FABR. and the European cockchafer M. melolontha L., occurs currently in several parts of central Europe. Orientation behaviour of the adult beetles has been the focus of recent studies (REINECKE et al. 2002 a, b, 2005). However, especially the larvae are dreaded because their belowground damage is not visible directly after feeding. There are a lot of speculations about belowground living insects and their way of living, but until now there were not that many experimental investigations. A rather unknown topic is the orientation behaviour of soil living organisms, which is also subject of some publications (HORBER 1954, HAUSS & SCHÜTTE 1976, HASLER 1986, HIBBARD et al. 1994, JEWETT & BJOSTAD 1996, BERNKLAU & BJOSTAD 1998A, BERNKLAU & BJOSTAD 1998B, BERNKLAU et al. 2005).
We demonstrated previously that 5-lipoxygenase (5-LO), a key enzyme in leukotriene biosynthesis, can be phosphorylated by p38 MAPK-regulated MAPKAP kinases (MKs). Here we show that mutation of Ser-271 to Ala in 5-LO abolished MK2 catalyzed phosphorylation and clearly reduced phosphorylation by kinases prepared from stimulated polymorphonuclear leukocytes and Mono Mac 6 cells. Compared with heat shock protein 27 (Hsp-27), 5-LO was a weak substrate for MK2. However, the addition of unsaturated fatty acids (i.e. arachidonate 1-50 microm) up-regulated phosphorylation of 5-LO, but not of Hsp-27, by active MK2 in vitro, resulting in a similar phosphorylation as for Hsp-27. 5-LO was phosphorylated also by other serine/threonine kinases recognizing the motif Arg-Xaa-Xaa-Ser (protein kinase A, Ca(2+)/calmodulin-dependent kinase II), but these activities were not increased by fatty acids. HeLa cells expressing wild type 5-LO or S271A-5-LO, showed prominent 5-LO activity when incubated with Ca(2+)-ionophore plus arachidonate. However, when stimulated with only exogenous arachidonic acid, activity for the S271A mutant was significantly lower as compared with wild type 5-LO. It appears that phosphorylation at Ser-271 is more important for 5-LO activity induced by a stimulus that does not prominently increase intracellular Ca(2+) and that arachidonic acid stimulates leukotriene biosynthesis also by promoting this MK2-catalyzed phosphorylation.
Mining is one of the major pollution sources worldwide, causing huge disturbances to the environment. Industrial and artisanal mining activities are widespread in Mexico, a major global producer of various metals. This study aimed to assess the ecological impairments resulting from mining activities using aquatic macroinvertebrates assemblages (MA). A multiple co-inertia analysis was applied to determine the relationships between environmental factors, habitat quality, heavy metals, and aquatic macroinvertebrates in 15 study sites in two different seasons (dry and wet) along two rivers running across the Central Plateau of Mexico. The results revealed three contrasting environmental conditions associated with different MAs. High concentrations of heavy metals, nutrients, and salinity limit the presence of several families of seemingly sensitive macroinvertebrates. These factors were found to influence structural changes in MAs, showing that not only mining activities, but also agriculture and presence of villages in the basin, exert adverse effects on macroinvertebrate assemblages. Diversity indices showed that the lowest diversity matched both the most polluted and the most saline rivers. The rivers studied displayed high alkalinity and hardness levels, which can reduce the availability of metals and cause adverse effects on periphyton by inhibiting photosynthesis and damaging MAs. Aquatic biomonitoring in rivers, impacted by mining and other human activities, is critical for detecting the effect of metals and other pollutants to improve management and conservation strategies. This study supports the design of cost-effective and accurate water quality biomonitoring protocols in developing countries.
Ischemic injuries of the cardiovascular system are still the leading cause of death worldwide. They are often accompanied by loss of cardiomyocytes (CM) and their replacement by non-functional heart tissue. Cardiac fibroblasts (CF) play a major role in the recovery after ischemic injury and in the scar formation. In the last few years researchers were able to reprogram fibroblasts into CM in vitro and in murine models of myocardial infarction using various protocols including a cocktail of microRNAs (miRs). These miRs can target hundreds of messenger RNAs and inhibit their translation into proteins, potentially regulating multiple cellular signaling pathways. Because of this, there has been a rising interest in the use of miRs for therapeutic purposes. However, as different miRs have different effects in different cells, there is the danger of causing serious side effects. These could be alleviated by enacting a cell-specific transport of miRs, for example by using aptamers. Aptamers are usually short strands of DNA or RNA, which can fold into a specific three-dimensional confirmation which allows them to bind specifically to target molecules. Aptamers are commonly selected from a large library for their ability to bind to target molecules using a procedure called SELEX. Aptamers have already been used to transport miRs into cancer cells.
In this thesis, we first established the transport of miRs into cells of the cardiovascular system using aptamers. MiR-126 is an important part of the signaling in endothelial cells (EC), protects from atherosclerosis and supports angiogenesis, which is why we chose it as a candidate to transport into the vasculature. We first tested two aptamers for their ability to internalize into EC and fibroblasts. Both the aptamer for the ubiquitously expressed transferrin receptor (TRA) and a general internalizing RNA motif, but not a control construct, could internalize efficiently into all cell types tested. We then designed three chimeras (Ch) using different strategies to connect TRA to miR-126. While all chimeras could internalize efficiently, only Ch3, which connects TRA to Pre-miR-126 using a sticky bridge structure, had functional effects in EC. Ch3 reduced the protein expression of VCAM-1 in EC and increased the VEGF induced sprouting of EC in a spheroid-sprouting assay. Treatment of breast cancer cells with Ch3 emulated the effects of treatment with classical miR-126-3p and miR-126-5p mimics. In the SK-BR3 cell line Ch3 and miR-126-3p reduce the viability of the cells while they reduce recruitment of EC by the MCF7 cell line. miR-126-5p had no apparent effect in the SK-BR3 line, but increased viability of MCF7 cells, as did Ch3. This implies that Ch3 can be processed to both functional miR-126-3p and miR-126-5p in treated cells.
We were unable to achieve a reprogramming of adult murine cardiac fibroblasts into cells resembling CM using the cocktail of 4 miRs. This indicates that the miR-mediated transdifferentiation is only possible in neonatal fibroblasts. The effects in mice after an AMI might possibly be caused by an enhanced plasticity of fibroblasts in and close to the infarcted area.
We also screened to find aptamers specifically binding to cells of the cardiovascular system. We used two oligonucleotide libraries in a cell-SELEX to select candidates which bind to CF, but not EC. We observed that only the library which contains two randomized regions of 26 bases showed an enrichment of species binding to fibroblasts. We then sequenced rounds 5-7 of the SELEX and analyzed the data bioinfomatically to select 10 candidate aptamers. All candidates showed a strong binding not only to CF, but also EC. This indicates that the selection pressure against species binding to EC was not high enough and would have to be increased to find true CF-aptamers. Four promising candidates were also analyzed for their potential to be internalized and we surprisingly found that all of them were internalized by EC and CF more efficiently than TRA. The similar behavior of the candidates implies that they possibly share a ligand, which is expressed both by EC and CF, but more prominently by the latter.
This work demonstrates the possibility of using aptamers to transport miRs into cells of the cardiovascular system. It also shows that it is possible to select aptamers for non-cancerous mammalian cells, which has not been done before. It is reasonable to assume that a refinement of the cell-SELEX will allow selection of cell-specific aptamers. Due to the failure of reprogramming of adult fibroblasts into induced cardiomyocytes we were unable to test whether a miR-mediated reprogramming might be inducible using aptamer transported-miRs. Ultimately, aptamer mediated transport of miRs is a feasible and promising therapeutic option for the treatment of cardiovascular diseases and other disorders like cancer.
The amyloid precursor protein (APP) was discovered in the 1980s as the precursor protein of the amyloid A4 peptide. The amyloid A4 peptide, also known as A-beta (Aβ), is the main constituent of senile plaques implicated in Alzheimer’s disease (AD). In association with the amyloid deposits, increasing impairments in learning and memory as well as the degeneration of neurons especially in the hippocampus formation are hallmarks of the pathogenesis of AD. Within the last decades much effort has been expended into understanding the pathogenesis of AD. However, little is known about the physiological role of APP within the central nervous system (CNS). Allocating APP to the proteome of the highly dynamic presynaptic active zone (PAZ) identified APP as a novel player within this neuronal communication and signaling network. The analysis of the hippocampal PAZ proteome derived from APP-mutant mice demonstrates that APP is tightly embedded in the underlying protein network. Strikingly, APP deletion accounts for major dysregulation within the PAZ proteome network. Ca2+-homeostasis, neurotransmitter release and mitochondrial function are affected and resemble the outcome during the pathogenesis of AD. The observed changes in protein abundance that occur in the absence of APP as well as in AD suggest that APP is a structural and functional regulator within the hippocampal PAZ proteome. Within this review article, we intend to introduce APP as an important player within the hippocampal PAZ proteome and to outline the impact of APP deletion on individual PAZ proteome subcommunities.
In the deep-sea, the interaction between benthic fauna and substrate mainly occurs through bioturbational processes which can be preserved as traces (i.e., lebensspuren). Lebensspuren are common features of deep seafloor landscapes and usually more abundant than the organism that produce them (i.e., tracemakers), rendering them promising proxies to infer biodiversity. The density and diversity relationships between lebensspuren and benthic fauna are to the present day unclear and contradicting hypotheses have been proposed suggesting negative, positive, or even null correlations. To test these hypotheses, in this study lebensspuren, tracemakers (specific epibenthic fauna that produce these traces), degrading fauna (benthic fauna that can erase lebensspuren), and fauna in general were characterized taxonomically at eight deep-sea stations in the Kuril Kamchatka Trench area. No general correlation (over-all study area) could be observed between diversities of lebensspuren, tracemakers, degrading fauna and fauna. However, a diversity correlation was observed between specific stations, showing both negative and positive correlations depending on: 1) the number of unknown tracemakers (especially significant for dwelling lebensspuren); and 2) the lebensspuren with multiple origins; and 3) tracemakers that can produce different lebensspuren. Lebensspuren and faunal density were not correlated. However, lebensspuren density was either positively or negatively correlated with tracemaker densities, depending on the lebensspuren morphotypes. A positive correlation was observed for resting lebensspuren (e.g., ophiuroid impressions, Actinaria circular impressions), while negative correlations were observed for locomotion-feeding lebensspuren (e.g., echinoid trails). In conclusion, lebensspuren diversity may be a good proxy for tracemaker biodiversity when the lebensspuren-tracemaker tandem can be reliable characterized; and lebensspuren-density correlations vary depending the specific lebensspuren residence time, tracemaker density and associated behaviour (rate of movement), but on a global scale abiotic and other biotic 42 factors may also play an important role.
Research in cell and developmental biology requires the application of three-dimensional model systems that reproduce the natural environment of cells. Processes in developmental biology are therefore studied in entire systems like insects or plants. In cell biology, three-dimensional cell cultures (e.g. spheroids or organoids) model the physiology and pathology of cells, tissues or organs. In all systems, the cellular neighborhood and interactions, but also physicochemical influences, are realistically presented. The production and handling of these model systems is rather simple and allows for reproducible characterization.
Confocal and light sheet-based fluorescence microscopy (LSFM) enable the observation of these systems while maintaining their three-dimensional integrity. LSFM is applicable to imaging live samples at high spatio-temporal resolution over long periods of time. The quality of the acquired datasets enables the extraction of quantitative features about morphology, functionality and dynamics in the context of the complete system. This approach is referred to as image-based systems biology. Exploiting the potential of the generated datasets requires an image analysis pipeline for data management, visualization and the retrieval of biologically meaningful values.
The goal of this thesis was to identify, develop and optimize modules of the image analysis pipeline. The modules cover data management and reduction, visualization, reconstruction of multiview image datasets, the segmentation and tracking of cell nuclei and the extraction of quantitative features. The modules were developed in an application-driven manner to test and ensure their applicability to real datasets from three-dimensional fluorescence microscopy. The underlying datasets were taken from research projects in developmental biology in insects and plants, as well as from cell biology.
The datasets acquired in fluorescence microscopy are typically complex and require common image processing steps in order to manage, visualize, and analyze the datasets. The first module accomplishes automatic structuring of large image datasets, reduces the data amount by image cropping and compression and computes maximum projection images along different spatial directions. The second module corrects for intensity variations in the generated maximum projection images that occur as a function of time. The program was published as a part of an article in Nature Protocols. Another developed module named BugCube provides a web-based platform to visualize and share the processed image datasets.
In LSFM, samples can be rotated in-between two acquisitions enabling the generation of multiview image datasets. Prior to my work, Frederic Strobl and Alexander Ross acquired the complete embryogenesis of the red flour beetle, Tribolium castaneum, and the field cricket, Gryllus bimaculatus, with LSFM. I evaluated a plugin for the software FIJI as a module for the reconstruction of such datasets. The plugin was optimized for automation and efficiency. We obtained the first high quality three-dimensional reconstructions of Tribolium and Gryllus datasets.
Optical clearing increases the penetration depth into samples, thus providing endpoint images of entire three-dimensional objects with cellular detail. This work contributes a quantitative characterization module that was applied to endpoint images of optically cleared spheroids. A program for the generation of ground truth datasets was developed in order to evaluate the cell nuclei segmentation performance. The program was part of a paper that was published in BMC Bioinformatics. Using the program, I could show that the cell nuclei segmentation is robust and accurate. Approaches from computational topology and graph theory complete the segmentation of cell nuclei. Thus, the developed module provides a comprehensive quantitative characterization of spheroids on the level of the individual cell, the cell neighborhood and the whole cell aggregate. The module was employed in four applications to analyze the influence of different stress conditions on the morphology and cellular arrangement of cells in spheroids. The module was accepted for publication in Scientific Reports along with the results for one application. The cell nuclei segmentation further provided a data source for simulation models that used correlation functions to identify structural zones in spheroids. These results were published in Royal Society Interface.
The final part of this work presents a module for cell tracking and lineage reconstruction. In collaboration with Dr. Alexis Maizel, Dr. Jens Fangerau and Dr. Daniel von Wangenheim, I developed a module to track the positions of all cells involved in lateral root formation in Arabidopsis thaliana and used the extracted positions for extensive data analysis. We reconstructed the cell lineages and established the first atlas of all founder cells that contribute to the formation. The analysis of the retrieved data allowed us to study conserved and individual patterns in lateral root formation. The atlas and parts of the analysis presented in this thesis were published in Current Biology.
In this thesis, I developed modules for an image analysis pipeline in three-dimensional fluorescence microscopy and applied them in interdisciplinary research projects. The modules enabled the organization, processing, visualization and analysis of the datasets. The perspective of the image analysis pipeline is not restricted to image-based systems biology. With ongoing development of the image analysis pipeline, it can also be a valuable tool for medical diagnostics or industrial high-throughput approaches.
The DNA damage response (DDR) is a vast network of molecules that preserves genome integrity and allow the faithful transmission of genetic information in human cells. While the usual response to the detection of DNA lesions in cells involves the control of cell-cycle checkpoints, repair proteins or apoptosis, alterations of the repair processes can lead to cellular dysfunction, diseases, or cancer. Besides, cancer patients with DDR alterations often show poor survival and chemoresistance. Despite the progress made in recent years in identifying genes and proteins involved in DDR and their roles in cellular physiology and pathology, the question of the involvement of DDR in metabolism remains unclear. It remains to study the metabolites associated with specific repair pathways or alterations and to investigate whether differences exist depending on cellular origin. The identification of DDR-related metabolic pathways and of the pathways that cause metabolic reprogramming in DDR-deficient cells may produce new targets for the development of new therapies.
In this thesis, nuclear magnetic resonance spectroscopy (NMR) was used to assess the metabolic consequence of the loss of two central DNA repair proteins with importance in diseases context, ATM and RNase H2, in haematological cells. An increase in intracellular taurine was found in RNase H2- and ATM-deficient cells compared to wild-type cells for these genes and in cells after exposition to a source of DNA damage. The rise in taurine does not appear to result from an increase in its biosynthesis from cysteine, but more likely from other cellular processes such as degradation pathways.
Overall, evidence for metabolic reprogramming in haematological cells with faults in DNA repair resulting from ATM or RNase H2 deficiencies or upon exposition to a source of DNA damage is presented in this study.
White stork (Ciconia ciconia) nestlings can provide quantitative information on the quality of the surrounding environment by indicating the presence of pollutants, as they depend on locally foraged food. This study represents the first comparison of biomarkers in two fractions of white stork nestling blood: plasma and S9 (the post-mitochondrial fraction). The aim of this study was to evaluate acetylcholinesterase (AChE), carboxylesterase (CES), glutathione S-transferase (GST), and glutathione reductase (GR), as well as to establish a novel fluorescence-based method for glutathione (GSH) and reactive oxygen species (ROS) detection in plasma and S9. Considering the enzymatic biomarkers, lower variability in plasma was detected only for AChE, as CES, GST, and GR had lower variability in S9. Enzyme activity was higher in plasma for AChE, CES, and GST, while GR had higher activity in S9. Regarding the fluorescence-based method, lower variability was detected in plasma for GSH and ROS, although higher GSH detection was reported in S9, and higher ROS was detected in plasma. The present study indicated valuable differences by successfully establishing protocols for biomarker measurement in plasma and S9 based on variability, enzyme activity, and fluorescence. For a better understanding of the environmental effects on nestlings’ physiological condition, biomarkers can be measured in plasma and S9.
In an ideal world, extraction of machine-readable data and knowledge from natural-language biodiversity literature would be done automatically, but not so currently. The BIOfid project has developed some tools that can help with important parts of this highly demanding task, while certain parts of the workflow cannot be automated yet. BIOfid focuses on the 20th century legacy literature, a large part of which is only available in printed form. In this workshop, we will present the current state of the art in mobilisation of data from our corpus, as well as some challenges ahead of us. Together with the participants, we will exercise or explain the following tasks (some of which can be performed by the participants themselves, while other tasks currently require execution by our specialists with special equipment): Preparation of text files as an input; pre-processing with TextImager/TextAnnotator; semiautomated annotation and linking of named entities; generation of output in various formats; evaluation of the output. The workshop will also provide an outlook for further developments regarding extraction of statements from natural-language literature, with the long-term aim to produce machine-readable data from literature that can extend biodiversity databases and knowledge graphs.
Application of a developed tool to visualize newly synthesized AMPA receptor components in situ
(2018)
The information flow between neurons happens at contact points, the synapses. One underlying mechanism of learning and memory is the change in the strength of information flow in selected synapses. In order to match the huge demand in membranes and proteins to build and maintain the neurites' complex architecture, neurons use decentralized protein synthesis. Many candidate proteins for local synthesis are known, and the need of de novo synthesis for memory formation is well established. The underlying mechanisms of how somatic versus dendritic synthesis is regulated are yet to be elucidated. Which proteins are newly synthesized in order to allow learning?
In this thesis protein synthesis is studied in hippocampal neurons. The fractional distribution of somatic and dendritic synthesis for candidate proteins and their subsequent transport to their destination are investigated using a newly developed technique. In the first part of this study we describe the development of this technique and use it in the second part to answer biological questions.
We focus here on AMPA receptor subunits, the key players in fast excitatory transmission. AMPA receptors contain multiple subunits with diverse functions. It remains to be understood, when and where in a neuron these subunits come together to form a protein complex and how the choice of subunits is regulated.
The investigation of the subunits' site of synthesis and redistribution kinetics in this study will help us to understand how neurons are able to change their synaptic strength in an input specific manner which eventually allows learning and memory.
Key questions which are addressed in this study:
How can specific newly synthesized endogenous proteins be visualized in situ? What are the neuron's abilities to locally synthesize and fully assemble AMPA receptor complexes?
How fast do different AMPA receptor subunits redistribute within neurons after synthesis?
Antimicrobial resistance became a serious threat to the worldwide public health in this century. A better understanding of the mechanisms, by which bacteria infect host cells and how the host counteracts against the invading pathogens, is an important subject of current research. Intracellular bacteria of the Salmonella genus have been frequently used as a model system for bacterial infections. Salmonella are ingested by contaminated food or water and cause gastroenteritis and typhoid fever in animals and humans. Once inside the gastrointestinal tract, Salmonella can invade intestinal epithelial cells. The host cell can fight against intracellular pathogens by a process called xenophagy. For complex systems, such as processes involved in the bacterial infection of cells, computational systems biology provides approaches to describe mathematically how these intertwined mechanisms in the cell function. Computational systems biology allows the analysis of biological systems at different levels of abstraction. Functional dependencies as well as dynamic behavior can be studied. In this thesis, we used the Petri net formalism to gain a better insight into bacterial infections and host defense mechanisms and to predict cellular behavior that can be tested experimentally. We also focused on the development of new computational methods.
In this work, the first realization of a mathematical model of the xenophagic capturing of Salmonella enterica serovar Typhimurium in epithelial cells was developed. The mathematical model expressed in the Petri net formalism was constructed in an iterative way of modeling and analyses. For the model verification, we analyzed the Petri net, including a computational performance of knockout experiments named in silico knockouts, which was established in this work. The in silico knockouts of the proposed Petri net are consistent with the published experimental perturbation studies and, thus, ensures the biological credibility of the Petri net. In silico knockouts that have not been experimentally investigated yet provide hypotheses for future investigations of the pathway.
To study the dynamic behavior of an epithelial cell infected with Salmonella enterica serovar Typhimurium, a stochastic Petri net was constructed. In experimental research, a decision like "Which incubation time is needed to infect half of the epithelial cells with Salmonella?" is based on experience or practicability. A mathematical model can help to answer these questions and improve experimental design. The stochastic Petri net models the cell at different stages of the Salmonella infection. We parameterized the model by a set of experimental data derived from different literature sources. The kinetic parameters of the stochastic Petri net determine the time evolution of the bacterial infection of a cell. The model captures the stochastic variation and heterogeneity of the intracellular Salmonella population of a single cell over time. The stochastic Petri net is a valuable tool to examine the dynamics of Salmonella infections in epithelial cells and generate valuable information for experimental design.
In the last part of this thesis, a novel theoretical method was introduced to perform knockout experiments in silico. The new concept of in silico knockouts is based on the computation of signal flows at steady state and allows the determination of knockout behavior that is comparable to experimental perturbation behavior. In this context, we established the concept of Manatee invariants and demonstrated the suitability of their application for in silico knockouts by reflecting biological dependencies from the signal initiation to the response. As a proof of principle, we applied the proposed concept of in silico knockouts to the Petri net of the xenophagic recognition of Salmonella. To enable the application of in silico knockouts for the scientific community, we implemented the novel method in the software isiKnock. isiKnock allows the automatized performance and visualization of in silico knockouts in signaling pathways expressed in the Petri net formalism. In conclusion, the knockout analysis provides a valuable method to verify computational models of signaling pathways, to detect inconsistencies in the current knowledge of a pathway, and to predict unknown pathway behavior.
In summary, the main contributions of this thesis are the Petri net of the xenophagic capturing of Salmonella enterica serovar Typhimurium in epithelial cells to study the knockout behavior and the stochastic Petri net of an epithelial cell infected with Salmonella enterica serovar Typhimurium to analyze the infection dynamics. Moreover, we established a new method for in silico knockouts, including the concept of Manatee invariants and the software isiKnock. The results of these studies are useful to a better understanding of bacterial infections and provide valuable model analysis techniques for the field of computational systems biology.
The turnover time of terrestrial ecosystem carbon is an emergent ecosystem property that quantifies the strength of land surface on the global carbon cycle–climate feedback. However, observation- and modeling-based estimates of carbon turnover and its response to climate are still characterized by large uncertainties. In this study, by assessing the apparent whole ecosystem carbon turnover times (τ) as the ratio between carbon stocks and fluxes, we provide an update of this ecosystem level diagnostic and its associated uncertainties in high spatial resolution (0.083∘) using multiple, state-of-the-art, observation-based datasets of soil organic carbon stock (Csoil), vegetation biomass (Cveg) and gross primary productivity (GPP). Using this new ensemble of data, we estimated the global median τ to be 43+7−7 yr (median+difference to percentile 75−difference to percentile 25) when the full soil is considered, in contrast to limiting it to 1 m depth. Only considering the top 1 m of soil carbon in circumpolar regions (assuming maximum active layer depth is up to 1 m) yields a global median τ of 37+3−6 yr, which is longer than the previous estimates of 23+7−4 yr (Carvalhais et al., 2014). We show that the difference is mostly attributed to changes in global Csoil estimates. Csoil accounts for approximately 84 % of the total uncertainty in global τ estimates; GPP also contributes significantly (15 %), whereas Cveg contributes only marginally (less than 1 %) to the total uncertainty. The high uncertainty in Csoil is reflected in the large range across state-of-the-art data products, in which full-depth Csoil spans between 3362 and 4792 PgC. The uncertainty is especially high in circumpolar regions with an uncertainty of 50 % and a low spatial correlation between the different datasets (0.2<r<0.5) when compared to other regions (0.6<r<0.8). These uncertainties cast a shadow on current global estimates of τ in circumpolar regions, for which further geographical representativeness and clarification on variations in Csoil with soil depth are needed. Different GPP estimates contribute significantly to the uncertainties of τ mainly in semiarid and arid regions, whereas Cveg causes the uncertainties of τ in the subtropics and tropics. In spite of the large uncertainties, our findings reveal that the latitudinal gradients of τ are consistent across different datasets and soil depths. The current results show a strong ensemble agreement on the negative correlation between τ and temperature along latitude that is stronger in temperate zones (30–60∘ N) than in the subtropical and tropical zones (30∘ S–30∘ N). Additionally, while the strength of the τ–precipitation correlation was dependent on the Csoil data source, the latitudinal gradients also agree among different ensemble members. Overall, and despite the large variation in τ, we identified robust features in the spatial patterns of τ that emerge beyond the differences stemming from the data-driven estimates of Csoil, Cveg and GPP. These robust patterns, and associated uncertainties, can be used to infer τ–climate relationships and for constraining contemporaneous behavior of Earth system models (ESMs), which could contribute to uncertainty reductions in future projections of the carbon cycle–climate feedback. The dataset of τ is openly available at https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019).
The turnover time of terrestrial carbon (τ) controls the global carbon cycle – climate feedback and, yet, is poorly simulated by the current Earth System Models (ESMs). In this study, by assessing apparent carbon turnover time as the ratio between carbon stocks and fluxes, we provide a new, updated ensemble of diagnostic terrestrial carbon turnover times and associated uncertainties on a global scale using multiple, state-of-the-art, observation-based datasets of soil organic carbon stock (Csoil), vegetation biomass (Cveg) and gross primary productivity (GPP). Using this new ensemble, we estimated the global average τ to be 42$% &' years when the full soil depth is considered, longer than the previous estimates of 23$) &* years. Only considering the top 1 m (assuming maximum active layer depth is up to 1 meter) of soil carbon in circumpolar regions yields a global τ of 35$) &' years. Csoil in circumpolar regions account for two thirds of the total uncertainty in global τ estimates, whereas Csoil in non-circumpolar contributes merely 9.38%. GPP (2.25%) and Cveg (0.05%) contribute even less to the total uncertainty. Therefore, the high uncertainty in Csoil is the main factor behind the uncertainty in global τ, as reflected in the larger range of full-depth Csoil (3152-4372 PgC). The uncertainty is especially high in circumpolar regions with a behaviour of ESMs which could contribute to uncertainty reductions in future projections of the carbon cycle - climate feedback. The dataset of the terrestrial turnover time ensemble (DOI: 10.17871/bgitau.201911) is openly available from the data portal: https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019) uncertainty of 50% and the spatial correlations among different datasets are also low compared to other regions. Overall, we argue that current global datasets do not support robust estimates of τ globally, for which we need clarification on variations of Csoil with soil depth and stronger estimates of Csoil in circumpolar regions. Despite the large variation in both magnitude and spatial patterns of τ, we identified robust features in the spatial patterns of τ that emerge regardless of soil depth and differences in data sources of Csoil, Cveg and GPP. Our findings show that the latitudinal gradients of τ are consistent across different datasets and soil depth. Furthermore, there is a strong consensus on the negative correlation between τ and temperature along latitude that is stronger in temperate zones (30ºN-60ºN) than in subtropical and tropical zones (30ºS30ºN). The identified robust patterns can be used to infer the response of τ to climate and for constraining contemporaneous behaviour of ESMs which could contribute to uncertainty reductions in future projections of the carbon cycle - climate feedback. The dataset of the terrestrial turnover time ensemble (DOI:10.17871/bgitau.201911) is openly available from the data portal: https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019).
Abstract: The hallmarks of Alzheimer’s disease (AD) are characterized by cognitive decline and behavioral changes. The most prominent brain region affected by the progression of AD is the hippocampal formation. The pathogenesis involves a successive loss of hippocampal neurons accompanied by a decline in learning and memory consolidation mainly attributed to an accumulation of senile plaques. The amyloid precursor protein (APP) has been identified as precursor of Aβ-peptides, the main constituents of senile plaques. Until now, little is known about the physiological function of APP within the central nervous system. The allocation of APP to the proteome of the highly dynamic presynaptic active zone (PAZ) highlights APP as a yet unknown player in neuronal communication and signaling. In this study, we analyze the impact of APP deletion on the hippocampal PAZ proteome. The native hippocampal PAZ derived from APP mouse mutants (APP-KOs and NexCreAPP/APLP2-cDKOs) was isolated by subcellular fractionation and immunopurification. Subsequently, an isobaric labeling was performed using TMT6 for protein identification and quantification by high-resolution mass spectrometry. We combine bioinformatics tools and biochemical approaches to address the proteomics dataset and to understand the role of individual proteins. The impact of APP deletion on the hippocampal PAZ proteome was visualized by creating protein-protein interaction (PPI) networks that incorporated APP into the synaptic vesicle cycle, cytoskeletal organization, and calcium-homeostasis. The combination of subcellular fractionation, immunopurification, proteomic analysis, and bioinformatics allowed us to identify APP as structural and functional regulator in a context-sensitive manner within the hippocampal active zone network.
Author Summary: More than 20 years ago, the amyloid precursor protein (APP) was identified as the precursor protein of the Aβ peptide, the main component of senile plaques in brains affected by Alzheimer’s disease. However, little is known about the physiological function of amyloid precursor protein. Allocating APP to the proteome of the structurally and functionally dynamic presynaptic active zone highlights APP as a hitherto unknown player within the presynaptic network. The hippocampus is the most prominent brain region for learning and memory consolidation, and a vulnerable target for neurodegenerative disease, e. g. Alzheimer’s disease. Therefore, our experimental design is focused on the hippocampal neurotransmitter release site. Currently, the underlying mechanism of how APP acts within presynaptic networks is still elusive. Within the scope of this research article, we constructed a network of APP within the presynaptic active zone and how deletion of APP affects these individual networks. We combine bioinformatics tools and biochemical approaches to address the dataset provided by proteomics. Furthermore, we could unravel that APP executes regulatory functions within the synaptic vesicle cycle, cytoskeletal rearrangements and Ca2+-homeostasis. Taken together, our findings offer a new perspective on the physiological function of APP in the central nervous system and may provide a molecular link to the pathogenesis of Alzheimer’s disease.