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Institute
- Graduate School of Life Sciences (799) (remove)
Sonstige beteiligte Institutionen
- Helmholtz Institute for RNA-based Infection Research (HIRI) (7)
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg (2)
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- Carl-Ludwig-Institut für Physiologie, Universität Leipzig (1)
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- DAAD - Deutscher Akademischer Austauschdienst (1)
The unicellular pathogen Trypanosoma brucei is the causative agent of African
trypanosomiasis, an endemic disease prevalent in sub-Saharan Africa. Trypanosoma brucei alternates between a mammalian host and the tsetse fly vector. The extracellular parasite survives in the mammalian bloodstream by periodically exchanging their ˈvariant surface glycoproteinˈ (VSG) coat to evade the host immune response. This antigenic variation is achieved through monoallelic expression of one VSG variant from subtelomeric ˈbloodstream
form expression sitesˈ (BES) at a given timepoint. During the differentiation from the bloodstream form (BSF) to the procyclic form (PCF) in the tsetse fly midgut, the stage specific surface protein is transcriptionally silenced and replaced by procyclins. Due to their subtelomeric localization on the chromosomes, VSG transcription and silencing is partly regulated by homologues of the mammalian telomere complex such as TbTRF, TbTIF2 and TbRAP1 as well as by ˈtelomere-associated proteinsˈ (TelAPs) like TelAP1. To gain more insights into transcription regulation of VSG genes, the identification and characterization of other TelAPs is critical and has not yet been achieved. In a previous study, two biochemical approaches were used to identify other novel TelAPs. By using ˈco-immunoprecipitationˈ (co-IP) to enrich possible interaction partners of TbTRF and by affinity chromatography using telomeric repeat oligonucleotides, a listing of TelAP candidates has been conducted. With this approach TelAP1 was identified as a novel component of the telomere complex, involved in the kinetics of transcriptional BES silencing during BSF to PCF differentiation. To gain further insights into the telomere complex composition, other previously enriched proteins were characterized through a screening process using RNA interference to deplete potential candidates. VSG expression profile changes and overall proteomic changes after depletion were analyzed by mass spectrometry. With this method, one can gain insights into the functions of the proteins and their involvement in VSG expression site regulation. To validate the interaction of proteins enriched by co-IP with TbTRF and TelAP1 and to identify novel interaction proteins, I performed reciprocal affinity purifications of the four most promising candidates (TelAP2, TelAP3, PPL2 and PolIE) and additionally confirmed colocalization of two candidates with TbTRF via immunofluorescence (TelAP2, TelAP3). TelAP3 colocalizes with TbTRF and potentially interacts with TbTRF, TbTIF2, TelAP1 and TelAP2, as well as with two translesion polymerases PPL2 and PolIE in BSF. PPL2 and PolIE seem to be in close contact to each other at the telomeric ends and fulfill different roles as only PolIE is involved in VSG regulation while PPL2 is not. TelAP2 was previously characterized to be associated with telomeres by partially colocalizing with TbTRF and cells show a VSG derepression phenotype when the protein was depleted. Here I show that TelAP2 interacts with the telomere-binding proteins TbTRF and TbTIF2 as well as with the telomere-associated protein TelAP1 in BSF and that TelAP2 depletion results in a loss of TelAP1 colocalization with TbTRF in BSF.
In conclusion, this study demonstrates that characterizing potential TelAPs is effective in gaining insights into the telomeric complex's composition and its role in VSG regulation in Trypanosoma brucei. Understanding these interactions could potentially lead to new therapeutic targets for combatting African trypanosomiasis.
Development Of A Human iPSC-Derived Cortical Neuron Model Of Adaptor- Protein-Complex-4-Deficiency
(2024)
Adaptor-protein-4-deficiency (AP-4-deficiency) is an autosomal-recessive childhood- onset form of complicated hereditary spastic paraplegia (HSP) caused by bi-allelic loss- of-function mutations in one of the four subunits of the AP-4-complex. These four conditions are named SPG47 (AP4B1, OMIM #614066), SPG50 (AP4M1, OMIM #612936), SPG51 (AP4E1, OMIM #613744) and SPG52 (AP4S1, OMIM #614067), respectively and all present with global developmental delay, progressive spasticity and seizures. Imaging features include a thinning of the corpus callosum, ventriculomegaly and white matter changes. AP-4 is a highly conserved heterotetrameric complex, which is responsible for polarized sorting of transmembrane cargo including the autophagy- related protein 9 A (ATG9A). Loss of any of the four subunits leads to an instable complex and defective sorting of AP-4-cargo. ATG9A is implicated in autophagosome formation and neurite outgrowth. It is missorted in AP-4-deficient cells and CNS-specific knockout of Atg9a in mice results in a phenotype reminiscent of AP-4-deficiency. However, the AP-4-related cellular phenotypes including ATG9A missorting have not been investigated in human neurons.
Thus, the aim of this study is to provide the first human induced pluripotent stem cell- derived (iPSC) cortical neuron model of AP-4-deficiency to explore AP-4-related phenotypes in preparation for a high-content screening. Under the hypothesis that AP-4- deficiency leads to ATG9A missorting, elevated ATG9A levels, impaired autophagy and neurite outgrowth in human iPSC-derived cortical neurons, in vitro biochemical and imaging assays including automated high-content imaging and analysis were applied. First, these phenotypes were investigated in fibroblasts from three patients with compound heterozygous mutations in the AP4B1 gene and their sex-matched parental controls. The same cell lines were used to generate iPSCs and differentiate them into human excitatory cortical neurons.
This work shows that ATG9A is accumulating in the trans-Golgi-network in AP-4- deficient human fibroblasts and that ATG9A levels are increased compared to parental controls and wild type cells suggesting a compensatory mechanism. Protein levels of the AP4E1-subunit were used as a surrogate marker for the AP-4-complex and were decreased in AP-4-deficient fibroblasts with co-immunoprecipitation confirming the instability of the complex. Lentiviral re-expression of the AP4B1-subunit rescues this corroborating the fact that a stable AP-4-complex is needed for ATG9A trafficking. Surprisingly, autophagic flux was present in AP-4-deficient fibroblasts under nutrient- rich and starvation conditions. These phenotypic markers were evaluated in iPSC-derived cortical neurons and here, a robust accumulation of ATG9A in the juxtanuclear area was seen together with elevated ATG9A protein levels. Strikingly, assessment of autophagy markers under nutrient-rich conditions showed alterations in AP-4-deficient iPSC- derived cortical neurons indicating dysfunctional autophagosome formation. These findings point towards a neuron-specific impairment of autophagy and need further investigation. Adding to the range of AP-4-related phenotypes, neurite outgrowth and branching are impaired in AP-4-deficient iPSC-derived cortical neurons as early as 24h after plating and together with recent studies point towards a distinct role of ATG9A in neurodevelopment independent of autophagy.
Together, this work provides the first patient-derived neuron model of AP-4-deficiency and shows that ATG9A is sorted in an AP-4-dependent manner. It establishes ATG9A- related phenotypes and impaired neurite outgrowth as robust markers for a high-content screening. This disease model holds the promise of providing a platform to further study AP-4-deficiency and to search for novel therapeutic targets.
The expression of the MYC proto-oncogene is elevated in a large proportion of patients with pancreatic ductal adenocarcinoma (PDAC). Previous findings in PDAC have shown that this increased MYC expression mediates immune evasion and promotes S-phase progression. How these functions are mediated and whether a downstream factor of MYC mediates these functions has remained elusive. Recent studies identifying the MYC interactome revealed a complex network of interaction partners, highlighting the need to identify the oncogenic pathway of MYC in an unbiased manner.
In this work, we have shown that MYC ensures genomic stability during S-phase and prevents transcription-replication conflicts. Depletion of MYC and inhibition of ATR kinase showed a synergistic effect to induce DNA damage. A targeted siRNA screen targeting downstream factors of MYC revealed that PAF1c is required for DNA repair and S-phase progression. Recruitment of PAF1c to RNAPII was shown to be MYC dependent. PAF1c was shown to be largely dispensable for cell proliferation and regulation of MYC target genes.
Depletion of CTR9, a subunit of PAF1c, caused strong tumor regression in a pancreatic ductal adenocarcinoma model, with long-term survival in a subset of mice. This effect was not due to induction of DNA damage, but to restoration of tumor immune surveillance.
Depletion of PAF1c resulted in the release of RNAPII with transcription elongation factors, including SPT6, from the bodies of long genes, promoting full-length transcription of short genes. This resulted in the downregulation of long DNA repair genes and the concomitant upregulation of short genes, including MHC class I genes. These data demonstrate that a balance between long and short gene transcription is essential for tumor progression and that interference with PAF1c levels shifts this balance toward a tumor-suppressive transcriptional program. It also directly links MYC-mediated S-phase progression to immune evasion. Unlike MYC, PAF1c has a stable, known folded structure; therefore, the development of a small molecule targeting PAF1c may disrupt the immune evasive function of MYC while sparing its physiological functions in cellular growth.
Adoptive cellular immunotherapy with chimeric antigen receptor (CAR) T cells is highly effective in haematological malignancies. This success, however, has not been achieved in solid tumours so far. In contrast to hematologic malignancies, solid tumours include a hostile tumour microenvironment (TME), that poses additional challenges for curative effects and consistent therapeutic outcome. These challenges manifest in physical and immunological barriers that dampen efficacy of the CAR T cells. Preclinical testing of novel cellular immunotherapies is performed mainly in 2D cell culture and animal experiments. While 2D cell culture is an easy technique for efficacy analysis, animal studies reveal information about toxicity in vivo. However, 2D cell culture cannot fully reflect the complexity observed in vivo, because cells are cultured without anchorage to a matrix and only short-term periods are feasible. Animal studies provide a more complex tissue environment, but xenografts often lack human stroma and tumour inoculation occurs mostly ectopically. This emphasises the need for standardisable and scalable tumour models with incorporated TME-aspects, which enable preclinical testing with enhanced predictive value for the clinical outcome of immunotherapies. Therefore, microphysiologic 3D tumour models based on the biological SISmuc (Small Intestinal mucosa and Submucosa) matrix with preserved basement membrane were engaged and improved in this work to serve as a modular and versatile tumour model for efficacy testing of CAR T cells. In order to reflect a variety of cancer entities, TME-aspects, long-term stability and to enhance the read-out options they were further adapted to achieve scalable and standardisable defined microphysiologic 3D tumour models. In this work, novel culture modalities (semi-static, sandwich-culture) were characterised and established that led to an increased and organised tissue generation and long-term stability. Application of the SISmuc matrix was extended to sarcoma and melanoma models and serial bioluminescence intensity (BLI)-based in vivo imaging analysis was established in the microphysiologic 3D tumour models, which represents a time-efficient read-out method for quality evaluation of the models and treatment efficacy analysis, that is independent of the cell phenotype. Isolation of cancer-associated-fibroblasts (CAFs) from lung (tumour) tissue was demonstrated and CAF-implementation further led to stromal-enriched microphysiologic 3D tumour models with in vivo-comparable tissue-like architecture. Presence of CAFs was confirmed by CAF-associated markers (FAP, α-SMA, MMP-2/-9) and cytokines correlated with CAF phenotype, angiogenesis, invasion and immunomodulation. Additionally, an endothelial cell barrier was implemented for static and dynamic culture in a novel bioreactor set-up, which is of particular interest for the analysis of immune cell diapedesis. Studies in microphysiologic 3D Ewing’s sarcoma models indicated that sarcoma cells could be sensitised for GD2-targeting CAR T cells. After enhancing the scale of assessment of the microphysiologic 3D tumour models and improving them for CAR T cell testing, the tumour models were used to analyse their sensitivity towards differently designed receptor tyrosine kinase-like orphan receptor 1 (ROR1) CAR T cells and to study the effects of the incorporated TME-aspects on the CAR T cell treatment respectively. ROR1 has been described as a suitable target for several malignancies including triple negative breast cancer (TNBC), as well as lung cancer. Therefore, microphysiologic 3D TNBC and lung cancer models were established. Analysis of ROR1 CAR T cells that differed in costimulation, spacer length and targeting domain, revealed, that the microphysiologic 3D tumour models are highly sensitive and can distinguish optimal from sub-optimal CAR design. Here, higher affinity of the targeting domain induced stronger anti-tumour efficacy and anti-tumour function depended on spacer length, respectively. Long-term treatment for 14 days with ROR1 CAR T cells was demonstrated in dynamic microphysiologic 3D lung tumour models, which did not result in complete tumour cell removal, whereas direct injection of CAR T cells into TNBC and lung tumour models represented an alternative route of application in addition to administration via the medium flow, as it induced strong anti-tumour response. Influence of the incorporated TME-aspects on ROR1 CAR T cell therapy represented by CAF-incorporation and/or TGF-β supplementation was analysed. Presence of TGF-β revealed that the specific TGF-β receptor inhibitor SD-208 improves ROR1 CAR T cell function, because it effectively abrogated immunosuppressive effects of TGF-β in TNBC models. Implementation of CAFs should provide a physical and immunological barrier towards ROR1 CAR T cells, which, however, was not confirmed, as ROR1 CAR T cell function was retained in the presence of CAFs in stromal-enriched microphysiologic 3D lung tumour models. The absence of an effect of CAF enrichment on CAR T cell efficacy suggests a missing component for the development of an immunosuppressive TME, even though immunomodulatory cytokines were detected in co-culture models. Finally, improved gene-edited ROR1 CAR T cells lacking exhaustion-associated genes (PD-1, TGF-β-receptor or both) were challenged by the combination of CAF-enrichment and TGF-β in microphysiologic 3D TNBC models. Results indicated that the absence of PD-1 and TGF-β receptor leads to improved CAR T cells, that induce strong tumour cell lysis, and are protected against the hostile TME. Collectively, the microphysiologic 3D tumour models presented in this work reflect aspects of the hostile TME of solid tumours, engage BLI-based analysis and provide long-term tissue homeostasis. Therefore, they present a defined, scalable, reproducible, standardisable and exportable model for translational research with enhanced predictive value for efficacy testing and candidate selection of cellular immunotherapy, as exemplified by ROR1 CAR T cells.
Among the defense strategies developed in microbes over millions of years, the innate adaptive CRISPR-Cas immune systems have spread across most of bacteria and archaea. The flexibility, simplicity, and specificity of CRISPR-Cas systems have laid the foundation for CRISPR-based genetic tools. Yet, the efficient administration of CRISPR-based tools demands rational designs to maximize the on-target efficiency and off-target specificity. Specifically, the selection of guide RNAs (gRNAs), which play a crucial role in the target recognition of CRISPR-Cas systems, is non-trivial. Despite the fact that the emerging machine learning techniques provide a solution to aid in gRNA design with prediction algorithms, design rules for many CRISPR-Cas systems are ill-defined, hindering their broader applications.
CRISPR interference (CRISPRi), an alternative gene silencing technique using a catalytically dead Cas protein to interfere with transcription, is a leading technique in bacteria for functional interrogation, pathway manipulation, and genome-wide screens. Although the application is promising, it also is hindered by under-investigated design rules. Therefore, in this work, I develop a state-of-art predictive machine learning model for guide silencing efficiency in bacteria leveraging the advantages of feature engineering, data integration, interpretable AI, and automated machine learning. I first systematically investigate the influential factors that attribute to the extent of depletion in multiple CRISPRi genome-wide essentiality screens in Escherichia coli and demonstrate the surprising dominant contribution of gene-specific effects, such as gene expression level. These observations allowed me to segregate the confounding gene-specific effects using a mixed-effect random forest (MERF) model to provide a better estimate of guide efficiency, together with the improvement led by integrating multiple screens. The MERF model outperformed existing tools in an independent high-throughput saturating screen. I next interpret the predictive model to extract the design rules for robust gene silencing, such as the preference for cytosine and disfavoring for guanine and thymine within and around the protospacer adjacent motif (PAM) sequence. I further incorporated the MERF model in a web-based tool that is freely accessible at www.ciao.helmholtz-hiri.de.
When comparing the MERF model with existing tools, the performance of the alternative gRNA design tool optimized for CRISPRi in eukaryotes when applied to bacteria was far from satisfying, questioning the robustness of prediction algorithms across organisms. In addition, the CRISPR-Cas systems exhibit diverse mechanisms albeit with some similarities. The captured predictive patterns from one dataset thereby are at risk of poor generalization when applied across organisms and CRISPR-Cas techniques. To fill the gap, the machine learning approach I present here for CRISPRi could serve as a blueprint for the effective development of prediction algorithms for specific organisms or CRISPR-Cas systems of interest. The explicit workflow includes three principle steps: 1) accommodating the feature set for the CRISPR-Cas system or technique; 2) optimizing a machine learning model using automated machine learning; 3) explaining the model using interpretable AI. To illustrate the applicability of the workflow and diversity of results when applied across different bacteria and CRISPR-Cas systems, I have applied this workflow to analyze three distinct CRISPR-Cas genome-wide screens. From the CRISPR base editor essentiality screen in E. coli, I have determined the PAM preference and sequence context in the editing window for efficient editing, such as A at the 2nd position of PAM, A/TT/TG downstream of PAM, and TC at the 4th to 5th position of gRNAs. From the CRISPR-Cas13a screen in E. coli, in addition to the strong correlation with the guide depletion, the target expression level is the strongest predictor in the model, supporting it as a main determinant of the activation of Cas13-induced immunity and better characterizing the CRISPR-Cas13 system. From the CRISPR-Cas12a screen in Klebsiella pneumoniae, I have extracted the design rules for robust antimicrobial activity across K. pneumoniae strains and provided a predictive algorithm for gRNA design, facilitating CRISPR-Cas12a as an alternative technique to tackle antibiotic resistance.
Overall, this thesis presents an accurate prediction algorithm for CRISPRi guide efficiency in bacteria, providing insights into the determinants of efficient silencing and guide designs. The systematic exploration has led to a robust machine learning approach for effective model development in other bacteria and CRISPR-Cas systems. Applying the approach in the analysis of independent CRISPR-Cas screens not only sheds light on the design rules but also the mechanisms of the CRISPR-Cas systems. Together, I demonstrate that applied machine learning paves the way to a deeper understanding and a broader application of CRISPR-Cas systems.
The WHO-designated neglected-disease pathogen Chlamydia trachomatis (CT) is a gram-negative bacterium responsible for the most frequently diagnosed sexually transmitted infection worldwide. CT infections can lead to infertility, blindness and reactive arthritis, among others. CT acts as an infectious agent by its ability to evade the immune response of its host, which includes the impairment of the NF-κB mediated inflammatory response and the Mcl1 pro-apoptotic pathway through its deubiquitylating, deneddylating and transacetylating enzyme ChlaDUB1 (Cdu1). Expression of Cdu1 is also connected to host cell Golgi apparatus fragmentation, a key process in CT infections.
Cdu1 may this be an attractive drug target for the treatment of CT infections. However, a lead molecule for the development of novel potent inhibitors has been unknown so far. Sequence alignments and phylogenetic searches allocate Cdu1 in the CE clan of cysteine proteases. The adenovirus protease (adenain) also belongs to this clan and shares a high degree of structural similarity with Cdu1. Taking advantage of topological similarities between the active sites of Cdu1 and adenain, a target-hopping approach on a focused set of adenain inhibitors, developed at Novartis, has been pursued. The thereby identified cyano-pyrimidines represent the first active-site directed covalent reversible inhibitors for Cdu1. High-resolution crystal structures of Cdu1 in complex with the covalently bound cyano-pyrimidines as well as with its substrate ubiquitin have been elucidated. The structural data of this thesis, combined with enzymatic assays and covalent docking studies, provide valuable insights into Cdu1s activity, substrate recognition, active site pocket flexibility and potential hotspots for ligand interaction. Structure-informed drug design permitted the optimization of this cyano-pyrimidine based scaffold towards HJR108, the first molecule of its kind specifically designed to disrupt the function of Cdu1. The structures of potentially more potent and selective Cdu1 inhibitors are herein proposed.
This thesis provides important insights towards our understanding of the structural basis of ubiquitin recognition by Cdu1, and the basis to design highly specific Cdu1 covalent inhibitors.
Electrochemical impedance spectroscopy (EIS) is a valuable technique analyzing electrochemical behavior of biological systems such as electrical characterization of cells and biomolecules, drug screening, and biomaterials in biomedical field. In EIS, an alternating current (AC) power signal is applied to the biological system, and the impedance of the system is measured over a range of frequencies.
In vitro culture models of endothelial or epithelial barrier tissue can be achieved by culturing barrier tissue on scaffolds made with synthetic or biological materials that provide separate compartments (apical and basal sides), allowing for further studies on drug transport. EIS is a great candidate for non-invasive and real-time monitoring of the electrical properties that correlate with barrier integrity during the tissue modeling. Although commercially available transendothelial/transepithelial electrical resistance (TEER) measurement devices are widely used, their use is particularly common in static transwell culture. EIS is considered more suitable than TEER measurement devices in bioreactor cultures that involve dynamic fluid flow to obtain accurate and reliable measurements. Furthermore, while TEER measurement devices can only assess resistance at a single frequency, EIS measurements can capture both resistance and capacitance properties of cells, providing additional information about the cellular barrier's characteristics across various frequencies. Incorporating EIS into a bioreactor system requires the careful optimization of electrode integration within the bioreactor setup and measurement parameters to ensure accurate EIS measurements. Since bioreactors vary in size and design depending on the purpose of the study, most studies have reported using an electrode system specifically designed for a particular bioreactor. The aim of this work was to produce multi-applicable electrodes and established methods for automated non-invasive and real-time monitoring using the EIS technique in bioreactor cultures. Key to the electrode material, titanium nitride (TiN) coating was fabricated on different substrates (materials and shape) using physical vapor deposition (PVD) and housed in a polydimethylsiloxane (PDMS) structure to allow the electrodes to function as independent units. Various electrode designs were evaluated for double-layer capacitance and morphology using EIS and scanning electron microscopy (SEM), respectively. The TiN-coated tube electrode was identified as the optimal choice. Furthermore, EIS measurements were performed to examine the impact of influential parameters related to culture conditions on the TiN-coated electrode system. In order to demonstrate the versatility of the electrodes, these electrodes were then integrated into in different types of perfusion bioreactors for monitoring barrier cells. Blood-brain barrier (BBB) cells were cultured in the newly developed dynamic flow bioreactor, while human umblical vascular endothelial cells (HUVECs) and Caco-2 cells were cultured in the miniature hollow fiber bioreactor (HFBR). As a result, the TiN-coated tube electrode system enabled investigation of BBB barrier integrity in long-term bioreactor culture. While EIS measurement could not detect HUVECs electrical properties in miniature HFBR culture, there was the possibility of measuring the barrier integrity of Caco-2 cells, indicating potential usefulness for evaluating their barrier function. Following the bioreactor cultures, the application of the TiN-coated tube electrode was expanded to hemofiltration, based on the hypothesis that the EIS system may be used to monitor clotting or clogging phenomena in hemofiltration. The findings suggest that the EIS monitoring system can track changes in ion concentration of blood before and after hemofiltration in real-time, which may serve as an indicator of clogging of filter membranes. Overall, our research demonstrates the potential of TiN-coated tube electrodes for sensitive and versatile non-invasive monitoring in bioreactor cultures and medical devices.
Barth Syndrome (BTHS) is an inherited X-chromosomal linked disorder, characterized by early development of cardiomyopathy, immune system defects, skeletal muscle myopathy and growth retardation. The disease displays a wide variety of symptoms including heart failure, exercise intolerance and fatigue due to the muscle weakness. The cause of the disease are mutations in the gene encoding for the mitochondrial transacylase Tafazzin (TAZ), which is important for remodeling of the phospholipid cardiolipin (CL). All mutations result in a pronounced decrease of the functional enzyme leading to an increase of monolysocardiolipin (MLCL), the precursor of mature CL, and a decrease in mature CL itself. CL is a hallmark phospholipid of mitochondrial membranes, highly enriched in the inner mitochondrial membrane (IMM). It is not only important for the formation of the cristae structures, but also for the function of different protein complexes associated with the mitochondrial membrane. Reduced levels of mature CL cause remodeling of the respiratory chain supercomplexes, impaired respiration, defects in the Krebs cycle and a loss of mitochondrial calcium uniporter (MCU) protein. The defective Ca2+ handling causes impaired redox homeostasis and energy metabolism resulting in cellular arrhythmias and defective electrical conduction. In an uncompensated situation, blunting mitochondrial Ca2+ uptake provokes increased mitochondrial emission of H2O2 during workload transitions, related to oxidation of NADPH, which is required to regenerate anti-oxidative enzymes. However, in the hearts and cardiac myocytes of mice with a global knock-down of the Taz gene (Taz-KD), no increase in mitochondrial ROS was observed, suggesting that other metabolic pathways may have compensated for reduced Krebs cycle activation.
The healthy heart produces most of its energy by consuming fatty acids. In this study, the fatty acid uptake into mitochondria and their further degradation was investigated, which showed a switch of the metabolism in general in the Taz-KD mouse model. In vivo studies revealed an increase of glucose uptake into the heart and decreased fatty acid uptake and oxidation. Disturbed energy conversion resulted in activation of retrograde signaling pathways, implicating overall changes in the cell metabolism. Upregulated integrated stress response (ISR) was confirmed by increased levels of the downstream target, i.e., the activating transcription factor 4 (ATF4). A Tafazzin knockout mouse embryonal fibroblast cell model (TazKO) was used to inhibit the ISR using siRNA transfection or pharmaceutical inhibition. This verified the central role of
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the ISR in regulating the metabolism in BTHS. Moreover, an increased metabolic flux into glutathione biosynthesis was observed, which supports redox homeostasis. In vivo PET-CT scans depicted elevated activity of the xCT system in the BTHS mouse heart, which transports essential amino acids for the biosynthesis of glutathione precursors. Furthermore, the stress induced signaling pathway also affected the glutamate metabolism, which fuels into the Krebs cycle via -ketoglutarate and therefore supports energy converting pathways. In summary, this thesis provides novel insights into the energy metabolism and redox homeostasis in Barth syndrome cardiomyopathy and its regulation by the integrated stress response, which plays a central role in the metabolic alterations. The aim of the thesis was to improve the understanding of these metabolic changes and to identify novel targets, which can provide new possibilities for therapeutic intervention in Barth syndrome.
Anxiety patients overgeneralize fear, also because of an inability to perceptually discriminate threat and safety signals. Therefore, some studies have developed discrimination training that successfully reduced the occurrence of fear generalization. The present work is the first to take a treatment-like approach by using discrimination training after generalization has occurred. Therefore, two studies were conducted with healthy participants using the same fear conditioning and generalization paradigm, with two faces as conditioned stimuli (CSs), and four facial morphs between CSs as generalization stimuli (GSs). Only one face (CS+) was followed by a loud scream (unconditioned stimulus, US). In Study 1, participants underwent either fear-relevant (discriminating faces) or fear-irrelevant discrimination training (discriminating width of lines) or a non-discriminative control training between the two generalization tests, each with or without feedback (n = 20 each). Generalization of US expectancy was reduced more effectively by fear-relevant compared to fear-irrelevant discrimination training. However, neither discrimination training was more effective than non-discriminative control training. Moreover, feedback reduced generalization of US expectancy only in discrimination training. Study 2 was designed to replicate the effects of the discrimination-training conditions in a large sample (N = 244) and examine their benefits in individuals at risk for anxiety disorders. Again, feedback reduced fear generalization particularly well for US expectancy. Fear relevance was not confirmed to be particularly fear-reducing in healthy participants, but may enhance training effects in individuals at risk of anxiety disorder. In summary, this work provides evidence that existing fear generalization can be reduced by discrimination training, likely involving several (higher-level) processes besides perceptual discrimination (e.g., motivational mechanisms in feedback conditions). Its use may be promising as part of individualized therapy for patients with difficulty discriminating similar stimuli.
Cognition refers to the ability to of animals to acquire, process, store and use vital information from the environment. Cognitive processes are necessary to predict the future and reduce the uncertainty of the ever-changing environment. Classically, research on animal cognition focuses on decisive cognitive tests to determine the capacity of a species by the testing the ability of a few individuals. This approach views variability between these tested key individuals as unwanted noise and is thus often neglected. However, inter-individual variability provides important insights to behavioral plasticity, cognitive specialization and brain modularity. Honey bees Apis mellifera are a robust and traditional model for the study of learning, memory and cognition due to their impressive capabilities and rich behavioral repertoire. In this thesis I have applied a novel view on the learning abilities of honey bees by looking explicitly at individual differences in a variety of learning tasks. Are some individual bees consistently smarter than some of her sisters? If so, will a smart individual always perform good independent of the time, the context and the cognitive requirements or do bees show distinct isolated ‘cognitive modules’?
My thesis presents the first comprehensive investigation of consistent individual differences in the cognitive abilities of honey bees. To speak of an individual as behaving consistently, a crucial step is to test the individual multiple times to examine the repeatability of a behavior. I show that free-flying bees remain consistent in a visual discrimination task for three consecutive days. Successively, I explored individual consistency in cognitive proficiency across tasks involving different sensory modalities, contexts and cognitive requirements. I found that free-flying bees show a cognitive specialization between visual and olfactory learning but remained consistent across a simple discrimination task and a complex concept learning task. I wished to further explore individual consistency with respect to tasks of different cognitive complexity, a question that has never been tackled before in an insect. I thus performed a series of four experiments using either visual or olfactory stimuli and a different training context (free-flying and restrained) and tested bees in a discrimination task, reversal learning and negative patterning. Intriguingly, across all these experiments I evidenced the same results: The bees’ performances were consistent across the discrimination task and reversal learning and negative patterning respectively. No association was evidenced between reversal learning and negative patterning. After establishing the existence of consistent individual differences in the cognitive proficiency of honey bees I wished to determine factors which could underlie these differences. Since genetic components are known to underlie inter-individual variability in learning abilities, I studied the effects of genetics on consistency in cognitive proficiency by contrasting bees originating from either from a hive with a single patriline (low genetic diversity) or with multiple patrilines (high genetic diversity). These two groups of bees showed differences in the patterns of individually correlated performances, indicating a genetic component accounts for consistent cognitive individuality. Another major factor underlying variability in learning performances is the individual responsiveness to sucrose solution and to visual stimuli, as evidenced by many studies on restrained bees showing a positive correlation between responsiveness to task relevant stimuli and learning performances. I thus tested whether these relationships between sucrose/visual responsiveness and learning performances are applicable for free-flying bees. Free-flying bees were again subjected to reversal learning and negative patterning and subsequently tested in the laboratory for their responsiveness to sucrose and to light. There was no evidence of a positive relationship between sucrose/visual responsiveness and neither performances of free-flying bees in an elemental discrimination, reversal learning and negative patterning. These findings indicate that relationships established between responsiveness to task relevant stimuli and learning proficiency established in the laboratory with restrained bees might not hold true for a completely different behavioral context i.e. for free-flying bees in their natural environment.
These results show that the honey bee is an excellent insect model to study consistency in cognitive proficiency and to identify the underlying factors. I mainly discuss the results with respect to the question of brain modularity in insects and the adaptive significance of individuality in cognitive abilities for honey bee colonies. I also provide a proposition of research questions which tie in this theme of consistent cognitive proficiency and could provide fruitful areas for future research.