@phdthesis{Janz2024,
  author    = {Janz, Anna},
  title     = {Human induced pluripotent stem cells (iPSCs) in inherited cardiomyopathies: Generation and characterization of an iPSC-derived cardiomyocyte model system of dilated cardiomyopathy with ataxia (DCMA)},
  doi       = {10.25972/OPUS-24096},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-240966},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {The emergence of human induced pluripotent stem cells (iPSCs) and the rise of the clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) gene editing technology innovated the research platform for scientists based on living human pluripotent cells. The revolutionary combination of both Nobel Prize-honored techniques enables direct disease modeling especially for research focused on genetic diseases. To allow the study on mutation-associated pathomechanisms, we established robust human in vitro systems of three inherited cardiomyopathies: arrhythmogenic cardiomyopathy (ACM), dilated cardiomyopathy with juvenile cataract (DCMJC) and dilated cardiomyopathy with ataxia (DCMA). Sendai virus vectors encoding OCT3/4, SOX2, KLF4, and c-MYC were used to reprogram human healthy control or mutation-bearing dermal fibroblasts from patients to an embryonic state thereby allowing the robust and efficient generation of in total five transgene-free iPSC lines. The nucleofection-mediated CRISPR/Cas9 plasmid delivery in healthy control iPSCs enabled precise and efficient genome editing by mutating the respective disease genes to create isogenic mutant control iPSCs. Here, a PKP2 knock-out and a DSG2 knock-out iPSC line were established to serve as a model of ACM. Moreover, a DNAJC19 C-terminal truncated variant (DNAJC19tv) was established to mimic a splice acceptor site mutation in DNAJC19 of two patients with the potential of recapitulating DCMA-associated phenotypes. In total eight self-generated iPSC lines were assessed matching internationally defined quality control criteria. The cells retained their ability to differentiate into cells of all three germ layers in vitro and maintained a stable karyotype. All iPSC lines exhibited a typical stem cell-like morphology as well as expression of characteristic pluripotency markers with high population purities, thus validating the further usage of all iPSC lines in in vitro systems of ACM, DCMA and DCMJC. Furthermore, cardiac-specific disease mechanisms underlying DCMA were investigated using in vitro generated iPSC-derived cardiomyocytes (iPSC-CMs). DCMA is an autosomal recessive disorder characterized by life threatening early onset cardiomyopathy associated with a metabolic syndrome. Causal mutations were identified in the DNAJC19 gene encoding an inner mitochondrial membrane (IMM) protein with a presumed function in mitochondrial biogenesis and cardiolipin (CL) remodeling. In total, two DCMA patient-derived iPSC lines (DCMAP1, DCMAP2) of siblings with discordant cardiac phenotypes, a third isogenic mutant control iPSC line (DNAJC19tv) as well as two control lines (NC6M and NC47F) were directed towards the cardiovascular lineage upon response to extracellular specification cues. The monolayer cardiac differentiation approach was successfully adapted for all five iPSC lines and optimized towards ventricular subtype identity, higher population purities and enhanced maturity states to fulfill all DCMA-specific requirements prior to phenotypic investigations. To provide a solid basis for the study of DCMA, the combination of lactate-based metabolic enrichment, magnetic-activated cell sorting, mattress-based cultivation and prolonged cultivation time was performed in an approach-dependent manner. The application of the designated strategies was sufficient to ensure adult-like characteristics, which included at least 60-day-old iPSC-CMs. Therefore, the novel human DCMA platform was established to enable the study of the pathogenesis underlying DCMA with respect to structural, morphological and functional changes. The disease-associated protein, DNAJC19, is constituent of the TIM23 import machinery and can directly interact with PHB2, a component of the membrane bound hetero-oligomeric prohibitin ring complexes that are crucial for phospholipid and protein clustering in the IMM. DNAJC19 mutations were predicted to cause a loss of the DnaJ interaction domain, which was confirmed by loss of full-length DNAJC19 protein in all mutant cell lines. The subcellular investigation of DNAJC19 demonstrated a nuclear restriction in mutant iPSC-CMs. The loss of DNAJC19 co-localization with mitochondrial structures was accompanied by enhanced fragmentation, an overall reduction of mitochondrial mass and smaller cardiomyocytes. Ultrastructural analysis yielded decreased mitochondria sizes and abnormal cristae providing a link to defects in mitochondrial biogenesis and CL remodeling. Preliminary data on CL profiles revealed longer acyl chains and a more unsaturated acyl chain composition highlighting abnormities in the phospholipid maturation in DCMA. However, the assessment of mitochondrial function in iPSCs and dermal fibroblasts revealed an overall higher oxygen consumption that was even more enhanced in iPSC-CMs when comparing all three mutants to healthy controls. Excess oxygen consumption rates indicated a higher electron transport chain (ETC) activity to meet cellular ATP demands that probably result from proton leakage or the decoupling of the ETC complexes provoked by abnormal CL embedding in the IMM. Moreover, in particular iPSC-CMs presented increased extracellular acidification rates that indicated a shift towards the utilization of other substrates than fatty acids, such as glucose, pyruvate or glutamine. The examination of metabolic features via double radioactive tracer uptakes (18F-FDG, 125I-BMIPP) displayed significantly decreased fatty acid uptake in all mutants that was accompanied by increased glucose uptake in one patient cell line only, underlining a highly dynamic preference of substrates between mutant iPSC-CMs. To connect molecular changes directly to physiological processes, insights on calcium kinetics, contractility and arrhythmic potential were assessed and unraveled significantly increased beating frequencies, elevated diastolic calcium concentrations and a shared trend towards reduced cell shortenings in all mutant cell lines basally and upon isoproterenol stimulation. Extended speed of recovery was seen in all mutant iPSC-CMs but most striking in one patient-derived iPSC-CM model, that additionally showed significantly prolonged relaxation times. The investigations of calcium transient shapes pointed towards enhanced arrhythmic features in mutant cells comprised by both the occurrence of DADs/EADs and fibrillation-like events with discordant preferences. Taken together, new insights into a novel in vitro model system of DCMA were gained to study a genetically determined cardiomyopathy in a patient-specific manner upon incorporation of an isogenic mutant control. Based on our results, we suggest that loss of full-length DNAJC19 impedes PHB2-complex stabilization within the IMM, thus hindering PHB-rings from building IMM-specific phospholipid clusters. These clusters are essential to enable normal CL remodeling during cristae morphogenesis. Disturbed cristae and mitochondrial fragmentation were observed and refer to an essential role of DNAJC19 in mitochondrial morphogenesis and biogenesis. Alterations in mitochondrial morphology are generally linked to reduced ATP yields and aberrant reactive oxygen species production thereby having fundamental downstream effects on the cardiomyocytes` functionality. DCMA-associated cellular dysfunctions were in particular manifested in excess oxygen consumption, altered substrate utilization and abnormal calcium kinetics. The summarized data highlight the usage of human iPSC-derived CMs as a powerful tool to recapitulate DCMA-associated phenotypes that offers an unique potential to identify therapeutic strategies in order to reverse the pathological process and to pave the way towards clinical applications for a personalized therapy of DCMA in the future.},
  subject      = {Induzierte pluripotente Stammzelle},
  language  = {en}
}
@phdthesis{Yu2024,
  author    = {Yu, Yanying},
  title     = {Applied machine learning for the analysis of CRISPR-Cas systems},
  doi       = {10.25972/OPUS-32021},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-320219},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {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.},
  subject      = {Maschinelles Lernen},
  language  = {en}
}