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Since the advent of high-throughput sequencing technologies in the mid-2010s, RNA se-
quencing (RNA-seq) has been established as the method of choice for studying gene
expression. In comparison to microarray-based methods, which have mainly been used to
study gene expression before the rise of RNA-seq, RNA-seq is able to profile the entire
transcriptome of an organism without the need to predefine genes of interest. Today,
a wide variety of RNA-seq methods and protocols exist, including dual RNA sequenc-
ing (dual RNA-seq) and multi RNA sequencing (multi RNA-seq). Dual RNA-seq and
multi RNA-seq simultaneously investigate the transcriptomes of two or more species, re-
spectively. Therefore, the total RNA of all interacting species is sequenced together and
only separated in silico. Compared to conventional RNA-seq, which can only investi-
gate one species at a time, dual RNA-seq and multi RNA-seq analyses can connect the
transcriptome changes of the species being investigated and thus give a clearer picture of
the interspecies interactions. Dual RNA-seq and multi RNA-seq have been applied to a
variety of host-pathogen, mutualistic and commensal interaction systems.
We applied dual RNA-seq to a host-pathogen system of human mast cells and Staphylo-
coccus aureus (S. aureus). S. aureus, a commensal gram-positive bacterium, can become
an opportunistic pathogen and infect skin lesions of atopic dermatitis (AD) patients.
Among the first immune cells S. aureus encounters are mast cells, which have previously
been shown to be able to kill the bacteria by discharging antimicrobial products and re-
leasing extracellular traps made of protein and deoxyribonucleic acid (DNA). However,
S. aureus is known to evade the host’s immune response by internalizing within mast
cells. Our dual RNA-seq analysis of different infection settings revealed that mast cells
and S. aureus need physical contact to influence each other’s gene expression. We could
show that S. aureus cells internalizing within mast cells undergo profound transcriptome
changes to adjust their metabolism to survive in the intracellular niche. On the host side,
we found out that infected mast cells elicit a type-I interferon (IFN-I) response in an
autocrine manner and in a paracrine manner to non-infected bystander-cells. Our study
provides the first evidence that mast cells are capable to produce IFN-I upon infection
with a bacterial pathogen.
Significant advances in fluorescence imaging techniques enable life scientists today to gain insights into biological systems at an unprecedented scale. The interpretation of image features in such bioimage datasets and their subsequent quantitative analysis is referred to as bioimage analysis. A substantial proportion of bioimage analyses is still performed manually by a human expert - a tedious process that is long known to be subjective. Particularly in tasks that require the annotation of image features with a low signal-to-noise ratio, like in fluorescence images of tissue samples, the inter-rater agreement drops. However, like any other scientific analysis, also bioimage analysis has to meet the general quality criteria of quantitative research, which are objectivity, reliability, and validity. Thus, the automation of bioimage analysis with computer-aided approaches is highly desirable. Albeit conventional hard-coded algorithms are fully unbiased, a human user has to set its respective feature extraction parameters. Thus, also these approaches can be considered subjective.
Recently, deep learning (DL) has enabled impressive advances in computer vision research. The predominant difference between DL and conventional algorithms is the capability of DL models to learn the respective task on base of an annotated training dataset, instead of following user-defined rules for feature extraction. This thesis hypothesized that DL can be used to increase the objectivity, reliability, and validity of bioimage analyses, thus going beyond mere automation. However, in absence of ground truth annotations, DL models have to be trained on manual and thus subjective annotations, which could cause the model to incorporate such a bias. Moreover, model training is stochastic and even training on the same data could result in models with divergent outputs. Consequently, both the training on subjective annotations and the model-to-model variability could impair the quality of DL-based bioimage analyses. This thesis systematically assessed the impacts of these two limitations experimentally by analyzing fluorescence signals of a protein called cFOS in mouse brain sections. Since the abundance of cFOS correlates with mouse behavior, behavioral analyses could be used for cross-validation of the bioimage analysis results. Furthermore, this thesis showed that pooling the input of multiple human experts during model training and integration of multiple trained models in a model ensemble can mitigate the impact of these limitations. In summary, the present study establishes guidelines for how DL can be used to increase the general quality of bioimage analyses.
N-MYC is a member of the human MYC proto-oncogene family, which comprises three transcription factors (C-, N- and L-MYC) that function in multiple biological processes. Deregulated expression of MYC proteins is linked to tumour initiation, maintenance and progression. For example, a large fraction of neuroblastoma displays high N-MYC levels due to an amplification of the N-MYC encoding gene. MYCN-amplified neuroblastoma depend on high N-MYC protein levels, which are maintained by Aurora-A kinase. Aurora-A interaction with N-MYC interferes with degradation of N-MYC via the E3 ubiquitin ligase SCFFBXW7. However, the underlying mechanism of Aurora-A-mediated stabilisation of N-MYC remains to be elucidated.
To identify novel N-MYC interacting proteins, which could be involved in N-MYC stabilisation by Aurora-A, a proteomic analysis of purified N-MYC protein complexes was conducted. Since two alanine mutations in MBI of N-MYC, T58A and S62A (N-MYC mut), disable Aurora-A-mediated stabilisation of N-MYC, N-MYC protein complexes from cells expressing either N-MYC wt or mut were analysed. Proteomic analysis revealed that N-MYC interacts with two deubiquitinating enzymes, USP7 and USP11, which catalyse the removal of ubiquitin chains from target proteins, preventing recognition by the proteasome and subsequent degradation. Although N-MYC interaction with USP7 and USP11 was confirmed in subsequent immunoprecipitation experiments, neither USP7, nor USP11 was shown to be involved in the regulation of N-MYC stability. Besides USP7/11, proteomic analyses identified numerous additional N-MYC interacting proteins that were not described to interact with MYC transcription factors previously. Interestingly, many of the identified N-MYC interaction partners displayed a preference for the interaction with N-MYC wt, suggesting a MBI-dependent interaction. Among these were several proteins, which are involved in three-dimensional organisation of chromatin domains and transcriptional elongation by POL II. Not only the interaction of N-MYC with proteins functioning in elongation, such as the DSIF component SPT5 and the PAF1C components CDC73 and CTR9, was validated in immunoprecipitation experiments, but also with the POL III transcription factor TFIIIC and topoisomerases TOP2A/B. ChIP-sequencing analysis of N-MYC and TFIIIC subunit 5 (TFIIIC5) revealed a large number of joint binding sites in POL II promoters and intergenic regions, which are characterised by the presence of a specific motif that is highly similar to the CTCF motif. Additionally, N-MYC was shown to interact with the ring-shaped cohesin complex that is known to bind to CTCF motifs and to assist the insulator protein CTCF. Importantly, individual ChIP experiments demonstrated that N-MYC, TFIIIC5 and cohesin subunit RAD21 occupy joint binding sites comprising a CTCF motif.
Collectively, the results indicate that N-MYC functions in two biological processes that have not been linked to MYC biology previously. Furthermore, the identification of joint binding sites of N-MYC, TFIIIC and cohesin and the confirmation of their interaction with each other suggests a novel function of MYC transcription factors in three-dimensional organisation of chromatin.
Platelet activation and adhesion results in thrombus formation that is essential for normal hemostasis, but can also cause irreversible vessel occlusion leading to myocardial infarction or stroke. The C-type lectin-like receptor 2 (CLEC-2) was recently identified to be expressed on the platelet surface, however, a role for this receptor in hemostasis and thrombosis had not been demonstrated. In the current study, the involvement of CLEC-2 in platelet function and thrombus formation was investigated using mice as a model system. In the first part of the thesis, it was found that treatment of mice with a newly generated monoclonal antibody against murine CLEC-2 (INU1) led to the complete and highly specific loss of the receptor in circulating platelets (a process termed “immunodepletion”). CLEC-2-deficient platelets were completely unresponsive to the CLEC-2-specific agonist rhodocytin, whereas activation induced by all other tested agonists was unaltered. This selective defect translated into severely decreased platelet aggregate formation under flow ex vivo; and in vivo thrombosis models revealed impaired stabilization of formed thrombi with enhanced embolization. Consequently, CLEC-2 deficiency profoundly protected mice from occlusive arterial thrombus formation. Furthermore, variable bleeding times in INU1-treated mice indicated a moderate hemostatic defect. This reveals for the first time that CLEC-2 significantly contributes to thrombus stability in vitro and in vivo and plays a crucial role in hemostasis and arterial thrombosis. Thus, CLEC-2 represents a potential novel anti-thrombotic target that can be functionally inactivated in vivo. This in vivo down-regulation of platelet surface receptors might be a promising approach for future anti-thrombotic therapy. The second part of the work investigated the effect of double-immunodepletion of the immunoreceptor tyrosine-based activation motif (ITAM)- and hemITAM-coupled receptors, platelet glycoprotein (GP) VI and CLEC-2, on hemostasis and thrombosis using a combination of the GPVI- and CLEC-2-specific antibodies, JAQ1 and INU1, respectively. Isolated targeting of either GPVI or CLEC-2 in vivo did not affect expression or function of the respective other receptor. However, simultaneous treatment with both antibodies resulted in the sustained loss of GPVI and CLEC-2 signaling in platelets, while leaving other activation pathways intact. In contrast to single deficiency of either receptor, GPVI/CLEC-2 double-deficient mice displayed a dramatic hemostatic defect. Furthermore, this treatment resulted in profound impairment of arterial thrombus formation that far exceeded the effects seen in single-depleted animals. Importantly, similar results were obtained in Gp6-/- mice that were depleted of CLEC-2 by INU1-treatment, demonstrating that this severe bleeding phenotype was not caused by secondary effects of combined antibody treatment. These data suggest that GPVI and CLEC-2 can be independently or simultaneously down-regulated in platelets in vivo and reveal an unexpected functional redundancy of the two receptors in hemostasis and thrombosis. Since GPVI and CLEC-2 have intensively been discussed as potential anti-thrombotic targets, these results may have important implications for the development of novel, yet save anti-GPVI or anti-CLEC-2-based therapies.
Die Funktionalität β1- und β2-adrenerger Rezeptoren wird durch Polymorphismen in ihrer kodierenden Region moduliert. Wir haben uns die Technik des Fluoreszenz-Resonanz- Energie-Transfers (FRET) zu Nutze gemacht, um den Einfluss der am häufigsten vorkommenden Polymorphismen (Ser49Gly und Gly389Arg im β1AR, Arg16Gly und Gln27Glu im β2AR) auf die Rezeptorkonformation nach Aktivierung zu untersuchen. Dafür wurden FRET-Sensoren für die beiden βAR-Subtypen mit einem gelb-fluoreszierenden Protein (YFP) sowie einem cyan-fluoreszierenden Protein (CFP oder Cerulean) in der dritten intrazellulären Schleife bzw. am C-Terminus verwendet. Nach Stimulierung der βARSensoren konnte die Aktivierung der polymorphen Rezeptorvarianten in lebenden Zellen in Echtzeit untersucht werden. Dabei behielten die FRET-Sensoren sowohl die Bindungsaffinitäten der nativen Rezeptoren als auch eine intakte Funktionalität hinsichtlich der Bildung von sekundären Botenstoffen. Der Vergleich der Aktivierungskinetiken der verschieden polymorphen Varianten des β1AR und β2AR ergab keine signifikanten Unterschiede nach einer einmaligen Stimulation. Es zeigte sich jedoch, dass Rezeptorpolymorphismen die Aktivierungskinetik vorstimulierter βAR erheblich beeinflussen. So konnten wir im Vergleich zur ersten Aktivierung eine schnellere Aktivierung der Gly16-Varianten des β2AR sowie des Gly49Arg389-β1AR feststellen, während die Arg16-β2AR-Variante und der Ser49Gly389-β1AR dagegen bei einer wiederholten Stimulation langsamer aktiviert wurden. Diese Ergebnisse lassen auf ein "Rezeptorgedächtnis" schließen, das spezifisch für bestimmte polymorphe Rezeptorvarianten ist und eine βAR-Subtyp-spezische Ausprägung zeigt. Die Ausbildung der unterschiedlichen Aktivierungskinetiken hing von der Interaktion des Rezeptors mit löslichen intrazellulären Faktoren ab und bedurfte einer Phosphorylierung intrazellulärer Serin- und Threonin-Reste durch G-Protein-gekoppelte Rezeptorkinasen. Die Interaktion mit löslichen intrazellulären Faktoren scheint für den β1AR weniger stark ausgeprägt zu sein als für den β2AR. Die cAMP-Produktion war für die schneller werdenden, “hyperfunktionellen” Gly16-β2ARVarianten signifikant um mehr als 50% höher im Vergleich zur “hypofunktionellen” Arg16- Variante. Die unterschiedliche Funktionalität spiegelte sich im Therapieausgang bei Tokoysepatientinnen wider, dessen Erfolg mit dem Arg16Gly Polymorphismus verknüpft war. Die Daten implizieren eine intrinsische, polymorphismusabhängige Eigenschaft der βAR, die die Aktivierungskinetik der Rezeptoren bei wiederholten Stimulationen determiniert. Diese könnte auch für die zwischen Individuen variierende Ansprechbarkeit auf β-Agonisten und β-Blocker mitverantwortlich sein.