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Understanding the causal relationship between genotype and phenotype is a major objective in biology. The main interest is in understanding trait architecture and identifying loci contributing to the respective traits. Genome-wide association mapping (GWAS) is one tool to elucidate these relationships and has been successfully used in many different species. However, most studies concentrate on marginal marker effects and ignore epistatic and gene-environment interactions. These interactions are problematic to account for, but are likely to make major contributions to many phenotypes that are not regulated by independent genetic effects, but by more sophisticated gene-regulatory networks. Further complication arises from the fact that these networks vary in different natural accessions. However, understanding the differences of gene regulatory networks and gene-gene interactions is crucial to conceive trait architecture and predict phenotypes.
The basic subject of this study – using data from the Arabidopsis 1001 Genomes Project – is the analysis of pre-mature stop codons. These have been incurred in nearly one-third of the ~ 30k genes. A gene-gene interaction network of the co-occurrence of stop codons has been built and the over and under representation of different pairs has been statistically analyzed. To further classify the significant over and under- represented gene-gene interactions in terms of molecular function of the encoded proteins, gene ontology terms (GO-SLIM) have been applied. Furthermore, co- expression analysis specifies gene clusters that co-occur over different genetic and phenotypic backgrounds. To link these patterns to evolutionary constrains, spatial location of the respective alleles have been analyzed as well. The latter shows clear patterns for certain gene pairs that indicate differential selection.
Interleukin 2 (IL-2) was the first cytokine applied for cancer treatment in human history. It has been approved as monotherapy for renal cell carcinoma and melanoma by the FDA and does mediate the regression of the tumors in patients. One of the possible mechanisms is that the administration of IL-2 led to T lymphocytes expansion, including CD4+ and CD8+ T cells. In addition, a recent study demonstrated that antigen-specific T cells could also be expanded through the induction of IL-2, which plays a crucial role in mediating tumor regression. However, despite the long-term and extensive use of IL-2 in the clinic, the ratio of patients who get a complete response was still low, and only about one-fifth of patients showed objective tumor regression. Therefore, the function of IL-2 in cancer treatment should continue to be optimized and investigated. A study by Franz O. Smith et al. has shown that the combination treatment of IL-2 and tumor-associated antigen vaccine has a strong trend to increased objective responses compared to patients with melanoma receiving IL-2 alone. Peptide vaccines are anti-cancer vaccines able to induce a powerful tumor antigenspecific immune response capable of eradicating the tumors. According to the type of antigens, peptide vaccines can be classified into two distinct categories: Tumor-associated antigens (TAA) vaccine and tumor-specific neoantigens (TSA) vaccine. Currently, Peptide vaccines are mainly investigated in phase I and phase II clinical trials of human cancer patients with various advanced cancers such as lung cancer, gastrointestinal tumors, and breast cancers. Vaccinia virus (VACV) is one of the safest viral vectors, which has been wildly used in cancer treatment and pathogen prevention. As an oncolytic vector, VACV can carry multiple large foreign genes, which enable the virus to introduce diagnostic and therapeutic agents without dramatically reducing the viral replication. Meanwhile, the recombinant vaccinia virus (rVACV) can be easily generated by homologous recombination. Here, we used the vaccinia virus as the therapeutic cancer vector, expressing mouse Interleukin 2 (IL-2) and tumor-associated antigens simultaneously to investigate the combined effect of anti-tumor immune response in the 4T1 mouse tumor model. As expected, the VACV driven mIL-2 expression remarkably increased both CD4+ and CD8+ populations in vivo, and the virus-expressed tumor-associated peptides successfully elicited theantigen-specific T cell response to inhibit the growth of tumors. Furthermore, the experiments with tumor-bearing animals showed that the mIL-2 plus tumor antigens expressing VACV vector gave a better anti-cancer response than the mIL-2 alone expressing vector. The combinations did significantly more inhibit tumor growth than mIL-2 treatment alone. Moreover, the results confirmed our previous unpublished data that the mIL-2 expression driven by synthetic early/late promoter in the Lister strain VACV could enhance the tumor regression in the 4T1 mouse model.
Antikörper, die gegen eine klinisch relevante Gruppe von Rezeptoren innerhalb der Tumornekrosefaktor-Rezeptor-Superfamilie (TNFRSF) gerichtet sind, darunter CD40 und CD95 (Fas/Apo-1), benötigen ebenfalls eine Bindung an Fc-Gamma-Rezeptoren (FcγRs), um eine starke agonistische Wirkung zu entfalten. Diese FcγR-Abhängigkeit beruht weitgehend auf der bloßen zellulären Verankerung durch die Fc-Domäne des Antikörpers und benötigt dabei kein FcγR-Signalling. Ziel dieser Doktorarbeit war es, das agonistische Potenzial von αCD40- und αCD95-Antikörpern unabhängig von der Bindung an FcγRs durch die Verankerung an Myelomzellen zu entfalten. Zu diesem Zweck wurden verschiedene Antikörpervarianten (IgG1, IgG1-N297A, Fab2) gegen die TNFRSF-Mitglieder CD40 und CD95 genetisch mit einem einzelkettig kodierten B-Zell-aktivierenden Faktor (scBaff) Trimer als C-terminale myelom-spezifische Verankerungsdomäne fusioniert, welche die Fc-Domäne-vermittelte FcγR-Bindung ersetzt. Diese bispezifischen Antikörper-scBaff-Fusionsproteine wurden in Bindungsstudien und funktionellen Assays mit Tumorzelllinien untersucht, die einen oder mehrere der drei Baff-Rezeptoren exprimieren: BaffR, Transmembran-Aktivator und CAML-Interaktor (TACI) und B-Zell-Reifungsantigen (BCMA). Zelluläre Bindungsstudien zeigten, dass die Bindungseigenschaften der verschiedenen Domänen innerhalb der Antikörper-scBaff-Fusionen gegenüber der Zielantigene vollständig intakt blieben. In Ko-Kulturversuchen von CD40- und CD95-responsiven Zellen mit BaffR-, BCMA- oder TACI-exprimierenden Verankerungszellen zeigten die Antikörper-Fusionsproteine einen starken Agonismus, während in Ko-Kulturen mit Zellen ohne Expression von Baff-interagierenden Rezeptoren nur eine geringe Rezeptorstimulation beobachtet wurde. Die hier vorgestellten αCD40- und αCD95-Antikörper-scBaff-Fusionsproteine zeigen also Myelom-spezifische Aktivität und versprechen im Vergleich zu herkömmlichen CD40- und CD95-Agonisten geringere systemische Nebenwirkungen.
Das Nebennierenrindenkarzinom (ACC) ist eine sehr seltene maligne Erkrankung, die mit einer infausten Prognose vergesellschaftet ist. In Zeiten apparativ geprägter Medizin treten suspekte Befunde der Nebenniere gehäufter auf als je zuvor. Diese Nebennierenraumforderungen, die zumeist bei Bildgebungen auffallen, die aus anderen Gründen indiziert waren, werden Nebenniereninzidentalome genannt und sind meist benigne Befunde. Dennoch wird es angesichts dieser steigenden Zahl an Inzidentalomen immer wichtiger, die Entität der gefundenen Raumforderung schnell zu sichern, um die entsprechende Therapie einleiten zu können. Somit sollen das Zeitfenster bis zur Krebstherapie verkleinert und gleichsam unnötige chirurgische Eingriffe bei Patient*innen mit benignen Nebennierentumoren vermieden werden. Um die diagnostischen Schritte weiter zu verbessern, wurde in der vorliegenden Arbeit eine bioinformatische Regressionsanalyse an Steroidhormonkonzentrationen von ACC-Patient*innen und Kontrollen durchgeführt und der diagnostische Wert der berechneten Steroidsignaturen untersucht. Dabei zeigte sich im geschlechtsspezifischen Modell jeweils eine 6-Steroid-Signatur mit bester Trennschärfe zwischen benignen und malignen NN-Befunden. So konnte mit der 6-Steroid-Signatur in der männlichen Patientengruppe mit einer Sensitivität von 80% und Spezifität von 97%, in der weiblichen Patientinnengruppe mit einer Sensitivität von 78% und Spezifität von 97% die Diagnose richtig zugewiesen werden. Im Rahmen der targeted Metabolomics Untersuchung konnten Tumor-assoziierte Stoffwechselalterationen aufgezeigt werden. Eine Plasma-Metabolit-Signatur zur Differenzierung von ACCs und Nebennierenadenomen, welche die gängige Diagnostik bei der Abklärung von unklaren Nebennierentumoren erleichtern könnte, erscheint jedoch angesichts der großen Anzahl an zu bestimmenden Metaboliten - auch unter ökonomischen Gesichtspunkten - zu diesem Zeitpunkt noch nicht mit der Routine-Patient*innenversorgung vereinbar.
Transcription describes the process of converting the information contained in DNA into RNA. Although, tremendous progress has been made in recent decades to uncover this complex mechanism, it is still not fully understood. Given the advances and reduction in cost of high-throughput sequencing experiments, more and more data have been generated to help elucidating this complex process. Importantly, these sequencing experiments produce massive amounts of data that are incomprehensible in their raw form for humans. Further, sequencing techniques are not always 100% accurate and are subject to a certain degree of variability and, in special cases, they might introduce technical artifacts. Thus, computational and statistical methods are indispensable to uncover the information buried in these datasets.
In this thesis, I worked with multiple high throughput datasets from herpes simplex virus 1 (HSV-1) and human cytomegalovirus (HCMV) infections. During the last decade, it has became clear that a gene might not have a single, but multiple sites at which transcription initiates. These multiple transcription start sites (TiSS) demonstrated to have regulatory effects on the gene itself depending on which TiSS is used. Specialized experimental approaches were developed to help identify TiSS (TiSS-profiling). In order to facilitate the identification of all potential TiSS that are used for cell type- and condition-specific transcription, I developed the tool iTiSS. By using a new general enrichment-based approach to predict TiSS, iTiSS proved to be applicable in integrated studies and made it less prone to false positives compared to other TiSS-calling tools. Another improvement in recent years was made in metabolic labeling experiments such as SLAM-seq. Here, they removed the time consuming and laborious step of physically separating new from old RNA in the samples. This was achieved by inducing specific nucleotide conversions in newly synthesized RNA that are later visible in the data. Consequently, the separation of new and old RNA is now done computationally and, hence, tools are needed that accurately quantify these fold-changes. My second tool that I developed, called GRAND-SLAM proved to be capable to accomplish this task and outperform competing programs. As both of my tools, iTiSS and GRAND-SLAM are not specifically tailored to my own goals, but could also facilitate the research of other groups in this field, I made them publicly available on GitHub.
I applied my tools to datasets generated in our lab as well as to publicly available data sets from HSV-1 and HCMV, respectively. For HSV-1, I was able to predict and validate TiSS with nucleotide precision using iTiSS. This has lead to the most comprehensive annotation for HSV-1 to date, which now serves as the fundamental basis of any future transcriptomic research on HSV-1. By combining both my tools, I was further able to uncover parts of the highly complex gene kinetics in HCMV and to resolve the limitations caused by the densely packed genome of HCMV.
With the ever-increasing advances in sequencing techniques and their decrease in cost, the amounts of data produced will continue to rise massively in the future. Additionally, more and more specialized omics approaches are appearing, calling for new tools to leverage their full information potential. Consequently, it has become apparent that specialized computational tools such as iTiSS and GRAND-SLAM are needed and will become an essential and indispensable part of the analysis.
Clostridioides difficile is a bacterial species well known for its ability to cause C. difficile
infection (also known as CDI). The investigation of the role of this species in the human
gut has been so far dominated by a disease-centred perspective, focused on studying
C. difficile in relation to its associated disease.
In this context, the first aim of this thesis was to combine publicly available
metagenomic data to analyse the microbial composition of stool samples from patients
diagnosed with CDI, with a particular focus on identifying a CDI-specific microbial
signature.
However, similarly to many other bacterial species inhabiting the human gut, C.
difficile association with disease is not valid in absolute terms, as C. difficile can be
found also among healthy subjects. Further aims of this thesis were to 1) identify
potential C. difficile reservoirs by screening a wide range of habitats, hosts, body sites
and age groups, and characterize the biotic context associated with C. difficile
presence, and 2) investigate C. difficile within-species diversity and its toxigenic
potential across different age groups.
The first part of the thesis starts with the description of the concepts and
definitions used to identify bacterial species and within-species diversity, and then
proceeds to provide an overview of the bacterial species at the centre of my
investigation, C. difficile. The first Chapter includes a detailed description of the
discovery, biology and physiology of this clinically relevant species, followed by an
overview of the diagnostic protocols used in the clinical setting to diagnose CDI.
The second part of the thesis describes the methodology used to investigate
the questions mentioned above, while the third part presents the results of such
investigative effort. I first show that C. difficile could be found in only a fraction of the
CDI samples and that simultaneous colonization of multiple enteropathogenic species
able to cause CDI-like clinical manifestations is more common than previously
thought, raising concerns about CDI overdiagnosis. I then show that the CDIassociated
gut microbiome is characterized by a specific microbial signature,
distinguishable from the community composition associated with non-CDI diarrhea.
Beyond the nosocomial and CDI context, I show that while rarely found in adults, C.
difficile is a common member of the infant gut microbiome, where its presence is
associated with multiple indicators typical of a desirable healthy microbiome
development.
In addition, I describe C. difficile extensive carriage among asymptomatic
subjects, of all age groups and a potentially novel clade of C. difficile identified
exclusively among infants.
Finally, I discuss the limitations, challenges and future perspectives of my
investigation.