Integrative bioinformatics applications for complex human disease contexts

This thesis presents new methods for the analysis of high-throughput data from modern sources in the context of complex human diseases, at the example of a bioinformatics analysis workflow. New measurement techniques improve the resolution with which cellular and molecular processes can be monitored. While RNA sequencing (RNA-seq) measures mRNA expression, single-cell RNA-seq (scRNA-seq) resolves this on a per-cell basis. Long-read sequencing is increasingly used in genomics. With imaging mass spectrometry (IMS) the protein level in tissues is measured spatially resolved. All these techniques induce specific challenges, which need to be addressed with new computational methods. Collecting knowledge with contextual annotations is important for integrative data analyses. Such knowledge is available through large literature repositories, from which information, such as miRNA-gene interactions, can be extracted using text mining methods. After aggregating this information in new databases, specific questions can be answered with traceable evidence. The combination of experimental data with these databases offers new possibilities for data integrative methods and for answering questions relevant for complex human diseases. Several data sources are made available, such as literature for text mining miRNA-gene interactions (Chapter 2), next- and third-generation sequencing data for genomics and transcriptomics (Chapters 4.1, 5), and IMS for spatially resolved proteomics (Chapter 4.4). For these data sources new methods for information extraction and pre-processing are developed. For instance, third-generation sequencing runs can be monitored and evaluated using the poreSTAT and sequ-into methods. The integrative (down-stream) analyses make use of these (heterogeneous) data sources. The cPred method (Chapter 4.2) for cell type prediction from scRNA-seq data was successfully applied in the context of the SARS-CoV-2 pandemic. The robust differential expression (DE) analysis pipeline RoDE (Chapter 6.1) contains a large set of methods for (differential) data analysis, reporting and visualization of RNA-seq data. Topics of accessibility of bioinformatics software are discussed along practical applications (Chapter 3). The developed miRNA-gene interaction database gives valuable insights into atherosclerosis-relevant processes and serves as regulatory network for the prediction of active miRNA regulators in RoDE (Chapter 6.1). The cPred predictions, RoDE results, scRNA-seq and IMS data are unified as input for the 3D-index Aorta3D (Chapter 6.2), which makes atherosclerosis related datasets browsable. Finally, the scRNA-seq analysis with subsequent cPred cell type prediction, and the robust analysis of bulk-RNA-seq datasets, led to novel insights into COVID-19. Taken all discussed methods together, the integrative analysis methods for complex human disease contexts have been improved at essential positions.Die Dissertation beschreibt Methoden zur Prozessierung von aktuellen Hochdurchsatzdaten, sowie Verfahren zu deren weiterer integrativen Analyse. Diese findet Anwendung vor allem im Kontext von komplexen menschlichen Krankheiten. Neue Messtechniken erlauben eine detailliertere Beobachtung biomedizinischer Prozesse. Mit RNA-Sequenzierung (RNA-seq) wird mRNA-Expression gemessen, mit Hilfe von moderner single-cell-RNA-seq (scRNA-seq) sogar für (sehr viele) einzelne Zellen. Long-Read-Sequenzierung wird zunehmend zur Sequenzierung ganzer Genome eingesetzt. Mittels bildgebender Massenspektrometrie (IMS) können Proteine in Geweben räumlich aufgelöst quantifiziert werden. Diese Techniken bringen spezifische Herausforderungen mit sich, die mit neuen bioinformatischen Methoden angegangen werden müssen. Für die integrative Datenanalyse ist auch die Gewinnung von geeignetem Kontextwissen wichtig. Wissenschaftliche Erkenntnisse werden in Artikeln veröffentlicht, die über große Literaturdatenbanken zugänglich sind. Mittels Textmining können daraus Informationen extrahiert werden, z.B. miRNA-Gen-Interaktionen, die in eigenen Datenbank aggregiert werden um spezifische Fragen mit nachvollziehbaren Belegen zu beantworten. In Kombination mit experimentellen Daten bieten sich so neue Möglichkeiten für integrative Methoden. Durch die Extraktion von Rohdaten und deren Vorprozessierung werden mehrere Datenquellen erschlossen, wie z.B. Literatur für Textmining von miRNA-Gen-Interaktionen (Kapitel 2), Long-Read- und RNA-seq-Daten für Genomics und Transcriptomics (Kapitel 4.2, 5) und IMS für Protein-Messungen (Kapitel 4.4). So dienen z.B. die poreSTAT und sequ-into Methoden der Vorprozessierung und Auswertung von Long-Read-Sequenzierungen. In der integrativen (down-stream) Analyse werden diese (heterogenen) Datenquellen verwendet. Für die Bestimmung von Zelltypen in scRNA-seq-Experimenten wurde die cPred-Methode (Kapitel 4.2) erfolgreich im Kontext der SARS-CoV-2-Pandemie eingesetzt. Auch die robuste Pipeline RoDE fand dort Anwendung, die viele Methoden zur (differentiellen) Datenanalyse, zum Reporting und zur Visualisierung bereitstellt (Kapitel 6.1). Themen der Benutzbarkeit von (bioinformatischer) Software werden an Hand von praktischen Anwendungen diskutiert (Kapitel 3). Die entwickelte miRNA-Gen-Interaktionsdatenbank gibt wertvolle Einblicke in Atherosklerose-relevante Prozesse und dient als regulatorisches Netzwerk für die Vorhersage von aktiven miRNA-Regulatoren in RoDE (Kapitel 6.1). Die cPred-Methode, RoDE-Ergebnisse, scRNA-seq- und IMS-Daten werden im 3D-Index Aorta3D (Kapitel 6.2) zusammengeführt, der relevante Datensätze durchsuchbar macht. Die diskutierten Methoden führen zu erheblichen Verbesserungen für die integrative Datenanalyse in komplexen menschlichen Krankheitskontexten

Development of a Modular Biosensor System for Rapid Pathogen Detection

Progress in the field of pathogen detection relies on at least one of the following three qualities: selectivity, speed, and cost-effectiveness. Here, we demonstrate a proof of concept for an optical biosensing system for the detection of the opportunistic human pathogen Pseudomonas aeruginosa while addressing the abovementioned traits through a modular design. The biosensor detects pathogen-specific quorum sensing molecules and generates a fluorescence signal via an intracellular amplifier. Using a tailored measurement device built from low-cost components, the image analysis software detected the presence of P. aeruginosa in 42 min of incubation. Due to its modular design, individual components can be optimized or modified to specifically detect a variety of different pathogens. This biosensor system represents a successful integration of synthetic biology with software and hardware engineering

Protective immune trajectories in early viral containment of non-pneumonic SARS-CoV-2 infection

The antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remains unclear. Here, we combine a multi-omics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype associated with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies

Modelling approach for anisotropic inter-ply slippage in finite element forming simulation of thermoplastic UD-tapes

Finite Element (FE) forming simulation offers the possibility of a detailed analysis of thermoforming processes by means of constitutive modelling of intra- and inter-ply deformation mechanisms, which makes manufacturing defects predictable. Inter-ply slippage is a deformation mechanism, which influences the forming behaviour and which is usually assumed to be isotropic in FE forming simulation so far. Thus, the relative (fibre) orientation between the slipping plies is neglected for modelling of frictional behaviour. Characterization results, however, reveal a dependency of frictional behaviour on the relative orientation of the slipping plies. In this work, an anisotropic model for inter-ply slippage is presented, which is based on an FE forming simulation approach implemented within several user subroutines of the commercially available FE solver Abaqus. This approach accounts for the relative orientation between the slipping plies for modelling frictional behaviour. For this purpose, relative orientation of the slipping plies is consecutively evaluated, since it changes during forming due to inter-ply slipping and intra-ply shearing. The presented approach is parametrized based on characterization results with and without relative orientation for a thermoplastic UD-tape (PA6-CF) and applied to forming simulation of a generic geometry. Forming simulation results reveal an influence of the consideration of relative fibre orientation on the simulation results. This influence, however, is small for the considered geometry

Tryptophan usage by Helicobacter pylori differs among strains

Abstract Because of its association with severe gastric pathologies, including gastric cancer, Helicobacter pylori has been subject of research for more than 30 years. Its capacity to adapt and survive in the human stomach can be attributed to its genetic flexibility. Its natural competence and its capacity to turn genes on and off allows H. pylori to adapt rapidly to the changing conditions of its host. Because of its genetic variability, it is difficult to establish the uniqueness of each strain obtained from a human host. The methods considered to-date to deliver the best result for differentiation of strains are Rapid Amplification of Polymorphic DNA (RAPD), Multilocus Sequence Typing (MLST) and Whole Genome Sequencing (WGS) analysis. While RAPD analysis is cost-effective, it requires a stable genome for its reliability. MLST and WGS are optimal for strain identification, however, they require analysis of data at the bioinformatics level. Using the StainFree method, which modifies tryptophan residues on proteins using 2, 2, 2, - trichloroethanol (TCE), we observed a strain specific pattern of tryptophan in 1D acrylamide gels. In order to establish the effectiveness of tryptophan fingerprinting for strain identification, we compared the graphic analysis of tryptophan-labelled bands in the gel images with MLST results. Based on this, we find that tryptophan banding patterns can be used as an alternative method for the differentiation of H. pylori strains. Furthermore, investigating the origin for these differences, we found that H. pylori strains alters the number and/or position of tryptophan present in several proteins at the genetic code level, with most exchanges taking place in membrane- and cation-binding proteins, which could be part of a novel response of H. pylori to host adaptation

Mural cell-derived chemokines provide a protective niche to safeguard vascular macrophages and limit chronic inflammation

Maladaptive, non-resolving inflammation contributes to chronic inflammatory diseases such as atherosclerosis. Because macrophages remove necrotic cells, defective macrophage programs can promote chronic inflammation with persistent tissue injury. Here, we investigated the mechanisms sustaining vascular macrophages. Intravital imaging revealed a spatiotemporal macrophage niche across vascular beds alongside mural cells (MCs)-pericytes and smooth muscle cells. Single-cell transcriptomics, co-culture, and genetic deletion experiments revealed MC-derived expression of the chemokines CCL2 and MIF, which actively preserved macrophage survival and their homeostatic functions. In atherosclerosis, this positioned macrophages in viable plaque areas, away from the necrotic core, and maintained a homeostatic macrophage phenotype. Disruption of this MC-macrophage unit via MC-specific deletion of these chemokines triggered detrimental macrophage relocalizing, exacerbated plaque necrosis, inflammation, and atheroprogression. In line, CCL2 inhibition at advanced stages of atherosclerosis showed detrimental effects. This work presents a MC-driven safeguard toward maintaining the homeostatic vascular macrophage niche