Organoids are microscopically small patient-derived 3D organs that can be cultivated in the laboratory over months mimicking human organs and their functions in vitro. These mini-organs have a human genetic background, maintain disease traits in vitro and are currently available for almost every human organ. Due to these advantages, organoid research and its commercial applications are rapidly evolving and increasingly used. Given the high variability of these complex 3D structures, classical cell culture-based image quantification tools techniques do not accurately capture organoids in microscope images. This has resulted in much image quantification at our laboratory - like in many others - being performed using manual time-consuming tools with a high researcher variability. In sum, there is a global challenge to in a standardized manner quantify organoid experiments. We propose the first Software as a Service (SaaS) toolbox explicitly tailored to organoid imaging, building upon powerful AI-based algorithms for cutting-edge image quantification and independent of the underlying microscope and culture system hardware. The SaaS seamlessly fits in the analysis workflow by offering a user-friendly approach to upload brightfield and immunofluorescence microscope images and videos of organoid cultures, which - at the core of our product - are automatically quantified by AI-models generating a range of organoid metrics. Overall, the provided automation drastically reduces analysis time, promotes accurate phenotypical organoid analyses and ensures standardization of results between different researchers, culture conditions, and imaging hardware. Integrated in an easy-to-use web app, the SaaS tool is of great interest and essential for researchers working in the emerging field of organoids, as shown by the high utilization in our laboratory and the high interest from external partner institutions.

The human immune system has evolved sophisticated mechanisms to recognize and eliminate infected, stressed or cancer cells. Presentation of antigens by HLA-I enables the identification of diseased cells by antigen-specific T cells, while changes in HLA-I expression levels are sensed by NK cells. Many human NK cell receptors bind HLA-I; but whether and how NK cells might interact with HLA-II remained unknown. We recently discovered that a subset of commonly expressed HLA-DP molecules serve as ligands for the natural cytotoxicity receptor NKp44, implicating HLA-II in the regulation of NK cells. Remarkably, the strength of NKp44-binding to HLA-DP was dependent on both the HLA-DP allotype and the HLA-DP-presented peptide. The ability of NK cell receptors to bind HLA-II molecules represents a paradigm shift from previous models describing NK cell function largely in the context of HLA-I, and suggests a novel regulatory framework in which NK cells interact directly with HLA-II-expressing cells, including APCs and activated stroma cells. HLA-DP allotypes have been associated with the incidence and outcome of several infectious and inflammatory diseases, and the newly identified interactions between HLA-DP and NKp44 now provide a molecular mechanism implicating NK cells in the pathogenesis of these diseases. As NKp44 and HLA-DP are not expressed in mice, but have evolved recently in primates and humans, studies investigating the underlying mechanisms have to be performed in humans. The applicant proposes an innovative and integrated research program, combining functional immunological and virological approaches with recently developed human organoid systems and proteomics technologies to investigate the impact of interactions between NKp44 and HLA-DP for human diseases, with the ultimate goal to harness NK cells for immunotherapeutic interventions against infections and inflammatory diseases.

The main question to be addressed by SPOCk’S MS is how protein complex conformation adapts to local changes, such as processing of polyproteins, protein phosphorylation or conversion of substrates. While labelling strategies combined with mass spectrometry (MS), such as hydrogen deuterium exchange and hydroxyl footprinting, are very versatile in studying protein structure, these techniques are employed on bulk samples averaging over all species present. SPOCk’S MS will remedy these by studying the footprinting and therefore exposed surface area on conformation and mass selected species. Labelling still happens in solution avoiding gas phase associated artefacts. The labelling positions are then read out using newly developed top-down MS technology. Ultra-violet and free-electron lasers will be employed to fragment the protein complexes in the gas phase. In order to achieve the highest possible sequence and thus structural coverage, lasers will be complemented by additional dissociation and separation stages to allow MS^N. SPOCk’S MS will allow sampling conformational space of proteins and protein complexes and especially report about the transient nature of protein interfaces. Constraints derived in MS will be fed into a dedicated software pipeline to derive atomistic models. SPOCk’S MS will be used to study intracellular viral protein complexes, especially coronaviral replication/transcription complexes, which are highly flexible and often resist crystallisation and are barely accessible by conventional structural biology techniques. Objectives: - Integrate labelling with complex species selective native MS for time-resolved structural studies - Combine fragmentation techniques to maximise information content from MS - Develop software suite to analyse data and model protein complex structures based on MS constraints - Apply SPOCk’S MS to protein complexes of human pathogenic viruses