Periodic Reporting for period 1 - RNA-top (RNA topology of test samples and single extracellular vesicles: how cells package RNA messages to communicate (RNA-top))
Período documentado: 2023-02-01 hasta 2025-07-31
Cells in the body communicate by exchanging RNA that is associated with extracellular vesicles (EV-RNA). Therefore, analysis of EV-RNA may provide disease biomarkers. However, so far EV-RNA biomarkers are irreproducible. Since RNA is thought to be present within EVs, current procedures focus on isolating intra-vesicular EV-RNA. Recent evidence suggests, however, that EV-RNA may also be present on the EV surface. Funded by the Marie Skłodowska-Curie Actions programme, the goal of RNA-top is to investigate the precise location of EV-RNA (RNA topology) to improve EV-RNA biomarker development. This will improve the reproducibility and robustness of EV-RNA biomarkers, allowing for their clinical implementation. On the long term, reproducible and robust EV-RNA biomarkers in the clinic will improve the quality of life and survival of (cancer) patients. First, synthetic EV-mimicks (liposomes) with known RNA topology will be produced to set-up workflows to detect EV-RNA by super resolution microscopy and spectral flow cytometry. Workflows will then be extrapolated to study the RNA topology of cell-derived EVs.
The RNA-top project successfully established workflows to investigate the topology of RNA associated with extracellular vesicles (EVs). A liposome model system was developed during the secondment to serve as a controllable test sample for RNA topology studies, enabling method optimization and validation. Using this model, a flow cytometry-based method was implemented to detect RNA on the outer surface of vesicles, while a complementary workflow based on super-resolution microscopy was set up to study internal RNA localization. Although optimization of background fluorescence is ongoing, the approach is expected to yield reliable results. In addition, the project generated unforeseen methodological insights with relevance for the reproducibility of EV isolation and analysis, which will be reported in future publications. During the non-academic placement, automated quality-control software was developed to detect flow cytometry instrument issues, which has already been implemented in the host laboratory. Together, these outcomes provide new technical tools, model systems, and methodological advances to improve reproducibility in EV research and biomarker development.
The project generated several important outputs. A liposome-based model was developed as a controllable test system for RNA topology studies, enabling method validation and optimization. Workflows were established for detecting RNA on the vesicle surface (flow cytometry) and for probing internal RNA localization (super-resolution microscopy), with further optimization ongoing. Automated quality-control software for flow cytometry instruments was developed during the non-academic placement and has already been implemented in the host laboratory to improve data quality and efficiency. In addition, the project generated novel methodological insights with potential to improve the reproducibility of extracellular vesicle isolation and downstream biomarker studies, which will be reported in future publications.
The potential impacts of these results include advancing the scientific understanding of EV-RNA topology, improving reproducibility in biomarker research, and providing practical tools for quality assurance in flow cytometry. These outcomes are relevant for both academic researchers and translational applications in biomarker development. For further uptake and success, continued research and validation in patient-derived samples will be required, as well as wider dissemination of the workflows and software tools. Future steps may include the integration of these methods into standardization frameworks (e.g. MISEV, EV-TRACK, MIFlowCyt-EV, MIBloodEV) and engagement with the EV community to ensure adoption. At this stage, no IPR opportunities were pursued, but potential commercial applications have already been explored through a collaboration with an industrial partner on the development of filters to improve sample preparation by removing residual platelets.
The potential impacts of these results include advancing the scientific understanding of EV-RNA topology, improving reproducibility in biomarker research, and providing practical tools for quality assurance in flow cytometry. These outcomes are relevant for both academic researchers and translational applications in biomarker development. For further uptake and success, continued research and validation in patient-derived samples will be required, as well as wider dissemination of the workflows and software tools. Future steps may include the integration of these methods into standardization frameworks (e.g. MISEV, EV-TRACK, MIFlowCyt-EV, MIBloodEV) and engagement with the EV community to ensure adoption. At this stage, no IPR opportunities were pursued, but potential commercial applications have already been explored through a collaboration with an industrial partner on the development of filters to improve sample preparation by removing residual platelets.