Next-generation of multi-omics research: going to the single cell

Project Details


Over the past decade, high-throughput technologies have revolutionized the analysis of biological systems including also medical diagnostics. The possibility to gather large datasets enables researchers nowadays to ask biological questions in a global context. The impact of the loss of a single gene's function can now be monitored on the level of the transcriptome, the proteome, and the metabolome simultaneously. While these investigations on the individual omics-levels have revealed key biological mechanisms and identified new pathways, our understanding as to how the layers interact is still limited and the multi-omics integration represents the maybe most urgent challenge in systems biomedicine.
A major issue in omics-analyses and particularly for multi-omics integration is the immanent cellular heterogeneity. Bulk analyses of several millions of cells as typically done in omics-approaches smear out potentially essential signatures of causative regulatory mechanisms and prevent the development of an integrative perspective. Therefore, major efforts have been recently undertaken to increase the resolution for many of these omics-technologies from the population level to single-cell resolution and have revealed a surprisingly large cellular heterogeneity of many multicellular systems including organ and whole animal characterization but also in vitro analyses. With the lead of single-cell transcriptomics, other technologies have started to go in the same direction; namely, single-cell proteomics and single-cell metabolomics are new players emerging. At the same time, new sequencing methods are emerging, which will allow to detect smaller amounts (single molecule protein and DNA sequencing) or provide a spatial component to the analysis (subcellular RiboSeq).
The single-cell resolution comes with additional challenges for data analysis and integration where in particular the small processed sample size leads to noisy data which has to be addressed for the interpretation. New cutting-edge approaches in bioinformatic analysis are targeting this issue from different angles including imputation and theory of stochastic processes in an adaptive manner to acknowledge the experimental advancements and specificity. While these methodologies are now rather well established for the individual single-cell or low-volume omics level, integrative approaches are just emerging.
Gunnar Dittmar, Alexander Skupin and Paul Wilmes teamed up to create a lecture series with the purpose of bringing key specialists in their fields to Luxembourg to raise the awareness of these new emerging technologies and at the same time provide the opportunity to forge new collaborations with the technology leaders in the world. Thereby the lecture series will cover on the one hand the recent development in the cutting-edge experimental technologies including single-cell sequencing, metabolomics and low volume proteomics and on the other hand the corresponding computational analysis approaches. The lectures by world-wide leading experts in the individual domains will give comprehensive overviews of the current possibilities and challenges in the respective fields and provide an up-to-date briefing. This will ensure a high participation to the lecture series because these technologies are used across the different biomedical disciplines and trigger potential new collaboration with leading laboratories. Furthermore, the lecture series will also facilitate the discussions on the still open question on omics-integration at single cell resolution already on-going between the different scientific stakeholders in Luxembourg including the Luxembourg Institute of Health, the University of Luxembourg where the Luxembourg Centre for Systems Biomedicine is already heavily involved in single cell analysis as well as the Luxembourg Institute for Science and Technology.
Effective start/end date1/09/2131/08/22


  • FNR - Fonds National de la Recherche: €20,000.00


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