Periodic Reporting for period 3 - EPIC-XS (European Proteomics Infrastructure Consortium providing Access)
Periodo di rendicontazione: 2022-01-01 al 2023-06-30
EPIC-XS was the ultimate proteomics project allowing user in Europe access for research projects of a translational nature across all areas of proteomics., EPIC-XScombined developing novel technologies, with providing access t to large numbers of non-expert users from throughout Europe.
Through the project lifetime EPIC-XS provided proteomics technologies to no less then 240 transnational access projects, originating from more than 221 different users. Results from the EPIC-XS transnational access and joint research activities have results in more than 250 scientific, peer-reviewed, open-access publications in well-respected journals.
Since the start of the project, EPIC-XS provided access for 240 projects involving 221 users, of which 102 female and 119 male users. EPIC-XS users were mostly academic, but the consortium also worked with non-academic parties, mainly to be inform them on the possibilities of the newly developed high-end proteomics methodologies, but also to participate in EPIC-XS TNA opportunities. Hands-on training helped researchers to develop best practice workflows and aid the dissemination of proteomics data into publicly available databases, thereby broadening the expertise of experienced scientists and those new to the field of proteomics. Standard operating procedures and new protocols were rapidly exchanged in between the access sites, to broaden and strengthen the services that can be offered throughout Europe. The transnational access was provided to institutions in 33 different countries and in total this access already has resulted in 44 published articles from the user projects alone.
Joint Research Activities
EPIC-XS featured four Joint Research Activities (JRAs) that were interactive efforts between the EPIC-XS partners and which have resulted in groundbreaking new proteomics technologies.
Proteomics research is evolving at an astonishing rate. Tremendous steps have been made in terms of sensitivity, dynamic range, comprehensiveness, robustness, and costs (in time and money). Thes steps have enabled proteomics to impact both fundamental as well as translational research, benefitting mankind. Proteomics can now be used to investigate the proteome of single cells discovering new cells and cell responses, analyse hundreds to thousands of clinical samples for diagnostic protein markers of health and disease, chart the spatio-temporal behaviour of proteins in cells and tissue, and how they all functionally interact with each other. The Joint Research Activities of EPIC-XS have pioneered many of these proteomics technologies and contributed to the translation of these technologies to the clinic and the wider life science research communities. Researchers in EPIC-XS have been very important in making these advances in proteomics methods. A new horizon in proteomics comes from more protein-centric approaches (top-down), complementing the by now more routine peptide-centric approaches (bottom-up) . Protein-centric approaches are important for the detection of “proteoforms”, a term for all the forms proteins, linked to one gene, can have in our cells or subcellular organelles or tissue. Although our DNA only contains about 20,000 genes, recent work on proteoform by among others EPIC-XS partners, have revealed that the number of proteoforms may easily exceed several millions. To understand the true regulation in molecular biology, we need tools to dissect the functional roles, not only of selected genes, but rather for each proteoform, visualizing its structure and function, localization and interactions. This is a very ambitious goal, but essential to make impactful contributions to our understanding of biology.
Several EPIC-XS consortium partners have implemented structural proteomics approaches in their work, deriving structural information on proteins that can be directly related to cryoEM, microscopy and computational data. Obtained (cryoEM) or predicted (AI using Alphafold) structures are validated by emerging proteomics technologies, such as limited proteolysis (LipMS), cross-linking MS (XL-MS) and hydrogen-deuterium exchange MS, and these methods are now frequently exploited through biomolecular, biotechnological, and biomedical applications aiding to the development, for instance, of new drugs.
The equipment used to get proteomics-based information is expensive and capacity is very often a limiting factor as well as the expertise to analyse the data. AI-technologies have also entered the field of proteomics and contributed already immensely to improve the analysis and biological interpretation of the huge amount of data generated. To fully benefit from the rapidly expanding toolbox of proteomics research tools biomedical and biological researchers require access and support.