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PROTEOMICS4D Report Summary

Project ID: 670821
Funded under: H2020-EU.1.1.

Periodic Reporting for period 1 - PROTEOMICS4D (Proteomics 4D: The proteome in context)

Reporting period: 2015-09-01 to 2017-02-28

Summary of the context and overall objectives of the project

Powerful, recently developed technologies, exemplified by genomic, proteomic and metabolomic technologies have made the precise measurement of the major bio-molecules that constitute a living cell or tissue a reality. The same methods also quantitatively describe how the molecular makeup of specific cells or tissues respond to genetic changes or to a changing environment. Whereas it is well known that genetic changes are frequently associated with disease, the molecular mechanisms that translate changes of our genetic blueprint into specific (disease) phenotypes remain largely unknown.

The ERC project “Proteomics 4D: the proteome in context” is based on the notion that the proteome, the ensemble of all proteins in a cell is organized in a network of interlinked multi protein modules and that these protein modules represent both integrators of genetic variation and key determinants of complex phenotypes. The main objective of the project, therefore, is the development and the application of novel technologies to determine how genetic variability affects the organization of the proteome and how an altered proteome state causes a (disease) phenotype. In essence, the project attempts to study the biological function of specific proteins in the context of all other proteins of the cell.

The project will progress from determining the composition, topology, structure and modification of wild type and mutated protein kinase modules specifically selected for their known association with cancer, towards a more generic, high throughput platform that will allow us to study the effects of disease associated mutations on proteome organization on a more comprehensive level. This will be achieved by integrating new experimental and analytical techniques, specifically a range of mass spectrometric techniques with computational methods. We commit to disseminating experimental and computational resources to offer the widest community benefit from the results of the project.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The work performed for the project period involved the development of innovative research methods and their use for the generation of biological knowledge related to the organization of the modular proteome. Specifically, we generated reagents to characterise a kinase complex that is frequently mutated in cancer. We then collected quantitative data on the expression and state of modification of the respective complex components and determined changes in the composition and topology of the complex induced by cancer associated mutations. We also obtained structural data from recombinantly expressed complexes. Next, we developed experimental and computational workflows for the global analysis of protein complexes upon cellular perturbations (SEC-SWATH), for the systematic generation of structural restraints from limited sample amounts (AXL-MS), and software tools to precisely map post-translational modifications (P-SWATH, IPF) of perturbed proteomes and new algorithms to identify perturbed functional modules in disease tissue by quantifying the covariance of protein complex components in clinical cohorts. Furthermore, we refined our pipelines for the identification and quantification of proteins from large scale mass spectrometric measurements of clinical cohorts.

The main biological results of this work so far are a multilayered analysis of kinase mutations and the network, topology and structural changes upon mutation. We also devised and applied global and local methods to determine, in a differential manner, the modular proteome and relative modifications, the quantitative relationships within modules and the assembly and topology of selected modules. These research projects are ongoing and we expect that in the next year the first results will be written up for publication in peer-reviewed scientific journals. Additionally, as essential objective of the project, we started disseminating our methods by organizing workshops, courses and publishing review articles.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The state of the art in proteomics is the identification and quantitation of large numbers of proteins from an increasing number of samples. In these analyses, to date, proteins have been considered as independent entities. However, this is not how proteins function in the environment of a living cell. Rather, multiple proteins generally assemble in multiprotein complexes that constitute the functional modules of the cell. The project “Proteomics 4D: the proteome in context” builds on this knowledge and technological advances pioneered in our group to develop generic approaches, both at the global and local scale, to reveal protein in their functional context, their assemblies and their modifications. Proteomics data that consider proteins in context promises to more accurately reflect the functional state of the cell and, therefore, be more predictive of the phenotype.

We expect that our work will enable life scientists to integrate orthogonal techniques towards exploring the function of proteins in the context of their cellular functions. Tackling biological questions from a protein module perspective, rather than that of a single protein one, represents a paradigm shift in linking our genetic make-up to disease phenotypes. We are committed to disseminate the acquired knowledge by releasing open source software, publications, communications to conferences and leading workshops and courses. Our efforts will guarantee a wide and effortless access to protein module based approaches to enable further discoveries within the scientific community and the economic sector. We are confident that a context-aware study of the proteome results into a more accurate understanding of disease states and it will significantly advance translational medicine, science as a whole and human health.
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