Three-dimensional dynamic views of proteomes as a novel readout for physiological and pathological alterations

Informations projet

Proteomes-in-3D

N° de convention de subvention: 866004

DOI

10.3030/866004

Projet clôturé

Date de signature de la CE 19 Février 2020

Date de début 1 Mars 2020

Date de fin 28 Février 2025

Financé au titre de

• EXCELLENT SCIENCE - European Research Council (ERC)

Coût total

€ 2 000 000,00

Contribution de l’UE

€ 2 000 000,00

Coordonné par

EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Switzerland

Periodic Reporting for period 4 - Proteomes-in-3D (Three-dimensional dynamic views of proteomes as a novel readout for physiological and pathological alterations)

Période du rapport: 2024-09-01 au 2025-02-28

Résumé du contexte et des objectifs généraux du projet

Systems biology of proteins classically uses a technique called proteomics, which measures thousands of proteins in a biological system at once. This is very powerful, but it does not look at the structures (i.e. shapes) of these proteins, but only at their amounts. However, protein structures are critically important to understand how proteins function in health or mis-function in disease. In this project, the Picotti lab has addressed this problem by developing an approach to study the structure and function of thousands of proteins at the same time, within their native biological context. The group applied these methods to study protein aggregation (a type of protein structural change), in particular in diseases that are linked to aggregation such as the neurodegenerative Parkinson’s disease (PD). The overall goal of the project was to study protein aggregates or assemblies in healthy physiology and in disease and their modulating factors, develop new approaches to the discovery of disease biomarkers and extend the functional and mechanistic knowledge obtainable from systems biology. The approach provided the community with new methods for global analyses of proteins in cells and tissues, allowed the discovery of a new type of disease biomarkers for neurodegenerative and other diseases and shed light on regulators and mechanisms of protein aggregation.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

We have shown that global protein structural information (ie structures of thousands of proteins) detects multiple functional molecular events in the cell, for example enzyme catalysis and protein-protein interaction (among others). So for the first time, with a single analysis, we can monitor multiple different molecular processes going on in the cell and watch what happens when the cell changes. We have also shown that our global structural readout can be used to help identify drug targets and off-targets in mammalian cells, which is of interest in biopharma. We have pioneered the new concept of structural biomarkers and applied it to the discovery of 70 new candidate biomarkers for Parkinson's disease. Further, we have identified new regulators of protein conformational changes and protein aggregation and are building an open access database providing the community with an unprecedented data on protein dyamics for more than 10,000 proteins. These achievements resulted in a number of awards to the PI leading the projects and to group members and in two patents that have been licensed to an ETH spin-off company.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

Our work demonstrates the new concept that global protein structural analysis is more powerful than classical abundance-based proteomics for learning functional information, at the molecular level, both when studying organisms like yeast cells in the laboratory and in diagnosis and study of human disease. The new approach improve substantially our ability to marry molecular and global understanding of biological systems.We have used the detailed molecular information that we could gain with our approach to characterize a number of biological processes in health and disease.

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