IBEC researcher Benedetta Bolognesi awarded an ERC Consolidator Grant

Benedetta Bolognesi, Principal Investigator at the Institute for Bioengineering of Catalonia (IBEC), based in the Barcelona Science Park, has been awarded an ERC Consolidator Grant. The €2 million grant over 5 years will allow Bolognesi and her team to develop a new method for identifying mutations that lead to the formation of amyloids, aggregates of proteins that contribute to a variety of diseases, including Alzheimer’s and Parkinson’s.

The ERC Advanced Grant funding, awarded by the European Research Council (ERC), is amongst the most prestigious and competitive EU funding schemes, providing researchers with the opportunity to pursue ambitious, curiosity-driven projects that could lead to major scientific breakthroughs. They are awarded to established, leading researchers with a proven track-record of significant research achievements over the past decade. Bolognesi is part of the 14.5% of selected candidates across Europe, chosen from among 2,130 applications received in this call.

The researcher began her career as a group leader at the end of 2018 with the creation of IBEC’s Protein Phase Transitions in Health and Disease group. After four years as a junior group leader, she was promoted to consolidated group leader.

The project to be developed with this new funding is named Global Amyloid Mapping: Solving Amyloid Nucleation by Deep Mutagenesis (GLAM-Map).

Amyloids are proteins that aggregate into fibrils, accumulating in the body without being degraded. Their formation appears to underlie more than 50 human diseases, including Alzheimer’s disease, Parkinson’s disease, frontotemporal dementia, amyotrophic lateral sclerosis (ALS), and type II diabetes.

In the process of amyloid formation, proteins go through many steps before adopting their final conformation, ultimately leading to the formation of insoluble aggregates. These intermediate states are crucial for understanding the protein’s evolution toward its amyloid structure. However, studying these states is extremely challenging with conventional methods due to their transient nature.

As an alternative to studying this process, Benedetta and her team have developed a new methodology based on deep mutational scanning. With this approach, thousands of mutations are introduced into protein sequences to study their effects on the aggregation rate in a highly parallel way.

The project has three main objectives: to map the impact of mutations on more than 60 amyloids, to build models of the transition states of disease-associated amyloids, and to uncover genetic sequences that initiate amyloid formation in response to environmental stress. The research seeks to unravel the rules that govern amyloid formation, identify mutations that accelerate aggregation and cause disease, and understand the steps of this process.

The results are expected to contribute to the development of new therapeutic approaches for amyloid diseases, including severe dementias. Moreover, the results will be able to feed new models and predictors of protein aggregation to employ for disease variant interpretation and the synthetic design of novel proteins.

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