ERC Consolidator Grant 2022 - PROMISE : Proteome diversification in evolution - An IBPS winner!

Elodie Laine, Sorbonne University lecturer in the “Analytical Genomics” team of the LCQB, is the winner of the “ERC Consolidator Grant 2022” program for her PROMISE Project: Proteome diversification in evolution.

This prestigious and highly competitive funding is granted by the European Research Council (ERC) to support European Union researchers at the start of their careers, by providing them with the necessary means to carry out innovative and ambitious research projects.

The awarding of this funding to Elodie Laine demonstrates the recognition of her exceptional scientific contributions in the field of proteome diversification during evolution.

Elodie presents her project to us:

How have proteins diversified through evolution? What combinations of amino acids play a crucial role in their interactions? Did complex behavioural traits, such as vocal learning, emerge from protein innovations or through the re-use of evolutionary ancient themes? 

The PROMISE project aims to answer these questions by exploiting massive amounts of protein-related data with cutting-edge AI (artificial intelligence) techniques.
PROMISE hypothesizes that the natural variations observed between different "proteoforms" (different variations of the same protein) resulting from duplication (of different genes) or alternative splicing (of the same gene) events tell us where and how to target proteins to modulate their interactions and functioning.

The expected results will be transferable to a wide range of important societal questions, such as the inter-individual variability in disease susceptibility and the design of more specific drugs and more biocompatible de novo proteins.



Schematic overview of PROMISE. 

A. Classical MSA (on top) and interaction network (at the bottom).

B. Novel graph-based proteo-transcripto-genomics integration. Three transcripts from one species are highlights as coloured paths in the graph. Through evolutionary and physically informed representation learning (boxes in blue), PROMISE will(1)yield proteoform-centric interaction networks,(2)identify convergent molecular patterns between humans and zebra finches, and(3)unravel inter-residue dependencies modulating protein interactions.