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Tracking and guiding artificial enzyme evolution via landscape inference

Project description

A closer look at artificial enzyme evolution

Directed evolution is an effective method for protein engineering that represents one of the most widespread tools in basic and applied biology. The EU-funded GuideArtifEvol project will introduce full-gene next-generation sequencing to supervise the investigation of variants at the sequence level and quantitatively characterise the fitness landscape, focusing on the non-additive effects of mutations on fitness (epistasis). This information will be included in DE protocols to guide a more efficient exploration of the sequence space. The project aims to improve understanding of the topology of the enzyme’s fitness landscape and its distortions under selective pressures and elucidate the correlations between sequence, function, and evolution in proteins.

Objective

Directed evolution is an effective method for protein engineering. The host laboratory is designing innovative techniques for the directed evolution experiments of enzymes, with the possibility to test millions or billions of variants to be tested at each cycle. In this project, I will introduce the use of full-gene next generation sequencing to supervise the exploration of variants at the sequence level and quantitatively characterize the fitness landscape, with a focus on non-additive effects of mutations into fitness (epistasis). Furthermore, this information will be included in DE protocols to guide a more efficient exploration of the sequence space.
The project is a strongly interdisciplinary project consisting of experimental synthetic biology, physics modelling and bioinformatics analysis. It is focused in the study of DNA processing enzymes such as polymerase and endonucleases. The proposal includes the development of specific tools which should have an immediate impact on the scientific community: i. extend the applications of next generation sequencers to characterize full length genetic libraries of protein variants ; ii. adapt quantitative methods, previously developed for sets of structurally homologous proteins and derived from Potts model to study the catalytic properties of during directed evolution. iii. develop a new experimental protocol to control the number of mutations in libraries.
The analysis will provide a better understanding of the topology of the fitness landscape of an enzyme, and its distortions under selective pressures, thereby clarifying the relations between sequence,function and evolution in proteins.

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Funding Scheme

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MSCA-IF-EF-ST - Standard EF

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Call for proposal

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(opens in new window) H2020-MSCA-IF-2018

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Coordinator

ECOLE SUPERIEURE DE PHYSIQUE ET DECHIMIE INDUSTRIELLES DE LA VILLE DEPARIS
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 196 707,84
Address
RUE VAUQUELIN 10
75231 Paris
France

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Region
Ile-de-France Ile-de-France Paris
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 196 707,84
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