GuideArtifEvol · Tracking and guiding artificial enzyme evolution via landscape inference
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2019-09-01 → 2021-12-21
- EU contribution
- €196,708
- Participants
- 1
- Scheme
- MSCA-IF-EF-ST
Lines connect the coordinator with its partners.
Results in brief
Tracking and guiding artificial enzyme evolution via landscape inference
Enzymes are molecules that exist in Nature and that catalyze chemical reactions. They are highly specific to bind to their substrates and very efficient in their activities. They are perfect candidates for applications in which chemical reactions are needed and many of them are already used in different industries, from pharmaceuticals and diagnostics to food and cloth industries. Enzymes most of the time cannot be directly used in a different context as the natural one, or the desired outcome of the chemical reaction is not exactly the same as the natural one. Therefore, there is a large interest in engineering enzymes to adapt them to work in different conditions, to increase their efficiency, change their substrates or remove secondary activities. Directed evolution has been proved to be an effective method for enzyme engineering: it has successfully increased the efficiency of some enzymes, adapted others to work in different conditions, and even changed their substrates. The process mimics natural evolution: it generates a set of diverse variants of the gene codifying for the enzyme and subjects this set to functional screening or selection in order to extract the best performing variants. These two steps are applied iteratively, leading to optimized variants of the enzyme. While it is an effective strategy, the underlying of the process remains unknown and the overall protocol is time consuming. Previous work has focused on increasing diversity and smarter strategies for selection and screening. In this project I focus on how the sequence space is explored during directed evolution experiments. I use an experimental platform that tests millions of variants of an enzyme simultaneously, and I incorporate next generation DNA sequencers to the overall protocol. This permits to have an insight on the effect of DNA mutations in the activity of the enzyme and it will aid to focus experimental efforts in those which have a stronger impact.
Data: CORDIS, © European Union
Project 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.
Original text from CORDIS.
Participants
- ECOLE SUPERIEURE DE PHYSIQUE ET DECHIMIE INDUSTRIELLES DE LA VILLE DEPARIS · ParisCoordinatorFrance
Links
Data: CORDIS, © European Union