ES-Cat is a Marie Curie Initial Training Network set up to provide young researchers with hands-on research experience and formal training ten European partner groups use directed evolution as a tool to reproduce Nature's remarkable ability to generate molecular machines - in particular enzymes – that perform at levels near perfection.
15 fully-funded PhD studentship are available in the partner groups, for start dates from March 2017. Students interested in joining the programme should email the groups in which they would like to work (see table below) with a description of their background and interests, a CV, their academic record (with marks) and the names of two referees who can comment on their scientific track record. Applicants must have at least a 2.1 in Chemistry, Biochemistry or a related subject. The only formal restriction is that you have to undertake the PhD programme in a country where you have not been resident in the past five years. You should apply as soon as possible directly to the partner group that you wish to work in.
Research. Instead of seeing rational and combinatorial protein engineering approaches as alternatives, we combine them in this network to achieve a ‘smarter’ and more efficient exploration of protein sequence space. By harnessing the forces of Darwinian evolution and design in the laboratory we want to
(i) screen large and diverse libraries for proteins with improved and useful functions,
(ii) optimize existing proteins for applications in medicine or biotechnology, and
(iii) provide a better understanding of how existing enzymes evolved and how enzyme mechanisms can be manipulated.
The range of methodologies represented by academic and industrial groups with diverse and complementary skills in ES-Cat allows an integrated approach, combining in silico structural and sequence analysis with experimental high-throughput screening selection methods (phage-, ribozyme and SNAP display, robotic liquid handling, lab-on-a-chip/microfluidics) with subsequent systematic kinetic and biophysical analysis. This integration of methods and disciplines will improve the likelihood of success of directed evolution campaigns, shorten biocatalyst development times, and make protein engineering applicable to a wider range of industrial targets. It will also train the next generation of creative researchers ready to fill roles in tailoring enzymes and other proteins for industrial applications in synthetic biology efforts to move towards a bio-based economy.
Training. ES-Cat is designed to educate young researchers in an interdisciplinary environment based on a training programme in which methods and disciplines to improve predictability of directed evolution campaigns, to shorten biocatalyst development times, and to make protein engineering applicable to a wider range of industrial targets are integrated. We also address dissemination of the vision, activities and results of the ES-Cat network to the general public, hopefully improving citizen awareness.
Technology Transfer. Research and training in this area strongly interface basic research with industrial applications. Preparation for such translational activities is part of the training programme that encompasses course on entrepreneurship, IP protection or economic challenges in applied biotechnology. The incorporation of seven industrial partners ensures a continuous reality test of our research training. Opportunities to engage in collaborative projects with industrial partners are offered to all young researchers.
ES-Cat comprises ten partner groups:
|short name||Principal Investigator||Affiliation|
|UCAM||Dept of Biochemistry
University of Cambridge, UK
|RUG||University of Groningen, Netherlands|
|EMAUG||University of Greifswald, Germany|
|UCL||Université Catholique de Louvain, Belgium|
|BGU||Ben Gurion University of the Negev, Israel|
|ICRC||International Clinical Research Center, St. Anne's University Hospital Brno, Czech Republic|
|MEDI||Dr Lutz Jermutus
Dr Ralph Minter
|MedImmune, Cambridge, UK|
|JM||Dr Ursula Schell||Johnson Matthey, Cambridge, UK|
|EN||Dr Veronika Stepankova||Enantis, Brno, Czech Republic|
|WWU||Prof Erich Bornberg-Bauer||University of Münster, Germany|
The research leading to the results in these web pages has received €3.9 millions of funding from the Horizon 2020 Programme (Marie Curie Actions) of the European Union under grant agreement n° 722610. This material reflects only the author’s views and the Union is not liable for any use that may be made of the information contained therein.