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EU Innovative Training Network ES-Cat

Eva Schuiten

 
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Background:
I obtained my bachelor degree in Life Science & Technology from the Technical University of Delft (Delft, Netherlands) and Leiden University (Leiden, Netherlands). At the start of 2017 I finished my masters in Life Science & Technology at the TU Delft with a specialization in Biocatalysis. I performed my master thesis in the Biocatalysis group at the TU Delft under supervision of Prof. Dr. U. Hanefeld and Dr. M.P. Bracco Garcia.  The subject of my thesis was switching enzyme activity, in which the goal was to change the activity of an esterase to activity of a hydroxynitrile lyase, using only two amino acid substitutions. During my masters I also did an industrial internship at ChiralVision B.V. (Leiden, Netherlands), a small company specialized in enzyme immobilization, where I worked on immobilization of lipases on different polymer beads.

Training and Transferable Skills:

  • Site-directed mutagenesis using PCR
  • Protein overexpression in E. coli
  • Protein isolation (affinity chromatography)
  • Enzyme activity assays (esterase, lipase etc.)
  • Enzyme immobilization on polymer beads
  • Use of programs (YASARA, PyMOL, MATLAB, COMSOL)

Research Projects:
Enzymes are interesting alternatives to regular chemical catalysts used in chemical productions due to their high selectivity, efficiency and ability to operate under mild aqueous conditions. In addition enzymes are biodegradable and non-toxic, offering opportunities to make the chemical industry more ‘green’. However, it is unlikely that the enzymes found in nature will fit a process perfectly. Often enzymes are not stable enough in the desired reaction conditions or the desired substrate is not accepted. Many industrially interesting chemical reactions do not occur in nature, hence there is often no (known) natural enzyme capable of catalysis. These enzymes have to be ‘engineered’ through rational and random protein engineering approaches.
Rational design is an effective approach to protein engineering, but is only applicable when the structure and mechanism of the enzyme of interest is well known. Random protein engineering, like directed evolution, require little to no information about the enzyme. However, random approaches are labor intensive and most importantly a very good selection system (‘You get what you screen for’) is required. The project will focus on combining rational and random protein engineering techniques to increase discovery rate of successful mutants and reduce the workload, through the design of smaller ‘smart’ mutant libraries. These libraries will be designed to increase dehalogenase activity of a promiscuous epoxide hydrolase with low dehalogenase activity and the used methods should also be applicable for other enzymes. In addition to the design of libraries, high-throughput screening methods using the robotic screening platform at the host laboratory will be developed further, allowing for faster screening of small libraries.

 

 

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