These 4 building blocks have been continuously developed over the years. Since 2011, the methods have been regularly analyzed and put to the test in an ongoing improvement process. Only two years ago, each step was evaluated in the laboratory as part of enzyme engineering. This led to the realization that a portfolio of methods was needed to be able to flexibly develop the existing platform.
Smarter and more sustainable
When it became common in the early 2000s to perform enzyme engineering with high-throughput technology in order to test larger enzyme libraries faster, c-LEcta relied on the knowledge-based approach. At high throughput, huge libraries are scanned using pipetting robots and machine workstations. In such a setup, a throughput of more than 10,000 variants per week can be achieved. Disadvantage: the process consumes a lot of resources (energy and plastic) and is very inflexible in terms of adjusting parameters.
With the knowledge-based approach, the number of enzyme variants to be tested can be limited from the beginning.
Here, the c-LEcta was very early on in using bioinformatics. The computer-aided modelling of a three-dimensional enzyme structure is an important data source. It allows a statement about the amino acids that occupy certain positions and express properties. A molecular dynamic analysis can also be used to identify moving elements or enzyme-substrate interactions, which are often crucial for enzyme catalysis. Another important source are sequences of similar enzymes, which can be found in huge numbers in publicly accessible databases.
If you combine the analysis of both sources and then add the chemical understanding and scientific intuition of the c-LEcta experts, then the most important components flow into a knowledge-based library design. The software suite ASSET-DB developed by c-LEcta supports the method optimally. The data are analyzed statistically by bioinformaticians and new correlations are discovered. The software also provides the basis for future benefits of correlation analysis and machine learning, which is seen as a further leap in the effectiveness of the application of knowledge-based approaches.
Greater variety of production platforms
Not only in enzyme engineering there was a continuous development. In the area of master and process development, too, the company adapts to new requirements.
While c-LEcta initially relied on E.coli as an organism for the production of the enzymes, two more robust platforms were added over the years, which make it possible to produce a wide range of different enzyme products. For example, the use of Bacillus makes it easier to remove the enzyme from the cell, which results in increased yield and simplified product processing. In addition, the use of Bacillus in the food industry has long been recognized.
Furthermore, the yeast Pichia pastoris has been in use since 2006, which also expels enzymes and allows the production of enzymes with a more complex structure, such as those found in mammals and fungi. Pichia is often the preferred expression agent in pharmaceutical applications.
c-LEcta is currently also developing fungal expression systems. These also enable higher yields for enzymes with complex structures. We are thus opening up a complete platform for production managers. Together with Bacillus and the mushrooms, we are then optimally prepared for the requirements of the food industry, which uses these two platforms primarily for enzyme production.
