Difference between revisions of "Team:KU Leuven/Project/About"

Patterns are fascinating, from the veins of a leaf to the spots on a zebra, from a single cell to a whole organism. Patterns are found everywhere in nature, but how these are formed is not entirely clear. We, the KU Leuven 2015 iGEM team, decided to work on the fundamental mechanisms behind pattern formation. The way cells interact to generate a specific pattern has triggered our curiosity and added a new dimension to the way the patterns are looked upon. Our mission is to create different and astonishing biological patterns with engineered bacteria for a better understanding of nature with the prospect of applying the knowledge in industry.

A better understanding of the pattern formation process in combination with the appropriate and detailed predictive mathematical models will be advantageous in many different fields, ranging from construction and design, to medicine, to electronics, to even art. Tumor formation and tissue regeneration are a few among the many examples where the medical world could benefit from a deeper knowledge of pattern formation. The generation of patterns in a controlled way will also allow the production of novel biomaterials. After forming a pattern, the cells can be engineered to precipitate or deposit networked biominerals, opening up exciting new avenues for the production of microstructured biocomposites. In the long term, the ability to construct predesigned patterns of bacteria could lead to applications in miniature electrical conductors and/or electrical circuits.

We are engineering two different types of bacteria to form a desired pattern. We aim to create an impact on the cell behaviour and the motility corresponding to a stimuli generated by bacteria. Our preliminary design focuses on crafting a new construct that makes the cells of the same type to adhere to each other and repel the different type in a controlled manner, thus creating a desired pattern.

We will define the kinetic parameters in the wet lab for generating precise models to represent pattern-forming bacteria. We will use techniques like chromatography, chemiluminescence, fluorescence and biological assays coupled to image analysis to quantify certain gene products.

Different levels of protein production will affect the shape and size of patterns that the bacteria form, therefore we will control promoter induction and experiment runtime to study the resulting effects. Additionally, this will give the modeling team more data to fit their models to different conditions. Synergically, simulations from the cyber lab will aid tuning the experimental conditions that lead to the desirable patterns.