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- Thijs Ettema
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I started my studies at the Radboud University Nijmegen in 2010, to learn about the molecular mechanisms that govern life. As I learned about chemistry and molecular biology, I became interested in methods to build models of living cells in the computer. Being able to create a ‘cell in the box’ that behaves as a real cell requires a thorough understanding of biology, a major challenge! Apart from its academic value, the cell in the box may also allow us to apply biotechnology more effectively.
To learn more about this field, I chose courses that revolved around topics such as systems biology, bioinformatics and computational biology. This culminated in a research intership at Richard Notebaart’s group at the CMBI, where I analyzed metabolic networks to identify potential drug-targets for cancer therapy.
I continued my studies at Uppsala University, where I chose courses that focused on microorganisms. These tiny creatures are easier to model than the ‘macroorganisms’ that we can see, because the size of their biological system is smaller. After participating in the iGEM 2014 with the Uppsala team and doing a mini-internship at Sorin Tănase-Nicola’s group, I have now joined the Ettema-Lab for my thesis project.
My own contribution to the lab will be the study of binning techniques. The study of many microorganisms is hindered by the fact that they cannot be cultured. At the Ettema-Lab, we try to circumvent this problem by using metagenomic approaches. We sequence the DNA that is present in mixed samples (containing different organisms) to deduce the sequences of genomes that were present in the sample.
Sequencing a sample results in ‘reads’, short (~150 bp) pieces of DNA. Assembling these reads results in ‘contigs’, which are larger fragments of a genome. These contigs are still mixed; this is where binning comes in. In binning algorithms, contigs are clustered into genome bins based on properties that are supposed to be genome-specific.
Using binning algorithms may allow us to reconstruct genomes. These reconstructed genomes may enable us to study a cell in the box, even when its real-life counterpart cannot be studied in a laboratory environment.