What you can learn from computer modelling

Speaker: Christine Jacobs-Wagner
Department: Casimir Research School
Subject: How to achieve cellular replication without fail: lessons from bacterial cells
Location: Delft
Date: October 13, 2017

Although Christine Jacobs-Wagner studied biochemistry in college, she would describe herself more as a cell biologist. According to her, one is not defined by education, but rather by the questions they pose themselves. That’s why her lab is very multidisciplinary, which made her seminar really interesting. I liked the way she didn’t just come to Delft to lecture us about what’s she’s done, but rather to get feedback from the scientists here, who might have a stronger modelling background than hers. This is how science should work, and it’s a great feeling to be a part of it.

She spoke about the importance of distributing plasmids evenly during cell division. If one of the daughter cells doesn’t inherit an essential plasmid for some reason, it will not survive. That’s why it is crucial to have a method in place to guarantee the survival of both daughter cells. The ParA and ParB proteins make up such a system. This was the focus of her research.

Untitled
Plasmids should be distributed like these green dots

The ParA proteins bind to the nucleoid of a bacterium, and the ParB associates with plasmid DNA. When they interact, ParB induces a reaction which breaks the ParA-DNA bond. This is all well understood, but how would this have the desired effect of distributing all plasmids evenly? Well, it might be easier to observe what happens when there’s only one plasmid in the cell. It starts to oscillate along the long axis, but why?

 

 

Then she proceeded with an in silico model, a computer simulation. Unfortunately, the first model didn’t show the desired behaviour. The plasmid made a random walk, so the Par proteins didn’t do anything. At least, not until she adapted the model to make the DNA non-static. She could model ParA molecules as tiny springs, which oscillate around an equilibrium position. This was a very small change, but it had a great impact. It was all she needed to accurately model the oscillatory behaviour.

It was really cool to see such a small change make such a big difference. For further research and exploration of the ParA-B system, an analytical model would be useful, but that will also be a big challenge. I’m excited for the future!

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