Modelling, mathematics and more...
The more we find out about biology, the more we realize how complicated it is. Or at least, that is how it can seem when you see the growing mountain of scientific data - a mountain that is increasing ever more quickly as technological improvements forge ahead.
So how do scientists make sense of the large quantity of information that has been gathered using different techniques and that describes different steps in a biological process? ‘Systems biology’ is a rapidly growing discipline that seeks to do just that.
Traditionally it has been necessary for biologists to break problems down into ‘bite-size’ chunks.
For example, although they know that a process such as DNA repair involves a whole team of proteins, for many years the analysis has been done one protein at a time. This can tell scientists what the function of its component parts are, where it goes inside cells and what makes it active or inactive. Now, a goal of systems biology is to put the pieces back together again and this is what researchers who work on mismatch repair are aiming for.
Importantly, they’re not using the pieces to make a static ‘snapshot’, but are making a dynamic model. Imagine comparing a single photograph taken at a party and video recording the whole evening. The photograph only shows you a few of the people who were there and doesn’t tell you who they spoke to; the video tells you about how long the partygoers stayed for and who they interacted with.
But, because we can’t just video the process of mending DNA, ‘seeing’ the dynamics of mismatch repair is much more challenging. Mathematical modelling is an integral part of building the dynamic picture. For example, scientists take data from experiments that show the strength of an interaction between two proteins and put that together with data about the amount of those proteins inside a cell. They can then use mathematics to make predictions about the behaviour of the proteins.
Because mismatch repair involves many proteins and many steps, putting all the information together requires a team effort from scientists with different expertise, including those who gather very detailed data from real cells and those who use computer programming to make simulations. Therefore, systems biology is not just about integrating the science; it is about integrating the scientists.
What do researchers hope to learn from making models of mismatch repair? The answer is that it can help us to understand why DNA repair can go wrong, as can happen in cancer. Imagine we’re back at the party and something has gone wrong: an argument has broken out. If we rewind the video we can see that a guy started dancing with someone else’s girlfriend. Likewise, if we have a dynamic model of mismatch repair we can predict what will happen if a protein changes one of its interactions.
Therefore, although integrating the many strands of scientific evidence is in itself a complicated process, it can help us to make sense of the true complexity of biology.
Mary Muers