Maths helps understand disease
The software will be able to monitor whole body systems and their response to stimulus, such as disease, in real time.
Image: Petrovich9/iStockphoto

The current challenge for systems biology, or the study of whole body processes, is how to measure the changes that take place, moment by moment, among roughly 12,000 proteins in a cell when that cell is exposed to a stimulus – such as the hormone insulin.

Australian bioinformaticians have now created clever software that allows exactly this kind of processing, enabling analysis of the vast quantity of data produced by an exquisitely sensitive new generation of mass spectrometers.

The new software will even allow the re-processing of older data run in the lab, identifying at least 25% more proteins than have been identified in the past. In the not-so-exact science of systems biology, which sometimes struggles to ascertain whether or not a molecule is present in a sample, this is a giant leap forward.

PhD student Pengyi Yang and Dr Jean Yee-Hwa Yang, from Sydney’s Garvan Institute of Medical Research and the University of Sydney respectively, have developed an algorithm that will allow scientists to identify specific proteins out of the hundreds of thousands of protein fragments in a sample. Details of the project are published in the Journal of Proteome Research.

Prior to being processed by a mass spectrometer, a tissue sample is ‘digested’ by an enzyme, which breaks down the proteins into a peptide soup. Until now, it was only possible to ‘reassemble’ them (in a virtual sense) as members of protein groups. That is because over 2 million peptides are shared between two or more proteins within the 89,486 proteins recorded in the International Protein Index.

The new software enhances protein identification and will enable scientists to investigate complex diseases (such as type 2 diabetes) as entire systems operating through time, by monitoring the thousands of protein changes that take place.

“It’s now necessary to combine the disciplines of mathematics, computer science and biology to cope with the data being produced in systems biology,” said Pengyi Yang.

“Previously, the majority of labs were focused on their favourite genes or proteins. Now you need to look at all proteins, all genes, in a cell. When you try to do that you need a computational methodology to analyse the information.”

“For this project we created a mathematical model and implemented it using a computational approach – applied to the biology.”

Editor's Note: Original news release can be found here.