"This is a premiere example of what can be achieved through interdisciplinary and collaborative research," says Kusalik, a professor in the computer science department.
Kinases are often involved in cellular functions that go awry, such as when pathogens like viruses or bacteria "hijack" a cell's functions for their own purposes. Pathogens also have kinases of their own.
"Kinases have a central role in controlling cellular processes and are associated with many diseases. They're logical points for understanding biology and represent important treatment targets," says Napper, an associate professor of biochemistry with the U of S and senior scientist at the Vaccine and Infectious Disease Organization-International Vaccine Centre (VIDO-InterVac).
The standard lab tool in kinase research is the microarray, which allows researchers to analyze many different kinases within a sample simultaneously. A microarray looks like a standard microscope slide with rows of spots, each spot representing a different molecular test.
"With older methods, it was like having a little flashlight in a cave - you can see, but it doesn't tell you all that is there," Napper says. "These arrays give you the whole picture - but you end up with absolutely mountains of data."
The problem for Napper and fellow VIDO-InterVac senior scientist Philip Griebel was that the mountains of data were making no sense. Griebel is also a faculty member with the U of S School of Public Health.
"They knew there were problems with the methodology they were following, because the results 'weren't working out,' but they didn't have sufficient expertise in bioinformatics to come up with an alternate method. That's where we came in," Kusalik says.
Kusalik is an expert in bioinformatics, which is the application of computers and information technology to biology and medicine. One well-known application of bioinformatics is DNA sequencing, including the Human Genome Project.
For Kusalik, the problem wasn't the volume of data, but how it was being handled. Standard software for analyzing DNA microarrays doesn't work well with other microarrays. He explains that it's like using a descrambler box from one cable company to watch television from another company. You might get fuzzy glimpses of the picture, but it will be impossible to view the entire program with any clarity.
The solution was to build software tailor-made for kinases.
"By developing a technique specifically designed for kinase microarrays we are able to get more data, and with more accuracy," Kusalik says.
This claim is borne out in the research described in the Science Signalling paper, as well as by colleagues in the field. Napper says that other research groups have approached them to run their existing data sets through the new software.
"It's very brave of them - it may prove some of their earlier conclusions wrong," he says.
"We're going to leave it up to other people to decide if they want to re-analyze their data. I bet there's a lot more interesting biology that's going to come out of their studies."
This work was supported by the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canada Research Chairs program. Additional funding was provided through Genome Canada and the Alberta Meat and Livestock Agency (ALMA). The Beef Cattle Research Council is also funding further work to apply this technology to various livestock diseases.
Publication Link: "A Systematic Approach for Analysis of Peptide Array Kinome Data" Science Signalling, 17 April 2012 Vol. 5, Issue 220, p. pl2 http://stke.sciencemag.org/cgi/content/abstract/5/220/pl2
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