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The Interactorium: Another Dimension in Protein Interaction


Marc Wilkins and his team have developed a new tool that enables intracellular interactions to be visualized in stunning 3-D.

By Tim Dean

January 20, 2010 | SYDNEY, AUSTRALIA—Sitting in a darkened room, I gaze up at a giant projection of what could be abstract artwork. Arrayed before me is a constellation of tiny floating dots, some loosely scattered, some clustered within larger structures, and many of them bound together by a startling array of glowing lines. But this is not art; this is an up close and personal view a common yeast cell.

“Imagine for a moment that you’ve come up to a yeast cell and you’ve just poked your head inside the outside membrane,” says Marc Wilkins, the “father” of proteomics and director of the NSW Systems Biology Initiative at the University of New South Wales. Wilkins’ team has developed a new 3-D visualization tool for exploring the inner workings of cells, called The Interactorium.

Wilkins points out the cell’s various organelles—nucleus, mitochondria, etc.—while the thousands of dots scattered around are the proteins. Then, with a couple of clicks of the mouse, Ph.D. student Yose Widjaja—the brains behind the coding of The Interactorium—gracefully rotates the mass of dots and lines, selects a single ‘node’, and the view zooms in to reveal the protein in detail.

Mere words and still images can’t do justice to the beauty and elegance of The Interactorium. Even a “simple” yeast cell is a startlingly complex thing: thousands of different proteins, each with potentially dozens of interactions. Trying to visualize this with a conventional database or a 2-D diagram is an exercise in futility. But The Interactorium presents it all in glorious, intuitively navigable 3-D, displaying a vast amount of information in an immediately digestible form.

But The Interactorium is more than pretty pictures. Wilkins hopes it will not only enhance our understanding of the inner workings and dynamics of cells—healthy and diseased—but also aid in the development of new drugs that target specific proteins.

Information Overload

The trick is how to represent the multitude of interactions that take place inside a cell in an intelligible way. Even with a yeast cell, you’re staring down the barrel of 6,000 genes, let alone the 22,000-odd genes for a human cell. And then you have the host of interactions between them all. Vast databases have been constructed containing information about these biomolecules, but staring at a table of data doesn’t help make sense of it all.

Visualization tools for protein interactions aren’t new, of course. Cytoscape and VisANT, for example, have proved most useful in representing different parts of cells. But both are limited to 2-D views. Even 3-D tools like GEOMI (Geometry for Maximum Insight) struggle to handle even a relatively simple cell like yeast.

“If we wanted to move up to a very large number of proteins and a large number of interactions, the software available to us didn’t support that,” says Wilkins. “You’d reach a certain level whereby the existing software hits the wall around about a thousand proteins.”

Wilkins admits the 3-D navigability of the old technology was “pretty slow. It was a Java-based platform and it really wasn’t going to be as fast and powerful for being able to build things in three dimensions and navigate them in the kind of way we can do here now.”

This is where Widjaja stepped in. His Honours project was a visualization tool called Skyrails, originally intended to model things like social networks. However, with a deft piece of interdepartmental collaboration, he soon discovered another potential application for Skyrails: the interactome. “It was an astonishingly fast and powerful platform for generating a navigable three dimensional space,” says Wilkins. “We got talking about some of the types of things we were doing and this collaboration arose from that in which we have now built a virtual cell.”

Thus was The Interactorium born, and it now forms the crux of Widjaja’s ongoing Ph.D. project.

Cell Space

When you first fire up The Interactorium—which you can do on most desktops or laptops with a 3-D graphics card—you can view the cell in one of two ways: the first is the Complex Viewer, which just shows the interactome; the second is the Virtual Cell, which adds localization data. The latter view includes a wire frame panorama of the guts of the cell. “As you navigate around, the size of the organelles bear some approximation to the number of proteins you actually see in each of them,” says Wilkins. “We haven’t literally built these organelles to be the size and shape of an organelle—of course that can be done if that’s imperative.”

“The cytoplasm is a very busy place,” Wilkins continues. “All the lines are the interactions. That’s when you start to see all of the proteins and the protein complexes. We like to look at the cell as not just a set of individual proteins but protein complexes—we think it’s the biologically appropriate view.” Many networks display one dot per single or gene. “We instead have very much focused on what is the functional unit inside the cell and sought to build it up from there.”

But the crucial part is visualizing the interactions. The lines between the proteins that represent the interactions are of different thickness, which relates to the ‘quality’ of the interaction. “Beneath this there’s a very sophisticated database about what the proteins are, where they’re found inside the cell and what complexes they’re known to be part of. Mousing over the lines between two proteins says whether there’s evidence in the literature that supports this interaction.”

This provides an immediate gauge of the confidence in the interaction or the complex being displayed and assess the quality of the data. Wilkins says it beats an Excel spreadsheet or having to work through stacks of papers and databases.

Predictably Powerful

This is all powered by a sophisticated database compiled by Wilkins’ colleague Simone Li, which gathers a broad selection of the literature on the yeast cell. One of the strengths of The Interactorium is that none of the data about the cell is hard coded. Plug in a different database—say for a human cell—and The Interactorium will lay it all out for you.

They’ve even added a deeper layer into the visualization. “We’ve got a virtual cell; we’ve got organelles; we’ve got complexes; we’ve got proteins—if we keep on working through that hierarchy the next logical thing is if there’s structural data for particular proteins. So when you get sufficiently close to a particular node of interest, it’ll render the protein structure in three dimensions for you.”

One of the most exciting applications of The Interactorium is the ability to get a better understanding of the inner workings of a cell, such as which elements are static and which are dynamic. But The Interactorium also provides an idea of the blanks, of what we don’t know. “If you have a group of five proteins that all interact with each other in this network, and the functions of four of them are known, you can make extremely strong hypotheses and predictions of what the function of the next one is,” says Wilkins. He points out that half the genes in the human genome still have no known function, and even in humble yeast, there are 1,000 or so genes for which there’s no known function.

Wilkins has received interest from researchers from cancer to drug discovery. There’s a lot of interest in terms of using network-based analysis for understanding changes in cells, whether they are stem cells as they are going from pluripotency to a final tissue type or looking at changes in cancer cells. People are also interested in using this kind of thing for drug discovery: understanding networks, understanding pathways, seeing how those are associated with phenotypes or the genesis of disease. If there are particular proteins that have a sensitive interaction inside these networks, you might ask the question: ‘Can we block that with a particular drug or peptide?’”

The Interactorium might also help predict drug side effects. “If you make a drug against a particular protein, is it only going to be acting against one protein or one interaction? And if you block that interaction, in a network sense, is the cell going to be able to do the same thing by another path?” Its early days for The Interactorium—the first report has already been published online in Proteomics—but already its potential to reveal secrets of protein interaction are plain to see.

Tim Dean is the editor of Australian Life Scientist magazine.


This article also appeared in the January-February 2010 issue of Bio-IT World Magazine.
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