Uncovering New Relationships and Organizational Principles

Proteins play important roles in cells and tissues. Some proteins provide structural integrity, others drive biochemical reactions, and yet others regulate gene expression. Proteomics is the study of the structure, function, and interaction of all the proteins in a cell or organism, which can number in the hundreds of thousands or millions of variations.

To better understand proteins in their dynamic world, researchers in the Washburn Lab and their collaborators used an advanced mathematical approach called topological data analysis (TDA) to study two different kinds of proteins and their interaction networks. The researchers changed, or perturbed, parts of these two protein networks and then determined how the networks were affected. Using TDA, groups of proteins exhibiting similar effects and sharing similar properties were identified as topological network modules. Additionally, the researchers were able to obtain an expanded view of cascading interactions across the larger network and identify new areas of biological networks to explore.

“TDA is a fast and efficient way to interpret complicated data sets,” says Michael Washburn, PhD, director of proteomics. “There’s very little data out there on disrupted or perturbed protein interaction networks. Most of the focus has been on static networks. By perturbing a system, you can learn how it works as a dynamic network. This approach can provide an accessible route to visualize relationships between proteins.”

This work was published in the March 8, 2017 issue of the Nature Publishing Group's Scientific Reports.