Node interference and robustness: performing virtual knock-out experiments on biological networks: the case of leukocyte integrin activation network

Abstract

The increasing availability of large network datasets derived from high-throughput experiments requires the development of tools to extract relevant information from biological networks, and the development of computational methods capable of detecting qualitative and quantitative changes in the topological properties of biological networks is of critical relevance. We introduce the notions of node interference and robustness as measures of the reciprocal influence between nodes within a network. We examine the theoretical significance of these new, centrality-based, measures by characterizing the topological relationships between nodes and groups of nodes. Node interference analysis allows topologically determining the context of functional influence of single nodes. Conversely, the node robustness analysis allows topologically identifying the nodes having the highest functional influence on a specific node. A new Cytoscape plug-in calculating these measures was developed and applied to a protein-protein interaction network specifically regulating integrin activation in human primary leukocytes. Notably, the functional effects of compounds inhibiting important protein kinases, such as SRC, HCK, FGR and JAK2, are predicted by the interference and robustness analysis, are in agreement with previous studies and are confirmed by laboratory experiments. The interference and robustness notions can be applied to a variety of different contexts, including, for instance, the identification of potential side effects of drugs or the characterization of the consequences of genes deletion, duplication or of proteins degradation, opening new perspectives in biological network analysis.

Figure 1. Betweenness interference.

a. Node5 and node4 are in the shortest paths from node0 to the other nodes. b. Node5 have been removed. Node4 is now essential for connecting node0 to the rest of the network: it is the only node in the shortest paths connecting node0 to the other nodes: node4 betweenness increases.

Figure 2. Positive and negative interference.

a Node3 and node4 are the nodes connecting the top of the network with the bottom. b Node6 has been removed: node4 becomes a peripheral node, its betweenness decreases. The presence of node6 is important for node4 to play a central role (positive interference). At the same time, node3 and node5 become fundamental connections betweenn the top and the bottom. Their betweenness values increase. The presence of Node6 in the network on the left damages the “central role” of node3 and node5 (negative interference).

Figure 3. Integrin network.

The network of the 61 integrins and 241 binary interactions, involved in the process of adhesion regulation.

Figure 4. Interference of HCK and FGR.

First fifteen negative interference values of HCK and FGR, expressed as percentage.

Figure 5. Interference of SRC and JAK2.

First fifteen negative interference values of SRC and JAK2, expressed as percentage. Note the reciprocal high interference of SRC and JAK2.

Figure 6. Effects of Jak2 inhibition.

Lymphocytes were pre-treated with the indicated concentrations of tyrphostin AG490 at 37°C for 15 min and stimulated with CXCL12 for 1 min. Plots are averaged values of adherent with standard deviation N = 5.