High-Betweenness Proteins in the Yeast Protein Interaction Network

By M. P. Joy, Amy Brock, Donald E. Ingber, Sui Huang. Journal of Biomedicine and Biotechnology, 2005

489 citations recorded by the source corpus.

Structural features found in biomolecular networks that are absent in random networks produced by simple algorithms can provide insight into the function and evolution of cell regulatory networks. Here we analyze “betweenness” of network nodes, a graph theoretical centrality measure, in the yeast protein interaction network. Proteins that have high betweenness, but low connectivity (degree), were found to be abundant in the yeast proteome. This finding is not explained by algorithms proposed to explain the scale-free property of protein interaction networks, where low-connectivity proteins also have low betweenness. These data suggest the existence of some modular organization of the network, and that the high-betweenness, low-connectivity proteins may act as important links between these modules. We found that proteins with high betweenness are more likely to be essential and that evolutionary age of proteins is positively correlated with betweenness. By comparing different models of genome evolution that generate scale-free networks, we show that rewiring of interactions via mutation is an important factor in the production of such proteins. The evolutionary and functional significance of these observations are discussed.

Subfields: Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/67725c88f362d664f85c5ac6dcaca884fab87622

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Citations in the corpus

Analyzing and modeling real-world phenomena with complex networks: a survey of applications (2007, background): “The functional importance of proteins can also be addressed in terms of network entropy [338] and betweenness centrality [339].”
Graph theory and networks in Biology. (2006, methodology): “Recently, in [106] the measure Cb was applied to the yeast protein interaction network and the mean value of Cb for the essential proteins in the network was approximately 80% higher than for non-essential proteins.”
The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics (2007, background): “This is in agreement with the previous observation by Huang and his colleagues, who found that proteins with high betweenness but low degree (i.e., nonhub–bottlenecks) are abundant in the yeast protein interaction network [18].”
Using graph theory to analyze biological networks (2011, background): “Calculation of this centrality measure is discussed in [82] and [83] and their properties within the PPI network of yeast are detailed in [84].”
Centrality Analysis Methods for Biological Networks and Their Application to Gene Regulatory Networks (2008, background): “In particular, proteins with a high betweenness and low degree value (HBLC, high betweenness low connectivity proteins) are prominent as they are supposed to support modularization of the network (Joy et al. (2005)).”
Global landscape of protein complexes in the yeast Saccharomyces cerevisiae (2006, result): “Consistent with previous studies 17,35 , essential genes tend to be more highly conserved, highly connected and central to the network (as deﬁned by betweenness), presumably reﬂecting their integrating role.”