The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics

By Haiyuan Yu, Philip M. Kim, Emmett Sprecher, Valery Trifonov, Mark Gerstein. PLoS Comput. Biol., 2007

1,031 citations recorded by the source corpus.

It has been a long-standing goal in systems biology to find relations between the topological properties and functional features of protein networks. However, most of the focus in network studies has been on highly connected proteins (“hubs”). As a complementary notion, it is possible to define bottlenecks as proteins with a high betweenness centrality (i.e., network nodes that have many “shortest paths” going through them, analogous to major bridges and tunnels on a highway map). Bottlenecks are, in fact, key connector proteins with surprising functional and dynamic properties. In particular, they are more likely to be essential proteins. In fact, in regulatory and other directed networks, betweenness (i.e., “bottleneck-ness”) is a much more significant indicator of essentiality than degree (i.e., “hub-ness”). Furthermore, bottlenecks correspond to the dynamic components of the interaction network—they are significantly less well coexpressed with their neighbors than nonbottlenecks, implying that expression dynamics is wired into the network topology.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e6770951fec51d31a2be0d7c0865ebafc8e00069

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Citations in the corpus

Why Do Hubs in the Yeast Protein Interaction Network Tend To Be Essential: Reexamining the Connection between the Network Topology and Essentiality (2008, result): “Since then the correlation between degree and essentiality was confirmed by other studies [4–7], but until recently there was no systematic attempt to examine the reasons for this correlation.”
Studying protein^protein interaction networks: a systems view on diseases (2012, methodology): “…techniques that identify key mediators suggest that these are not necessarily network hubs (e.g. P63104): relatively poorly connected network nodes may also play crucial role in linking different parts of large and complex networks (see also [41, F. Vaggi et al. , submitted for publication]).”
Integration of biological networks and gene expression data using Cytoscape (2007, background): “Essential genes are also associated with nodes, which occupy central positions in large interaction networks, particularly those frequently found to connect other nodes togethe”
Network Pharmacology: A New Approach for Chinese Herbal Medicine Research (2013, background): “Using network pharmacology to investigate CHM pharmacological effects and drug targets, attention should be paid to degree centrality [84], betweenness centrality [85], and bridging centrality [86].”
Network pharmacology: the next paradigm in drug discovery. (2008, background): “However, the hypothesis that protein function relates to network topology has been strengthened by recent work that has refined the relationship between network topology and system function by focusing on 'betweenness centrality' (the number of nonredundant shortest paths traveling through a nod”
Centrality measure in graphs (2010, background): “Now an even more widespread interest is developing, for applications: in electrical circuits [29,30] in molecular bonding patterns [31–33]inbiochemicalreactionnetworks[34, 35 ]inecologicalorpopulation-genetics migration patterns [36] and perhaps in food-webs [37].”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, methodology): “Later more global network measures, such as bottlenecks or more globally central proteins were also shown to contribute to the determination of essential nodes (Chin & Samanta, 2003; Estrada, 2006; Yu et al., 2007b; Missiuro et al., 2009; Li et al., 2011a).”