ArticleBMC systems biology2017
Delineating functional principles of the bow tie structure of a kinase-phosphatase network in the budding yeast.
Article in BMC systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Scalable phosphotyrosine enrichment with SH2 superbinder enables deep profiling of EGF responses.The EMBO journal · 2026Article
- R2HaPpY: Rapid-robust phosphotyrosine peptide enrichment using HaloTag-Src SH2 pY superbinder.bioRxiv : the preprint server for biology · 2025Article
- Expression, Purification, and Preliminary Characterization of Putative Protein Tyrosine Phosphatase Oca1.Protein and peptide letters · 2025Article
- Revisiting the evolution of bow-tie architecture in signaling networks.NPJ systems biology and applications · 2024Article
- Bow-tie architectures in biological and artificial neural networks: Implications for network evolution and assay design.iScience · 2023Article
- Protein phosphatases of Saccharomyces cerevisiae.Current genetics · 2019Review
- A Link Between Alzheimer's and Type II Diabetes Mellitus? CaBioEssays : news and reviews in molecular, cellular and developmental biology · 2018Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
backgroundKinases and phosphatases (KP) form complex self-regulating networks essential for cellular signal processing. In spite of having a wealth of data about interactions among KPs and their substrates, we have very limited models of the structures of the directed networks they form and consequently our ability to formulate hypotheses about how their structure determines the flow of information in these networks is restricted.
resultsWe assembled and studied the largest bona fide kinase-phosphatase network (KP-Net) known to date for the yeast Saccharomyces cerevisiae. Application of the vertex sort (VS) algorithm on the KP-Net allowed us to elucidate its hierarchical structure in which nodes are sorted into top, core and bottom layers, forming a bow tie structure with a strongly connected core layer. Surprisingly, phosphatases tend to sort into the top layer, implying they are less regulated by phosphorylation than kinases. Superposition of the widest range of KP biological properties over the KP-Net hierarchy shows that core layer KPs: (i), receive the largest number of inputs; (ii), form bottlenecks implicated in multiple pathways and in decision-making; (iii), and are among the most regulated KPs both temporally and spatially. Moreover, top layer KPs are more abundant and less noisy than those in the bottom layer. Finally, we showed that the VS algorithm depends on node degrees without biasing the biological results of the sorted network. The VS algorithm is available as an R package ( https://cran.r-project.org/web/packages/VertexSort/index.html ).
conclusionsThe KP-Net model we propose possesses a bow tie hierarchical structure in which the top layer appears to ensure highest fidelity and the core layer appears to mediate signal integration and cell state-dependent signal interpretation. Our model of the yeast KP-Net provides both functional insight into its organization as we understand today and a framework for future investigation of information processing in yeast and eukaryotes in general.
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