Cell Communication and Signaling (Mar 2022)

Reconstruction and analysis of a large-scale binary Ras-effector signaling network

  • Simona Catozzi,
  • Camille Ternet,
  • Alize Gourrege,
  • Kieran Wynne,
  • Giorgio Oliviero,
  • Christina Kiel

DOI
https://doi.org/10.1186/s12964-022-00823-5
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 19

Abstract

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Abstract Background Ras is a key cellular signaling hub that controls numerous cell fates via multiple downstream effector pathways. While pathways downstream of effectors such as Raf, PI3K and RalGDS are extensively described in the literature, how other effectors signal downstream of Ras is often still enigmatic. Methods A comprehensive and unbiased Ras-effector network was reconstructed downstream of 43 effector proteins (converging onto 12 effector classes) using public pathway and protein–protein interaction (PPI) databases. The output is an oriented graph of pairwise interactions defining a 3-layer signaling network downstream of Ras. The 2290 proteins comprising the network were studied for their implication in signaling crosstalk and feedbacks, their subcellular localizations, and their cellular functions. Results The final Ras-effector network consists of 2290 proteins that are connected via 19,080 binary PPIs, increasingly distributed across the downstream layers, with 441 PPIs in layer 1, 1660 in layer 2, and 16,979 in layer 3. We identified a high level of crosstalk among proteins of the 12 effector classes. A class-specific Ras sub-network was generated in CellDesigner (.xml file) and a functional enrichment analysis thereof shows that 58% of the processes have previously been associated to a respective effector pathway, with the remaining providing insights into novel and unexplored functions of specific effector pathways. Conclusions Our large-scale and cell general Ras-effector network is a crucial steppingstone towards defining the network boundaries. It constitutes a ‘reference interactome’ and can be contextualized for specific conditions, e.g. different cell types or biopsy material obtained from cancer patients. Further, it can serve as a basis for elucidating systems properties, such as input–output relationships, crosstalk, and pathway redundancy. Graphical abstract Video Abstract.

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