» Articles » PMID: 35246154

Reconstruction and Analysis of a Large-scale Binary Ras-effector Signaling Network

Overview
Publisher Biomed Central
Date 2022 Mar 5
PMID 35246154
Authors
Affiliations
Soon will be listed here.
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. Video Abstract.

Citing Articles

KRAS Mutation Subtypes and Their Association with Other Driver Mutations in Oncogenic Pathways.

Mondal K, Posa M, Shenoy R, Roychoudhury S Cells. 2024; 13(14.

PMID: 39056802 PMC: 11274496. DOI: 10.3390/cells13141221.


Functional and structural insights into RAS effector proteins.

Mozzarelli A, Simanshu D, Castel P Mol Cell. 2024; 84(15):2807-2821.

PMID: 39025071 PMC: 11316660. DOI: 10.1016/j.molcel.2024.06.027.


K-RAS Is…Complicated.

Clark G Cancers (Basel). 2023; 15(22).

PMID: 38001740 PMC: 10670387. DOI: 10.3390/cancers15225480.


Analysis of context-specific KRAS-effector (sub)complexes in Caco-2 cells.

Ternet C, Junk P, Sevrin T, Catozzi S, Wahlen E, Heldin J Life Sci Alliance. 2023; 6(5).

PMID: 36894174 PMC: 9998658. DOI: 10.26508/lsa.202201670.


Whole-cell energy modeling reveals quantitative changes of predicted energy flows in RAS mutant cancer cell lines.

Sevrin T, Strasser L, Ternet C, Junk P, Caffarini M, Prins S iScience. 2023; 26(2):105931.

PMID: 36711246 PMC: 9874014. DOI: 10.1016/j.isci.2023.105931.


References
1.
Morris J, Knudsen G, Verschueren E, Johnson J, Cimermancic P, Greninger A . Affinity purification-mass spectrometry and network analysis to understand protein-protein interactions. Nat Protoc. 2014; 9(11):2539-54. PMC: 4332878. DOI: 10.1038/nprot.2014.164. View

2.
Tian Y, Hou Y, Zhou X, Cheng H, Zhou R . Tumor suppressor RASSF1A promoter: p53 binding and methylation. PLoS One. 2011; 6(2):e17017. PMC: 3045384. DOI: 10.1371/journal.pone.0017017. View

3.
Roux K, Kim D, Burke B, May D . BioID: A Screen for Protein-Protein Interactions. Curr Protoc Protein Sci. 2018; 91:19.23.1-19.23.15. PMC: 6028010. DOI: 10.1002/cpps.51. View

4.
Xu L, Lubkov V, Taylor L, Bar-Sagi D . Feedback regulation of Ras signaling by Rabex-5-mediated ubiquitination. Curr Biol. 2010; 20(15):1372-7. PMC: 3436604. DOI: 10.1016/j.cub.2010.06.051. View

5.
Rowland M, Fontana W, Deeds E . Crosstalk and competition in signaling networks. Biophys J. 2013; 103(11):2389-98. PMC: 3514525. DOI: 10.1016/j.bpj.2012.10.006. View