Local and global features of genetic networks supporting a phenotypic switch

被引:2
|
作者
Shomar, Aseel [1 ,2 ]
Barak, Omri [2 ,3 ]
Brenner, Naama [1 ,2 ]
机构
[1] Technion, Dept Chem Engn, Haifa, Israel
[2] Technion, Lorry Lokey Ctr Life Sci & Engn, Network Biol Res Labs, Haifa, Israel
[3] Technion, Rappaport Fac Med, Haifa, Israel
来源
PLOS ONE | 2020年 / 15卷 / 09期
关键词
EPITHELIAL-MESENCHYMAL TRANSITION; NEGATIVE FEEDBACK LOOP; BOOLEAN NETWORK; PLASTICITY; MODELS; ZEB1;
D O I
10.1371/journal.pone.0238433
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Phenotypic switches are associated with alterations in the cell's gene expression profile and are vital to many aspects of biology. Previous studies have identified local motifs of the genetic regulatory network that could underlie such switches. Recent advancements allowed the study of networks at the global, many-gene, level; however, the relationship between the local and global scales in giving rise to phenotypic switches remains elusive. In this work, we studied the epithelial-mesenchymal transition (EMT) using a gene regulatory network model. This model supports two clusters of stable steady-states identified with the epithelial and mesenchymal phenotypes, and a range of intermediate less stable hybrid states, whose importance in cancer has been recently highlighted. Using an array of network perturbations and quantifying the resulting landscape, we investigated how features of the network at different levels give rise to these landscape properties. We found that local connectivity patterns affect the landscape in a mostly incremental manner; in particular, a specific previously identified double-negative feedback motif is not required when embedded in the full network, because the landscape is maintained at a global level. Nevertheless, despite the distributed nature of the switch, it is possible to find combinations of a few local changes that disrupt it. At the level of network architecture, we identified a crucial role for peripheral genes that act as incoming signals to the network in creating clusters of states. Such incoming signals are a signature of modularity and are expected to appear also in other biological networks. Hybrid states between epithelial and mesenchymal arise in the model due to barriers in the interaction between genes, causing hysteresis at all connections. Our results suggest emergent switches can neither be pinpointed to local motifs, nor do they arise as typical properties of random network ensembles. Rather, they arise through an interplay between the nature of local interactions, and the core-periphery structure induced by the modularity of the cell.
引用
收藏
页数:19
相关论文
共 50 条
  • [31] Video Summarization with Global and Local Features
    Guan, Genliang
    Wang, Zhiyong
    Yu, Kaimin
    Mei, Shaohui
    He, Mingyi
    Feng, Dagan
    [J]. 2012 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO WORKSHOPS (ICMEW), 2012, : 570 - 575
  • [32] Stochastic Stabilization of Phenotypic States: The Genetic Bistable Switch as a Case Study
    Weber, Marc
    Buceta, Javier
    [J]. PLOS ONE, 2013, 8 (09):
  • [33] A Scheme for Supporting Global and Local Mobility Management in NGN
    Yu, Myoung Ju
    Kim, Hyun Jong
    Choi, Won Seok
    Choi, Seong Gon
    [J]. 12TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY: ICT FOR GREEN GROWTH AND SUSTAINABLE DEVELOPMENT, VOLS 1 AND 2, 2010, : 190 - 194
  • [34] A Multi-tree Genetic Programming Representation for Melanoma Detection Using Local and Global Features
    Ul Ain, Qurrat
    Al-Sahaf, Harith
    Xue, Bing
    Zhang, Mengjie
    [J]. AI 2018: ADVANCES IN ARTIFICIAL INTELLIGENCE, 2018, 11320 : 111 - 123
  • [35] Flipping the Switch on Local Exploration: Genetic Algorithms with Reversals
    Grover, Ankit
    Yadav, Vaishali
    Alicea, Bradly
    [J]. THIRD CONGRESS ON INTELLIGENT SYSTEMS, CIS 2022, VOL 1, 2023, 608 : 719 - 734
  • [36] Learning global and local features using graph neural networks for person re-identification
    Zhang, Ji
    Ainam, Jean-Paul
    Song, Wenai
    Zhao, Li-hui
    Wang, Xin
    Li, Hongzhou
    [J]. SIGNAL PROCESSING-IMAGE COMMUNICATION, 2022, 107
  • [37] Preventing stenosis by local inhibition of KCa3.1 -: A finger on the phenotypic switch
    Lounsbury, Karen M.
    [J]. ARTERIOSCLEROSIS THROMBOSIS AND VASCULAR BIOLOGY, 2008, 28 (06) : 1036 - 1038
  • [38] Global and local modelling in RBF networks
    Herrera, L. J.
    Pomares, H.
    Rojas, I.
    Guillen, A.
    Rubio, G.
    Urquiza, J.
    [J]. NEUROCOMPUTING, 2011, 74 (16) : 2594 - 2602
  • [39] Knowledge networks in local and global space
    Lorentzen, Anne
    [J]. ENTREPRENEURSHIP AND REGIONAL DEVELOPMENT, 2008, 20 (06): : 533 - 545
  • [40] Local modeling of global interactome networks
    Scholtens, D
    Vidal, M
    Gentleman, R
    [J]. BIOINFORMATICS, 2005, 21 (17) : 3548 - 3557