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Author (up) Timmermann, T.; Gonzalez, B.; Ruz, G.A. doi  openurl
  Title Reconstruction of a gene regulatory network of the induced systemic resistance defense response in Arabidopsis using boolean networks Type
  Year 2020 Publication Bmc Bioinformatics Abbreviated Journal BMC Bioinformatics  
  Volume 21 Issue 1 Pages 16 pp  
  Keywords Boolean networks; Differential evolution; Gene regulatory networks; Induced systemic resistance; Paraburkholderia phytofirmans; Pseudomonas syringae  
  Abstract Background An important process for plant survival is the immune system. The induced systemic resistance (ISR) triggered by beneficial microbes is an important cost-effective defense mechanism by which plants are primed to an eventual pathogen attack. Defense mechanisms such as ISR depend on an accurate and context-specific regulation of gene expression. Interactions between genes and their products give rise to complex circuits known as gene regulatory networks (GRNs). Here, we explore the regulatory mechanism of the ISR defense response triggered by the beneficial bacterium Paraburkholderia phytofirmans PsJN in Arabidopsis thaliana plants infected with Pseudomonas syringae DC3000. To achieve this, a GRN underlying the ISR response was inferred using gene expression time-series data of certain defense-related genes, differential evolution, and threshold Boolean networks. Results One thousand threshold Boolean networks were inferred that met the restriction of the desired dynamics. From these networks, a consensus network was obtained that helped to find plausible interactions between the genes. A representative network was selected from the consensus network and biological restrictions were applied to it. The dynamics of the selected network showed that the largest attractor, a limit cycle of length 3, represents the final stage of the defense response (12, 18, and 24 h). Also, the structural robustness of the GRN was studied through the networks' attractors. Conclusions A computational intelligence approach was designed to reconstruct a GRN underlying the ISR defense response in plants using gene expression time-series data of A. thaliana colonized by P. phytofirmans PsJN and subsequently infected with P. syringae DC3000. Using differential evolution, 1000 GRNs from time-series data were successfully inferred. Through the study of the network dynamics of the selected GRN, it can be concluded that it is structurally robust since three mutations were necessary to completely disarm the Boolean trajectory that represents the biological data. The proposed method to reconstruct GRNs is general and can be used to infer other biologically relevant networks to formulate new biological hypotheses.  
  Address [Timmermann, Tania; Gonzalez, Bernardo; Ruz, Gonzalo A.] Univ Adolfo Ibanez, Fac Ingn & Ciencias, Lab Bioingn, Santiago, Chile, Email:  
  Corporate Author Thesis  
  Publisher Bmc Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1471-2105 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000529043500003 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 1143  
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