title: Computational design of host transcription-factors sets whose misregulation mimics the transcriptomic effect of viral infections.
abstract: The molecular mechanisms underlying viral pathogenesis are yet poorly understood owed to the large number of factors involved and the complexity of their interactions. Could we identify a minimal set of host transcription factors (TF) whose misregulation would result in the transcriptional profile characteristic of infected cells in absence of the virus? How many of such sets exist? Are all orthogonal or share critical TFs involved in specific biological functions? We have developed a computational methodology that uses a quantitative model of the transcriptional regulatory network (TRN) of Arabidopsis thaliana to explore the landscape of all possible re-engineered TRNs whose transcriptomic profiles mimic those observed in infected plants. We found core sets containing between six and 34 TFs, depending on the virus, whose in silico knockout or overexpression in the TRN resulted in transcriptional profiles that minimally deviate from those observed in infected plants.
authors.affiliation: Instituto de Biología Molecular y Celular de Plantas, Consejo Superior de Investigaciones Científicas-UPV, Campus UPV CPI 8E, Ingeniero Fausto Elio s/n, 46022 València, Spain.
authors.forename: Javier
authors.initials: J
authors.lastname: Carrera
authors.forename: Santiago F
authors.initials: SF
authors.lastname: Elena
mesh_terms: D017360:Arabidopsis / Q000235:genetics / Q000378:metabolism / Q000821:virology; D029681:Arabidopsis Proteins / Q000235:genetics / Q000378:metabolism; D019295:Computational Biology / Q000379:methods; D008954:Models, Biological; D010935:Plant Diseases; D010942:Plant Viruses / Q000502:physiology*; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism; D059467:Transcriptome
chemical_list: D029681:Arabidopsis Proteins; D014157:Transcription Factors