Identifying Early Warning Signals for the Sudden Transition from Mild to Severe Tobacco Etch Disease by Dynamical Network Biomarkers
1
Instituto de Biología Integrativa de Sistemas (I2SysBio), CSIC-Universitat de València, Paterna, 46980 València, Spain
2
Instituto de Biología Molecular y Celular de Plantas (IBMCP), CSIC-Universitat Politècnica de València, 46022 València, Spain
3
The Santa Fe Institute, Santa Fe, NM 87501, USA
*
Author to whom correspondence should be addressed.
Viruses 2020, 12(1), 16; https://doi.org/10.3390/v12010016
Received: 26 November 2019 / Revised: 17 December 2019 / Accepted: 19 December 2019 / Published: 20 December 2019
(This article belongs to the Special Issue The Complexity of the Potyviral Interaction Network)
Complex systems exhibit critical thresholds at which they transition among alternative phases. Complex systems theory has been applied to analyze disease progression, distinguishing three stages along progression: (i) a normal noninfected state; (ii) a predisease state, in which the host is infected and responds and therapeutic interventions could still be effective; and (iii) an irreversible state, where the system is seriously threatened. The dynamical network biomarker (DNB) theory sought for early warnings of the transition from health to disease. Such DNBs might range from individual genes to complex structures in transcriptional regulatory or protein–protein interaction networks. Here, we revisit transcriptomic data obtained during infection of tobacco plants with tobacco etch potyvirus to identify DNBs signaling the transition from mild/reversible to severe/irreversible disease. We identified genes showing a sudden transition in expression along disease categories. Some of these genes cluster in modules that show the properties of DNBs. These modules contain both genes known to be involved in response to pathogens (e.g., ADH2, CYP19, ERF1, KAB1, LAP1, MBF1C, MYB58, PR1, or TPS5) and other genes not previously related to biotic stress responses (e.g., ABCI6, BBX21, NAP1, OSM34, or ZPN1).
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Keywords:
complex systems; DNB; phase transitions; plant-virus interaction; potyvirus; protein-protein interaction networks; response to infection; systems biology; tobacco etch virus
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Externally hosted supplementary file 1
Doi: 10.25833/03zt-f819
Link: https://mynotebook.labarchives.com/share/sfelena/MzIuNXwxMzc4ODcvMjUvVHJlZU5vZGUvMjA2MDQxODQ1OHw4Mi41
Description: Table S1: List of genes showing a significant biphasic behavior in gene expression. Table S2: List of enriched functional categories among genes listed in Supplementary Table S1. File S1: Computations of I* and list of genes for each PPIN-based DNBs (PPINDNB). File S2: Computation of I* and list of genes for each TRN-based DNBs (TRNDNB)
MDPI and ACS Style
Tarazona, A.; Forment, J.; Elena, S.F. Identifying Early Warning Signals for the Sudden Transition from Mild to Severe Tobacco Etch Disease by Dynamical Network Biomarkers. Viruses 2020, 12, 16. https://doi.org/10.3390/v12010016
AMA Style
Tarazona A, Forment J, Elena SF. Identifying Early Warning Signals for the Sudden Transition from Mild to Severe Tobacco Etch Disease by Dynamical Network Biomarkers. Viruses. 2020; 12(1):16. https://doi.org/10.3390/v12010016
Chicago/Turabian StyleTarazona, Adrián; Forment, Javier; Elena, Santiago F. 2020. "Identifying Early Warning Signals for the Sudden Transition from Mild to Severe Tobacco Etch Disease by Dynamical Network Biomarkers" Viruses 12, no. 1: 16. https://doi.org/10.3390/v12010016
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