A systems biology approach to the evolution of plant–virus interactions

Abstract

ElsevierElena Fito, SF.; Carrera, J.; Rodrigo, J. (2011). A systems biology approach to the evolution of plant-virus interactions. Current Opinion in Plant Biology. 14(4):372-377. doi:10.1016/j.pbi.2011.03.013. Omic approaches to the analysis of plant-virus interactions are becoming increasingly popular. These types of data, in combination with models of interaction networks, will aid in revealing not only host components that are important for the virus life cycle, but also general patterns about the way in which different viruses manipulate host regulation of gene expression for their own benefit and possible mechanisms by which viruses evade host defenses. Here, we review studies identifying host genes regulated by viruses and discuss how these genes integrate in host regulatory and interaction networks, with a particular focus on the physical properties of these networks. A systems biology approach to the evolution of plant-virus interactions The systems biology approachGenomic tools have allowed assessment of gene expression at a genome-wide scale, providing unprecedented views of the host-virus interaction. To make use of all of the information contained in these large data sets, however, it is necessary to use computational and mathematical tools to disentangle the interactions between the molecular components of both biological entities and to identify how these interactions determine the outcome of the infection [1,2••], which is known as the field of genomic systems biology (GSB). GSB is a top-down approach that takes advantage of the recent development of high-throughput experimental techniques for obtaining omic data, and constitutes the antithesis of the reductionist paradigm (with a bottom-up perspective) that has been dominating molecular biology. The GSB approach consists of cycling between the generation of experimental data and modeling by means of reverse-engineering techniques to propose testable hypotheses about biological systems, experimental validation of these hypotheses and quantification of the relevant model parameters, and then using the newly acquired quantitative description to refine the computational model and finally make predictions of the system behavior [3,4•].To complete its infectious cycle, a few components of a virus, including its nucleic acids and encoded proteins, must establish multiple and complex interactions not only among themselves [5,6•,7,8] but also with a myriad of components of the host cell [9,10•,11]. The outcome of all these interactions is that the plant controls the spread of viral infection or, alternatively, the virus overcomes the host defenses and establishes a productive infection that may or may not be associated with the development of symptoms. While the GSB approach is being extensively used in the analysis of animal virus interactions (e.g. hepatitis C, human immunodeficiency, yellow fever, influenza A and herpesviruses), plant virology has not yet benefitted to the same extent, and the most relevant studies in the field generally apply some t...

Characterization of a Viral Synergism in the MonocotBrachypodium distachyonReveals Distinctly Altered Host Molecular Processes Associated with Disease

“…8) with previously known dicot-infecting plant viruses (Whitham et al, 2003;Ascencio-Ibáñez et al, 2008;García-Marcos et al, 2009;Elena et al, 2011;Hanssen et al, 2011) revealed several distinctive features of virus-host interactions of monocots. PMV and PMV+SPMV infection prominently triggered SA-mediated defense responses, a response that appears conserved with several dicot host:virus interactions (Murphy et al, 1999;Kachroo et al, 2000;Whitham et al, 2003Whitham et al, , 2006Huang et al, 2005;Ascencio-Ibáñez et al, 2008;Hanssen et al, 2011;Pacheco et al, 2012).…”

“…Because high-quality genome sequence information is available for Arabidopsis, and because antiviral defenses are well studied in that model (Whitham et al, 2003;Ascencio-Ibáñez et al, 2008;García-Marcos et al, 2009;Elena et al, 2011;Hanssen et al, 2011), for our subsequent analysis, we chose to compare our transcriptome results with Arabidopsis-virus responses. Moreover, such a comparison allows us to compare and contrast antiviral responses in monocot and dicot plants.…”

“…Model plant species, such as Arabidopsis (Arabidopsis thaliana) and Nicotiana benthamiana, have been crucial in determining the mechanics of antiviral defenses. Genome-wide expression studies in these model plants identified networks of genes affected commonly by several plant viruses, whereby diverse DNA and RNA viruses alter genes in primary and secondary metabolism, detoxification, cell wall remodeling, and defense responses (Whitham et al, 2003(Whitham et al, , 2006Ascencio-Ibáñez et al, 2008;García-Marcos et al, 2009;Elena et al, 2011;Hanssen et al, 2011;Postnikova and Nemchinov, 2012). At the cellular level, specific recognition of viral nucleic acids or viral proteins by host resistance gene products inhibits viral replication or accumulation (Kohm et al, 1993;Bendahmane et al, 1999;Ishibashi et al, 2007).…”

Plant Metabolic Modeling: Achieving New Insight into Metabolism and Metabolic Engineering

“…The applications include analyses of the abiotic stress response (Cramer et al, 2011), of the host/pathogen interaction (Elena et al, 2011;Pritchard and Birch, 2011), of nitrogen nutrition (Gutiérrez, 2012), and of general metabolism (Sweetlove et al, 2003).…”

Network Analysis and Modeling in Systems Biology

“…An excellent and updated review on topology of interaction networks may be found in (Winterbach et al 2013). Some studies have dealt with the topological properties and features of PPINs (Albert and Barabási 2002;Pržulj, Wigle, and Jurisica 2004;Pržulj 2011;Yook, Oltvai, and Barabási 2004), however just a few have focused on viral PPINs (Elena, Carrera, and Rodrigo 2011;Elena and Rodrigo 2012;Fossum et al 2009). Viral infection is a complex process and it requires a systems approach to be fully described.…”