Abstract
Systems biology approaches are required to advance our understanding of virus–host interactions, how these interactions cause disease and, ultimately, how to improve diagnostics, therapeutics and vaccines.
Over the past decade, the field of systems virology has evolved from using first-generation microarrays to the integration of multidimensional data sets. This has resulted in significant findings, including the identification of gene expression signatures that are predictive of viral pathogenesis and vaccine efficacy, insights into how viruses disrupt cellular metabolism, and the mapping of virus–host interactomes.
To fulfil its initial promise of revolutionizing our understanding of virus–host interactions, the field of systems virology must move beyond just the listing of molecules that are differentially expressed following viral infection; it must now look to define the relationships between key host molecules and their interactions with viral components.
Several key computational challenges must be addressed in order to move into this new phase of systems virology, including consideration of nonlinear relationships such as the dynamics of the system, the integration of multidimensional data sets and the identification of causal relationships.
Virologists, computer scientists and mathematicians must combine their skills and expertise in applying systems approaches to untangle the complex question of how viruses kill.
Katze and colleagues provide an overview of the evolution of systems virology and the insights obtained from using such methodologies to study virus–host interactions. Combining systems, mathematical and computational approaches with traditional virology research will offer a better understanding of how viruses cause disease and will help in the development of therapeutics.
High-throughput molecular profiling and computational biology are changing the face of virology, providing a new appreciation of the importance of the host in viral pathogenesis and offering unprecedented opportunities for better diagnostics, therapeutics and vaccines. Here, we provide a snapshot of the evolution of systems virology, from global gene expression profiling and signatures of disease outcome, to geometry-based computational methods that promise to yield novel therapeutic targets, personalized medicine and a deeper understanding of how viruses cause disease. To realize these goals, pipettes and Petri dishes need to join forces with the powers of mathematics and computational biology.
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