Viruses are the most abundant biological entity on earth. However, the role of viruses within ecosystems are poorly understood. As an attempt to better understand the role and functional relationships of viruses and their influence on rumen bacterial communities, we investigated viral and bacterial community relationships using culture independent metagenomic approaches under 4 different dietary conditions (55% corn silage, 27% condensed distillers plus solubles (CDS), 40% modified distillers grains plus solubles (MDGS), corn based control diet) in a Latin-square design with 5 fistulated steers. Rumen samples were collected after total rumen evacuation and mixing following a 21-d adaptation period. Tangential flow filtration was performed to enrich for viral particles from the rumen sample. The enriched viral metagenome and the total metagenome were sequenced using the Ion Torrent Personnel Genome Machine (PGM) to identify species composition, interactions between viruses and bacteria, and to identify the role of virus auxiliary genes within rumen metabolism. The metagenome analysis displayed the total metagenome contained 118 differentially abundant genes and the viral metagenome 309 differentially abundant genes based on diet. Interestingly, the metagenomes and metaviromes contained different metabolic profiles. To better understand the role of the virome in ecosystem function, we mapped the genes identified to a community metabolic network. Using the metabolic networks we compared topological features of enzyme nodes to identify the roles of differentially abundant genes. The nodes that were differentially abundant in the total metagenome and virome had significantly higher betweenness centrality (P < 0.05) and a lower average shortest path length compared with non-differential genes in the network (P < 0.05). In addition, differential viral genes had a significantly higher total degree and in-degree compared with non-differential genes and the differential genes in the total metagenome (P < 0.05). Currently, we are applying network approaches to understand the ecological roles of viruses within energy metabolism in the rumen environment.