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For over a decade, studies of messenger RNA regulation have revealed an unprecedented level of connectivity between the RNA pool and global gene expression. These connections are underpinned by a vast array of RNA elements that coordinate RNA-protein and RNA-RNA interactions, each directing mRNA fate from transcription to translation. Consequently, viruses have evolved an arsenal of strategies to target these RNA features and ultimately take control of the pathways they influence, and these strategies contribute to the global shutdown of the host gene expression machinery known as "Host Shutoff". This takeover of the host cell is mechanistically orchestrated by a number of non-homologous virally encoded endoribonucleases. Recent large-scale screens estimate that over 70 % of the host transcriptome is decimated by the expression of these viral nucleases. While this takeover strategy seems extraordinarily well conserved, each viral endonuclease has evolved to target distinct mRNA elements. Herein, we will explore each of these RNA structures/sequence features that render messenger RNA susceptible or resistant to viral endonuclease cleavage. By further understanding these targeting and escape mechanisms we will continue to unravel untold depths of cellular RNA regulation that further underscores the integral relationship between RNA fate and the fate of the cell. [ABSTRACT FROM AUTHOR]

Abstract: Comparative interactomics is a strategy for inferring potential interactions among orthologous proteins or “interologs”. Herein we focus, in contrast to standard homology-based inference, on the divergence of protein interaction profiles among closely related organisms, showing that the approach can correlate specific traits to phenotypic differences. As a model, this new comparative interactomic approach was applied at a large scale to human papillomaviruses (HPVs) proteins. The oncogenic potential of HPVs is mainly determined by the E6 and E7 early proteins. We have mapped and overlapped the virus–host protein interaction networks of E6 and E7 proteins from 11 distinct HPV genotypes, selected for their different tropisms and pathologies. We generated robust and comprehensive datasets by combining two orthogonal protein interaction assays: yeast two-hybrid (Y2H), and our recently described “high-throughput Gaussia princeps protein complementation assay” (HT-GPCA). HT-GPCA detects protein interaction by measuring the interaction-mediated reconstitution of activity of a split G. princeps luciferase. Hierarchical clustering of interaction profiles recapitulated HPV phylogeny and was used to correlate specific virus–host interaction profiles with pathological traits, reflecting the distinct carcinogenic potentials of different HPVs. This comparative interactomics constitutes a reliable and powerful strategy to decipher molecular relationships in virtually any combination of microorganism–host interactions. [Copyright &y& Elsevier]