A Structure-Informed Atlas of Human-Virus Interactions.

While knowledge of protein-protein interactions (PPIs) is critical for understanding virus-host relationships, limitations on the scalability of high-throughput methods have hampered their identification beyond a number of well-studied viruses. Here, we implement an in silico computational framework (pathogen host interactome prediction using structure similarity [P-HIPSTer]) that employs structural information to predict ∼282,000 pan viral-human PPIs with an experimental validation rate of ∼76%. In addition to rediscovering known biology, P-HIPSTer has yielded a series of new findings: the discovery of shared and unique machinery employed across human-infecting viruses, a likely role for ZIKV-ESR1 interactions in modulating viral replication, the identification of PPIs that discriminate between human papilloma viruses (HPVs) with high and low oncogenic potential, and a structure-enabled history of evolutionary selective pressure imposed on the human proteome.

Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform.

Background: The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.

Analysis of the coding genome of diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the most common form of human lymphoma. Although a number of structural alterations have been associated with the pathogenesis of this malignancy, the full spectrum of genetic lesions that are present in the DLBCL genome, and therefore the identity of dysregulated cellular pathways, remains unknown. By combining next-generation sequencing and copy number analysis, we show that the DLBCL coding genome contains, on average, more than 30 clonally represented gene alterations per case.