Drosophila melanogaster is a proven model system for many aspects of human biology. Here we present a two-hybrid-based protein-interaction map of the fly proteome. A total of 10,623 predicted transcripts were isolated and screened against standard and normalized complementary DNA libraries to produce a draft map of 7048 proteins and 20,405 interactions. A computational method of rating two-hybrid interaction confidence was developed to refine this draft map to a higher confidence map of 4679 proteins and 4780 interactions. Statistical modeling of the network showed two levels of organization: a short-range organization, presumably corresponding to multiprotein complexes, and a more global organization, presumably corresponding to intercomplex connections. The network recapitulated known pathways, extended pathways, and uncovered previously unknown pathway components. This map serves as a starting point for a systems biology modeling of multicellular organisms, including humans.

Detailed observations of transcriptional, translational, and post-translational events in the human brain are essential to improving our understanding of its development, function, and vulnerability to disease. Here, we exploited label-free quantitative tandem mass-spectrometry proteomics to create an in-depth proteomic survey of adult human brain regions. Integration of protein data with existing whole-transcriptome sequencing (RNA-seq) from the BrainSpan project revealed varied patterns of protein:RNA relationships with generally increased magnitudes of protein abundance differences between brain regions compared to RNA. Many of the differences amplified in protein data were reflective of cyto-architectural and functional variation between brain regions. Comparing structurally similar cortical regions revealed significant differences in the abundance of receptor-associated and resident plasma membrane proteins that were not readily observed in the RNA expression data.

This study shows that sPRM is a promising approach to rapidly screen large numbers of proteins in urine in order to provide earlier diagnosis and potentially better understand the pathogenesis of ADPKD development and progression.