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Generating reference maps of the interactome networks underlying most cellular functions can greatly illuminate genetic studies by providing a protein-centric approach to finding new components of existing pathways, complexes, and processes. Here, we applied state-of-the-art experimental and bioinformatics methods to identify high-confidence binary protein-protein interactions (PPIs) for Drosophila melanogaster. We performed four all-by-all yeast two-hybrid (Y2H) screens of >10,000 Drosophila proteins, resulting in the ‘FlyBi’ dataset of 8,723 PPIs among 2,939 proteins. As part of this effort, we tested subsets of our data and data from previous PPI datasets using an orthogonal assay, which allowed us to normalize data quality across datasets. Next, we integrated our FlyBi data with previous PPI data, resulting in an expanded, high-confidence binary Drosophila reference interaction network, DroRI, comprising 17,232 interactions among 6,511 proteins. These data are accessible through the Molecular Interaction Search Tool (MIST) and other databases. To assess the utility of the PPI resource, we used novel interactions from the FlyBi dataset to generate an autophagy interaction network that we validated in vivo using two different autophagy-related assays. We found that deformed wings (dwg) encodes a protein that is both a regulator and a target of autophagy. Altogether, the resources generated in this project provide a strong foundation for building high-confidence new hypotheses regarding protein networks and function.

SummaryHundreds of different protein complexes that perform important functions across all cellular processes, collectively comprising the “complexome” of an organism, have been identified1. However, less is known about the fraction of the interactome that exists outside the complexome, in the “outer-complexome”. To investigate features of “inner”- versus outer-complexome organisation in yeast, we generated a high-quality atlas of binary protein-protein interactions (PPIs), combining three previous maps2–4 and a new reference all-by-all binary interactome map. A greater proportion of interactions in our map are in the outer-complexome, in comparison to those found by affinity purification followed by mass spectrometry5–7 or in literature curated datasets8–11. In addition, recent advances in deep learning predictions of PPI structures12 mirror the existing experimentally resolved structures in being largely focused on the inner complexome and missing most interactions in the outer-complexome. Our new PPI network suggests that the outer-complexome contains considerably more PPIs than the inner-complexome, and integration with functional similarity networks13–15 reveals that interactions in the inner-complexome are highly detectable and correspond to pairs of proteins with high functional similarity, while proteins connected by more transient, harder-to-detect interactions in the outer-complexome, exhibit higher functional heterogeneity.

SUMMARYWhile viral infections are known to hijack the transcription and translation of the host cell, the extent to which encoded viral proteins coordinate these perturbations remains unclear. Here we demonstrate that the oncoviral proteins Tax and HBZ interact with specific components of the spliceosome machinery, including the U2 auxiliary factor large subunit (U2AF2), and the complementary factor for APOBEC-1 (A1CF), respectively. Tax and HBZ perturb the splicing landscape in T-cells by altering cassette exons in opposing manners, with Tax inducing exon inclusion while HBZ induces exon exclusion. Among Tax- and HBZ-dependent splicing changes, we identify events that are also altered in Adult T cell leukemia (ATL) patients, and in well-known cancer census genes. Our interactome mapping approach, applicable to other viral oncogenes, has identified spliceosome perturbation as a novel mechanism coordinately used by Tax and HBZ to reprogram the transcriptome.HighlightsTax and HBZ interact with RNA-binding proteins as well as transcription factorsHTLV-1 encoded proteins Tax and HBZ alter the splicing landscape in T-cellsTax and HBZ expression affect alternative splicing of 33 and 63 cancer genes, respectivelyOpposing roles for Tax and HBZ in deregulation of gene expressionGraphical abstract

et al., Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype–phenotype relationships1,2. Here we present a human ‘all-by-all’ reference interactome map of human binary protein interactions, or ‘HuRI’. With approximately 53,000 protein–protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome3, transcriptome4 and proteome5 data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein–protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes., This work was primarily supported by the National Institutes of Health (NIH) National Human Genome Research Institute (NHGRI) grant U41HG001715 (M.V., F.P.R., D.E.H., M.A.C., G.D.B. and J.T.) with additional support from NIH grants P50HG004233 (M.V. and F.P.R.), U01HL098166 (M.V.), U01HG007690 (M.V.), R01GM109199 (M.A.C.), Canadian Institute for Health Research (CIHR) Foundation Grants (F.P.R. and J. Rak), the Canada Excellence Research Chairs Program (F.P.R.) and an American Heart Association grant 15CVGPS23430000 (M.V.). D.-K.K. was supported by a Banting Postdoctoral Fellowship through the Natural Sciences and Engineering Research Council (NSERC) of Canada and by the Basic Science Research Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Education (2017R1A6A3A03004385). C. Pons was supported by a Ramon Cajal fellowship (RYC-2017-22959). G.M.S. was supported by NIH Training Grant T32CA009361. M.V. is a Chercheurv Qualifié Honoraire from the Fonds de la Recherche Scientifique (FRS-FNRS, Wallonia-Brussels Federation, Belgium).

Global insights into cellular organization and function require comprehensive understanding of interactome networks. Similar to how a reference genome sequence revolutionized human genetics, a reference map of the human interactome network is critical to fully understand genotype-phenotype relationships. Here we present the first human “all-by-all” binary reference interactome map, or “HuRI”. With ~53,000 high-quality protein-protein interactions (PPIs), HuRI is approximately four times larger than the information curated from small-scale studies available in the literature. Integrating HuRI with genome, transcriptome and proteome data enables the study of cellular function within essentially any physiological or pathological cellular context. We demonstrate the use of HuRI in identifying specific subcellular roles of PPIs and protein function modulation via splicing during brain development. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms underlying tissue-specific phenotypes of Mendelian diseases. HuRI thus represents an unprecedented, systematic reference linking genomic variation to phenotypic outcomes.

Perturbations in activity and dosage of the UBE3A ubiquitin-ligase have been linked to Angelman syndrome and autism spectrum disorders. UBE3A was initially identified as the cellular protein hijacked by the human papillomavirus E6 protein to mediate the ubiquitylation of p53, a function critical to the oncogenic potential of these viruses. Although a number of substrates have been identified, the normal cellular functions and pathways affected by UBE3A are largely unknown. Previously, we showed that UBE3A associates with HERC2, NEURL4, and MAPK6/ERK3 in a high-molecular-weight complex of unknown function that we refer to as the HUN complex (HERC2, UBE3A, and NEURL4). In this study, the combination of two complementary proteomic approaches with a rigorous network analysis revealed cellular functions and pathways in which UBE3A and the HUN complex are involved. In addition to finding new UBE3A-associated proteins, such as MCM6, SUGT1, EIF3C, and ASPP2, network analysis revealed that UBE3A-associated proteins are connected to several fundamental cellular processes including translation, DNA replication, intracellular trafficking, and centrosome regulation. Our analysis suggests that UBE3A could be involved in the control and/or integration of these cellular processes, in some cases as a component of the HUN complex, and also provides evidence for crosstalk between the HUN complex and CAMKII interaction networks. This study contributes to a deeper understanding of the cellular functions of UBE3A and its potential role in pathways that may be affected in Angelman syndrome, UBE3A-associated autism spectrum disorders, and human papillomavirus-associated cancers.

Proteins effect a number of biological functions, from cellular signaling, organization, mobility, and transport to catalyzing biochemical reactions and coordinating an immune response. These varied functions are often dependent upon macromolecular interactions, particularly with other proteins. Small-scale studies in the scientific literature report protein–protein interactions (PPIs), but slowly and with bias towards well-studied proteins. In an era where genomic sequence is readily available, deducing genotype–phenotype relationships requires an understanding of protein connectivity at proteome-scale. A proteome-scale map of the protein–protein interaction network provides a global view of cellular organization and function. Here, we discuss a summary of methods for building proteome-scale interactome maps and the current status and implications of mapping achievements. Not only do interactome maps serve as a reference, detailing global cellular function and organization patterns, but they can also reveal the mechanisms altered by disease alleles, highlight the patterns of interaction rewiring across evolution, and help pinpoint biologically and therapeutically relevant proteins. Despite the considerable strides made in proteome-wide mapping, several technical challenges persist. Therefore, future considerations that impact current mapping efforts are also discussed.

The objective of the study was to identify the deregulated miRNA in autonomous adenoma and to correlate the data with mRNA regulation. Seven autonomous adenoma with adjacent healthy thyroid tissues were investigated. Twelve miRNAs were downregulated and one was upregulated in the tumors. Combining bioinformatic mRNA target prediction and microarray data on mRNA regulations allowed to identify mRNA targets of our deregulated miRNAs. A large enrichment in mRNA encoding proteins involved in extracellular matrix organization and different phosphodiesterases were identified among these putative targets. The direct interaction between miR-101-3p and miR-144-3p and PDE4D mRNA was experimentally validated. The global miRNA profiles were not greatly modified, confirming the definition of these tumors as minimal deviation tumors. These results support a role for miRNA in the regulation of extracellular matrix proteins and tissue remodeling occurring during tumor development, and in the important negative feedback of the cAMP pathway, which limits the consequences of its constitutive activation in these tumors.