During development and disease, the exocytosis of signalling molecules, such as Wnt ligands, is essential to orchestrate cellular programs in multicellular organisms. However, it remains a largely unresolved question whether signalling molecules follow specialized transport routes through the exocytic pathway. Here we identify several Drosophila p24 proteins that are required for Wnt signalling. We demonstrate that one of these p24 proteins, namely Opossum, shuttles in the early secretory pathway, and that the Drosophila Wnt proteins are retained in the absence of p24 proteins. Our results indicate that Wnt secretion relies on a specialized anterograde secretion route with p24 proteins functioning as conserved cargo receptors.

EROS (essential for reactive oxygen species) protein is indispensable for expression of gp91phox, the catalytic core of the phagocyte NADPH oxidase. EROS deficiency in humans is a novel cause of the severe immunodeficiency, chronic granulomatous disease, but its mechanism of action was unknown until now. We elucidate the role of EROS, showing it acts at the earliest stages of gp91phox maturation. It binds the immature 58 kDa gp91phox directly, preventing gp91phox degradation and allowing glycosylation via the oligosaccharyltransferase machinery and the incorporation of the heme prosthetic groups essential for catalysis. EROS also regulates the purine receptors P2X7 and P2X1 through direct interactions, and P2X7 is almost absent in EROS-deficient mouse and human primary cells. Accordingly, lack of murine EROS results in markedly abnormal P2X7 signalling, inflammasome activation, and T cell responses. The loss of both ROS and P2X7 signalling leads to resistance to influenza infection in mice. Our work identifies EROS as a highly selective chaperone for key proteins in innate and adaptive immunity and a rheostat for immunity to infection. It has profound implications for our understanding of immune physiology, ROS dysregulation, and possibly gene therapy.

Immune signalling pathways need to be tightly regulated as overactivation of these pathways can result in chronic inflammatory diseases and cancer. NF-κB signalling and associated innate immune pathways are crucial in the first line of defense against infection in all animals. In a genome-wide RNAi screen for modulators of Drosophila immune deficiency (IMD)/NF-κB signalling, we identified components of the Ras/MAPK pathway as essential for suppression of IMD pathway activity, even in the absence of an immune challenge. Downregulation of Ras/MAPK activity mimics the induction of innate immune responses by microbial patterns. Conversely, ectopic Ras/MAPK pathway activation results in the suppression of Drosophila IMD/NF-κB signalling. Mechanistically, we show that the Ras/MAPK pathway acts by inducing transcription of the IMD pathway inhibitor Pirk/Rudra/PIMS. Finally, in vivo experiments demonstrate a requirement for Ras/MAPK signalling in restricting innate immune responses in haemocytes, fat body and adult intestinal stem cells. Our observations provide an example of a pathway that promotes cell proliferation and has simultaneously been utilized to limit the immune response.

Despite exceptional experimental efforts to map out the human interactome, the continued data incompleteness limits our ability to understand the molecular roots of human disease. Computational tools offer a promising alternative, helping identify biologically significant, yet unmapped protein-protein interactions (PPIs). While link prediction methods connect proteins on the basis of biological or network-based similarity, interacting proteins are not necessarily similar and similar proteins do not necessarily interact. Here, we offer structural and evolutionary evidence that proteins interact not if they are similar to each other, but if one of them is similar to the other's partners. This approach, that mathematically relies on network paths of length three (L3), significantly outperforms all existing link prediction methods. Given its high accuracy, we show that L3 can offer mechanistic insights into disease mechanisms and can complement future experimental efforts to complete the human interactome.

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.

Generating reference maps of interactome networks illuminates genetic studies by providing a protein-centric approach to finding new components of existing pathways, complexes, and processes. We apply state-of-the-art methods to identify binary protein-protein interactions (PPIs) for Drosophila melanogaster. Four all-by-all yeast two-hybrid (Y2H) screens of > 10,000 Drosophila proteins result in the 'FlyBi' dataset of 8723 PPIs among 2939 proteins. Testing subsets of data from FlyBi and previous PPI studies using an orthogonal assay allows for normalization of data quality; subsequent integration of FlyBi and previous data results in an expanded binary Drosophila reference interaction network, DroRI, comprising 17,232 interactions among 6511 proteins. We use FlyBi data to generate an autophagy network, then validate in vivo using autophagy-related assays. The deformed wings (dwg) gene encodes a protein that is both a regulator and a target of autophagy. Altogether, these resources provide a foundation for building new hypotheses regarding protein networks and function.

Mammalian BET proteins comprise a family of bromodomain-containing epigenetic regulators with complex functions in chromatin organization and gene regulation. We identified the sole member of the BET protein family in Drosophila, Fs(1)h, as an inhibitor of the stress responsive transcription factor CncC, the fly ortholog of Nrf2. Fs(1)h physically interacts with CncC in a manner that requires the function of its bromodomains and the acetylation of CncC. Treatment of cultured Drosophila cells or adult flies with fs(1)h RNAi or with the BET protein inhibitor JQ1 de-represses CncC transcriptional activity and engages protective gene expression programs. The mechanism by which Fs(1)h inhibits CncC function is distinct from the canonical mechanism that stimulates Nrf2 function by abrogating Keap1-dependent proteasomal degradation. Consistent with the independent modes of CncC regulation by Keap1 and Fs(1)h, combinations of drugs that can specifically target these pathways cause a strong synergistic and specific activation of protective CncC- dependent gene expression and boosts oxidative stress resistance. This synergism might be exploitable for the design of combinatorial therapies to target diseases associated with oxidative stress or inflammation.

Complementary assays are required to comprehensively map complex biological entities such as genomes, proteomes and interactome networks. However, how various assays can be optimally combined to approach completeness while maintaining high precision often remains unclear. Here, we propose a framework for binary protein-protein interaction (PPI) mapping based on optimally combining assays and/or assay versions to maximize detection of true positive interactions, while avoiding detection of random protein pairs. We have engineered a novel NanoLuc two-hybrid (N2H) system that integrates 12 different versions, differing by protein expression systems and tagging configurations. The resulting union of N2H versions recovers as many PPIs as 10 distinct assays combined. Thus, to further improve PPI mapping, developing alternative versions of existing assays might be as productive as designing completely new assays. Our findings should be applicable to systematic mapping of other biological landscapes.

Alternative translation initiation and alternative splicing may give rise to N-terminal proteoforms, proteins that differ at their N-terminus compared with their canonical counterparts. Such proteoforms can have altered localizations, stabilities, and functions. Although proteoforms generated from splice variants can be engaged in different protein complexes, it remained to be studied to what extent this applies to N-terminal proteoforms. To address this, we mapped the interactomes of several pairs of N-terminal proteoforms and their canonical counterparts. First, we generated a catalogue of N-terminal proteoforms found in the HEK293T cellular cytosol from which 22 pairs were selected for interactome profiling. In addition, we provide evidence for the expression of several N-terminal proteoforms, identified in our catalogue, across different human tissues, as well as tissue-specific expression, highlighting their biological relevance. Protein-protein interaction profiling revealed that the overlap of the interactomes for both proteoforms is generally high, showing their functional relation. We also showed that N-terminal proteoforms can be engaged in new interactions and/or lose several interactions compared with their canonical counterparts, thus further expanding the functional diversity of proteomes.

The Nrf2 transcription factor is well conserved throughout metazoan evolution and serves as a central regulator of adaptive cellular responses to oxidative stress. We carried out an RNAi screen in Drosophila S2 cells to better understand the regulatory mechanisms governing Nrf2 target gene expression. This paper describes the identification and characterization of the RNA polymerase II (Pol II) kinase Cdk12 as a factor that is required for Nrf2 target gene expression in cell culture and in vivo. Cdk12 is, however, not essential for bulk mRNA transcription and cells lacking CDK12 function are viable and able to proliferate. Consistent with previous findings on the DNA damage and heat shock responses, it emerges that Cdk12 may be specifically required for stress activated gene expression. Transcriptome analysis revealed that antioxidant gene expression is compromised in flies with reduced Cdk12 function, which makes them oxidative stress sensitive. In addition to supporting Reactive Oxygen Species (ROS) induced gene activation, Cdk12 suppresses genes that support metabolic functions in stressed conditions. We suggest that Cdk12 acts as a gene-selective Pol II kinase that engages a global shift in gene expression to switch cells from a metabolically active state to "stress-defence mode" when challenged by external stress.

Amino acids regulate TOR complex 1 (TORC1) via two counteracting mechanisms, one activating and one inactivating. The presence of amino acids causes TORC1 recruitment to lysosomes where TORC1 is activated by binding Rheb. How the absence of amino acids inactivates TORC1 is less well understood. Amino acid starvation recruits the TSC1/TSC2 complex to the vicinity of TORC1 to inhibit Rheb; however, the upstream mechanisms regulating TSC2 are not known. We identify here the eIF4A-containing eIF4F translation initiation complex as an upstream regulator of TSC2 in response to amino acid withdrawal in Drosophila We find that TORC1 and translation preinitiation complexes bind each other. Cells lacking eIF4F components retain elevated TORC1 activity upon amino acid removal. This effect is specific for eIF4F and not a general consequence of blocked translation. This study identifies specific components of the translation machinery as important mediators of TORC1 inactivation upon amino acid removal.

Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ?14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ?30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a "broader" human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help "connect the dots" of the genomic revolution.

Cooperativity and antagonism between transcription factors (TFs) can drastically modify their binding to regulatory DNA elements. While mapping these relationships between TFs is important for understanding their context-specific functions, existing approaches either rely on DNA binding motif predictions, interrogate one TF at a time, or study individual TFs in parallel. Here, we introduce paired yeast one-hybrid (pY1H) assays to detect cooperativity and antagonism across hundreds of TF-pairs at DNA regions of interest. We provide evidence that a wide variety of TFs are subject to modulation by other TFs in a DNA region-specific manner. We also demonstrate that TF-TF relationships are often affected by alternative isoform usage and identify cooperativity and antagonism between human TFs and viral proteins from human papillomaviruses, Epstein-Barr virus, and other viruses. Altogether, pY1H assays provide a broadly applicable framework to study how different functional relationships affect protein occupancy at regulatory DNA regions.

Understanding the mechanisms of coronavirus disease 2019 (COVID-19) disease severity to efficiently design therapies for emerging virus variants remains an urgent challenge of the ongoing pandemic. Infection and immune reactions are mediated by direct contacts between viral molecules and the host proteome, and the vast majority of these virus-host contacts (the 'contactome') have not been identified. Here, we present a systematic contactome map of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with the human host encompassing more than 200 binary virus-host and intraviral protein-protein interactions. We find that host proteins genetically associated with comorbidities of severe illness and long COVID are enriched in SARS-CoV-2 targeted network communities. Evaluating contactome-derived hypotheses, we demonstrate that viral NSP14 activates nuclear factor κB (NF-κB)-dependent transcription, even in the presence of cytokine signaling. Moreover, for several tested host proteins, genetic knock-down substantially reduces viral replication. Additionally, we show for USP25 that this effect is phenocopied by the small-molecule inhibitor AZ1. Our results connect viral proteins to human genetic architecture for COVID-19 severity and offer potential therapeutic targets.

Protein-protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays and AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.