Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing.

While alternative splicing is known to diversify the functional characteristics of some genes, the extent to which protein isoforms globally contribute to functional complexity on a proteomic scale remains unknown. To address this systematically, we cloned full-length open reading frames of alternatively spliced transcripts for a large number of human genes and used protein-protein interaction profiling to functionally compare hundreds of protein isoform pairs. The majority of isoform pairs share less than 50% of their interactions. In the global context of interactome network maps, alternative isoforms tend to behave like distinct proteins rather than minor variants of each other. Interaction partners specific to alternative isoforms tend to be expressed in a highly tissue-specific manner and belong to distinct functional modules. Our strategy, applicable to other functional characteristics, reveals a widespread expansion of protein interaction capabilities through alternative splicing and suggests that many alternative "isoforms" are functionally divergent (i.e., "functional alloforms").

A reference map of the human binary protein 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.

AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor.

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 or 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.

eIF4A inactivates TORC1 in response to amino acid starvation.

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.

Keap1-Independent Regulation of Nrf2 Activity by Protein Acetylation and a BET Bromodomain Protein.

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.

Discovery of progenitor cell signatures by time-series synexpression analysis during Drosophila embryonic cell immortalization.

The use of time series profiling to identify groups of functionally related genes (synexpression groups) is a powerful approach for the discovery of gene function. Here we apply this strategy during Ras(V12) immortalization of Drosophila embryonic cells, a phenomenon not well characterized. Using high-resolution transcriptional time-series datasets, we generated a gene network based on temporal expression profile similarities. This analysis revealed that common immortalized cells are related to adult muscle precursors (AMPs), a stem cell-like population contributing to adult muscles and sharing properties with vertebrate satellite cells. Remarkably, the immortalized cells retained the capacity for myogenic differentiation when treated with the steroid hormone ecdysone. Further, we validated in vivo the transcription factor CG9650, the ortholog of mammalian Bcl11a/b, as a regulator of AMP proliferation predicted by our analysis. Our study demonstrates the power of time series synexpression analysis to characterize Drosophila embryonic progenitor lines and identify stem/progenitor cell regulators.

Landscape of protein-protein interactions in Drosophila immune deficiency signaling during bacterial challenge.

The Drosophila defense against pathogens largely relies on the activation of two signaling pathways: immune deficiency (IMD) and Toll. The IMD pathway is triggered mainly by Gram-negative bacteria, whereas the Toll pathway responds predominantly to Gram-positive bacteria and fungi. The activation of these pathways leads to the rapid induction of numerous NF-κB-induced immune response genes, including antimicrobial peptide genes. The IMD pathway shows significant similarities with the TNF receptor pathway. Recent evidence indicates that the IMD pathway is also activated in response to various noninfectious stimuli (i.e., inflammatory-like reactions). To gain a better understanding of the molecular machinery underlying the pleiotropic functions of this pathway, we first performed a comprehensive proteomics analysis to identify the proteins interacting with the 11 canonical members of the pathway initially identified by genetic studies. We identified 369 interacting proteins (corresponding to 291 genes) in heat-killed Escherichia coli-stimulated Drosophila S2 cells, 92% of which have human orthologs. A comparative analysis of gene ontology from fly or human gene annotation databases points to four significant common categories: (i) the NuA4, nucleosome acetyltransferase of H4, histone acetyltransferase complex, (ii) the switching defective/sucrose nonfermenting-type chromatin remodeling complex, (iii) transcription coactivator activity, and (iv) translation factor activity. Here we demonstrate that sumoylation of the IκB kinase homolog immune response-deficient 5 plays an important role in the induction of antimicrobial peptide genes through a highly conserved sumoylation consensus site during bacterial challenge. Taken together, the proteomics data presented here provide a unique avenue for a comparative functional analysis of proteins involved in innate immune reactions in flies and mammals.

Drosophila Ras/MAPK signalling regulates innate immune responses in immune and intestinal stem cells.

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.

p24 proteins are required for secretion of Wnt ligands.

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.

N-terminal proteoforms may engage in different protein complexes.

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.

Paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism across transcription factors.

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.

AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor.

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.

Assessment of community efforts to advance network-based prediction of protein-protein interactions.

Comprehensive understanding of the human protein-protein interaction (PPI) network, aka the human interactome, can provide important insights into the molecular mechanisms of complex biological processes and diseases. Despite the remarkable experimental efforts undertaken to date to determine the structure of the human interactome, many PPIs remain unmapped. Computational approaches, especially network-based methods, can facilitate the identification of previously uncharacterized PPIs. Many such methods have been proposed. Yet, a systematic evaluation of existing network-based methods in predicting PPIs is still lacking. Here, we report community efforts initiated by the International Network Medicine Consortium to benchmark the ability of 26 representative network-based methods to predict PPIs across six different interactomes of four different organisms: A. thaliana, C. elegans, S. cerevisiae, and H. sapiens. Through extensive computational and experimental validations, we found that advanced similarity-based methods, which leverage the underlying network characteristics of PPIs, show superior performance over other general link prediction methods in the interactomes we considered.

A proteome-scale map of the SARS-CoV-2-human contactome.

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.

Next-generation large-scale binary protein interaction network for Drosophila melanogaster.

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.

EROS is a selective chaperone regulating the phagocyte NADPH oxidase and purinergic signalling.

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.

Network-based prediction of protein interactions.

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.

Maximizing binary interactome mapping with a minimal number of assays.

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.

Cdk12 Is A Gene-Selective RNA Polymerase II Kinase That Regulates a Subset of the Transcriptome, Including Nrf2 Target Genes.

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.

Functional analysis of the Drosophila embryonic germ cell transcriptome by RNA interference.

In Drosophila melanogaster, primordial germ cells are specified at the posterior pole of the very early embryo. This process is regulated by the posterior localized germ plasm that contains a large number of RNAs of maternal origin. Transcription in the primordial germ cells is actively down-regulated until germ cell fate is established. Bulk expression of the zygotic genes commences concomitantly with the degradation of the maternal transcripts. Thus, during embryogenesis, maternally provided and zygotically transcribed mRNAs determine germ cell development collectively. In an effort to identify novel genes involved in the regulation of germ cell behavior, we carried out a large-scale RNAi screen targeting both maternal and zygotic components of the embryonic germ line transcriptome. We identified 48 genes necessary for distinct stages in germ cell development. We found pebble and fascetto to be essential for germ cell migration and germ cell division, respectively. Our data uncover a previously unanticipated role of mei-P26 in maintenance of embryonic germ cell fate. We also performed systematic co-RNAi experiments, through which we found a low rate of functional redundancy among homologous gene pairs. As our data indicate a high degree of evolutionary conservation in genetic regulation of germ cell development, they are likely to provide valuable insights into the biology of the germ line in general.