INTRODUCTION:We described a protected case with familial Alzheimer's disease, homozygous for apolipoprotein E3 (APOE3) Christchurch variant (ApoE3Ch), exhibiting low tau protein levels despite genetic predisposition to the disease due to presenilin (PSEN)1-E280A. We reported the loss of interaction between ApoE3Ch and heparan sulfate proteoglycans (HSPGs) as a critical protective pathway. Here, we characterized differential interacting partners for both wild-type and Christchurch variants to identify additional protective mechanisms of ApoE3Ch. METHODS:We performed pull-down of mouse brain lysates using His-tag-ApoE3 recombinant proteins and determined interacting partners of ApoE3 via mass-spectrometry. We then performed in vitro and in vivo assays to validate the top interactors. RESULTS:We found enhanced binding of ApoE3Ch to tau and Dickkopf-1 (Dkk1, a WNT/β-catenin antagonist) that resulted in reduced tau aggregation in vitro. We demonstrated that ApoE3Ch interacts directly with Dkk1 and tau, reducing tau pathology. These findings supported the hypothesis of novel protective effects of direct ApoE3Ch interactions. HIGHLIGHTS:⁠Apolipoprotein E3 (ApoE3) Christchurch variant (ApoE3Ch) exhibits different protein interaction profiles compared to wild-type ApoE3, as revealed by proteomic analyses and pull-down experiments. The ApoE3Ch variant alters the protein's interaction with tau, thus affecting its aggregation in a tau biosensor cell assay and the retina of microtubule-associated protein tau (MAPT*P301S) transgenic mice. ⁠Gene ontology and pathway analyses indicate that ApoE3Ch interactors are associated with brain-related disorders and specific upstream regulators, including MAPT, a gene encoding for tau. ⁠Protein-protein interaction studies showed increased binding of ApoE3Ch to Dickkopf1 (Dkk1), a Wnt/β-catenin pathway antagonist, as compared to ApoE3WT, thus indicating that multiple protective mechanisms are regulated by the ApoE3Ch variant Our study uncovers a novel protective effect of the ApoE3Ch variant against tau pathology, thus proposing new insights into Alzheimer's disease mechanisms and potential therapeutic targets.

We describe a next-generation Drosophila protein interaction map-"DPIM2"-established from affinity purification-mass spectrometry of 5,805 baits, covering the largest fraction of the Drosophila proteome. The network contains 32,668 interactions among 3,644 proteins, organized into 632 clusters representing putative functional modules. Our analysis expands the pool of known protein interactions in Drosophila, provides annotation for poorly studied genes, and postulates previously undescribed protein interaction relationships. The predictive power and functional relevance of this network are probed through the lens of the Notch signaling pathway, and we find that newly identified members of complexes that include known Notch modifiers can also modulate Notch signaling. DPIM2 allows direct comparisons with a recently published human protein interaction network, defining the existence of functional interactions conserved across species. Thus, DPIM2 defines a valuable resource for predicting protein co-complex memberships and functional associations as well as generates functional hypotheses regarding specific protein interactions.

INTRODUCTION: We discovered that the APOE3 Christchurch (APOE3Ch) variant may provide resistance to Alzheimer's disease (AD). This resistance may be due to reduced pathological interactions between ApoE3Ch and heparan sulfate proteoglycans (HSPGs). METHODS: We developed and characterized the binding, structure, and preclinical efficacy of novel antibodies targeting human ApoE-HSPG interactions. RESULTS: We found that one of these antibodies, called 7C11, preferentially bound ApoE4, a major risk factor for sporadic AD, and disrupts heparin-ApoE4 interactions. We also determined the crystal structure of a Fab fragment of 7C11 and used computer modeling to predict how it would bind to ApoE. When we tested 7C11 in mouse models, we found that it reduced recombinant ApoE-induced tau pathology in the retina of MAPT*P301S mice and curbed pTau S396 phosphorylation in brains of systemically treated APOE4 knock-in mice. Targeting ApoE-HSPG interactions using 7C11 antibody may be a promising approach to developing new therapies for AD.

Affinity purification–mass spectrometry elucidates protein interaction networks and co-complexes to build, to our knowledge, the largest experimentally derived human protein interaction network so far, termed BioPlex 2.0. The thousands of proteins within a cell function as modules and networks to coordinate their biological activities. Large-scale efforts are underway to build protein interaction maps that reveal cellular proteome architecture. Here, Wade Harper and colleagues use affinity purification mass spectrometry to elucidate protein interaction networks and co-complexes and build the largest experimentally derived human proteome interaction network to date, termed BioPlex 2.0. Containing over 29,000 novel co-associations and 1,300 protein communities representing diverse cellular activities, BioPlex 2.0 is more than double the size of their earlier interaction network BioPlex 1.0 and will be a valuable resource for exploring uncharacterized proteins and candidate disease-linked genes. The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein–protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidating how genome variation contributes to disease1,2,3. Here we present BioPlex 2.0 (Biophysical Interactions of ORFeome-derived complexes), which uses robust affinity purification–mass spectrometry methodology4 to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein-coding genes from the human genome, and constitutes, to our knowledge, the largest such network so far. With more than 56,000 candidate interactions, BioPlex 2.0 contains more than 29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering5 of interacting proteins identified more than 1,300 protein communities representing diverse cellular activities. Genes essential for cell fitness6,7 are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2,000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.

Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors.

In eukaryotic cells, RNAs exist as ribonucleoprotein particles (RNPs). Despite the importance of these complexes in many biological processes, including splicing, polyadenylation, stability, transportation, localization, and translation, their compositions are largely unknown. We affinity-purified 20 distinct RNA-binding proteins (RBPs) from cultured Drosophila melanogaster cells under native conditions and identified both the RNA and protein compositions of these RNP complexes. We identified "high occupancy target" (HOT) RNAs that interact with the majority of the RBPs we surveyed. HOT RNAs encode components of the nonsense-mediated decay and splicing machinery, as well as RNA-binding and translation initiation proteins. The RNP complexes contain proteins and mRNAs involved in RNA binding and post-transcriptional regulation. Genes with the capacity to produce hundreds of mRNA isoforms, ultracomplex genes, interact extensively with heterogeneous nuclear ribonuclear proteins (hnRNPs). Our data are consistent with a model in which subsets of RNPs include mRNA and protein products from the same gene, indicating the widespread existence of auto-regulatory RNPs. From the simultaneous acquisition and integrative analysis of protein and RNA constituents of RNPs, we identify extensive cross-regulatory and hierarchical interactions in post-transcriptional control.

Specific cellular fates and functions depend on differential gene expression, which occurs primarily at the transcriptional level and is controlled by complex regulatory networks of transcription factors (TFs). TFs act through combinatorial interactions with other TFs, cofactors, and chromatin-remodeling proteins. Here, we define protein-protein interactions using a coaffinity purification/mass spectrometry method and study 459 Drosophila melanogaster transcription-related factors, representing approximately half of the established catalog of TFs. We probe this network in vivo, demonstrating functional interactions for many interacting proteins, and test the predictive value of our data set. Building on these analyses, we combine regulatory network inference models with physical interactions to define an integrated network that connects combinatorial TF protein interactions to the transcriptional regulatory network of the cell. We use this integrated network as a tool to connect the functional network of genetic modifiers related to mastermind, a transcriptional cofactor of the Notch pathway.

Recent large-scale studies have provided a global description of the interactome—the whole network of protein interactions in a cell or an organism—for several model organisms. Defining protein interactions on a proteome-wide scale has led to a better understanding of the cellular functions of many proteins, especially those that have not been studied by classical molecular genetic approaches. Here we describe the resources, methods, and techniques necessary for generation of such a proteome-scale interactome in a high throughput manner. These procedures will also be applicable to low or medium throughput focused studies aimed at understanding interactions between members of specific pathways such as Notch signaling.

Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when, what and where of potential interactions, is therefore crucial to understanding the cellular function of any protein-especially those that have not been well studied by traditional molecular genetic approaches. We generated a large-scale resource of affinity-tagged expression-ready clones and used co-affinity purification combined with tandem mass-spectrometry to identify protein partners of nearly 5,000 Drosophila melanogaster proteins. The resulting protein complex "map" provided a blueprint of metazoan protein complex organization. Here we describe how the map has provided valuable insights into protein function in addition to generating hundreds of testable hypotheses. We also discuss recent technological advancements that will be critical in addressing the next generation of questions arising from the map.

Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when, what and where of potential interactions, is therefore crucial to understanding the cellular function of any protein—especially those that have not been well studied by traditional molecular genetic approaches. We generated a large-scale resource of affinity-tagged expression-ready clones and used co-affinity purification combined with tandem mass-spectrometry to identify protein partners of nearly 5,000 Drosophila melanogaster proteins. The resulting protein complex "map" provided a blueprint of metazoan protein complex organization. Here we describe how the map has provided valuable insights into protein function in addition to generating hundreds of testable hypotheses. We also discuss recent technological advancements that will be critical in addressing the next generation of questions arising from the map.

Determining the composition of protein complexes is an essential step toward understanding the cell as an integrated system. Using coaffinity purification coupled to mass spectrometry analysis, we examined protein associations involving nearly 5,000 individual, FLAG-HA epitope-tagged Drosophila proteins. Stringent analysis of these data, based on a statistical framework designed to define individual protein-protein interactions, led to the generation of a Drosophila protein interaction map (DPiM) encompassing 556 protein complexes. The high quality of the DPiM and its usefulness as a paradigm for metazoan proteomes are apparent from the recovery of many known complexes, significant enrichment for shared functional attributes, and validation in human cells. The DPiM defines potential novel members for several important protein complexes and assigns functional links to 586 protein-coding genes lacking previous experimental annotation. The DPiM represents, to our knowledge, the largest metazoan protein complex map and provides a valuable resource for analysis of protein complex evolution.

Coupling of messenger RNA (mRNA) nuclear export with prior processing steps aids in the fidelity and efficiency of mRNA transport to the cytoplasm. In this study, we show that the processes of export and polyadenylation are coupled via the Drosophila melanogaster CCCH-type zinc finger protein CG6694/dZC3H3 through both physical and functional interactions. We show that depletion of dZC3H3 from S2R+ cells results in transcript hyperadenylation. Using targeted coimmunoprecipitation and liquid chromatography mass spectrometry (MS)/MS techniques, we characterize interactions of known components of the mRNA nuclear export and polyadenylation machineries with dZC3H3. Furthermore, we demonstrate the functional conservation of this factor, as depletion of its human homologue ZC3H3 by small interfering RNA results in an mRNA export defect in human cells as well. Nuclear polyadenylated (poly(A)) RNA in ZC3H3-depleted cells is sequestered in foci removed from SC35-containing speckles, indicating a shift from the normal subnuclear distribution of poly(A) RNA. Our data suggest a model wherein ZC3H3 interfaces between the polyadenylation machinery, newly poly(A) mRNAs, and factors for transcript export.