A multi-scale map of cell structure fusing protein images and interactions.

The cell is a multi-scale structure with modular organization across at least four orders of magnitude1. Two central approaches for mapping this structure-protein fluorescent imaging and protein biophysical association-each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately2,3. Here we integrate immunofluorescence images in the Human Protein Atlas4 with affinity purifications in BioPlex5 to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.

CRISPR screens in cancer spheroids identify 3D growth-specific vulnerabilities.

Cancer genomics studies have identified thousands of putative cancer driver genes1. Development of high-throughput and accurate models to define the functions of these genes is a major challenge. Here we devised a scalable cancer-spheroid model and performed genome-wide CRISPR screens in 2D monolayers and 3D lung-cancer spheroids. CRISPR phenotypes in 3D more accurately recapitulated those of in vivo tumours, and genes with differential sensitivities between 2D and 3D conditions were highly enriched for genes that are mutated in lung cancers. These analyses also revealed drivers that are essential for cancer growth in 3D and in vivo, but not in 2D. Notably, we found that carboxypeptidase D is responsible for removal of a C-terminal RKRR motif2 from the α-chain of the insulin-like growth factor 1 receptor that is critical for receptor activity. Carboxypeptidase D expression correlates with patient outcomes in patients with lung cancer, and loss of carboxypeptidase D reduced tumour growth. Our results reveal key differences between 2D and 3D cancer models, and establish a generalizable strategy for performing CRISPR screens in spheroids to reveal cancer vulnerabilities.

Drebrin restricts rotavirus entry by inhibiting dynamin-mediated endocytosis.

Despite the wide administration of several effective vaccines, rotavirus (RV) remains the single most important etiological agent of severe diarrhea in infants and young children worldwide, with an annual mortality of over 200,000 people. RV attachment and internalization into target cells is mediated by its outer capsid protein VP4. To better understand the molecular details of RV entry, we performed tandem affinity purification coupled with high-resolution mass spectrometry to map the host proteins that interact with VP4. We identified an actin-binding protein, drebrin (DBN1), that coprecipitates and colocalizes with VP4 during RV infection. Importantly, blocking DBN1 function by siRNA silencing, CRISPR knockout (KO), or chemical inhibition significantly increased host cell susceptibility to RV infection. Dbn1 KO mice exhibited higher incidence of diarrhea and more viral antigen shedding in their stool samples compared with the wild-type littermates. In addition, we found that uptake of other dynamin-dependent cargos, including transferrin, cholera toxin, and multiple viruses, was also enhanced in DBN1-deficient cells. Inhibition of cortactin or dynamin-2 abrogated the increased virus entry observed in DBN1-deficient cells, suggesting that DBN1 suppresses dynamin-mediated endocytosis via interaction with cortactin. Our study unveiled an unexpected role of DBN1 in restricting the entry of RV and other viruses into host cells and more broadly to function as a crucial negative regulator of diverse dynamin-dependent endocytic pathways.

Comparative Proteomics Reveals Strain-Specific ß-TrCP Degradation via Rotavirus NSP1 Hijacking a Host Cullin-3-Rbx1 Complex.

Rotaviruses (RVs) are the leading cause of severe gastroenteritis in young children, accounting for half a million deaths annually worldwide. RV encodes non-structural protein 1 (NSP1), a well-characterized interferon (IFN) antagonist, which facilitates virus replication by mediating the degradation of host antiviral factors including IRF3 and ß-TrCP. Here, we utilized six human and animal RV NSP1s as baits and performed tandem-affinity purification coupled with high-resolution mass spectrometry to comprehensively characterize NSP1-host protein interaction network. Multiple Cullin-RING ubiquitin ligase (CRL) complexes were identified. Importantly, inhibition of cullin-3 (Cul3) or RING-box protein 1 (Rbx1), by siRNA silencing or chemical perturbation, significantly impairs strain-specific NSP1-mediated ß-TrCP degradation. Mechanistically, we demonstrate that NSP1 localizes to the Golgi with the host Cul3-Rbx1 CRL complex, which targets ß-TrCP and NSP1 for co-destruction at the proteasome. Our study uncovers a novel mechanism that RV employs to promote ß-TrCP turnover and provides molecular insights into virus-mediated innate immunity inhibition.

A deep learning model of tumor cell architecture elucidates response and resistance to CDK4/6 inhibitors.

Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6is) have revolutionized breast cancer therapy. However, <50% of patients have an objective response, and nearly all patients develop resistance during therapy. To elucidate the underlying mechanisms, we constructed an interpretable deep learning model of the response to palbociclib, a CDK4/6i, based on a reference map of multiprotein assemblies in cancer. The model identifies eight core assemblies that integrate rare and common alterations across 90 genes to stratify palbociclib-sensitive versus palbociclib-resistant cell lines. Predictions translate to patients and patient-derived xenografts, whereas single-gene biomarkers do not. Most predictive assemblies can be shown by CRISPR-Cas9 genetic disruption to regulate the CDK4/6i response. Validated assemblies relate to cell-cycle control, growth factor signaling and a histone regulatory complex that we show promotes S-phase entry through the activation of the histone modifiers KAT6A and TBL1XR1 and the transcription factor RUNX1. This study enables an integrated assessment of how a tumor's genetic profile modulates CDK4/6i resistance.

UHRF1 is a mediator of KRAS driven oncogenesis in lung adenocarcinoma.

KRAS is a frequent driver in lung cancer. To identify KRAS-specific vulnerabilities in lung cancer, we performed RNAi screens in primary spheroids derived from a Kras mutant mouse lung cancer model and discovered an epigenetic regulator Ubiquitin-like containing PHD and RING finger domains 1 (UHRF1). In human lung cancer models UHRF1 knock-out selectively impaired growth and induced apoptosis only in KRAS mutant cells. Genome-wide methylation and gene expression analysis of UHRF1-depleted KRAS mutant cells revealed global DNA hypomethylation leading to upregulation of tumor suppressor genes (TSGs). A focused CRISPR/Cas9 screen validated several of these TSGs as mediators of UHRF1-driven tumorigenesis. In vivo, UHRF1 knock-out inhibited tumor growth of KRAS-driven mouse lung cancer models. Finally, in lung cancer patients high UHRF1 expression is anti-correlated with TSG expression and predicts worse outcomes for patients with KRAS mutant tumors. These results nominate UHRF1 as a KRAS-specific vulnerability and potential target for therapeutic intervention.

A multi-scale map of protein assemblies in the DNA damage response.

The DNA damage response (DDR) ensures error-free DNA replication and transcription and is disrupted in numerous diseases. An ongoing challenge is to determine the proteins orchestrating DDR and their organization into complexes, including constitutive interactions and those responding to genomic insult. Here, we use multi-conditional network analysis to systematically map DDR assemblies at multiple scales. Affinity purifications of 21 DDR proteins, with/without genotoxin exposure, are combined with multi-omics data to reveal a hierarchical organization of 605 proteins into 109 assemblies. The map captures canonical repair mechanisms and proposes new DDR-associated proteins extending to stress, transport, and chromatin functions. We find that protein assemblies closely align with genetic dependencies in processing specific genotoxins and that proteins in multiple assemblies typically act in multiple genotoxin responses. Follow-up by DDR functional readouts newly implicates 12 assembly members in double-strand-break repair. The DNA damage response assemblies map is available for interactive visualization and query (ccmi.org/ddram/).

Interpretation of cancer mutations using a multiscale map of protein systems.

A major goal of cancer research is to understand how mutations distributed across diverse genes affect common cellular systems, including multiprotein complexes and assemblies. Two challenges­how to comprehensively map such systems and how to identify which are under mutational selection­have hindered this understanding. Accordingly, we created a comprehensive map of cancer protein systems integrating both new and published multi-omic interaction data at multiple scales of analysis. We then developed a unified statistical model that pinpoints 395 specific systems under mutational selection across 13 cancer types. This map, called NeST (Nested Systems in Tumors), incorporates canonical processes and notable discoveries, including a PIK3CA-actomyosin complex that inhibits phosphatidylinositol 3-kinase signaling and recurrent mutations in collagen complexes that promote tumor proliferation. These systems can be used as clinical biomarkers and implicate a total of 548 genes in cancer evolution and progression. This work shows how disparate tumor mutations converge on protein assemblies at different scales.

Combined Proteomic and Genetic Interaction Mapping Reveals New RAS Effector Pathways and Susceptibilities.

Activating mutations in RAS GTPases drive many cancers, but limited understanding of less-studied RAS interactors, and of the specific roles of different RAS interactor paralogs, continues to limit target discovery. We developed a multistage discovery and screening process to systematically identify genes conferring RAS-related susceptibilities in lung adenocarcinoma. Using affinity purification mass spectrometry, we generated a protein-protein interaction map of RAS interactors and pathway components containing hundreds of interactions. From this network, we constructed a CRISPR dual knockout library targeting 119 RAS-related genes that we screened for KRAS-dependent genetic interactions (GI). This approach identified new RAS effectors, including the adhesion controller RADIL and the endocytosis regulator RIN1, and >250 synthetic lethal GIs, including a potent KRAS-dependent interaction between RAP1GDS1 and RHOA. Many GIs link specific paralogs within and between gene families. These findings illustrate the power of multiomic approaches to uncover synthetic lethal combinations specific for hitherto untreatable cancer genotypes. SIGNIFICANCE: We establish a deep network of protein-protein and genetic interactions in the RAS pathway. Many interactions validated here demonstrate important specificities and redundancies among paralogous RAS regulators and effectors. By comparing synthetic lethal interactions across KRAS-dependent and KRAS-independent cell lines, we identify several new combination therapy targets for RAS-driven cancers.This article is highlighted in the In This Issue feature, p. 1775.

The ciliopathy-associated CPLANE proteins direct basal body recruitment of intraflagellar transport machinery.

Cilia use microtubule-based intraflagellar transport (IFT) to organize intercellular signaling. Ciliopathies are a spectrum of human diseases resulting from defects in cilia structure or function. The mechanisms regulating the assembly of ciliary multiprotein complexes and the transport of these complexes to the base of cilia remain largely unknown. Combining proteomics, in vivo imaging and genetic analysis of proteins linked to planar cell polarity (Inturned, Fuzzy and Wdpcp), we identified and characterized a new genetic module, which we term CPLANE (ciliogenesis and planar polarity effector), and an extensive associated protein network. CPLANE proteins physically and functionally interact with the poorly understood ciliopathy-associated protein Jbts17 at basal bodies, where they act to recruit a specific subset of IFT-A proteins. In the absence of CPLANE, defective IFT-A particles enter the axoneme and IFT-B trafficking is severely perturbed. Accordingly, mutation of CPLANE genes elicits specific ciliopathy phenotypes in mouse models and is associated with ciliopathies in human patients.