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Kim, D.-K.

Publications and source records attributed to Kim, D.-K..

At least 19 recordsLinked to original sources

Stress granule fusion is a mitochondria-coordinated process for stress adaptation

Stress granules are cytoplasmic membraneless organelles assembled during stress to maintain cellular homeostasis. Although fusion is a hallmark of liquid-like behavior of these condensates, whether this process carries functional significance beyond its physical coalescence remains unclear. Here, we show that stress granule fusion is facilitated by mitochondrial dynamics and membrane potential. Intact mitochondria actively associate with stress granules, facilitating fusion and maturation. In contrast, loss of mitochondrial membrane potential, along with disrupted mitochondrial structure or motility, weakens these interactions and reduces fusion frequency. We find that impaired fusion leads to the accumulation of immature granules that retain fewer sequestered components, which correlates with premature cell death. Remarkably, restoring mitochondrial membrane potential rescues granule fusion and enlargement, and is accompanied by increased cell viability and a corresponding increase in granule-associated apoptotic factors. These results demonstrate that stress granule fusion is actively coordinated by mitochondria rather than driven solely by passive coalescence, reshaping how condensate dynamics are understood to integrate with organelle function during cellular stress response.

cell biology↗

Deep Plasma Proteomics Coupled with Functional Genomics Reveals Drivers of Parkinson's Disease Progression and Levodopa Response

Parkinsons disease (PD) is a progressive neurodegenerative disorder lacking disease-modifying therapies, and its clinical management is limited by the absence of accessible biomarkers for tracking disease progression and treatment response. To map these complex disease trajectories, we implemented an ultra-deep plasma proteomics workflow integrating Mag-Net extracellular vesicle enrichment with Orbitrap Astral mass spectrometry to profile longitudinal samples from PD patients. This approach quantified 6,481 plasma proteins at unprecedented depth in PD studies, revealing distinct signatures directly associated with disease duration and dopaminergic therapy exposure. Candidate biomarkers were subsequently validated in an independent cohort using ELISA, demonstrating robust predictive utility in AI-driven prediction models. To uncover the mechanistic drivers underlying these systemic changes, we intersected our proteomic data with novel proteome-wide gene overexpression perturbation screens designed to identify regulators of alpha-synuclein pre-formed fibril (PFF) uptake and PFF-induced neuronal toxicity. Finally, an integrative network analysis combining three independent proteome-wide assays revealed that key pathological hubs, such as CD14, IFNG, and PLAT, are targets of currently approved pharmacological agents. Collectively, these findings provide a comprehensive, systems-level map for PD biomarker discovery and highlight druggable pathways to advance precision medicine strategies.

neuroscience↗

Cereblon Promotes Influenza Virus Replication through AMPK Ubiquitination

Influenza A and B viruses (IAV and IBV) continually threaten global health, with IAV posing a risk of emerging pandemics. Rapid viral evolution makes current treatments less effective, highlighting the urgent need for broad-spectrum antivirals. Targeting host factors essential for viral replication may offer a highly promising broad-spectrum antiviral strategy. In this context, cereblon (CRBN), a substrate adaptor of the CRL4 E3 ubiquitin ligase complex, is found to promote both IAV and IBV replication as a key pro-viral host factor. Mechanistically, CRBN targets and degrades AMP-activated protein kinase (AMPK) via the proteasome. This CRBN-driven degradation shifts the metabolism of the infected cells toward anabolism, promoting lipid droplet (LD) formation and creating a microenvironment favorable for viral replication. Genetic depletion or inhibition of CRBN stabilizes AMPK, significantly reduces LD formation, and effectively suppresses the replication of various IAV and IBV strains in vivo, demonstrating its broad-spectrum potential. Notably, Crbn knockout mice show marked resistance to lethal IAV infection. CRBN inhibition with immunomodulatory imide drugs--known CRBN inhibitors--significantly decreases IAV replication in vivo. This research underscores CRBN as a crucial regulator of host metabolism during viral infection, revealing the CRBN-AMPK axis as a promising target for host-directed pan-influenza antiviral development. Author SummaryInfluenza A and B viruses are response for recurring seasonal epidemics and occasional pandemics that pose serious global health challenges. Current antiviral drugs often lose effectiveness as influenza viruses rapidly develop resistance through genetic mutations. To overcome this limitation, our study focused on a host factor targeted by influenza viruses-the ubiquitin E3 ligase substrate adaptor cereblon (CRBN). We discovered that influenza viruses exploit CRBN to enhance their replication by altering host cell metabolism. Specifically, CRBN binds to a key energy sensor - AMPK and induces the ubiquitination and degradation of AMPK{gamma}. Consequently, the AMPK suppression shifts the cellular environment from catabolism to anabolism, activating lipogenic enzymes and promoting lipid droplets formation which provide a favorable environment for viral growth. Our study highlight that blocking CRBN either genetically or chemical inhibition (immunomodulatory imide drugs) of CRBN reduces LD formation and strongly suppresses diverse influenza strains replication in vitro and in vivo. These findings reveal not only how viruses hijack host metabolism via the CRBN-AMPK pathway but also present a potential therapeutic for novel broad-spectrum anti-influenza.

microbiology↗

The protein phosphatase 2C domain contributes to the pathobiological function of adenylyl cyclase in Cryptococcus neoformans

Adenylyl cyclase produces cyclic adenosine monophosphate, a signalling molecule that controls fungal development and virulence. Fungal adenylyl cyclases are distinguished by the presence of a conserved protein phosphatase 2C domain, whose function remains unknown. Here we show that the protein phosphatase 2C domain of Cac1, the adenylyl cyclase of the human pathogen Cryptococcus neoformans, has an unusual structure but functions as a metal-dependent serine/threonine phosphatase. Deletion of this domain or the adenylyl cyclase catalytic domain demonstrated that the protein phosphatase 2C domain is required for full Cac1 activity, influencing melanin and capsule synthesis, sexual differentiation, titan cell formation, and cell wall integrity. Notably, loss of the protein phosphatase 2C domain induces type 2 helper T-cell-biased immunity and extensive pulmonary damage yet does not cause mortality in mice. Integrated transcriptomic and phosphoproteomic analyses further revealed shared and domain-specific signalling outputs. Together, these findings define a pivotal role for the adenylyl cyclase-linked protein phosphatase 2C domain in C. neoformans pathobiology.

microbiology↗

BOGO: A Proteome-Wide Gene Overexpression Platform for Discovering Rational Cancer Combination Therapies

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/673780v2_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@19d5d7dorg.highwire.dtl.DTLVardef@64f7eborg.highwire.dtl.DTLVardef@d08b75org.highwire.dtl.DTLVardef@173c448_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG Cancer drug resistance remains a major barrier to durable treatment success, often leading to relapse despite advances in precision oncology. While combination therapies are being increasingly investigated, such as chemotherapy with small molecule inhibitors, predicting drug response and identifying rational drug combinations based on resistance mechanisms remain major challenges. Therefore, a proteome-wide, single-gene overexpression screening platform is essential for guiding rational therapy selection. Here, we present BOGO (Bxb1-landing pad human ORFeome-integrated system for a proteome-wide Gene Overexpression), a robust, scalable, and reproducible screening platform that enables single-copy, site-specific integration and overexpression of [~]19,000 human open across cancer cell models. Using BOGO, we identified drug-specific response drivers for 16 chemotherapeutic agents and integrated clinical datasets to uncover proliferation and resistance-associated genes with prognostic potential. Drug response similarity networks revealed both shared and unique mechanisms, highlighting key pathways such as autophagy, apoptosis, and Wnt signaling, and notable resistance-associated genes including BCL2, POLD2, and TRADD. In particular, we proposed a synergistic combination of the BCL2 family inhibitor ABT-263 (Navitoclax(R)) and the DNA analog TAS-102 (Lonsurf(R)), which revealed that lysosomal modulation is a key mechanism driving DNA analog resistance. This combination therapy selectively enhanced cytotoxicity in colorectal and pancreatic cancer cells in vitro, and demonstrated therapeutic benefit in vivo in both cell line-derived xenograft (CDX) and patient-derived xenograft (PDX) models. Together, these findings establish BOGO as a powerful gene overexpression perturbation platform for systematically identifying chemoresistance and chemosensitization drivers, and for discovering rational combination therapies. Its scalability and reproducibility position BOGO as a broadly applicable tool for functional genomics and therapeutic discovery beyond cancer resistance.

systems biology↗

An integrated in silico-in vitro workflow for discovering high-affinity, selective antibodies to the KRAS(G12D)-MHC I complex

Antibodies that recognize peptide-loaded class I major histocompatibility complex (pMHC I) molecules could enable therapeutic targeting of intracellular oncogenic proteins, yet their discovery has been hampered by the small size of peptide antigens and allele-specificity. We describe an integrated in silico-in vitro workflow for generating high-affinity, selective antibodies to KRAS(G12D)10 presented by HLA-C*08:02, a clinically validated cancer neoantigen. In silico, multiple human antibody-derived variable fragments (Fvs) plausibly docked to the target pMHC were generated, followed by limited complementarity-determining region (CDR) sequence design. In vitro, CDR diversity was introduced at 3-4 positions per Fv to construct yeast surface display library for iterative selections. This workflow yielded antibodies with exclusive binding to KRAS(G12D)10/HLA-C*08:02 without cross-reactivity. Affinity maturation achieved nanomolar dissociation constants, and incorporation into chimeric antigen receptor T cells enabled specific activation against target-positive cells. This study establishes a practical design-to-function pipeline for TCR-like antibody discovery, and demonstrates the feasibility of therapeutic targeting against KRAS(G12D)-driven malignancies.

biochemistry↗

A global genetic interaction map of a human cell reveals conserved principles of genetic networks

We generated a genome-scale, genetic interaction network from the analysis of more than 4 million double mutants in the haploid human cell line, HAP1. The network maps [~]90,000 genetic interactions, including thousands of extreme synthetic lethal and genetic suppression interactions. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes, pathways, biological processes, and cellular compartments. Comparative analyses showed that general principles of genetic networks are conserved from yeast to human cells. A genetic interaction network mapped in a single genetic background complements the DepMap gene co-essentiality network, recapitulating many of the same biological connections and also capturing unique functional information to reveal roles of uncharacterized genes and molecular determinants of specific cancer cell line genetic dependencies.

systems biology↗

Transcriptomic profiling of a novel gastric implantation model identifies mechanisms and pathways that drive implantation into explanted human peritoneum

Epithelial cancers such as stomach and ovary cancer tend to metastasize to the peritoneum, often leading to intractable disease and poor survival. Currently, the mechanisms that enable gastric cancer cells to penetrate the mesothelium, and to implant, invade, and survive in the peritoneal niche are poorly understood. To investigate these mechanisms, we developed a novel human peritoneal explant model. Briefly, fresh peritoneal tissue samples from abdominal surgery patients were cultured on top of a layer of GFP-labeled human gastric adenocarcinoma cells (AGS); 2% of these cells implanted into the peritoneum. The transcriptomic profile of the implanted AGS cells was compared to the profile of AGS cells that failed to implant using RNA sequencing. Differentially expressed genes were enriched significantly (fold change>2) for genes that enable cell adhesion, motility, and membrane depolarization. We compared this list of genes with a previously identified peritoneal metastasis whole exome sequencing dataset (SRP043661). Upon further analysis based on subcellular localization, cell adhesion and cytoskeletal organization, we found nine core "peritoneal implantation" genes. We functionally validated these genes with CRISPR knockout and assessed peritoneal implantation and invasion using the human peritoneal explant model described above. From these data we identified ADAM12 as a key player of peritoneal metastasis. Knock out of ADAM12 significantly impaired peritoneal metastasis in vivo and ex vivo. Exploration of three publicly available independent datasets indicated that ADAM12 is indeed clinically relevant in peritoneal metastasis. To explore the role of ITGA{beta}1 in mediating cell-matrix interactions in the presence of ADAM12, we performed ITGA{beta}1 pull-down assays followed by mass spectrometry analysis in ADAM12 WT cells. ADAM12 KO cells show a marked disruption of the ITGA{beta}1 interactome in GCa cells. Key cytoskeletal proteins such as MYH14, MYH10, MYH9, ACTA2, SPTN1 and TPM1-TPM4 were found to be interactors with ITGA{beta}1 in ADAM12 WT cells but not ADAM12 KO cells. Our approach and the new data identify a distinct peritoneal metastasis gene set that facilitates implantation and invasion of gastric cancer cells within the peritoneum. Disruption of these pathways with peritoneal-directed therapies has the potential to improve survival in patients with high-risk primary gastric cancer.

cancer biology↗

A comprehensive two-hybrid analysis to explore the L. pneumophila effector-effector interactome

Legionella pneumophila uses over 300 translocated effector proteins to rewire host cells during infection and create a replicative niche for intracellular growth. To date, several studies have identified L. pneumophila effectors that indirectly and directly regulate the activity of other effectors, providing an additional layer of regulatory complexity. Amongst these are "metaeffectors" - a special class of effectors that regulate the activity of other effectors once inside the host. A defining feature of metaeffectors is direct, physical interaction with a target effector. Metaeffector identification to date has depended on phenotypes in heterologous systems and experimental serendipity. Using a multiplexed, recombinant-barcode-based yeast two-hybrid technology we screened for protein-protein interactions amongst all L. pneumophila effectors and several components of the Dot/Icm type IV secretion system (>167,000 protein combinations). Of the 52 protein interactions identified by this approach, 44 are novel protein interactions, including ten novel effector-effector interactions (doubling the number of known effector-effector interactions).

microbiology↗

Formation of a giant unilocular vacuole via macropinocytosis-like process confers anoikis resistance

Cell survival in metazoans depends on cell attachment to the extracellular matrix (ECM) or to neighboring cells. Loss of such attachment triggers a type of programmed cell death known as anoikis, the acquisition of resistance to which is a key step in cancer development. The mechanisms underlying anoikis resistance remain unclear, however. The intracellular F-actin cytoskeleton plays a key role in sensing the loss of cell-ECM attachment, but how its disruption affects cell fate during such stress is not well understood. Here, we reveal a cell survival strategy characterized by the formation of a giant unilocular vacuole (GUVac) in the cytoplasm of the cells whose actin cytoskeleton is disrupted during loss of matrix attachment. Time-lapse imaging and electron microscopy showed that large vacuoles with a diameter of >500 nm accumulated early after inhibition of actin polymerization in cells in suspension culture, and that these vacuoles subsequently coalesced to form a GUVac. GUVac formation was found to result from a variation of a macropinocytosis-like process, characterized by the presence of inwardly curved membrane invaginations. This phenomenon relies on both F-actin depolymerization and the recruitment of septin proteins for micron-sized plasma membrane invagination. The vacuole fusion step during GUVac formation requires PI(3)P produced by VPS34 and PI3K-C2 on the surface of vacuoles. Furthermore, its induction after loss of matrix attachment conferred anoikis resistance. Our results thus show that the formation of a previously unrecognized organelle promotes cell survival in the face of altered actin and matrix environments.

cell biology↗

Microvilli regulate the release modes of alpha-tectorin to organize the domain-specific matrix architecture of the tectorial membrane.

The tectorial membrane (TM) is an apical extracellular matrix (ECM) in the cochlea essential for auditory transduction. The TM exhibits highly ordered domain-specific architecture. Alpha-tectorin/TECTA is a glycosylphosphatidylinositol (GPI)-anchored ECM protein essential for TM organization. Here, we identified that TECTA is released by distinct modes: proteolytic shedding by TMPRSS2 and GPI-anchor-dependent release from the microvillus tip. In the medial/limbal domain, proteolytically shed TECTA forms dense fibers. In the lateral/body domain produced by the supporting cells displaying dense microvilli, the proteolytic shedding restricts TECTA to the microvillus tip and compartmentalizes the collagen-binding site. The tip-localized TECTA, in turn, is released in a GPI-anchor-dependent manner to form collagen-crosslinking fibers, required for maintaining the spacing and parallel organization of collagen fibrils. Overall, we showed that distinct release modes of TECTA determine the domain-specific organization pattern, and the microvillus coordinates the release modes along its membrane to organize the higher-order ECM architecture. O_FIG O_LINKSMALLFIG WIDTH=146 HEIGHT=200 SRC="FIGDIR/small/574255v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@10479c6org.highwire.dtl.DTLVardef@d6cb33org.highwire.dtl.DTLVardef@1b6b4fdorg.highwire.dtl.DTLVardef@2477f4_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

developmental biology↗

SUBTLE: An unsupervised platform with temporal link embedding that maps animal behavior

While huge strides have recently been made in language-based machine learning, the ability of artificial systems to comprehend the sequences that comprise animal behavior has been lagging behind. In contrast, humans instinctively recognize behaviors by finding similarities in behavioral sequences. Here, we develop an unsupervised behavior-mapping framework, SUBTLE (spectrogram-UMAP-based temporal-link embedding), to capture comparable behavioral repertoires from 3D action skeletons. To find the best embedding method, we devise a temporal proximity index as a metric to gauge temporal representation in the behavioral embedding space. The method achieves the best performance compared to current embedding strategies. Its spectrogram-based UMAP clustering not only identifies subtle inter-group differences but also matches human-annotated labels. SUBTLE framework automates the tasks of both identifying behavioral repertoires like walking, grooming, standing, and rearing, and profiling individual behavior signatures like subtle inter-group differences by age. SUBTLE highlights the importance of temporal representation in the behavioral embedding space for human-like behavioral categorization. One Sentence SummaryUnsupervised behavior-mapping from 3D action skeletons achieves superior performance, captures behavioral repertoires, and identifies inter-group differences, emphasizing how temporal representation is critical in the behavioral embedding space.

neuroscience↗

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

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.

cell biology↗

Spontaneous emergence of music detectors in a deep neural network trained for natural sound recognition

Music exists in almost every society, has universal acoustic features, and is processed by distinct neural circuits in humans even with no experience of musical training. These characteristics suggest an innateness of the sense of music in our brain, but it is unclear how this innateness emerges and what functions it has. Here, using an artificial deep neural network that models the auditory information processing of the brain, we show that units tuned to music can spontaneously emerge by learning natural sound detection, even without learning music. By simulating the responses of network units to 35,487 natural sounds in 527 categories, we found that various subclasses of music are strongly clustered in the embedding space, and that this clustering arises from the music-selective response of the network units. The music-selective units encoded the temporal structure of music in multiple timescales, following the population-level response characteristics observed in the brain. We confirmed that the process of generalization is critical for the emergence of music-selectivity and that music-selectivity can work as a functional basis for the generalization of natural sound, thereby elucidating its origin. These findings suggest that our sense of music can be innate, universally shaped by evolutionary adaptation to process natural sound. One-sentence summaryMusic-selectivity can arise spontaneously in deep neural networks trained for natural sound detection without learning music.

neuroscience↗

Host diversity and behavior determine patterns of interspecies transmission and geographic diffusion of avian Influenza A subtypes among North American wild reservoir species

Wild birds can carry avian influenza viruses (AIV), including those with pandemic or panzootic potential, long distances. Even though AIV has a broad host range, few studies account for host diversity when estimating AIV spread. We analyzed AIV genomic sequences from North American wild birds, including 303 newly sequenced isolates, to estimate interspecies transmission and geographic diffusion patterns among multiple co-circulating subtypes. Our results show high transition rates within Anseriformes and Charadriiformes, but limited transitions between these orders. Patterns of interspecies transmission were positively associated with breeding habitat range overlap, and negatively associated with host genetic distance. Distance between regions (negative correlation) and summer temperature at origin (positive correlation) were strong predictors of diffusion. Taken together, this study demonstrates that host diversity and ecology can determine evolutionary processes that underlie AIV natural history and spread. Understanding these processes can provide important insights for effective control of AIV.

evolutionary biology↗

Interactome and structural basis for targeting the human T-cell leukemia virus Tax oncoprotein

Human T-cell leukemia virus type-1 (HTLV-1) is the causative agent of adult T-cell leukemia (ATL). Although ATL is a well-characterized T-cell neoplasm, linked to intermittent expression of the viral Tax-1 protein, there is currently no strategy to target Tax-1 functions using small molecules. Here, we report a comprehensive interaction map between Tax-1 and human PDZ domain-containing proteins (hPDZome). We show that Tax-1 interacts with more than one-third of hPDZome components, including proteins involved in cell cycle, cell-cell junctions, cytoskeleton organization, and membrane complex assembly. Using nuclear magnetic resonance (NMR) spectroscopy, we have determined the structural basis of the interaction between the C-terminal PDZ binding motif (PBM) of Tax-1, and the PDZ domains of syntenin-1, an evolutionary conserved hub that controls exosome trafficking. Finally, we have used confocal imaging, molecular modelling, NMR and mammalian cell-based assays to demonstrate that the Tax-1/syntenin-1 interaction is amenable to small-molecule inhibition. Altogether, our study highlights the biological significance of Tax-PDZ interactome and its interplay with exosome formation. It shows a direct link between extracellular vesicles and HTLV-1 transmission, providing a novel framework for the design of targeted therapies for HTLV-1-induced diseases.

biochemistry↗

Binary Interactome Models of Inner- Versus Outer-Complexome Organization

Hundreds 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.

systems biology↗

A map of direct SARS-CoV-2 protein interactions implicates specific human host processes

Key steps in viral propagation, immune suppression, and pathology are mediated by direct, binary, physical interactions between viral and host proteins. To understand the biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, we generated an unbiased systematic map of binary interactions between viral and host proteins, complementing previous co-complex association maps by conveying more direct mechanistic understanding and potentially enabling targeted disruption of direct interactions. To this end, we deployed two parallel strategies, identifying 205 virus-host and 27 intraviral binary interactions amongst 171 host and 19 viral proteins, and confirming high quality of these interactions via a calibrated orthogonal assay. Host proteins interacting with SARS-CoV-2 proteins are enriched in various cellular processes, including immune signaling and inflammation, protein ubiquitination, and membrane trafficking. Specific subnetworks provide new hypotheses related to viral modulation of host protein homeostasis and T-cell regulation. The binary virus-host protein interactions we identified can now be prioritized as targets for therapeutic intervention. More generally, we provide a resource of systematic maps describing which SARS-CoV-2 and human proteins interact directly.

systems biology↗