Protein Interaction Mapping Identifies RBBP6 as a Negative Regulator of Ebola Virus Replication

FGF2 Mediated USP42-PPARγ Axis Activation Ameliorates Liver Oxidative Damage and Promotes Regeneration

Liver regeneration is critical for maintaining whole-body homeostasis, especially under exposure to deadly chemical toxins. Understanding the molecular mechanisms underlying liver repair is critical for the development of intervention strategies to treat liver diseases. In this study, ubiquitin-specific Proteases 42 (USP42) is identified as a novel deubiquitinases (DUB) of peroxisome proliferators-activated receptor γ (PPARγ) in hepatocytes. This DUB interacted, deubiquitinated, and stabilized PPARγ, and increased PPARγ targeted proliferative and antioxidative gene expressions, which protects the liver from carbon tetrachloride (CCL4) induced oxidative injury and promotes liver regeneration. In addition, fibroblast growth factor 2 (FGF2) initiated USP42 expression and enhanced the interaction between USP42 and PPARγ during the liver regeneration process. Moreover, the PPARγ full agonist, rosiglitazone (RSG), possesses the ability to further reinforce the USP42-PPARγ interplay, which enlightens to construct of an extracellular vesicle-based targeting strategy to activate the liver USP42-PPARγ axis and promote liver regeneration. In summary, the work uncovers the importance of USP42-PPARγ axis-mediated liver tissue homeostasis and provides a promising regimen to target this protein-protein interplay for liver regeneration.

Ebola virus nucleoprotein interaction with host protein phosphatase-1 regulates its dimerization and capsid formation

Ebola virus (EBOV) replication is regulated by the host protein phosphatases, PP1 and PP2A, which dephosphorylate the transcriptional cofactor of EBOV polymerase VP30. The PP1-targeting compound 1E7-03 induces VP30 phosphorylation and inhibits EBOV infection. Here, we investigate the broader role of PP1 in EBOV replication and transcription, including its interaction with nucleoprotein (NP). When EBOV-infected cells were continuously treated with 1E7-03, the NP E619K mutation was found and selected for further analysis. The NP E619K mutation moderately reduced the EBOV minigenome transcription, which was restored by the treatment with 1E7-03. Proteomics, immunoprecipitation, dimerization, split NanoBit, and colocalization analyses indicated that NP interacts with PP1 and that NP E619K mutations enhanced this binding. Treatment with 1E7-03 dissociated PP1-NP complex, but enhanced NP dimerization, which was more pronounced for NP E619K mutant. Mutation and deletion analyses pointed to several potential PP1-binding sites in NP that were located in the moderately disordered NP regions. When NP was co-expressed with VP24 and VP35, formation of EBOV capsids was impaired with NP E619K mutation. Treatment with 1E7-03 restored the capsid formation by the NP E619K mutant but inhibited capsids formed by WT NP. Our findings suggest that PP1 binds to NP and that this binding might regulate NP dimerization and capsid formation. Collectively, our results point to a new role for PP1 in EBOV replication, in which NP binding to PP1 may facilitate viral transcription by delaying capsid formation and EBOV replication.

Supervised learning approaches for predicting Ebola-Human Protein-Protein interactions

The goal of this research work is to predict protein-protein interactions (PPIs) between the Ebola virus and the host who is at risk of infection. Since there are very limited databases available on the Ebola virus; we have prepared a comprehensive database of all the PPIs between the Ebola virus and human proteins (EbolaInt). Our work focuses on the finding of some new protein-protein interactions between humans and the Ebola virus using some state- of-the-arts machine learning techniques. However, it is basically a two-class problem with a positive interacting dataset and a negative non-interacting dataset. These datasets contain various sequence-based human protein features such as structure of amino acid and conjoint triad and domain-related features. In this research, we have briefly discussed and used some well-known supervised learning approaches to predict PPIs between human proteins and Ebola virus proteins, including K-nearest neighbours (KNN), random forest (RF), support vector machine (SVM), and deep feed-forward multi-layer perceptron (DMLP) etc. We have validated our prediction results using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Our goal with this prediction is to compare all other models' accuracy, precision, recall, and f1-score for predicting these PPIs. In the result section, DMLP is giving the highest accuracy along with the prediction of 2655 potential human target proteins.

Ginkgolic acid inhibits Ebola virus transcription and replication by disrupting the interaction between nucleoprotein and VP30 protein

The Ebola virus, a filovirus, has been responsible for significant human fatalities since its discovery. Despite extensive research, effective small-molecule drugs remain elusive due to its complex pathogenesis. Inhibition of RNA synthesis is a promising therapeutic target, and the VP30 protein plays a critical role in this process. The interaction between VP30 and the nucleoprotein (NP) is essential for viral replication. We identified ginkgolic acid as a small molecule with strong affinity for VP30, which was validated through multiple assays, including thermal shift, surface plasmon resonance, fluorescence polarization, pull-down, and co-immunoprecipitation. The antiviral efficacy of ginkgolic acid was demonstrated in the EBOV transcription- and replication-competent virus-like particle (trVLP) system. Furthermore, we resolved the crystal structure of the VP30-ginkgolic acid complex, revealing two ginkgolic acid molecules located at the VP30/NP interaction interface. This structural information provides insight into the molecular basis of ginkgolic acid's antiviral activity and suggests a novel therapeutic strategy targeting the VP30/NP interaction.

Proximity Proteomics to Profile Ebola Virus Protein Interactome in Its Functional Context

Proximity labeling-based proteomics (proximity proteomics) has emerged as a popular and versatile approach to illuminate the molecular interactions between viruses and their hosts. In this approach, a proximity labeling enzyme tag is fused to a bait protein and labels neighboring proteins with a chemical handle such as biotin, allowing for downstream affinity purification. Compared to another widely used technique, affinity purification coupled mass spectrometry, proximity proteomics enables the detection of low affinity or transient interactors that might have important functions in the viral life cycle. Further, proximity proteomics can identify interactors of a labile bait protein, of which affinity purification is technically challenging. Here, we describe a proximity proteomic protocol to identify cellular interactors of the Ebola virus polymerase. A similar strategy is readily applicable to elucidate the virus-host interactions for Marburg virus.

N Protein of Tomato Spotted Wilt Virus Proven to Be Antagonistic Against Tomato Yellow Leaf Curl Virus in Nicotiana benthamiana

Two phylogenetically unrelated viruses transmitted by different insect vectors, tomato spotted wilt virus (TSWV) and tomato yellow leaf curl virus (TYLCV), are major threats to tomato and other vegetable production. Although co-infections of TSWV and TYLCV on the same host plant have been reported on numerous occasions, there is still lack of research attempting to elucidate the mechanisms underlying the relationship between two viruses when they coexist in the same tomato or other plants. After assessing the effect of four TSWV-coded proteins on suppressing TYLCV in TSWV N transgenic Nicotiana benthamiana seedlings, the TSWV N protein proved to be effective in reducing TYLCV quantity and viral symptoms. Western blot analysis indicated that TSWV N was involved in down-regulating the expression level of the V1, C3, and C4 proteins of TYLCV, among which V1 was the most significantly suppressed one. Moreover, TSWV N was confirmed to reduce TYLCV V1 within both nucleus and cytoplasm, but a greater suppression was observed in cytoplasm. The co-immunoprecipitation and mass spectrometry identified 244 differential proteins from the TYLCV-infected TSWV N transgenic N. benthamiana seedling. These proteins pertaining to energy metabolism pathways were enriched, suggesting that TSWV N could inhibit TYLCV through competing for energy or regulating energy-related metabolism. The evidence presented here offers a novel perspective that will facilitate a comprehensive understanding of virus-virus and virus-host interactions, as well as a potential strategy for plant virus control through using TSWV N in the near future.

AP3B1 facilitates PDIA3/ERP57 function to regulate rabies virus glycoprotein selective degradation and viral entry

Rabies virus causes an estimated 59,000 annual fatalities worldwide and promising therapeutic treatments are necessary to develop. In this study, affinity tag-purification mass spectrometry was employed to delineate RABV glycoprotein and host protein interactions, and PDIA3/ERP57 was identified as a potential inhibitor of RABV infection. PDIA3 restricted RABV infection with follow mechanisms: PDIA3 mediated the degradation of RABV G protein by targeting lysine 332 via the selective macroautophagy/autophagy pathway; The PDIA3 interactor, AP3B1 (adaptor related protein complex 3 subunit beta 1) was indispensable in PDIA3-triggered selective degradation of the G protein; Furthermore, PDIA3 competitively bound with NCAM1/NCAM (neural cell adhesion molecule 1) to block RABV G, hindering viral entry into host cells. PDIA3 190-199 aa residues bound to the RABV G protein were necessary and sufficient to defend against RABV. These results demonstrated the therapeutic potential of biologics that target PDIA3 or utilize PDIA3 190-199 aa peptide to treat clinical rabies.Abbreviation: aa: amino acids; ANXA2: annexin A2; AP-MS: affinity tag purification-mass spectrometry; AP3B1: adaptor related protein complex 3 subunit beta 1; ATP6V1A: ATPase H+ transporting V1 subunit A; ATP6V1H: ATPase H+ transporting V1 subunit H; BafA1: bafilomycin A1; CHX: cycloheximide; co-IP: co-immunoprecipitation; DDX17: DEAD-box helicase 17; DmERp60: drosophila melanogaster endoplasmic reticulum p60; EBOV: Zaire ebolavirus virus; EV: empty vector; GANAB: glucosidase II alpha subunit; G protein: glycoprotein; GRM2/mGluR2: glutamate metabotropic receptor 2; HsPDIA3: homo sapiens protein disulfide isomerase family A member 3; IAV: influenza virus; ILF2: interleukin enhancer binding factor 2; KO: knockout; MAGT1: magnesium transporter 1; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MmPDIA3: mus musculus protein disulfide isomerase associated 3; NCAM1/NCAM: neural cell adhesion molecule 1; NGFR/p75NTR: nerve growth factor receptor; NGLY1: N-glycanase 1; OTUD4: OTU deubiquitinase 4; PDI: protein disulfide isomerase; PPIs: protein-protein interactions; RABV: rabies virus; RUVBL2: RuvB like AAA ATPase 2; SCAMP3: secretory carrier membrane protein 3; ScPdi1: Saccharomyces cerevisiae s288c protein disulfide isomerase 1; SLC25A6: solute carrier family 25 member 6; SQSTM1/p62: sequestosome 1; VSV: vesicular stomatitis virus.

RNA binding motif 4 inhibits the replication of ebolavirus by directly targeting 3'-leader region of genomic RNA

Ebola virus (EBOV) belongs to Filoviridae family possessing single-stranded negative-sense RNA genome, which is a serious threat to human health. Nowadays, no therapeutics have been proven to be successful in efficiently decreasing the mortality rate. RNA binding proteins (RBPs) are reported to participate in maintaining cell integrity and regulation of viral replication. However, little is known about whether and how RBPs participate in regulating the life cycle of EBOV. In our study, we found that RNA binding motif protein 4 (RBM4) inhibited the replication of EBOV in HEK293T and Huh-7 cells by suppressing viral mRNA production. Such inhibition resulted from the direct interaction between the RRM1 domain of RBM4 and the "CU" enrichment elements located in the PE1 and TSS of the 3'-leader region within the viral genome. Simultaneously, RBM4 could upregulate the expression of some cytokines involved in the host innate immune responses to synergistically exert its antiviral function. The findings therefore suggest that RBM4 might serve as a novel target of anti-EBOV strategy.

Analysis of the serum proteome profile of wild stump-tailed macaques (Macaca arctoides) seropositive for Zika virus antibodies in Thailand

Zika virus (ZIKV) is a member of the Flaviviridae virus family and poses a significant global health concern. ZIKV is transmitted by Aedes mosquitoes, and it has been implicated in various neurological conditions associated with fetal brain development. ZIKV has two transmission cycles: a sylvatic cycle in which nonhuman primates are infected via arboreal mosquito bites, and an interhuman (urban) cycle in which the virus is transmitted among primates by Aedes mosquitoes. ZIKV was first discovered in wild macaques, and the danger posed by the virus is increased due to the close proximity between humans and wild animals in modern society. However, data regarding the extent and role of infection in nonhuman primates are limited. Thus, there is an urgent need for improved surveillance, diagnostic methods, and public health interventions to effectively combat ZIKV transmission and its associated health impacts in Southeast Asia. In this study, we used a proteomics and bioinformatics approach to profile serum proteins in wild stump-tailed macaques seropositive for neutralizing antibodies against ZIKV. A total of 9,532 total proteins were identified, and 338 differentially expressed proteins were identified between naïve and seropositive animals. A total of 52 important proteins were used to construct a serum proteomic profile. These 52 important proteins were associated with immune and inflammatory responses (36.54%), neurological damage (23.08%), viral activities (21.15%), the apoptosis signaling pathway (9.61%), and other pathways (9.61%). Our proteomic profile identified proteins that inhibit the apoptosis pathway, intracellular resource competition with the virus, and neurological damage due to ZIKV and the host immune and defense responses.

The role of lipoprotein‑associated phospholipase A2 in inflammatory response and macrophage infiltration in sepsis and the regulatory mechanisms

Lipoproteinassociated phospholipase A2 (Lp-PLA2), encoded by the phospholipase A2 group VII (Pla2g7) gene, has been pertinent to inflammatory responses. This study investigates the correlation between Lp-PLA2 and inflammatory injury in septic mice and explores its regulatory mechanism. Lp-PLA2 was found to be upregulated in the serum of septic mice induced by cecal ligation and puncture and in the culture supernatant of RAW264.7 cells following lipopolysaccharide and adenosine triphosphate treatments. The contents of Lp-PLA2 were positively correlated with increased concentrations of proinflammatory cytokines in patients with sepsis. Both animal and cellular models showed increased concentrations of proinflammatory cytokines. Spi-1 proto-oncogene (Spi1), highly expressed in these models, was found to activate Pla2g7 transcription. Knockdown of Pla2g7 or Spi1 reduced the proinflammatory cytokine production, mitigated organ damage in mice, and suppressed macrophage migration in vitro. Retinoblastoma binding protein 6 (Rbbp6), poorly expressed in both models, was found to reduce Spi1 protein stability through ubiquitination modification. Rbbp6 overexpression similarly suppressed inflammatory activation of RAW264.7 cells, which was counteracted by Pla2g7 or Spi1 upregulation. In summary, this study demonstrates that the Pla2g7 loss and Spi1 upregulation participate in inflammatory responses in sepsis by elevating the Lp-PLA2 levels.

Host-pathogen interactions of emerging zoonotic viruses: bats, humans and filoviruses

This paper provides an overview of the phenomena of cross-species transmission of viruses (known as spillover), focusing on the highly pathogenic filovirus family and their natural reservoir: bats. It also describes the host-pathogen relationship of viruses and their reservoirs, in addition to humans, and discusses current theories of persistent infection.

I'm Walking into Spiderwebs: Making Sense of Protein-Protein Interaction Data

Protein-protein interactions (PPIs) are at the heart of the molecular landscape permeating life. Proteomics studies can explore this protein interaction landscape using mass spectrometry (MS). Thanks to their high sensitivity, mass spectrometers can easily identify thousands of proteins within a single sample, but that same sensitivity generates tangled spiderwebs of data that hide biologically relevant findings. So, what does a researcher do when she finds herself walking into spiderwebs? In a field focused on discovery, MS data require rigor in their analysis, experimental validation, or a combination of both. In this Review, we provide a brief primer on MS-based experimental methods to identify PPIs. We discuss approaches to analyze the resulting data and remove the proteomic background. We consider the advantages between comprehensive and targeted studies. We also discuss how scoring might be improved through AI-based protein structure information. Women have been essential to the development of proteomics, so we will specifically highlight work by women that has made this field thrive in recent years.

A T-Cell-Derived 3-Gene Signature Distinguishes SARS-CoV-2 from Common Respiratory Viruses

Research on the host responses to respiratory viruses could help develop effective interventions and therapies against the current and future pandemics from the host perspective. To explore the pathogenesis that distinguishes SARS-CoV-2 infections from other respiratory viruses, we performed a multi-cohort analysis with integrated bioinformatics and machine learning. We collected 3730 blood samples from both asymptomatic and symptomatic individuals infected with SARS-CoV-2, seasonal human coronavirus (sHCoVs), influenza virus (IFV), respiratory syncytial virus (RSV), or human rhinovirus (HRV) across 15 cohorts. First, we identified an enhanced cellular immune response but limited interferon activities in SARS-CoV-2 infection, especially in asymptomatic cases. Second, we identified a SARS-CoV-2-specific 3-gene signature (CLSPN, RBBP6, CCDC91) that was predominantly expressed by T cells, could distinguish SARS-CoV-2 infection, including Omicron, from other common respiratory viruses regardless of symptoms, and was predictive of SARS-CoV-2 infection before detectable viral RNA on RT-PCR testing in a longitude follow-up study. Thereafter, a user-friendly online tool, based on datasets collected here, was developed for querying a gene of interest across multiple viral infections. Our results not only identify a unique host response to the viral pathogenesis in SARS-CoV-2 but also provide insights into developing effective tools against viral pandemics from the host perspective.

Molecular insights into the Ebola virus life cycle

Ebola virus and other orthoebolaviruses cause severe haemorrhagic fevers in humans, with very high case fatality rates. Their non-segmented single-stranded RNA genome encodes only seven structural proteins and a small number of non-structural proteins to facilitate the virus life cycle. The basics of this life cycle are well established, but recent advances have substantially increased our understanding of its molecular details, including the viral and host factors involved. Here we provide a comprehensive overview of our current knowledge of the molecular details of the orthoebolavirus life cycle, with a special focus on proviral host factors. We discuss the multistep entry process, viral RNA synthesis in specialized phase-separated intracellular compartments called inclusion bodies, the expression of viral proteins and ultimately the assembly of new virus particles and their release at the cell surface. In doing so, we integrate recent studies into the increasingly detailed model that has developed for these fundamental aspects of orthoebolavirus biology.

Mapping protein-protein interactions by mass spectrometry

Protein-protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization and function of the proteome, and their perturbation is associated with various diseases, such as cancer, neurodegeneration, and infectious diseases. Recent advances in mass spectrometry (MS)-based protein interactomics have significantly expanded our understanding of the PPIs in cells, with techniques that continue to improve in terms of sensitivity, and specificity providing new opportunities for the study of PPIs in diverse biological systems. These techniques differ depending on the type of interaction being studied, with each approach having its set of advantages, disadvantages, and applicability. This review highlights recent advances in enrichment methodologies for interactomes before MS analysis and compares their unique features and specifications. It emphasizes prospects for further improvement and their potential applications in advancing our knowledge of PPIs in various biological contexts.

Multi-level bioinformatics resources support drug target discovery of protein-protein interactions

Drug discovery often begins with a new target. Protein-protein interactions (PPIs) are crucial to multitudinous cellular processes and offer a promising avenue for drug-target discovery. PPIs are characterized by multi-level complexity: at the protein level, interaction networks can be used to identify potential targets, whereas at the residue level, the details of the interactions of individual PPIs can be used to examine a target's druggability. Much great progress has been made in target discovery through multi-level PPI-related computational approaches, but these resources have not been fully discussed. Here, we systematically survey bioinformatics tools for identifying and assessing potential drug targets, examining their characteristics, limitations and applications. This work will aid the integration of the broader protein-to-network context with the analysis of detailed binding mechanisms to support the discovery of drug targets.

Single-cell image-based genetic screens systematically identify regulators of Ebola virus subcellular infection dynamics

Ebola virus (EBOV) is a high-consequence filovirus that gives rise to frequent epidemics with high case fatality rates and few therapeutic options. Here, we applied image-based screening of a genome-wide CRISPR library to systematically identify host cell regulators of Ebola virus infection in 39,085,093 million single cells. Measuring viral RNA and protein levels together with their localization in cells identified over 998 related host factors and provided detailed information about the role of each gene across the virus replication cycle. We trained a deep learning model on single-cell images to associate each host factor with predicted replication steps, and confirmed the predicted relationship for select host factors. Among the findings, we showed that the mitochondrial complex III subunit UQCRB is a post-entry regulator of Ebola virus RNA replication, and demonstrated that UQCRB inhibition with a small molecule reduced overall Ebola virus infection with an IC50 of 5 μM. Using a random forest model, we also identified perturbations that reduced infection by disrupting the equilibrium between viral RNA and protein. One such protein, STRAP, is a spliceosome-associated factor that was found to be closely associated with VP35, a viral protein required for RNA processing. Loss of STRAP expression resulted in a reduction in full-length viral genome production and subsequent production of non-infectious virus particles. Overall, the data produced in this genome-wide high-content single-cell screen and secondary screens in additional cell lines and related filoviruses (MARV and SUDV) revealed new insights about the role of host factors in virus replication and potential new targets for therapeutic intervention.

The Role of Ebola Virus VP24 Nuclear Trafficking Signals in Infectious Particle Production

Ebola virus (EBOV) protein VP24 carries out at least two critical functions. It promotes condensation of viral nucleocapsids, which is crucial for infectious virus production, and it suppresses interferon (IFN) signaling, which requires interaction with the NPI-1 subfamily of importin-α (IMPA) nuclear transport proteins. Interestingly, over-expressed IMPA leads to VP24 nuclear accumulation and a carboxy-terminus nuclear export signal (NES) has been reported, suggesting that VP24 may undergo nuclear trafficking. For the first time, we demonstrate that NPI-1 IMPA overexpression leads to the nuclear accumulation of VP24 during EBOV infection. To assess the functional impact of nuclear trafficking, we generated tetracistronic minigenomes encoding VP24 nuclear import and/or export signal mutants. The minigenomes, which also encode Renilla luciferase and viral proteins VP40 and GP, were used to generate transcription and replication competent virus-like particles (trVLPs) that can be used to assess EBOV RNA synthesis, gene expression, entry and viral particle production. With this system, we confirmed that NES or IMPA binding site mutations altered VP24 nuclear localization, demonstrating functional trafficking signals. While these mutations minimally affected transcription and replication, the trVLPs exhibited impaired infectivity and formation of shortened nucleocapsids for the IMPA binding mutant. For the NES mutants, infectivity was reduced approximately 1000-fold. The NES mutant could still suppress IFN signaling but failed to promote nucleocapsid formation. To determine whether VP24 nuclear export is required for infectivity, the residues surrounding the wildtype NES were mutated to alanine or the VP24 NES was replaced with the Protein Kinase A Inhibitor NES. While nuclear export remained intact for these mutants, infectivity was severely impaired. These data demonstrate that VP24 undergoes nuclear trafficking and illuminates a separate and critical role for the NES and surrounding sequences in infectivity and nucleocapsid assembly.

Kernel Bayesian nonlinear matrix factorization based on variational inference for human-virus protein-protein interaction prediction

Identification of potential human-virus protein-protein interactions (PPIs) contributes to the understanding of the mechanisms of viral infection and to the development of antiviral drugs. Existing computational models often have more hyperparameters that need to be adjusted manually, which limits their computational efficiency and generalization ability. Based on this, this study proposes a kernel Bayesian logistic matrix decomposition model with automatic rank determination, VKBNMF, for the prediction of human-virus PPIs. VKBNMF introduces auxiliary information into the logistic matrix decomposition and sets the prior probabilities of the latent variables to build a Bayesian framework for automatic parameter search. In addition, we construct the variational inference framework of VKBNMF to ensure the solution efficiency. The experimental results show that for the scenarios of paired PPIs, VKBNMF achieves an average AUPR of 0.9101, 0.9316, 0.8727, and 0.9517 on the four benchmark datasets, respectively, and for the scenarios of new human (viral) proteins, VKBNMF still achieves a higher hit rate. The case study also further demonstrated that VKBNMF can be used as an effective tool for the prediction of human-virus PPIs.

A foundational atlas of autism protein interactions reveals molecular convergence

Translating high-confidence (hc) autism spectrum disorder (ASD) genes into viable treatment targets remains elusive. We constructed a foundational protein-protein interaction (PPI) network in HEK293T cells involving 100 hcASD risk genes, revealing over 1,800 PPIs (87% novel). Interactors, expressed in the human brain and enriched for ASD but not schizophrenia genetic risk, converged on protein complexes involved in neurogenesis, tubulin biology, transcriptional regulation, and chromatin modification. A PPI map of 54 patient-derived missense variants identified differential physical interactions, and we leveraged AlphaFold-Multimer predictions to prioritize direct PPIs and specific variants for interrogation in Xenopus tropicalis and human forebrain organoids. A mutation in the transcription factor FOXP1 led to reconfiguration of DNA binding sites and altered development of deep cortical layer neurons in forebrain organoids. This work offers new insights into molecular mechanisms underlying ASD and describes a powerful platform to develop and test therapeutic strategies for many genetically-defined conditions.

A protein-proximity screen reveals Ebola virus co-opts the mRNA decapping complex through the scaffold protein EDC4

The interaction of host and Ebola virus (EBOV) proteins is required for establishing infection of the cell. To identify protein binding partners, a proximity-dependent protein interaction screen was performed for six EBOV proteins. Hits were computationally mapped onto a human protein-protein interactome and then annotated with viral proteins to reveal known and previously undescribed EBOV-host protein interactions and processes. Importantly, this approach efficiently arranged proteins into functional complexes associated with single viral proteins. Focused characterization of interactions between EBOV VP35 and the mRNA decapping complex demonstrated that VP35 binds the scaffold protein EDC4 through the C-terminal subdomain, with each protein found associated in EBOV-infected cells. Mechanistically, depletion of three components of the complex each similarly inhibited viral replication by reducing early viral RNA synthesis. Overall, we demonstrate successful identification of EBOV protein interaction with entire cellular machines, providing a deeper understanding of replication mechanism for therapeutic intervention.

Human-virus protein-protein interactions maps assist in revealing the pathogenesis of viral infection

Many significant viral infections have been recorded in human history, which have caused enormous negative impacts worldwide. Human-virus protein-protein interactions (PPIs) mediate viral infection and immune processes in the host. The identification, quantification, localization, and construction of human-virus PPIs maps are critical prerequisites for understanding the biophysical basis of the viral invasion process and characterising the framework for all protein functions. With the technological revolution and the introduction of artificial intelligence, the human-virus PPIs maps have been expanded rapidly in the past decade and shed light on solving complicated biomedical problems. However, there is still a lack of prospective insight into the field. In this work, we comprehensively review and compare the effectiveness, potential, and limitations of diverse approaches for constructing large-scale PPIs maps in human-virus, including experimental methods based on biophysics and biochemistry, databases of human-virus PPIs, computational methods based on artificial intelligence, and tools for visualising PPIs maps. The work aims to provide a toolbox for researchers, hoping to better assist in deciphering the relationship between humans and viruses.

Viral Targeting of Importin Alpha-Mediated Nuclear Import to Block Innate Immunity

Cellular nucleocytoplasmic trafficking is mediated by the importin family of nuclear transport proteins. The well-characterized importin alpha (IMPA) and importin beta (IMPB) nuclear import pathway plays a crucial role in the innate immune response to viral infection by mediating the nuclear import of transcription factors such as IRF3, NFκB, and STAT1. The nuclear transport of these transcription factors ultimately leads to the upregulation of a wide range of antiviral genes, including IFN and IFN-stimulated genes (ISGs). To replicate efficiently in cells, viruses have developed mechanisms to block these signaling pathways. One strategy to evade host innate immune responses involves blocking the nuclear import of host antiviral transcription factors. By binding IMPA proteins, these viral proteins prevent the nuclear transport of key transcription factors and suppress the induction of antiviral gene expression. In this review, we describe examples of proteins encoded by viruses from several different families that utilize such a competitive inhibition strategy to suppress the induction of antiviral gene expression.

DeepProSite: structure-aware protein binding site prediction using ESMFold and pretrained language model

MOTIVATION

Identifying the functional sites of a protein, such as the binding sites of proteins, peptides, or other biological components, is crucial for understanding related biological processes and drug design. However, existing sequence-based methods have limited predictive accuracy, as they only consider sequence-adjacent contextual features and lack structural information.

RESULTS

In this study, DeepProSite is presented as a new framework for identifying protein binding site that utilizes protein structure and sequence information. DeepProSite first generates protein structures from ESMFold and sequence representations from pretrained language models. It then uses Graph Transformer and formulates binding site predictions as graph node classifications. In predicting protein-protein/peptide binding sites, DeepProSite outperforms state-of-the-art sequence- and structure-based methods on most metrics. Moreover, DeepProSite maintains its performance when predicting unbound structures, in contrast to competing structure-based prediction methods. DeepProSite is also extended to the prediction of binding sites for nucleic acids and other ligands, verifying its generalization capability. Finally, an online server for predicting multiple types of residue is established as the implementation of the proposed DeepProSite.

AVAILABILITY AND IMPLEMENTATION

The datasets and source codes can be accessed at https://github.com/WeiLab-Biology/DeepProSite. The proposed DeepProSite can be accessed at https://inner.wei-group.net/DeepProSite/.

Ebola virus VP35 perturbs type I interferon signaling to facilitate viral replication

As one of the deadliest viruses, Ebola virus (EBOV) causes lethal hemorrhagic fevers in humans and nonhuman primates. The suppression of innate immunity leads to robust systemic virus replication of EBOV, leading to enhanced transmission. However, the mechanism of EBOV-host interaction is not fully understood. Here, we identified multiple dysregulated genes in early stage of EBOV infection through transcriptomic analysis, which are highly clustered to Jak-STAT signaling. EBOV VP35 and VP30 were found to inhibit type I interferon (IFN) signaling. Moreover, exogenous expression of VP35 blocks the phosphorylation of endogenous STAT1, and suppresses nuclear translocation of STAT1. Using serial truncated mutations of VP35, N-terminal 1-220 amino acid residues of VP35 were identified to be essential for blocking on type I IFN signaling. Remarkably, VP35 of EBOV suppresses type I IFN signaling more efficiently than those of Bundibugyo virus (BDBV) and Marburg virus (MARV), resulting in stable replication to facilitate the pathogenesis. Altogether, this study enriches understanding on EBOV evasion of innate immune response, and provides insights into the interplay between filoviruses and host.

Ebola Virus Uses Tunneling Nanotubes as an Alternate Route of Dissemination

Ebola virus (EBOV) disease is marked by rapid virus replication and spread. EBOV enters the cell by macropinocytosis and replicates in the cytoplasm, and nascent virions egress from the cell surface to infect neighboring cells. Here, we show that EBOV uses an alternate route to disseminate: tunneling nanotubes (TNTs). TNTs, an actin-based long-range intercellular communication system, allows for direct exchange of cytosolic constituents between cells. Using live, scanning electron, and high-resolution quantitative 3-dimensional microscopy, we show that EBOV infection of primary human cells results in the enhanced formation of TNTs containing viral nucleocapsids. TNTs promote the intercellular transfer of nucleocapsids in the absence of live virus, and virus could replicate in cells devoid of entry factors after initial stall. Our studies suggest an alternate model of EBOV dissemination within the host, laying the groundwork for further investigations into the pathogenesis of filoviruses and, importantly, stimulating new areas of antiviral design.

Proteomic and genetic analyses of influenza A viruses identify pan-viral host targets

Influenza A Virus (IAV) is a recurring respiratory virus with limited availability of antiviral therapies. Understanding host proteins essential for IAV infection can identify targets for alternative host-directed therapies (HDTs). Using affinity purification-mass spectrometry and global phosphoproteomic and protein abundance analyses using three IAV strains (pH1N1, H3N2, H5N1) in three human cell types (A549, NHBE, THP-1), we map 332 IAV-human protein-protein interactions and identify 13 IAV-modulated kinases. Whole exome sequencing of patients who experienced severe influenza reveals several genes, including scaffold protein AHNAK, with predicted loss-of-function variants that are also identified in our proteomic analyses. Of our identified host factors, 54 significantly alter IAV infection upon siRNA knockdown, and two factors, AHNAK and coatomer subunit COPB1, are also essential for productive infection by SARS-CoV-2. Finally, 16 compounds targeting our identified host factors suppress IAV replication, with two targeting CDK2 and FLT3 showing pan-antiviral activity across influenza and coronavirus families. This study provides a comprehensive network model of IAV infection in human cells, identifying functional host targets for pan-viral HDT.

A Transformer-Based Ensemble Framework for the Prediction of Protein-Protein Interaction Sites

The identification of protein-protein interaction (PPI) sites is essential in the research of protein function and the discovery of new drugs. So far, a variety of computational tools based on machine learning have been developed to accelerate the identification of PPI sites. However, existing methods suffer from the low predictive accuracy or the limited scope of application. Specifically, some methods learned only global or local sequential features, leading to low predictive accuracy, while others achieved improved performance by extracting residue interactions from structures but were limited in their application scope for the serious dependence on precise structure information. There is an urgent need to develop a method that integrates comprehensive information to realize proteome-wide accurate profiling of PPI sites. Herein, a novel ensemble framework for PPI sites prediction, EnsemPPIS, was therefore proposed based on transformer and gated convolutional networks. EnsemPPIS can effectively capture not only global and local patterns but also residue interactions. Specifically, EnsemPPIS was unique in (a) extracting residue interactions from protein sequences with transformer and (b) further integrating global and local sequential features with the ensemble learning strategy. Compared with various existing methods, EnsemPPIS exhibited either superior performance or broader applicability on multiple PPI sites prediction tasks. Moreover, pattern analysis based on the interpretability of EnsemPPIS demonstrated that EnsemPPIS was fully capable of learning residue interactions within the local structure of PPI sites using only sequence information. The web server of EnsemPPIS is freely available at http://idrblab.org/ensemppis.

Next-generation proteomics for quantitative Jumbophage-bacteria interaction mapping

Host-pathogen interactions are pivotal in regulating establishment, progression, and outcome of an infection. While affinity-purification mass spectrometry has become instrumental in characterizing such interactions, it suffers from limitations in scalability and biological authenticity. Here we present the use of co-fractionation mass spectrometry for high throughput analysis of host-pathogen interactions from native viral infections of two jumbophages (ϕKZ and ϕPA3) in Pseudomonas aeruginosa. This approach enabled the detection of > 6000 unique host-pathogen interactions for each phage, encompassing > 50% of their respective proteomes. This deep coverage provided evidence for interactions between KZ-like phage proteins and the host ribosome, and revealed protein complexes for previously undescribed phage ORFs, including a ϕPA3 complex showing strong structural and sequence similarity to ϕKZ non-virion RNA polymerase. Interactome-wide comparison across phages showed similar perturbed protein interactions suggesting fundamentally conserved mechanisms of phage predation within the KZ-like phage family. To enable accessibility to this data, we developed PhageMAP, an online resource for network query, visualization, and interaction prediction ( https://phagemap.ucsf.edu/ ). We anticipate this study will lay the foundation for the application of co-fractionation mass spectrometry for the scalable profiling of host-pathogen interactomes and protein complex dynamics upon infection.

Lessons learned for pandemic preparedness: A collaborative network is imperative

The scientific community improvised to respond quickly to the SARS-CoV-2 pandemic without a template on how to work together on a global scale to understand and combat the virus. Here, we describe how we tackled impediments to success and the valuable lessons learned that prepare us for a future pandemic.

Ebola Virus NP Binding to Host Protein Phosphatase-1 Regulates Capsid Formation

The Ebola virus (EBOV) transcriptional regulation involves host protein phosphatases PP1 and PP2A, which dephosphorylate the transcriptional cofactor of EBOV polymerase VP30. The 1E7-03 compound, which targets PP1, induces VP30 phosphorylation and inhibits EBOV infection. This study aimed to investigate the role of PP1 in EBOV replication. When EBOV-infected cells were continuously treated with 1E7-03, the NP E619K mutation was selected. This mutation moderately reduced EBOV minigenome transcription, which was restored by the treatment with 1E7-03. Formation of EBOV capsids, when NP was co-expressed with VP24 and VP35, was impaired with NPE 619K. Treatment with 1E7-03 restored capsid formation by NP E619K mutation, but inhibited capsids formed by WT NP. The dimerization of NP E619K, tested in a split NanoBiT assay, was significantly decreased (~ 15-fold) compared to WT NP. NP E619K bound more efficiently to PP1 (~ 3-fold) but not B56 subunit of PP2A or VP30. Cross-linking and co-immunoprecipitation experiments showed fewer monomers and dimers for NP E619K which were increased with 1E7-03 treatment. NP E619K showed increased co-localization with PP1α compared to WT NP. Mutations of potential PP1 binding sites and NP deletions disrupted its interaction with PP1. Collectively, our findings suggest that PP1 binding to the NP regulates NP dimerization and capsid formation, and that NP E619K mutation, which has the enhanced PP1 binding, disrupts these processes. Our results point to a new role for PP1 in EBOV replication in which NP binding to PP1 may facilitate viral transcription by delaying capsid formation and EBOV replication.

Interferon-inducible phospholipids govern IFITM3-dependent endosomal antiviral immunity

The interferon-induced transmembrane proteins (IFITM) are implicated in several biological processes, including antiviral defense, but their modes of action remain debated. Here, taking advantage of pseudotyped viral entry assays and replicating viruses, we uncover the requirement of host co-factors for endosomal antiviral inhibition through high-throughput proteomics and lipidomics in cellular models of IFITM restriction. Unlike plasma membrane (PM)-localized IFITM restriction that targets infectious SARS-CoV2 and other PM-fusing viral envelopes, inhibition of endosomal viral entry depends on lysines within the conserved IFITM intracellular loop. These residues recruit Phosphatidylinositol 3,4,5-trisphosphate (PIP3) that we show here to be required for endosomal IFITM activity. We identify PIP3 as an interferon-inducible phospholipid that acts as a rheostat for endosomal antiviral immunity. PIP3 levels correlated with the potency of endosomal IFITM restriction and exogenous PIP3 enhanced inhibition of endocytic viruses, including the recent SARS-CoV2 Omicron variant. Together, our results identify PIP3 as a critical regulator of endosomal IFITM restriction linking it to the Pi3K/Akt/mTORC pathway and elucidate cell-compartment-specific antiviral mechanisms with potential relevance for the development of broadly acting antiviral strategies.

Predicting Protein-Peptide Interactions: Benchmarking Deep Learning Techniques and a Comparison with Focused Docking

The accurate prediction of protein structures achieved by deep learning (DL) methods is a significant milestone and has deeply impacted structural biology. Shortly after its release, AlphaFold2 has been evaluated for predicting protein-peptide interactions and shown to significantly outperform RoseTTAfold as well as a conventional blind docking method: PIPER-FlexPepDock. Since then, new AlphaFold2 models, trained specifically to predict multimeric assemblies, have been released and a new ab initio folding model OmegaFold has become available. Here, we assess docking success rates for these new DL folding models and compare their performance with our state-of-the-art, focused peptide-docking software AutoDock CrankPep (ADCP). The evaluation is done using the same dataset and performance metric for all methods. We show that, for a set of 99 nonredundant protein-peptide complexes, the new AlphaFold2 model outperforms other Deep Learning approaches and achieves remarkable docking success rates for peptides. While the docking success rate of ADCP is more modest when considering the top-ranking solution only, it samples correct solutions for around 62% of the complexes. Interestingly, different methods succeed on different complexes, and we describe a consensus docking approach using ADCP and AlphaFold2, which achieves a remarkable 60% for the top-ranking results and 66% for the top 5 results for this set of 99 protein-peptide complexes.

Large-scale phage-based screening reveals extensive pan-viral mimicry of host short linear motifs

Viruses mimic host short linear motifs (SLiMs) to hijack and deregulate cellular functions. Studies of motif-mediated interactions therefore provide insight into virus-host dependencies, and reveal targets for therapeutic intervention. Here, we describe the pan-viral discovery of 1712 SLiM-based virus-host interactions using a phage peptidome tiling the intrinsically disordered protein regions of 229 RNA viruses. We find mimicry of host SLiMs to be a ubiquitous viral strategy, reveal novel host proteins hijacked by viruses, and identify cellular pathways frequently deregulated by viral motif mimicry. Using structural and biophysical analyses, we show that viral mimicry-based interactions have similar binding strength and bound conformations as endogenous interactions. Finally, we establish polyadenylate-binding protein 1 as a potential target for broad-spectrum antiviral agent development. Our platform enables rapid discovery of mechanisms of viral interference and the identification of potential therapeutic targets which can aid in combating future epidemics and pandemics.

Next-generation interaction proteomics for quantitative Jumbophage-bacteria interaction mapping

Host-pathogen interactions (HPIs) are pivotal in regulating establishment, progression, and outcome of an infection. Affinity-purification mass spectrometry has become instrumental for the characterization of HPIs, however the targeted nature of exogenously expressing individual viral proteins has limited its utility to the analysis of relatively small pathogens. Here we present the use of co-fractionation mass spectrometry (SEC-MS) for the high-throughput analysis of HPIs from native viral infections of two jumbophages ( ϕ KZ and ϕ PA3) in Pseudomonas aeruginosa . This enabled the detection > 6000 unique host-pathogen and > 200 pathogen-pathogen interactions for each phage, encompassing > 50% of the phage proteome. Interactome-wide comparison across phages showed similar perturbed protein interactions suggesting fundamentally conserved mechanisms of phage predation within the KZ-like phage family. Prediction of novel ORFs revealed a ϕ PA3 complex showing strong structural and sequence similarity to ϕ KZ nvRNAp, suggesting ϕ PA3 also possesses two RNA polymerases acting at different stages of the infection cycle. We further expanded our understanding on the molecular organization of the virion packaged and injected proteome by identifying 23 novel virion components and 5 novel injected proteins, as well as providing the first evidence for interactions between KZ-like phage proteins and the host ribosome. To enable accessibility to this data, we developed PhageMAP, an online resource for network query, visualization, and interaction prediction ( https://phagemap.ucsf.edu/ ). We anticipate this study will lay the foundation for the application of co-fractionation mass spectrometry for the scalable profiling of hostpathogen interactomes and protein complex dynamics upon infection.

Proteomic analysis of antiviral innate immunity

The capacity of host cells to detect and restrict an infecting virus rests on an array of cell-autonomous antiviral effectors and innate immune receptors that can trigger inflammatory processes at tissue and organismal levels. Dynamic changes in protein abundance, subcellular localisation, post-translational modifications and interactions with other biomolecules govern these processes. Proteomics is therefore an ideal experimental tool to discover novel mechanisms of host antiviral immunity. Additional information can be gleaned both about host and virus by systematic analysis of viral immune evasion strategies. In this review, we summarise recent advances in proteomic technologies and their application to antiviral innate immunity.

How viral proteins bind short linear motifs and intrinsically disordered domains

Viruses are the obligate intracellular parasites that exploit the host cellular machinery to replicate their genome. During the viral life cycle viruses manipulate the host cell through interactions with host proteins. Many of these protein-protein interactions are mediated through the recognition of host globular domains by short linear motifs (SLiMs), or longer intrinsically disordered domains (IDD), in the disordered regions of viral proteins. However, viruses also employ their own globular domains for binding to SLiMs and IDDs present in host proteins or virus proteins. In this review, we focus on the different strategies adopted by viruses to utilize proteins or protein domains for binding to the disordered regions of human or/and viral ligands. With a set of examples, we describe viral domains that bind human SLiMs. We also provide examples of viral proteins that bind to SLiMs, or IDDs, of viral proteins as a part of complex assembly and regulation of protein functions. The protein-protein interactions are often crucial for viral replication, and may thus offer possibilities for innovative inhibitor design.

Marburg Virus VP30 Is Required for Transcription Initiation at the Glycoprotein Gene

Marburg virus (MARV) is an enveloped, negative-sense RNA virus from the filovirus family that causes outbreaks of severe, frequently fatal illness in humans. Of the seven MARV proteins, the VP30 protein stands out because it is essential for viral growth but lacks a definitive function. Here, we used model MARV genome RNAs for one or two reporter genes and the MARV VP40, glycoprotein (GP), and VP24 genes to demonstrate that VP30 is dispensable for the transcription of some genes but critical for transcription reinitiation at the GP gene. This results in the loss of the expression of GP and downstream genes and the impaired production of infectious particles when VP30 is absent. Bicistronic minigenome assays demonstrate that the VP40 gene end/GP gene start junction specifically confers VP30 dependence. A region at the GP gene start site predicted to form a stem-loop contributes to VP30 dependence because the replacement of the GP stem-loop with corresponding sequences from the MARV VP35 gene relieves VP30 dependence. Finally, a Cys3-His zinc binding motif characteristic of filovirus VP30 proteins was demonstrated to be critical for reinitiation at GP. These findings address a long-standing gap in our understanding of MARV biology by defining a critical role for VP30 in MARV transcription. IMPORTANCE Marburg virus and Ebola virus encode VP30 proteins. While the role of VP30 in Ebola virus transcription has been well studied, the role of VP30 in the Marburg virus life cycle is not well understood. The work here demonstrates that different gene start sites within the Marburg viral genome have variable levels of dependence on Marburg virus VP30, with its expression being critical for transcription reinitiation at the GP gene start site. These findings address a long-standing question regarding Marburg virus VP30 function and further our understanding of how Marburg virus gene expression is regulated.

Evidence for Viral mRNA Export from Ebola Virus Inclusion Bodies by the Nuclear RNA Export Factor NXF1

Many negative-sense RNA viruses, including the highly pathogenic Ebola virus (EBOV), use cytoplasmic inclusion bodies (IBs) for viral RNA synthesis. However, it remains unclear how viral mRNAs are exported from these IBs for subsequent translation. We recently demonstrated that the nuclear RNA export factor 1 (NXF1) is involved in a late step in viral protein expression, i.e., downstream of viral mRNA transcription, and proposed it to be involved in this mRNA export process. We now provide further evidence for this function by showing that NXF1 is not required for translation of viral mRNAs, thus pinpointing its function to a step between mRNA transcription and translation. We further show that RNA binding of both NXF1 and EBOV NP is necessary for export of NXF1 from IBs, supporting a model in which NP hands viral mRNA over to NXF1 for export. Mapping of NP-NXF1 interactions allowed refinement of this model, revealing two separate interaction sites, one of them directly involving the RNA binding cleft of NP, even though these interactions are RNA-independent. Immunofluorescence analyses demonstrated that individual NXF1 domains are sufficient for its recruitment into IBs, and complementation assays helped to define NXF1 domains important for its function in the EBOV life cycle. Finally, we show that NXF1 is also required for protein expression of other viruses that replicate in cytoplasmic IBs, including Lloviu and Junín virus. These data suggest a role for NXF1 in viral mRNA export from IBs for various viruses, making it a potential target for broadly active antivirals. IMPORTANCE Filoviruses such as the Ebola virus (EBOV) cause severe hemorrhagic fevers with high case fatality rates and limited treatment options. The identification of virus-host cell interactions shared among several viruses would represent promising targets for the development of broadly active antivirals. In this study, we reveal the mechanistic details of how EBOV usurps the nuclear RNA export factor 1 (NXF1) to export viral mRNAs from viral inclusion bodies (IBs). We further show that NXF1 is not only required for the EBOV life cycle but also necessary for other viruses known to replicate in cytoplasmic IBs, including the filovirus Lloviu virus and the highly pathogenic arenavirus Junín virus. This suggests NXF1 as a promising target for the development of broadly active antivirals.

Accurate Prediction for Protein-Peptide Binding Based on High-Temperature Molecular Dynamics Simulations

The structural characterization of protein-peptide interactions is fundamental to elucidating biological processes and designing peptide drugs. Molecular dynamics (MD) simulations are extensively used to study biomolecular systems. However, simulating the protein-peptide binding process is usually quite expensive. Based on our previous studies, herein, we propose a simple and effective method to predict the binding site and pose of the peptide simultaneously using high-temperature (high-T) MD simulations with the RSFF2C force field. Thousands of binding events (nonspecific or specific) can be sampled during microseconds of high-T MD. From density-based clustering analysis, the structures of all of the 12 complexes (nine with linear peptides and three with cyclic peptides) can be successfully predicted with root-mean-square deviation (RMSD) < 2.5 Å. By directly simulating the process of the ligand binding onto the receptor, our method approaches experimental precision for the first time, significantly surpassing previous protein-peptide docking methods in terms of accuracy.

Vimentin inhibits α-tubulin acetylation via enhancing α-TAT1 degradation to suppress the replication of human parainfluenza virus type 3

We previously found that, among human parainfluenza virus type 3 (HPIV3) proteins, the interaction of nucleoprotein (N) and phosphoprotein (P) provides the minimal requirement for the formation of cytoplasmic inclusion bodies (IBs), which are sites of RNA synthesis, and that acetylated α-tubulin enhances IB fusion and viral replication. In this study, using immunoprecipitation and mass spectrometry assays, we determined that vimentin (VIM) specifically interacted with the N-P complex of HPIV3, and that the head domain of VIM was responsible for this interaction, contributing to the inhibition of IB fusion and viral replication. Furthermore, we found that VIM promoted the degradation of α-tubulin acetyltransferase 1 (α-TAT1), through its head region, thereby inhibiting the acetylation of α-tubulin, IB fusion, and viral replication. In addition, we identified a 20-amino-acid peptide derived from the head region of VIM that participated in the interaction with the N-P complex and inhibited viral replication. Our findings suggest that VIM inhibits the formation of HPIV3 IBs by downregulating α-tubulin acetylation via enhancing the degradation of α-TAT1. Our work sheds light on a new mechanism by which VIM suppresses HPIV3 replication.

CAPG Is Required for Ebola Virus Infection by Controlling Virus Egress from Infected Cells

The replication of Ebola virus (EBOV) is dependent upon actin functionality, especially at cell entry through macropinocytosis and at release of virus from cells. Previously, major actin-regulatory factors involved in actin nucleation, such as Rac1 and Arp2/3, were shown important in both steps. However, downstream of nucleation, many other cell factors are needed to control actin dynamics. How these regulate EBOV infection remains largely unclear. Here, we identified the actin-regulating protein, CAPG, as important for EBOV replication. Notably, knockdown of CAPG specifically inhibited viral infectivity and yield of infectious particles. Cell-based mechanistic analysis revealed a requirement of CAPG for virus production from infected cells. Proximity ligation and split-green fluorescent protein reconstitution assays revealed strong association of CAPG with VP40 that was mediated through the S1 domain of CAPG. Overall, CAPG is a novel host factor regulating EBOV infection through connecting actin filament stabilization to viral egress from cells.

Molecular, ecological, and behavioral drivers of the bat-virus relationship

Bats perform important ecological roles in our ecosystem. However, recent studies have demonstrated that bats are reservoirs of emerging viruses that have spilled over into humans and agricultural animals to cause severe diseases. These viruses include Hendra and Nipah paramyxoviruses, Ebola and Marburg filoviruses, and coronaviruses that are closely related to severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and the recently emerged SARS-CoV-2. Intriguingly, bats that are naturally or experimentally infected with these viruses do not show clinical signs of disease. Here we have reviewed ecological, behavioral, and molecular factors that may influence the ability of bats to harbor viruses. We have summarized known zoonotic potential of bat-borne viruses and stress on the need for further studies to better understand the evolutionary relationship between bats and their viruses, along with discovering the intrinsic and external factors that facilitate the successful spillover of viruses from bats.

Structural insights into the interactions between lloviu virus VP30 and nucleoprotein

The family Filoviridae comprises many notorious viruses, such as Ebola virus (EBOV) and Marburg virus (MARV), that can infect humans and nonhuman primates. Lloviu virus (LLOV), a less well studied filovirus, is considered a potential pathogen for humans. The VP30 C-terminal domain (CTD) of these filoviruses exhibits nucleoprotein (NP) binding and plays an essential role in viral transcription, replication and assembly. In this study, we confirmed the interactions between LLOV VP30 CTD and its NP fragment, and also determined the crystal structure of the chimeric dimeric LLOV NP-VP30 CTD at 2.50 Å resolution. The structure is highly conserved across the family Filoviridae. While in the dimer structure, only one VP30 CTD binds the NP fragment, which indicates that the interaction between LLOV VP30 CTD and NP is not strong. Our work provides a preliminary model to investigate the interactions between LLOV VP30 and NP and suggests a potential target for anti-filovirus drug development.

Dabie bandavirus Nonstructural Protein Interacts with Actin to Induce F-Actin Rearrangement and Inhibit Viral Adsorption and Entry

Dabie bandavirus (DBV) is an emerging Bandavirus that causes multiorgan failure with a high fatality rate in humans. While many viruses can manipulate the actin cytoskeleton to facilitate viral growth, the regulation pattern of the actin cytoskeleton and the molecular mechanisms involved in DBV entry into the host cells remain unclear. In this study, we demonstrate that expression of nonstructural protein (NSs) or infection with DBV induces actin rearrangement, which presents a point-like distribution, and this destruction is dependent on inclusion bodies (IBs). Further experiments showed that NSs inhibits viral adsorption by destroying the filopodium structure. In addition, NSs also compromised the viral entry by inhibiting clathrin aggregation on the cell surface and capturing clathrin into IBs. Furthermore, NSs induced clathrin light chain B (CLTB) degradation through the K48-linked ubiquitin proteasome pathway, which could negatively regulate clathrin-mediated endocytosis, inhibiting the viral entry. Finally, we confirmed that this NSs-induced antiviral mechanism is broadly applicable to other viruses, such as enterovirus 71 (EV71) and influenza virus, A/PR8/34 (PR8), which use the same clathrin-mediated endocytosis to enter host cells. In conclusion, our study provides new insights into the role of NSs in inhibiting endocytosis and a novel strategy for treating DBV infections. IMPORTANCEDabie bandavirus (DBV), a member of the Phenuiviridae family, is a newly emerging tick-borne pathogen that causes multifunctional organ failure and even death in humans. The actin cytoskeleton is involved in various crucial cellular processes and plays an important role in viral life activities. However, the relationship between DBV infection and the actin cytoskeleton has not been described in detail. Here, we show for the first time the interaction between NSs and actin to induce actin rearrangement, which inhibits the viral adsorption and entry. We also identify a key mechanism underlying NSs-induced entry inhibition in which NSs prevents clathrin aggregation on the cell surface by hijacking clathrin into the inclusion body and induces CLTB degradation through the K48-linked ubiquitination modification. This paper is the first to reveal the antiviral mechanism of NSs and provides a theoretical basis for the search for new antiviral targets.

Inhibition of Venezuelan Equine Encephalitis Virus Using Small Interfering RNAs

Acutely infectious new world alphaviruses such as Venezuelan Equine Encephalitis Virus (VEEV) pose important challenges to the human population due to a lack of effective therapeutic intervention strategies. Small interfering RNAs that can selectively target the viral genome (vsiRNAs) has been observed to offer survival advantages in several in vitro and in vivo models of acute virus infections, including alphaviruses such as Chikungunya virus and filoviruses such as Ebola virus. In this study, novel vsiRNAs that targeted conserved regions in the nonstructural and structural genes of the VEEV genome were designed and evaluated for antiviral activity in mammalian cells in the context of VEEV infection. The data demonstrate that vsiRNAs were able to effectively decrease the infectious virus titer at earlier time points post infection in the context of the attenuated TC-83 strain and the virulent Trinidad Donkey strain, while the inhibition was overcome at later time points. Depletion of Argonaute 2 protein (Ago2), the catalytic component of the RISC complex, negated the inhibitory effect of the vsiRNAs, underscoring the involvement of the siRNA pathway in the inhibition process. Depletion of the RNAi pathway proteins Dicer, MOV10, TRBP2 and Matrin 3 decreased viral load in infected cells, alluding to an impact of the RNAi pathway in the establishment of a productive infection. Additional studies focused on rational combinations of effective vsiRNAs and delivery strategies to confer better in vivo bioavailability and distribution to key target tissues such as the brain can provide effective solutions to treat encephalitic diseases resulting from alphavirus infections.

Ebola Virus Encodes Two microRNAs in Huh7-Infected Cells

MicroRNAs (miRNAs) are important gene regulatory molecules involved in a broad range of cellular activities. Although the existence and functions of miRNAs are clearly defined and well established in eukaryotes, this is not always the case for those of viral origin. Indeed, the existence of viral miRNAs is the subject of intense controversy, especially those of RNA viruses. Here, we characterized the miRNA transcriptome of cultured human liver cells infected or not with either of the two Ebola virus (EBOV) variants: Mayinga or Makona; or with Reston virus (RESTV). Bioinformatic analyses revealed the presence of two EBOV-encoded miRNAs, miR-MAY-251 and miR-MAK-403, originating from the EBOV Mayinga and Makona variants, respectively. From the miRDB database, miR-MAY-251 and miR-MAK-403 displayed on average more than 700 potential human host target candidates, 25% of which had a confidence score higher than 80%. By RT-qPCR and dual luciferase assays, we assessed the potential regulatory effect of these two EBOV miRNAs on selected host mRNA targets. Further analysis of Panther pathways unveiled that these two EBOV miRNAs, in addition to general regulatory functions, can potentially target genes involved in the hemorrhagic phenotype, regulation of viral replication and modulation of host immune defense.

Seq-BEL: Sequence-Based Ensemble Learning for Predicting Virus-Human Protein-Protein Interaction

Infectious diseases are currently the most important and widespread health problem, and identifying viral infection mechanisms is critical for controlling diseases caused by highly infectious viruses. Because of the lack of non-interactive protein pairs and serious imbalance between positive and negative sample ratios, the supervised learning algorithm is not suitable for prediction. At the same time, due to the lack of information on viral proteins and significant dissimilarity in sequence, some ensemble learning models have poor generalization ability. In this paper, we propose a Sequence-Based Ensemble Learning (Seq-BEL) method to predict the potential virus-human PPIs. Specifically, based on the amino acid sequence of proteins and the currently known virus-human PPI network, Seq-BEL calculates various features and similarities of human proteins and viral proteins, and then combines these similarities and features to score the potential of virus-human PPIs. The computational results show that Seq-BEL achieves success in predicting potential virus-human PPIs and outperforms other state-of-the-art methods. More importantly, Seq-BEL also has good predictive performance for new human proteins and new viral proteins. In addition, the model has the advantages of strong robustness and good generalization ability, and can be used as an effective tool for virus-human PPI prediction.

Ebola virus VP35 hijacks the PKA-CREB1 pathway for replication and pathogenesis by AKIP1 association

Ebola virus (EBOV), one of the deadliest viruses, is the cause of fatal Ebola virus disease (EVD). The underlying mechanism of viral replication and EBOV-related hemorrhage is not fully understood. Here, we show that EBOV VP35, a cofactor of viral RNA-dependent RNA polymerase, binds human A kinase interacting protein (AKIP1), which consequently activates protein kinase A (PKA) and the PKA-downstream transcription factor CREB1. During EBOV infection, CREB1 is recruited into EBOV ribonucleoprotein complexes in viral inclusion bodies (VIBs) and employed for viral replication. AKIP1 depletion or PKA-CREB1 inhibition dramatically impairs EBOV replication. Meanwhile, the transcription of several coagulation-related genes, including THBD and SERPINB2, is substantially upregulated by VP35-dependent CREB1 activation, which may contribute to EBOV-related hemorrhage. The finding that EBOV VP35 hijacks the host PKA-CREB1 signal axis for viral replication and pathogenesis provides novel potential therapeutic approaches against EVD.

Ebola virus virion protein 35 (VP35) is a cofactor of the viral RNA-dependent RNA polymerase, required for viral assembly and IFN antagonist. Here, Zhu et al. provide evidence that EBOV VP35 induces an AKIP1-mediated (human A kinase interacting protein) activation of the PKA-CREB1 signaling pathway and contributes to viral replication and pathogenesis in vitro and in vivo.

The Intricacy of the Viral-Human Protein Interaction Networks: Resources, Data, and Analyses

Viral infections are one of the major causes of human diseases that cause yearly millions of deaths and seriously threaten global health, as we have experienced with the COVID-19 pandemic. Numerous approaches have been adopted to understand viral diseases and develop pharmacological treatments. Among them, the study of virus-host protein-protein interactions is a powerful strategy to comprehend the molecular mechanisms employed by the virus to infect the host cells and to interact with their components. Experimental protein-protein interactions described in the scientific literature have been systematically captured into several molecular interaction databases. These data are organized in structured formats and can be easily downloaded by users to perform further bioinformatic and network studies. Network analysis of available virus-host interactomes allow us to understand how the host interactome is perturbed upon viral infection and what are the key host proteins targeted by the virus and the main cellular pathways that are subverted. In this review, we give an overview of publicly available viral-human protein-protein interactions resources and the community standards, curation rules and adopted ontologies. A description of the main virus-human interactome available is provided, together with the main network analyses that have been performed. We finally discuss the main limitations and future challenges to assess the quality and reliability of protein-protein interaction datasets and resources.