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Herpes Simplex Virus Type-1 (HSV-1) forms progeny in the nucleus within distinct membrane-less inclusions, the viral replication compartments (VRCs), where viral gene expression, DNA replication, and packaging occur. The way in which the VRCs maintain spatial integrity remains unresolved. Here, we demonstrate that the essential viral transcription factor ICP4 is an intrinsically disordered protein (IDP) capable of driving protein condensation and liquid–liquid phase separation (LLPS) in transfected cells. Particularly, ICP4 forms nuclear liquid-like condensates in a dose- and time-dependent manner. Fluorescence recovery after photobleaching (FRAP) assays revealed rapid exchange rates of EYFP-ICP4 between phase-separated condensates and the surroundings, akin to other viral IDPs that drive LLPS. Likewise, HSV-1 VRCs revealed by EYFP-tagged ICP4 retained their liquid-like nature, suggesting that they are phase-separated condensates. Individual VRCs homotypically fused when reaching close proximity and grew over the course of infection. Together, the results of this study demonstrate that the HSV-1 transcription factor ICP4 has characteristics of a viral IDP, forms condensates in the cell nucleus by LLPS, and can be used as a proxy for HSV-1 VRCs with characteristics of liquid–liquid phase-separated condensates.

Background RNA-binding proteins (RBPs) function as master regulators of gene expression. Alterations in RBP expression and function are often observed in cancer and influence critical pathways implicated in tumor initiation and growth. Identification and characterization of oncogenic RBPs and their regulatory networks provide new opportunities for targeted therapy. Results We identify the RNA-binding protein SERBP1 as a novel regulator of glioblastoma (GBM) development. High SERBP1 expression is prevalent in GBMs and correlates with poor patient survival and poor response to chemo- and radiotherapy. SERBP1 knockdown causes delay in tumor growth and impacts cancer-relevant phenotypes in GBM and glioma stem cell lines. RNAcompete identifies a GC-rich region as SERBP1-binding motif; subsequent genomic and functional analyses establish SERBP1 regulation role in metabolic routes preferentially used by cancer cells. An important consequence of these functions is SERBP1 impact on methionine production. SERBP1 knockdown decreases methionine levels causing a subsequent reduction in histone methylation as shown for H3K27me3 and upregulation of genes associated with neurogenesis, neuronal differentiation, and function. Further analysis demonstrates that several of these genes are downregulated in GBM, potentially through epigenetic silencing as indicated by the presence of H3K27me3 sites. Conclusions SERBP1 is the first example of an RNA-binding protein functioning as a central regulator of cancer metabolism and indirect modulator of epigenetic regulation in GBM. By bridging these two processes, SERBP1 enhances glioma stem cell phenotypes and contributes to GBM poorly differentiated state.

Cells react to their microenvironment by integrating external stimuli into phenotypic decisions via an intracellular signaling network. To analyze the interplay of environment, local neighborhood, and internal cell state effects on phenotypic variability, we developed an experimental approach that enables multiplexed mass cytometric imaging analysis of up to 240 pooled spheroid microtissues. We quantified the contributions of environment, neighborhood, and intracellular state to marker variability in single cells of the spheroids. A linear model explained on average more than half of the variability of 34 markers across four cell lines and six growth conditions. The contributions of cell‐intrinsic and environmental factors to marker variability are hierarchically interdependent, a finding that we propose has general implications for systems‐level studies of single‐cell phenotypic variability. By the overexpression of 51 signaling protein constructs in subsets of cells, we also identified proteins that have cell‐intrinsic and cell‐extrinsic effects. Our study deconvolves factors influencing cellular phenotype in a 3D tissue and provides a scalable experimental system, analytical principles, and rich multiplexed imaging datasets for future studies. SYNOPSIS A barcoding‐based, high‐throughput approach enables multiplexed imaging of 3D spheroid microtissues. Quantitative single‐cell analyses show interdependence of global environment, local neighborhood, and internal cell state in determining cellular phenotype. A novel barcoding‐based, high‐throughput approach enables multiplexed mass cytometric imaging of 3D microtissues. A linear model quantifies environment, neighborhood, and internal cell state dependencies of marker expression. A strong interdependence is identified between environmental and internal cell state predictors of cellular marker expression. Systematic overexpression of signaling proteins within cells of 3D microtissues revealed non‐cell autonomous signaling. Graphical Abstract A barcoding‐based, high‐throughput approach enables multiplexed imaging of 3D spheroid microtissues. Quantitative single‐cell analyses show interdependence of global environment, local neighborhood, and internal cell state in determining cellular phenotype.

Human adenoviruses (HAdVs) are fatal to immuno-suppressed individuals, but no effective anti-HAdV therapy is available. Here, we present a novel image-based high-throughput screening (HTS) platform, which scores the full viral replication cycle from virus entry to dissemination of progeny and second-round infections. We analysed 1,280 small molecular weight compounds of the Prestwick Chemical Library (PCL) for interference with HAdV-C2 infection in a quadruplicate, blinded format, and performed robust image analyses and hit filtering. We present the entire set of the screening data including all images, image analyses and data processing pipelines. The data are made available at the Image Data Resource (IDR, idr0081). Our screen identified Nelfinavir mesylate as an inhibitor of HAdV-C2 multi-round plaque formation, but not single round infection. Nelfinavir has been FDA-approved for anti-retroviral therapy in humans. Our results underscore the power of image-based full cycle infection assays in identifying viral inhibitors with clinical potential. Measurement(s) nucleus • number of infected nuclei • infection index (number of infected nuclei/number of nuclei) • Plaque • fluorescent reporter intensity • percent cell viability Technology Type(s) epifluorescence microscopy • compound toxicity assay Factor Type(s) compound treatment Sample Characteristic - Organism Human mastadenovirus C Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.12594470

Viruses are genetically and structurally diverse, and outnumber cells by orders of magnitude. They can cause acute and chronic infections, suppress, or exacerbate immunity, or dysregulate survival and growth of cells. To identify chemical agents with pro- or antiviral effects we conducted arrayed high-content image-based multi-cycle infection screens of 1,280 mainly FDA-approved compounds with three human viruses, rhinovirus (RV), influenza A virus (IAV), and herpes simplex virus (HSV) differing in genome organization, composition, presence of an envelope, and tropism. Based on Z’-factors assessing screening quality and Z-scores ranking individual compounds, we identified potent inhibitors and enhancers of infection: the RNA mutagen 5-Azacytidine against RV-A16; the broad-spectrum antimycotic drug Clotrimazole inhibiting IAV-WSN; the chemotherapeutic agent Raltitrexed blocking HSV-1; and Clobetasol enhancing HSV-1. Remarkably, the topical antiseptic compound Aminacrine, which is clinically used against bacterial and fungal agents, inhibited all three viruses. Our data underscore the versatility and potency of image-based, full cycle virus propagation assays in cell-based screenings for antiviral agents. Measurement(s) transmission of virus • drug toxicity Technology Type(s) fluorescence microscopy Factor Type(s) virus genotype • cell line • incubation temperature • number of cells seeded/ seeding density • inoculation time • virus input FFU • drug concentration Sample Characteristic - Organism Homo sapiens • Rhinovirus A • Influenza A virus • Human alphaherpesvirus 1 Sample Characteristic - Environment epithelium Sample Characteristic - Location Switzerland

This study introduces label-free digital holo-tomographic microscopy (DHTM) and refractive index gradient (RIG) measurements of live, virus-infected cells. We use DHTM to describe virus type-specific cytopathic effects, including cyclic volume changes of vaccinia virus infections, and cytoplasmic condensations in herpesvirus and rhinovirus infections, distinct from apoptotic cells. This work shows for the first time that DHTM is suitable to observe virus-infected cells and distinguishes virus type-specific signatures under noninvasive conditions. It provides a basis for future studies, where correlative fluorescence microscopy of cell and virus structures annotate distinct RIG values derived from DHTM. Cytopathic effects (CPEs) are a hallmark of infections. CPEs are difficult to observe due to phototoxicity from classical light microscopy. We report distinct patterns of virus infections in live cells using digital holo-tomographic microscopy (DHTM). DHTM is label-free and records the phase shift of low-energy light passing through the specimen on a transparent surface with minimal perturbation. DHTM measures the refractive index (RI) and computes the refractive index gradient (RIG), unveiling optical heterogeneity in cells. We find that vaccinia virus (VACV), herpes simplex virus (HSV), and rhinovirus (RV) infections progressively and distinctly increased RIG. VACV infection, but not HSV and RV infections, induced oscillations of cell volume, while all three viruses altered cytoplasmic membrane dynamics and induced apoptotic features akin to those caused by the chemical compound staurosporine. In sum, we introduce DHTM for quantitative label-free microscopy in infection research and uncover virus type-specific changes and CPE in living cells with minimal interference. IMPORTANCE This study introduces label-free digital holo-tomographic microscopy (DHTM) and refractive index gradient (RIG) measurements of live, virus-infected cells. We use DHTM to describe virus type-specific cytopathic effects, including cyclic volume changes of vaccinia virus infections, and cytoplasmic condensations in herpesvirus and rhinovirus infections, distinct from apoptotic cells. This work shows for the first time that DHTM is suitable to observe virus-infected cells and distinguishes virus type-specific signatures under noninvasive conditions. It provides a basis for future studies, where correlative fluorescence microscopy of cell and virus structures annotate distinct RIG values derived from DHTM.

Viruses threaten humans, livestock, and plants, and are difficult to combat. Imaging of viruses by light microscopy is key to uncover the nature of known and emerging viruses in the quest for finding new ways to treat viral disease and deepening the understanding of virus–host interactions. Here, we provide an overview of recent technology for imaging cells and viruses by light microscopy, in particular fluorescence microscopy in static and live-cell modes. The review lays out guidelines for how novel fluorescent chemical probes and proteins can be used in light microscopy to illuminate cells, and how they can be used to study virus infections. We discuss advantages and opportunities of confocal and multi-photon microscopy, selective plane illumination microscopy, and super-resolution microscopy. We emphasize the prevalent concepts in image processing and data analyses, and provide an outlook into label-free digital holographic microscopy for virus research.

Human adenoviruses (HAdVs) are fatal to immuno-suppressed people, but no effective anti-HAdV therapy is available. Here, we present a novel image-based high-throughput screening (HTS) platform, which scores the full viral replication cycle from virus entry to dissemination of progeny. We analysed 1,280 small molecular weight compounds of the Prestwick Chemical Library (PCL) for interference with HAdV-C2 infection in a quadru-plicate, blinded format, and included robust image analyses, and hit filtering. We present the entire set of the screening data including all the images, image analyses and data processing pipelines. The data are made available at the Image Data Repository (IDR), accession number idr0081. Our screen identified Nelfinavir mesylate as an inhibitor of HAdV-C2 multi-round plaque formation, but not single round infection. Nelfinavir has been FDA-approved for anti-retroviral therapy in humans. Our results underscore the power of image-based full cycle infection assays in identifying viral inhibitors with clinical potential. Competing Interest Statement The authors have declared no competing interest. Footnotes * We received the GenBank accession number MT277585 and indicate the data structure for the IDR web client. * https://idr.openmicroscopy.org/webclient/

Imaging across scales gives insight into disease mechanisms in organisms, tissues and cells. Yet, rare infection phenotypes, such as virus-induced cell lysis have remained difficult to study. Here, we developed fixed and live cell imaging modalities and a deep learning approach to identify herpesvirus and adenovirus infections in the absence of virus-specific stainings. Procedures comprises staining of infected nuclei with DNA-dyes, fluorescence microscopy, and validation by virus-specific live-cell imaging. Deep learning of multi-round infection phenotypes identified hallmarks of adenovirus-infected cell nuclei. At an accuracy of >95%, the procedure predicts two distinct infection outcomes 20 hours prior to lysis, nonlytic (nonspreading) and lytic (spreading) infections. Phenotypic prediction and live-cell imaging revealed a faster enrichment of GFP-tagged virion proteins in lytic compared to nonlytic infected nuclei, and distinct mechanics of lytic and nonlytic nuclei upon laser-induced ruptures. The results unleash the power of deep learning based prediction in unraveling rare infection phenotypes. Footnotes * https://http://viresnet.github.io/movies

Cytopathic effects (CPEs) are a hallmark of infections. CPEs can be observed by phase contrast or fluorescence light microscopy, albeit at the cost of phototoxicity. We report that digital holo-tomographic microscopy (DHTM) reveals distinct patterns of virus infections in live cells with minimal perturbation. DHTM is label-free, and records the phase shift of low energy light passing through the specimen on a transparent surface. DHTM infers a 3-dimensional (3D) tomogram based on the refractive index (RI). By measuring RI and computing the refractive index gradient (RIG) values DHTM unveils on optical heterogeneity in cells upon virus infection. We find that vaccinia virus (VACV), herpes simplex virus (HSV) and rhinovirus (RV) infections progressively and distinctly increased RIG. VACV, but not HSV and RV infection induced oscillations of cell volume, while all three viruses altered cytoplasmic membrane dynamics, and induced apoptotic features akin to the chemical compound staurosporin, but with virus-specific signatures. In sum, we introduce DHTM for quantitative label-free microscopy in infection research, and uncover virus-type specific changes and CPE in living cells at minimal interference. Footnotes * Here we refine terminology of our imaging modality from digital holographic microscopy to digital holo-tomographic microscopy. This better describes the main instrument we have used in this study. Further changes concern Acknowledgement section of the manuscript. No figures or supplementary files were updated.