A high-content image-based drug screen of clinical compounds against cell transmission of adenovirus

Stepwise virus assembly in the cell nucleus revealed by spatiotemporal click chemistry of DNA replication

Biomolecular assemblies are fundamental to life and viral disease. The spatiotemporal coordination of viral replication and assembly is largely unknown. Here, we developed a dual-color click chemistry procedure for imaging adenovirus DNA (vDNA) replication in the cell nucleus. Late- but not early-replicated vDNA was packaged into virions. Early-replicated vDNA segregated from the viral replication compartment (VRC). Single object tracking, superresolution microscopy, fluorescence recovery after photobleaching, and correlative light-electron microscopy revealed a stepwise assembly program involving vDNA and capsid intermediates. Depending on replication and the scaffolding protein 52K, late-replicated vDNA with rapidly exchanging green fluorescent protein-tagged capsid linchpin protein V and incomplete virions emerged from the VRC periphery. These nanogel-like puncta exhibited restricted movements and were located with the capsid proteins hexon, VI, and virions in the nuclear periphery, suggestive of sites for virion formation. Our findings identify VRC dynamics and assembly intermediates, essential for stepwise productive adenovirus morphogenesis.

Breaking the Chain: Protease Inhibitors as Game Changers in Respiratory Viruses Management

Respiratory viral infections (VRTIs) rank among the leading causes of global morbidity and mortality, affecting millions of individuals each year across all age groups. These infections are caused by various pathogens, including rhinoviruses (RVs), adenoviruses (AdVs), and coronaviruses (CoVs), which are particularly prevalent during colder seasons. Although many VRTIs are self-limiting, their frequent recurrence and potential for severe health complications highlight the critical need for effective therapeutic strategies. Viral proteases are crucial for the maturation and replication of viruses, making them promising therapeutic targets. This review explores the pivotal role of viral proteases in the lifecycle of respiratory viruses and the development of protease inhibitors as a strategic response to these infections. Recent advances in antiviral therapy have highlighted the effectiveness of protease inhibitors in curtailing the spread and severity of viral diseases, especially during the ongoing COVID-19 pandemic. It also assesses the current efforts aimed at identifying and developing inhibitors targeting key proteases from major respiratory viruses, including human RVs, AdVs, and (severe acute respiratory syndrome coronavirus-2) SARS-CoV-2. Despite the recent identification of SARS-CoV-2, within the last five years, the scientific community has devoted considerable time and resources to investigate existing drugs and develop new inhibitors targeting the virus's main protease. However, research efforts in identifying inhibitors of the proteases of RVs and AdVs are limited. Therefore, herein, it is proposed to utilize this knowledge to develop new inhibitors for the proteases of other viruses affecting the respiratory tract or to develop dual inhibitors. Finally, by detailing the mechanisms of action and therapeutic potentials of these inhibitors, this review aims to demonstrate their significant role in transforming the management of respiratory viral diseases and to offer insights into future research directions.

A versatile automated pipeline for quantifying virus infectivity by label-free light microscopy and artificial intelligence

Virus infectivity is traditionally determined by endpoint titration in cell cultures, and requires complex processing steps and human annotation. Here we developed an artificial intelligence (AI)-powered automated framework for ready detection of virus-induced cytopathic effect (DVICE). DVICE uses the convolutional neural network EfficientNet-B0 and transmitted light microscopy images of infected cell cultures, including coronavirus, influenza virus, rhinovirus, herpes simplex virus, vaccinia virus, and adenovirus. DVICE robustly measures virus-induced cytopathic effects (CPE), as shown by class activation mapping. Leave-one-out cross-validation in different cell types demonstrates high accuracy for different viruses, including SARS-CoV-2 in human saliva. Strikingly, DVICE exhibits virus class specificity, as shown with adenovirus, herpesvirus, rhinovirus, vaccinia virus, and SARS-CoV-2. In sum, DVICE provides unbiased infectivity scores of infectious agents causing CPE, and can be adapted to laboratory diagnostics, drug screening, serum neutralization or clinical samples.

Identification of broad anti-coronavirus chemical agents for repurposing against SARS-CoV-2 and variants of concern

Endemic human coronaviruses (hCoVs) 229E and OC43 cause respiratory disease with recurrent infections, while severe acute respiratory syndrome (SARS)-CoV-2 spreads across the world with impact on health and societies. Here, we report an image-based multicycle infection procedure with α-coronavirus hCoV-229E-eGFP in an arrayed chemical library screen of 5440 clinical and preclinical compounds. Toxicity counter selection and challenge with the β-coronaviruses OC43 and SARS-CoV-2 in tissue culture and human airway epithelial explant cultures (HAEEC) identified four FDA-approved compounds with oral availability. Methylene blue (MB, used for the treatment of methemoglobinemia), Mycophenolic acid (MPA, used in organ transplantation) and the anti-fungal agent Posaconazole (POS) had the broadest anti-CoV spectrum. They inhibited the shedding of SARS-CoV-2 and variants-of-concern (alpha, beta, gamma, delta) from HAEEC in either pre- or post exposure regimens at clinically relevant concentrations. Co-treatment of cultured cells with MB and the FDA-approved SARS-CoV-2 RNA-polymerase inhibitor Remdesivir reduced the effective anti-viral concentrations of MB by 2-fold, and Remdesivir by 4 to 10-fold, indicated by BLISS independence synergy modelling. Neither MB, nor MPA, nor POS affected the cell delivery of SARS-CoV-2 or OC43 (+)sense RNA, but blocked subsequent viral RNA accumulation in cells. Unlike Remdesivir, MB, MPA or POS did not reduce the release of viral RNA in post exposure regimen, thus indicating infection inhibition at a post-replicating step as well. In summary, the data emphasize the power of unbiased, full cycle compound screens to identify and repurpose broadly acting drugs against coronaviruses.

Metabolic Modifications by Common Respiratory Viruses and Their Potential as New Antiviral Targets

Respiratory viruses are known to be the most frequent causative mediators of lung infections in humans, bearing significant impact on the host cell signaling machinery due to their host-dependency for efficient replication. Certain cellular functions are actively induced by respiratory viruses for their own benefit. This includes metabolic pathways such as glycolysis, fatty acid synthesis (FAS) and the tricarboxylic acid (TCA) cycle, among others, which are modified during viral infections. Here, we summarize the current knowledge of metabolic pathway modifications mediated by the acute respiratory viruses respiratory syncytial virus (RSV), rhinovirus (RV), influenza virus (IV), parainfluenza virus (PIV), coronavirus (CoV) and adenovirus (AdV), and highlight potential targets and compounds for therapeutic approaches.

Machine Learning and Artificial Intelligence for the Prediction of Host-Pathogen Interactions: A Viral Case

The research of interactions between the pathogens and their hosts is key for understanding the biology of infection. Commencing on the level of individual molecules, these interactions define the behavior of infectious agents and the outcomes they elicit. Discovery of host-pathogen interactions (HPIs) conventionally involves a stepwise laborious research process. Yet, amid the global pandemic the urge for rapid discovery acceleration through the novel computational methodologies has become ever so poignant. This review explores the challenges of HPI discovery and investigates the efforts currently undertaken to apply the latest machine learning (ML) and artificial intelligence (AI) methodologies to this field. This includes applications to molecular and genetic data, as well as image and language data. Furthermore, a number of breakthroughs, obstacles, along with prospects of AI for host-pathogen interactions (HPI), are discussed.

Microscopy deep learning predicts virus infections and reveals mechanics of lytic-infected cells

Imaging across scales reveals disease mechanisms in organisms, tissues, and cells. Yet, particular infection phenotypes, such as virus-induced cell lysis, have remained difficult to study. Here, we developed imaging modalities and deep learning procedures to identify herpesvirus and adenovirus (AdV) infected cells without virus-specific stainings. Fluorescence microscopy of vital DNA-dyes and live-cell imaging revealed learnable virus-specific nuclear patterns transferable to related viruses of the same family. Deep learning predicted two major AdV infection outcomes, non-lytic (nonspreading) and lytic (spreading) infections, up to about 20 hr prior to cell lysis. Using these predictive algorithms, lytic and non-lytic nuclei had the same levels of green fluorescent protein (GFP)-tagged virion proteins but lytic nuclei enriched the virion proteins faster, and collapsed more extensively upon laser-rupture than non-lytic nuclei, revealing impaired mechanical properties of lytic nuclei. Our algorithms may be used to infer infection phenotypes of emerging viruses, enhance single cell biology, and facilitate differential diagnosis of non-lytic and lytic infections.

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Artificial intelligence identifies HSV- and AdV-infected cells without specific probes.

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Imaging lytic-infected cells reveals nuclear envelope rupture and AdV dissemination.

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Live cell imaging and neural networks presciently pinpoint lytic-infected cells.

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Lytic-infected cell nuclei have mechanical properties distinct from non-lytic nuclei.

The right tools for the job: the central role for next generation chemical probes and chemistry-based target deconvolution methods in phenotypic drug discovery

The reconnection of the scientific community with phenotypic drug discovery has created exciting new possibilities to develop therapies for diseases with highly complex biology. It promises to revolutionise fields such as neurodegenerative disease and regenerative medicine, where the development of new drugs has consistently proved elusive. Arguably, the greatest challenge in readopting the phenotypic drug discovery approach exists in establishing a crucial chain of translatability between phenotype and benefit to patients in the clinic. This remains a key stumbling block for the field which needs to be overcome in order to fully realise the potential of phenotypic drug discovery. Excellent quality chemical probes and chemistry-based target deconvolution techniques will be a crucial part of this process. In this review, we discuss the current capabilities of chemical probes and chemistry-based target deconvolution methods and evaluate the next advances necessary in order to fully support phenotypic screening approaches in drug discovery.

Emerging antiviral therapeutics for human adenovirus infection: Recent developments and novel strategies

Human adenoviruses (HAdV) are ubiquitous human pathogens that cause a significant burden of respiratory, ocular, and gastrointestinal illnesses. Although HAdV infections are generally self-limiting, pediatric and immunocompromised individuals are at particular risk for developing severe disease. Currently, no approved antiviral therapies specific to HAdV exist. Recent outbreaks underscore the need for effective antiviral agents to treat life-threatening infections. In this review we will focus on recent developments in search of potential therapeutic agents for controlling HAdV infections, with a focus on those targeting post-entry stages of the virus replicative cycle.

The FDA-Approved Drug Nelfinavir Inhibits Lytic Cell-Free but Not Cell-Associated Nonlytic Transmission of Human Adenovirus

Adenoviruses (AdVs) are prevalent and give rise to chronic and recurrent disease. Human AdV (HAdV) species B and C, such as HAdV-C2, -C5, and -B14, cause respiratory disease and constitute a health threat for immunocompromised individuals. HAdV-Cs are well known for lysing cells owing to the E3 CR1-β-encoded adenovirus death protein (ADP). We previously reported a high-throughput image-based screening framework and identified an inhibitor of HAdV-C2 multiround infection, nelfinavir mesylate. Nelfinavir is the active ingredient of Viracept, an FDA-approved inhibitor of human immunodeficiency virus (HIV) aspartyl protease that is used to treat AIDS. It is not effective against single-round HAdV infections. Here, we show that nelfinavir inhibits lytic cell-free transmission of HAdV, indicated by the suppression of comet-shaped infection foci in cell culture. Comet-shaped foci occur upon convection-based transmission of cell-free viral particles from an infected cell to neighboring uninfected cells. HAdV lacking ADP was insensitive to nelfinavir but gave rise to comet-shaped foci, indicating that ADP enhances but is not required for cell lysis. This was supported by the notion that HAdV-B14 and -B14p1 lacking ADP were highly sensitive to nelfinavir, although HAdV-A31, -B3, -B7, -B11, -B16, -B21, -D8, -D30, and -D37 were less sensitive. Conspicuously, nelfinavir uncovered slow-growing round HAdV-C2 foci, independent of neutralizing antibodies in the medium, indicative of nonlytic cell-to-cell transmission. Our study demonstrates the repurposing potential of nelfinavir with postexposure efficacy against different HAdVs and describes an alternative nonlytic cell-to-cell transmission mode of HAdV.