Chemical Evolution of Rhinovirus Identifies Capsid-Destabilizing Mutations Driving Low-pH-Independent Genome Uncoating.

Rhinoviruses (RVs) cause recurrent infections of the nasal and pulmonary tracts, life-threatening conditions in chronic respiratory illness patients, predisposition of children to asthmatic exacerbation, and large economic cost. RVs are difficult to treat. They rapidly evolve resistance and are genetically diverse. Here, we provide insight into RV drug resistance mechanisms against chemical compounds neutralizing low pH in endolysosomes. Serial passaging of RV-A16 in the presence of the vacuolar proton ATPase inhibitor bafilomycin A1 (BafA1) or the endolysosomotropic agent ammonium chloride (NH4Cl) promoted the emergence of resistant virus populations. We found two reproducible point mutations in viral proteins 1 and 3 (VP1 and VP3), A2526G (serine 66 to asparagine [S66N]), and G2274U (cysteine 220 to phenylalanine [C220F]), respectively. Both mutations conferred cross-resistance to BafA1, NH4Cl, and the protonophore niclosamide, as identified by massive parallel sequencing and reverse genetics, but not the double mutation, which we could not rescue. Both VP1-S66 and VP3-C220 locate at the interprotomeric face, and their mutations increase the sensitivity of virions to low pH, elevated temperature, and soluble intercellular adhesion molecule 1 receptor. These results indicate that the ability of RV to uncoat at low endosomal pH confers virion resistance to extracellular stress. The data endorse endosomal acidification inhibitors as a viable strategy against RVs, especially if inhibitors are directly applied to the airways. IMPORTANCE Rhinoviruses (RVs) are the predominant agents causing the common cold. Anti-RV drugs and vaccines are not available, largely due to rapid evolutionary adaptation of RVs giving rise to resistant mutants and an immense diversity of antigens in more than 160 different RV types. In this study, we obtained insight into the cell biology of RVs by harnessing the ability of RVs to evolve resistance against host-targeting small chemical compounds neutralizing endosomal pH, an important cue for uncoating of normal RVs. We show that RVs grown in cells treated with inhibitors of endolysosomal acidification evolved capsid mutations yielding reduced virion stability against elevated temperature, low pH, and incubation with recombinant soluble receptor fragments. This fitness cost makes it unlikely that RV mutants adapted to neutral pH become prevalent in nature. The data support the concept of host-directed drug development against respiratory viruses in general, notably at low risk of gain-of-function mutations.

Preexisting cell state rather than stochastic noise confers high or low infection susceptibility of human lung epithelial cells to adenovirus.

Viruses display large variability across all stages of their life cycle, including entry, gene expression, replication, assembly, and egress. We previously reported that the immediate early adenovirus (AdV) E1A transcripts accumulate in human lung epithelial A549 cancer cells with high variability, mostly independent of the number of incoming viral genomes, but somewhat correlated to the cell cycle state at the time of inoculation. Here, we leveraged the classical Luria-Delbrück fluctuation analysis to address whether infection variability primarily arises from the cell state or stochastic noise. The E1A expression was measured by the expression of green fluorescent protein (GFP) from the endogenous E1A promoter in AdV-C5_E1A-FS2A-GFP and found to be highly correlated with the viral plaque formation, indicating reliability of the reporter virus. As an ensemble, randomly picked clonal A549 cell isolates displayed significantly higher coefficients of variation in the E1A expression than technical noise, indicating a phenotypic variability larger than noise. The underlying cell state determining infection variability was maintained for at least 9 weeks of cell cultivation. Our results indicate that preexisting cell states tune adenovirus infection in favor of the cell or the virus. These findings have implications for antiviral strategies and gene therapy applications.IMPORTANCEViral infections are known for their variability. Underlying mechanisms are still incompletely understood but have been associated with particular cell states, for example, the eukaryotic cell division cycle in DNA virus infections. A cell state is the collective of biochemical, morphological, and contextual features owing to particular conditions or at random. It affects how intrinsic or extrinsic cues trigger a response, such as cell division or anti-viral state. Here, we provide evidence that cell states with a built-in memory confer high or low susceptibility of clonal human epithelial cells to adenovirus infection. Results are reminiscent of the Luria-Delbrück fluctuation test with bacteriophage infections back in 1943, which demonstrated that mutations, in the absence of selective pressure prior to infection, cause infection resistance rather than being a consequence of infection. Our findings of dynamic cell states conferring adenovirus infection susceptibility uncover new challenges for the prediction and treatment of viral infections.

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.

Machine learning for cross-scale microscopy of viruses.

Despite advances in virological sciences and antiviral research, viruses continue to emerge, circulate, and threaten public health. We still lack a comprehensive understanding of how cells and individuals remain susceptible to infectious agents. This deficiency is in part due to the complexity of viruses, including the cell states controlling virus-host interactions. Microscopy samples distinct cellular infection stages in a multi-parametric, time-resolved manner at molecular resolution and is increasingly enhanced by machine learning and deep learning. Here we discuss how state-of-the-art artificial intelligence (AI) augments light and electron microscopy and advances virological research of cells. We describe current procedures for image denoising, object segmentation, tracking, classification, and super-resolution and showcase examples of how AI has improved the acquisition and analyses of microscopy data. The power of AI-enhanced microscopy will continue to help unravel virus infection mechanisms, develop antiviral agents, and improve viral vectors.

Label-free microscopy for virus infections.

Microscopy has been essential to elucidate micro- and nano-scale processes in space and time and has provided insights into cell and organismic functions. It is widely employed in cell biology, microbiology, physiology, clinical sciences and virology. While label-dependent microscopy, such as fluorescence microscopy, provides molecular specificity, it has remained difficult to multiplex in live samples. In contrast, label-free microscopy reports on overall features of the specimen at minimal perturbation. Here, we discuss modalities of label-free imaging at the molecular, cellular and tissue levels, including transmitted light microscopy, quantitative phase imaging, cryogenic electron microscopy or tomography and atomic force microscopy. We highlight how label-free microscopy is used to probe the structural organization and mechanical properties of viruses, including virus particles and infected cells across a wide range of spatial scales. We discuss the working principles of imaging procedures and analyses and showcase how they open new avenues in virology. Finally, we discuss orthogonal approaches that enhance and complement label-free microscopy techniques.

Asymmetric cell division safeguards memory CD8 T cell development.

The strength of T cell receptor (TCR) stimulation and asymmetric distribution of fate determinants are both implied to affect T cell differentiation. Here, we uncover asymmetric cell division (ACD) as a safeguard mechanism for memory CD8 T cell generation specifically upon strong TCR stimulation. Using live imaging approaches, we find that strong TCR stimulation induces elevated ACD rates, and subsequent single-cell-derived colonies comprise both effector and memory precursor cells. The abundance of memory precursor cells emerging from a single activated T cell positively correlates with first mitosis ACD. Accordingly, preventing ACD by inhibition of protein kinase Cζ (PKCζ) during the first mitosis upon strong TCR stimulation markedly curtails the formation of memory precursor cells. Conversely, no effect of ACD on fate commitment is observed upon weak TCR stimulation. Our data provide relevant mechanistic insights into the role of ACD for CD8 T cell fate regulation upon different activation conditions.

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 ß-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.

Methylene blue, Mycophenolic acid, Posaconazole, and Niclosamide inhibit SARS-CoV-2 Omicron variant BA.1 infection of human airway epithelial organoids.

Sublineages of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) Omicron variants continue to amass mutations in the spike (S) glycoprotein, which leads to immune evasion and rapid spread of the virus across the human population. Here we demonstrate the susceptibility of the Omicron variant BA.1 (B.1.1.529.1) to four repurposable drugs, Methylene blue (MB), Mycophenolic acid (MPA), Posaconazole (POS), and Niclosamide (Niclo) in post-exposure treatments of primary human airway cell cultures. MB, MPA, POS, and Niclo are known to block infection of human nasal and bronchial airway epithelial explant cultures (HAEEC) with the Wuhan strain, and four variants of concern (VoC), Alpha (B.1.1.7), Beta (B.1.351), Gamma (B.1.1.28), Delta (B.1.617.2) (Weiss et al., 2021, Murer et al., 2022). Our results here not only reinforce the broad anti-coronavirus effects of MB, MPA, POS and Niclo, but also demonstrate that the Omicron variant BA.1 (B.1.1.529.1) sheds infectious virus from HAEEC over at least 15 d, and maintains both intracellular and extracellular viral genomic RNA without overt toxicity, suggesting viral persistence. The data emphasize the potential of repurposable drugs against COVID-19.

High-content, arrayed compound screens with rhinovirus, influenza A virus and herpes simplex virus infections.

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.

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.

GT198 (PSMC3IP) germline variants in early-onset breast cancer patients from hereditary breast and ovarian cancer families.

GT198, located 470 kb downstream of BRCA1, encodes for the nuclear PSMC3-interacting protein, which functions as co-activator of steroid hormone-mediated gene expression, and is involved in RAD51 and DMC1-mediated homologous recombination during DNA repair of double-strand breaks. Recently, germline variants in GT198 have been identified in hereditary breast and ovarian cancer (HBOC) patients, mainly in cases with early-onset. We screened a cohort of 166 BRCA1/2 mutation-negative HBOC patients, of which 56 developed early-onset breast cancer before the age of 36 years, for GT198 variants. We identified 7 novel or rare GT198 variants in 8 out of 166 index patients: c.-115G>A (rs191843707); c.-70T>A (rs752276800); c.-37A>T (rs199620968); c.-24C>G (rs200359709); c.519G>A p.(Trp173*); c.537+51G>C (rs375509656); c.*24G>A. Three out of 7 identified variants (c.-115G>A, c.519G>A and c.*24G>A) with putative pathogenic impact were found in HBOC patients with breast cancer onset at ≤ 36 years. The nonsense mutation c.519G>A p.(Trp173*) was located within the DNA binding domain of GT198 and is predicted to induce nonsense-mediated mRNA decay. Functional analyses of c.-115G>A, and c.*24A>G indicated an influence of these variants on gene expression. This is the second study that gives evidence for an association between pathogenic GT198 germline variants and early-onset breast cancer in HBOC.