Rationale: Coronavirus disease 2019 (COVID-19) is characterized by increased incidence of microthrombosis with hyperactive platelets sporadically containing viral RNA. It is unclear if SARS-CoV-2 (severe acute respiratory syndrome, corona virus-2) directly alters platelet activation or if these changes are a reaction to infection-mediated global inflammatory alterations. Importantly, the direct effect of SARS-CoV-2 on platelets has yet to be studied. Objective: To characterize the direct SARS-CoV-2–platelet interactions using in vitro studies with purified infectious virions and samples from infected patients. Methods and Results: Platelet RNA analyzed by ARTIC v3 sequencing for SARS-CoV-2 showed presence of fragmented viral genome in all patients with COVID-19. Immunofluorescent imaging of platelets from patients with COVID-19 confirmed presence of SARS-CoV-2 proteins, whereas there was no detection of viral RNA by real-time quantitative polymerase chain reaction. Transmission electron microscopy of platelets incubated with purified SARS-CoV-2 virions demonstrated rapid internalization and digestion leading to distinct morphological changes and resulted in a release of extracellular vesicles. Interactions between SARS-CoV-2 and platelets occurred with or without ACE (angiotensin-converting enzyme) 2 presence as measured by immunofluorescence. Transmission electron microscopy showed that SARS-CoV-2 virions became internalized when they were attached to microparticles, bypassing the need for ACE2. Enrichment analysis of platelet transcriptome from patients with acute COVID-19, compared with those with clinical thrombosis, suggested upregulation of pathways related to virally mediated cell death, specifically necroptosis and apoptosis. Platelets incubated with infectious virus appeared to undergo cell death in 30 minutes postincubation as assessed by transmission electron microscopy and platelets from patients with COVID-19 showed evidence of increased markers of apoptosis and necroptosis by Western blot. Immunofluorescence confirmed colocalization of SARS-CoV-2 with phospho-MLKL (mixed lineage kinase domain-like pseudokinase) and caspase 3 on nonpermeabilized platelets in vitro and in COVID-19 platelets. Conclusions: Platelets internalize SARS-CoV-2 virions, directly or attached to microparticles, and viral internalization leads to rapid digestion, programmed cell death, and extracellular vesicle release. During COVID-19, platelets mediate a rapid response to SARS-CoV-2 and this response can contribute to dysregulated immunity and thrombosis.

TLR7 senses RNA in endosomal compartments. TLR7 expression and signaling have been demonstrated in plasmacytoid and myeloid dendritic cells, B cells, and T cells. The regulation of TLR7 signaling can play a crucial role in shaping the immune response to RNA viruses with different cellular tropisms, and in developing adjuvants capable of promoting balanced humoral and cell-mediated immunity. We used unique characteristics of two ssRNA viruses, dengue virus and influenza virus, to delineate factors that regulate viral RNA-human TLR7 signaling beyond recognition in endosomal compartments. Our data show that TLR7 recognition of enveloped RNA virus genomes is linked to virus fusion or uncoating from the endosome. The signaling threshold required to activate TLR7-type I IFN production is greater than that required to activate TLR7-NF-κB-IL-8 production. The higher order structure of viral RNA appears to be an important determinant of TLR7-signaling potency. A greater understanding of viral RNA-TLR7 activity relationships will promote rational approaches to interventional and vaccine strategies for important human viral pathogens.

The challenge of distinguishing genetic drift from selection remains a central focus of population genetics. Time-sampled data may provide a powerful tool for distinguishing these processes, and we here propose approximate Bayesian, maximum likelihood, and analytical methods for the inference of demography and selection from time course data. Utilizing these novel statistical and computational tools, we evaluate whole-genome datasets of an influenza A H1N1 strain in the presence and absence of oseltamivir (an inhibitor of neuraminidase) collected at thirteen time points. Results reveal a striking consistency amongst the three estimation procedures developed, showing strongly increased selection pressure in the presence of drug treatment. Importantly, these approaches re-identify the known oseltamivir resistance site, successfully validating the approaches used. Enticingly, a number of previously unknown variants have also been identified as being positively selected. Results are interpreted in the light of Fisher's Geometric Model, allowing for a quantification of the increased distance to optimum exerted by the presence of drug, and theoretical predictions regarding the distribution of beneficial fitness effects of contending mutations are empirically tested. Further, given the fit to expectations of the Geometric Model, results suggest the ability to predict certain aspects of viral evolution in response to changing host environments and novel selective pressures. In recent years, considerable attention has been given to the evolution of drug resistance in the influenza A H1N1 strain. As a major annual cause of morbidity and mortality, combined with the rapid global spread of drug resistance, influenza remains as one of the most important global health concerns. Our work here focuses on a novel multi-faceted population-genetic approach utilizing unique whole-genome multi-time point experimental datasets in both the presence and absence of drug treatment. In addition, we present novel theoretical results and two newly developed and widely applicable statistical methodologies for utilizing time-sampled data – with a focus on distinguishing the relative contribution of genetic drift from that of positive and purifying selection. Results illustrate the available mutational paths to drug resistance, and offer important insights in to the mode and tempo of adaptation in a viral population.

Influenza A virus (IAV) lacks the enzyme for adding 5′ caps to its RNAs and snatches the 5′ ends of host capped RNAs to prime transcription. Neither the preference of the host RNA sequences snatched nor the effect of cap-snatching on host processes is completely defined. Previous studies of influenza cap-snatching used poly(A)-selected RNAs from infected cells or relied on annotated host genes to define the snatched host RNAs, and thus lack details on many noncoding host RNAs including snRNAs, snoRNAs, and promoter-associated capped small (cs)RNAs, which are made by “paused” Pol II during transcription initiation. In this study, we used a nonbiased technique, CapSeq, to identify host and viral-capped RNAs including nonpolyadenylated RNAs in the same samples, and investigated the substrate–product correlation between the host RNAs and the viral RNAs. We demonstrated that noncoding host RNAs, particularly U1 and U2, are the preferred cap-snatching source over mRNAs or pre-mRNAs. We also found that csRNAs are highly snatched by IAV. Because the functions of csRNAs remain mostly unknown, especially in somatic cells, our finding reveals that csRNAs at least play roles in the process of IAV infection. Our findings support a model where nascent RNAs including csRNAs are the preferred targets for cap-snatching by IAV and raise questions about how IAV might use snatching preferences to modulate host-mRNA splicing and transcription.

Influenza and other respiratory viruses present a significant threat to public health, national security, and the world economy, and can lead to the emergence of global pandemics such as from COVID-19. A barrier to the development of effective therapeutics is the absence of a robust and predictive preclinical model, with most studies relying on a combination of in vitro screening with immortalized cell lines and low-throughput animal models. Here, we integrate human primary airway epithelial cells into a custom-engineered 96-device platform (PREDICT96-ALI) in which tissues are cultured in an array of microchannel-based culture chambers at an air–liquid interface, in a configuration compatible with high resolution in-situ imaging and real-time sensing. We apply this platform to influenza A virus and coronavirus infections, evaluating viral infection kinetics and antiviral agent dosing across multiple strains and donor populations of human primary cells. Human coronaviruses HCoV-NL63 and SARS-CoV-2 enter host cells via ACE2 and utilize the protease TMPRSS2 for spike protein priming, and we confirm their expression, demonstrate infection across a range of multiplicities of infection, and evaluate the efficacy of camostat mesylate, a known inhibitor of HCoV-NL63 infection. This new capability can be used to address a major gap in the rapid assessment of therapeutic efficacy of small molecules and antiviral agents against influenza and other respiratory viruses including coronaviruses.

New variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to emerge, causing surges, breakthrough infections, and devastating losses—underscoring the importance of identifying SARS-CoV-2 antivirals. A simple, accessible human cell culture model permissive to SARS-CoV-2 variants is critical for identifying and assessing antivirals in a high-throughput manner. Although human alveolar A549 cells are a valuable model for studying respiratory virus infections, they lack two essential host factors for SARS-CoV-2 infection: angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). SARS-CoV-2 uses the ACE2 receptor for viral entry and TMPRSS2 to prime the SARS-CoV-2 spike protein, both of which are negligibly expressed in A549 cells. Here, we report the generation of a suitable human cell line for SARS-CoV-2 studies by transducing human ACE2 and TMPRSS2 into A549 cells. We show that subclones highly expressing ACE2 and TMPRSS2 (“ACE2plus” and the subclone “ACE2plusC3”) are susceptible to infection with SARS-CoV-2, including the delta and omicron variants. These subclones express more ACE2 and TMPRSS2 transcripts than existing commercial A549 cells engineered to express ACE2 and TMPRSS2. Additionally, the antiviral drugs EIDD-1931, remdesivir, nirmatrelvir, and nelfinavir strongly inhibit SARS-CoV-2 variants in our infection model. Our data show that ACE2plusC3 cells are highly permissive to SARS-CoV-2 infection and can be used to identify anti-SARS-CoV-2 drugs.