ABSTRACT
All respiratory viruses establish primary infections in the nasal epithelium, where efficient innate immune induction may prevent dissemination to the lower airway and thus minimize pathogenesis. Human coronaviruses (HCoVs) cause a range of pathologies, but the host and viral determinants of disease during common cold versus lethal HCoV infections are poorly understood. We model the initial site of infection using primary nasal epithelial cells cultured at air-liquid interface (ALI). HCoV-229E, HCoV-NL63 and human rhinovirus-16 are common cold-associated viruses that exhibit unique features in this model: early induction of antiviral interferon (IFN) signaling, IFN-mediated viral clearance, and preferential replication at nasal airway temperature (33C) which confers muted host IFN responses. In contrast, lethal SARS-CoV-2 and MERS-CoV encode antagonist proteins that prevent IFN-mediated clearance in nasal cultures. Our study identifies features shared among common cold-associated viruses, highlighting nasal innate immune responses as predictive of infection outcomes and nasally-directed IFNs as potential therapeutics.
Subject(s)
InfectionsABSTRACT
The nasal epithelium is the initial entry portal and primary barrier to infection by all human coronaviruses (HCoVs). We utilize primary nasal epithelial cells grown at air-liquid interface, which recapitulate the heterogeneous cellular population as well as mucociliary clearance functions of the in vivo nasal epithelium, to compare lethal (SARS-CoV-2 and MERS-CoV) and seasonal (HCoV-NL63 and HCoV-229E) HCoVs. All four HCoVs replicate productively in nasal cultures but diverge significantly in terms of cytotoxicity induced following infection, as the seasonal HCoVs as well as SARS-CoV-2 cause cellular cytotoxicity as well as epithelial barrier disruption, while MERS-CoV does not. Treatment of nasal cultures with type 2 cytokine IL-13 to mimic asthmatic airways differentially impacts HCoV replication, enhancing MERS-CoV replication but reducing that of SARS-CoV-2 and HCoV-NL63. This study highlights diversity among HCoVs during infection of the nasal epithelium, which is likely to influence downstream infection outcomes such as disease severity and transmissibility.
Subject(s)
Drug-Related Side Effects and Adverse ReactionsABSTRACT
Background Little is known about the dynamics of SARS-CoV-2 antigen burden in respiratory samples in different patient populations at different stages of infection. Current rapid antigen tests cannot quantitate and track antigen dynamics with high sensitivity and specificity in respiratory samples. Methods We developed and validated an ultra-sensitive SARS-CoV-2 antigen assay with smartphone readout using the Microbubbling Digital Assay previously developed by our group, which is a platform that enables highly sensitive detection and quantitation of protein biomarkers. A computer vision-based algorithm was developed for microbubble smartphone image recognition and quantitation. A machine learning-based classifier was developed to classify the smartphone images based on detected microbubbles. Using this assay, we tracked antigen dynamics in serial swab samples from COVID patients hospitalized in ICU and immunocompromised COVID patients. Results The limit of detection (LOD) of the Microbubbling SARS-CoV-2 Antigen Assay was 0.5 pg/mL (10.6 fM) recombinant nucleocapsid (N) antigen or 4000 copies/mL inactivated SARS-CoV-2 virus in nasopharyngeal (NP) swabs, comparable to many rRT-PCR methods. The assay had high analytical specificity towards SARS-CoV-2. Compared to EUA-approved rRT-PCR methods, the Microbubbling Antigen Assay demonstrated a positive percent agreement (PPA) of 97% (95% confidence interval (CI), 92-99%) in symptomatic individuals within 7 days of symptom onset and positive SARS-CoV-2 nucleic acid results, and a negative percent agreement (NPA) of 97% (95% CI, 94-100%) in symptomatic and asymptomatic individuals with negative nucleic acid results. Antigen positivity rate in NP swabs gradually decreased as days-after-symptom-onset increased, despite persistent nucleic acid positivity of the same samples. The computer vision and machine learning-based automatic microbubble image classifier could accurately identify positives and negatives, based on microbubble counts and sizes. Total microbubble volume, a potential marker of antigen burden, correlated inversely with Ct values and days-after-symptom-onset. Antigen was detected for longer periods of time in immunocompromised patients with hematologic malignancies, compared to immunocompetent individuals. Simultaneous detectable antigens and nucleic acids may indicate the presence of replicating viruses in patients with persistent infections. Conclusions The Microbubbling SARS-CoV-2 Antigen Assay enables sensitive and specific detection of acute infections, and quantitation and tracking of antigen dynamics in different patient populations at various stages of infection. With smartphone compatibility and automated image processing, the assay is well-positioned to be adapted for point-of-care diagnosis and to explore the clinical implications of antigen dynamics in future studies.