ABSTRACT
Understanding the T-cell responses involved in inhibiting COVID-19 severity is crucial for developing new therapeutic and vaccine strategies. Here, we characterized SARS-CoV-2 spike-specific CD8+ T cells interacting with overlapping peptides on peripheral blood mononuclear cells from acute-phase COVID-19 patients. Relative to severe COVID-19, patients with mild COVID-19 had more frequent antigen-specific CD8+ T cells, and significantly increased SARS-CoV-2 spike-specific CD8+ T cells simultaneously expressing granzyme A, granzyme B, and perforin, suggesting that inducing highly cytotoxic CD8+ T cells during early infection suppresses COVID-19 severity. The BNT162b2 mRNA vaccine induced these antigen-specific CD8+ T cells in healthy donors, although lesser than in infected patients, and the induced subpopulation was not maintained long-term after second vaccination. Importantly, these CD8+ T cells showed cross-reactivity with the Delta and Omicron strains of SARS-CoV-2. Incorporating factors that efficiently induce CD8+ T cells with polyfunctional cytotoxic activity may improve future vaccine efficacy against such variants.
Subject(s)
COVID-19ABSTRACT
High-throughput, high-accuracy detection of emerging viruses allows for pandemic prevention and control. Currently, reverse transcription-polymerase chain reaction (RT-PCR) is used to diagnose the presence of SARS-CoV-2. The principle of the test is to detect RNA in the virus using a pair of primers that specifically binds to the base sequence of the viral RNA. However, RT-PCR is a sophisticated technique requiring a time-consuming pretreatment procedure for extracting viral RNA from clinical specimens and to obtain high sensitivity. Here, we report a method for detecting novel coronaviruses with high sensitivity using artificial intelligent nanopores utilizing a simple procedure that does not require RNA extraction. Artificial intelligent nanopore platform consists of machine learning software on the servers, portable high-speed and high-precision current measuring instrument, and scalable, cost-effective semiconducting nanopore modules. Here we show that the artificial intelligent nanopores are successful in accurate identification of four types of coronaviruses, HCoV-229E, SARS-CoV, MERS-CoV, and SARS-CoV-2, which are usually extremely difficult to detect. The positive/negative diagnostics of the new coronavirus is achieved with a sensitivity of 95 % and specificity of 92 % with a 5-minute diagnosis. The platform enables high throughput diagnostics with low false negatives for the novel coronavirus.
Subject(s)
Severe Acute Respiratory SyndromeABSTRACT
Coronavirus disease 2019 (COVID-19) is a disease that causes fatal disorders including severe pneumonia. To develop a therapeutic drug for COVID-19, a model that can reproduce the viral life cycle and evaluate the drug efficacy of anti-viral drugs is essential. In this study, we established a method to generate human bronchial organoids (hBO) from commercially available cryopreserved human bronchial epithelial cells and examined whether they could be used as a model for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) research. Our hBO contain basal, club, ciliated, and goblet cells. Angiotensin-converting enzyme 2 (ACE2), which is a receptor for SARS-CoV-2, and transmembrane serine proteinase 2 (TMPRSS2), which is an essential serine protease for priming spike (S) protein of SARS-CoV-2, were highly expressed. After SARS-CoV-2 infection, not only the intracellular viral genome, but also progeny virus, cytotoxicity, pyknotic cells, and moderate increases of the type I interferon signal could be observed. Treatment with camostat, an inhibitor of TMPRSS2, reduced the viral copy number to 2% of the control group. Furthermore, the gene expression profile in SARS-CoV-2-infected hBO was obtained by performing RNA-seq analysis. In conclusion, we succeeded in generating hBO that can be used for SARS-CoV-2 research and COVID-19 drug discovery. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/115600v2_ufig1.gif" ALT="Figure 1"> View larger version (99K): org.highwire.dtl.DTLVardef@13a6908org.highwire.dtl.DTLVardef@1c59300org.highwire.dtl.DTLVardef@362167org.highwire.dtl.DTLVardef@1cb31ed_HPS_FORMAT_FIGEXP M_FIG C_FIG