Single-epitope T cell-based vaccine protects against SARS-CoV-2 infection in a preclinical animal model.

Currently authorized COVID-19 vaccines induce humoral and cellular responses to epitopes in the SARS-CoV-2 spike protein, though the relative roles of antibodies and T cells in protection are not well understood. To understand the role of vaccine-elicited T cell responses in protection, we established a T cell-only vaccine using a DC-targeted lentiviral vector expressing single CD8+ T cell epitopes of the viral nucleocapsid, spike, and ORF1. Immunization of angiotensin-converting enzyme 2-transgenic mice with ex vivo lentiviral vector-transduced DCs or by direct injection of the vector induced the proliferation of functional antigen-specific CD8+ T cells, resulting in a 3-log decrease in virus load upon live virus challenge that was effective against the ancestral virus and Omicron variants. The Pfizer/BNT162b2 vaccine was also protective in mice, but the antibodies elicited did not cross-react on the Omicron variants, suggesting that the protection was mediated by T cells. The studies suggest that the T cell response plays an important role in vaccine protection. The findings suggest that the incorporation of additional T cell epitopes into current vaccines would increase their effectiveness and broaden protection.

A rapid nucleic acid detection platform based on phosphorothioate-DNA and sulfur binding domain.

Nucleic acid detection plays a key role in diverse diagnosis and disease control. Currently available nucleic acid detection techniques are challenged by trade-offs among speed, simplicity, precision and cost. Here, we described a novel method, designated SENSOR (Sulfur DNA mediated nucleic acid sensing platform), for rapid nucleic acid detection. SENSOR was developed from phosphorothioate (PT)-DNA and sulfur binding domain (SBD) which specifically binds double-stranded PT-modified DNA. SENSOR utilizes PT-DNA oligo and SBD as targeting module, which is linked with split luciferase reporter to generate luminescence signal within 10 min. We tested detection on synthesized nucleic acid and COVID-19 pseudovirus, achieving attomolar sensitivity combined with an amplification procedure. Single nucleotide polymorphisms (SNP) could also be discriminated. Indicating SENSOR a new promising nucleic acid detection technique.

Anti-PEG Antibodies Boosted in Humans by SARS-CoV-2 Lipid Nanoparticle mRNA Vaccine.

Humans commonly have low level antibodies to poly(ethylene) glycol (PEG) due to environmental exposure. Lipid nanoparticle (LNP) mRNA vaccines for SARS-CoV-2 contain small amounts of PEG, but it is not known whether PEG antibodies are enhanced by vaccination and what their impact is on particle-immune cell interactions in human blood. We studied plasma from 130 adults receiving either the BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) mRNA vaccines or no SARS-CoV-2 vaccine for PEG-specific antibodies. Anti-PEG IgG was commonly detected prior to vaccination and was significantly boosted a mean of 13.1-fold (range 1.0-70.9) following mRNA-1273 vaccination and a mean of 1.78-fold (range 0.68-16.6) following BNT162b2 vaccination. Anti-PEG IgM increased 68.5-fold (range 0.9-377.1) and 2.64-fold (0.76-12.84) following mRNA-1273 and BNT162b2 vaccination, respectively. The rise in PEG-specific antibodies following mRNA-1273 vaccination was associated with a significant increase in the association of clinically relevant PEGylated LNPs with blood phagocytes ex vivo. PEG antibodies did not impact the SARS-CoV-2 specific neutralizing antibody response to vaccination. However, the elevated levels of vaccine-induced anti-PEG antibodies correlated with increased systemic reactogenicity following two doses of vaccination. We conclude that PEG-specific antibodies can be boosted by LNP mRNA vaccination and that the rise in PEG-specific antibodies is associated with systemic reactogenicity and an increase of PEG particle-leukocyte association in human blood. The longer-term clinical impact of the increase in PEG-specific antibodies induced by lipid nanoparticle mRNA vaccines should be monitored. It may be useful to identify suitable alternatives to PEG for developing next-generation LNP vaccines to overcome PEG immunogenicity in the future.

Time-dependent viral interference between influenza virus and coronavirus in the infection of differentiated porcine airway epithelial cells.

Coronaviruses and influenza viruses are circulating in humans and animals all over the world. Co-infection with these two viruses may aggravate clinical signs. However, the molecular mechanisms of co-infections by these two viruses are incompletely understood. In this study, we applied air-liquid interface (ALI) cultures of well-differentiated porcine tracheal epithelial cells (PTECs) to analyze the co-infection by a swine influenza virus (SIV, H3N2 subtype) and porcine respiratory coronavirus (PRCoV) at different time intervals. Our results revealed that in short-term intervals, prior infection by influenza virus caused complete inhibition of coronavirus infection, while in long-term intervals, some coronavirus replication was detectable. The influenza virus infection resulted in (i) an upregulation of porcine aminopeptidase N, the cellular receptor for PRCoV and (ii) in the induction of an innate immune response which was responsible for the inhibition of PRCoV replication. By contrast, prior infection by coronavirus only caused a slight inhibition of influenza virus replication. Taken together, the timing and the order of virus infection are important determinants in co-infections. This study is the first to show the impact of SIV and PRCoV co- and super-infection on the cellular level. Our results have implications also for human viruses, including potential co-infections by SARS-CoV-2 and seasonal influenza viruses.

Person-Specific Biomolecular Coronas Modulate Nanoparticle Interactions with Immune Cells in Human Blood.

When nanoparticles interact with human blood, a multitude of plasma components adsorb onto the surface of the nanoparticles, forming a biomolecular corona. Corona composition is known to be influenced by the chemical composition of nanoparticles. In contrast, the possible effects of variations in the human blood proteome between healthy individuals on the formation of the corona and its subsequent interactions with immune cells in blood are unknown. Herein, we prepared and examined a matrix of 11 particles (including organic and inorganic particles of three sizes and five surface chemistries) and plasma samples from 23 healthy donors to form donor-specific biomolecular coronas (personalized coronas) and investigated the impact of the personalized coronas on particle interactions with immune cells in human blood. Among the particles examined, poly(ethylene glycol) (PEG)-coated mesoporous silica (MS) particles, irrespective of particle size (800, 450, or 100 nm in diameter), displayed the widest range (up to 60-fold difference) of donor-dependent variance in immune cell association. In contrast, PEG particles (after MS core removal) of 860, 518, or 133 nm in diameter displayed consistent stealth behavior (negligible cell association), irrespective of plasma donor. For comparison, clinically relevant PEGylated doxorubicin-encapsulated liposomes (Doxil) (74 nm in diameter) showed significant variance in association with monocytes and B cells across all plasma donors studied. An in-depth proteomic analysis of each biomolecular corona studied was performed, and the results were compared against the nanoparticle-blood cell association results, with individual variance in the proteome driving differential association with specific immune cell types. We identified key immunoglobulin and complement proteins that explicitly enriched or depleted within the corona and which strongly correlated with the cell association pattern observed across the 23 donors. This study demonstrates how plasma variance in healthy individuals significantly influences the blood immune cell interactions of nanoparticles.

The Cell Tropism of Porcine Respiratory Coronavirus for Airway Epithelial Cells Is Determined by the Expression of Porcine Aminopeptidase N.

Porcine respiratory coronavirus (PRCoV) infects the epithelial cells in the respiratory tract of pigs, causing a mild respiratory disease. We applied air-liquid interface (ALI) cultures of well-differentiated porcine airway cells to mimic the respiratory tract epithelium in vitro and use it for analyzing the infection by PRCoV. As reported for most coronaviruses, virus entry and virus release occurred mainly via the apical membrane domain. A novel finding was that PRCoV preferentially targets non-ciliated and among them the non-mucus-producing cells. Aminopeptidase N (APN), the cellular receptor for PRCoV was also more abundantly expressed on this type of cell suggesting that APN is a determinant of the cell tropism. Interestingly, differentiation-dependent differences were found both in the expression of pAPN and the susceptibility to PRCoV infection. Cells in an early differentiation stage express higher levels of pAPN and are more susceptible to infection by PRCoV than are well-differentiated cells. A difference in the susceptibility to infection was also detected when tracheal and bronchial cells were compared. The increased susceptibility to infection of bronchial epithelial cells was, however, not due to an increased abundance of APN on the cell surface. Our data reveal a complex pattern of infection in porcine differentiated airway epithelial cells that could not be elucidated with immortalized cell lines. The results are expected to have relevance also for the analysis of other respiratory viruses.

A discussion on some simple epidemiological models.

The present text discusses some basic considerations on the dynamics of the coronavirus pandemic, in particular in France. The goal is not to make accurate predictions, which is probably impossible, but to illustrate some general qualitative behaviors which may be observed. The conclusions of the text only correspond to consequences of the models discussed here, where the parameters are roughly estimated as a function of the evolution of the number of deaths due to COVID-19. They are of course not definitive and are subject to possibly important modifications, due to new information or applications of less simplistic models.