| Literature DB >> 35695453 |
Katharina S Schmitz1, Daryl Geers1, Rory D de Vries1, T Francesca Bovier2,3, Anna Z Mykytyn1, Corine H Geurts van Kessel1, Bart L Haagmans1, Matteo Porotto2,3,4, Rik L de Swart1, Anne Moscona2,3,5,6.
Abstract
The ability of SARS-CoV-2 to evolve in response to selective pressures poses a challenge to vaccine and antiviral efficacy. The S1 subunit of the spike (S) protein contains the receptor-binding domain and is therefore under selective pressure to evade neutralizing antibodies elicited by vaccination or infection. In contrast, the S2 subunit of S is only transiently exposed after receptor binding, which makes it a less efficient target for antibodies. As a result, S2 has a lower mutational frequency than S1. We recently described monomeric and dimeric SARS-CoV-2 fusion-inhibitory lipopeptides that block viral infection by interfering with S2 conformational rearrangements during viral entry. Importantly, a dimeric lipopeptide was shown to block SARS-CoV-2 transmission between ferrets in vivo. Because the S2 subunit is relatively conserved in newly emerging SARS-CoV-2 variants of concern (VOCs), we hypothesize that fusion-inhibitory lipopeptides are cross-protective against infection with VOCs. Here, we directly compared the in vitro efficacies of two fusion-inhibitory lipopeptides against VOC, in comparison with a set of seven postvaccination sera (two doses) and a commercial monoclonal antibody preparation. For the beta, delta, and omicron VOCs, it has been reported that convalescent and postvaccination sera are less potent in virus neutralization assays. Both fusion-inhibitory lipopeptides were equally effective against all five VOCs compared to ancestral virus, whereas postvaccination sera and therapeutic monoclonal antibody lost potency to newer VOCs, in particular to omicron BA.1 and BA.2. The neutralizing activity of the lipopeptides is consistent, and they can be expected to neutralize future VOCs based on their mechanism of action. IMPORTANCE SARS-CoV-2, the causative agent of COVID-19, continues to spread globally, with waves resulting from new variants that evade immunity generated by vaccines and previous strains and escape available monoclonal antibody therapy. Fusion-inhibitory peptides may provide an intervention strategy that is not similarly affected by this viral evolution.Entities:
Keywords: SARS-CoV-2; Spike protein; fusion inhibitor; postvaccine sera; viral evolution
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Year: 2022 PMID: 35695453 PMCID: PMC9239157 DOI: 10.1128/mbio.01249-22
Source DB: PubMed Journal: mBio Impact factor: 7.786
FIG 1Fusion-inhibitory activity of [SARSHRC-PEG4]2-chol (A) and SARSHRC-PEG24-chol (B) peptide against emerging SARS-CoV-2 S variants. Inhibitory activity was assessed in an assay based on alpha complementation of β-galactosidase (β-Gal) where hACE2 receptor-bearing cells expressing the omega peptide of β-Gal are mixed with cells coexpressing glycoprotein S and the alpha peptide of β-Gal, and cell fusion leads to alpha-omega complementation (24). Fusion is stopped by lysing the cells, and after addition of the substrate (Tropix Galacto-Star chemiluminescent reporter assay system; Applied Biosystems), luminescence is quantified on a Tecan M1000PRO microplate reader. Fusion between cells expressing SARS-CoV-2 glycoprotein (D614G, alpha, beta, delta, or omicron) and the α subunit of β-galactosidase and human kidney epithelial 293T cells expressing hACE2 receptor and the ω subunit of β-galactosidase was assessed in the presence of different dilutions of inhibitory peptide. The resulting luminescence was quantified using a Tecan Infinite M1000PRO reader. Percent inhibition was calculated as the ratio of relative luminescence units in the presence of a specific concentration of inhibitor and the relative luminescence units in the absence of inhibitor and corrected for background luminescence. % inhibition = 100 × [1 − (luminescence at X − background)/(luminescence in the absence of inhibitor − background)]. Values are presented as mean (±standard error of the mean) from three independent experiments and are shown in the table below.
FIG 2Potency of inhibitory lipopeptides and postvaccination sera against entry of wild-type SARS-CoV-2 and VOCs (D614G, alpha, beta, delta, omicron BA.1, and omicron BA.2). In an 8-h infectious virus entry assay, the efficacy of [SARSHRC-PEG4]2-chol, SARSHRC-PEG24-chol, and control [HPIV3HRC-PEG4]2-chol peptides (top), seven postvaccination sera, a control prevaccination serum (numbered, bottom), and one commercial SARS-CoV-2 therapeutic monoclonal antibody (REGEN-COV) against ancestral SARS-CoV-2 and VOCs (alpha, beta, delta, and omicron) was determined as previously described (7, 15). Samples were run in triplicate and repeated in three independent experiments. Virus entry was assessed in Calu-3 cells grown in Opti-MEM (Gibco), supplemented with penicillin (100 IU/mL) and streptomycin (100 IU/mL) at 37°C in a humidified CO2 incubator. Heat-inactivated sera were 2-fold diluted in Opti-MEM starting at a dilution of 1:16 in 50 μL. Fusion-inhibitory peptides were diluted 10-fold in Opti-MEM starting at a concentration of 5,000 nM. 400 PFU of SARS-CoV-2 (D614G, alpha, beta, delta, omicron BA.1, and omicron BA.2) were added to each well in 50 μL and incubated at 37°C for 1 h. The virus-inhibitor mixtures were then transferred onto the human airway cell line Calu-3 and incubated for 8 h. After incubation, cells were fixed and plaques were stained with polyclonal rabbit anti-SARS-CoV-2 nucleocapsid antibody (Sino Biological) and a secondary peroxidase-labeled goat anti-rabbit IgG (Dako). Signal was developed by using a precipitate-forming 3,3′,5,5′-tetramethylbenzidine substrate (TrueBlue; Kirkegaard & Perry Laboratories), and the number of infected cells was counted per well by using an Immunospot image analyzer (CTL Europe GmbH). Infection controls were included on each plate, and we used one nonreactive fusion-inhibitory peptide (HPIV3) and one prevaccination serum as a negative control in each assay. IC50 values were determined by performing four-parameter nonlinear regression with variable slope on normalized and transformed data (GraphPad Prism 9), and potencies were defined within each class based on transformed IC50. The response range was log transformed, and strongest to weakest responses were calculated per sample type (inhibitory peptide or sera). The response range was subdivided into 10 ranks with equivalent distances, and each sample was assigned one of these ranks. Ranks were then visualized in SigmaPlot. When no neutralization was observed, we set the value as 1 dilution step lower than the lowest dilution. IC50 values for inhibitory peptides are shown in nanomolar concentrations, and IC50 values for postvaccination sera are shown as dilutions.