ABSTRACT
The continuous emergence of highly immune evasive SARS-CoV-2 variants, like XBB.1.5 and XBB.1.16, highlights the need to update COVID-19 vaccine compositions. However, immune imprinting induced by wildtype (WT)-based vaccination would compromise the antibody response to Omicron-based boosters. Vaccination strategies that can counter immune imprinting are critically needed. In this study, we investigated the degree and dynamics of immune imprinting in mouse models and human cohorts, especially focusing on the role of repeated Omicron stimulation. Our results show that in mice, the efficacy of single Omicron-boosting is heavily limited by immune imprinting, especially when using variants antigenically distinct from WT, like XBB, while the concerning situation could be largely mitigated by a second Omicron booster. Similarly, in humans, we found that repeated Omicron infections could also alleviate WT-vaccination-induced immune imprinting and generate high neutralizing titers against XBB.1.5 and XBB.1.16 in both plasma and nasal mucosa. By isolating 781 RBD-targeting mAbs from repeated Omicron infection cohorts, we revealed that double Omicron exposure alleviates immune imprinting by generating a large proportion of highly matured and potent Omicron-specific antibodies. Importantly, epitope characterization using deep mutational scanning (DMS) showed that these Omicron-specific antibodies target distinct RBD epitopes compared to WT-induced antibodies, and the bias towards non-neutralizing epitopes observed in single Omicron exposures due to imprinting was largely restored after repeated Omicron stimulation, together leading to a substantial neutralizing epitope shift. Based on the DMS profiles, we identified evolution hotspots of XBB.1.5 RBD and demonstrated the combinations of these mutations could further boost XBB.1.5’s immune-evasion capability while maintaining high ACE2 binding affinity. Our findings suggest the WT component should be abandoned when updating COVID-19 vaccine antigen compositions to XBB lineages, and those who haven't been exposed to Omicron yet should receive two updated vaccine boosters.
Subject(s)
COVID-19 , Severe Acute Respiratory SyndromeABSTRACT
The emergence of highly immune-escape Omicron variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), such as BQ and XBB, has led to concerns about the efficacy of vaccines. Using lentivirus-based pseudovirus neutralizing assay, we showed that heterologous vaccination involving parental mRNA vaccine as a booster or second booster in individuals that received two or three doses of inactivated vaccines strongly augments the neutralizing activity against emerging Omicron subvariants, including BF.7, BQ.1.1, and XBB.1, by 4.3- to 219-folds. Therefore, a heterologous boosting strategy with mRNA-based vaccines should be considered in populations where inactivated vaccines were primarily used.
Subject(s)
Coronavirus InfectionsABSTRACT
BACKGROUND This study has assessed a new Anti-COVID-19 Monoclonal Antibody Nasal Spray (SA58) for post-exposure prophylaxis (PEP) against symptomatic coronavirus disease 2019 (COVID-19). METHODS We conducted an efficacy study in adults aged 18 years and older within three days of exposure to a SARS-CoV-2 infected individual. Recruited participants were randomized in a ratio of 3:1 to receive SA58 or placebo. Primary endpoints were laboratory-confirmed symptomatic COVID-19 within study period. FINDINGS A total of 1,222 participants were randomized and dosed (SA58, n=901; placebo, n=321). Median of follow-up was 2.25 days and 2.79 days for SA58 and placebo, respectively. Adverse events occurred in 221 of 901 (25%) and 72 of 321 (22%) participants with SA58 and placebo, respectively, with no significant difference (P=0.49). All adverse events were mild in severity. Laboratory-confirmed symptomatic COVID-19 developed in 7 of 824 participants (0.22 per 100 person-days) in the SA58 group vs 14 of 299 (1.17 per 100 person-days) in the placebo group, resulting in an estimated efficacy of 80.82% (95%CI 52.41%-92.27%). There were 32 SARS-CoV-2 RT-PCR positives (1.04 per 100 person-days) in the SA58 group vs 32 (2.80 per 100 person-days) in the placebo group, resulting in an estimated efficacy of 61.83% (95%CI 37.50%-76.69%). A total of 21 RT-PCR positive samples were sequenced. 21 lineages of SARS-CoV-2 variants were identified, and all were the Omicron variant BF.7. INTERPRETATION SA58 Nasal Spray showed favorable efficacy and safety in preventing SARS-CoV-2 infection or symptomatic COVID-19 in healthy adult workers who had exposure to SARS-CoV-2 within 72 hours.
Subject(s)
COVID-19 , Severe Acute Respiratory SyndromeABSTRACT
Recent emergence of SARS-CoV-2 Omicron sublineages BA.2.12.1, BA.2.13, BA.4 and BA.5 all contain L452 mutations and show potential higher transmissibility over BA.2. The new variants’ receptor binding and immune evasion capability require immediate investigation, especially on the role of L452 substitutions. Herein, coupled with structural comparisons, we showed that BA.2 sublineages, including BA.2.12.1 and BA.2.13, exhibit increased ACE2-binding affinities compared to BA.1; while BA.4/BA.5 shows the weakest receptor-binding activity due to F486V and R493Q reversion. Importantly, compared to BA.2, BA.2.12.1 and BA.4/BA.5 exhibit stronger neutralization escape from the plasma of 3-dose vaccinees and, most strikingly, from vaccinated BA.1 convalescents. To delineate the underlying evasion mechanism, we determined the escaping mutation profiles, epitope distribution and Omicron sub-lineage neutralization efficacy of 1640 RBD-directed neutralizing antibodies (NAbs), including 614 isolated from BA.1 convalescents. Interestingly, post-vaccination BA.1 infection mainly recalls wildtype-induced humoral memory and elicits antibodies that neutralize both wild-type and BA.1. These cross-reactive NAbs are significantly enriched on non-ACE2-competing epitopes; and surprisingly, the majority are undermined by R346 and L452 substitutions, namely R346K (BA.1.1), L452M (BA.2.13), L452Q (BA.2.12.1) and L452R (BA.4/BA.5), suggesting that R346K and L452 mutations appeared under the immune pressure of Omicron convalescents. Nevertheless, BA.1 infection can also induce new clones of BA.1-specific antibodies that potently neutralize BA.1 but do not respond to wild-type SARS-CoV-2, due to the high susceptibility to N501, N440, K417 and E484. However, these NAbs are largely escaped by BA.2 sublineages and BA.4/BA.5 due to D405N and F486V, exhibiting poor neutralization breadths. As for therapeutic NAbs, LY-CoV1404 (Bamlanivimab) and COV2-2130 (Cilgavimab) can still effectively neutralize BA.2.12.1 and BA.4/BA.5, while the S371F, D405N and R408S mutations carried by BA.2/BA.4/BA.5 sublineages would undermine most broad sarbecovirus NAbs. Together, our results indicate that Omicron can evolve mutations to specifically evade humoral immunity elicited by BA.1 infection. The continuous evolution of Omicron poses great challenges to SARS-CoV-2 herd immunity and suggests that BA.1-derived vaccine boosters may not be ideal for achieving broad-spectrum protection.
ABSTRACT
The SARS-CoV-2 B.1.1.529 variant (Omicron) contains 15 mutations on the receptor-binding domain (RBD). How Omicron would evade RBD neutralizing antibodies (NAbs) and humoral immunity requires immediate investigation. Here, we used high-throughput yeast display screening1,2 to determine the RBD escaping mutation profiles for 247 human anti-RBD NAbs identified from SARS-CoV/SARS-CoV-2 convalescents and vaccinees. Based on the results, NAbs could be unsupervised clustered into six epitope groups (A-F), which is highly concordant with knowledge-based structural classifications3-5. Strikingly, various single mutations of Omicron could impair NAbs of different epitope groups. Specifically, NAbs in Group A-D, whose epitope overlaps with ACE2-binding motif, are largely escaped by K417N, N440K, G446S, E484A, Q493K, and G496S. Group E (S309 site)6 and F (CR3022 site)7 NAbs, which often exhibit broad sarbecovirus neutralizing activity, are less affected by Omicron, but still, a subset of NAbs are escaped by G339D, S371L, and S375F. Furthermore, B.1.1.529 pseudovirus neutralization and RBD binding assay showed that single mutation tolerating NAbs could also be escaped due to multiple synergetic mutations on their epitopes. In total, over 85% of the tested NAbs are escaped by Omicron. Regarding NAb drugs, LY-CoV016/LY-CoV555 cocktail, REGN-CoV2 cocktail, AZD1061/AZD8895 cocktail, and BRII-196 were escaped by Omicron, while VIR7831 and DXP-604 still function at reduced efficacy. Together, data suggest Omicron could cause significant humoral immune evasion, while NAbs targeting the sarbecovirus conserved region remain most effective. Our results offer instructions for developing NAb drugs and vaccines against Omicron and future variants.
ABSTRACT
Artificial intelligence can potentially provide a substantial role in streamlining chest computed tomography (CT) diagnosis of COVID-19 patients. However, several critical hurdles have impeded the development of robust AI model, which include deficiency, isolation, and heterogeneity of CT data generated from diverse institutions. These bring about lack of generalization of AI model and therefore prevent it from applications in clinical practices. To overcome this, we proposed a federated learning-based Unified CT-COVID AI Diagnostic Initiative (UCADI, http://www.ai-ct-covid.team/), a decentralized architecture where the AI model is distributed to and executed at each host institution with the data sources or client ends for training and inferencing without sharing individual patient data. Specifically, we firstly developed an initial AI CT model based on data collected from three Tongji hospitals in Wuhan. After model evaluation, we found that the initial model can identify COVID from Tongji CT test data at near radiologist-level (97.5% sensitivity) but performed worse when it was tested on COVID cases from Wuhan Union Hospital (72% sensitivity), indicating a lack of model generalization. Next, we used the publicly available UCADI framework to build a federated model which integrated COVID CT cases from the Tongji hospitals and Wuhan Union hospital (WU) without transferring the WU data. The federated model not only performed similarly on Tongji test data but improved the detection sensitivity (98%) on WU test cases. The UCADI framework will allow participants worldwide to use and contribute to the model, to deliver a real-world, globally built and validated clinic CT-COVID AI tool. This effort directly supports the United Nations Sustainable Development Goals' number 3, Good Health and Well-Being, and allows sharing and transferring of knowledge to fight this devastating disease around the world.