Biology subjects

Sahin, U.

Publications and source records attributed to Sahin, U..

9 recordsLinked to original sources

bioRxiv2022

Exposure to BA.4/BA.5 Spike glycoprotein drives pan-Omicron neutralization in vaccine-experienced humans and mice

The SARS-CoV-2 Omicron variant and its sublineages show pronounced viral escape from neutralizing antibodies elicited by vaccination or prior SARS-CoV-2 variant infection owing to over 30 amino acid alterations within the spike (S) glycoprotein. We and others have recently reported that breakthrough infection of vaccinated individuals with Omicron sublineages BA.1 and BA.2 are associated with distinct patterns of cross-neutralizing activity against SARS-CoV-2 variants of concern (VOCs). BA.2 breakthrough infection mediated overall stronger cross-neutralization of BA.2 and its descendants (BA.2.12.1, BA.4, and BA.5) compared to BA.1 breakthrough infection. Here we characterized the effect of Omicron BA.4/BA.5 S glycoprotein exposure on the magnitude and breadth of the neutralizing antibody response upon breakthrough infection in vaccinated individuals and in mice upon booster vaccination. We show that immune sera from triple mRNA-vaccinated individuals with subsequent Omicron BA.4/BA.5 breakthrough infection display broad and robust neutralizing activity against Omicron BA.1, BA.2, BA.2.12.1, and BA.4/BA.5. Administration of a prototypic BA.4/BA.5-adapted mRNA booster vaccine to mice following SARS-CoV-2 wild-type strain-based primary immunization is associated with similarly broad neutralizing activity. Immunization of naive mice with a bivalent mRNA vaccine (wild-type + Omicron BA.4/BA.5) induces strong and broad neutralizing activity against Omicron VOCs and previous variants. These findings suggest that when administered as boosters, mono- and bivalent Omicron BA.4/BA.5-adapted vaccines may enhance neutralization breadth, and in a bivalent format may also have the potential to confer protection to individuals with no pre-existing immunity against SARS-CoV-2.

immunology↗

bioRxiv2022

Omicron BA.2 breakthrough infection enhances cross-neutralization of BA.2.12.1 and BA.4/BA.5

Recently, we reported that BNT162b2-vaccinated individuals after Omicron BA.1 breakthrough infection have strong serum neutralizing activity against Omicron BA.1, BA.2, and previous SARS-CoV-2 variants of concern (VOCs), yet less against the highly contagious Omicron sublineages BA.4 and BA.5 that have displaced previous variants. As the latter sublineages are derived from Omicron BA.2, we characterized serum neutralizing activity of COVID-19 mRNA vaccine triple-immunized individuals who experienced BA.2 breakthrough infection. We demonstrate that sera of these individuals have broadly neutralizing activity against previous VOCs as well as all tested Omicron sublineages, including BA.2 derived variants BA.2.12.1, BA.4/BA.5. Furthermore, applying antibody depletion we showed that neutralization of BA.2 and BA.4/BA.5 sublineages by BA.2 convalescent sera is driven to a significant extent by antibodies targeting the N-terminal domain (NTD) of the spike glycoprotein, whereas their neutralization by Omicron BA.1 convalescent sera depends exclusively on antibodies targeting the receptor binding domain (RBD). These findings suggest that exposure to Omicron BA.2, in contrast to BA.1 spike glycoprotein, triggers significant NTD specific recall responses in vaccinated individuals and thereby enhances the neutralization of BA.4/BA.5 sublineages. Given the current epidemiology with a predominance of BA.2 derived sublineages like BA.4/BA.5 and rapidly ongoing evolution, these findings are of high relevance for the development of Omicron adapted vaccines.

immunology↗

bioRxiv2022

Neutralization of Omicron sublineages and Deltacron SARS-CoV-2 by 3 doses of BNT162b2 vaccine or BA.1 infection

Distinct SARS-CoV-2 Omicron sublineages have evolved showing increased fitness and immune evasion than the original Omicron variant BA.1. Here we report the neutralization activity of sera from BNT162b2 vaccinated individuals or unimmunized Omicron BA.1-infected individuals against Omicron sublineages and "Deltacron" variant (XD). BNT162b2 post-dose 3 immune sera neutralized USA-WA1/2020, Omicron BA.1-, BA.2-, BA.2.12.1-, BA.3-, BA.4/5-, and XD-spike SARS-CoV-2s with geometric mean titers (GMTs) of 1335, 393, 298, 315, 216, 103, and 301, respectively; thus, BA.4/5 SARS-CoV-2 spike variant showed the highest propensity to evade vaccine neutralization compared to the original Omicron variants BA.1. BA.1-convalescent sera neutralized USA-WA1/2020, BA.1-, BA.2-, BA.2.12.1-, BA.3-, BA.4/5-, and Deltacron-spike SARS-CoV-2s with GMTs of 15, 430, 110, 109, 102, 25, and 284, respectively. The low neutralization titers of vaccinated sera or convalescent sera from BA. 1 infected individuals against the emerging and rapidly spreading Omicron BA.4/5 variants provide important results for consideration in the selection of an updated vaccine in the current Omicron wave.

microbiology↗

bioRxiv2022

Multiple instance learning to predict immune checkpoint blockade efficacy using neoantigen candidates

A successful response to immune checkpoint blockade treatment (ICB) depends on the functional re-invigoration of neoantigen-specific T cells and their anti-tumoral activity. Previous studies showed that the patients neoantigen candidate load is an imperfect predictor of the response to ICB. Further studies provided evidence that the overall response to ICB is also affected by the qualitative properties of a few or even single candidates, limiting the predictive power based on candidate quantity alone. To our knowledge, this is the first study to predict the response to ICB therapy based on qualitative neoantigen candidate profiles in the context of the mutation type, using a multiple instance learning approach. Multiple instance learning is a special branch of machine learning which classifies labelled bags that are formed by a set of unlabeled instances. The multiple instance learning approach performed systematically better than random guessing and was independent of the neoantigen candidate load. Qualitative modeling performed better in comparison to the quantitative approach, in particular for modelling low-abundant fusion genes. Our findings suggest that multiple instance learning is an appropriate method to predict immunotherapy efficacy based on qualitative neoantigen candidate profiles without relying on direct T-cell response information and provide a foundation for future developments in the field.

bioinformatics↗

bioRxiv2022

Omicron breakthrough infection drives cross-variant neutralization and memory B cell formation

Omicron is the evolutionarily most distinct SARS-CoV-2 variant (VOC) to date and displays multiple amino acid alterations located in neutralizing antibody sites of the spike (S) protein. We report here that Omicron breakthrough infection in BNT162b2 vaccinated individuals results in strong neutralizing activity not only against Omicron, but also broadly against previous SARS-CoV-2 VOCs and against SARS-CoV-1. We found that Omicron breakthrough infection mediates a robust B cell recall response, and primarily expands preformed memory B cells that recognize epitopes shared broadly by different variants, rather than inducing new B cells against strictly Omicron-specific epitopes. Our data suggest that, despite imprinting of the immune response by previous vaccination, the preformed B cell memory pool has sufficient plasticity for being refocused and quantitatively remodeled by exposure to heterologous S protein, thus allowing effective neutralization of variants that evade a previously established neutralizing antibody response. One Sentence SummaryBreakthrough infection in individuals double- and triple-vaccinated with BNT162b2 drives cross-variant neutralization and memory B cell formation.

immunology↗

bioRxiv2021

Early Computational Detection of Potential High Risk SARS-CoV-2 Variants

The ongoing COVID-19 pandemic is leading to the discovery of hundreds of novel SARS-CoV-2 variants on a daily basis. While most variants do not impact the course of the pandemic, some variants pose a significantly increased risk when the acquired mutations allow better evasion of antibody neutralisation in previously infected or vaccinated subjects or increased transmissibility. Early detection of such high risk variants (HRVs) is paramount for the proper management of the pandemic. However, experimental assays to determine immune evasion and transmissibility characteristics of new variants are resource-intensive and time-consuming, potentially leading to delays in appropriate responses by decision makers. Here we present a novel in silico approach combining spike (S) protein structure modelling and large protein transformer language models on S protein sequences to accurately rank SARS-CoV-2 variants for immune escape and fitness potential. These metrics can be combined into an automated Early Warning System (EWS) capable of evaluating new variants in minutes and risk-monitoring variant lineages in near real-time. The system accurately pinpoints the putatively dangerous variants by selecting on average less than 0.3% of the novel variants each week. With only the S protein nucleotide sequence as input, the EWS detects HRVs earlier and with better precision than baseline metrics such as the growth metric (which requires real-world observations) or random sampling. Notably, Omicron BA.1 was flagged by the EWS on the day its sequence was made available. Additionally, our immune escape and fitness metrics were experimentally validated using in vitro pseudovirus-based virus neutralisation test (pVNT) assays and binding assays. The EWS flagged as potentially dangerous all 16 variants (Alpha-Omicron BA.1/2/4/5) designated by the World Health Organisation (WHO) with an average lead time of more than one and a half months ahead of them being designated as such. One-Sentence SummaryA COVID-19 Early Warning System combining structural modelling with machine learning to detect and monitor high risk SARS-CoV-2 variants, identifying all 16 WHO designated variants on average more than one and a half months in advance by selecting on average less than 0.3% of the weekly novel variants.

bioinformatics↗

bioRxiv2021

BNT162b2-Elicited Neutralization of Delta Plus, Lambda, and Other Variants

BNT162b2-elicited human sera are known to neutralize the currently dominant Delta SARS-CoV-2 variant. Here, we report the ability of 20 human sera, drawn 2 or 4 weeks after two doses of BNT162b2, to neutralize USA-WA1/2020 SARS-CoV-2 bearing variant spikes from Delta plus (Delta-AY.1, Delta-AY.2), Delta-{Delta}144 (Delta with the Y144 deletion of the Alpha variant), Lambda, and B. 1.1.519 lineage viruses. Geometric mean plaque reduction neutralization titers against Delta-AY.1, Delta-AY.2, and Delta-{Delta}144 viruses are slightly lower than against USA-WA1/2020, but all sera neutralize the variant viruses to titers of [≥]80. Neutralization titers against Lambda and B. 1.1.519 variants and against USA-WA1/2020 are equivalent. The susceptibility of Delta plus, Lambda, and other variants to neutralization by the sera indicates that antigenic change has not led to virus escape from vaccine-elicited neutralizing antibodies and supports ongoing mass immunization with BNT162b2 to control the variants and to minimize the emergence of new variants.

microbiology↗

bioRxiv2021

Large-scale analysis of SARS-CoV-2 spike-glycoprotein mutants demonstrates the need for continuous screening of virus isolates

Due to the widespread of the COVID-19 pandemic, the SARS-CoV-2 genome is evolving in diverse human populations. Several studies already reported different strains and an increase in the mutation rate. Particularly, mutations in SARS-CoV-2 spike-glycoprotein are of great interest as it mediates infection in human and recently approved mRNA vaccines are designed to induce immune responses against it. We analyzed 146,917 SARS-CoV-2 genome assemblies and 2,393 NGS datasets from GISAID, NCBI Virus and NCBI SRA archives focusing on non-synonymous mutations in the spike protein. Only around 13.8% of the samples contained the wild-type spike protein with no variation from the reference. Among the spike protein mutants, we confirmed a low mutation rate exhibiting less than 10 non-synonymous mutations in 99.98% of the analyzed sequences, but the mean and median number of spike protein mutations per sample increased over time. 2,592 distinct variants were found in total. The majority of the observed variants were recurrent, but only nine and 23 recurrent variants were found in at least 0.5% of the mutant genome assemblies and NGS samples, respectively. Further, we found high-confidence subclonal variants in about 15.1% of the NGS data sets with mutant spike protein, which might indicate co-infection with various SARS-CoV-2 strains and/or intra-host evolution. Lastly, some variants might have an effect on antibody binding or T-cell recognition. These findings demonstrate the increasing importance of monitoring SARS-CoV-2 sequences for an early detection of variants that require adaptations in preventive and therapeutic strategies.

genomics↗

bioRxiv2021

Neutralization of SARS-CoV-2 lineage B.1.1.7 pseudovirus by BNT162b2 vaccine-elicited human sera

Recently, a new SARS-CoV-2 lineage called B.1.1.7 has emerged in the United Kingdom that was reported to spread more efficiently than other strains. This variant has an unusually large number of mutations with 10 amino acid changes in the spike protein, raising concerns that its recognition by neutralizing antibodies may be affected. Here, we investigated SARS-CoV-2-S pseudoviruses bearing either the Wuhan reference strain or the B.1.1.7 lineage spike protein with sera of 16 participants in a previously reported trial with the mRNA-based COVID-19 vaccine BNT162b2. The immune sera had equivalent neutralizing titers to both variants. These data, together with the combined immunity involving humoral and cellular effectors induced by this vaccine, make it unlikely that the B.1.1.7 lineage will escape BNT162b2-mediated protection.

immunology↗