ABSTRACT
Pronounced immune escape by the SARS-CoV-2 Omicron variant has resulted in large numbers of individuals with hybrid immunity, generated through a combination of vaccination and infection. Based primarily on circulating neutralizing antibody (NAb) data, concerns have been raised that omicron breakthrough infections in triple-vaccinated individuals result in poor induction of omicron-specific immunity, and that a history of prior SARS-CoV-2 in particular is associated with profound immune dampening. Taking a broader and comprehensive approach, we characterized mucosal and blood immunity to both spike and non-spike antigens following BA.1/BA.2 infections in triple mRNA-vaccinated individuals, with and without a history of previous SARS-CoV-2 infection. We find that the majority of individuals increase BA.1/BA.2/BA.5-specific NAb following infection, but confirm that the magnitude of increase and post-omicron titres are indeed higher in those who were infection-naive. In contrast, significant increases in nasal antibody responses are seen regardless of prior infection history, including neutralizing activity against BA.5 spike. Spike-specific T cells increase only in infection-naive vaccinees; however, post-omicron T cell responses are still significantly higher in previously-infected individuals, who appear to have maximally induced responses with a CD8+ phenotype of high cytotoxic potential after their 3rd mRNA vaccine dose. Antibody and T cell responses to non-spike antigens also increase significantly regardless of prior infection status, with a boost seen in previously-infected individuals to immunity primed by their first infection. These findings suggest that hybrid immunity induced by omicron breakthrough infections is highly dynamic, complex, and compartmentalised, with significant immune enhancement that can help protect against COVID-19 caused by future omicron variants.
Subject(s)
Breakthrough Pain , COVID-19 , Status EpilepticusABSTRACT
Both infection and vaccination, alone or in combination, generate antibody and T cell responses against SARS-CoV-2. However, the maintenance of such responses - and hence protection from disease - requires careful characterisation. In a large prospective study of UK healthcare workers (PITCH, within the larger SIREN study) we previously observed that prior infection impacted strongly on subsequent cellular and humoral immunity induced after long and short dosing intervals of BNT162b2 (Pfizer/BioNTech) vaccination. Here, we report longer follow up of 684 HCWs in this cohort over 6-9 months following two doses of BNT162b2 or AZ1222 (Oxford/AstraZeneca) vaccination and following a subsequent BNT162b2 booster vaccination. We make three important observations: Firstly, the dynamics of humoral and cellular responses differ; binding and neutralising antibodies declined whereas T and B cell responses were better maintained after the second vaccine dose. Secondly, vaccine boosting restored IgG levels to post second dose levels and broadened neutralising activity against variants of concern including omicron BA.1, alongside further boosting of T cell responses. Thirdly, prior infection maintained its impact driving larger T cell responses compared to never infected people, including after the third dose. In conclusion, the maintenance of T cell responses in time and against variants of concern may account for continued protection against severe disease.
Subject(s)
COVID-19 , HallucinationsABSTRACT
We identify amino acid variants within dominant SARS-CoV-2 T-cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T-cells assessed by IFN-{gamma} and cytotoxic killing assays. These data demonstrate the potential for T-cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T-cell as well as humoral immunity.
ABSTRACT
A major issue in identification of protective T cell responses against SARS-CoV-2 lies in distinguishing people infected with SARS-CoV-2 from those with cross-reactive immunity generated by exposure to other coronaviruses. We characterised SARS-CoV-2 T cell immune responses in 168 PCR-confirmed SARS-CoV-2 infected subjects and 118 seronegative subjects without known SARS-CoV-2 exposure using a range of T cell assays that differentially capture immune cell function. Strong ex vivo ELISpot and proliferation responses to multiple antigens (including M, NP and ORF3) were found in those who had been infected by SARS-CoV-2 but were rare in pre-pandemic and unexposed seronegative subjects. However, seronegative doctors with high occupational exposure and recent COVID-19 compatible illness showed patterns of T cell responses characteristic of infection, indicating that these readouts are highly sensitive. By contrast, over 90% of convalescent or unexposed people showed proliferation and cellular lactate responses to spike subunits S1/S2, indicating pre-existing cross-reactive T cell populations. The detection of T cell responses to SARS-CoV-2 is therefore critically dependent on the choice of assay and antigen. Memory responses to specific non-spike proteins provides a method to distinguish recent infection from pre-existing immunity in exposed populations.
Subject(s)
Severe Acute Respiratory Syndrome , COVID-19ABSTRACT
We have developed periscope, a tool for the detection and quantification of sub-genomic RNA in ARTIC network protocol generated Nanopore SARS-CoV-2 sequence data. We applied periscope to 1155 SARS-CoV-2 sequences from Sheffield, UK. Using a simple local alignment to detect reads which contain the leader sequence we were able to identify and quantify reads arising from canonical and non-canonical sub-genomic RNA. We were able to detect all canonical sub-genomic RNAs at expected abundances, with the exception of ORF10, suggesting that this is not a functional ORF. A number of recurrent non-canonical sub-genomic RNAs are detected. We show that the results are reproducible using technical replicates and determine the optimum number of reads for sub-genomic RNA analysis. Finally variants found in genomic RNA are transmitted to sub-genomic RNAs with high fidelity in most cases. This tool can be applied to tens of thousands of sequences worldwide to provide the most comprehensive analysis of SARS-CoV-2 sub-genomic RNA to date.