Pre-existing polymerase-specific T cells expand in abortive seronegative SARS-CoV-2 infection
Bibliographic record
Abstract
Abstract Individuals with likely exposure to the highly infectious SARS-CoV-2 do not necessarily develop PCR or antibody positivity, suggesting some may clear sub-clinical infection before seroconversion. T cells can contribute to the rapid clearance of SARS-CoV-2 and other coronavirus infections 1–5 . We hypothesised that pre-existing memory T cell responses, with cross-protective potential against SARS-CoV-2 6–12 , would expand in vivo to mediate rapid viral control, potentially aborting infection. We studied T cells against the replication transcription complex (RTC) of SARS-CoV-2 since this is transcribed first in the viral life cycle 13–15 and should be highly conserved. We measured SARS-CoV-2-reactive T cells in a cohort of intensively monitored healthcare workers (HCW) who remained repeatedly negative by PCR, antibody binding, and neutralisation for SARS-CoV-2 (exposed seronegative, ES). 16-weeks post-recruitment, ES had memory T cells that were stronger and more multispecific than an unexposed pre-pandemic cohort, and more frequently directed against the RTC than the structural protein-dominated responses seen post-detectable infection (matched concurrent cohort). The postulate that HCW with the strongest RTC-specific T cells had an abortive infection was supported by a low-level increase in IFI27 transcript, a robust early innate signature of SARS-CoV-2 infection 16 . We showed that the RNA-polymerase within RTC was the largest region of high sequence conservation across human seasonal coronaviruses (HCoV) and was preferentially targeted by T cells from UK and Singapore pre-pandemic cohorts and from ES. RTC epitope-specific T cells capable of cross-recognising HCoV variants were identified in ES. Longitudinal samples from ES and an additional validation cohort, showed pre-existing RNA-polymerase-specific T cells expanded in vivo following SARS-CoV-2 exposure, becoming enriched in the memory response of those with abortive compared to overt infection. In summary, we provide evidence of abortive seronegative SARS-CoV-2 infection with expansion of cross-reactive RTC-specific T cells, highlighting these highly conserved proteins as targets for future vaccines against endemic and emerging Coronaviridae .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".