A Brazilian Zika virus isolate preferentially induces T follicular helper cell responses while suppressing Th1 immunity
Bibliographic record
Abstract
Abstract Zika virus (ZIKV) is a mosquito-borne pathogen that caused a series of increasingly severe outbreaks in Micronesia, French Polynesia, and South and Central America. Recent work from our laboratory has shown that, compared to a pre-epidemic isolate (ZIKV-CDN), a Brazilian ZIKV isolate (ZIKV-BR) possesses a novel capacity to suppress antigen-specific CD8 T cell responses, resulting in sustained infection. However, it is unknown whether ZIKV-BR also modulates CD4 T cell immunity. Thus, we investigated the CD4 T cell response to infection with each ZIKV isolate. Our data demonstrate that the CD4 T cell response to ZIKV-BR is reduced in magnitude compared to the response induced by ZIKV-CDN. Further, CD4 T cells are less polarized to the Th1 subtype, express less T-Bet, and are functionally impaired, as they produce less IFN-γ following ex vivo restimulation. Although we observed no alterations in the Th2, Th17 or T regulatory cell compartments, we observed a striking accumulation of PD-1hiCXCR5+ T follicular helper (Tfh) cells 10 days post-infection with ZIKV-BR. This response correlated with an enhanced germinal center B cell response, and increased detection of germinal center formation by confocal microscopy. Future studies will aim to determine the mechanism through which ZIKV-BR infection enhances the Tfh response, and the implications of promoting Tfh responses while dampening Th1 responses for antiviral immunity. Together, our data suggest that contemporary ZIKV strains have evolved to modulate CD4 T cell responses and this could provide a model for interrogating the signals required for Tfh development.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".