In vivo CRISPR screens reveal a HIF-1α-mTOR-network regulates T follicular helper versus Th1 cells
Bibliographic record
Abstract
T follicular helper (Tfh) cells provide signals to initiate and maintain the germinal center (GC) reaction and are crucial for the generation of robust, long-lived antibody responses, but how the GC microenvironment affects Tfh cells is not well understood. Here we develop an in vivo T cell-intrinsic CRISPR-knockout screen to evaluate Tfh and Th1 cells in an acute viral infection model to identify regulators of Tfh cells in their physiological setting. Using a screen of druggable-targets, alongside genetic, transcriptomic and cellular analyses, we identify a function of HIF-1α in suppressing mTORC1-mediated and Myc-related pathways, and provide evidence that VHL-mediated degradation of HIF-1α is required for Tfh development; an expanded in vivo CRISPR screen reveals multiple components of these pathways that regulate Tfh versus Th1 cells, including signaling molecules, cell-cycle regulators, nutrient transporters, metabolic enzymes and autophagy mediators. Collectively, our data serve as a resource for studying Tfh versus Th1 decisions, and implicate the VHL-HIF-1α axis in fine-tuning Tfh generation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".