Innate Recognition of Intracellular Bacterial Growth Is Driven by the TIFA-Dependent Cytosolic Surveillance Pathway
Bibliographic record
Abstract
Intestinal epithelial cells (IECs) act as sentinels for incoming pathogens. Cytosol-invasive bacteria, such as Shigella flexneri, trigger a robust pro-inflammatory nuclear factor κB (NF-κB) response from IECs that is believed to depend entirely on the peptidoglycan sensor NOD1. We found that, during Shigella infection, the TRAF-interacting forkhead-associated protein A (TIFA)-dependent cytosolic surveillance pathway, which senses the bacterial metabolite heptose-1,7-bisphosphate (HBP), functions after NOD1 to detect bacteria replicating free in the host cytosol. Whereas NOD1 mediated a transient burst of NF-κB activation during bacterial entry, TIFA sensed HBP released during bacterial replication, assembling into large signaling complexes to drive a dynamic inflammatory response that reflected the rate of intracellular bacterial proliferation. Strikingly, IECs lacking TIFA were unable to discriminate between proliferating and stagnant intracellular bacteria, despite the NOD1/2 pathways being intact. Our results define TIFA as a rheostat for intracellular bacterial replication, escalating the immune response to invasive Gram-negative bacteria that exploit the host cytosol for growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".