Global Functional Analyses of Cellular Responses to Pore-Forming Toxins
Bibliographic record
Abstract
Here we present the first global functional analysis of cellular responses to pore-forming toxins (PFTs). PFTs are uniquely important bacterial virulence factors, comprising the single largest class of bacterial protein toxins and being important for the pathogenesis in humans of many Gram positive and Gram negative bacteria. Their mode of action is deceptively simple, poking holes in the plasma membrane of cells. The scattered studies to date of PFT-host cell interactions indicate a handful of genes are involved in cellular defenses to PFTs. How many genes are involved in cellular defenses against PFTs and how cellular defenses are coordinated are unknown. To address these questions, we performed the first genome-wide RNA interference (RNAi) screen for genes that, when knocked down, result in hypersensitivity to a PFT. This screen identifies 106 genes (∼0.5% of genome) in seven functional groups that protect Caenorhabditis elegans from PFT attack. Interactome analyses of these 106 genes suggest that two previously identified mitogen-activated protein kinase (MAPK) pathways, one (p38) studied in detail and the other (JNK) not, form a core PFT defense network. Additional microarray, real-time PCR, and functional studies reveal that the JNK MAPK pathway, but not the p38 MAPK pathway, is a key central regulator of PFT-induced transcriptional and functional responses. We find C. elegans activator protein 1 (AP-1; c-jun, c-fos) is a downstream target of the JNK-mediated PFT protection pathway, protects C. elegans against both small-pore and large-pore PFTs and protects human cells against a large-pore PFT. This in vivo RNAi genomic study of PFT responses proves that cellular commitment to PFT defenses is enormous, demonstrates the JNK MAPK pathway as a key regulator of transcriptionally-induced PFT defenses, and identifies AP-1 as the first cellular component broadly important for defense against large- and small-pore PFTs.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".