Altered IFN-γ–Mediated Immunity and Transcriptional Expression Patterns in <i>N</i>-Ethyl-<i>N</i>-Nitrosourea–Induced STAT4 Mutants Confer Susceptibility to Acute Typhoid-like Disease
Bibliographic record
Abstract
Salmonella enterica is a ubiquitous Gram-negative intracellular bacterium that continues to pose a global challenge to human health. The etiology of Salmonella pathogenesis is complex and controlled by pathogen, environmental, and host genetic factors. In fact, patients immunodeficient in genes in the IL-12, IL-23/IFN-γ pathway are predisposed to invasive nontyphoidal Salmonella infection. Using a forward genomics approach by N-ethyl-N-nitrosourea (ENU) germline mutagenesis in mice, we identified the Ity14 (Immunity to Typhimurium locus 14) pedigree exhibiting increased susceptibility following in vivo Salmonella challenge. A DNA-binding domain mutation (p.G418_E445) in Stat4 (Signal Transducer and Activator of Transcription Factor 4) was the causative mutation. STAT4 signals downstream of IL-12 to mediate transcriptional regulation of inflammatory immune responses. In mutant Ity14 mice, the increased splenic and hepatic bacterial load resulted from an intrinsic defect in innate cell function, IFN-γ-mediated immunity, and disorganized granuloma formation. We further show that NK and NKT cells play an important role in mediating control of Salmonella in Stat4(Ity14/Ity14) mice. Stat4(Ity14/Ity14) mice had increased expression of genes involved in cell-cell interactions and communication, as well as increased CD11b expression on a subset of splenic myeloid dendritic cells, resulting in compromised recruitment of inflammatory cells to the spleen during Salmonella infection. Stat4(Ity14/Ity14) presented upregulated compensatory mechanisms, although inefficient and ultimately Stat4(Ity14/Ity14) mice develop fatal bacteremia. The following study further elucidates the pathophysiological impact of STAT4 during Salmonella infection.
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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 | 0.001 |
| 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".