Polarity effects, resistance, and probiotic enhancement of intoxication of Salmonella enterica fraB mutants in murine models
Bibliographic record
Abstract
FraB is a deglycase in a metabolic pathway that allows Salmonella to utilize fructose-asparagine (F-Asn). Some fraB mutants are sensitive to F-Asn due to the accumulation of 6-phosphofructose-aspartate (6-P-F-Asp), a toxic intermediate in this pathway. We determined that different alleles of fraB cause different amounts of 6-P-F-Asp-mediated toxicity due to effects on the expression of the downstream gene, fraD, a kinase. Mutations in fraD or fraA (a transporter) cause resistance to F-Asn intoxication, and these mutations occur during infection. To better mimic the effect of a hypothetical FraB inhibitor in mouse models, we characterized a non-polar mutant encoding a catalytically inactive FraB (FraB E214A). We also compared a typical mouse chow and a high-fat chow and found that the latter decreases the variation in colonization typically observed during infection of CBA/J mice with Salmonella. Because the high-fat chow lacks F-Asn, the fraB E214A mutant was not attenuated in mice fed this diet unless F-Asn was supplemented. F-Asn supplementation resulted in a 100-fold reduction of colony forming units (CFU) recovered from feces compared to wild-type. Co-infection of Salmonella with a Salmonella "probiotic" strain that is neither virulent nor capable of consuming F-Asn (a SPI1 SPI2 fraR-BDAE ansB mutant) led to a dramatic 10,000-fold reduction in CFU and a 1000-fold reduction in lipocalin-2, a proxy marker of inflammation. This probiotic strain presumably competes for nutrients other than F-Asn, driving the fraB mutant to consume a higher proportion of F-Asn and greater 6-P-F-Asp intoxication. Thus, a putative inhibitor of FraB, when administered with F-Asn and a probiotic, may provide a new therapeutic strategy for treating Salmonella gastroenteritis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".