Thin Aggregative Fimbriae and Cellulose Enhance Long-Term Survival and Persistence of<i>Salmonella</i>
Bibliographic record
Abstract
Salmonella spp. are environmentally persistent pathogens that have served as one of the important models for understanding how bacteria adapt to stressful conditions. However, it remains poorly understood how they survive extreme conditions encountered outside their hosts. Here we show that the rdar morphotype, a multicellular phenotype characterized by fimbria- and cellulose-mediated colony pattern formation, enhances the resistance of Salmonella to desiccation. When colonies were stored on plastic for several months in the absence of exogenous nutrients, survival of wild-type cells was increased compared to mutants deficient in fimbriae and/or cellulose production. Differences between strains were further highlighted upon exposure to sodium hypochlorite, as cellulose-deficient strains were 1,000-fold more susceptible. Measurements of gene expression using luciferase reporters indicated that production of thin aggregative fimbriae (Tafi) may initiate formation of colony surface patterns characteristic of the rdar morphotype. We hypothesize that Tafi play a role in the organization of different components of the extracellular matrix. Conservation of the rdar morphotype among pathogenic S. enterica isolates and the survival advantages that it provides collectively suggest that this phenotype could play a role in the transmission of Salmonella between hosts.
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) | 0.000 | 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 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".