l-Cysteine is required for induced antibiotic resistance in actively swarming Salmonella enterica serovar Typhimurium
Bibliographic record
Abstract
Swarm-cell differentiation in Salmonella enterica serovar Typhimurium (S. typhimurium) results in a biosynthetic mode of growth, despite growing on a rich medium, and cells that have elevated antibiotic resistance. These phenotypes are not a prerequisite for swarm motility. By blocking the switch to anabolic growth using amino acid auxotrophs and screening for the presence of elevated antibiotic resistance in the swarm state, we found that cysteine biosynthesis is crucial for complete swarm-cell differentiation. Mutants were made in each cys biosynthetic operon and all had decreased antibiotic resistance in the swarm state, while swim-cell resistance remained the same as that of wild-type cells. This swarm-state-specific decreased resistance in Deltacys strains could be restored to wild-type levels by the addition of cysteine to swarm medium. Two regulatory mutants, DeltacysB and DeltacysE, failed to swarm unless cysteine was supplemented to the medium. We show that all CysB-responsive operons involved in cysteine biosynthesis are upregulated in the swarm state, even though swarm cells are cultivated on a medium that represses cysteine biosynthesis in the swim state. While swarm medium has sufficient cysteine for growth of S. typhimurium, it does not contain enough for swarm-cell differentiation. We hypothesize that in these cells, the additional cysteine requirement is for use in pathways not directly related to cell 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 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".