Bacteriophage-Insensitive Mutants of Antimicrobial-Resistant Salmonella Enterica are Altered in their Tetracycline Resistance and Virulence in Caco-2 Intestinal Cells
Bibliographic record
Abstract
Bacteriophages have shown promise as therapeutic alternatives to antibiotics for the control of infectious bacteria, including the human pathogen Salmonella. However, the development of effective phage-based applications requires the elucidation of key interactions between phages and target hosts, particularly since host resistance to phage is inevitable. Little is known about the alteration of host phenotypes following the development of resistance to phage. The aim of this study is to evaluate the antibiotic susceptibility and virulence of a Salmonella isolate following the development of resistance to bacteriophage SI1. We observed enhanced susceptibility to tetracycline and decreased invasion capacity in a differentiated Caco-2 intestinal cell line. Whole genome sequence analysis revealed an array of mutations, most notably, truncations in vgrG1_2, a core gene involved in Type VI secretion and mutations in the lipopolysaccharide, thereby indicating the plausible attachment site of phage SI1. These findings shed light on understanding the underlying mechanism for phage immunity within the host. Importantly, we reveal an associated genetic cost to the bacterial host with developing resistance to phages. Taken together, these results will aid in advancing strategies to delay or eliminate the development of host resistance when designing informed phage-based antimicrobials.
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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 | 0.000 |
| 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".