Evolutionary responses of Escherichia coli to phage pressure: insights into mucoidy and colanic acid overexpression
Bibliographic record
Abstract
BACKGROUND: Antibiotic resistance is a major issue affecting all spheres of human activity, including agriculture. One significant example is the Avian Pathogenic Escherichia coli (APEC), a bacterium that infects poultry and leads to substantial economic losses in the farming industry. As antibiotics lose efficacity, bacteriophages (phages) -viruses that specifically target bacteria-are emerging as a promising alternative to antibiotics for treating and preventing bacterial infections. However, bacteria can develop resistance to phages through various mechanisms. Studying the coevolution between a phage and its host bacterium is important to gain insight into the phage's potential as a therapeutic agent. This study investigates the evolutionary responses of an APEC strain and a laboratory E. coli strain to a commercial phage originally isolated from APEC. RESULTS: In most cases, phage resistance resulted in a significant increase in mucoidy. Genomic analysis revealed that this resistance consistently correlated with amino acid changes, particularly in proteins involved in colanic acid production, such as YrfF. Further investigation of a mutation found in the YrfF protein demonstrated that this mutation altered the protein's structure and its interaction with the membrane. Transcriptomic analysis confirmed that the genes involved in colanic acid production were significantly overexpressed. Although the strains possessed a CRISPR-Cas system, it did not contribute to phage resistance. CONCLUSIONS: This study suggests that specific amino acid changes in key proteins may be a mechanism employed by E. coli, including APEC, to defend against phage infections.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".