Comparative analysis of outer membrane vesicles from cationic adapted Escherichia coli isolates reveals unique vesicle membrane morphologies and different antimicrobial susceptibilities when supplemented to unadapted E. coli
Bibliographic record
Abstract
Cationic antimicrobials (CA) such as the therapeutic antibiotic colistin (COL) and antiseptics cetrimide (CET) and chlorhexidine (CHX) all exert their mechanism of action by disrupting bacterial membranes, leading to cell content leakage and death. Resistance to CAs is rapidly increasing and of the many antimicrobial resistance mechanisms that may contribute, the role of outer membrane vesicle (OMV) formation is least understood. Here, we gradually adapted E. coli BW215113 K-12 to COL, CET, and CHX by prolonged exposure in vitro to determine how each CA impacts OMV formation. We assessed OMVs isolated from each CA-adapted strain by nanoparticle tracking analysis (NTA) and cryo-transmission electron microscopy (cryo-TEM), and compared OMV proteomes using liquid chromatography-mass spectroscopy. The results of NTA analysis showed that all three CA-adapted strains had increased OMV formation as compared to unadapted BW25113 (WT), where CA-adapted OMVs were significantly larger. Cryo-TEM analyses revealed that each strain’s OMVs had distinctive morphological alterations, where CET-OMVs looked similar to unadapted WT OMVs but were encapsulated and aggregated, CHX-OMVs were multilamellar and COL-OMVs were large (4-12X) and tubular as compared to WT OMVs. Proteomic analysis highlighted significant increases in EptC abundance in COL-OMVs and decreased abundance of MlaA in CHX-OMVs. Antimicrobial susceptibility testing of E. coli BW25113 K-12 supplemented with purified CA-adapted OMVs demonstrated that CET-OMVs did not alter CET susceptibility, CHX-OMVs enhanced BW25113 tolerance to CHX exposure by 2-fold, and COL-OMV supplementation to BW25113 increased COL susceptibility by 2-fold compared to unadapted WT OMVs. Hence, CA adaptation by E. coli has significant ramifications on OMV production and morphology, and CA-adapted OMV exposure has significant consequences for bacterial antimicrobial susceptibility.
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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) | 0.000 | 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".