Comparative Analysis of Outer Membrane Vesicle Isolation Methods With an Escherichia coli tolA Mutant Reveals a Hypervesiculating Phenotype With Outer-Inner Membrane Vesicle Content
Bibliographic record
Abstract
Outer membrane vesicles (OMVs) produced by Gram-negative bacteria are mediators of cell survival and pathogenesis by facilitating virulence factor dissemination and resistance to antimicrobials. Studies of OMV properties often focus on hypervesiculating Escherichia coli mutants that have increased OMV production when compared to their corresponding wild-type (WT) strains. Currently, two conventional techniques, ultracentrifugation (UC) and ultradiafiltration (UF), are used interchangeably to isolate OMVs, however, there is concern that each technique may inadvertently alter the properties of isolated OMVs during study. To address this concern, we compared two OMV isolation methods, UC and UF, with respect to final OMV quantities, size distributions, and morphologies using a hypervesiculating Escherichia coli K-12 Δ tolA mutant. Nanoparticle tracking analysis (NTA) indicated that UC techniques result in lower vesicle yields compared to UF. However, UF permitted isolation of OMVs with smaller average sizes than UC, highlighting a potential OMV isolation size bias by each technique. Cryo-transmission electron microscopy (cryo-TEM) visualization of isolated OMVs revealed distinct morphological differences between WT and Δ tolA OMVs, where Δ tolA OMVs isolated by either UC or UF method possessed a greater proportion of OMVs with two or more membranes. Proteomic OMV analysis of WT and Δ tolA OMVs confirmed that Δ tolA enhances inner plasma membrane carryover in multi-lamellar OMVs. This study demonstrates that UC and UF are useful techniques for OMV isolation, where UF may be preferable due to faster isolation, higher OMV yields and enrichment of smaller sized vesicles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".