Development of flow cytometry assay to quantify packaging of <i>C. jejuni</i> by <i>Tetrahymena</i> species
Bibliographic record
Abstract
The human pathogen Campylobacter jejuni can be packaged within multilamellar bodies (MLB), also called fecal pellets, produced by ciliates such as Tetrahymena pyriformis when these microorganisms are cocultivated. This packaging increases the survival of C. jejuni in oxygenic conditions and potentially protects it against other stressors. Traditional methods for detecting and quantifying these pellets, such as transmission electron microscopy (TEM) and fluorescence microscopy, are time-consuming and labor intensive. In this study, we devised an approach for utilizing flow cytometry to distinguish and quantify C. jejuni-containing pellets produced by both T. pyriformis and T. thermophila. Cocultures of each Tetrahymena species with four different C. jejuni strains, along with monoculture controls, were incubated for 24 h, stained with SYTO9, and analysed using flow cytometry. The results revealed ciliate species-specific and bacterial strain-specific differences in the number of pellets and their fluorescence intensity. TEM confirmed that this variability in fluorescence corresponds to differences in the number of bacteria per pellet. Our method provides a rapid and efficient means of quantifying bacteria-containing MLBs, which would facilitate the screening and comparison of a large quantity of C. jejuni strains and different conditions for studying the packaging of C. jejuni by ciliates.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".