Community heterogeneity and single‐cell digestive activity of estuarine heterotrophic nanoflagellates assessed using lysotracker and flow cytometry
Bibliographic record
Abstract
Heterotrophic nanoflagellates (HNFs) are an essential component of all aquatic microbial food webs, and yet the exploration of the numerical and single-cell responses of these organisms in mixed assemblages still represents a major technical challenge. LysoTracker Green staining combined with flow cytometry was recently proposed for the enumeration of aquatic HNFs. Here we show that LysoTracker Green not only allows the enumeration of HNFs in estuarine samples with a wide range of HNF abundances, but also allows the discrimination of distinct HNF populations in mixed assemblages. In addition, the resulting cytometric parameters can be used to characterize cell size and the level of activity of the cells in the different populations that are detected. LysoTracker Green accumulates preferentially in lysosomes, and we demonstrate that the green fluorescence emission from HNF cells stained with LysoTracker strongly correlates with cell-specific beta-glucosaminidase (beta-Gam) activity, a key digestive enzyme of lysosomal origin in eukaryotic cells. Our results further show that different populations that develop in estuarine regrowth cultures are characterized by different intrinsic ranges of size and of feeding activity, and that there is a wide range of single-cell responses within these HNF populations. We found a large degree of uncoupling between cell size and feeding activity, both between and within HNF populations, and there appears to be no clear allometric scaling of feeding activity. We were able to reconstruct the succession of distinct HNF populations that developed during the regrowth experiments, and explore the complex interactions that occurred between numerical (change in abundance of the cytometric populations) and single-cell HNF responses.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".