Oceanic Crustal Fluid Single Cell Genomics Complements Metagenomic and Metatranscriptomic Surveys With Orders of Magnitude Less Sample Volume
Bibliographic record
Abstract
Fluids circulating through oceanic crust play important roles in global biogeochemical cycling mediated by their microbial inhabitants, but studying these sites is challenged by sampling logistics and low biomass. Borehole observatories installed at the North Pond study site on the western flank of the Mid-Atlantic Ridge have enabled investigation of the microbial biosphere in cold, oxygenated basaltic oceanic crust. Here we test a methodology that applies redox-sensitive fluorescent molecules for flow cytometric sorting of cells for single cell genomic sequencing from small volumes of low biomass (approximately 103 cells ml–1) crustal fluid. We compare the resulting genomic data to a recently published paired metagenomic and metatranscriptomic analysis from the same site. Even with low coverage genome sequencing, sorting cells from less than one milliliter of crustal fluid results in similar interpretation of dominant taxa and functional profiles as compared to ‘omics analysis that typically filter orders of magnitude more fluid volume. The diverse community dominated by Gammaproteobacteria, Bacteroidetes, Desulfobacterota, Alphaproteobacteria, and Zetaproteobacteria, had evidence of autotrophy and heterotrophy, a variety of nitrogen and sulfur cycling metabolisms, and motility. Together, results indicate fluorescence activated cell sorting methodology is a powerful addition to the toolbox for the study of low biomass systems or at sites where only small sample volumes are available for analysis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".