Single-cell quantification of the microbiota by flow cytometry: MicFLY
Bibliographic record
Abstract
SUMMARY The intestinal microbiota regulates multiple host functions, including digestion and immune development. Our knowledge of the microbiota has been shaped by available technology that primarily measures relative abundance. However, understanding the basis of shifts in microbiota composition requires single cell, absolute abundance measurements. In response to this problem, we developed Mic robiota Fl ow C y tometry (MicFLY), a single cell technology that directly quantifies and characterizes total bacterial abundances with species-level resolution in the microbiota. Using MicFLY, we can identify all major intestinal taxa, discriminate live from dead bacteria, perform single cell measurements of heterogeneous bacterial mRNA expression and concurrently quantify Immunoglobulin (Ig) A and G binding to intestinal bacteria. Using longitudinal species-resolved, quantitative analysis of the preterm infant microbiota, we identify that E. coli unbound by IgG and IgA associates with the development of necrotizing enterocolitis. The application of MicFLY single cell technology permits measurement of the microbiota at a finer scale and with deeper mechanistic understanding of compositional changes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".