Super-resolution confocal cryo-CLEM with cryo-FIB milling for in situ imaging of Deinococcus radiodurans
Bibliographic record
Abstract
Studying bacterial cell envelope architecture with electron microscopy is challenging due to the poor preservation of microbial ultrastructure with traditional methods. Here, we established and validated a super-resolution cryo-correlative light and electron microscopy (cryo-CLEM) method, and combined it with cryo-focused ion beam (cryo-FIB) milling and scanning electron microscopy (SEM) volume imaging to structurally characterize the bacterium Deinococcus radiodurans. Subsequent cryo-electron tomography (cryo-ET) revealed an unusual diderm cell envelope architecture with a thick layer of peptidoglycan (PG) between the inner and outer membranes, an additional periplasmic layer, and a proteinaceous surface S-layer. Cells grew in tetrads, and division septa were formed by invagination of the inner membrane (IM), followed by a thick layer of PG. Cytoskeletal filaments, FtsA and FtsZ, were observed at the leading edges of constricting septa. Numerous macromolecular complexes were found associated with the cytoplasmic side of the IM. Altogether, our study revealed several unique ultrastructural features of D. radiodurans cells, opening new lines of investigation into the physiology and evolution of the bacterium.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".