Uncharacterized Bacterial Structures Revealed by Electron Cryotomography
Bibliographic record
Abstract
ABSTRACT Electron cryotomography (ECT) can reveal the native structure and arrangement of macromolecular complexes inside intact cells. This technique has greatly advanced our understanding of the ultrastructure of bacterial cells. We now view bacteria as structurally complex assemblies of macromolecular machines rather than as undifferentiated bags of enzymes. To date, our group has applied ECT to nearly 90 different bacterial species, collecting more than 15,000 cryotomograms. In addition to known structures, we have observed, to our knowledge, several uncharacterized features in these tomograms. Some are completely novel structures; others expand the features or species range of known structure types. Here, we present a survey of these uncharacterized bacterial structures in the hopes of accelerating their identification and study, and furthering our understanding of the structural complexity of bacterial cells. IMPORTANCE Bacteria are more structurally complex than is commonly appreciated. Here we present a survey of previously uncharacterized structures that we observed in bacterial cells by electron cryotomography, structures that will initiate new lines of research investigating their identities and roles.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".