Preservation of protein globules and peptidoglycan in the mineralized cell wall of nitrate-reducing, iron(II)-oxidizing bacteria: a cryo-electron microscopy study
Bibliographic record
Abstract
Iron-oxidizing bacteria are important actors of the geochemical cycle of iron in modern environments and may have played a key role all over Earth's history. However, in order to better assess that role on the modern and the past Earth, there is a need for better understanding the mechanisms of bacterial iron oxidation and for defining potential biosignatures to be looked for in the geologic record. In this study, we investigated experimentally and at the nanometre scale the mineralization of iron-oxidizing bacteria with a combination of synchrotron-based scanning transmission X-ray microscopy (STXM), scanning transmission electron microscopy (STEM) and cryo-transmission electron microscopy (cryo-TEM). We show that the use of cryo-TEM instead of conventional microscopy provides detailed information of the successive iron biomineralization stages in anaerobic nitrate-reducing iron-oxidizing bacteria. These results suggest the existence of preferential Fe-binding and Fe-oxidizing sites on the outer face of the plasma membrane leading to the nucleation and growth of Fe minerals within the periplasm of these cells that eventually become completely encrusted. In contrast, the septa of dividing cells remain nonmineralized. In addition, the use of cryo-TEM offers a detailed view of the exceptional preservation of protein globules and the peptidoglycan within the Fe-mineralized cell walls of these bacteria. These organic molecules and ultrastructural details might be protected from further degradation by entrapment in the mineral matrix down to the nanometre scale. This is discussed in the light of previous studies on the properties of Fe-organic interactions and more generally on the fossilization of mineral-organic assemblies.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".