Magnetotaxis as an Adaptation to Enable Bacterial Shuttling of Microbial Sulfur and Sulfur Cycling Across Aquatic Oxic‐Anoxic Interfaces
Bibliographic record
Abstract
Abstract Magnetotactic bacteria (MTB) widely inhabit the oxic‐anoxic interface (OAI) of sediments and water columns, with their motility guided by geomagnetic fields (a behavior known as magnetotaxis). Beside biomineralizing membrane‐enveloped magnetite or greigite nanocrystals called magnetosomes, cells of many MTB groups contain numerous sulfur globules within their cells. Here, by combining transmission electron microscopy and synchrotron‐based scanning transmission X‐ray microscopy, we investigated the cellular structure and chemistry of Candidatus Magnetobacterium casensis (Mcas), a giant rod‐shaped MTB from the Nitrospirae phylum. We find that nitrate‐storing vacuoles and linearly polymeric sulfur globules occur exclusively within some Mcas cells along with magnetosomal magnetite. Genomic prediction indicates that Mcas cells have the potential to oxidize sulfide to sulfate (i.e., S2− → S0 → SO32− → SO42−), to reduce sulfate to sulfide (i.e., SO42− → SO32− → S2−), and to reduce nitrate to NH4+/N2. Together with previous environmental observations, comparative genomic analysis allows us to propose a model for Mcas involving the microbial sulfur cycle across aquatic OAIs based on magnetotaxis. Via directional movement guided by geomagnetic fields, Mcas cells shuttle either upward to upper microoxic zones for sulfur oxidation and nitrate accumulation in the OAI, or downward to deeper anoxic zones for sulfur deposition by coupling sulfide oxidation and nitrate reduction. Development of magnetotaxis makes MTB an efficient bacterial shuttle for C, N, S, and Fe across aquatic OAI environments and likely contributes significantly to their global biogeochemical cycling. It also benefits cell growth and magnetosomal magnetite formation in MTB.
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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".