Magnetotaxis Enables Magnetotactic Bacteria to Navigate in Flow
Bibliographic record
Abstract
Abstract Magnetotactic bacteria (MTB) play an important role in Earth's biogeochemical cycles by transporting minerals in aquatic ecosystems, and have shown promise for controlled transport of microscale objects in flow conditions. However, how MTB traverse complex flow environments is not clear. Here, using microfluidics and high‐speed imaging, it is revealed that magnetotaxis enables directed motion of Magnetospirillum magneticum over long distances in flow velocities ranging from 2 to 1260 µm s−1, corresponding to shear rates ranging from 0.2 to 142 s−1—a range relevant to both aquatic environments and biomedical applications. The ability of MTB to overcome a current is influenced by the flow, the magnetic field, and their relative orientation. MTB can overcome 2.3‐fold higher flow velocities when directed to swim perpendicular to the flow as compared to upstream, as the latter orientation induces higher drag. The results indicate a threshold drag of 9.5 pN, corresponding to a flow velocity of 550 µm s−1, where magnetotaxis enables MTB to overcome counterdirectional flow. These findings bring new insights into the interactions of MTB with complex flow environments relevant to aquatic ecosystems, while suggesting opportunities for in vivo applications of MTB in microbiorobotics and targeted drug delivery.
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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".