Redox‐reactive membrane vesicles produced by <i>Shewanella</i>
Bibliographic record
Abstract
This manuscript is dedicated to our friend, mentor, and coauthor Dr Terry Beveridge, who devoted his scientific career to advancing fundamental aspects of microbial ultrastructure using innovative electron microscopic approaches. During his graduate studies with Professor Robert Murray, Terry provided some of the first glimpses and structural evaluations of the regular surface arrays (S-layers) of Gram-negative bacteria (Beveridge & Murray, 1974, 1975, 1976a). Beginning with his early electron microscopic assessments of metal binding by cell walls from Gram-positive bacteria (Beveridge & Murray, 1976b, 1980) and continuing with more than 30 years of pioneering research on microbe-mineral interactions (Hoyle & Beveridge, 1983, 1984; Ferris et al., 1986; Gorby et al., 1988; Beveridge, 1989; Mullen et al., 1989; Urrutia Mera et al., 1992; Mera & Beveridge, 1993; Brown et al., 1994; Konhauser et al., 1994; Beveridge et al., 1997; Newman et al., 1997; Lower et al., 2001; Glasauer et al., 2002; Baesman et al., 2007), Terry helped to shape the developing field of biogeochemistry. Terry and his associates are also widely regarded for their research defining the structure and function of outer membrane vesicles from Gram-negative bacteria that facilitate processes ranging from the delivery of pathogenic enzymes to the possible exchange of genetic information. The current report represents the confluence of two of Terry's thematic research streams by demonstrating that membrane vesicles produced by dissimilatory metal-reducing bacteria from the genus Shewanella catalyze the enzymatic transformation and precipitation of heavy metals and radionuclides. Under low-shear conditions, membrane vesicles are commonly tethered to intact cells by electrically conductive filaments known as bacterial nanowires. The functional role of membrane vesicles and associated nanowires is not known, but the potential for mineralized vesicles that morphologically resemble nanofossils to serve as palaeontological indicators of early life on Earth and as biosignatures of life on other planets is recognized.
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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 | 0.001 | 0.000 |
| 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".