Sulfate-reducing Bacteria and Mercury Methylation in the Water Column of the Lake 658 of the Experimental Lake Area
Bibliographic record
Abstract
Sulfate-reducing bacteria (SRB) appear to be the main mediators of mercury methylation in sediments, which are deemed to be major sites of methylmercury (MMHg) production. However, recent studies have also found significant MMHg formation in the water column of lakes across North America. To investigate the potential involvement of SRB in mercury methylation in the water column of a stratified oligotrophic lake, two of the main families of SRB (Desulfobacteraceae and Desulfovibrionaceae) were quantified by Real-Time Polymerase Chain Reaction of the 16S rRNA gene. MMHg production was measured applying a stable isotope technique using 198HgCl. Methylation assays were conducted at different water depths and under stimulation with lactate, acetate or propionate and inhibition with molybdate. Desulfobacteraceae and Desulfovibrionaceae16S rRNA gene copies in control samples accounted for 0.05% to 33% and <0.01% to 1.12% of the total bacterial 16S rRNA, respectively. MMHg formation was as high as 0.3 ng L−1 day−1 and largest in lactate amended samples. Strain isolation was only achieved in lactate amended media with all isolated strains being SRB belonging to the Desulfovibrio genus according to their 16S rRNA gene sequence. Isolated strains methylated between 0.06 and 0.2% of 198HgCl per day. Acetate and propionate did not stimulate mercury methylation as much as lactate. Two strains were identified as Desulfovibrio sp. 12ML1 (FJ865472) and Desulfovibrio sp. 12ML3 (FJ865473), based on partial sequences of their 16S rRNA and DSR gene. Methylation assays and bacteria characterization suggest that Desulfovibrionaceae is an important mercury methylators in Lake 658. Supplemental materials are available for this article. Go to the publisher's online edition of Geomicrobiology Journal to view the free supplemental file.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.001 | 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 teacher head, 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".