Sulfur Isotope Enrichment during Maintenance Metabolism in the Thermophilic Sulfate-Reducing Bacterium <i>Desulfotomaculum putei</i>
Bibliographic record
Abstract
Values of Delta(34)S (=delta(34)S(HS)-delta(34)S(SO(4)), where delta(34)S(HS) and delta(34)S(SO(4)) indicate the differences in the isotopic compositions of the HS(-) and SO(4)(2-) in the eluent, respectively) for many modern marine sediments are in the range of -55 to -75 per thousand, much greater than the -2 to -46 per thousand epsilon(34)S (kinetic isotope enrichment) values commonly observed for microbial sulfate reduction in laboratory batch culture and chemostat experiments. It has been proposed that at extremely low sulfate reduction rates under hypersulfidic conditions with a nonlimited supply of sulfate, isotopic enrichment in laboratory culture experiments should increase to the levels recorded in nature. We examined the effect of extremely low sulfate reduction rates and electron donor limitation on S isotope fractionation by culturing a thermophilic, sulfate-reducing bacterium, Desulfotomaculum putei, in a biomass-recycling culture vessel, or "retentostat." The cell-specific rate of sulfate reduction and the specific growth rate decreased progressively from the exponential phase to the maintenance phase, yielding average maintenance coefficients of 10(-16) to 10(-18) mol of SO(4) cell(-1) h(-1) toward the end of the experiments. Overall S mass and isotopic balance were conserved during the experiment. The differences in the delta(34)S values of the sulfate and sulfide eluting from the retentostat were significantly larger, attaining a maximum Delta(34)S of -20.9 per thousand, than the -9.7 per thousand observed during the batch culture experiment, but differences did not attain the values observed in marine sediments.
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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".