Effects of Copper Availability on the Physiology of Marine Heterotrophic Bacteria
Bibliographic record
Abstract
Marine heterotrophic bacteria play a crucial role in the cycling of energy and nutrients in the ocean. Copper (Cu) belongs to the repertoire of essential trace nutrients for bacterial growth, yet physiological responses of marine heterotrophic bacteria to Cu deficiency remain unexplored. Here, we examined these responses in oceanic and coastal isolates of heterotrophic bacteria from ecologically significant microbial clades (Flavobacteriia [Bacteroidetes], Roseobacter clade [Alphaproteobacteria] and Alteromonadales [Gammaproteobacteria]). Bacterial growth, Cu quotas (Cu:P), macronutrient content and stoichiometry (cellular C, N, P, S and C:N, S:P), as well as carbon metabolism (respiration, productivity, carbon demand, growth efficiency) were monitored across a gradient of Cu conditions, characteristic of coastal and open-ocean surface waters. Cu deficiency had most severe effects on a Flavobacteriia member Dokdonia sp. strain Dokd-P16 for which we observed significant reductions in growth, C metabolism and Cu quotas. Other strains did not significantly reduce their growth rate, but adjusted their Cu content and some C metabolic rates (Ruegeria pomeroyi DSS-3, Roseobacter clade) or were unaffected (Pseudoalteromonas sp. strains PAlt-P26 and PAlt-P2, Alteromonadales clade). These diverse bacterial responses were accompanied by constant cellular composition of major elements and stoichiometric ratios. Changes in bacterial Cu quotas occurred within a modest range (~5-fold range) relative to the 50-fold variation in total Cu in the media. We hypothesize that this may reflect a well-controlled Cu homeostasis in marine heterotrophic bacteria. In a preliminary assessment, we found that Cu quotas of our bacteria and those of eukaryotic phytoplankton are not statistically different. However, compared to eukaryotic phytoplankton, the variability of Cu quotas in marine heterotrophic bacteria is smaller, which could reflect differences in their Cu homeostasis. Using Cu quotas obtained in our study, we assessed the contribution of bacterial Cu to the biogenic Cu pool in an oceanic euphotic zone in the NE Pacific. These preliminary estimates suggest that up to 50 % of the biogenic Cu could be contained in the heterotrophic bacteria biomass. Our study sheds light on the interactions between Cu and marine heterotrophic bacteria, and expands the understanding of factors influencing microbial ecology and bacterial role in Cu cycle.
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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) | 0.001 | 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 | 0.001 |
| 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".