Hydroxypyridinones in nitrogen-fixing bacterial cultures: a metal buffer for molybdenum and simulation of natural conditions
Bibliographic record
Abstract
Organic matter regulates the availability of important trace elements in aquatic and terrestrial ecosystems by acting as a source and container for microbes. To overcome the limitation of trace elements, nitrogen-fixing bacteria, e.g. release low-molecular-weight chelators (metallophores), which scavenge the essential cofactors of the nitrogenase, iron, and molybdenum (Mo), via complexation and subsequent uptake. The formation of metallophores is triggered by limiting conditions, which must be replicated in the laboratory in order to study metallophores as a mediator in metal cycling. While ethylenediaminetetraacetic acid (EDTA)-based buffer systems for metal cations are well established, there is limited knowledge regarding the buffering of oxoanions such as molybdate in a bacterial growth medium. To mimic the availability of molybdenum in nature under laboratory conditions, this study created a Mo-buffer system for bacterial growth media of the model organisms Azotobacter vinelandii and Frankia sp. CH37. We investigated selected hydroxypyridinones (HPs) as potential molybdenum-chelating agents, determining the amount required for efficient molybdenum complexation by calculating speciation plots of the various candidate complexes in artificial growth media at various pH values. The Mo-maltol system was identified as an ideal, nontoxic molybdenum-buffer system. In the presence of the Mo-maltol system, the growth of Frankia sp. was limited under diazotrophic conditions, whereas A. vinelandii could acquire molybdenum through the release of protochelin and subsequent molybdenum uptake. The study paves the way for unravelling molybdenum recruitment and homeostasis under limiting conditions in bacteria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".