Metallophore profiling of nitrogen-fixing <i>Frankia</i> spp. to understand metal management in the rhizosphere of actinorhizal plants
Bibliographic record
Abstract
Frankia spp. are widespread nitrogen-fixing soil bacteria, which often live in symbiosis with a broad range of hosts. Metal homeostasis plays a crucial role in the success of the symbiosis regarding the acquisition of essential trace metals and detoxification of potentially toxic elements. We have hypothesised that Frankia releases many organic ligands with a broad spectrum of affinity for essential and toxic metals. We coined the term 'ligandosphere' to describe the entirety of excreted metal complexing agents and ligands derived from the dissolved organic matter. Using metal isotope-coded profiling (MICP); metallophores of physiological important and toxic trace metals were identified by the addition of stable metal isotope pairs such as 54Fe/58Fe, 63Cu/65Cu, 66Zn/68Zn or 95Mo/98Mo. Liquid chromatography coupled to a mass spectrometer revealed strong variations of the metallophore profile in between the 14 test-strains. In total, about 83 organic ligands were identified as binding to one of the tested metals. The predicted sum formula of the major Fe binding ligands and MS/MS experiments suggested that several metallophore candidates have a similar molecular backbone. Growth experiments with a hyper-producer of metallophores revealed a positive relationship between metallophore production and the concentration of Cu in the growth medium. The present study provides the first comprehensive overview of the complexity of Frankia's ligandosphere. It opens a path to a deeper understanding of mechanisms that regulate metal homeostasis in frankiae. Deciphering these mechanisms is important since the fitness of actinorhizal plants and their potential in ecological restoration relies heavily on their symbiosis with frankiae.
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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".