Multiple plant hormone catabolism activities: an adaptation to a plant‐associated lifestyle by <i>Achromobacter</i> spp.
Bibliographic record
Abstract
Elaborating the plant hormone catabolic activities of bacteria is important for developing a detailed understanding of plant-microbe interactions. In this work, the plant hormone catabolic and plant growth promotion activities of Achromobacter xylosoxidans SOLR10 and A. insolitus AB2 are described. The genome sequences of these strains were obtained and analysed in detail, revealing the genetic mechanisms behind its multiple plant hormone catabolism abilities. Achromobacter strains catabolized indoleacetic acid (IAA) and phenylacetic acid (PAA) (auxins); salicylic acid (SA) and its precursor, benzoic acid (BA); and the ethylene precursor 1-aminocyclopropane-1-carboxylate (ACC). The inoculation of cucumber plants resulted in increased plant growth and development, indicating the beneficial properties of SOLR10 and AB2 strains. Genomic analysis demonstrated the presence of IAA, PAA and BA degradation gene clusters, as well as the nag gene cluster (SA catabolism) and the acdS gene (ACC deaminase), in the genomes of strains SOLR10 and AB2. Additionally, detailed analysis revealed that plant hormone catabolism genes were commonly detected in the Achromobacter genus but were mostly absent in the Bordetella genus, consistent with the notion that Achromobacter evolved in soils in close association with its plant hosts.
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) | 0.001 | 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 | 0.000 |
| 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".