The environmental adaptation of acidophilic archaea: promotion of horizontal gene transfer by genomic islands
Bibliographic record
Abstract
Acid mine drainage (AMD) is an extremely acidic leachate highly contaminated with metal ions, yet it harbors a significantly high abundance of archaea. Genomic islands (GIs), as one of the productions of horizontal gene transfer (HGT), play an important role in the environmental adaptation and evolutionary processes of archaea. However, the distribution, structure, and function of GI within the genomes of archaea remain poorly understood. In this study, through the bioinformatic analysis of archaea in AMD, including Ferroplasma acidiphilum ZJ isolated from laboratory and 25 acidophilic archaea collected from NCBI database, 176 GIs were predicted and annotated. Furthermore, we analyzed their structural features and provided insights into the role of HGT in environmental adaptation. The size and distribution of GIs in the genomes were found to be random. In the majority of GIs, the GC content was lower than the average GC content of the strain genome, suggesting that GIs were typically looped out of the genomes with poor stability and transferred into those with higher stability. tRNAs with classical stem-loop secondary structures have been found at the ends of several GIs, suggesting that GIs frequently integrate near tRNAs. In contrast to functional genes directly involved in cellular life processes, GIs were more likely to carry genes related to genetic information and metabolism. Several GIs were identified to carry genes involved in iron oxidation, mercury reduction, and various toxin-antitoxin systems, which enhance the adaptability of the strains to highly acidic environments.
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 | 0.001 | 0.001 |
| 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".