The influence of environmental adaptation on bacterial genome structure
Bibliographic record
Abstract
AIMS: Researchers have long been puzzled by the diversity of life. Now that the complete genomic sequence of many organisms has been determined, it is possible to evaluate the impact of organismal variation on sequence structure or vice versa. The aim of this investigation was to explore genomic changes mandated by organismal adaptation to its ecological niches. METHODS AND RESULTS: Coding sequences from three phylogenetically related bacterial species namely Mycoplasma genitalium, M. pneumoniae and Ureaplasma urealyticum were subject to in depth sequence analyses. M. genitalium and M. pneumoniae both belong to the genus Mycoplasma while U. urealyticum is a member of the genus Ureaplasma. However, M. genitalium and U. urealyticum are urogenital pathogens while M. pneumoniae is a respiratory pathogen. Complete transcriptomes were downloaded from NCBI for each species, and were subject to in silico investigation using in-house software, and public sequence analysis tools. Clear similarities in transcriptome structure were identified among the functionally similar species M. genitalium and U. urealyticum while no such relationship was identified among the phylogenetically related species M. genitalium and M. pneumoniae. CONCLUSIONS: It is plausible to conclude that, in these bacterial species, environmental stimuli might be more influential in shaping sequence signatures than phylogenetic relationships. SIGNIFICANCE AND IMPACT OF THE STUDY: This study suggests that molecular signatures within the transcriptomes of the species examined are likely to be a product of evolutionary adaptation to diverse environmental ecological stimuli, and not a result of common phylogeny.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".