A Pan-Genomic Approach to Understand the Basis of Host Adaptation in Achromobacter
Bibliographic record
Abstract
Over the past decade, there has been a rising interest in Achromobacter sp., an emerging opportunistic pathogen responsible for nosocomial and cystic fibrosis lung infections. Species of this genus are ubiquitous in the environment, can outcompete resident microbiota, and are resistant to commonly used disinfectants as well as antibiotics. Nevertheless, the Achromobacter genus suffers from difficulties in diagnosis, unresolved taxonomy and limited understanding of how it adapts to the cystic fibrosis lung, not to mention other host environments. The goals of this first genus-wide comparative genomics study were to clarify the taxonomy of this genus and identify genomic features associated with pathogenicity and host adaptation. This was done with a widely applicable approach based on pan-genome analysis. First, using all publicly available genomes, a combination of phylogenetic analysis based on 1,780 conserved genes with average nucleotide identity and accessory genome composition allowed the identification of a largely clinical lineage composed of Achromobacter xylosoxidans, Achromobacter insuavis, Achromobacter dolens, and Achromobacter ruhlandii. Within this lineage, we identified 35 positively selected genes involved in metabolism, regulation and efflux-mediated antibiotic resistance. Second, resistome analysis showed that this clinical lineage carried additional antibiotic resistance genes compared with other isolates. Finally, we identified putative mobile elements that contribute 53% of the genus's resistome and support horizontal gene transfer between Achromobacter and other ecologically similar genera. This study provides strong phylogenetic and pan-genomic bases to motivate further research on Achromobacter, and contributes to the understanding of opportunistic pathogen evolution.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".