Chromids Aid Genome Expansion and Functional Diversification in the Family <i>Burkholderiaceae</i>
Bibliographic record
Abstract
Multipartite genomes, containing at least two large replicons, are found in diverse bacteria; however, the advantage of this genome structure remains incompletely understood. Here, we perform comparative genomics of hundreds of finished β-proteobacterial genomes to gain insights into the role and emergence of multipartite genomes. Almost all essential secondary replicons (chromids) of the β-proteobacteria are found in the family Burkholderiaceae. These replicons arose from just two plasmid acquisition events, and they were likely stabilized early in their evolution by the presence of core genes. On average, Burkholderiaceae genera with multipartite genomes had a larger total genome size, but smaller chromosome, than genera without secondary replicons. Pangenome-level functional enrichment analyses suggested that interreplicon functional biases are partially driven by the enrichment of secondary replicons in the accessory pangenome fraction. Nevertheless, the small overlap in orthologous groups present in each replicon's pangenome indicated a clear functional separation of the replicons. Chromids appeared biased to environmental adaptation, as the functional categories enriched on chromids were also overrepresented on the chromosomes of the environmental genera (Paraburkholderia and Cupriavidus) compared with the pathogenic genera (Burkholderia and Ralstonia). Using ancestral state reconstruction, it was predicted that the rate of accumulation of modern-day genes by chromids was more rapid than the rate of gene accumulation by the chromosomes. Overall, the data are consistent with a model where the primary advantage of secondary replicons is in facilitating increased rates of gene acquisition through horizontal gene transfer, consequently resulting in replicons enriched in genes associated with adaptation to novel environments.
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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 | 0.001 | 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".