Roseobacters in a Sea of Poly- and Paraphyly: Whole Genome-Based Taxonomy of the Family Rhodobacteraceae and the Proposal for the Split of the “Roseobacter Clade” Into a Novel Family, Roseobacteraceae fam. nov.
Why this work is in the frame
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Bibliographic record
Abstract
The family Rhodobacteraceae consists of alphaproteobacteria that are metabolically, phenotypically, and ecologically diverse. It includes the roseobacter clade, an informal designation, representing one of the most abundant groups of marine bacteria. The rapid pace of discovery of novel roseobacters in the last three decades meant that the best practice for taxonomic classification, a polyphasic approach utilizing phenotypic, genotypic, and phylogenetic characteristics, was not always followed. Early efforts for classification relied heavily on 16S rRNA gene sequence similarity and resulted in numerous taxonomic inconsistencies, with several poly- and paraphyletic genera within this family. Next-generation sequencing technologies have allowed whole-genome sequences to be obtained for most type strains, making a revision of their taxonomy possible. In this study, we performed whole-genome phylogenetic and genotypic analyses combined with a meta-analysis of phenotypic data to review taxonomic classifications of 331 type strains (under 119 genera) within the Rhodobacteraceae family. Representatives of the roseobacter clade not only have different environmental adaptions from other Rhodobacteraceae isolates but were also found to be distinct based on genomic, phylogenetic, and in silico -predicted phenotypic data. As such, we propose to move this group of bacteria into a new family, Roseobacteraceae fam. nov. In total, reclassifications resulted to 327 species and 128 genera, suggesting that misidentification is more problematic at the genus than species level. By resolving taxonomic inconsistencies of type strains within this family, we have established a set of coherent criteria based on whole-genome-based analyses that will help guide future taxonomic efforts and prevent the propagation of errors.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it