The phylogeny of proteobacteria: relationships to other eubacterial phyla and eukaryotes
Bibliographic record
Abstract
The evolutionary relationships of proteobacteria, which comprise the largest and phenotypically most diverse division among prokaryotes, are examined based on the analyses of available molecular sequence data. Sequence alignments of different proteins have led to the identification of numerous conserved inserts and deletions (referred to as signature sequences), which either are unique characteristics of various proteobacterial species or are shared by only members from certain subdivisions of proteobacteria. These signature sequences provide molecular means to define the proteobacterial phyla and their various subdivisions and to understand their evolutionary relationships to the other groups of eubacteria as well as the eukaryotes. Based on signature sequences that are present in different proteins it is now possible to infer that the various eubacterial phyla evolved from a common ancestor in the following order: low-G+C Gram-positive-->high-G+C Gram-positive-->Deinococcus-Thermus (green nonsulfur bacteria)-->cyanobacteria-->Spirochetes-->Chlamydia-Cytophaga-Aquifex -green sulfur bacteria-->Proteobacteria-1 (epsilon and delta)-->Proteobacteria-2 (alpha)-->Proteobacteria-3 (beta)-->Proteobacteria-4 (gamma). An unexpected but important aspect of the relationship deduced here is that the main eubacterial phyla are related to each other linearly rather than in a tree-like manner, suggesting that the major evolutionary changes within Bacteria have taken place in a directional manner. The identified signatures permit placement of prokaryotes into different groups/divisions and could be used for determinative purposes. These signatures generally support the origin of mitochondria from an alpha-proteobacterium and provide evidence that the nuclear cytosolic homologs of many genes are also derived from proteobacteria.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".