Phylogenetic Distribution and Evolutionary History of Bacterial DEAD-Box Proteins
Bibliographic record
Abstract
DEAD-box proteins are found in all domains of life and participate in almost all cellular processes that involve RNA. The presence of DEAD and Helicase_C conserved domains distinguish these proteins. DEAD-box proteins exhibit RNA-dependent ATPase activity in vitro, and several also show RNA helicase activity. In this study, we analyzed the distribution and architecture of DEAD-box proteins among bacterial genomes to gain insight into the evolutionary pathways that have shaped their history. We identified 1,848 unique DEAD-box proteins from 563 bacterial genomes. Bacterial genomes can possess a single copy DEAD-box gene, or up to 12 copies of the gene, such as in Shewanella. The alignment of 1,208 sequences allowed us to perform a robust analysis of the hallmark motifs of DEAD-box proteins and determine the residues that occur at high frequency, some of which were previously overlooked. Bacterial DEAD-box proteins do not generally contain a conserved C-terminal domain, with the exception of some members that possess a DbpA RNA-binding domain (RBD). Phylogenetic analysis showed a separation of DbpA-RBD-containing and DbpA-RBD-lacking sequences and revealed a group of DEAD-box protein genes that expanded mainly in the Proteobacteria. Analysis of DEAD-box proteins from Firmicutes and γ-Proteobacteria, was used to deduce orthologous relationships of the well-studied DEAD-box proteins from Escherichia coli and Bacillus subtilis. These analyses suggest that DbpA-RBD is an ancestral domain that most likely emerged as a specialized domain of the RNA-dependent ATPases. Moreover, these data revealed numerous events of gene family expansion and reduction following speciation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".