In and out: an analysis of epibiotic vs periplasmic bacterial predators
Bibliographic record
Abstract
Bdellovibrio and like organisms (BALO) are obligate predators of Gram-negative bacteria, belonging to the α- and δ-proteobacteria. BALO prey using either a periplasmic or an epibiotic predatory strategy, but the genetic background underlying these phenotypes is not known. Here we compare the epibiotic Bdellovibrio exovorus and Micavibrio aeruginosavorus to the periplasmic B. bacteriovorus and Bacteriovorax marinus. Electron microscopy showed that M. aeruginosavorus, but not B. exovorus, can attach to prey cells in a non-polar manner through its longitudinal side. Both these predators were resistant to a surprisingly high number of antibiotic compounds, possibly via 26 and 19 antibiotic-resistance genes, respectively, most of them encoding efflux pumps. Comparative genomic analysis of all the BALOs revealed that epibiotic predators have a much smaller genome (ca. 2.5 Mbp) than the periplasmic predators (ca. 3.5 Mbp). Additionally, periplasmic predators have, on average, 888 more proteins, at least 60% more peptidases, and one more rRNA operon. Fifteen and 219 protein families were specific to the epibiotic and the periplasmic predators, respectively, the latter clearly forming the core of the periplasmic 'predatome', which is upregulated during the growth phase. Metabolic deficiencies of epibiotic genomes include the synthesis of inosine, riboflavin, vitamin B6 and the siderophore aerobactin. The phylogeny of the epibiotic predators suggests that they evolved by convergent evolution, with M. aeruginosavorus originating from a non-predatory ancestor while B. exovorus evolved from periplasmic predators by gene loss.
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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 | 0.000 |
| 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".