Functional domains of Acinetobacter bacteriophage tail fibers
Bibliographic record
Abstract
A rapid increase in antimicrobial resistant bacterial infections around the world is causing a global health crisis. The Gram-negative bacterium Acinetobacter baumannii is categorized as a Priority 1 pathogen for research and development of new antimicrobials by the World Health Organization due to its numerous intrinsic antibiotic resistance mechanisms and ability to quickly acquire new resistance determinants. Specialized phage enzymes, called depolymerases, degrade the bacterial capsule polysaccharide layer and show therapeutic potential by sensitizing the bacterium to phages, select antibiotics, and serum killing. The functional domains responsible for the capsule degradation activity are often found in the tail fibers of select A. baumannii phages. To further explore the functional domains associated with depolymerase activity, tail-associated proteins of 71 sequenced and fully characterized phages were identified from published literature and analyzed for functional domains using InterProScan. Multisequence alignments and phylogenetic analyses were conducted on the domain groups and assessed in the context of noted halo formation or depolymerase characterization. Proteins derived from phages noted to have halo formation or a functional depolymerase, but no functional domain hits, were modeled with AlphaFold2 Multimer, and compared to other protein models using the DALI server. The domains associated with depolymerase function were pectin lyase-like (SSF51126), tailspike binding (cd20481), (Trans)glycosidases (SSF51445), and potentially SGNH hydrolases. These findings expand our knowledge on phage depolymerases, enabling researchers to better exploit these enzymes for therapeutic use in combating the antimicrobial resistance crisis.
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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 | 0.000 | 0.000 |
| 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".