Species-Level Identification of Isolates of the <i>Acinetobacter calcoaceticus</i> - <i>Acinetobacter baumannii</i> Complex by Sequence Analysis of the 16S-23S rRNA Gene Spacer Region
Bibliographic record
Abstract
The species Acinetobacter calcoaceticus, A. baumannii, genomic species 3, and genomic species 13TU included in the Acinetobacter calcoaceticus-Acinetobacter baumannii complex are genetically highly related and difficult to distinguish phenotypically. Except for A. calcoaceticus, they are all important nosocomial species. In the present study, the usefulness of the 16S-23S rRNA gene intergenic spacer (ITS) sequence for the differentiation of (genomic) species in the A. calcoaceticus-A. baumannii complex was evaluated. The ITSs of 11 reference strains of the complex and 17 strains of other (genomic) species of Acinetobacter were sequenced. The ITS lengths (607 to 638 bp) and sequences were highly conserved for strains within the A. calcoaceticus-A. baumannii complex. Intraspecies ITS sequence similarities ranged from 0.99 to 1.0, whereas interspecies similarities varied from 0.86 to 0.92. By using these criteria, 79 clinical isolates identified as A. calcoaceticus (18 isolates) or A. baumannii (61 isolates) with the API 20 NE system (bioMerieux Vitek, Marcy l'Etoile, France) were identified as A. baumannii (46 isolates), genomic species 3 (19 isolates), and genomic species 13TU (11 isolates) by ITS sequencing. An identification rate of 96.2% (76 of 79 isolates) was obtained by using ITS sequence analysis for identification of isolates in the A. calcoaceticus-A. baumannii complex, and the accuracy of the method was confirmed for a subset of strains by amplified rRNA gene restriction analysis and genomic DNA analysis by AFLP analysis by using libraries of profiles of reference strains. In conclusion, ITS sequence-based identification is reliable and provides a promising tool for elucidation of the clinical significance of the different species of the A. calcoaceticus-A. baumannii complex.
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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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".