Three novel multiplex PCR assays for rapid detection of virulence, antimicrobial resistance, and toxin genes in <i>Acinetobacter calcoaceticus-baumannii</i> complex species
Bibliographic record
Abstract
The Acinetobacter calcoaceticus-baumannii (ACB) complex is an often-overlooked group of nosocomial pathogens with a significant environmental presence. Rapid molecular screening methods for virulence, antimicrobial resistance, and toxin (VAT) genes are required to investigate the potential pathogenicity of environmental isolates. This study aimed to develop and apply novel ACB complex-specific multiplex PCR (mPCR) primers and protocols for the rapid detection of eight VAT genes. We optimized three single-tube mPCR assays using reference DNA from ACB complex and other Acinetobacter species. These assays were then applied to detect VAT genes in cultured ACB complex isolates recovered from clinical and environmental sources. Widespread detection of VAT genes in environmental isolates confirmed the validity, functionality, and applicability of these novel assays. Overall, the three newly developed ACB complex species-specific mPCR assays are rapid and simple tools that can be adopted in diagnostic and clinical lab settings. The detection of VAT genes in environmental isolates suggests that environmental niches could serve as a reservoir for potentially pathogenic ACB complex and warrants further investigation. The newly developed mPCR assays are specific, sensitive, and efficient, making them well-suited for high-throughput screening in epidemiological studies and evaluating the potential pathogenicity of ACB complex recovered from various sources.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".