Development and validation of main spectral profile for rapid identification of Yersinia ruckeri isolated from Atlantic salmon using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry
Bibliographic record
Abstract
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) allows rapid and reliable identification of microorganisms. The accuracy of bacterial identification using MALDI-TOF MS depends on main spectral profiles (MSPs) provided in a quality-assured commercial reference library, which requires ongoing improvement. This study aimed to develop and validate an in-house MALDI-TOF MS MSP to rapidly identify Yersinia ruckeri isolated from Atlantic salmon ( Salmo salar ). The novel MSP was prepared using an isolate of Y. ruckeri recovered from Atlantic salmon and confirmed by 16S rRNA gene sequencing. Subsequently, a validation set which comprises 29 isolates of Y. ruckeri were examined from three fishes: Atlantic salmon ( Salmo salar ) ( n = 26), American eel ( Anguilla rostrata ) ( n = 1), and Atlantic cod ( Gadus morhua ) ( n = 2). These isolates were randomly selected from the Atlantic Veterinary College, Aquatic Diagnostic Services Bacteriology Laboratory's culture collection to validate the novel MSP. Analytical sensitivity of MALDI-TOF MS using the novel MSP to identify the validation set was 86.2%. Repeatability was assessed by acquiring spectra from 30 different spots of a randomly-selected isolate of Y. ruckeri , and analyzed spectra from each spot were compared against the novel MSP. The coefficient of variation was 3.3%. The novel MSP clustered with Bruker MSPs ( n = 3) of Y. ruckeri in the reference library and did not falsely identify any closely related bacteria to Y. ruckeri . This study reports the development of a novel MSP of high analytical sensitivity and specificity for rapid identification of Y. ruckeri using MALDI-TOF MS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".