Mass Spectrometry–Based Escherichia coli H Antigen/Flagella Typing: Validation and Comparison with Traditional Serotyping
Bibliographic record
Abstract
BACKGROUND: Escherichia coli H antigen typing with antisera, a useful method for flagella clinical identification and classification, is a time-consuming process because of the need to induce flagella growth and the occurrence of undetermined strains. We developed an alternative rapid and analytically sensitive mass spectrometry (MS) method, termed MS-based H antigen typing (MS-H), and applied it at the protein sequence level for H antigen typing. We also performed a comparison with traditional serotyping on reference strains and clinical isolates. METHODS: On the basis of international guidelines, the analytical selectivity and sensitivity, imprecision, correlation, repeatability, and reproducibility of the MS-H platform was evaluated using reference strains. Comparison of MS-H typing and serotyping was performed using 302 clinical isolates from 5 Canadian provinces, and discrepant results between the 2 platforms were resolved through whole genome sequencing. RESULTS: Repeated tests on reference strain EDL933 demonstrated a lower limit of the measuring interval at the subsingle colony (16.97 μg or 1.465 × 10(7) cells) level and close correlation (r(2) > 0.99) between cell culture biomass and sequence coverage. The CV was <10.0% among multiple repeats with 4 reference strains. Intra- and interlaboratory tests demonstrated that the MS-H method was robust and reproducible under various sample preparation and instrumentation conditions. Using discrepancy analysis via whole genome sequencing, performed on isolates with discrepant results, MS-H accurately identified 12.3% more isolates than conventional serotyping. CONCLUSIONS: MS-H typing of E. coli is useful for fast and accurate flagella typing and could be very useful during E. coli outbreaks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".