Monoclonal Antibodies Recognizing the Surface Autolysin IspC of Listeria monocytogenes Serotype 4b: Epitope Localization, Kinetic Characterization, and Cross-Reaction Studies
Bibliographic record
Abstract
Listeria monocytogenes serotype 4b is responsible for a high percentage of fatal cases of food-borne infection. In a previous study, we created 15 monoclonal antibodies (MAbs) against a ≈ 77 kDa antigen that is associated with the cell surface of live L. monocytogenes serotype 4b cells. Here we report an extensive characterization of these MAbs to further their development as diagnostic reagents. The ≈ 77 kDa target antigen was identified by mass spectrometry and N-terminal sequencing to be IspC, a novel surface associated autolysin. Epitope localization experiments revealed that each of the 15 MAbs recognized the C-terminal cell-wall binding domain of IspC. The presence of IspC was shown to be highly conserved within L. monocytogenes serotype 4b, as evidenced by a strong reaction between anti-IspC MAbs and all 4b isolates. To determine the range of cross-reactivity with other L. monocytogenes serotypes ELISA was used to test each MAb against multiple isolates from each of the L. monocytogenes serotypes. Of the 15 MAbs, five: M2774, M2775, M2780, M2790 and M2797, showed specificity for L. monocytogenes serotype 4b and only cross reacted with serotype 4ab isolates. The kinetics of the interaction between each of the MAbs and IspC was measured using surface plasmon resonance. The MAbs M2773, M2792, M2775, M2797 and M2781 each had very low dissociation constants (4.5 × 10(-9) to 1.2 × 10(-8) M). While several of these antibodies have properties which could be useful in diagnostic tests, the combined high fidelity and affinity of M2775 for the IspC protein and serotype 4b isolates, makes it a particularly promising candidate for use in the development of a specific L. monocytogenes serotype 4b diagnostic test.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".