The modification and evaluation of an ELISA test for the surveillance of Mycobacterium avium subsp. paratuberculosis infection in wild ruminants
Bibliographic record
Abstract
BACKGROUND: Enzyme-linked immunosorbent assay (ELISA) is often used to test wildlife samples for Mycobacterium avium subsp. paratuberculosis (MAP) infection. However, commercially available kits are only validated for use with domestic ruminant species. A literature review was performed to document the current use of MAP serum ELISA in wild and semi-domestic ruminants. We then modified and evaluated a commercial ELISA kit (IDEXX Mycobacterium paratuberculosis Antibody Test Kit) for use with species for which it was not originally developed: elk (Cervus elaphus), bison (Bison bison) and caribou (Rangifer tarandus). We tested the affinity of different conjugates for immunoglobulin G (IgG) isolated from these species, performed checkerboard tests to determine the optimal dilutions of samples and conjugates, and established cut-off values using two different methods: a Receiver Operational Curve on a panel of known samples for elk, and an alternate method involving a panel of unknown serum samples for the three species. RESULTS: We found that the anti-bovine conjugate included in the IDEXX ELISA kit has limited affinity for elk, bison, and caribou IgG. Protein G showed good affinity for IgG of all three species, while anti-deer conjugate also bound elk and caribou IgG. Using Protein G with elk serum, a cut-off sample-to-positive (S/P) value of 0.22 was selected, resulting in a sensitivity and specificity of 73% and 90%, respectively, whereas, using an anti-deer conjugate with elk serum, an S/P cut-off value of 0.29 gave a sensitivity of 68%, with 100% specificity. Cut-off values for bison and caribou using the Protein G conjugate were 0.17 and 0.25 respectively. CONCLUSIONS: Due to incomplete reporting and a lack of test validation, it is difficult to critically appraise results of many sero-surveys that have previously been done for MAP in wildlife. Commercial ELISA kits may have limited or no capacity to detect antibodies from species other than for which they were developed. In order to generate reliable test results, it is essential to evaluate the test and perform modifications if deemed necessary. Despite the challenges inherent to wildlife diagnostics, we have shown that several methods can be used to improve confidence in test results.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".