Proteomic approaches to early diagnosis of Johne’s disease in dairy cows
Bibliographic record
Abstract
Mycobacterium avium subsp. paratuberculosis (MAP) is the etiological agent of paratuberculosis or Johne’s disease (JD), an infectious, chronic granulomatous enteritis of ruminants. Current diagnostic tests for JD have limited sensitivity and specificity for the identification of subclinically infected animals warranting an investigation of MAP species-specific and sensitive antigens that might improve diagnostic test sensitivity and specificity. The aim of the first study was to identify antigenic proteins from the MAP cell envelope by comparing protein profiles from MAP, Mycobacterium avium subspecies hominissuis and M. smegmatis using a 2D-DIGE proteomic approach. Thirteen protein spots were selected and 15 proteins were subsequently identified by LC-MS/MS. The aim of the second study was to generate antibodies to recombinantly expressed MAP cell envelope proteins as well as to an extract of MAP total cell envelope proteins that was subsequently used to identify MAP organisms by IHC and immunomagnetic separation. Six MAP cell envelope proteins were recombinantly expressed, three of which were suitable for polyclonal antibody generation. Polyclonal antibodies generated to an extract of MAP cell envelope proteins detected MAP organisms in infected tissues using IHC and IF techniques thereby providing a more sensitive alternative to acid-fast staining of MAP in tissues for JD diagnosis. Furthermore, these antibodies were effective in immunomagnetic capture of MAP microorganisms in solution thereby providing proof-in-principle for a novel diagnostic approach. The objective of third study was to use an extract of MAP total cell envelope proteins as well as the six recombinant MAP proteins in ELISA formats to detect MAP-specific antibodies in cattle serum. The diagnostic sensitivity and specificity of the MAP envelope protein ELISA after serum absorption was 75% and 96% respectively. While ELISAs using the six recombinant protein antigens had reasonably high sensitivities, specificities were comparatively less than the commercial serum ELISA kit. The potential use of these recombinant proteins ELISAs for diagnosis of early MAP infection and control of JD requires further investigation and validation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".