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Variation in the Performance of Different Batches of Two Mycobacterium avium Subspecies paratuberculosis Antibody ELISAs Used for Pooled Milk Samples

SIMPLE SUMMARY: This article explores variation in the performance of different batches of tests for the detection of antibodies against the ruminant pathogen Mycobacterium avium subspecies paratuberculosis (MAP) in milk. The results indicate that variation is present and that it has sources mainly...

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Detalles Bibliográficos
Autores principales: Köhler, Heike, Wichert, Annika, Donat, Karsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8868366/
https://www.ncbi.nlm.nih.gov/pubmed/35203150
http://dx.doi.org/10.3390/ani12040442
Descripción
Sumario:SIMPLE SUMMARY: This article explores variation in the performance of different batches of tests for the detection of antibodies against the ruminant pathogen Mycobacterium avium subspecies paratuberculosis (MAP) in milk. The results indicate that variation is present and that it has sources mainly in the manufacturing process of the test kits and, to a lesser degree, in the test laboratories. ABSTRACT: Regionally, the monitoring of paratuberculosis at the herd level is performed by the detection of specific antibodies in pooled milk samples by ELISA. The negative/positive cut-off S/P values applied for pooled milk samples are low and particularly vulnerable to variation in the test performance. In this study, a batch variation in the test performance of two ELISA tests was assessed to identify consequences for sample classification. A total of 72 pooled milk samples (50 from MAP-infected herds, 22 from one MAP-non-infected herd) were analyzed using three different batches, each of two different MAP antibody ELISA tests (A and B). Receiver operating characteristic (ROC) analysis was performed, with the results of each batch, S/P values of the samples and optical density (OD) readings of the negative and positive control samples included in the kits being compared between the batches of one test. ROC analysis revealed a considerable variation in the test performance of the batches of the two individual tests, caused by differences in the S/P values of the samples and resulting in different sensitivities at a specificity of 100%. Major sources of variation originate from the manufacturing processes of test batches. These sources have to be better controlled, and the test performance has to be revisited regularly.