Evaluation of a PCR assay on overgrown environmental samples cultured for Mycobacterium avium subsp. paratuberculosis

Autor: Juan Carlos Arango-Sabogal, J M Fairbrother, Olivia Labrecque, Julie Paré, Jean-Philippe Roy, Vincent Wellemans, Gilles Fecteau
Rok vydání: 2016
Předmět:
Zdroj: Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc. 28(6)
ISSN: 1943-4936
Popis: Culture of Mycobacterium avium subsp. paratuberculosis (MAP) is the definitive antemortem test method for paratuberculosis. Microbial overgrowth is a challenge for MAP culture, as it complicates, delays, and increases the cost of the process. Additionally, herd status determination is impeded when noninterpretable (NI) results are obtained. The performance of PCR is comparable to fecal culture, thus it may be a complementary detection tool to classify NI samples. Our study aimed to determine if MAP DNA can be identified by PCR performed on NI environmental samples and to evaluate the performance of PCR before and after the culture of these samples in liquid media. A total of 154 environmental samples (62 NI, 62 negative, and 30 positive) were analyzed by PCR before being incubated in an automated system. Growth was confirmed by acid-fast bacilli stain and then the same PCR method was again applied on incubated samples, regardless of culture and stain results. Change in MAP DNA after incubation was assessed by converting the PCR quantification cycle (Cq) values into fold change using the 2−ΔCqmethod (ΔCq = Cq after culture − Cq before culture). A total of 1.6% (standard error [SE] = 1.6) of the NI environmental samples had detectable MAP DNA. The PCR had a significantly better performance when applied after culture than before culture ( p = 0.004). After culture, a 66-fold change (SE = 17.1) in MAP DNA was observed on average. Performing a PCR on NI samples improves MAP culturing. The PCR method used in our study is a reliable and consistent method to classify NI environmental samples.
Databáze: OpenAIRE