Have a personal or library account? Click to login
A novel, rapid, and simple PMA-qPCR method for detection and counting of viable Brucella organisms Cover

A novel, rapid, and simple PMA-qPCR method for detection and counting of viable Brucella organisms

Open Access
|May 2020

Abstract

Introduction

The plate counting method widely used at present to discern viable from non-viable Brucella in the host or cell is time-consuming and laborious. Therefore, it is necessary to establish a rapid, simple method for detecting and counting viable Brucella organisms.

Material and Methods

Using propidium monoazide (PMA) to inhibit amplification of DNA from dead Brucella, a novel, rapid PMA-quantitative PCR (PMA-qPCR) detection method for counting viable Brucella was established. The standard recombinant plasmid with the target BCSP31 gene fragment inserted was constructed for drawing a standard curve. The reaction conditions were optimised, and the sensitivity, specificity, and repeatability were analysed.

Results

The optimal exposure time and working concentration of PMA were 10 min and 15 μg/mL, respectively. The correlation coefficient (R2) of the standard curve was 0.999. The sensitivity of the method was 103 CFU/mL, moreover, its specificity and repeatability also met the requirements. The concentration of B. suis measured by the PMA-qPCR did not differ significantly from that measured by the plate counting method, and the concentrations of viable bacteria in infected cells determined by the two methods were of the same order of magnitude.

Conclusion

In this study, a rapid and simple PMA-qPCR counting method for viable Brucella was established, which will facilitate related research.

Language: English
Page range: 253 - 261
Submitted on: Sep 19, 2019
Accepted on: Apr 28, 2020
Published on: May 12, 2020
Published by: National Veterinary Research Institute in Pulawy
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2020 Shi-Jun Zhang, Lu-Lu Wang, Shi-Ying Lu, Pan Hu, Yan-Song Li, Ying Zhang, Heng-Zhen Chang, Fei-Fei Zhai, Zeng-Shan Liu, Zhao-Hui Li, Hong-Lin Ren, published by National Veterinary Research Institute in Pulawy
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.