Integrating filter paper extraction, isothermal amplification, and lateral flow dipstick methods to detect Streptococcus agalactiae in milk within 15 min

Author:

Zhu Lingling,Gong Fengju,Liu Xia,Sun Xueqiang,Yu Yong,Shu Jie,Pan Zihao

Abstract

IntroductionMastitis is one of the most serious diseases affecting dairy farming, causing huge economic losses worldwide. Streptococcus agalactiae is the main pathogenic bacterium of contagious mastitis and can deliver a devastating blow to a farm's economy. Rapid detection is the key to disease control.MethodsIn this study, a rapid detection method for S. agalactiae was established. This method combines filter paper extraction, multienzyme isothermal rapid amplification (MIRA), and lateral flow dipsticks (LFD). To simplify the extraction procedure, we designed a disposable extraction device (DED). First, DED performance was evaluated by polymerase chain reaction (PCR) and then the lysis formula and extraction time were optimized. Second, this study compared the extraction performance of a filter paper and an automatic nucleic acid extraction instrument. After screening primers, MIRA for S. agalactiae was established and combined with LFD. Specificity and sensitivity were evaluated after optimizing the reaction conditions.ResultsThe results showed that the lowest extraction line for DED was 0.01–0.001 ng/μl. In the specificity study, 12 different bacteria were tested, and only S. agalactiae was found to be positive. In the sensitivity study, seven dilution gradients were established, and the lowest detection line was 3.52 × 102 CFU/ml.DiscussionIn summary, the method established in this study does not require laboratory equipment and is suitable for on-site detection. The entire method takes only 15 min, is low in cost, has high precision and low technical requirements for operators, which is in contrast with the high cost and cumbersome operation of traditional methods, and is suitable for on-site testing in areas with limited facilities.

Publisher

Frontiers Media SA

Subject

General Veterinary

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