High throughput test method for tomato bacterial disease by locking-type probe

Abstract

The present invention relates to a high-throughput detection method for tomato bacterial diseases, and more particularly to a high-throughput detection method for reverse dot hybridization of tomato bacterial wilt pathogen, tomato canker pathogen and tomato spot disease using padlock probes , belonging to the category of crop disease prevention and treatment and entry-exit plant quarantine. The present invention is based on the rolling circle amplification technology of padlock probes, amplifies a variety of pathogens with a pair of universal primers, and then combines it with the reverse dot hybridization technology to judge the results through color reaction, which can shorten the traditional tomato The detection time of bacterial diseases ensures the specificity and sensitivity of detection, and realizes high-throughput detection. Moreover, this method can shorten the cycle of traditional pathogen detection and improve the speed of customs clearance. This is of great significance for improving the interception and detection rate of imported bulk agricultural products, improving the ability to prevent the invasion of foreign harmful organisms, speeding up the customs clearance of import and export goods at my country's ports, and reducing enterprise costs.

Description

technical field [0001] The present invention relates to a high-throughput detection method for tomato bacterial diseases, and more particularly to a high-throughput detection method for reverse dot hybridization of tomato bacterial wilt pathogen, tomato canker pathogen and tomato spot disease using padlock probes , belonging to the category of crop disease prevention and treatment and entry-exit plant quarantine. Background technique [0002] Tomato bacterial canker, tomato bacterial spot and tomato bacterial wilt are three important diseases in tomato production. The pathogenic bacteria responsible for these diseases are Clavibacter michiganensis subsp. michiganensis (hereinafter referred to as CMM), Pseudomonas syringae .pv. Tomatoes (hereinafter referred to as PST), Ralstonia solanacearum Race1 (hereinafter referred to as RS1). These diseases mainly affect tomato economic crops, causing serious economic losses, and are the most difficult bacterial diseases of t...

AI Technical Summary

Problems solved by technology

Traditional methods for detecting and identifying pathogens include pathogen isolation, purification, biochemical detection, serological identification, and pathogenicity detection[4], etc., but these methods have low sensitivity and lack of specificity. Long time [5], and it is difficult to detect a large number of samples in a short time

In addition, there are many other identification methods, but there are also certain defects.

For example, the method of identifying P. syringae.pv. Tomato, that is, the radioactive hybridization of bacterial clones in a semi-selective medium, but it is limited by the toxin produced by the strain [6]

Conventional PCR cannot perform accurate quantitative analysis[7], although Real-time PCR can quantitatively detect many pathogenic microorganisms and viruses[8-9], but often There will be false positive results

Moreover, all these methods cannot achieve the purpose of detecting multiple diseases in the same system.

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