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Pathovar-Specific PCR Method for Detection and Identification of Xanthomonas translucens pv. undulosa.

Bacterial leaf streak disease caused by Xanthomonas translucens pv. undulosa is an economically important disease threatening wheat and barley crops around the globe. So far, specific PCR-based detection and identification… Click to show full abstract

Bacterial leaf streak disease caused by Xanthomonas translucens pv. undulosa is an economically important disease threatening wheat and barley crops around the globe. So far, specific PCR-based detection and identification tests for X. translucens pathovars are not available. In this study, we used comparative genomics approach to design a pathovar-specific primer pair for detection of X. translucens pv. undulosa in naturally infected seeds and its differentiation from other pathovars of the species. For this aim, complete genome sequences of strains of different X. translucens pathovars were compared and the specific PCR primer pair XtuF/XtuR was designed. These primers were strictly specific to X. translucens pv. undulosa as the expected 229 bp DNA fragment was not amplified in the closely-related pathovars nor in other xanthomonads, wheat pathogenic bacteria, and other plant pathogenic bacteria. High sensitivity of the primer pair XtuF/XtuR allowed detection of pure DNA of the pathogen in a concentration as low as 4.5 pg/µl. The pathogen was also detected in water suspension at a concentration of 8.6 × 102 cfu/ml. The PCR test was capable of detecting the pathogen in extracts of naturally infected wheat seeds at a concentration of 3.5 × 104 cfu/g while culture plate method was able to detect the pathogen at a concentration of 50 × 105 cfu/g of the same seeds. The PCR test developed in this study is a step forward for precise detection and identification of X. translucens pv. undulosa to prevent outbreaks of the bacterial leaf streak disease.

Keywords: translucens undulosa; xanthomonas translucens; detection identification; detection; specific pcr

Journal Title: Plant disease
Year Published: 2023

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