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Published on: February 4, 2018
Application of hyper-branched rolling circle amplification (HRCA) and HRCA-based strip test for the detection of
Xiaoli Nie1, Chunyun Zhang2, Yuanyuan Wang1
1College of Oceanology, School of Marine Science and Technology, Harbin Institute of Technology at Weihai, Wenhua West Road, 2#, Weihai, 264209, Shandong Province, People's Republic of China.
Abstract:
Harmful algal blooms (HABs) are global threats to marine ecosystems, fisheries, and human health. Therefore, developing effective and accurate methods for identifying causative algae and monitoring seawater quality is urgent. However, traditional, microscopy-based methods are complex, inaccurate, and time-consuming. Here, we present a novel method for effective and sensitive detection of Chattonella marina using hyper-branched rolling circle amplification (HRCA) and HRCA-based strip test (HBST). The large subunit (LSU) ribosomal DNA (rDNA) D1-D2 region of C. marina was firstly sequenced to design a species-specific padlock probe (PLP). The HRCA reaction with two amplification primers and further HBST for C. marina was established. The optimized reaction conditions for HRCA were PLP concentration, 20 pM; ligation temperature, 65 °C; ligation time, 60 min; amplification temperature, 61 °C; and amplification time, 60 min. The developed HBST detection procedure involved HRCA reaction, test strip preparation, hybridization, coloration, and judgment of hybridization by the naked eye. Specificity and sensitivity of the established methods were validated. Moreover, the results showed that the established detection methods were specific and sensitive to C. marina. The detection limits of HRCA and HBST assays were 10 copies and 1 copy μL-1 of plasmid with LSU rDNA of C. marina, which are of two and three respective magnitude orders higher than conventional PCR. Finally, the protocols were applied to the simulated field samples and the results showed that the developed HBST assay had higher detection sensitivity than HRCA and PCR. In conclusion, the methods presented in this study are promising for sensitive, intuitive, and specific detection of C. marina in field monitoring natural samples and may provide a good detection model for other harmful algae in the future.
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