Abstract

BackgroundSpecies adulteration is a concern in herbal products, especially when plant substitutes of lower economic value replace valuable botanicals. Styphnolobium japonicum is well known as a potential adulterant of Ginkgo biloba, which is one of the most demanded medicinal plants due to its wide use in pharmaceuticals, food supplements, and traditional medicine. Despite bearing some resemblance to ginkgo's flavonol composition, S. japonicum lacks many of G. biloba's desired therapeutic properties. To prevent adulteration practices, it is crucial to implement rigorous quality control measures, including fast and simple diagnostic tools that can be used on-field. PurposeThis study aims to develop for the first time a species-specific loop-mediated isothermal amplification (LAMP) method for the fast identification of S. japonicum in ginkgo-containing products. MethodsA set of four specific primers (SjF3, SjB3, SjFIP, and SjBIP) and loop primers (SjLF and SjLB) were designed for a LAMP based assay using the 5.8S partial sequence and the internal transcribed spacer 2 of nuclear ribosomal DNA of S. japonicum. ResultsThe successful amplification of the LAMP assay was inspected through visual detection, with the highest intensity recorded at the optimal conditions set at 68 °C for 40 min. The primers showed high specificity and were able to accurately discriminate S. japonicum from G. biloba and 49 other species of medicinal plants. Furthermore, the proposed LAMP assay proved to be fast, selective, and highly sensitive, as demonstrated by the absolute and relative limits of detection, which were reached at 0.5 pg for S. japonicum DNA and 0.01 % S. japonicum in G. biloba, respectively. ConclusionsThis novel approach allows easy identification and discrimination of S. japonicum as a potential adulterant of G. biloba, thus being a useful tool for quality control. Compared to chromatographic or PCR-based methods, the assay proved to be fast, sensitive and did not require expensive equipment, thus offering the possibly usage in field analysis.

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