Background: Although there has been some success using DNA barcoding to authenticate raw natural health product (NHP) botanical ingredients, there are many gaps in our understanding of DNA degradation, which may explain low PCR and sequencing success in processed NHPs. Objective: In this study, we measured multiple DNA variables after each step in the processing of a green tea extract in order to document DNA quality and quantity. Methods: We sampled plant material after each step of green tea extract processing: five steps at a Chinese tea farm (n = 10) and five at an NHP processing facility (n = 3). We hypothesized that processing treatments degrade and remove DNA from NHPs, reflected by decreasing quantities of extractable genomic DNA (gDNA), an increasing proportion of small DNA fragments in genomic extracts, and decreasing quantitative PCR (QPCR) efficiency [higher cycle threshold (Ct) values]. DNA from end-production green tea extract was sequenced in order to try to validate material as the botanical of interest. Results: We saw a 41.1% decrease in mean extractable gDNA through farm processing (P < 0.01) and a 99.7% decrease through facility processing (P < 0.05). There was a 26.3% decrease in mean DNA fragment size through farm processing (P < 0.001) and an 82.0% decrease through facility processing (P < 0.05). QPCR efficiency was reduced through processing, marked by significant increases in Ct values with 100 base pair (bp) and 200 bp PCR targets (P < 0.05), and an inability to amplify 300 bp targets when using DNA template from end-production green tea extract. Conclusions: Although there was significant degradation and removal of DNA through processing, sufficiently intact DNA was able to be recovered from highly processed green tea extract for further sequencing and identification. Highlights: This work addresses a key gap in the understanding of DNA degradation through processing and provides useful information to consider when designing molecular diagnostic techniques for NHP identification.
Background: Although there has been some success using DNA barcoding to authenticate raw natural health product (NHP) botanical ingredients, there are many gaps in our understanding of DNA degradation, which may explain low PCR and sequencing success in processed NHPs. Objective: In this study, we measured multiple DNA variables after each step in the processing of a green tea extract in order to document DNA quality and quantity. Methods: We sampled plant material after each step of green tea extract processing: five steps at a Chinese tea farm (n = 10) and five at an NHP processing facility (n = 3). We hypothesized that processing treatments degrade and remove DNA from NHPs, reflected by decreasing quantities of extractable genomic DNA (gDNA), an increasing proportion of small DNA fragments in genomic extracts, and decreasing quantitative PCR (QPCR) efficiency [higher cycle threshold (Ct) values]. DNA from end-production green tea extract was sequenced in order to try to validate material as the botanical of interest. Results: We saw a 41.1% decrease in mean extractable gDNA through farm processing (P < 0.01) and a 99.7% decrease through facility processing (P < 0.05). There was a 26.3% decrease in mean DNA fragment size through farm processing (P < 0.001) and an 82.0% decrease through facility processing (P < 0.05). QPCR efficiency was reduced through processing, marked by significant increases in Ct values with 100 base pair (bp) and 200 bp PCR targets (P < 0.05), and an inability to amplify 300 bp targets when using DNA template from end-production green tea extract. Conclusions: Although there was significant degradation and removal of DNA through processing, sufficiently intact DNA was able to be recovered from highly processed green tea extract for further sequencing and identification. Highlights: This work addresses a key gap in the understanding of DNA degradation through processing and provides useful information to consider when designing molecular diagnostic techniques for NHP identification.
Authors: Adam C Faller; Dhivya Shanmughanandhan; Subramanyam Ragupathy; Yanjun Zhang; Zhengfei Lu; Peter Chang; Gary Swanson; Steven G Newmaster Journal: Front Plant Sci Date: 2021-05-24 Impact factor: 5.753