High-throughput detection and screening of biological ingredients in
Shenling Baizhu San by shotgun metabarcoding
Abstract
High-throughput detection and screening of biological ingredients in a
single bulk sample containing a wide range of taxa still have
considerable problems. Recently, a new approach named “shotgun
metabarcoding” combining shotgun sequencing and multiple barcodes has
been proposed. Here, Shenling Baizhu San (SLBZS), a traditional patent
medicine composed of ten plant and fungus ingredients was used to test
its species detection capability. Mock and pharmaceutical samples of
SLBZS were collected, and a total of 39.52 Gb of raw data were obtained
via PCR-free shotgun sequencing. All ingredients made for mock samples
can be successfully re-detected except Coix lacryma-jobi was failed to
be detected in the second mock sample, and the positive control, the
roots of Panax quinquefolius, can be re-detected in the second mock
sample. For pharmaceutical samples, not only labeled ingredients but
also adulterants, e.g. P. quinquefolius, were detected in a sample. The
presence of P. quinquefolius was verified using the SNP detection method
with a pair of Panax specific primers. In addition, 18 genera of fungal
species were detected in both mock and pharmaceutical samples, however,
the total number of fungal reads was relatively small. As a result, this
study confirmed that shotgun metabarcoding could authenticate all the
biological ingredients of SLBZS, has the potential to enable genomic
analyses ideally of all species a single bulk sample.