Analysis of fungal diversity on the surface of Armeniacae Semen Amarum using a DNA metabarcoding technique
10.16438/j.0513-4870.2021-0119
- VernacularTitle:基于DNA宏条形码技术的中药材苦杏仁表面真菌多样性研究
- Author:
Meng-yue GUO
1
,
2
;
Jing-sheng YU
1
,
2
;
Wen-jun JIANG
1
,
2
;
Xiao-hui PANG
1
,
2
Author Information
1. Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China
2. Engineering Research Center of Chinese Medicine Resources, Ministry of Education, Beijing 100193, China
- Publication Type:Research Article
- Keywords:
Armeniacae Semen Amarum;
DNA metabarcoding;
high-throughput sequencing;
fungal diversity;
ITS2
- From:
Acta Pharmaceutica Sinica
2021;56(8):2295-2301
- CountryChina
- Language:Chinese
-
Abstract:
Medicinal and edible Armeniacae Semen Amarum (ASA) is susceptible to fungal contamination because it is rich in oil and other nutrients. In this study, the fungal community diversity in ASA samples was analyzed based on a DNA metabarcoding technique to provide evidence for its safe use. Twelve batches of ASA samples samples from four medicinal material markets and three processing approaches were collected. Total DNA was extracted, the ITS2 sequences were amplified, and high-throughput sequencing was performed using the Illumina MiSeq PE300 platform. The results show that Ascomycota was the most dominant fungus in ASA samples. The predominant genus in sample SW1_P was Diutina, whereas the most predominant genus in the other samples was Aspergillus. Three harmful fungi were identified, namely, Aspergillus flavus, Wallemia sebi, and Rhizopus arrhizus. In addition, significant differences were observed in the relative abundance of Botryosphaeriales and Alternaria in ASA samples from different collection sites. Meanwhile, there were significant differences in the relative abundance of Hypocreales and Cladosporium in ASA samples from different processing approaches. In summary, the DNA metabarcoding technique can effectively clarify the fungal community diversity and quickly detect potential toxigenic fungi in ASA samples, thus providing a warning for mycotoxin contamination.
