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Wang X, Hu D, Liao F, Chen S, Meng Y, Dai J, Dong TTX, Lao Z, Yu L, Liang Y, Lai X, Tsim KWK, Li G. Comparative proteomic analysis of edible bird's nest from different origins. Sci Rep 2023; 13:15859. [PMID: 37739981 PMCID: PMC10516954 DOI: 10.1038/s41598-023-41851-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 08/31/2023] [Indexed: 09/24/2023] Open
Abstract
Edible bird's nest (EBN) mainly made of saliva that secreted by a variety of swiftlets is a kind of precious traditional Chinese medicine. EBNs from different biological and geographical origins exhibit varieties in morphology, material composition, nutritive value and commercial value. Here, we collected four different EBN samples from Huaiji, China (Grass EBN), Nha Trang, Vietnam (Imperial EBN) and East Kalimantan, Indonesia (White EBN and Feather EBN) respectively, and applied label-free quantitative MS-based proteomics technique to identify its protein composition. First, phylogenetic analysis was performed based on cytb gene to identify its biological origin. Second, a total of 37 proteins of EBNs were identified, among which there were six common proteins that detected in all samples and exhibited relatively higher content. Gene ontology analysis revealed the possible function of EBN proteins, and principal component analysis and hierarchical clustering analysis based on 37 proteins were performed to compare the difference of various EBNs. In summary, our study deciphered the common and characteristic protein components of EBNs of different origins and described their possible functions by GO enrichment analysis, which helps to establish an objective and reliable quality evaluation system.
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Affiliation(s)
- Xianyang Wang
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Dingwen Hu
- College of Life Science, Wuhan University, Wuhan, China
| | - Feng Liao
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Sitai Chen
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Guangzhou University of Chinese Medicine, Guangzhou, China
| | | | - Jie Dai
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Tina Ting Xia Dong
- Division of Life Science and Center for Chinese Medicine, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Zizhao Lao
- Mathematical Engineering Academy of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Liangwen Yu
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Guangzhou University of Chinese Medicine, Guangzhou, China
| | | | - Xiaoping Lai
- Mathematical Engineering Academy of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China.
| | - Karl Wah Keung Tsim
- Division of Life Science and Center for Chinese Medicine, The Hong Kong University of Science and Technology, Hong Kong, China.
| | - Geng Li
- State Key Laboratory of Traditional Chinese Medicine Syndrome, Guangzhou University of Chinese Medicine, Guangzhou, China.
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