GC-MS Fingerprinting Combined with Chemical Pattern-Recognition Analysis Reveals Novel Chemical Markers of the Medicinal Seahorse

Seahorse is a valuable marine-animal drug widely used in traditional Chinese medicine (TCM), and which was first documented in the “Ben Cao Jing Ji Zhu” during the Liang Dynasty. <i>Hippocampus kelloggi</i> (HK) is the most common seahorse species in the medicinal material market and is...

Full description

Bibliographic Details
Main Authors: Yuanyuan Jiang, Hongfei Wu, Paul Chi Lui Ho, Xuemei Tang, Hui Ao, Lu Chen, Jinjin Cai
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Molecules
Subjects:
Online Access:https://www.mdpi.com/1420-3049/28/23/7824
_version_ 1797399800325341184
author Yuanyuan Jiang
Hongfei Wu
Paul Chi Lui Ho
Xuemei Tang
Hui Ao
Lu Chen
Jinjin Cai
author_facet Yuanyuan Jiang
Hongfei Wu
Paul Chi Lui Ho
Xuemei Tang
Hui Ao
Lu Chen
Jinjin Cai
author_sort Yuanyuan Jiang
collection DOAJ
description Seahorse is a valuable marine-animal drug widely used in traditional Chinese medicine (TCM), and which was first documented in the “Ben Cao Jing Ji Zhu” during the Liang Dynasty. <i>Hippocampus kelloggi</i> (HK) is the most common seahorse species in the medicinal material market and is one of the genuine sources of medicinal seahorse documented in the Chinese pharmacopeia. It is mainly cultivated in the Shandong, Fujian, and Guangxi Provinces in China. However, pseudo-HK, represented by <i>Hippocampus ingens</i> (HI) due to its similar appearance and traits, is often found in the market, compromising the safety and efficacy of clinical use. Currently, there is a lack of reliable methods for identifying these species based on their chemical composition. In this study, we employed, for the first time, a strategy combining gas chromatography-mass spectrometry (GC-MS) fingerprints and chemical patterns in order to identify HK and HI; it is also the first metabolomic study to date of HI as to chemical components. The obtained results revealed remarkable similarities in the chemical fingerprints, while significant differences were also observed. By employing hierarchical cluster analysis (HCA) and principal component analysis (PCA), based on the relative contents of their characteristic peaks, all 34 samples were successfully differentiated according to their species of origin, with samples from the same species forming distinct clusters. Moreover, nonadecanoic acid and behenic acid were exclusively detected in HK samples, further distinguishing them from HI samples. Additionally, the relative contents of lauric acid, tetradecanoic acid, pentadecanoic acid, n-hexadecanoic acid, palmitoleic acid, margaric acid, oleic acid, fenozan acid, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) exhibited significant differences between HK and HI (<i>p</i> < 0.0001), as determined by an unpaired <i>t</i>-test. Orthogonal partial least squares discriminant analysis (OPLS-DA) identified seven components (DHA, EPA, n-hexadecanoic acid, tetradecanoic acid, palmitoleic acid, octadecanoic acid, and margaric acid) with high discriminatory value (VIP value > 1). Thus, nonadecanoic acid, behenic acid, and these seven compounds can be utilized as chemical markers for distinguishing HK from HI. In conclusion, our study successfully developed a combined strategy of GC-MS fingerprinting and chemical pattern recognition for the identification of HK and HI, and we also discovered chemical markers that can directly differentiate between the two species. This study can provide a foundation for the authentication of Hippocampus and holds significant importance for the conservation of wild seahorse resources.
first_indexed 2024-03-09T01:46:21Z
format Article
id doaj.art-d16296e84b014c3f93e4558362261816
institution Directory Open Access Journal
issn 1420-3049
language English
last_indexed 2024-03-09T01:46:21Z
publishDate 2023-11-01
publisher MDPI AG
record_format Article
series Molecules
spelling doaj.art-d16296e84b014c3f93e45583622618162023-12-08T15:22:27ZengMDPI AGMolecules1420-30492023-11-012823782410.3390/molecules28237824GC-MS Fingerprinting Combined with Chemical Pattern-Recognition Analysis Reveals Novel Chemical Markers of the Medicinal SeahorseYuanyuan Jiang0Hongfei Wu1Paul Chi Lui Ho2Xuemei Tang3Hui Ao4Lu Chen5Jinjin Cai6State Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, ChinaState Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, ChinaSchool of Pharmacy, Monash University Malaysia, Subang Jaya 47500, MalaysiaChengdu Institute of Food Inspection, Chengdu 610045, ChinaState Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, ChinaState Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, ChinaHospital of Chengdu University of Traditional Chinese Medicine, Chengdu 610075, ChinaSeahorse is a valuable marine-animal drug widely used in traditional Chinese medicine (TCM), and which was first documented in the “Ben Cao Jing Ji Zhu” during the Liang Dynasty. <i>Hippocampus kelloggi</i> (HK) is the most common seahorse species in the medicinal material market and is one of the genuine sources of medicinal seahorse documented in the Chinese pharmacopeia. It is mainly cultivated in the Shandong, Fujian, and Guangxi Provinces in China. However, pseudo-HK, represented by <i>Hippocampus ingens</i> (HI) due to its similar appearance and traits, is often found in the market, compromising the safety and efficacy of clinical use. Currently, there is a lack of reliable methods for identifying these species based on their chemical composition. In this study, we employed, for the first time, a strategy combining gas chromatography-mass spectrometry (GC-MS) fingerprints and chemical patterns in order to identify HK and HI; it is also the first metabolomic study to date of HI as to chemical components. The obtained results revealed remarkable similarities in the chemical fingerprints, while significant differences were also observed. By employing hierarchical cluster analysis (HCA) and principal component analysis (PCA), based on the relative contents of their characteristic peaks, all 34 samples were successfully differentiated according to their species of origin, with samples from the same species forming distinct clusters. Moreover, nonadecanoic acid and behenic acid were exclusively detected in HK samples, further distinguishing them from HI samples. Additionally, the relative contents of lauric acid, tetradecanoic acid, pentadecanoic acid, n-hexadecanoic acid, palmitoleic acid, margaric acid, oleic acid, fenozan acid, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) exhibited significant differences between HK and HI (<i>p</i> < 0.0001), as determined by an unpaired <i>t</i>-test. Orthogonal partial least squares discriminant analysis (OPLS-DA) identified seven components (DHA, EPA, n-hexadecanoic acid, tetradecanoic acid, palmitoleic acid, octadecanoic acid, and margaric acid) with high discriminatory value (VIP value > 1). Thus, nonadecanoic acid, behenic acid, and these seven compounds can be utilized as chemical markers for distinguishing HK from HI. In conclusion, our study successfully developed a combined strategy of GC-MS fingerprinting and chemical pattern recognition for the identification of HK and HI, and we also discovered chemical markers that can directly differentiate between the two species. This study can provide a foundation for the authentication of Hippocampus and holds significant importance for the conservation of wild seahorse resources.https://www.mdpi.com/1420-3049/28/23/7824seahorse<i>Hippocampus kelloggi</i><i>Hippocampus ingens</i>GC-MS fingerprintchemical pattern recognition
spellingShingle Yuanyuan Jiang
Hongfei Wu
Paul Chi Lui Ho
Xuemei Tang
Hui Ao
Lu Chen
Jinjin Cai
GC-MS Fingerprinting Combined with Chemical Pattern-Recognition Analysis Reveals Novel Chemical Markers of the Medicinal Seahorse
Molecules
seahorse
<i>Hippocampus kelloggi</i>
<i>Hippocampus ingens</i>
GC-MS fingerprint
chemical pattern recognition
title GC-MS Fingerprinting Combined with Chemical Pattern-Recognition Analysis Reveals Novel Chemical Markers of the Medicinal Seahorse
title_full GC-MS Fingerprinting Combined with Chemical Pattern-Recognition Analysis Reveals Novel Chemical Markers of the Medicinal Seahorse
title_fullStr GC-MS Fingerprinting Combined with Chemical Pattern-Recognition Analysis Reveals Novel Chemical Markers of the Medicinal Seahorse
title_full_unstemmed GC-MS Fingerprinting Combined with Chemical Pattern-Recognition Analysis Reveals Novel Chemical Markers of the Medicinal Seahorse
title_short GC-MS Fingerprinting Combined with Chemical Pattern-Recognition Analysis Reveals Novel Chemical Markers of the Medicinal Seahorse
title_sort gc ms fingerprinting combined with chemical pattern recognition analysis reveals novel chemical markers of the medicinal seahorse
topic seahorse
<i>Hippocampus kelloggi</i>
<i>Hippocampus ingens</i>
GC-MS fingerprint
chemical pattern recognition
url https://www.mdpi.com/1420-3049/28/23/7824
work_keys_str_mv AT yuanyuanjiang gcmsfingerprintingcombinedwithchemicalpatternrecognitionanalysisrevealsnovelchemicalmarkersofthemedicinalseahorse
AT hongfeiwu gcmsfingerprintingcombinedwithchemicalpatternrecognitionanalysisrevealsnovelchemicalmarkersofthemedicinalseahorse
AT paulchiluiho gcmsfingerprintingcombinedwithchemicalpatternrecognitionanalysisrevealsnovelchemicalmarkersofthemedicinalseahorse
AT xuemeitang gcmsfingerprintingcombinedwithchemicalpatternrecognitionanalysisrevealsnovelchemicalmarkersofthemedicinalseahorse
AT huiao gcmsfingerprintingcombinedwithchemicalpatternrecognitionanalysisrevealsnovelchemicalmarkersofthemedicinalseahorse
AT luchen gcmsfingerprintingcombinedwithchemicalpatternrecognitionanalysisrevealsnovelchemicalmarkersofthemedicinalseahorse
AT jinjincai gcmsfingerprintingcombinedwithchemicalpatternrecognitionanalysisrevealsnovelchemicalmarkersofthemedicinalseahorse