Dataset Information

Integrative analysis of the steroidal alkaloids distribution and biosynthesis of bulbs Fritillariae Cirrhosae through metabolome and transcriptome analyses.

ABSTRACT:

Background

Bulbus Fritillariae Cirrhosae (BFC) is an endangered high-altitude medicine and food homology plant with anti-tumor, anti-asthmatic, and antitussive activities as it contains a variety of active ingredients, especially steroidal alkaloids. Bulbus Fritillariae Thunbergia (BFT) is another species of Fritillaria that grows at lower altitude areas. Production of plant-derived active ingredients through a synthetic biology strategy is one of the current hot topics in biological research, which requires a complete understanding of the related molecular pathways. Our knowledge of the steroidal alkaloid biosynthesis in Fritillaria species is still very limited.

Results

To promote our understanding of these pathways, we performed non-target metabolomics and transcriptome analysis of BFC and BFT. Metabolomics analysis identified 1288 metabolites in BFC and BFT in total. Steroidal alkaloids, including the proposed active ingredients of Fritillaria species peimine, peimisine, peiminine, etc., were the most abundant alkaloids detected. Our metabolomics data also showed that the contents of the majority of the steroidal alkaloids in BFC were higher than in BFT. Further, our comparative transcriptome analyses between BFC and BFT identified differentially expressed gene sets among these species, which are potentially involved in the alkaloids biosynthesis of BFC.

Conclusion

These findings promote our understanding of the mechanism of steroidal alkaloids biosynthesis in Fritillaria species.

SUBMITTER: Lu Q

PROVIDER: S-EPMC9284883 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Publications

Integrative analysis of the steroidal alkaloids distribution and biosynthesis of bulbs Fritillariae Cirrhosae through metabolome and transcriptome analyses.

Lu Qiuxia Q Li Rui R Liao Jiaqing J Hu Yuqin Y Gao Yundong Y Wang Mingcheng M Li Jian J Zhao Qi Q

BMC genomics 20220714 1

<h4>Background</h4>Bulbus Fritillariae Cirrhosae (BFC) is an endangered high-altitude medicine and food homology plant with anti-tumor, anti-asthmatic, and antitussive activities as it contains a variety of active ingredients, especially steroidal alkaloids. Bulbus Fritillariae Thunbergia (BFT) is another species of Fritillaria that grows at lower altitude areas. Production of plant-derived active ingredients through a synthetic biology strategy is one of the current hot topics in biological res ...[more]

PMID: 35836113

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Project description:This paper focuses on determining the authenticity and identifying the species of Fritillariae cirrhosae using electronic nose, electronic tongue, and electronic eye sensors, near infrared and mid-level data fusion. 80 batches of Fritillariae cirrhosae and its counterfeits (including several batches of Fritillaria unibracteata Hsiao et K.C. Hsia, Fritillaria przewalskii Maxim, Fritillaria delavayi Franch and Fritillaria ussuriensis Maxim) were initially identified by Chinese medicine specialists and by criteria in the 2020 edition of Chinese Pharmacopoeia. After obtaining the information from several sensors we constructed single-source PLS-DA models for authenticity identification and single-source PCA-DA models for species identification. We selected variables of interest by VIP value and Wilk's lambda value, and we subsequently constructed the three-source fusion model of intelligent senses and the four-source fusion model of intelligent senses and near-infrared spectroscopy. We then explained and analyzed the four-source fusion models based on the sensitive substances detected by key sensors. The accuracies of single-source authenticity PLS-DA identification models based on electronic nose, electronic eye, electronic tongue sensors and near-infrared were respectively 96.25%, 91.25%, 97.50% and 97.50%. The accuracies of single-source PCA-DA species identification models were respectively 85%, 71.25%, 97.50% and 97.50%. After three-source data fusion, the accuracy of the authenticity identification of the PLS-DA identification model was 97.50% and the accuracy of the species identification of the PCA-DA model was 95%. After four-source data fusion, the accuracy of the authenticity of the PLS-DA identification model was 98.75% and the accuracy of the species identification of the PCA-DA model was 97.50%. In terms of authenticity identification, four-source data fusion can improve the performance of the model, while for the identification of the species the four-source data fusion failed to optimize the performance of the model. We conclude that electronic nose, electronic tongue, electronic eye data and near-infrared spectroscopy combined with data fusion and chemometrics methods can identify the authenticity and determine the species of Fritillariae cirrhosae. Our model explanation and analysis can help other researchers identify key quality factors for sample identification. This study aims to provide a reference method for the quality evaluation of Chinese herbs.

Dataset Information

Integrative analysis of the steroidal alkaloids distribution and biosynthesis of bulbs Fritillariae Cirrhosae through metabolome and transcriptome analyses.

Background

Results

Conclusion

Publications

Integrative analysis of the steroidal alkaloids distribution and biosynthesis of bulbs Fritillariae Cirrhosae through metabolome and transcriptome analyses.

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