Untargeted Metabolomics Profiling of Growth-Year-Associated Changes in Relative Metabolite Abundance in Tetrastigma hemsleyanum Tuberous Roots
4 affiliations
- 1College of Biological and Environmental Engineering, Zhejiang Shuren University, Hangzhou 310015, China
- 2Zhejiang Key Laboratory of Environment and Health of New Pollutants, School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- 3State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- 4College of Life Sciences, Zhejiang University, Hangzhou 310058, China
Abstract
Background/Objectives:Tetrastigma hemsleyanum is a traditional medicinal plant whose tuberous roots are rich in flavonoids and phenolic acids, but how the relative abundance of these constituents changes across growth years remains poorly resolved. Methods: Tuberous roots from five growth years (S1–S5; three independently grown plants per year) were analyzed by UHPLC–Orbitrap-MS-based untargeted metabolomics. Annotations were graded using Metabolomics Standards Initiative (MSI) criteria: of 349 curated entries, 252 were Level 2 and 56 Level 3, and none reached Level 1 because authentic standards were not analyzed. Results: Principal component analysis showed non-linear differentiation, with first-year roots the most distinct. Combined VIP, fold-change, and t-test criteria identified 264 differential entries between adjacent growth years, all remaining significant after Benjamini–Hochberg correction (q < 0.01). Flavonol-related features (e.g., quercetin-related signals, myricetin, and rutin) were relatively abundant at S1; flavone C-glycoside, flavan-3-ol, and phenolic-acid features (e.g., vitexin, catechin, and ferulic acid) at S3; and amino-acid, organic-acid, and nucleotide features at S4. KEGG mapping of 46 differential annotations indicated flavonoid- and amino-acid-related pathways. Conclusions: Given the small sample size, relative peak-area data, and putative annotations, these results are hypothesis-generating; they identify candidate stages and constituents for targeted quantification rather than an optimal harvest year.
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BibTeX
@article{ye2026untargeted,
title = {{Untargeted Metabolomics Profiling of Growth-Year-Associated Changes in Relative Metabolite Abundance in Tetrastigma hemsleyanum Tuberous Roots}},
author = {Mingli Ye and Boya Liu and Xin Li and Haifeng Han and Yukai Ba and Zhengrui Chen and Yu Liu and Yonggang Zhao},
journal = {Metabolites},
year = {2026},
month = oct,
doi = {10.3390/metabo16110831},
url = {https://www.mdpi.com/2218-1989/16/11/831},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Untargeted Metabolomics Profiling of Growth-Year-Associated Changes in Relative Metabolite Abundance in Tetrastigma hemsleyanum Tuberous Roots
AU - Mingli Ye
AU - Boya Liu
AU - Xin Li
AU - Haifeng Han
AU - Yukai Ba
AU - Zhengrui Chen
AU - Yu Liu
AU - Yonggang Zhao
PY - 2026
DA - 2026/10/30
JO - Metabolites
DO - 10.3390/metabo16110831
UR - https://www.mdpi.com/2218-1989/16/11/831
AB - Background/Objectives:Tetrastigma hemsleyanum is a traditional medicinal plant whose tuberous roots are rich in flavonoids and phenolic acids, but how the relative abundance of these constituents changes across growth years remains poorly resolved. Methods: Tuberous roots from five growth years (S1–S5; three independently grown plants per year) were analyzed by UHPLC–Orbitrap-MS-based untargeted metabolomics. Annotations were graded using Metabolomics Standards Initiative (MSI) criteria: of 349 curated entries, 252 were Level 2 and 56 Level 3, and none reached Level 1 because authentic standards were not analyzed. Results: Principal component analysis showed non-linear differentiation, with first-year roots the most distinct. Combined VIP, fold-change, and t-test criteria identified 264 differential entries between adjacent growth years, all remaining significant after Benjamini–Hochberg correction (q < 0.01). Flavonol-related features (e.g., quercetin-related signals, myricetin, and rutin) were relatively abundant at S1; flavone C-glycoside, flavan-3-ol, and phenolic-acid features (e.g., vitexin, catechin, and ferulic acid) at S3; and amino-acid, organic-acid, and nucleotide features at S4. KEGG mapping of 46 differential annotations indicated flavonoid- and amino-acid-related pathways. Conclusions: Given the small sample size, relative peak-area data, and putative annotations, these results are hypothesis-generating; they identify candidate stages and constituents for targeted quantification rather than an optimal harvest year.
SN - 2218-1989
ER -