UPLC/MS-based untargeted metabolomics reveals the changes of metabolites profile of Salvia miltiorrhiza bunge during Sweating processing

Cao, Mengyang; Liu, Yingying; Jiang, Weimin; Meng, Xiaoxi; Zhang, Wei; Chen, Weidong; Peng, Daiyin; Xing, Shihai

doi:10.1038/s41598-020-76650-w

Cited by 34 publications

(23 citation statements)

References 44 publications

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“…The metabolites with variable importance in projection value (VIP) ≥ 1, p value < 0.05, and fold change (FC) of ≥1.6 (up-regulated) or ≤0.625 (downregulated) were considered to be differential metabolites. Volcano plots were used to filter metabolites of interest based on the log2(FC) of the metabolites [80,81]. Data were expressed as the mean ± standard deviation (SD) of four biological replicates.…”

Section: Discussionmentioning

confidence: 99%

Metabolite Profiling and Transcriptome Analysis Provide Insight into Seed Coat Color in Brassica juncea

Shen

Tang

Zhang

et al. 2021

IJMS

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The allotetraploid species Brassica juncea (mustard) is grown worldwide as oilseed and vegetable crops; the yellow seed-color trait is particularly important for oilseed crops. Here, to examine the factors affecting seed coat color, we performed a metabolic and transcriptomic analysis of yellow- and dark-seeded B. juncea seeds. In this study, we identified 236 compounds, including 31 phenolic acids, 47 flavonoids, 17 glucosinolates, 38 lipids, 69 other hydroxycinnamic acid compounds, and 34 novel unknown compounds. Of these, 36 compounds (especially epicatechin and its derivatives) accumulated significantly different levels during the development of yellow- and dark-seeded B. juncea. In addition, the transcript levels of BjuDFR, BjuANS,BjuBAN, BjuTT8, and BjuTT19 were closely associated with changes to epicatechin and its derivatives during seed development, implicating this pathway in the seed coat color determinant in B. juncea. Furthermore, we found numerous variations of sequences in the TT8A genes that may be associated with the stability of seed coat color in B. rapa, B. napus, and B. juncea, which might have undergone functional differentiation during polyploidization in the Brassica species. The results provide valuable information for understanding the accumulation of metabolites in the seed coat color of B. juncea and lay a foundation for exploring the underlying mechanism.

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Section: Discussionmentioning

confidence: 99%

Metabolite Profiling and Transcriptome Analysis Provide Insight into Seed Coat Color in Brassica juncea

Shen

Tang

Zhang

et al. 2021

IJMS

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“…As previously mentioned, the integrated metabolomics analysis in this study was conducted by GC–MS and UPLC–MS. The methodology has previously been described ( Cao et al, 2020 ). In brief, GC–MS analysis was conducted using an Agilent 7890B gas chromatography system coupled to an Agilent 5977A MSD system (Agilent Technologies Inc., CA, United States).…”

Section: Methodsmentioning

confidence: 99%

In situ Metabolomics of Metabolic Reprogramming Involved in a Mouse Model of Type 2 Diabetic Kidney Disease

et al. 2021

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The in situ metabolic profiling of the kidney is crucial to investigate the complex metabolic reprogramming underlying diabetic kidney disease (DKD) and to allow exploration of potential metabolic targets to improve kidney function. However, as the kidney is a highly heterogeneous organ, traditional metabolomic methods based on bulk analysis that produce an averaged measurement are inadequate. Herein, we employed an in situ metabolomics approach to discover alternations of DKD-associated metabolites and metabolic pathways. A series of histology-specific metabolic disturbances were discovered in situ using airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI–MSI). In combination with integrated metabolomics analysis, five dysfunctional metabolic pathways were identified and located in the kidneys of type-2 DKD mice simultaneously for the first time, including taurine metabolism, arginine and proline metabolism, histidine metabolism, biosynthesis of unsaturated fatty acids, and fatty acid degradation pathways. As crucial nodes of metabolic pathways, five dysregulated rate-limiting enzymes related to altered metabolic pathways were further identified. These findings reveal alternations from metabolites to enzymes at the molecular level in the progression of DKD and provide insights into DKD-associated metabolic reprogramming.

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“…The resulting matrix of features included information on mass-to-charge ratio (m/z), retention time (RT), and peak intensities. Metabolites were identified by progenesis QI Data Processing Software based on precise mass number, secondary fragments and isotope distribution, and qualitative by mapping on public databases such as HMDB (http: //www.hmdb.ca/, accessed on 12 June 2021), Metlin (http://metlin.scripps.edu/, accessed on 12 June 2021), Lipidmaps (http://www.lipidmaps.org/, accessed on 12 June 2021), and self-built databases [93]. The data in both positive and negative modes were merged to form a combined data set, which was imported into R software package according to the method of Luo et al [94].…”

Section: Lc-ms Data Analysesmentioning

confidence: 99%

Metabolic Profiles of Brassica juncea Roots in Response to Cadmium Stress

et al. 2021

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Brassica juncea has great application potential in phytoremediation of cadmium (Cd)-contaminated soil because of its excellent Cd accumulating and high biomass. In this study, we compared the effects of Cd under 48 h and 7 d stress in roots of Brassica juncea using metabolite profiling. The results showed that many metabolic pathways and metabolites in Brassica juncea roots were altered significantly in response to Cd stress. We found that significant differences in levels of amino acids, organic acids, carbohydrates, lipids, flavonoids, alkaloids, and indoles were induced by Cd stress at different times, which played a pivotal role in the adaptation of Brassica juncea roots to Cd stress. Meanwhile, Brassica juncea roots could resist 48 h Cd stress by regulating the biosynthesis of amino acids, linoleic acid metabolism, aminoacyl-tRNA biosynthesis, glycerophospholipid metabolism, ABC transporters, arginine biosynthesis, valine, leucine and isoleucine biosynthesis, and alpha-linolenic acid metabolism; however, they regulated alpha-linolenic acid metabolism, glycerophospholipid metabolism, ABC transporters, and linoleic acid metabolism to resist 7 d Cd stress. A metabolomic expedition to the response of Brassica juncea to Cd stress will help to comprehend its tolerance and accumulation mechanisms of Cd.

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UPLC/MS-based untargeted metabolomics reveals the changes of metabolites profile of Salvia miltiorrhiza bunge during Sweating processing

Cited by 34 publications

References 44 publications

Metabolite Profiling and Transcriptome Analysis Provide Insight into Seed Coat Color in Brassica juncea

Metabolite Profiling and Transcriptome Analysis Provide Insight into Seed Coat Color in Brassica juncea

In situ Metabolomics of Metabolic Reprogramming Involved in a Mouse Model of Type 2 Diabetic Kidney Disease

Metabolic Profiles of Brassica juncea Roots in Response to Cadmium Stress

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