Mass spectrometry imaging guided molecular networking to expedite discovery and structural analysis of agarwood natural products

Kuo, Ting-Hao; Huang, Hou-Chun; Hsu, Cheng-Chih

doi:10.1016/j.aca.2019.05.070

Cited by 29 publications

(20 citation statements)

References 50 publications

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“…The MS data was processed through GNPS online workflow and visualized by MS/MS molecular networking. Their spectral similarities were evaluated through cosine calculation (cos θ), the larger the cos θ value, the higher the similarity of the MS/MS fragments [ 7 ]. The results showed that the cluster of molecular networking in the negative mode (Fig.…”

Section: Resultsmentioning

confidence: 99%

The combination of UHPLC-HRMS and molecular networking improving discovery efficiency of chemical components in Chinese Classical Formula

et al. 2021

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Background It is essential to identify the chemical components for the quality control methods establishment of Chinese Classical Formula (CCF). However, CCF are complex mixture of several herbal medicines with huge number of different compounds and they are not equal to the combination of chemical components from each herb due to particular formula ratio and preparation techniques. Therefore, it is time-consuming to identify compounds in a CCF by analyzing the LC–MS/MS data one by one, especially for unknown components. Methods An ultra-high pressure liquid chromatography-linear ion trap-orbitrap high resolution mass spectrometry (UHPLC-LTQ-Orbitrap-MS/MS) approach was developed to comprehensively profile and characterize multi-components in CCF with Erdong decoction composed of eight herbal medicines as an example. Then the MS data of Erdong decoction was analyzed by MS/MS-based molecular networking and these compounds with similar structures were connected to each other into a cluster in the network map. Then the unknown compounds connected to known compounds in a cluster of the network map were identified due to their similar structures. Results Based on the clusters of the molecular networking, 113 compounds were rapidly tentative identification from Erdong decoction for the first time in the negative mode, which including steroidal saponins, triterpenoid saponins, flavonoid O-glycosides and flavonoid C-glycosides. In addition, 10 alkaloids were tentatively identified in the positive mode from Nelumbinis folium by comparison with literatures. Conclusion MS/MS-based molecular networking technique is very useful for the rapid identification of components in CCF. In Erdong decoction, this method was very suitable for the identification of major steroidal saponins, triterpenoid saponins, and flavonoid C-glycosides.

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Section: Resultsmentioning

confidence: 99%

The combination of UHPLC-HRMS and molecular networking improving discovery efficiency of chemical components in Chinese Classical Formula

et al. 2021

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“…In this way, metabolites with the same structural moieties tend to cluster and form a molecular family in the network. This strategy is beneficial for annotating metabolites as well as discovering novel structural analogues, and has been widely applied in examining specialized metabolites from plants [15] and microbes [16]. Here we showed that the Arthrobotrys metabolomic dataset yielded 12,179 nodes and hundreds of molecular clusters spanning in the molecular network (Figure 2a and Figure S1).…”

Section: Revealing Chemical Diversity Of Metabolites Of Nematode-trapmentioning

confidence: 87%

Nematode-Trapping Fungi Produce Diverse Metabolites during Predator–Prey Interaction

et al. 2020

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Nematode-trapping fungi are natural antagonists of nematodes. These predatory fungi are capable of switching their lifestyle from a saprophytic to predatory stage in the presence of nematodes by developing specialized trapping devices to capture and consume nematodes. The biochemical mechanisms of such predator–prey interaction have become increasingly studied given the potential application of nematode-trapping fungi as biocontrol agents, but the involved fungal metabolites remain underexplored. Here, we report a comprehensive liquid–chromatography mass spectrometry (LC–MS) metabolomics study on one hundred wild isolates of nematode-trapping fungi in three different species, Arthrobotrys oligospora, Arthrobotrys thaumasia, and Arthrobotrys musiformis. Molecular networking analysis revealed that the fungi were capable of producing thousands of metabolites, and such chemical diversity of metabolites was notably increased as the fungi switched lifestyle to the predatory stage. Structural annotations by tandem mass spectrometry revealed that those fungal metabolites belonged to various structural families, such as peptide, siderophore, fatty alcohol, and fatty acid amide, and their production exhibited species specificity. Several small peptides (<1.5 kDa) produced by A. musiformis in the predatory stage were found, with their partial amino acid sequences resolved by the tandem mass spectra. Four fungal metabolites (desferriferrichrome, linoleyl alcohol, nonadecanamide, and citicoline) that were significantly enriched in the predatory stage were identified and validated by chemical standards, and their bioactivities against nematode prey were assessed. The availability of the metabolomics datasets will facilitate comparative studies on the metabolites of nematode-trapping fungi in the future.

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“…For example, osmium tetroxide was used to treat the surface of the xylem to oxidize the C=C double bond of coniferin., and spatially differentiation of two substances with close molecular weight, coniferin and sucrose, by detecting the spatial distribution of the oxidized compounds [97] namely multimodal MSI. For data processing, Kuo et al [98] combined MSI data with LC-MS/MS molecular network, identifying the structures of dozens of metabolites in agarwood and classifying them into three categories. Compound identification is one of the major problems in MSI.…”

Section: Visualization Of Specific Metabolites Spatio-temporal Distributionsmentioning

confidence: 99%

Mass spectrometry imaging for direct visualization of components in plants tissues

Han

Sheng

et al. 2021

J of Separation Science

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Mass spectrometry is considered the most informative technique for components identification and has been widely adopted in plant sciences. However, the spatial distribution of compounds in the plant, which is vital for the exploration of plant physiological mechanisms, is missed in MS analysis. In recent years, mass spectrometry imaging has brought a great breakthrough in plant analysis because it can determine both the molecular compositions and spatial distributions, which is conducive to understand functions and regulation pathways of specific components in plants. Mass spectrometry imaging analysis of plant tissue is toward high sensitivity, high spatial resolution, and even single-cell analysis. Despite many challenges and technical barriers, such as difficulties of sample pretreatment caused by morphological diversity of plant tissues, obstacles for high spatial resolution imaging, and so on, lots of researches have contributed to remarkable progress, including improvement in tissue preparation, matrix innovation, and ionization mode development. This review focuses on the advances of mass spectrometry imaging analysis of plants in the last 5 years, including commonly used ionization techniques, technical advances, and recent applications of mass spectrometry imaging in plants.

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Mass spectrometry imaging guided molecular networking to expedite discovery and structural analysis of agarwood natural products

Cited by 29 publications

References 50 publications

The combination of UHPLC-HRMS and molecular networking improving discovery efficiency of chemical components in Chinese Classical Formula

The combination of UHPLC-HRMS and molecular networking improving discovery efficiency of chemical components in Chinese Classical Formula

Nematode-Trapping Fungi Produce Diverse Metabolites during Predator–Prey Interaction

Mass spectrometry imaging for direct visualization of components in plants tissues

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