Dataset Information

Mass Spectrometry-Based Untargeted Metabolomics and ?-Glucosidase Inhibitory Activity of Lingzhi (Ganoderma lingzhi) During the Developmental Stages.

ABSTRACT: Lingzhi is a Ganoderma mushroom species which has a wide range of bioactivities. Analysis of the changes in metabolites during the developmental stages of lingzhi is important to understand the underlying mechanism of its biosynthesis, as well as its bioactivity. It may also provide valuable information for the cultivation efficiency of lingzhi. In this study, mass spectrometry based untargeted metabolomics was carried out to analyze the alteration of metabolites during developmental stages of lingzhi. Eight developmental stages were categorized on the basis of morphological changes; starting from mycelium stage to post-mature stage. GC/MS and LC/MS analyses along with multivariate analysis of lingzhi developmental stages were performed. Amino acids, organic acids, sugars, polyols, fatty acids, fatty alcohols, and some small polar metabolites were extracted as marker metabolites from GC/MS analysis, while, lanostane-type triterpenoids were observed in LC/MS analysis of lingzhi. The marker metabolites from untargeted analysis of lingzhi developmental stages were correlated with the ?-glucosidase inhibitory activity. Two metabolites, compounds 34 and 35, were identified as potential contributors of the ?-glucosidase inhibitory activity. The current result shows that some metabolites are involved in the developmental process and ?-glucosidase inhibitory activity of lingzhi.

SUBMITTER: Satria D

PROVIDER: S-EPMC6600326 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Mass Spectrometry-Based Untargeted Metabolomics and α-Glucosidase Inhibitory Activity of Lingzhi (<i>Ganoderma lingzhi</i>) During the Developmental Stages.

Satria Dedi D Tamrakar Sonam S Suhara Hiroto H Kaneko Shuhei S Shimizu Kuniyoshi K

Molecules (Basel, Switzerland) 20190529 11

Lingzhi is a <i>Ganoderma</i> mushroom species which has a wide range of bioactivities. Analysis of the changes in metabolites during the developmental stages of lingzhi is important to understand the underlying mechanism of its biosynthesis, as well as its bioactivity. It may also provide valuable information for the cultivation efficiency of lingzhi. In this study, mass spectrometry based untargeted metabolomics was carried out to analyze the alteration of metabolites during developmental stag ...[more]

PMID: 31146329

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Project description:Mass spectral data sets often contain experimental artefacts, and data filtering prior to statistical analysis is crucial to extract reliable information. This is particularly true in untargeted metabolomics analyses, where the analyte(s) of interest are not known a priori. It is often assumed that chemical interferents (i.e. solvent contaminants such as plasticizers) are consistent across samples, and can be removed by background subtraction from blank injections. On the contrary, it is shown here that chemical contaminants may vary in abundance across each injection, potentially leading to their misidentification as relevant sample components. With this metabolomics study, we demonstrate the effectiveness of hierarchical cluster analysis (HCA) of replicate injections (technical replicates) as a methodology to identify chemical interferents and reduce their contaminating contribution to metabolomics models. Pools of metabolites with varying complexity were prepared from the botanical Angelica keiskei Koidzumi and spiked with known metabolites. Each set of pools was analyzed in triplicate and at multiple concentrations using ultraperformance liquid chromatography coupled to mass spectrometry (UPLC-MS). Before filtering, HCA failed to cluster replicates in the data sets. To identify contaminant peaks, we developed a filtering process that evaluated the relative peak area variance of each variable within triplicate injections. These interferent peaks were found across all samples, but did not show consistent peak area from injection to injection, even when evaluating the same chemical sample. This filtering process identified 128 ions that appear to originate from the UPLC-MS system. Data sets collected for a high number of pools with comparatively simple chemical composition were highly influenced by these chemical interferents, as were samples that were analyzed at a low concentration. When chemical interferent masses were removed, technical replicates clustered in all data sets. This work highlights the importance of technical replication in mass spectrometry-based studies, and presents a new application of HCA as a tool for evaluating the effectiveness of data filtering prior to statistical analysis.

Dataset Information

Mass Spectrometry-Based Untargeted Metabolomics and ?-Glucosidase Inhibitory Activity of Lingzhi (Ganoderma lingzhi) During the Developmental Stages.

Publications

Mass Spectrometry-Based Untargeted Metabolomics and α-Glucosidase Inhibitory Activity of Lingzhi (<i>Ganoderma lingzhi</i>) During the Developmental Stages.

Similar Datasets

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