Metabolic map of mature maize kernels

Rao, Jun; Cheng, F. H.; Hu, Chaoyang; Quan, Sheng; Lin, Hong; Wang, Jing; Chen, Guihua; Zhao, Xiangxiang; Alexander, Danny; Guo, Lining; Wang, Guoying; Lai, Jinsheng; Zhang, Dabing; Shi, Jiannong

doi:10.1007/s11306-014-0624-3

Cited by 61 publications

(71 citation statements)

References 56 publications

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“…Metabolite profiling of HCT-116 cells for MB-treated and MB-untreated group was performed using an established metabolomic profiling platform combining UPLC/LC-MS with GC-MS as previously described [14, 25, 26]. Briefly, samples were prepared with a recovery standard for QC purposes.…”

Section: Methodsmentioning

confidence: 99%

“…Likewise, the samples for LC were stored overnight under nitrogen followed by further LC analysis [14]. The metabolites present in those two groups of HCT-116 cells were identified using an automated comparison with Metabolon’s reference library entries [14, 25, 26]. Library matching for each metabolite was performed for each sample and corrected manually if necessary.…”

Section: Methodsmentioning

confidence: 99%

“…A p value equals or less than 0.05 were considered statistically significant. After data normalization, the metabolomic data were analyzed as previously reported [14, 25, 26]. First, all the metabolomic data were subjected to Multi Experiment Viewer software (version 4.8; http://www.jcvi.org/cms/research/software/) for hierarchical clustering by using the Pearson correlation coefficient.…”

Section: Methodsmentioning

confidence: 99%

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Macranthoidin B Modulates Key Metabolic Pathways to Enhance ROS Generation and Induce Cytotoxicity and Apoptosis in Colorectal Cancer

Fan

Rao

Zhang³

et al. 2018

Cell Physiol Biochem

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Background/Aims: Induction of oxidative stress and reactive oxygen species (ROS) mediated-apoptosis have been utilized as effective strategies in anticancer therapy. Macranthoidin B (MB) is a potent inducer of ROS-mediated apoptosis in cancer, but its mechanism of action is poorly understood. Method: Superoxide production with MB exposure in colorectal cancer (CRC) cells was measured using lucigenin chemiluminescence and real-time PCR. MB’s inhibitory effect on proliferation and viability of CRC cells was determined by proliferation assays. MB’s effect on apoptosis of CRC cells was determined by Western blotting and annexin V-FITC/PI staining. MB’s effect on the growth of CRC xenografts in mice was assessed. An established metabolomics profiling platform combining ultra-performance liquid chromatography-tandem mass spectrometry (LC-MS) with gas chromatography-mass spectrometry (GC-MS) was performed to determine MB’s effect on total metabolite variation in CRC cells. Results: We found that MB increases ROS generation via modulating key metabolic pathways. Using metabolomics profiling platform combining LC-MS with GC-MS, a total of 236 metabolites were identified in HCT-116 cells in which 31 metabolites were determined to be significantly regulated (p ≤ 0.05) after MB exposure. A number of key metabolites revealed by metabolomics analysis include glucose, fructose, citrate, arginine, phenylalanine, and S-adenosylhomocysteine (SAH), suggesting specific modulation of metabolism on carbohydrates, amino acids and peptides, lipids, nucleotide, cofactors and vitamins in HCT-116 CRC cells with MB treatment highly associated with apoptosis triggered by enhanced ROS and activated caspase-3. Conclusion: Our results demonstrate that MB represses CRC cell proliferation by inducing ROS-mediated apoptosis.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Macranthoidin B Modulates Key Metabolic Pathways to Enhance ROS Generation and Induce Cytotoxicity and Apoptosis in Colorectal Cancer

Fan

Rao

Zhang³

et al. 2018

Cell Physiol Biochem

Self Cite

View full text Add to dashboard Cite

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“…The study of molecular and biochemical impacts of environmental factors on wheat grain development and protein synthesis has also been carried out, but the dynamic metabolome changes in developing wheat grains have not been described. Also, kernel metabolites can be used to generate bodily energy, including essential human nutrients, and serve as a resource for production of bioenergy . Thus dynamic metabolome profiling during grain development would yield information facilitating an understanding of the biochemical mechanism of grain development, and data on nutritive quality.…”

Section: Introductionmentioning

confidence: 99%

Dynamic metabolome profiling reveals significant metabolic changes during grain development of bread wheat (Triticum aestivum L.)

et al. 2016

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The present metabolome approach identified dynamic changes in metabolite levels, and correlations among such levels, in developing seeds. The comprehensive metabolic map may be useful when breeding programs seek to improve grain quality. The work highlights the utility of GC/MS-based metabolomics, in conjunction with univariate and multivariate data analysis, when it is sought to understand metabolic changes in developing seeds. © 2015 Society of Chemical Industry.

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“…For functional understanding of phenotypes it is essential to integrate genomic information to characterize gene-tometabolite associations (Carreno-Quintero et al 2013). Metabolic analysis has been increasingly and successfully used to assist elite germplasm selection (Fernie and Schauer 2009;Rao et al 2014). In tomato, the first study using metabolite profiling showed that metabolic traits correlated with phenotypic traits such as yield or harvest index, exposing the challenge to use metabolites as biomarkers (Hermann and Schauer 2013).…”

Section: Introductionmentioning

confidence: 99%

Metabolic analyses of interspecific tomato recombinant inbred lines for fruit quality improvement

et al. 2015

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Elucidating the determinants of tomato nutritional value and fruit quality to introduce improved varieties on the international market represents a major challenge for crop biotechnology. Different strategies can be undertaken to exploit the natural variability of Solanum to re-incorporate lost allelic diversity into commercial varieties. One of them is the characterization of selected germplasm for breeding programs. To achieve this goal, 18 RILs (S. lycopersicum 9 S. pimpinellifolium) were comprehensively phenotyped for fruit polar metabolites and quality associated traits. Metabolites were quantified by GC-MS and 1 H NMR. Integrative analyses by neuronal clustering and network construction revealed that fruit properties are strongly associated with the metabolites aspartate, serine, glutamate and 2-oxoglutarate. Shelf life and firmness appeared to be linked to malate content. By a comparative analysis of the whole data set, ten RILs presented higher number of traits with positive effect than the S. lycopersicum 9 S. pimpinellifolium hybrid. Thus, these lines can be proposed as promising candidates for breeding programs aimed to improve fruit quality.

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Metabolic map of mature maize kernels

Cited by 61 publications

References 56 publications

Macranthoidin B Modulates Key Metabolic Pathways to Enhance ROS Generation and Induce Cytotoxicity and Apoptosis in Colorectal Cancer

Macranthoidin B Modulates Key Metabolic Pathways to Enhance ROS Generation and Induce Cytotoxicity and Apoptosis in Colorectal Cancer

Dynamic metabolome profiling reveals significant metabolic changes during grain development of bread wheat (Triticum aestivum L.)

Metabolic analyses of interspecific tomato recombinant inbred lines for fruit quality improvement

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