Chenfei Ma

Shanghai Agrobiological Gene Center, Shanghai, Shanghai Shi, China

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Publications (10)33.52 Total impact

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    ABSTRACT: In this study, metabolic profiles of a set of 48 rice germplasms from the Chinese core collection were obtained by gas chromatography and time-of-flight mass spectrometry (GC-TOF-MS). Forty-one metabolites were identified and relatively quantified according to the internal standard (IS). Wide ranges of variations for all metabolites were observed among rice accessions. The maximum/minimum ratios varied from 4.73 to 211.36. The metabolites were categorized into seven groups based on their chemical characteristics. Clustering analysis and a correlation network showed that most of the metabolites had variations among rice accessions in the same direction. Using 218 molecular markers, association mapping was conducted to identify the chromosomal loci influencing the concentrations of identified metabolites. Twenty markers were identified associating with the concentrations of 29 metabolites [-lg(P) > 3]. Allelic effects were investigated in detail in two markers (RM315 and RM541) as examples.
    Journal of Agricultural and Food Chemistry 08/2011; 59(17):9257-64. · 3.11 Impact Factor
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    ABSTRACT: We used proteomic analysis to determine the response of rice plant seedlings to drought-induced stress. The expression of 71 protein spots was significantly altered, and 60 spots were successfully identified. The greatest down-regulated protein functional category was translation. Up-regulated proteins were mainly related to protein folding and assembly. Additionally, many proteins involved in metabolism (e.g. carbohydrate metabolism) also showed differences in expression. cDNA microarray and GC-MS analysis showed 4756 differentially expressed mRNAs and 37 differentially expressed metabolites. Once these data were integrated with the proteomic analysis, we were able to elucidate the metabolic pathways affected by drought-induced stress. These results suggest that increased energy consumption from storage substances occurred during drought. In addition, increased expression of the enzymes involved in anabolic pathways corresponded with an increase in the content of six amino acids. We speculated that energy conversion from carbohydrates and/or fatty acids to amino acids was increased. Analysis of basic metabolism networks allowed us to understand how rice plants adjust to drought conditions.
    Proteomics 08/2011; 11(21):4122-38. · 4.43 Impact Factor
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    ABSTRACT: Artemisin is a sesquiterpene lactone with an endoperoxide bridge first isolated from the aerial parts of Artemisia annua L. (Compositae). It is an important antimalarial component, but as of present remains quite expensive due to its low content in the plant, the only commercial source of the compound. In this study, we found a 49% increase of the artemisinin content in A. annua SP18 on day 8 after treatment with methyl jasmonate (MeJA), together with an 80% increase in artemisinic acid and 28% in dihydroartemisinic acid, the two potential precursors of artemisinin. In addition, the effects of exogenous MeJA on other secondary metabolites were evaluated by metabolite profiling using orthogonal signal correction partial least square discriminant analysis (OSC-PLS). Six sesquiterpenoids and three triterpenoids were selected as marker compounds in OSC-PLS. Their content also changed significantly after MeJA treatment, including a 50% increase in methyl artemisinic acid, a 67% increase in squalene and a 60% increase in peak 51 (an unidentified sesquiterpenoid). These compounds are promising targets for further studies on artemisinin biosynthesis and metabolic engineering.
    Industrial Crops and Products - IND CROPS PRODUCTS. 01/2010; 31(2):214-218.
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    ABSTRACT: Artemisinin has been proven to be an effective antimalarial compound, especially for chloroquine-resistant and cerebral malaria. However, its biosynthesis pathway is still not completely clear. In order to get new clues about artemisinin biosynthesis, metabolic profiling by gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) was applied to compare the secondary metabolites of two Artemisia annua L., genotype SP18 and 001, for some phenotypic and agricultural trait differences, including artemisinin content, existed between the two genotypes. Samples at 7 time points of three growth stages were studied. The data of profiles were subjected to multivariate analysis with partial least squares discriminant analysis (PLS-DA). The results indicated that there were clear differences in terpenoids and artemisinin metabolism between different growth stages and genotypes. Twenty-one compounds, including artemisinin and its related precursors, were selected as the marker compounds of the PLS-DA between the two genotypes. Among them, artemisinic acid, arteannuin B, borneol, beta-farnesene and an unidentified sesquiterpenoid (peak 48) were abundant in 001, while camphor, methyl artemisinic acid and lanceol accumulated mainly in SP18. The relationship between these differences and artemisinin biosynthesis in the two genotypes of A. annua were discussed.
    Planta Medica 07/2009; 75(15):1625-33. · 2.35 Impact Factor
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    ABSTRACT: The cryIAc and sck genes were introduced to the rice for the purpose of improving the insect resistance. Metabolic profiles of wild and transgenic rice were compared to assess the unintended effects related to gene modification. Wild samples with different sowing dates or sites were also examined to determine the environmental effects on metabolites. The polar compounds of grains were extracted, trimethylsilylated and analyzed by gas chromatography-flame ionization detection (GC-FID). Partial least squares-discriminant analysis (PLS-DA) and principal component analysis (PCA) were applied to differentiate transgenic and wild rice grains. The significantly distinguishable metabolites were picked out, and then identified by gas chromatography-mass spectrometry (GC-MS). It was found that both the environment and gene manipulation had remarkable impacts on the contents of glycerol-3-phosphate, citric acid, linoleic acid, oleic acid, hexadecanoic acid, 2,3-dihydroxypropyl ester, sucrose, 9-octadecenoic acid (Z)-, 2,3-dihydroxypropyl ester and so on. Sucrose, mannitol and glutamic acid had a significant increase in transgenic grains in contrast to those in non-genetically modified (GM) rice.
    Journal of chromatography. B, Analytical technologies in the biomedical and life sciences 03/2009; 877(8-9):725-32. · 2.78 Impact Factor
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    ABSTRACT: Comprehensive 2-D GC (GC x GC) coupled with TOF MS or flame ionization detector (FID) was employed to characterize and quantify the chemical composition of volatile oil in the radixes of Panax ginseng C. A. Mey. (ginseng) at different ages. Thirty-six terpenoids were tentatively identified based on the MS library search and retention index in a ginseng sample at the age of 3 years. An obvious group-type separation was obtained in the GC x GC-TOF MS chromatogram. The data collected by GC x GC-FID were processed using a principal component analysis (PCA) method to classify the samples at different ages. The compounds responsible for the significant differentiation among samples were defined. It was found that the relative abundances of alpha-cadinol, alpha-bisabolol, thujopsene, and n-hexadecanoic acid significantly rise with the increase in age.
    Journal of Separation Science 10/2008; 31(19):3451-7. · 2.59 Impact Factor
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    ABSTRACT: Artemisia annua L. is an annual herb native of Asia and this plant has been famous for the discovery of the anti-malarial drug artemisinin since 1971. In this work, to investigate variety of whole metabolites, metabolic fingerprinting analysis of A. annua L. was carried out by GC and GC-MS coupled with trimethylsilyl derivatisation. Principal component analysis and partial least squares discriminant analysis were employed to classify GC data of A. annua L. samples at five developmental stages. The results indicated that there was no distinct difference of metabolites between control (001) and transgenic strain (F4) from the tender seedling stage to adult seedling stage, but clear differences were detected at pre-flower budding stage, flower budding stage and full flowering stage. Three precursors of artemisinin biosynthesis were studied at five developmental stages and found that a possible bottleneck exists in the conversion from artemisinic acid or dihydroartemisinic acid to artemisinin.
    Journal of Chromatography A 05/2008; 1186(1-2):412-9. · 4.61 Impact Factor
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    ABSTRACT: Artemisia annua L. is an annual herb native of Asia, it has been used for many centuries for the treatment of fever and malaria. In this paper, analysis of the volatile oil of Artemisia annua L. was performed by comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC x GC-TOF MS). Three hundred and three components were tentatively identified and terpene compounds are the main components of Artemisia annua L. volatile oil. Artemisinic acid is tentatively qualified.
    Journal of Chromatography A 06/2007; 1150(1-2):50-3. · 4.61 Impact Factor
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    ABSTRACT: A model is developed for predicting the resolution of interested component pair and calculating the optimum temperature programming condition in the comprehensive two-dimensional gas chromatography (GC x GC). Based on at least three isothermal runs, retention times and the peak widths at half-height on both dimensions are predicted for any kind of linear temperature-programmed run on the first dimension and isothermal runs on the second dimension. The calculation of the optimum temperature programming condition is based on the prediction of the resolution of "difficult-to-separate components" in a given mixture. The resolution of all the neighboring peaks on the first dimension is obtained by the predicted retention time and peak width on the first dimension, the resolution on the second dimension is calculated only for the adjacent components with un-enough resolution on the first dimension and eluted within a same modulation period on the second dimension. The optimum temperature programming condition is acquired when the resolutions of all components of interest by GC x GC separation meet the analytical requirement and the analysis time is the shortest. The validity of the model has been proven by using it to predict and optimize GC x GC temperature programming condition of an alkylpyridine mixture.
    Journal of Chromatography A 10/2005; 1086(1-2):175-84. · 4.61 Impact Factor
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    ABSTRACT: Amorpha-4,11-diene synthase (ADS) is a very important enzyme which catalyzes the committed step of artemisinin biosynthesis. In this work, two lines of transgenic Artemisia annua L. which ADS was over-expressed (line A9) and suppressed (line Amsi), respectively, were utilized. And the transgenic line GUS with β-Glucuronidase gene was regarded as the control. Their terpenoid metabolic profiling was investigated by using GC×GC–TOFMS. The metabolic profiling method established included simple extraction, two-dimension separation and multivariate analysis. Partial least squares discriminant analysis (PLS-DA) was used to classify two transgenic lines and the control line. Eleven important compounds in classification were identified. Most of them were sesquiterpenoids including monoterpenoid, diterpenoid and four bioprecursors of artemsisnin. Compared with the control, artemisinin and bioprecursors in the line A9 increased as a result of over-expressing ADS. Borneol and phytol also increased in the line A9, but (E)-β-farnesene and germacrene D were reversely altered. The result indicated that over-expression of the ADS affected not only artemisinin biosynthesis, but also the whole metabolic network of terpenoid. Compared with the line A9, no opposite change of artemisinin and related derivatives was observed in the line Amsi, the ADS inhibition had no significant effect on artemisinin biosynthesis in the line Amsi.
    Metabolomics 5(4):497-506. · 4.43 Impact Factor

Publication Stats

156 Citations
33.52 Total Impact Points

Institutions

  • 2011
    • Shanghai Agrobiological Gene Center
      Shanghai, Shanghai Shi, China
  • 2005–2011
    • Northeast Institute of Geography and Agroecology
      • Laboratory of Analytical Chemistry for Life Science
      Beijing, Beijing Shi, China
  • 2007–2010
    • Chinese Academy of Sciences
      • Laboratory of Photosynthesis and Environmental Biology
      Peping, Beijing, China
  • 2008
    • Dalian Institute of Chemical Physics
      Lü-ta-shih, Liaoning, China