一氧化氮参与盐胁迫下长春花酚类代谢的调控研究

为研究外源一氧化氮(NO)调控盐胁迫下长春花中酚类化合物的响应,采用液相色谱—质谱联用(LCMS)技术靶向分析梯度浓度硝普纳(SNP)处理对盐胁迫下长春花幼苗根、茎、花、叶4个部位中酚类化合物组分及含量水平的变化。结果共鉴定出L-苯丙氨酸和18种酚类物质,C6C1类5种、C6C3类5种、C6C3C6类8种,其中原儿茶酸、绿原酸、槲皮素在长春花根、茎、花、叶4个部位中均存在;不同浓度SNP处理后长春花不同部位酚类化合物响应积累明显不同,其中C6C1和C6C3小分子酚酸类化合物主要积累在根和茎中,C3C6C3类主要富集在花和叶中;L-苯丙氨酸在茎、叶中相对含量较高,盐胁迫下茎中含量显著升高,且随外源NO浓度增大呈下降趋势。外源NO影响盐胁迫下植物器官中酚类化合物的积累和变化,其中根和茎响应敏感,从种类和相对含量的角度,茎和叶更适合检测酚类化合物。     

Absolute Configuration of (+)-1-Acetoxy-p-menth-3-one Isolated from Essential Oil of Mentha gentilis (L.)

The most effective electro-energizing fermentation (E-E F) conditions for l-glutamate (l-Glu) production by Brevibacterium flavum No. 2247 were determined. The adding of 0.01 mm neutral red at the beginning of cultivation was found most effective. A 1.5 V direct current was applied to the culture broth at 6~8 hr after inoculation in the cathode compartment, l-Glu was produced at 51.0 mg per ml, and this is about a 15 % increase in yield compared to the yield of the not electro-energizing (E-E) control (44.3 mg/ml).     

Surface metabolites of the brown alga Taonia atomaria have the ability to regulate epibiosis

This study aimed to improve understanding of the strategies developed by the Mediterranean seaweed Taonia atomaria to chemically control bacterial epibiosis. An experimental protocol was optimized to specifically extract algal surface-associated metabolites by a technique involving dipping in organic solvents whilst the integrity of algal cell membranes was assessed by fluorescent microscopy. This methodology was validated using mass spectrometry-based profiles of algal extracts and analysis of their principal components, which led to the selection of methanol as the extraction solvent with a maximum exposure time of 15 s. Six compounds (A–F) were identified in the resulting surface extracts. Two of these surface-associated compounds (B and C) showed selective anti-adhesion properties against reference bacterial strains isolated from artificial surfaces while remaining inactive against epibiotic bacteria of T. atomaria. Such specificity was not observed for commercial antifouling biocides and other molecules identified in the surface or whole-cell extracts of T. atomaria.     

Comparative analysis of metabolome of rice seeds at three developmental stages using a recombinant inbred line population

Plants are considered an important food and nutrition source for humans. Despite advances in plant seed metabolomics, knowledge about the genetic and molecular bases of rice seed metabolomes at different developmental stages is still limited. Here, using Zhenshan 97 (ZS97) and Minghui 63 (MH63), we performed a widely targeted metabolic profiling in seeds during grain filling, mature seeds and germinating seeds. The diversity between MH63 and ZS97 was characterized in terms of the content of metabolites and the metabolic shifting across developmental stages. Taking advantage of the ultra‐high‐density genetic map of a population of 210 recombinant inbred lines (RILs) derived from a cross between ZS97 and MH63, we identified 4681 putative metabolic quantitative trait loci (mQTLs) in seeds across the three stages. Further analysis of the mQTLs for the codetected metabolites across the three stages revealed that the genetic regulation of metabolite accumulation was closely related to developmental stage. Using in silico analyses, we characterized 35 candidate genes responsible for 30 structurally identified or annotated compounds, among which LOC_Os07g04970 and LOC_Os06g03990 were identified to be responsible for feruloylserotonin and l ‐asparagine content variation across populations, respectively. Metabolite?agronomic trait association and colocation between mQTLs and phenotypic quantitative trait loci (pQTLs) revealed the complexity of the metabolite?agronomic trait relationship and the corresponding genetic basis.     

Simplified Intestinal Microbiota to Study Microbe-Diet-Host Interactions in a Mouse Model

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A structure-based anatomy of the E.coli metabolome

The Escherichia coli metabolome has been characterised using the two-dimensional structures of 745 metabolites, obtained from the EcoCyc and KEGG databases. Physicochemical properties of the metabolome have been calculated to provide an overview of this set of cognate ligands. A library of fragments commonly found among these molecules has been employed to reveal the main constituents of metabolites, and to assist a broad classification of the metabolome into biochemically relevant classes. Fragment-based fingerprints reveal the metabolome as a continuum in the two-dimensional structural space, where clusters of molecules sharing similar scaffolds can be identified, but are generally overlapping. Nucleotide, carbohydrate and amino acid-like molecules are the most prominent, but at high levels of similarity, a more detailed classification is possible. Classification schemes for the metabolome are a promising tool for understanding the chemical diversity of the metabolome. When used in conjunction with existing classifications of the proteome, they can help to elucidate the binding preferences and promiscuity of proteins and their cognate substrates.