Dataset Information

Comprehensive Profiling and Inheritance Patterns of Metabolites in Foxtail Millet.

ABSTRACT: Metabolomics aims at determining a sample's metabolites profile and hence provides a straight functional statement of an organism's physiological condition. Here, we investigated comprehensive profiling, natural variation and species-specific accumulation of both primary and secondary metabolites in foxtail millet using LC-MS, and inheritance patterns of metabolome in millet hybrids. The application of a broad target metabolomics method facilitated the simultaneous identification and quantification of more than 300 metabolites. The metabolic analysis of these compounds, such as flavonoids, phenolamides, hydrocinnamoyl derivatives, vitamins and LPCs, revealed their developmentally controlled accumulation, and natural variation in different tissues/varieties. Species-specific accumulation of secondary metabolites was observed based on a comparative metabolic analysis between millet and rice, such as flavonoid O-rutinosides/neohesperidosides and malonylated flavonoid O-glycosides. In analyzing the metabolic variations between hybrid progenies and their parental lines, including a photothermo-sensitive genic male sterility line and five Zhangzagu varieties, metabolic overdominant, and dominant patterns of inheritance could be observed. For example, hydrocinnamoyl derivatives and feruloylated flavonoids were identified as over-parent heterosis (overdominant) metabolites in milet hybrids. Our work paves the way for developing predictors of hybrid performance and the future analysis of the biosynthesis and regulation of relevant metabolic pathways in millet.

SUBMITTER: Li S

PROVIDER: S-EPMC6277888 | biostudies-other | 2018

REPOSITORIES: biostudies-other

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Comprehensive Profiling and Inheritance Patterns of Metabolites in Foxtail Millet.

Li Shuangdong S Dong Xuekui X Fan Guangyu G Yang Qiaofeng Q Shi Jian J Wei Wei W Zhao Fang F Li Ning N Wang Xiaoming X Wang Feng F Feng Xiaolei X Zhang Xiaolei X Song Guoliang G Shi Gaolei G Zhang Wenying W Qiu Fengcang F Wang Dequan D Li Xinru X Zhang Yali Y Zhao Zhihai Z

Frontiers in plant science 20181126

Metabolomics aims at determining a sample's metabolites profile and hence provides a straight functional statement of an organism's physiological condition. Here, we investigated comprehensive profiling, natural variation and species-specific accumulation of both primary and secondary metabolites in foxtail millet using LC-MS, and inheritance patterns of metabolome in millet hybrids. The application of a broad target metabolomics method facilitated the simultaneous identification and quantificat ...[more]

PMID: 30542359

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Project description:AimsThis study aimed to identify the plasma metabolite fingerprint in patients with heart failure and to develop a prediction tool based on differential metabolites for predicting the response to cardiac resynchronization therapy (CRT).Methods and resultsWe prospectively recruited 32 healthy individuals and 42 consecutive patients with HF who underwent CRT between January 2018 and January 2019. Peripheral venous blood samples, clinical data, and echocardiographic signatures were collected before CRT implantation. Liquid chromatography-mass spectrometry was used to perform untargeted metabolites profiling for peripheral plasma under ESI+ and ESI- modes. After 6 month follow-up, patients were categorized as CRT responders or non-responders based on the alterations of echocardiographic characteristics. Compared with healthy individuals, patients with HF had distinct metabolomic profiles under both ESI+ and ESI- modes, featuring increased free fatty acids, carnitine, ?-hydroxybutyrate, and dysregulated lipids with heterogeneous alterations such as phosphatidylcholines (PCs) and sphingomyelins. Disparities of baseline metabolomics profile were observed between CRT responders and non-responders under ESI+ mode but not under ESI- mode. Further metabolites analysis revealed that a group of 20 PCs metabolites under ESI+ mode were major contributors to the distinct profiles between the two groups. We utilized LASSO regression model and identified a panel of four PCs metabolites [including PC (20:0/18:4), PC (20:4/20:0), PC 40:4, and PC (20:4/18:0)] as major predictors for CRT response prediction. Among our whole population (n = 42), receive operating characteristics analysis revealed that the four PCs-based model could nicely discriminate the CRT responders from non-responders (area under the curve = 0.906) with a sensitivity of 83.3% and a specificity of 90.0%. Cross-validation analysis also showed a satisfactory and robust performance of the model with the area under the curve of 0.910 in the training dataset and 0.880 in the testing dataset.ConclusionsPatients with HF held significantly altered plasma metabolomics profile compared with the healthy individuals. Within the HF group, the non-responders had a distinct plasma metabolomics profile in contrast to the responders to CRT, which was characterized by increased PCs species. A novel predictive model incorporating four PCs metabolites performed well in identifying CRT non-responders. These four PCs might severe as potential biomarkers for predicting CRT response. Further validations are needed in multi-centre studies with larger external cohorts.

Project description:While specialized metabolites are thought to mediate ecological interactions, the evolutionary processes driving chemical diversification, particularly among closely related lineages, remain poorly understood. Here, we examine the evolutionary dynamics governing the distribution of natural product biosynthetic gene clusters (BGCs) among 118 strains representing all nine currently named species of the marine actinobacterial genus Salinispora. While much attention has been given to the role of horizontal gene transfer (HGT) in structuring BGC distributions, we find that vertical descent facilitates interspecies BGC diversification over evolutionary timescales. Moreover, we identified a distinct phylogenetic signal among Salinispora species at both the BGC and metabolite level, indicating that specialized metabolism represents a conserved phylogenetic trait. Using a combination of genomic analyses and liquid chromatography-high-resolution tandem mass spectrometry (LC-MS/MS) targeting nine experimentally characterized BGCs and their small molecule products, we identified gene gain/loss events, constrained interspecies recombination, and other evolutionary processes associated with vertical inheritance as major contributors to BGC diversification. These evolutionary dynamics had direct consequences for the compounds produced, as exemplified by species-level differences in salinosporamide production. Together, our results support the concept that specialized metabolites, and their cognate BGCs, can represent phylogenetically conserved functional traits with chemical diversification proceeding in species-specific patterns over evolutionary time frames. IMPORTANCE Microbial natural products are traditionally exploited for their pharmaceutical potential, yet our understanding of the evolutionary processes driving BGC evolution and compound diversification remain poorly developed. While HGT is recognized as an integral driver of BGC distributions, we find that the effects of vertical inheritance on BGC diversification had direct implications for species-level specialized metabolite production. As such, understanding the degree of genetic variation that corresponds to species delineations can enhance natural product discovery efforts. Resolving the evolutionary relationships between closely related strains and specialized metabolism can also facilitate our understanding of the ecological roles of small molecules in structuring the environmental distribution of microbes.

Dataset Information

Comprehensive Profiling and Inheritance Patterns of Metabolites in Foxtail Millet.

Publications

Comprehensive Profiling and Inheritance Patterns of Metabolites in Foxtail Millet.

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