A targeted metabolomics approach toward understanding metabolic variations in rice under pesticide stress

Mahdavi, Vahideh; Farimani, Mahdi Moridi; Fathi, Fariba; Ghassempour, Alireza

doi:10.1016/j.ab.2015.02.021

Cited by 59 publications

(23 citation statements)

References 48 publications

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“…Compounds in leaves were tentatively identified with Automated Mass Spectral Deconvolution and Identification System (AMDIS), our in-house mass spectra library and the standard mass spectral database (National Institute of Standards and Technology, NIST, version 11.0). The signal/noise (S/N) of the tentatively identified compound was higher than 10 in the AMDIS and the compound shared greater than or equal to 80% similarity with the known compounds in the database, indicating that the metabolite identification was reliable [ 21 , 22 ].…”

Section: Methodsmentioning

confidence: 99%

Time-course metabolic profiling in alfalfa leaves under Phoma medicaginis infection

Fan

Creamer

2018

PLoS ONE

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Information on disease process and pathogenicity mechanisms is important for understanding plant disease. Spring black stem and leaf spot caused by the necrotrophic pathogen Phoma medicaginis var. medicaginis Malbr. & Roum causes large losses to alfalfa. However, till now, little is known about alfalfa-P. medicagnis interactions and the pathogenicity mechanisms of the pathogen. Here, alfalfa inoculated with P. medicaginis was subjected to GC-MS based metabolic profiling. The metabolic response in P. medicaginis-inoculated and mock-inoculated alfalfa leaves was assessed at 2, 4, 6, 8, 12, 16, 20, 24, 26 and 28 days post inoculation. In total, 101 peaks were detected in the control and inoculated groups, from which 70 metabolites were tentatively identified. Using multivariate analysis, 16 significantly regulated compounds, including amino acids, nitrogen-containing compounds and organic acids, polyols, fatty acids, and sugars were tentatively identified (Variable importance values, VIP>1.0 and p <0.05). Among these metabolites, the levels of malate, 5-oxoproline, palmitic acid and stearic acid were increased significantly in P. medicaginis-infected alfalfa leaves compared to the controls. In contrast, the levels ofγ-aminobutyric acid and 2-pyrrolidinone were significantly decreased in infected leaves compared to the controls. Further metabolic pathway analysis of the 16 significantly regulated compounds demonstrated that glycolysis, the tricarboxylic acid cycle, and β-oxidation of fatty acids were significantly induced in the alfalfa leaves at later stages of P. medicaginis infection. The strong induction of tricarboxylic acid cycle pathways at later infection stages caused by the pathogen may induce senescence in the alfalfa leaves, leading to plant death. However, intermediate metabolites of these metabolic pathways, and inositol phosphate, glutathione, the metabolic pathways of some amino acids accumulated rapidly and strongly at early stages of infection, which may enhance the ability of alfalfa to resist necrotrophic P. medicaginis disease. Understanding metabolic pathways is essential for understanding pathogenesis.

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Section: Methodsmentioning

confidence: 99%

Time-course metabolic profiling in alfalfa leaves under Phoma medicaginis infection

Fan

Creamer

2018

PLoS ONE

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“…However, unlike in other areas of agriculture research where metabolomics is widely used in crop trait selection, pesticide monitoring, crop breeding or crop evaluation [9; 10; 11; 12], the application of metabolomics to livestock research is somewhat less widely used or appreciated. This is surprising given the potential of metabolomics to address many important questions in livestock and animal science.…”

Section: Introductionmentioning

confidence: 99%

Livestock metabolomics and the livestock metabolome: A systematic review

Goldansaz¹,

Guo²,

Sajed³

et al. 2017

PLoS ONE

269

247

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Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

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“…Metabolomics has shown the utility to study rice plant biology and compounds that are linked to tolerance to different stressors, including abiotic stress [35], mineral toxicity [36], nutrient limitation [37,38], drought stress [39], and pesticide stress [40], suggesting extensive metabolome adaptability in rice. Metabolomics has also characterized natural and genetic variations in rice via the phenotyping of brown rice seeds [41], cooked brown rice [42], mature seeds [43], embryo (a fraction of rice bran) and endosperm (white rice) [44], and leaves [39].…”

Section: Introductionmentioning

confidence: 99%

Comparative Rice Bran Metabolomics across Diverse Cultivars and Functional Rice Gene–Bran Metabolite Relationships

et al. 2018

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Rice (Oryza sativa L.) processing yields ~60 million metric tons of bran annually. Rice genes producing bran metabolites of nutritional and human health importance were assessed across 17 diverse cultivars from seven countries using non-targeted metabolomics, and resulted in 378–430 metabolites. Gambiaka cultivar had the highest number and Njavara had the lowest number of metabolites. The 71 rice bran compounds of significant variation by cultivar included 21 amino acids, seven carbohydrates, two metabolites from cofactors and vitamins, 33 lipids, six nucleotides, and two secondary metabolites. Tryptophan, α-ketoglutarate, γ-tocopherol/β-tocopherol, and γ-tocotrienol are examples of bran metabolites with extensive cultivar variation and genetic information. Thirty-four rice bran components that varied between cultivars linked to 535 putative biosynthetic genes using to the OryzaCyc 4.0, Plant Metabolic Network database. Rice genes responsible for bran composition with animal and human health importance is available for rice breeding programs to utilize in crop improvement.

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A targeted metabolomics approach toward understanding metabolic variations in rice under pesticide stress

Cited by 59 publications

References 48 publications

Time-course metabolic profiling in alfalfa leaves under Phoma medicaginis infection

Time-course metabolic profiling in alfalfa leaves under Phoma medicaginis infection

Livestock metabolomics and the livestock metabolome: A systematic review

Comparative Rice Bran Metabolomics across Diverse Cultivars and Functional Rice Gene–Bran Metabolite Relationships

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