Analytical Method Evaluation and Discovery of Variation within Maize Varieties in the Context of Food Safety: Transcript Profiling and Metabolomics

Zeng, Weiqing; Hazebroek, Jan; Beatty, Mary; Hayes, Kevin; Ponte, Christine; Maxwell, Carl A.; Zhong, Cathy Xiaoyan

doi:10.1021/jf405652j

Cited by 13 publications

(8 citation statements)

References 62 publications

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“…A recent application of plant metabolomics that has already been implemented in biotechnology and seed companies is the assessment of metabolic diversity within their crop core population or genetic lineage. This has been done for instance by Monsanto ® in soybean (Kusano et al 2015 ; Harrigan et al 2015 ) and maize (Venkatesh et al 2016 ) as well as by Pioneer ® in the latter species (Baniasadi et al 2014 ; Zeng et al 2014 ; Asiago et al 2012 ). Authors underline the potential of metabolomics to separate genetic and environmental effects on crop diversity (Venkatesh et al 2016 ; Baniasadi et al 2014 ) or for substantial equivalence studies of genetically modified (GM) genotypes (Harrigan et al 2015 ; Baniasadi et al 2014 ; Asiago et al 2012 ).…”

Section: Why Use Metabolic Markers?mentioning

confidence: 99%

“…Authors underline the potential of metabolomics to separate genetic and environmental effects on crop diversity (Venkatesh et al 2016 ; Baniasadi et al 2014 ) or for substantial equivalence studies of genetically modified (GM) genotypes (Harrigan et al 2015 ; Baniasadi et al 2014 ; Asiago et al 2012 ). These results could be used to improve acceptance of GMOs and might also be used for regulatory purposes (Zeng et al 2014 ). These companies have all the necessary tools in house to use metabolic data for breeding.…”

Section: Why Use Metabolic Markers?mentioning

confidence: 99%

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Fortune telling: metabolic markers of plant performance

et al. 2016

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Background In the last decade, metabolomics has emerged as a powerful diagnostic and predictive tool in many branches of science. Researchers in microbes, animal, food, medical and plant science have generated a large number of targeted or non-targeted metabolic profiles by using a vast array of analytical methods (GC–MS, LC–MS, 1H-NMR….). Comprehensive analysis of such profiles using adapted statistical methods and modeling has opened up the possibility of using single or combinations of metabolites as markers. Metabolic markers have been proposed as proxy, diagnostic or predictors of key traits in a range of model species and accurate predictions of disease outbreak frequency, developmental stages, food sensory evaluation and crop yield have been obtained.Aim of review(i) To provide a definition of plant performance and metabolic markers, (ii) to highlight recent key applications involving metabolic markers as tools for monitoring or predicting plant performance, and (iii) to propose a workable and cost-efficient pipeline to generate and use metabolic markers with a special focus on plant breeding.Key messageUsing examples in other models and domains, the review proposes that metabolic markers are tending to complement and possibly replace traditional molecular markers in plant science as efficient estimators of performance.

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Section: Why Use Metabolic Markers?mentioning

confidence: 99%

Section: Why Use Metabolic Markers?mentioning

confidence: 99%

Fortune telling: metabolic markers of plant performance

et al. 2016

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“…Extensive applications of this method in rice (De and Nag, 2014;Frank et al, 2007;Frank et al, 2012a), black gram (Na Jom et al, 2015) and mung beans (Na Jom et al, 2011) have demonstrated its utility in food crop analysis. Gas chromatography-mass spectrometry (GC-MS)-based metabolite profiling can evaluate the chemical constituents of corn with regard to genetic and environmental factors (Frank et al, 2012b), agronomic practices (Röhlig and Engel, 2010) and breeding strategies for crops (Zeng et al, 2014). Comparably, the cost-effective gas chromatography-flame ionization detection (GC-FID) based metabolite profiling approach has also been applied in food crops (Frank et al, 2007;Na Jom et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Metabolite profiles of commercial colored Thai corn hybrids (Zea mays L.)

2019

ANRES

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Corn hybrids (Zea mays L.) of various kernel colorizations are continually being developed due to increased demand, acceptance and utilization among consumers. A broad range gas chromatographyflame ionization detector-based metabolite profiling method was used to investigate the low molecular weight constituents of five colored Thai corn hybrids grown simultaneously at the same location and in the same season. The results showed that the majority of lipid metabolites was higher in the variety 7566 than the others as well as fraction IV (acids) metabolites. Notably, this variety also contained a high amount of nutritionally important phytosterols (sitostanol, campesterol, stigmasterol, ∆7-campestenol). Principal component analysis and hierarchical cluster analysis separated the varieties into three distinct groups based on metabolite abundance. Importantly, there was no separation based on kernel color. No previous research regarding differentiating colored Thai corn hybrids using metabolite profiling currently exists; thus, this method can provide valuable information for crop improvement, nutritional analysis and functional quality assessment within the food industry and nutritional sciences.

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“…Metabolomics has been used to identify the effect of different cultivation environments on plants and for the quality evaluation of agricultural products ( Kusano et al, 2011b ; Zeng et al, 2014 ; Sung et al, 2015 ; Garcia et al, 2016 ; Ya-Qin et al, 2017 ). According to Lisec et al (2006) , plants can produce approximately 200,000 metabolites and specific metabolites are produced in different plant species ( Kusano et al, 2011b , 2014a , b ), even in cultivars and ecotypes ( Sulpice et al, 2009 ).…”

Section: Introductionmentioning

confidence: 99%

Metabolomic Evaluation of the Quality of Leaf Lettuce Grown in Practical Plant Factory to Capture Metabolite Signature

et al. 2018

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Vegetables produce metabolites that affect their taste and nutritional value and compounds that contribute to human health. The quality of vegetables grown in plant factories under hydroponic cultivation, e.g., their sweetness and softness, can be improved by controlling growth factors including the temperature, humidity, light source, and fertilizer. However, soil is cheaper than hydroponic cultivation and the visual phenotype of vegetables grown under the two conditions is different. As it is not clear whether their metabolite composition is also different, we studied leaf lettuce raised under the hydroponic condition in practical plant factory and strictly controlled soil condition. We chose two representative cultivars, “black rose” (BR) and “red fire” (RF) because they are of high economic value. Metabolite profiling by comprehensive gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) resulted in the annotation of 101 metabolites from 223 peaks detected by GC-MS; LC-MS yielded 95 peaks. The principal component analysis (PCA) scatter plot showed that the most distinct separation patterns on the first principal component (PC1) coincided with differences in the cultivation methods. There were no clear separations related to cultivar differences in the plot. PC1 loading revealed the discriminant metabolites for each cultivation method. The level of amino acids such as lysine, phenylalanine, tryptophan, and valine was significantly increased in hydroponically grown leaf lettuce, while soil-cultivation derived leaf lettuce samples contained significantly higher levels of fatty-acid derived alcohols (tetracosanol and hexacosanol) and lettuce-specific sesquiterpene lactones (lactucopicrin-15-oxalate and 15-deoxylactucin-8-sulfate). These findings suggest that the metabolite composition of leaf lettuce is primarily affected by its cultivation condition. As the discriminant metabolites reveal important factors that contribute to the nutritional value and taste characteristics of leaf lettuce, we performed comprehensive metabolite profiling to identify metabolite compositions, i.e., metabolite signature, that directly improve its quality and value.

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Analytical Method Evaluation and Discovery of Variation within Maize Varieties in the Context of Food Safety: Transcript Profiling and Metabolomics

Cited by 13 publications

References 62 publications

Fortune telling: metabolic markers of plant performance

Fortune telling: metabolic markers of plant performance

Metabolite profiles of commercial colored Thai corn hybrids (Zea mays L.)

Metabolomic Evaluation of the Quality of Leaf Lettuce Grown in Practical Plant Factory to Capture Metabolite Signature

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