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Untargeted metabolic profiling reveals geography as the strongest predictor of metabolic phenotypes of a cosmopolitan weed.

ABSTRACT: Plants produce a multitude of metabolites that contribute to their fitness and survival and play a role in local adaptation to environmental conditions. The effects of environmental variation are particularly well studied within the genus Plantago; however, previous studies have largely focused on targeting specific metabolites. Studies exploring metabolome-wide changes are lacking, and the effects of natural environmental variation and herbivory on the metabolomes of plants growing in situ remain unknown. An untargeted metabolomic approach using ultra-high-performance liquid chromatography-mass spectrometry, coupled with variation partitioning, general linear mixed modeling, and network analysis was used to detect differences in metabolic phenotypes of Plantago major in fifteen natural populations across Denmark. Geographic region, distance, habitat type, phenological stage, soil parameters, light levels, and leaf area were investigated for their relative contributions to explaining differences in foliar metabolomes. Herbivory effects were further investigated by comparing metabolomes from damaged and undamaged leaves from each plant. Geographic region explained the greatest number of significant metabolic differences. Soil pH had the second largest effect, followed by habitat and leaf area, while phenological stage had no effect. No evidence of the induction of metabolic features was found between leaves damaged by herbivores compared to undamaged leaves on the same plant. Differences in metabolic phenotypes explained by geographic factors are attributed to genotypic variation and/or unmeasured environmental factors that differ at the regional level in Denmark. A small number of specialized features in the metabolome may be involved in facilitating the success of a widespread species such as Plantago major into such wide range of environmental conditions, although overall resilience in the metabolome was found in response to environmental parameters tested. Untargeted metabolomic approaches have great potential to improve our understanding of how specialized plant metabolites respond to environmental change and assist in adaptation to local conditions.

SUBMITTER: Iwanycki Ahlstrand N

PROVIDER: S-EPMC6053570 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Untargeted metabolic profiling reveals geography as the strongest predictor of metabolic phenotypes of a cosmopolitan weed.

Iwanycki Ahlstrand Natalie N Havskov Reghev Nicoline N Markussen Bo B Bruun Hansen Hans Christian HC Eiriksson Finnur F FF Thorsteinsdóttir Margrét M Rønsted Nina N Barnes Christopher J CJ

Ecology and evolution 20180622 13

Plants produce a multitude of metabolites that contribute to their fitness and survival and play a role in local adaptation to environmental conditions. The effects of environmental variation are particularly well studied within the genus <i>Plantago</i>; however, previous studies have largely focused on targeting specific metabolites. Studies exploring metabolome-wide changes are lacking, and the effects of natural environmental variation and herbivory on the metabolomes of plants growing <i>in ...[more]

PMID: 30038777

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Project description:PurposeGastric cancer is a common tumor of the digestive system. Identification of potential molecules associated with gastric cancer progression and validation of potential biomarkers for gastric cancer diagnosis are very important. Thus, the aim of our study was to determine the serum metabolic characteristics of the serum of patients with chronic gastritis (CG) or gastric cancer (GC) and validate candidate biomarkers for disease diagnosis.Experimental designA total of 123 human serum samples from patients with CG or GC were collected for untargeted metabolomic analysis via UHPLC-Q-TOF/MS to determine characteristics of the serum. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and heat map were used for multivariate analysis. In addition, commercial databases were used to identify the pathways of metabolites. Differential metabolites were identified based on a heat map with a t-test threshold (p < 0.05), fold-change threshold (FC > 1.5 or FC < 2/3) and variable importance in the projection (VIP >1). Then, differential metabolites were analyzed by receiver operating characteristic (ROC) curve to determine candidate biomarkers. All samples were analyzed for fasting lipid profiles.ResultsAnalysis of serum metabolomic profiles indicated that most of the altered metabolic pathways in the three groups were associated with lipid metabolism (p < 0.05) and lipids and lipid-like molecules were the predominating metabolites within the top 100 differential metabolites (p < 0.05, FC > 1.5 or FC < 2/3, and VIP >1). Moreover, differential metabolites, including hexadecasphinganine, linoleamide, and N-Hydroxy arachidonoyl amine had high diagnostic performance according to PLS-DA. In addition, fasting lipid profile analysis showed the serum levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A1 (Apo-A1) were decreased concomitant to the progression of the progression of the disease compared with those in the control group (p < 0.05).ConclusionsThus, this study demonstrated that lipid metabolism may influence the development of CG to GC. Hexadecasphinganine, linoleamide, and N-Hydroxy arachidonoyl amine were selected as candidate diagnostic markers for CG and GC.

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Untargeted metabolic profiling reveals geography as the strongest predictor of metabolic phenotypes of a cosmopolitan weed.

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Untargeted metabolic profiling reveals geography as the strongest predictor of metabolic phenotypes of a cosmopolitan weed.

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