Effects of MeJA on Arabidopsis metabolome under endogenous JA deficiency

Cao, Jingjing; Li, Mengya; Chen, Jian; Liu, Pei; Li, Zhen

doi:10.1038/srep37674

Cited by 62 publications

(50 citation statements)

References 59 publications

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“…We performed ultrahigh performance LC-HRMS (UPLC-HRMS) analysis as described previously (Cao et al, 2016). Briefly, an UPLC-HRMS system (UPLC, ACQUITY i-Class, Waters; HRMS, Q-Exactive, Thermo Fisher Scientific) equipped with a heated electrospray ionization source was used for the analysis of metabolites in seedlings.…”

Section: Lc-hrms Analysismentioning

confidence: 99%

Evolutionary Metabolomics Identifies Substantial Metabolic Divergence between Maize and Its Wild Ancestor, Teosinte

Cao

Wang

et al. 2019

Plant Cell

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Maize (Zea mays subsp mays) was domesticated from its wild ancestor, teosinte (Zea mays subsp parviglumis). Maize's distinct morphology and adaptation to diverse environments required coordinated changes in various metabolic pathways. However, how the metabolome was reshaped since domestication remains poorly understood. Here, we report a comprehensive assessment of divergence in the seedling metabolome between maize and teosinte. In total, 461 metabolites exhibited significant divergence due to selection. Interestingly, teosinte and tropical and temperate maize, representing major stages of maize evolution, targeted distinct sets of metabolites. Alkaloids, terpenoids, and lipids were specifically targeted in the divergence between teosinte and tropical maize, while benzoxazinoids were specifically targeted in the divergence between tropical and temperate maize. To identify genetic factors controlling metabolic divergence, we assayed the seedling metabolome of a large maize-by-teosinte cross population. We show that the recent metabolic divergence between tropical and temperate maize tended to have simpler genetic architecture than the divergence between teosinte and tropical maize. Through integrating transcriptome data, we identified candidate genes contributing to metabolic divergence, many of which were under selection at the nucleotide and transcript levels. Through overexpression or mutant analysis, we verified the roles of Flavanone 3-hydroxylase1, Purple aleurone1, and maize terpene synthase1 in the divergence of their related biosynthesis pathways. Our findings not only provide important insights into domestication-associated changes in the metabolism but also highlight the power of combining omics data for trait dissection.

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Section: Lc-hrms Analysismentioning

confidence: 99%

Evolutionary Metabolomics Identifies Substantial Metabolic Divergence between Maize and Its Wild Ancestor, Teosinte

Cao

Wang

et al. 2019

Plant Cell

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“…Conversely, MeJA levels were maintained high till 4DAS, while these levels returned to control levels at 8DAS. The results indicates that the two different forms of JAs are presumably interchangeable and might share common signal transduction pathway in Pongamia during salt stress (Diallo et al, 2014; Mitra Baldwin, 2014; Cao et al, 2016; Li et al, 2017). An exogenous application of JAs reduced shoot growth, enhanced water uptake and cell wall synthesis in certain crop species (Kang et al, 2005; Uddin et al, 2013; Shahzad et al, 2015; Tavallali Karimi, 2019).…”

Section: Discussionmentioning

confidence: 85%

Systematic hormone-metabolite network provides insights of high salinity tolerance inPongamia pinnata(L.) pierre

Marriboina

Sharma

Sengupta

et al. 2020

Preprint

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Salinity stress results significant losses in plant productivity, and loss of cultivable lands. Although Pongamia pinnata is reported to be a salt tolerant semiarid tree crop, the adaptive mechanisms to saline environment are elusive. The present investigation describes alterations in hormonal and metabolic responses in correlation with physiological and molecular variations in leaves and roots of Pongamia at sea salinity level (3% NaCl) for 8 days. At physiological level, salinity induced adjustments in plant morphology, leaf gas exchange and ion accumulation patterns were observed. Our study also revealed that phytohormones including JAs and ABA play crucial role in promoting the salt adaptive strategies such as apoplasmic Na+ sequestration and cell wall lignification in leaves and roots of Pongamia. Correlation studies demonstrated that hormones including ABA, JAs and SA showed a positive interaction with selective compatible metabolites (sugars, polyols and organic acids) to aid in maintaining osmotic balance and conferring salt tolerance to Pongamia. At the molecular level, our data showed that differential expression of transporter genes as well as antioxidant genes regulate the ionic and ROS homeostasis in Pongamia. Collectively, these results shed new insights on an integrated physiological, structural, molecular and metabolic adaptations conferring salinity tolerance to Pongamia.High lightOur data, for the first time, provide new insights for an integrated molecular and metabolic adaptation conferring salinity tolerance in Pongamia. The present investigation describes alterations in hormonal and metabolic responses in correlation with physiological and molecular variations in Pongamia at sea salinity level (3% NaCl) for 8 days.

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“…Pathway analysis typically uses a subset of the data that has met a threshold level rather than the entire data set [11][12][13] . In our study we chose to use the 90 metabolites that were different based on the t-test between the groups rather than the more restrictive 33 metabolites that were identified after adjusting the p-value for false discovery rate.…”

Section: Discussionmentioning

confidence: 99%

1605 Rumen fluid metabolomics analysis associated with feed efficiency on crossbred steers

Artegoitia¹,

Foote²,

Lewis³

et al. 2016

Journal of Animal Science

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The rumen has a central role in the efficiency of digestion in ruminants. To identify potential differences in rumen function that lead to differences in average daily gain (ADG), rumen fluid metabolomic analysis by LC-MS and multivariate/univariate statistical analysis were used to identify differences in rumen metabolites. Individual feed intake and body-weight was measured on 144 steers during 105 d on a high concentrate ration. Eight steers with the greatest ADG and 8 steers with the least-ADG with dry matter intake near the population average were selected. Blood and rumen fluid was collected from the 16 steers 26 d before slaughter and at slaughter, respectively. As a result of the metabolomics analysis of rumen fluid, 33 metabolites differed between the ADG groups based on t-test, fold changes and partial least square discriminant analysis. These metabolites were primarily involved in linoleic and alpha-linolenic metabolism (impact-value 1.0 and 0.75, respectively; P < 0.05); both pathways were down-regulated in the greatest-ADG compared with least-ADG group. Ruminal biohydrogenation might be associated with the overall animal production. The fatty acids were quantified in rumen and plasma using targeted MS to validate and evaluate the simple combination of metabolites that effectively predict ADG.Improving production efficiency of cattle by increasing meat produced per amount of feed offered would result in economic and environmental benefits 1 . However, the physiological mechanisms and the shifts in the metabolic pathways that result in increased efficiency are not fully elucidated. Digestion and nutrient absorption are considered important sources of variation in cattle growth efficiency 2 . Changes in ruminal microbial communities have been associated with differences in feed efficiency of beef cattle 3, 4 . Hence, differences in feed efficiency might be related to changes in the metabolism in the cattle rumen.Metabolomics, has been a useful approach to characterize the metabolism of rumen fluid in dairy cows 5-8 . For instance, phenotype differences on residual feed intake were associated with specific ruminal microbes and targeted metabolic pathway in dairy cows 8 . By definition when feed efficiency is defined as residual feed intake there is a difference in feed intake between the groups. The differences in feed intake can greatly influence the microbial communities. We have chosen an alternative model that classifies steers based on divergent body weight gain at similar feed intakes in order to avoid changes associated with feed intake. We hypothesized that cattle that differed in ADG had differences in rumen metabolism. Therefore, untargeted metabolomics profile based on UPLC-quadrupole time of flight tandem mass spectrometry (qTOF-MS/MS) coupled to univariate and multivariate analysis was used to identify rumen metabolites that differed with feed efficiency and determine biomarkers in rumen fluid and plasma for ADG. ResultsCharacteristics of steers in the two groups. The DMI did not differ bet...

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Effects of MeJA on Arabidopsis metabolome under endogenous JA deficiency

Cited by 62 publications

References 59 publications

Evolutionary Metabolomics Identifies Substantial Metabolic Divergence between Maize and Its Wild Ancestor, Teosinte

Evolutionary Metabolomics Identifies Substantial Metabolic Divergence between Maize and Its Wild Ancestor, Teosinte

Systematic hormone-metabolite network provides insights of high salinity tolerance inPongamia pinnata(L.) pierre

1605 Rumen fluid metabolomics analysis associated with feed efficiency on crossbred steers

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