Literature DB >> 33609206

LC-MS untargeted metabolomics assesses the delayed response of glufosinate treatment of transgenic glufosinate resistant (GR) buffalo grasses (Stenotaphrum secundatum L.).

Siriwat Boonchaisri1,2, Simone Rochfort3,4, Trevor Stevenson2, Daniel A Dias5.   

Abstract

INTRODUCTION: Glufosinate resistant (GR) buffalo grasses were genetically modified to resist the broad-spectrum herbicide, glufosinate by inserting a novel pat gene into its genome. This modification results in a production of additional phosphinothricin acetyltransferase (PAT) to detoxify the deleterious effects of glufosinate. The GR grasses and its associated herbicide form a modern, weeding program, to eradicate obnoxious weeds in turf lawn without damaging the grasses at relatively low costs and labor. As with several principal crops which are genetically modified to improve agricultural traits, biosafety of the GR buffalo grasses is inevitably expected to become a public concern. For the first time, we had previously examined the metabolome of glufosinate-resistant buffalo grasses, using a GC-MS untargeted approach to assess the risk of GR as well as identify any pleotropic effects arising from the genetically modification process. In this paper, an untargeted high-resolution LC-MS (LC-HRMS) untargeted metabolomics approach was carried out to complement our previous findings with respect to GR and wild type (WT) buffalo grasses.
OBJECTIVE: One of the major aims of this present work was to compare GR to WT buffalo grasses by including the detection of the secondary metabolome and determine any unprecedented metabolic changes.
METHODS: Eight-week old plants of 4 GR buffalo grasses, (93-1A, 93-2B, 93-3 C and 93-5A) and 3 wild type varieties (WT 8-4A, WT 9-1B and WT 9-1B) were submerged in either 5 % v/v of glufosinate or distilled water 3 days prior to a LC-HRMS based untargeted metabolomics analysis (glufosinate-treated or control, samples, respectively). An Ultra-High-Performance Liquid Chromatography (UHPLC) system coupled to a Velos Pro Orbitrap mass spectrometer system was employed to holistically measure the primary and secondary metabolome of both GR and WT buffalo grasses either treated with or without glufosinate and subsequently apply several bioinformatic tools including the automated pathway analysis algorithm, mummichog.
RESULTS: LC-HRMS untargeted based metabolomics clearly identified that the global metabolite pools of both GR and WT cultivars were highly similar, providing strong, supporting evidence of substantial equivalence between the GR and WT varieties. These findings indicate that if any associated risks to these GR grasses were somehow present, the risk would be within those acceptable ranges present in the WT. Additionally, mummichog-based pathway analysis indicated that phenylalanine metabolism and the TCA cycle were significantly impacted by glufosinate treatment in the WT cultivar. It was possible that alterations in the relative concentrations of several intermediates in these pathways were likely due to glufosinate-induced production of secondary metabolites to enhance plant defense mechanisms against herbicidal stress at the expense of primary metabolism.
CONCLUSIONS: GR buffalo grasses were found to be near identical to its WT comparator based on this complementary LC-HRMS based untargeted metabolomics. Therefore, these results further support the safe use of these GR buffalo grasses with substantial evidence. Interestingly, despite protected by PAT, GR buffalo grasses still demonstrated the response to glufosinate treatment by up-regulating some secondary metabolite-related pathways.

Entities:  

Keywords:  Buffalo grasses; Glufosinate resistance; High resolution liquid chromatography–mass spectrometry; Untargeted metabolomics

Year:  2021        PMID: 33609206     DOI: 10.1007/s11306-021-01776-5

Source DB:  PubMed          Journal:  Metabolomics        ISSN: 1573-3882            Impact factor:   4.290


  24 in total

1.  Utilization of GC-MS untargeted metabolomics to assess the delayed response of glufosinate treatment of transgenic herbicide resistant (HR) buffalo grasses (Stenotaphrum secundatum L.).

Authors:  Siriwat Boonchaisri; Trevor Stevenson; Daniel A Dias
Journal:  Metabolomics       Date:  2020-01-27       Impact factor: 4.290

Review 2.  Roles for glutathione transferases in plant secondary metabolism.

Authors:  David P Dixon; Mark Skipsey; Robert Edwards
Journal:  Phytochemistry       Date:  2010-01-14       Impact factor: 4.072

Review 3.  Multiple roles for plant glutathione transferases in xenobiotic detoxification.

Authors:  Ian Cummins; David P Dixon; Stefanie Freitag-Pohl; Mark Skipsey; Robert Edwards
Journal:  Drug Metab Rev       Date:  2011-03-22       Impact factor: 4.518

4.  Comparison of two GM maize varieties with a near-isogenic non-GM variety using transcriptomics, proteomics and metabolomics.

Authors:  Eugenia Barros; Sabine Lezar; Mikko J Anttonen; Jeroen P van Dijk; Richard M Röhlig; Esther J Kok; Karl-Heinz Engel
Journal:  Plant Biotechnol J       Date:  2010-02-03       Impact factor: 9.803

5.  Degradation of glutathione S-conjugates in Physcomitrella patens is initiated by cleavage of glycine.

Authors:  Corinna Bleuel; Dirk Wesenberg; Andreas J Meyer
Journal:  Plant Cell Physiol       Date:  2011-05-25       Impact factor: 4.927

Review 6.  Applications of stable isotope-based metabolomics and fluxomics toward synthetic biology of cyanobacteria.

Authors:  Piyoosh Kumar Babele; Jamey D Young
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2019-12-09

7.  Molecular characterization of a heteromeric ATP-citrate lyase that generates cytosolic acetyl-coenzyme A in Arabidopsis.

Authors:  Beth L Fatland; Jinshan Ke; Marc D Anderson; Wieslawa I Mentzen; Li Wei Cui; C Christy Allred; Jerry L Johnston; Basil J Nikolau; Eve Syrkin Wurtele
Journal:  Plant Physiol       Date:  2002-10       Impact factor: 8.340

Review 8.  Recent developments in metabolomics-based research in understanding transgenic grass metabolism.

Authors:  Siriwat Boonchaisri; Simone Rochfort; Trevor Stevenson; Daniel A Dias
Journal:  Metabolomics       Date:  2019-03-15       Impact factor: 4.290

9.  The rise and future of glyphosate and glyphosate-resistant crops.

Authors:  Jerry M Green
Journal:  Pest Manag Sci       Date:  2016-11-29       Impact factor: 4.845

10.  Progress in Metabolomics Standardisation and its Significance in Future Clinical Laboratory Medicine.

Authors:  Daniel A Dias; Therese Koal
Journal:  EJIFCC       Date:  2016-12-01
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  1 in total

1.  [A novel method for efficient screening and annotation of important pathway-associated metabolites based on the modified metabolome and probe molecules].

Authors:  Zaifang Li; Fujian Zheng; Yueyi Xia; Xiuqiong Zhang; Xinxin Wang; Chunxia Zhao; Xinjie Zhao; Xin Lu; Guowang Xu
Journal:  Se Pu       Date:  2022-09
  1 in total

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