Literature DB >> 23532390

Metabolomics for unknown plant metabolites.

Ryo Nakabayashi1, Kazuki Saito.   

Abstract

In this article we discuss current trends in the techniques available for plant metabolomics. Chemical assignment of unknown metabolites leads to understanding of biosynthetic mechanisms at the gene level for genome-sequenced plants. Metabolomics using mass spectrometry has achieved innovative results in phytochemical genomics for primary and secondary metabolism in the model plant Arabidopsis thaliana by using publicly and commercially available information and standard compounds. However, finding a consolidated analytical technique for elucidation of structural information (e.g., elemental composition and structure) remains challenging. Recently, hyphenated analytical techniques and computer-assisted structural analysis with high-throughput and high-accuracy have been developing. Metabolite-driven approaches using such technology will be of central importance in phytochemical genomics.

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Year:  2013        PMID: 23532390     DOI: 10.1007/s00216-013-6869-2

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  19 in total

Review 1.  Integration of omics approaches to understand oil/protein content during seed development in oilseed crops.

Authors:  Manju Gupta; Pudota B Bhaskar; Shreedharan Sriram; Po-Hao Wang
Journal:  Plant Cell Rep       Date:  2016-10-27       Impact factor: 4.570

2.  A Metabolomic Approach to Target Compounds from the Asteraceae Family for Dual COX and LOX Inhibition.

Authors:  Daniela A Chagas-Paula; Tong Zhang; Fernando B Da Costa; RuAngelie Edrada-Ebel
Journal:  Metabolites       Date:  2015-07-08

3.  Discrimination of conventional and organic white cabbage from a long-term field trial study using untargeted LC-MS-based metabolomics.

Authors:  Axel Mie; Kristian Holst Laursen; K Magnus Åberg; Jenny Forshed; Anna Lindahl; Kristian Thorup-Kristensen; Marie Olsson; Pia Knuthsen; Erik Huusfeldt Larsen; Søren Husted
Journal:  Anal Bioanal Chem       Date:  2014-03-12       Impact factor: 4.142

4.  Coordinating metabolite changes with our perception of plant abiotic stress responses: emerging views revealed by integrative-omic analyses.

Authors:  Jordan D Radomiljac; James Whelan; Margaretha van der Merwe
Journal:  Metabolites       Date:  2013-09-06

5.  A metabolic profiling strategy for the dissection of plant defense against fungal pathogens.

Authors:  Konstantinos A Aliferis; Denis Faubert; Suha Jabaji
Journal:  PLoS One       Date:  2014-11-04       Impact factor: 3.240

6.  Global metabolic analyses identify key differences in metabolite levels between polymyxin-susceptible and polymyxin-resistant Acinetobacter baumannii.

Authors:  Mohd Hafidz Mahamad Maifiah; Soon-Ee Cheah; Matthew D Johnson; Mei-Ling Han; John D Boyce; Visanu Thamlikitkul; Alan Forrest; Keith S Kaye; Paul Hertzog; Anthony W Purcell; Jiangning Song; Tony Velkov; Darren J Creek; Jian Li
Journal:  Sci Rep       Date:  2016-02-29       Impact factor: 4.379

7.  Metabolome-scale de novo pathway reconstruction using regioisomer-sensitive graph alignments.

Authors:  Yoshihiro Yamanishi; Yasuo Tabei; Masaaki Kotera
Journal:  Bioinformatics       Date:  2015-06-15       Impact factor: 6.937

Review 8.  Metabolic pathway reconstruction strategies for central metabolism and natural product biosynthesis.

Authors:  Masaaki Kotera; Susumu Goto
Journal:  Biophys Physicobiol       Date:  2016-07-15

9.  Metabolome-scale prediction of intermediate compounds in multistep metabolic pathways with a recursive supervised approach.

Authors:  Masaaki Kotera; Yasuo Tabei; Yoshihiro Yamanishi; Ai Muto; Yuki Moriya; Toshiaki Tokimatsu; Susumu Goto
Journal:  Bioinformatics       Date:  2014-06-15       Impact factor: 6.937

10.  A batch correction method for liquid chromatography-mass spectrometry data that does not depend on quality control samples.

Authors:  Martin Rusilowicz; Michael Dickinson; Adrian Charlton; Simon O'Keefe; Julie Wilson
Journal:  Metabolomics       Date:  2016-02-18       Impact factor: 4.290

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