Literature DB >> 35113397

The Contribution of Metabolomics to Systems Biology: Current Applications Bridging Genotype and Phenotype in Plant Science.

Marina C M Martins1, Valeria Mafra2, Carolina C Monte-Bello3,4,5, Camila Caldana5.   

Abstract

Metabolomics is a valuable approach used to acquire comprehensive information about the set of metabolites in a cell or tissue, enabling a functional screen of the cellular activities in biological systems. Although metabolomics provides a more immediate and dynamic picture of phenotypes in comparison to the other omics, it is also the most complicated to measure because no single analytical technology can capture the extraordinary complexity of metabolite diversity in terms of structure and physical properties. Metabolomics has been extensively employed for a wide range of applications in plant science, which will be described in detail in this chapter. Among them, metabolomics is used for discriminating patterns of plant responses to genetic and environmental perturbations, as diagnostics and prediction tool to elucidate the function of genes for important and complex agronomic traits in crop species, and flux measurements are used to dissect the structure and regulatory properties of metabolic networks.
© 2021. Springer Nature Switzerland AG.

Entities:  

Keywords:  Flux; Metabolism; Metabolites; Networks; Phenotype

Mesh:

Year:  2021        PMID: 35113397     DOI: 10.1007/978-3-030-80352-0_5

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  140 in total

1.  KNApSAcK family databases: integrated metabolite-plant species databases for multifaceted plant research.

Authors:  Farit Mochamad Afendi; Taketo Okada; Mami Yamazaki; Aki Hirai-Morita; Yukiko Nakamura; Kensuke Nakamura; Shun Ikeda; Hiroki Takahashi; Md Altaf-Ul-Amin; Latifah K Darusman; Kazuki Saito; Shigehiko Kanaya
Journal:  Plant Cell Physiol       Date:  2011-11-28       Impact factor: 4.927

Review 2.  Quantifying plant phenotypes with isotopic labeling & metabolic flux analysis.

Authors:  Doug K Allen
Journal:  Curr Opin Biotechnol       Date:  2015-11-21       Impact factor: 9.740

Review 3.  An introduction to liquid chromatography-mass spectrometry instrumentation applied in plant metabolomic analyses.

Authors:  J William Allwood; Royston Goodacre
Journal:  Phytochem Anal       Date:  2010 Jan-Feb       Impact factor: 3.373

Review 4.  Multidimensional approaches for studying plant defence against insects: from ecology to omics and synthetic biology.

Authors:  Pankaj Barah; Atle M Bones
Journal:  J Exp Bot       Date:  2014-12-22       Impact factor: 6.992

Review 5.  Tracking the metabolic pulse of plant lipid production with isotopic labeling and flux analyses: Past, present and future.

Authors:  Doug K Allen; Philip D Bates; Henrik Tjellström
Journal:  Prog Lipid Res       Date:  2015-03-13       Impact factor: 16.195

6.  13C labeling analysis of sugars by high resolution-mass spectrometry for metabolic flux analysis.

Authors:  Sébastien Acket; Anthony Degournay; Franck Merlier; Brigitte Thomasset
Journal:  Anal Biochem       Date:  2017-02-14       Impact factor: 3.365

7.  Transcript, protein and metabolite temporal dynamics in the CAM plant Agave.

Authors:  Paul E Abraham; Hengfu Yin; Anne M Borland; Deborah Weighill; Sung Don Lim; Henrique Cestari De Paoli; Nancy Engle; Piet C Jones; Ryan Agh; David J Weston; Stan D Wullschleger; Timothy Tschaplinski; Daniel Jacobson; John C Cushman; Robert L Hettich; Gerald A Tuskan; Xiaohan Yang
Journal:  Nat Plants       Date:  2016-11-21       Impact factor: 15.793

8.  Regulation of Primary Metabolism in Response to Low Oxygen Availability as Revealed by Carbon and Nitrogen Isotope Redistribution.

Authors:  Carla António; Carola Päpke; Marcio Rocha; Houssein Diab; Anis M Limami; Toshihiro Obata; Alisdair R Fernie; Joost T van Dongen
Journal:  Plant Physiol       Date:  2015-11-09       Impact factor: 8.340

Review 9.  Metabolomics of Disease Resistance in Crops.

Authors:  Vicent Arbona; Aurelio Gómez-Cadenas
Journal:  Curr Issues Mol Biol       Date:  2015-09-11       Impact factor: 2.081

Review 10.  Statistical methods for the analysis of high-throughput metabolomics data.

Authors:  Jörg Bartel; Jan Krumsiek; Fabian J Theis
Journal:  Comput Struct Biotechnol J       Date:  2013-03-22       Impact factor: 7.271

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.