High-resolution magic angle spinning NMR studies for metabolic characterization of Arabidopsis thaliana mutants with enhanced growth characteristics.

Dieuwertje Augustijn,A Alia,Bert J Van Der Zaal,Niels Van Tol,Huub J M De Groot

doi:10.1371/journal.pone.0209695

Dieuwertje Augustijn, A Alia + Show 3 more

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https://doi.org/10.1371/journal.pone.0209695

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Journal: PloS one	Publication Date: Dec 31, 2018
Citations: 5	License type: CC BY 4.0

Affiliation: Leiden University, Leipzig University

Abstract

Developing smart crops which yield more biomass to meet the increasing demand for plant biomass has been an active area of research in last few decades. We investigated metabolic alterations in two Arabidopsis thaliana mutants with enhanced growth characteristics that were previously obtained from a collection of plant lines expressing artificial transcription factors. The metabolic profiles were obtained directly from intact Arabidopsis leaves using high-resolution magic angle spinning (HR-MAS) NMR. Multivariate analysis showed significant alteration of metabolite levels between the mutants and the wild-type Col-0. Interestingly, most of the metabolites that were reduced in the faster-growing mutants are generally involved in the defence against stress. These results suggest a growth-defence trade-off in the phenotypically engineered mutants. Our results further corroborate the idea that plant growth can be enhanced by suppressing defence pathways.

Highlights

During the last few decades, the demand for agricultural products has increased dramatically [1,2,3]
The larger rosette surface area phenotype of the VP16-02-003 and VP16-05-014 mutant was confirmed by determining the rosette surface area (RSA) at 28 days post germination (Fig 1)
The concentration of free amino acids, proteins, soluble sugars and starch was determined for extracts of leaves from the VP16-02-003 and VP16-05-014 mutant and Col-0 to get a broader overview of amino acids, sugars, protein and starch

Summary

Introduction

During the last few decades, the demand for agricultural products has increased dramatically [1,2,3]. A possible way to meet this demand is to develop smart crops, varieties which can give more yield with fewer inputs [5,6]. This would reduce the need for chemicals such as pesticides and fungicides. We have explored genome interrogation using zinc finger artificial transcription factors (ZF-ATFs) as a novel technique to drastically modify genome-wide transcription patterns and to generate novel phenotypes of interest in the model plant species Arabidopsis thaliana [9,10,11,12]

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