Joost J. B. Keurentjes

Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry

Untargeted metabolomics aims to gather information on as many metabolites as possible in biological systems by taking into account all information present in the data sets. Here we describe a detailed protocol for large-scale untargeted metabolomics of plant tissues, based on reversed phase liquid chromatography coupled to high-resolution mass spectrometry (LC-QTOF MS) of aqueous methanol extracts. Dedicated software, MetAlign, is used for automated baseline correction and alignment of all extracted mass peaks across all samples, producing detailed information on the relative abundance of thousands of mass signals representing hundreds of metabolites. Subsequent statistics and bioinformatics tools can be used to provide a detailed view on the differences and similarities between (groups of) samples or to link metabolomics data to other systems biology information, genetic markers and/or specific quality parameters. The complete procedure from metabolite extraction to assembly of a data matrix with aligned mass signal intensities takes about 6 days for 50 samples.

The genetics of plant metabolism

Variation for metabolite composition and content is often observed in plants. However, it is poorly understood to what extent this variation has a genetic basis. Here, we describe the genetic analysis of natural variation in the metabolite composition in Arabidopsis thaliana. Instead of focusing on specific metabolites, we have applied empirical untargeted metabolomics using liquid chromatography–time of flight mass spectrometry (LC-QTOF MS). This uncovered many qualitative and quantitative differences in metabolite accumulation between A. thaliana accessions. Only 13.4% of the mass peaks were detected in all 14 accessions analyzed. Quantitative trait locus (QTL) analysis of more than 2,000 mass peaks, detected in a recombinant inbred line (RIL) population derived from the two most divergent accessions, enabled the identification of QTLs for about 75% of the mass signals. More than one-third of the signals were not detected in either parent, indicating the large potential for modification of metabolic composition through classical breeding.

Sucrose-Specific Induction of Anthocyanin Biosynthesis in Arabidopsis Requires the MYB75/PAP1 Gene

Sugar-induced anthocyanin accumulation has been observed in many plant species. We observed that sucrose (Suc) is the most effective inducer of anthocyanin biosynthesis in Arabidopsis (Arabidopsis thaliana) seedlings. Other sugars and osmotic controls are either less effective or ineffective. Analysis of Suc-induced anthocyanin accumulation in 43 Arabidopsis accessions shows that considerable natural variation exists for this trait. The Cape Verde Islands (Cvi) accession essentially does not respond to Suc, whereas Landsberg erecta is an intermediate responder. The existing Landsberg erecta/Cvi recombinant inbred line population was used in a quantitative trait loci analysis for Suc-induced anthocyanin accumulation (SIAA). A total of four quantitative trait loci for SIAA were identified in this way. The locus with the largest contribution to the trait, SIAA1, was fine mapped and using a candidate gene approach, it was shown that the MYB75/PAP1 gene encodes SIAA1. Genetic complementation studies and analysis of a laboratory-generated knockout mutation in this gene confirmed this conclusion. Suc, in a concentration-dependent way, induces MYB75/PAP1 mRNA accumulation. Moreover, MYB75/PAP1 is essential for the Suc-mediated expression of the dihydroflavonol reductase gene. The SIAA1 locus in Cvi probably is a weak or loss-of-function MYB75/PAP1 allele. The C24 accession similarly shows a very weak response to Suc-induced anthocyanin accumulation encoded by the same locus. Sequence analysis showed that the Cvi and C24 accessions harbor mutations both inside and downstream of the DNA-binding domain of the MYB75/PAP1 protein, which most likely result in loss of activity.

Starch as a major integrator in the regulation of plant growth

Rising demand for food and bioenergy makes it imperative to breed for increased crop yield. Vegetative plant growth could be driven by resource acquisition or developmental programs. Metabolite profiling in 94 Arabidopsis accessions revealed that biomass correlates negatively with many metabolites, especially starch. Starch accumulates in the light and is degraded at night to provide a sustained supply of carbon for growth. Multivariate analysis revealed that starch is an integrator of the overall metabolic response. We hypothesized that this reflects variation in a regulatory network that balances growth with the carbon supply. Transcript profiling in 21 accessions revealed coordinated changes of transcripts of more than 70 carbon-regulated genes and identified 2 genes (myo-inositol-1-phosphate synthase, a Kelch-domain protein) whose transcripts correlate with biomass. The impact of allelic variation at these 2 loci was shown by association mapping, identifying them as candidate lead genes with the potential to increase biomass production.

What Has Natural Variation Taught Us about Plant Development, Physiology, and Adaptation?

Nearly 100 genes and functional polymorphisms underlying natural variation in plant development and physiology have been identified. In crop plants, these include genes involved in domestication traits, such as those related to plant architecture, fruit and seed structure and morphology, as well as yield and quality traits improved by subsequent crop breeding. In wild plants, comparable traits have been dissected mainly in Arabidopsis thaliana. In this review, we discuss the major contributions of the analysis of natural variation to our understanding of plant development and physiology, focusing in particular on the timing of germination and flowering, plant growth and morphology, primary metabolism, and mineral accumulation. Overall, functional polymorphisms appear in all types of genes and gene regions, and they may have multiple mutational causes. However, understanding this diversity in relation to adaptation and environmental variation is a challenge for which tools are now available.

Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci

Accessions of a plant species can show considerable genetic differences that are analyzed effectively by using recombinant inbred line (RIL) populations. Here we describe the results of genome-wide expression variation analysis in an RIL population of Arabidopsis thaliana. For many genes, variation in expression could be explained by expression quantitative trait loci (eQTLs). The nature and consequences of this variation are discussed based on additional genetic parameters, such as heritability and transgression and by examining the genomic position of eQTLs versus gene position, polymorphism frequency, and gene ontology. Furthermore, we developed an approach for genetic regulatory network construction by combining eQTL mapping and regulator candidate gene selection. The power of our method was shown in a case study of genes associated with flowering time, a well studied regulatory network in Arabidopsis. Results that revealed clusters of coregulated genes and their most likely regulators were in agreement with published data, and unknown relationships could be predicted.

System-wide molecular evidence for phenotypic buffering in Arabidopsis

We profiled 162 lines of Arabidopsis for variation in transcript, protein and metabolite abundance using mRNA microarrays, two-dimensional polyacrylamide gel electrophoresis, gas chromatography time-of-flight mass spectrometry, liquid chromatography quadrupole time-of-flight mass spectrometry, and proton nuclear magnetic resonance. We added all publicly available phenotypic data from the same lines and mapped quantitative trait loci (QTL) for 40,580 molecular and 139 phenotypic traits. We found six QTL hot spots with major, system-wide effects, suggesting there are six breakpoints in a system otherwise buffered against many of the 500,000 SNPs.

Development of a near-isogenic line population of Arabidopsis thaliana and comparison of mapping power with a recombinant inbred line population

In Arabidopsis recombinant inbred line (RIL) populations are widely used for quantitative trait locus (QTL) analyses. However, mapping analyses with this type of population can be limited because of the masking effects of major QTL and epistatic interactions of multiple QTL. An alternative type of immortal experimental population commonly used in plant species are sets of introgression lines. Here we introduce the development of a genomewide coverage near-isogenic line (NIL) population of Arabidopsis thaliana, by introgressing genomic regions from the Cape Verde Islands (Cvi) accession into the Landsberg erecta (Ler) genetic background. We have empirically compared the QTL mapping power of this new population with an already existing RIL population derived from the same parents. For that, we analyzed and mapped QTL affecting six developmental traits with different heritability. Overall, in the NIL population smaller-effect QTL than in the RIL population could be detected although the localization resolution was lower. Furthermore, we estimated the effect of population size and of the number of replicates on the detection power of QTL affecting the developmental traits. In general, population size is more important than the number of replicates to increase the mapping power of RILs, whereas for NILs several replicates are absolutely required. These analyses are expected to facilitate experimental design for QTL mapping using these two common types of segregating populations.

Control of Fusarium Wilt of Radish by Combining Pseudomonas putida Strains that have Different Disease-Suppressive Mechanisms

ABSTRACT Biological control of soilborne plant pathogens in the field has given variable results. By combining specific strains of microorganisms, multiple traits antagonizing the pathogen can be combined and this may result in a higher level of protection. Pseudomonas putida WCS358 suppresses Fusarium wilt of radish by effectively competing for iron through the production of its pseudobactin siderophore. However, in some bioassays pseudobactin-negative mutants of WCS358 also suppressed disease to the same extent as WCS358, suggesting that an, as yet unknown, additional mechanism may be operative in this strain. P. putida strain RE8 induced systemic resistance against fusarium wilt. When WCS358 and RE8 were mixed through soil together, disease suppression was significantly enhanced to approximately 50% as compared to the 30% reduction for the single strain treatments. Moreover, when one strain failed to suppress disease in the single application, the combination still resulted in disease control. The enhanced disease suppression by the combination of P. putida strains WCS358 and RE8 is most likely the result of the combination of their different disease-suppressive mechanisms. These results demonstrate that combining biocontrol strains can lead to more effective, or at least, more reliable biocontrol of fusarium wilt of radish.

Metabolic Networks: How to Identify Key Components in the Regulation of Metabolism and Growth

Plants display enormous diversity in their metabolism. Although the biosynthesis and function of the myriad plant metabolites have been studied for decades, we have little understanding of the interactions between metabolites, metabolite signaling, interactions with development, and the role of