Plantmetabolomics.org: mass spectrometry-based Arabidopsis metabolomics--database and tools update

Abstract

The PlantMetabolomics (PM) database (http://www.plantmetabolomics.org) contains comprehensive targeted and untargeted mass spectrum metabolomics data for Arabidopsis mutants across a variety of metabolomics platforms. The database allows users to generate hypotheses about the changes in metabolism for mutants with genes of unknown function. Version 2.0 of PlantMetabolomics.org currently contains data for 140 mutant lines along with the morphological data. A web-based data analysis wizard allows researchers to select preprocessing and data-mining procedures to discover differences between mutants. This community resource enables researchers to formulate models of the metabolic network of Arabidopsis and enhances the research community's ability to formulate testable hypotheses concerning gene functions. PM features new web-based tools for data-mining analysis, visualization tools and enhanced cross links to other databases. The database is publicly available. PM aims to provide a hypothesis building platform for the researchers interested in any of the mutant lines or metabolites.

Figure 1.

(A) Log-ratio plot of a metabolite (PA 34:2), where each point shows the ratio of the concentration of the given metabolite in mutant samples versus the wild-type samples. The highlighted mutant line (SALK_040250) looks interesting as it is away from the central vertical axis and thus depicts difference between mutant samples and the wild-type samples. (B) The user can instantly access the stereomicroscopic images for this mutant and compare them with wild-type samples. Seed images at ×250 zoom of mutant's seeds look a little distorted as compared to the wild-type seeds (Seed image courtesy of Jennifer Robinson). (C) The user can also access the details of the metabolites including cross links to other databases. (D) Clicking on any of the points in the log-ratio plot in (A) shows the log-ratio plot of all the metabolites for that mutant. For example, some fatty acids including tetradecanoic acid look interesting for this mutant as they are away from the central vertical axis and show large fold change between the wild type and mutant samples.

Figure 2.

(A) Hierarchical clustering of lipidomics data from the Welti Lab compares SALK_040250 (At1g61720) mutant line with wild-type samples using Euclidean distance and average linkage method. (B) PCA loadings plot of the first 2 PCs shows that the wild type and mutant are not linearly separable. (C) Important metabolites for the classification between wild type and the mutant line using the Random Forest tool shows that the most important variables are glycerophospholipids with chain lengths of 34 and 36. (D) MDS plot of the mutant and wild-type samples using the Manhattan distance measure that shows that the mutant and wild type are not separable and that there is an outlier in the data.