AtMetExpress LC-MS

10/8/2011 ver 1.1
Fumio Matsuda, Metabolome analysis research team, RIKEN PSC

AtMetExpress LC-MS ia a phytochemical atlas of Arabidopsis thaliana. Now, following two datasets are available.

AtMetExpress Development LC-MS

AtMetExpress 20 Ecotypes LC-MS


AtMetExpress Development LC-MS

We analyzed phytochemical accumulation during development of the model plant Arabidopsis thaliana using liquid chromatography-mass spectrometry (LC-MS) in samples covering many growth stages and organs. We also obtained MS/MS spectral tags of many metabolites as a resource for elucidation of metabolite structure. These are part of the AtMetExpress metabolite accumulation atlas. Based on the dataset, we detected 1,589 metabolite signals from which the structures of 167 metabolites were elucidated.

Publication

F. Matsuda et al. AtMetExpress development: A phytochemical atlas of Arabidopsis thaliana development. Plant Physiol.(2010). 152(2) 566-678. 10.1104/pp.109.148031 [Pubmed]

AtMetExpress Development LC-MS database

[AtMetExpress Development database]

AtMetExpress Development database produced a peak search function by using following information as queries such as polarity, accession number, retention time, m/z, annotation text, and MS/MS spectral similarity. From a list of search results, a metabolite signal of interest could be selected and its detailed information such as lists of tagged MS2Ts, results of database searching, final annotation, annotation levels, heat map representation of metabolite levels in each tissue, and raw chromatogram data of representative peak in all samples.

Integrated clustering of transcripotme and metabolome data using BL-SOM

[BL-SOM viewer]

BL-SOM viewer is able to map genes (by AGI code) and metabolites (by metabolite accession) of your interest on the results of BL-SOM analysis of AtGenExpress and AtMetExpress data.

In order to clarify any possible similarity of expression pattern of each gene to the accumulation pattern of its associated metabolites, we conducted a clustering analysis using the batch-learning self-organizing map (BL-SOM) method developed by Kanaya lab. in NAIST. BL-SOM is an improved and a reproducible method of the original SOM, and thus applied to integrated analysis of transcriptome and metabolome leading to successful prediction of genes' functions. All 1,589 metabolite signals with 10,147 metabolism-related genes (selected by GO terms) were classified into a 30 by 26 lattice according to their relative expression level across 36 tissues.

Download

[Download raw data file]

All raw data files (36 tissues, 4 replicate, two acquisition modes (positive and negative ion mode) = 288 files) are downloadable from DROP Met. Meta-information of each data is also available.

[Raw and processed matrix data]

Raw and processed matirx data files (Intensity data of 1589 metabolite in 144 samples [36 tissues, 4 replicates]) produced in the project are downloadable.

[MS2T data]

MS/MS spectral tag data (MS2T) obtained in this project was available from MS2T viewer page.

Experimental Design

For determining the metabolite levels, we obtained quadruplicate metabolic profiles of 36 distinct tissues by using a liquid chromatography coupled with electrospray ionization-quadrupole-time-of-flight tandem mass spectrometer (LC-ESI-Q-Tof/MS) according to previously described methods (Matsuda et al (2009)). The obtained data matrix contains the relative peak intensity values of 1,589 metabolite signals from 144 samples as below (36 tissues by 4 replicates). The experimental design was compatible with that of the AtGenExpress developmental (Schmid et al., 2005) series for integrated analyses with transcriptome data.

Sample nameCorresponding microarray data in AtGenExpressTissueAgePhotoperiodSubstrate
ATME_1ATGE_1cotypedons10 dayscontinuous lightsoil
ATME_7ATGE_7seedling, green parts10 dayscontinuous lightsoil
ATME_9ATGE_9roots21 dayscontinuous lightsoil
ATME_10ATGE_10rosette leaf #4, 1 cm long14 dayscontinuous lightsoil
ATME_12ATGE_12rosette leaf #221 dayscontinuous lightsoil
ATME_13ATGE_13rosette leaf #421 dayscontinuous lightsoil
ATME_14ATGE_14rosette leaf #621 dayscontinuous lightsoil
ATME_15ATGE_15rosette leaf #821 dayscontinuous lightsoil
ATME_16ATGE_16rosette leaf #1021 dayscontinuous lightsoil
ATME_19ATGE_19leaf7. petiole21 dayscontinuous lightsoil
ATME_20ATGE_20leaf7, proximal half21 dayscontinuous lightsoil
ATME_21ATGE_21leaf7, distal half21 dayscontinuous lightsoil
ATME_25ATGE_25senescing leaves35 dayscontinuous lightsoil
ATME_26ATGE_26cauline leaves28 dayscontinuous lightsoil
ATME_27ATGE_27stem, 2nd internode28 dayscontinuous lightsoil
ATME_28ATGE_281st node28 dayscontinuous lightsoil
ATME_29ATGE_29shoot apex, inflorescence (after bolting)28 dayscontinuous lightsoil
ATME_32ATGE_32flowers stage 10/1128 dayscontinuous lightsoil
ATME_33ATGE_33flowers stage 1228 dayscontinuous lightsoil
ATME_39ATGE_39flowers stage 1528 dayscontinuous lightsoil
ATME_41ATGE_41flowers stage 15, sepals28 dayscontinuous lightsoil
ATME_42ATGE_42flowers stage 15, petals28 dayscontinuous lightsoil
ATME_45ATGE_45flowers stage 15, carpels28 dayscontinuous lightsoil
ATME_76ATGE_76siliques, w/ seeds stage 34 wklong day (16/8)soil
ATME_77ATGE_77siliques, w/ seeds stage 44 wklong day (16/8)soil
ATME_78ATGE_78siliques, w/ seeds stage 54 wklong day (16/8)soil
ATME_91ATGE_91leaf15 dayslong day (16/8)1x MS agar, 1% sucrose
ATME_92ATGE_92flower28 dayslong day (16/8)soil
ATME_93ATGE_93root15 dayslong day (16/8)1x MS agar, 1% sucrose
ATME_95ATGE_95root8 dayscontinuous light1x MS agar, 1% sucrose
ATME_96ATGE_96seedling, green parts8 dayscontinuous light1x MS agar
ATME_97ATGE_97seedling, green parts8 dayscontinuous light1x MS agar, 1% sucrose
ATME_98ATGE_98root21dayscontinuous light1x MS agar
ATME_99ATGE_99root21dayscontinuous light1x MS agar, 1% sucrose
ATME_101ATGE_101seedling, green parts21dayscontinuous light1x MS agar, 1% sucrose
ATME_84RIKEN-NAKABAYASHImature seed16 wklong day (16/8)soil




AtMetExpress 20 Ecotypes LC-MS

To investigate variations in the composition of secondary metabolites among Arabidopsis strains (accessions), metabolic profile data were obtained from the rosette leaves of 20 accessions of Arabidopsis by LC-ESI-Q-Tof/MS analysis. The 20 diverse accessions evaluated herein were previously selected by Clark et al. (2007) to investigate the genetic variations within the population of Arabidopsis. Metabolite signals were automatically indentified or annotated by the compound name, as well as characterized by the metabolite ontolgy terms.

Publication

F. Matsuda et al. Mass spectra-based framework for automated structural elucidation of metabolome data to explore phytochemical diversity. Front. Plant Sci. 2:40. doi: 10.3389/fpls.2011.00040 [View]

Download

[Download raw data file]

All raw data files (20 accessions, 5 replicate, 2 acquisition modes (positive and negative ion mode) = 200 files) are downloadable from DROP Met. Meta-information of each data is also available.

[Raw and processed matrix data]

Raw and processed matirx data files produced in the project are downloadable.

[MS2T data]

MS/MS spectral tag data (MS2T) obtained in this project was available from MS2T viewer page.

Experimental Design

For determining the metabolite levels, we obtained quadruplicate metabolic profiles of aerial part of 16-days-seedlings of 20 accessions by using LC-ESI-Q-Tof/MS according to previously described methods (Matsuda et al (2009)). The 20 diverse accessions evaluated herein were previously selected by Clark et al. (2007) to investigate the genetic variations within the population of Arabidopsis.

Sample nameAccession
AtMetEcotype01CS22676 Bay-0 (BAYREUTH)
AtMetEcotype02CS22677 Bor-4 (BORKY)
AtMetEcotype03CS22678 Br-0 (BRUNN)
AtMetEcotype04CS22679 Bur-0 (BURREN)
AtMetEcotype05CS22680 C24
AtMetEcotype06CS22681 Col-0 (COLUMBIA)
AtMetEcotype07CS22682 Cvi-0 (CAPE VERDI ISLANDS)
AtMetEcotype08CS22683 Est-1 (ESTLAND)
AtMetEcotype09CS22684 Fei-0 (ST. MARIA D. FEIRIA)
AtMetEcotype10CS22685 Goettingen-7 (GOETTINGEN)
AtMetEcotype11CS22686 Ler-1 (LANDSBERG ERECTA)
AtMetEcotype12CS22687 NFA-8 (NFA)
AtMetEcotype13CS22688 RRS-7 (RRS)
AtMetEcotype14CS22689 RRS-10 (RRS)
AtMetEcotype15CS22690 Sha (SHAKDARA)
AtMetEcotype16CS22691 Tamm-2 (TAMMISARI)
AtMetEcotype17CS22692 Ts-1 (TOSSA DEL MAR)
AtMetEcotype18CS22693 Tsu-1 (TSU)
AtMetEcotype19CS22694 Van-0 (VANCOUVER)
AtMetEcotype20CS22695 Lov-5 (LOVVIK)

Modified: 2011-8-10

RIKEN Plant Science Center
Metabolome analysis research team, LC-MS Branch