SE47:/S01/M01/D01
From Metabolonote
Sample Set Information
ID | SE47 |
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Title | Metabolomic correlation-network modules in Arabidopsis based on a graph-clustering approach |
Description | Deciphering the metabolome is essential for a better understanding of the cellular metabolism as a system. Typical metabolomics data show a few but significant correlations among metabolite levels when data sampling is repeated across individuals grown under strictly controlled conditions. Although several studies have assessed topologies in metabolomic correlation networks, it remains unclear whether highly connected metabolites in these networks have specific functions in known tissue- and/or genotype-dependent biochemical pathways. In our study of metabolite profiles we subjected root tissues to gas chromatography-time-of-flight/mass spectrometry (GC-TOF/MS) and used published information on the aerial parts of 3 Arabidopsis genotypes, Col-0 wild-type, methionine over-accumulation 1 (mto1), and transparent testa4 (tt4) to compare systematically the metabolomic correlations in samples of roots and aerial parts. We then applied graph clustering to the constructed correlation networks to extract densely connected metabolites and evaluated the clusters by biochemical-pathway enrichment analysis. We found that the number of significant correlations varied by tissue and genotype and that the obtained clusters were significantly enriched for metabolites included in biochemical pathways. We demonstrate that the graph-clustering approach identifies tissue- and/or genotype-dependent metabolomic clusters related to the biochemical pathway. Metabolomic correlations complement information about changes in mean metabolite levels and may help to elucidate the organization of metabolically functional modules. |
Authors | Atsushi Fukushima, Miyako Kusano, Henning Redestig, Masanori Arita, Kazuki Saito, RIKEN PSC |
Reference | Fukushima et al. (2011) BMC Syst Biol 5:1 (PMID: 21194489) |
Comment |
Sample Information
ID | S01 |
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Title | Arabidopsis thaliana |
Organism - Scientific Name | Arabidopsis thaliana |
Organism - ID | NCBI taxonomy:3702 |
Compound - ID | |
Compound - Source | |
Preparation | For metabolomic correlation analysis we sampled tissues from the roots of Arabidopsis thaliana Col-0 wild-type (WT), methionine over-accumulation 1 (mto1) (Inaba et al. 1994), and transparent testa4 (tt4) (Shikazono et al. 2003). Data on the aerial part were from Kusano et al. 2007. The number of biological replicates in roots was 53 (17 x WT, 16 x mto1, and 20 x tt4). We pooled 3 root samples as a batch for metabolite profiling. |
Sample Preparation Details ID | |
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Analytical Method Information
ID | M01 |
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Title | GC-TOF/MS |
Method Details ID | MS01 |
Sample Amount | 1 μl |
Comment |
Analytical Method Details Information
ID | MS01 |
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Title | GC-TOF/MS |
Instrument | GC Agilent 6890N gas chromatograph / MS Pegasus III TOF mass spectrometer |
Instrument Type | |
Ionization | EI |
Ion Mode | positive |
Description | As described in (Kusano et al. 2007), each sample was extracted, derivatized, and analyzed by GC-TOF/MS. |
Comment_of_details |
Data Analysis Information
ID | D01 |
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Title | Data Processing |
Data Analysis Details ID | DS01 |
Recommended decimal places of m/z | |
Comment |
Data Analysis Details Information
ID | DS01 |
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Title | Data processing |
Description | Briefly, we pre-processed all raw data using custom MATLAB software (version 6.5; Mathworks, Natick, MA, USA) for hyphenated data analysis (HDA) (Jonsson et al. 2006); it performs baseline correction, peak alignment, and peak deconvolution. For metabolite identification we used the Golm Metabolome Database (GMD) (Kopka et al. 2005) and our in-house mass spectral libraries (Kusano et al. 2007). |
Comment_of_details |