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Metabolites from surface seawater collected in Narragansett Bay

ABSTRACT: In aquatic environments, the production and consumption of organic compounds is directly tied to the metabolic potential of the in situ microbial community. The community’s metabolic potential can be assessed using metatranscriptomics, which is a measure of gene expression in the environment. More recently, advances in metabolomics deliver details on specific organic compounds found in the environment. While the integration of these two datasets is desirable, the vast data streams can hinder investigations into biological and chemical processes. Here, we use data in the Kyoto Encyclopedia of Genes and Genomes (KEGG) combined with K means clustering to jointly interrogate metabolomics and metatranscriptomics data collected from a coastal marine environment. Using KEGG allowed us to focus our analysis on genes and compounds connected by a defined biochemical reaction. The K means clustering provided an unbiased means to place metabolites and genes into groups based on their temporal variability. Each of the groups defined by the K means clustering contained both transcripts and metabolites, which emphasized the interconnected nature of these two datasets. While conceptually simple, this analysis allowed us to explore a tractable number of biochemical pathways within our data. Continued development of computational tools to analyze meta-omics data is a pressing need. The application of tools such as described here is an exciting step towards integrated multi-omics data analysis that can be used to address broad questions in biogeochemical cycling.

INSTRUMENT(S): LTQ FT Ultra (Thermo Scientific), TSQ Vantage (Thermo Scientific)

SUBMITTER: Krista Longnecker

PROVIDER: MTBLS293 | MetaboLights | 2016-01-14

REPOSITORIES: MetaboLights

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			Action	DRS
	MTBLS293	Other
	FILES	Other
	a_MTBLS293_NEG_rione_mass_spectrometry.txt	Txt
	a_MTBLS293_POS_rione_mass_spectrometry.txt	Txt
	a_MTBLS293_TAR_rione_mass_spectrometry.txt	Txt

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Project description:In this study we used microarray analysis to reveal the gene expression profile of the hippocampal CA1 subregion, which was laser-capture microdissected one week after kainic acid (KA)-induced status epilepticus (SE) in postnatal day 21 (P21) rats. These rats are developmentally roughly comparable to juvenile children, and KA-induced SE leads to selective damage of hippocampal CA1 pyramidal neurons in this age group while saving neurons of the other sub-regions. We searched for alterations in the gene expression pattern during the early epileptogenetic phase, i.e. one week after SE, and compared the results with those of age-matched control rats. To detect specifically changes in the CA1 pyramidal neurons, we used the laser-capture microdissection technique that allows the precise isolation of the region of interest. The RNA of this region was isolated, amplified, and labeled, and then hybridized to Illumina RatRef-12 Expression BeadChip Arrays. The gene expression data generated from the microarray was first normalized by the guantile normalization method, and then filtered by using the empirical Bayes method, and the contrasts were created by using the Limma R/Bioconductor. Finally, the data was clustered by using the non-hierarchical K-means clustering for genes, and the pathway analysis was performed by âGene set testâ, which analyzes the statistical significance of a set of genes simultaneously ranked by p-value and generates the KEGG categories (Chipster manual). The Illumina microarray analysis with the Chipster software v1.1.0 (http://chipster.csc.fi; CSC, Espoo, Finland) generated a total of 1592 differently expressed genes in the CA1 subregion of KA-treated rats compared to control rats. Using the K-means method the genes were classified in 10 different clusters. The subsequent KEGG-test for the probe set over-representation analysis revealed the 15 significantly (p<0.05) changed KEGG-pathways in response to KA-treatment, e.g. oxidative phosphorylation (26 genes changed), and long-term potentiation (LTP; 18 genes changed). Some of the differentially expressed genes were also identified to be involved in Ca2+ homeostasis, gliosis, inflammation, and GABAergic transmission.

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Metabolites from surface seawater collected in Narragansett Bay

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