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Paintomics: a web based tool for the joint visualization of transcriptomics and metabolomics data.

García-Alcalde F, García-López F, Dopazo J, Conesa A - Bioinformatics (2010)

Bottom Line: The development of the omics technologies such as transcriptomics, proteomics and metabolomics has made possible the realization of systems biology studies where biological systems are interrogated at different levels of biochemical activity (gene expression, protein activity and/or metabolite concentration).An effective approach to the analysis of these complex datasets is the joined visualization of the disparate biomolecular data on the framework of known biological pathways.We have developed the Paintomics web server as an easy-to-use bioinformatics resource that facilitates the integrated visual analysis of experiments where transcriptomics and metabolomics data have been measured on different conditions for the same samples.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe, Valencia, Spain.

ABSTRACT

Motivation: The development of the omics technologies such as transcriptomics, proteomics and metabolomics has made possible the realization of systems biology studies where biological systems are interrogated at different levels of biochemical activity (gene expression, protein activity and/or metabolite concentration). An effective approach to the analysis of these complex datasets is the joined visualization of the disparate biomolecular data on the framework of known biological pathways.

Results: We have developed the Paintomics web server as an easy-to-use bioinformatics resource that facilitates the integrated visual analysis of experiments where transcriptomics and metabolomics data have been measured on different conditions for the same samples. Basically, Paintomics takes complete transcriptomics and metabolomics datasets, together with lists of significant gene or metabolite changes, and paints this information on KEGG pathway maps.

Availability: Paintomics is freely available at http://www.paintomics.org.

Show MeSH
Painted citrate cycle map for the Arabidopsis DTT treatment example. Reduced levels of metabolites are found at the first part of the cycle (blue-colored metabolites), while increased concentrations are found on the second part of the pathway (red-colored metabolites). Black entry boxes represent significant regulation.
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Figure 1: Painted citrate cycle map for the Arabidopsis DTT treatment example. Reduced levels of metabolites are found at the first part of the cycle (blue-colored metabolites), while increased concentrations are found on the second part of the pathway (red-colored metabolites). Black entry boxes represent significant regulation.

Mentions: Paintomics was fed with data files and run with default parameters, selecting A.thaliana at the species check-box. A total of 60 pathways where obtained with at least one matching entry. From the visual analysis of these maps, conclusions on the co-regulation of transcripts and metabolites can be drawn. For example, citric acid map shows the down-regulation of the first part of the pathway (citrate, isocitrate, cis-asconitate and 2-oxoglutarate), while metabolites on the second part (malate, fumarate and succinate) had increased levels (Fig. 1). These changes were accompanied by the significant upregulation of genes on this second half of the cycle such as citrate synthase (CSY3), malate dehydrogenase (PMDH2) and succinate dehydrogenase (SDH2-2), pointing to a coordinated activity of genes and metabolites. Connections between the tricarboxylic acid cycle (TCA) and the pyruvate metabolism additionally reveal a decrease in pyruvate and phosphoenol pyruvate levels upon DTT treatment, which was accompanied by a significant upregulation of the pyruvate dehydrogenase (IAR4), malate dehydrogenase (IDH2) and phosphoenolpyruvate carboxilase (PCK1) enzymes that catalyze the conversion of these compounds toward acetyl-CoA, oxolacetate and finally malate. Interestingly, this pattern of metabolite balance at the TCA cycle was also observed by the authors although their transcriptomics analysis did not reveal any significant changes of genes in these pathways. These results led authors to postulate that changes in fluxes and metabolite concentrations in these pathways were most likely due of post-translational mechanisms. The integrated visualization offered by Paintomics did reveal the coordinated state of transcript and metabolite levels.Fig. 1.


Paintomics: a web based tool for the joint visualization of transcriptomics and metabolomics data.

García-Alcalde F, García-López F, Dopazo J, Conesa A - Bioinformatics (2010)

Painted citrate cycle map for the Arabidopsis DTT treatment example. Reduced levels of metabolites are found at the first part of the cycle (blue-colored metabolites), while increased concentrations are found on the second part of the pathway (red-colored metabolites). Black entry boxes represent significant regulation.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3008637&req=5

Figure 1: Painted citrate cycle map for the Arabidopsis DTT treatment example. Reduced levels of metabolites are found at the first part of the cycle (blue-colored metabolites), while increased concentrations are found on the second part of the pathway (red-colored metabolites). Black entry boxes represent significant regulation.
Mentions: Paintomics was fed with data files and run with default parameters, selecting A.thaliana at the species check-box. A total of 60 pathways where obtained with at least one matching entry. From the visual analysis of these maps, conclusions on the co-regulation of transcripts and metabolites can be drawn. For example, citric acid map shows the down-regulation of the first part of the pathway (citrate, isocitrate, cis-asconitate and 2-oxoglutarate), while metabolites on the second part (malate, fumarate and succinate) had increased levels (Fig. 1). These changes were accompanied by the significant upregulation of genes on this second half of the cycle such as citrate synthase (CSY3), malate dehydrogenase (PMDH2) and succinate dehydrogenase (SDH2-2), pointing to a coordinated activity of genes and metabolites. Connections between the tricarboxylic acid cycle (TCA) and the pyruvate metabolism additionally reveal a decrease in pyruvate and phosphoenol pyruvate levels upon DTT treatment, which was accompanied by a significant upregulation of the pyruvate dehydrogenase (IAR4), malate dehydrogenase (IDH2) and phosphoenolpyruvate carboxilase (PCK1) enzymes that catalyze the conversion of these compounds toward acetyl-CoA, oxolacetate and finally malate. Interestingly, this pattern of metabolite balance at the TCA cycle was also observed by the authors although their transcriptomics analysis did not reveal any significant changes of genes in these pathways. These results led authors to postulate that changes in fluxes and metabolite concentrations in these pathways were most likely due of post-translational mechanisms. The integrated visualization offered by Paintomics did reveal the coordinated state of transcript and metabolite levels.Fig. 1.

Bottom Line: The development of the omics technologies such as transcriptomics, proteomics and metabolomics has made possible the realization of systems biology studies where biological systems are interrogated at different levels of biochemical activity (gene expression, protein activity and/or metabolite concentration).An effective approach to the analysis of these complex datasets is the joined visualization of the disparate biomolecular data on the framework of known biological pathways.We have developed the Paintomics web server as an easy-to-use bioinformatics resource that facilitates the integrated visual analysis of experiments where transcriptomics and metabolomics data have been measured on different conditions for the same samples.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics and Genomics Department, Centro de Investigaciones Príncipe Felipe, Valencia, Spain.

ABSTRACT

Motivation: The development of the omics technologies such as transcriptomics, proteomics and metabolomics has made possible the realization of systems biology studies where biological systems are interrogated at different levels of biochemical activity (gene expression, protein activity and/or metabolite concentration). An effective approach to the analysis of these complex datasets is the joined visualization of the disparate biomolecular data on the framework of known biological pathways.

Results: We have developed the Paintomics web server as an easy-to-use bioinformatics resource that facilitates the integrated visual analysis of experiments where transcriptomics and metabolomics data have been measured on different conditions for the same samples. Basically, Paintomics takes complete transcriptomics and metabolomics datasets, together with lists of significant gene or metabolite changes, and paints this information on KEGG pathway maps.

Availability: Paintomics is freely available at http://www.paintomics.org.

Show MeSH