Take our Survey

Reference: Rossouw D, et al. (2008) Linking gene regulation and the exo-metabolome: A comparative transcriptomics approach to identify genes that impact on the production of volatile aroma compounds in yeast. BMC Genomics 9(1):530

Reference Help

Abstract


ABSTRACT: BACKGROUND: 'Omics' tools provide novel opportunities for system-wide analysis of complex cellular functions. Secondary metabolism is an example of a complex network of biochemical pathways, which, although well mapped from a biochemical point of view, is not well understood with regards to its physiological roles and genetic and biochemical regulation. Many of the metabolites produced by this network such as higher alcohols and esters are significant aroma impact compounds in fermentation products, and different yeast strains are known to produce highly divergent aroma profiles. Here, we investigated whether we can predict the impact of specific genes of known or unknown function on this metabolic network by combining whole transcriptome and partial exo-metabolome analysis. RESULTS: For this purpose, the gene expression levels of five different industrial wine yeast strains that produce divergent aroma profiles were established at three different time points of alcoholic fermentation in synthetic wine must. A matrix of gene expression data was generated and integrated with the concentrations of volatile aroma compounds measured at the same time points. This relatively unbiased approach to the study of volatile aroma compounds enabled us to identify candidate genes for aroma profile modification. Five of these genes, namely YMR210W, BAT1, AAD10, AAD14 and ACS1 were selected for overexpression in a commercial wine yeast, VIN13. Analysis of the data show a statistically significant correlation between the changes in the exo-metabome of the overexpressing strains and the changes that were predicted based on the unbiased alignment of transcriptomic and exo-metabolomic data. CONCLUSION: The data suggest that a comparative transcriptomics and metabolomics approach can be used to identify the metabolic impacts of the expression of individual genes in complex systems, and the amenability of transcriptomic data to direct applications of biotechnological relevance.

Reference Type
Journal Article
Authors
Rossouw D, Naes T, Bauer FF
Primary Lit For
Additional Lit For
Review For

Interaction Annotations


Increase the total number of rows showing on this page by using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; filter the table using the "Filter" box at the top of the table; click on the small "i" buttons located within a cell for an annotation to view further details about experiment type and any other genes involved in the interaction.

Interactor Interactor Type Assay Annotation Action Modification Phenotype Source Reference

Gene Ontology Annotations


Increase the total number of rows showing on this page using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; filter the table using the "Filter" box at the top of the table.

Gene Gene Ontology Term Qualifier Aspect Method Evidence Source Assigned On Annotation Extension Reference

Phenotype Annotations


Increase the total number of rows showing on this page using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; filter the table using the "Filter" box at the top of the table; click on the small "i" buttons located within a cell for an annotation to view further details.

Gene Phenotype Experiment Type Mutant Information Strain Background Chemical Details Reference

Regulation Annotations


Increase the total number of rows displayed on this page using the pull-down located below the table, or use the page scroll at the table's top right to browse through the table's pages; use the arrows to the right of a column header to sort by that column; to filter the table by a specific experiment type, type a keyword into the Filter box (for example, “microarray”); download this table as a .txt file using the Download button or click Analyze to further view and analyze the list of target genes using GO Term Finder, GO Slim Mapper, SPELL, or YeastMine.

Regulator Target Experiment Assay Construct Conditions Strain Background Reference