Investigating the effectiveness of DNA microarray analysis for identifying the genes involved in l-lactate production by Saccharomyces cerevisiae

Abstract

In order to determine whether transcriptome data obtained by DNA microarray analysis could be used to identify the genes involved in target metabolite production, we tried to identify the genes involved in L-lactate production by L-lactate-producing recombinant Saccharomyces cerevisiae strains. We obtained DNA microarray data for these strains. Plasmids carrying lactic acid bacteria, bovine, and human L-lactate dehydrogenase (LDH) genes were introduced into PDC1-disrupted S. cerevisiae strains. L-Lactate productivity of the strains harboring the human and bovine LDH genes was higher than that of the strains harboring lactic acid bacteria LDH genes. DNA microarray analysis revealed that the expression of 388 genes was significantly altered in the strains with the human and bovine LDH genes. Of these, the L-lactate productivity of human LDH-harboring deletion strains of 289 genes was compared with that of the standard and 56 randomly selected deletion strains containing the same LDH gene to validate the effectiveness of DNA microarray analysis for identifying the genes responsible for L-lactate production in the recombinant strains. Only deletion strains of the genes selected on the basis of the DNA microarray data showed significantly altered L-lactate production as compared to the standard and the randomly selected deletion strains. Our results indicated that the genes related to L-lactate production could be successfully identified by selecting the genes that exhibited significantly altered expression on DNA microarray analysis, and the effectiveness of DNA microarray analysis for identifying the genes responsible for L-lactate production was discussed.

Transcriptome of Saccharomyces cerevisiae during production of D-xylonate

“…The use of log2 ratios comparing samples of interest with appropriate control samples removes some of the experiment-specific sources of variation between experiments, but results in different ranges of fold change for different conditions. To normalize the arrays, Quantile normalization was applied to datasets with full data [14, 18, 36], and the log2 ratios from publications listed in Table 1 were scaled to the same range [-4.03, 4.07]. As a result, the exact fold-changes reported in the original source were lost, but the transformation provided similar log2 ratios for the most significantly changed genes in each study, keeping the rank or order of genes with transcriptional responses in a given condition the same.…”

Metabolic Engineering of Biocatalysts for Carboxylic Acids Production

“…The lactate productivity was compared between these two groups of deletion strains and a control strain without the human LDH gene. Significantly altered L-lactate production was observed in 59 of the deletion strains selected based on the transcriptome data and in none of the 56 randomly-selected strains (27). …”

Metabolic engineering of Saccharomyces cerevisiae to improve succinic acid production based on metabolic profiling

“…Since genome sequencing of it was completed 1) and genetic manipulation tools have been developed, S. cerevisiae has the potential as a host species for the production of fuel alcohols and chemical building blocks. Recently, the production of organic acids such as lactic acid [2][3][4][5][6][7][8][9][10][11] and malic acid [12][13][14][15] by S. cerevisiae has been examined because S. cerevisiae grows well under low pH conditions. Here, we report a metabolic engineering approach to succinic acid production by S. cerevisiae.…”