Effects of Inhibitors on the Transcriptional Profiling of Gluconobater oxydans NL71 Genes after Biooxidation of Xylose into Xylonate

Abstract

D-Xylonic acid belongs to the top 30 biomass-based platform chemicals and represents a promising application of xylose. Until today, Gluconobacter oxydans NL71 is the most efficient microbe capable of fermenting xylose into xylonate. However, its growth is seriously inhibited when concentrated lignocellulosic hydrolysates are used as substrates due to the presence of various degraded compounds formed during biomass pretreatment. Three critical lignocellulosic inhibitors were thereby identified, i.e., formic acid, furfural, and 4-hydroxybenzaldehyde. As microbe fermentation is mostly regulated at the genome level, four groups of cell transcriptomes were obtained for a comparative investigation by RNA sequencing of a control sample with samples treated separately with the above-mentioned inhibitors. The digital gene expression profiles screened 572, 714 genes, and 408 DEGs was obtained by the comparisons among four transcriptomes. A number of genes related to the different functional groups showed characteristic expression patterns induced by three inhibitors, in which 19 genes were further tested and confirmed by qRT-PCR. We extrapolated many differentially expressed genes that could explain the cellular responses to the inhibitory effects. We provide results that enable the scientific community to better define the molecular processes involved in the microbes' responses to lignocellulosic inhibitors during the cellular biooxidation of xylose into xylonic acid.

Keywords: Gluconobacter oxydans; lignocellulosic inhibitor; responsible gene; transcriptome sequencing; xylonate; xylose.

Figure 1

Volcano plot displaying differential expressed genes between the blank sample and the inhibitor treated samples. The y-axis corresponds to the mean expression value of the log₁₀(p-value) and the x-axis displays the log₂(Fold-change) value. The red dots represent the upregulated expressed genes, the green dots represent the downregulated expressed genes, and the blue dots represent the transcripts whose expression levels did not reach statistical significance between two samples.

Figure 2

Hierarchical clustering of the differentially expressed genes based on the log₁₀RPKM-values.

Figure 3

Clustering of the differentially expressed genes. The four major clusters obtained by the K-means algorithm. Expression ratios are expressed as log2.

Figure 4

Venn diagram showing the number of differentially expressed genes between every two samples.

Figure 5

Histogram of the gene ontology classification. The results summarized the three main categories: biological process (BP), cellular component (CC), and molecular function (MF). The X-axis indicates the number of genes in a category. The left Y-axis indicates the second level term of gene ontology. ^*The significantly enriched.