Transcriptional Regulation of Aerobic Metabolism in Pichia pastoris Fermentation

Abstract

In this study, we investigated the classical fermentation process in Pichia pastoris based on transcriptomics. We utilized methanol in pichia yeast cell as the focus of our study, based on two key steps: limiting carbon source replacement (from glycerol to methonal) and fermentative production of exogenous proteins. In the former, the core differential genes in co-expression net point to initiation of aerobic metabolism and generation of peroxisome. The transmission electron microscope (TEM) results showed that yeast gradually adapted methanol induction to increased cell volume, and decreased density, via large number of peroxisomes. In the fermentative production of exogenous proteins, the Gene Ontology (GO) mapping results show that PAS_chr2-1_0582 played a vital role in regulating aerobic metabolic drift. In order to confirm the above results, we disrupted PAS_chr2-1_0582 by homologous recombination. Alcohol consumption was equivalent to one fifth of the normal control, and fewer peroxisomes were observed in Δ0582 strain following methanol induction. In this study we determined the important core genes and GO terms regulating aerobic metabolic drift in Pichia, as well as developing new perspectives for the continued development within this field.

Fig 1. Fermentation of rHSA expression induced by methanol in P. pastoris.

The spot line represents changes in cell dry weight, and the columns indicate the rHSA levels. The whole fermentation cycle lasted for 108 h. The cell growth stage (G stage G0h-G24h) lasted 6h-30h, the glycerol fed-batch stage (GB stage GB0h-GB6h) lasted 30h-36h, and the methanol fed-batch stage 36h-108h (MB stage MB0h-MB72h).

Fig 2. Main GO terms affected by differential genes and patterns during the transition from time point 1 to 3 and 3 to 5.

Each box represents one pattern of a model expression profile. The upper number in the profile box is the model profile number, and the lower one is the p-value used to summarize the different gene expression patterns. (A) The 1–3 time points in the 8 expression patterns were clustered, respectively. Genes expressed during the 1–3 time points were distributed in No. 6,1, 0 and 7 pattern (p<0.05). The core gene during the first three time points was associated with redox function. (B) The 3–5 time points in the 8 constructed expression patterns were clustered, respectively. The main GOTerms were affected by differential genes. Genes expressed during the 3–5 time points were distributed in the No.3 and No.5 pattern (p<0.05). The core gene during the 3–5 time points was associated with protein transport.

Fig 3. Cellular changes during carbon source replacement.

A: Cells during carbon source replacement. B: Common cell. C: Methanol treatment increased cell volume and peroxisome production.

Fig 4. Core genes in differential gene co-expression network during the transition from time point 1 to 3.

Cycle node represents gene, the real line and dotted line between two nodes represent direct and indirect interactions between genes respectively. The red nodes represent genes with the K-core value greater than or equal to 10, the blue nodes represent genes with the K-core value less than 10.

Fig 5. Co-expression network core of differential genes.

Time Point 3 to 5. Cycle nodes represent genes; the real line and dotted line between two nodes represent direct and indirect interactions between genes, respectively. The red nodes represent genes with the K-core value greater than or equal to 4, the blue nodes represent genes with the K-core value less than 4.

Fig 6. Distribution of differential genes in the redox function tree during the transition from time point 3 to 5.

The green cycle node represents gene, and the red triangle nodes represent GO term.

Fig 7. Distribution of differential genes in the redox function tree during the transition from time point 1 to 3.

The green cycle nodes represent genes, and the red triangle nodes represent GO term.

Fig 8. Δ 0582 strains in alcohol fermentation.

The methanol consumption of Δ 0582 strains was significantly less than the normal control, equivalent to a fifth of the normal control.