Evaluation of the sub-optimal induction strategies for heterologous proteins production by Pichia pastoris Mut+/MutS strains and related transcriptional and metabolic analysis

Abstract

Heterologous proteins induction by methylotrophic recombinant Pichia pastoris is generally implemented at high cells density condition. Methanol concentration (MeOH) and dissolved oxygen concentration (DO) are two crucial operating parameters controlling proteins production. It is difficult to control MeOH/DO at their desired levels simultaneously due to the extremely high oxygen consumption features. Methanol utilization plus (Mut+) and slow (MutS) strains are the two typical phenotypes of recombinant P. pastoris with quite different dynamic characteristics. Therefore, different MeOH/DO combinational control strategies or sub-optimal induction strategies could be adopted. Environments of "high MeOH/low DO" and "high DO/low MeOH" are the realistic induction strategies. In this study, we summarized our own experimental results (using Mut+/MutS strains to produce human serum albumin-human granulocyte colony stimulating factor-HSA-GCSFm/porcine interferon-α-pIFN-α), and compared to data from the literature using the above mentioned two induction strategies. The results suggested that, heterologous proteins production by Mut+ strains favors "high DO/low MeOH (DO ~ 10%, MeOH ~ 0g/L)" induction condition, while proteins production by MutS strains prefers "high MeOH/low DO (MeOH 5-10g/L, DO ~ 0%)" induction environment. Thus, based on the P. pastoris types, the corresponding sub-optimal induction strategies should be applied accordingly. The related metabolic analysis indicating methanol utilizing efficiency and the transcriptional analysis reflecting gene up- or down-regulations involved in several key routes in methanol and sorbitol metabolism were implemented. The analysis results strongly supported the conclusions of using the proposed sub-optimal induction strategies for different heterologous proteins production by Mut+ and MutS strains.