Influence of methanol/sorbitol co-feeding rate on pAOX1 induction in a Pichia pastoris Mut+ strain in bioreactor with limited oxygen transfer rate.
High Pichia pastoris biomass density could be obtained using high co-feeding rate of methanol and sorbitol in a fed-batch or continuous culture, while further higher feeding rate finally leads to oxygen limitation in bioreactor. In the literature, there is lack of report about AOX1 promoter regulation with regard to dissolved oxygen level (DO). Therefore, in this work, chemostat cultures were performed to investigate the cell growth, metabolism and regulation of the AOX1 promoter (pAOX1) regarding co-feeding rate of optimized methanol/sorbitol mixture (methanol fraction 0.60 C-mol/C-mol) using a P. pastoris Mut+/pAOX1-lacZ strain. The oxygen transfer rates (OTR) in bioreactor were kept in the range of typical values of large bioreactor, i.e., 4-8 g/(L h) if DO equals 30 % saturation or 5-10 g/(L h) if DO nears zero. For DO >0, an increase of the carbon fed led to an increase of pAOX1 induction. By contrast, when dissolved oxygen was completely depleted, methanol accumulated, causing a 30 % decrease of pAOX1 induction. However, this decrease is more likely to be lined to methanol accumulation than to low level of dissolved oxygen (<4 % DO). Methanol/sorbitol co-feeding allowed cells to adapt to oxygen transient limitations that often occur at industrial scale with reduced effect on pAOX1 induction. The optimal feeding rate tested here was 6.6 mmol C (DCW h)(-1) at an OTR of 8.28 g O2(L h)(-1) with over fivefold pAOX1 induction (probably directly associated with target protein productivity) compared with previous work.
['Carly|F|F|', 'Niu|H|H|', 'Delvigne|F|F|', 'Fickers|P|P|']
D042931:Aldehyde Oxidase D018533:Biomass D019149:Bioreactors D002244:Carbon D007700:Kinetics D000432:Methanol D009154:Mutation D010100:Oxygen D010101:Oxygen Consumption D010843:Pichia D011401:Promoter Regions, Genetic D013012:Sorbitol
pAOX1 Pichia pastoris Chemostat Methanol/sorbitol feeding Process optimization