Enhancing the efficiency of recombinant hepatitis B surface antigen production in Pichia pastoris by employing continuous fermentation

Rahimi, Alireza; Hosseini, Seyed Nezamedin; Karimi, Afzal; Aghdasinia, Hassan; Mianroodi, Reza Arabi

doi:10.1016/j.bej.2018.10.019

Cited by 35 publications

(35 citation statements)

References 32 publications

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“…Considering Figs and Table , we can conclude that the proposed system control by ANN could not only nullify the impact of disturbance variables on the specific growth rate, final biomass and HBsAg amount but also increase the production efficiency of HBsAg considerably higher than the conventional method. Although the fed‐batch system combined with RNN sensor and PID controller demonstrated higher titer, specific productivity and yield compared with conventional fed‐batch fermentation, its efficiency, in terms of these parameters, was lower than that of chemostat fermentation with values of 187.71 μg mL −1 , 1.699 mg HBsAg L −1 h −1 and 0.526 mg g −1 respectively . This result might be related to the cell aging process in fed‐batch fermentation, in which old cells still remain in the system but do not produce HBsAg efficiently …”

Section: Discussionsupporting

confidence: 82%

“…The fed‐batch fermentation with initial broth volume 5 L was performed at 30 °C and pH ∼4.8, controlled by adding 20% (v/v) ammonia, under agitation/oxygen cascade operation (DO >20%) (Fig. ) . The methanol sensor was used during the fermentation to monitor the methanol concentration in the fermentation broth.…”

Section: Methodssupporting

confidence: 76%

“…In the third stage, the methanol transition phase, methanol was added gradually to the fermenter so that P. pastoris was being adapted to methanol as a new carbon source . Finally, after methanol adaptation, fed‐batch fermentation with methanol as sole carbon and energy source and limiting nutrient was applied …”

Section: Methodsmentioning

confidence: 99%

“…For each feeding strategy, two methanol fed‐batch fermentation processes were performed in the bench‐scale fermenter. In all performed fermentations, the same glycerol batch and methanol adaptation strategies were employed according to the established protocol in the production center at Pasteur Institute of Iran . All process variables during methanol fed‐batch fermentation except the feeding rate were controlled by the fermenter Control Station (Fig.…”

Section: Methodsmentioning

confidence: 99%

“…In this specific industrial strain, hepatitis B surface antigens (HBsAgs), the main component of HBV, are produced intracellularly and then form virus‐like particles (VLPs) during the downstream process . In the already established HBsAg production center based on P. pastoris with P AOX1 , increasing the process efficiency of the fermentation process still remains as one of the main objectives . Nevertheless, improvements in operational and controlling strategies without significant changes in the fermentation systems would be more favorable approaches to avoid challenges related to economic and regulatory issues …”

Section: Introductionmentioning

confidence: 99%

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Comparative study of μ‐stat methanol feeding control in fed‐batch fermentation of Pichia pastoris producing HBsAg: an open‐loop control versus recurrent artificial neural network‐based feedback control

Beiroti

Hosseini

Aghasadeghi

et al. 2019

J of Chemical Tech & Biotech

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BACKGROUND In recent decades, artificial neural network (ANN) has been shown to be a robust and promising tool in monitoring and controlling bioprocess systems. In a previous study, the authors designed a highly accurate and precise recurrent neural network (RNN) for predicting the biomass amount of recombinant Pichia pastoris Mut+ producing intracellular hepatitis B surface antigen (HBsAg) during fed‐batch methanol fermentation. In the current work, the aim was to compare the production efficiency of HBsAg between conventional predefined μ‐stat methanol feeding control (open‐loop control) – already established in large‐scale production – and methanol feeding based on a μ‐stat feedback control system using RNN. For this purpose, for each methanol feeding strategy, bench‐scale, fed‐batch fermentation processes were carried out twice. RESULTS According to the results, in contrast to the established μ‐stat predefined feeding strategy (open‐loop), the deviation of specific growth rate and biomass in μ‐stat feedback control based on RNN was negligible. Also, in the suggested methanol feeding control strategy, the HBsAg titer, specific productivity and yield between the performed fed‐batch fermentations – unlike the conventional method – were approximately identical, with average values of 110.8 μg mL−1, 1.52 μg g−1 dry biomass and 0.34 μg g−1 MeOH respectively. CONCLUSION Comparing the biomass growth pattern and HBsAg production efficiency with the conventional μ‐stat predefined feeding in open‐loop control, the new proposed feeding control system illustrated significantly high process efficiency. This reliable control system based on ANN can have many applications in the biopharmaceutical industry for the control of process key parameters as well as for enhancing process efficiency. © 2019 Society of Chemical Industry

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Section: Discussionsupporting

confidence: 82%

Section: Methodssupporting

confidence: 76%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Comparative study of μ‐stat methanol feeding control in fed‐batch fermentation of Pichia pastoris producing HBsAg: an open‐loop control versus recurrent artificial neural network‐based feedback control

Beiroti

Hosseini

Aghasadeghi

et al. 2019

J of Chemical Tech & Biotech

Self Cite

View full text Add to dashboard Cite

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Accurate and cost‐effective prediction of HBsAg titer in industrial scale fermentation process of recombinant Pichia pastoris by using neural network based soft sensor

Hosseini

Javidanbardan

Khatami

2019

Biotech and App Biochem

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In the current work, the attempt was made to apply best-fitted artificial neural network (ANN) architecture and the respective training process for predicting final titer of hepatitis B surface antigen (HBsAg), produced intracellularly by recombinant Pichia pastoris Mut + in the commercial scale. For this purpose, in large-scale fed-batch fermentation, using methanol for HBsAg induction and cell growth, three parameters of average specific growth rate, biomass yield, and dry biomass concentration-in the definite integral form with respect to fermentation time-were selected as input vectors; the final concentration of HBsAg was selected for the ANN output. Used dataset consists of 38 runs from previous batches; feed-forward ANN 3:5:1 with training algorithm of backpropagation based on a Bayesian regularization was trained and tested with a high degree of accuracy. Implementing the verified ANN for predicting the HBsAg titer of the five new fermentation runs, excluded from the dataset, in the full-scale production, the coefficient of regression and root-mean-square error were found to be 0.969299 and 2.716774, respectively. These results suggest that this verified soft sensor could be an excellent alternative for the current relatively expensive and time-intensive analytical techniques such as enzyme-linked immunosorbent assay in the biopharmaceutical industry.

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Development of a continuous fermentation process for the production of recombinant uricase enzyme by Pichia pastoris

Mahboudi,

Abbas Shojaosadati,

Maghsoudi

et al. 2023

Biotech and App Biochem

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Recent studies in the biopharmaceutical industry have shown an increase in the productivity and production efficiency of recombinant proteins by continuous culture. In this research, a new upstream fermentation process was developed for the production of recombinant uricase in the methylotrophic yeast Pichia pastoris. Expression of recombinant protein in this system is under the control of the AOX1 promoter and therefore requires methanol as an inducing agent and carbon/energy source. Considering the biphasic growth characteristics of conventional fed‐batch fermentation, physical separation of the growth and induction stages for better control of the continuous fermentation process resulted in higher dry‐cell weight (DCW) and enhanced recombinant urate oxidase activity. The DCW and recombinant uricase activity enzyme for fed‐batch fermentation were 79 g/L and 6.8 u/mL. During the continuous process, in the growth fermenter at a constant dilution rate of 0.025 h−1, DCW increased to 88.39 g/L. In the induction fermenter, at methanol feeding rates of 30, 60, and 80 mL/h, a recombinant uricase activity was 4.13, 7.2, and 0 u/mL, respectively. The optimum methanol feeding regime in continuous fermentation resulted in a 4.5‐fold improvement in productivity compared with fed‐batch fermentation from 0.04 u/mL/h (0.0017 mg/mL/h) to 0.18 u/mL/h (0.0078 mg/mL/h).

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Enhancing the efficiency of recombinant hepatitis B surface antigen production in Pichia pastoris by employing continuous fermentation

Cited by 35 publications

References 32 publications

Comparative study of μ‐stat methanol feeding control in fed‐batch fermentation of Pichia pastoris producing HBsAg: an open‐loop control versus recurrent artificial neural network‐based feedback control

Comparative study of μ‐stat methanol feeding control in fed‐batch fermentation of Pichia pastoris producing HBsAg: an open‐loop control versus recurrent artificial neural network‐based feedback control

Accurate and cost‐effective prediction of HBsAg titer in industrial scale fermentation process of recombinant Pichia pastoris by using neural network based soft sensor

Development of a continuous fermentation process for the production of recombinant uricase enzyme by Pichia pastoris

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