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Optimization of Fermentation Conditions for Reteplase Expression by Escherichia coli Using Response Surface Methodology
BACKGROUND: Expression of heterologous proteins at large scale is often a challenging job due to plasmid instability, accumulation of acetate and oxidative damage in bioreactors. Therefore, it is necessary to optimize parameters influencing cell growth and expression of recombinant protein. METHODS:...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Avicenna Research Institute
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6490408/ https://www.ncbi.nlm.nih.gov/pubmed/31057718 |
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author | Zare, Hamze Mir Mohammad Sadeghi, Hamid Akbari, Vajihe |
author_facet | Zare, Hamze Mir Mohammad Sadeghi, Hamid Akbari, Vajihe |
author_sort | Zare, Hamze |
collection | PubMed |
description | BACKGROUND: Expression of heterologous proteins at large scale is often a challenging job due to plasmid instability, accumulation of acetate and oxidative damage in bioreactors. Therefore, it is necessary to optimize parameters influencing cell growth and expression of recombinant protein. METHODS: In the present study, the optimal culture conditions for expression of reteplase by Escherichia coli (E. coli) BL21 (DE3) in a bench-top bioreactor was determined. Response Surface Methodology (RSM) based on Box-Behnken design was used to evaluate the effect of three variables (i.e., temperature, shaking speed and pH) and their interactions with cellular growth and protein production. The obtained data were analyzed by Design Expert software. RESULTS: Based on results of 15 experiments, a response surface quadratic model was developed which was used to explain the relation between production of reteplase and three investigated variables. The high value of “R-Squared” (0.9894) and F-value of 51.99 confirmed the accuracy of this model. According to the developed model, the optimum fermentation conditions for reteplase expression were temperature of 32°C, shaking speed of 210 rpm, and pH of 8.4. This predicted condition was applied for the production of reteplase in the bioreactor leading to a protein yield of 188 mg/l. CONCLUSION: Our results indicate the significant role of culture conditions (e.g., pH, temperature and oxygen supply) in protein expression at large scale and confirm the need for optimization. The proposed strategy here can also be applied to experimental set-up of optimization for fermentation of other proteins. |
format | Online Article Text |
id | pubmed-6490408 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Avicenna Research Institute |
record_format | MEDLINE/PubMed |
spelling | pubmed-64904082019-05-03 Optimization of Fermentation Conditions for Reteplase Expression by Escherichia coli Using Response Surface Methodology Zare, Hamze Mir Mohammad Sadeghi, Hamid Akbari, Vajihe Avicenna J Med Biotechnol Original Article BACKGROUND: Expression of heterologous proteins at large scale is often a challenging job due to plasmid instability, accumulation of acetate and oxidative damage in bioreactors. Therefore, it is necessary to optimize parameters influencing cell growth and expression of recombinant protein. METHODS: In the present study, the optimal culture conditions for expression of reteplase by Escherichia coli (E. coli) BL21 (DE3) in a bench-top bioreactor was determined. Response Surface Methodology (RSM) based on Box-Behnken design was used to evaluate the effect of three variables (i.e., temperature, shaking speed and pH) and their interactions with cellular growth and protein production. The obtained data were analyzed by Design Expert software. RESULTS: Based on results of 15 experiments, a response surface quadratic model was developed which was used to explain the relation between production of reteplase and three investigated variables. The high value of “R-Squared” (0.9894) and F-value of 51.99 confirmed the accuracy of this model. According to the developed model, the optimum fermentation conditions for reteplase expression were temperature of 32°C, shaking speed of 210 rpm, and pH of 8.4. This predicted condition was applied for the production of reteplase in the bioreactor leading to a protein yield of 188 mg/l. CONCLUSION: Our results indicate the significant role of culture conditions (e.g., pH, temperature and oxygen supply) in protein expression at large scale and confirm the need for optimization. The proposed strategy here can also be applied to experimental set-up of optimization for fermentation of other proteins. Avicenna Research Institute 2019 /pmc/articles/PMC6490408/ /pubmed/31057718 Text en Copyright© 2019 Avicenna Research Institute http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Zare, Hamze Mir Mohammad Sadeghi, Hamid Akbari, Vajihe Optimization of Fermentation Conditions for Reteplase Expression by Escherichia coli Using Response Surface Methodology |
title | Optimization of Fermentation Conditions for Reteplase Expression by Escherichia coli Using Response Surface Methodology |
title_full | Optimization of Fermentation Conditions for Reteplase Expression by Escherichia coli Using Response Surface Methodology |
title_fullStr | Optimization of Fermentation Conditions for Reteplase Expression by Escherichia coli Using Response Surface Methodology |
title_full_unstemmed | Optimization of Fermentation Conditions for Reteplase Expression by Escherichia coli Using Response Surface Methodology |
title_short | Optimization of Fermentation Conditions for Reteplase Expression by Escherichia coli Using Response Surface Methodology |
title_sort | optimization of fermentation conditions for reteplase expression by escherichia coli using response surface methodology |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6490408/ https://www.ncbi.nlm.nih.gov/pubmed/31057718 |
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