Critical physical parameters for optimum recombinant protein production in yeast systems

Yeasts become the most preferred expression system for the production of recombinant proteins which play an important role in the development of biopharmaceutical products, antibodies for disease treatment, and enzymes for the food industries. The ability to grow in simple media, and ease of genetic...

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Main Authors: Pallujam, Asha Devi, Zali, Siti Afiqah, Oslan, Siti Nur Hazwani, Salleh, Abu Bakar, Oslan, Siti Nurbaya
Format: Article
Language:English
Published: Malaysian Society for Biochemistry and Molecular Biology 2020
Online Access:http://psasir.upm.edu.my/id/eprint/88304/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/88304/
https://msbmb2010.wixsite.com/mjbmb/august-2020
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spelling my.upm.eprints.883042022-11-24T01:57:30Z http://psasir.upm.edu.my/id/eprint/88304/ Critical physical parameters for optimum recombinant protein production in yeast systems Pallujam, Asha Devi Zali, Siti Afiqah Oslan, Siti Nur Hazwani Salleh, Abu Bakar Oslan, Siti Nurbaya Yeasts become the most preferred expression system for the production of recombinant proteins which play an important role in the development of biopharmaceutical products, antibodies for disease treatment, and enzymes for the food industries. The ability to grow in simple media, and ease of genetic manipulation with the benefits of typical eukaryotic expression which include protein processing, folding, and posttranslational modifications, have pushed them as one of the emerging hosts for recombinant protein production. Furthermore, yeasts are additionally quicker, easy to use, and cost-effective with high yield production in comparison to higher expression hosts. The effective productivity of the recombinant proteins is also influenced by the external parameters. This paper reviews different optimization methods of the recombinant protein production for several factors such as pH, temperature, media, agitation rate, inducer, inoculum size and induction time using one factor at a time (OFAT), Response Surface Methodology (RSM) and Artificial Neural Network (ANN). This review highlights the current studies regarding the optimization of the recombinant proteins expressed in three different yeasts namely; Saccharomyces cerevisiae, Komagataella phaffii, and Yarrowia lipolytica. These are the critical parameters which can be used to optimize the recombinant protein in yeast systems. The purification methods used to purify the proteins are also discussed for each system. Malaysian Society for Biochemistry and Molecular Biology 2020 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/88304/1/ABSTRACT.pdf Pallujam, Asha Devi and Zali, Siti Afiqah and Oslan, Siti Nur Hazwani and Salleh, Abu Bakar and Oslan, Siti Nurbaya (2020) Critical physical parameters for optimum recombinant protein production in yeast systems. Malaysian Journal of Biochemistry and Molecular Biology, 23 (2). 34 - 45. ISSN 2600-9005 https://msbmb2010.wixsite.com/mjbmb/august-2020
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Yeasts become the most preferred expression system for the production of recombinant proteins which play an important role in the development of biopharmaceutical products, antibodies for disease treatment, and enzymes for the food industries. The ability to grow in simple media, and ease of genetic manipulation with the benefits of typical eukaryotic expression which include protein processing, folding, and posttranslational modifications, have pushed them as one of the emerging hosts for recombinant protein production. Furthermore, yeasts are additionally quicker, easy to use, and cost-effective with high yield production in comparison to higher expression hosts. The effective productivity of the recombinant proteins is also influenced by the external parameters. This paper reviews different optimization methods of the recombinant protein production for several factors such as pH, temperature, media, agitation rate, inducer, inoculum size and induction time using one factor at a time (OFAT), Response Surface Methodology (RSM) and Artificial Neural Network (ANN). This review highlights the current studies regarding the optimization of the recombinant proteins expressed in three different yeasts namely; Saccharomyces cerevisiae, Komagataella phaffii, and Yarrowia lipolytica. These are the critical parameters which can be used to optimize the recombinant protein in yeast systems. The purification methods used to purify the proteins are also discussed for each system.
format Article
author Pallujam, Asha Devi
Zali, Siti Afiqah
Oslan, Siti Nur Hazwani
Salleh, Abu Bakar
Oslan, Siti Nurbaya
spellingShingle Pallujam, Asha Devi
Zali, Siti Afiqah
Oslan, Siti Nur Hazwani
Salleh, Abu Bakar
Oslan, Siti Nurbaya
Critical physical parameters for optimum recombinant protein production in yeast systems
author_facet Pallujam, Asha Devi
Zali, Siti Afiqah
Oslan, Siti Nur Hazwani
Salleh, Abu Bakar
Oslan, Siti Nurbaya
author_sort Pallujam, Asha Devi
title Critical physical parameters for optimum recombinant protein production in yeast systems
title_short Critical physical parameters for optimum recombinant protein production in yeast systems
title_full Critical physical parameters for optimum recombinant protein production in yeast systems
title_fullStr Critical physical parameters for optimum recombinant protein production in yeast systems
title_full_unstemmed Critical physical parameters for optimum recombinant protein production in yeast systems
title_sort critical physical parameters for optimum recombinant protein production in yeast systems
publisher Malaysian Society for Biochemistry and Molecular Biology
publishDate 2020
url http://psasir.upm.edu.my/id/eprint/88304/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/88304/
https://msbmb2010.wixsite.com/mjbmb/august-2020
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score 13.214268