Modeling and tuning of glucose oxidase‐catalase system incorporating dissolved oxygen concentration
BACKGROUND Gluconic acid production by a glucose oxidase (GOx) and catalase (CAT) system has been proposed. However, the bioprocess optimal design and operation are limited by the lack of kinetic models of GOx involving oxygen as substrate. Herein, the GOx‐CAT system is modeled considering a continu...
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| Veröffentlicht in: | Journal of chemical technology and biotechnology (1986) 2023-06, Vol.98 (6), p.1520-1531 |
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| container_title | Journal of chemical technology and biotechnology (1986) |
| container_volume | 98 |
| creator | Ruales‐Salcedo, Angela V. Prado‐Rubio, Oscar Andrés Fontalvo, Javier Higuita, Juan Carlos Woodley, John M. |
| description | BACKGROUND
Gluconic acid production by a glucose oxidase (GOx) and catalase (CAT) system has been proposed. However, the bioprocess optimal design and operation are limited by the lack of kinetic models of GOx involving oxygen as substrate. Herein, the GOx‐CAT system is modeled considering a continuous oxygen supply at a bioreactor lab scale. Initially, experiments and modeling for parameter estimations of KLa and the individual enzymes were conducted. Then, experiments and modeling for the GOx‐CAT system were performed for final model tuning. Additionally, the model quality was evaluated, allowing for a deeper understanding of the system phenomenology.
RESULTS
From the oxygen transport model tuning, a highly accurate KLa estimation was obtained (R2>0.98 and confidence interval |
| doi_str_mv | 10.1002/jctb.7374 |
| format | Article |
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Gluconic acid production by a glucose oxidase (GOx) and catalase (CAT) system has been proposed. However, the bioprocess optimal design and operation are limited by the lack of kinetic models of GOx involving oxygen as substrate. Herein, the GOx‐CAT system is modeled considering a continuous oxygen supply at a bioreactor lab scale. Initially, experiments and modeling for parameter estimations of KLa and the individual enzymes were conducted. Then, experiments and modeling for the GOx‐CAT system were performed for final model tuning. Additionally, the model quality was evaluated, allowing for a deeper understanding of the system phenomenology.
RESULTS
From the oxygen transport model tuning, a highly accurate KLa estimation was obtained (R2>0.98 and confidence interval <2%). The highest oxygen transport rate was obtained for the combined system Buffer‐antifoam‐GOx‐CAT that was 2.5 times larger than that obtained for DI water. Kinetic models for the individual enzymes were very accurate and the parameters were fully identifiable. For the integrated system, the gluconic acid evolution was properly predicted and there was a loss of predictive power for the oxygen model. Parameter identifiability analysis showed that kcatCAT and KMHPCAT interpretability was compromised. However, the sensitivity analysis indicated that the model must not be simplified.
CONCLUSION
Herein its has been demonstrated that KLa is a complex parameter to be estimated for multi‐enzymatic systems due to its dependency on medium composition, particularly with GOx. Nonetheless, based on the acceptable model predictive power, the calculated parameters could be used for studies on the process design phase. © 2023 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).</description><identifier>ISSN: 0268-2575</identifier><identifier>EISSN: 1097-4660</identifier><identifier>DOI: 10.1002/jctb.7374</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>Acid production ; Bioreactors ; Biotechnology ; Catalase ; Chemical technology ; Confidence intervals ; Dissolved oxygen ; Enzymes ; Gluconic acid ; Glucose oxidase ; GOx‐CAT kinetic parameters ; KLa estimation ; Mathematical models ; Modelling ; oxidoreductase ; Oxygen ; Parameter estimation ; Parameter identification ; Phenomenology ; Sensitivity analysis ; Substrates ; Transport rate ; Tuning</subject><ispartof>Journal of chemical technology and biotechnology (1986), 2023-06, Vol.98 (6), p.1520-1531</ispartof><rights>2023 The Authors. published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).</rights><rights>2023. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2924-363295db77e694be4101ff00d299464624b1864704c9fa759d3d38aab833873a3</cites><orcidid>0000-0002-7868-8736 ; 0000-0003-1419-542X ; 0000-0001-6471-166X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjctb.7374$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjctb.7374$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Ruales‐Salcedo, Angela V.</creatorcontrib><creatorcontrib>Prado‐Rubio, Oscar Andrés</creatorcontrib><creatorcontrib>Fontalvo, Javier</creatorcontrib><creatorcontrib>Higuita, Juan Carlos</creatorcontrib><creatorcontrib>Woodley, John M.</creatorcontrib><title>Modeling and tuning of glucose oxidase‐catalase system incorporating dissolved oxygen concentration</title><title>Journal of chemical technology and biotechnology (1986)</title><description>BACKGROUND
Gluconic acid production by a glucose oxidase (GOx) and catalase (CAT) system has been proposed. However, the bioprocess optimal design and operation are limited by the lack of kinetic models of GOx involving oxygen as substrate. Herein, the GOx‐CAT system is modeled considering a continuous oxygen supply at a bioreactor lab scale. Initially, experiments and modeling for parameter estimations of KLa and the individual enzymes were conducted. Then, experiments and modeling for the GOx‐CAT system were performed for final model tuning. Additionally, the model quality was evaluated, allowing for a deeper understanding of the system phenomenology.
RESULTS
From the oxygen transport model tuning, a highly accurate KLa estimation was obtained (R2>0.98 and confidence interval <2%). The highest oxygen transport rate was obtained for the combined system Buffer‐antifoam‐GOx‐CAT that was 2.5 times larger than that obtained for DI water. Kinetic models for the individual enzymes were very accurate and the parameters were fully identifiable. For the integrated system, the gluconic acid evolution was properly predicted and there was a loss of predictive power for the oxygen model. Parameter identifiability analysis showed that kcatCAT and KMHPCAT interpretability was compromised. However, the sensitivity analysis indicated that the model must not be simplified.
CONCLUSION
Herein its has been demonstrated that KLa is a complex parameter to be estimated for multi‐enzymatic systems due to its dependency on medium composition, particularly with GOx. Nonetheless, based on the acceptable model predictive power, the calculated parameters could be used for studies on the process design phase. © 2023 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).</description><subject>Acid production</subject><subject>Bioreactors</subject><subject>Biotechnology</subject><subject>Catalase</subject><subject>Chemical technology</subject><subject>Confidence intervals</subject><subject>Dissolved oxygen</subject><subject>Enzymes</subject><subject>Gluconic acid</subject><subject>Glucose oxidase</subject><subject>GOx‐CAT kinetic parameters</subject><subject>KLa estimation</subject><subject>Mathematical models</subject><subject>Modelling</subject><subject>oxidoreductase</subject><subject>Oxygen</subject><subject>Parameter estimation</subject><subject>Parameter identification</subject><subject>Phenomenology</subject><subject>Sensitivity analysis</subject><subject>Substrates</subject><subject>Transport rate</subject><subject>Tuning</subject><issn>0268-2575</issn><issn>1097-4660</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp1kLtOwzAUhi0EEqUw8AaWmBjSOrbjywgVVxWxlNlybKdKldrFToBsPALPyJOQUFam80vn-8-RPgDOczTLEcLzjWnLGSecHoBJjiTPKGPoEEwQZiLDBS-OwUlKG4QQE5hNgHsK1jW1X0PtLWw7P8ZQwXXTmZAcDB-11cl9f34Z3epmiDD1qXVbWHsT4i5E3Y4VW6cUmjdnh0a_dh6a4I3z7bgO_hQcVbpJ7uxvTsHL7c1qcZ8tn-8eFlfLzGCJaUYYwbKwJeeOSVo6mqO8qhCyWErKKMO0zAWjHFEjK80LaYklQutSECI40WQKLvZ3dzG8di61ahO66IeXCgvEBZWcFgN1uadMDClFV6ldrLc69ipHarSoRotqtDiw8z37Xjeu_x9Uj4vV9W_jB3cKdkE</recordid><startdate>202306</startdate><enddate>202306</enddate><creator>Ruales‐Salcedo, Angela V.</creator><creator>Prado‐Rubio, Oscar Andrés</creator><creator>Fontalvo, Javier</creator><creator>Higuita, Juan Carlos</creator><creator>Woodley, John M.</creator><general>John Wiley & Sons, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7QR</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7T7</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><orcidid>https://orcid.org/0000-0002-7868-8736</orcidid><orcidid>https://orcid.org/0000-0003-1419-542X</orcidid><orcidid>https://orcid.org/0000-0001-6471-166X</orcidid></search><sort><creationdate>202306</creationdate><title>Modeling and tuning of glucose oxidase‐catalase system incorporating dissolved oxygen concentration</title><author>Ruales‐Salcedo, Angela V. ; Prado‐Rubio, Oscar Andrés ; Fontalvo, Javier ; Higuita, Juan Carlos ; Woodley, John M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2924-363295db77e694be4101ff00d299464624b1864704c9fa759d3d38aab833873a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Acid production</topic><topic>Bioreactors</topic><topic>Biotechnology</topic><topic>Catalase</topic><topic>Chemical technology</topic><topic>Confidence intervals</topic><topic>Dissolved oxygen</topic><topic>Enzymes</topic><topic>Gluconic acid</topic><topic>Glucose oxidase</topic><topic>GOx‐CAT kinetic parameters</topic><topic>KLa estimation</topic><topic>Mathematical models</topic><topic>Modelling</topic><topic>oxidoreductase</topic><topic>Oxygen</topic><topic>Parameter estimation</topic><topic>Parameter identification</topic><topic>Phenomenology</topic><topic>Sensitivity analysis</topic><topic>Substrates</topic><topic>Transport rate</topic><topic>Tuning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ruales‐Salcedo, Angela V.</creatorcontrib><creatorcontrib>Prado‐Rubio, Oscar Andrés</creatorcontrib><creatorcontrib>Fontalvo, Javier</creatorcontrib><creatorcontrib>Higuita, Juan Carlos</creatorcontrib><creatorcontrib>Woodley, John M.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Online Library Free Content</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Journal of chemical technology and biotechnology (1986)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ruales‐Salcedo, Angela V.</au><au>Prado‐Rubio, Oscar Andrés</au><au>Fontalvo, Javier</au><au>Higuita, Juan Carlos</au><au>Woodley, John M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling and tuning of glucose oxidase‐catalase system incorporating dissolved oxygen concentration</atitle><jtitle>Journal of chemical technology and biotechnology (1986)</jtitle><date>2023-06</date><risdate>2023</risdate><volume>98</volume><issue>6</issue><spage>1520</spage><epage>1531</epage><pages>1520-1531</pages><issn>0268-2575</issn><eissn>1097-4660</eissn><abstract>BACKGROUND
Gluconic acid production by a glucose oxidase (GOx) and catalase (CAT) system has been proposed. However, the bioprocess optimal design and operation are limited by the lack of kinetic models of GOx involving oxygen as substrate. Herein, the GOx‐CAT system is modeled considering a continuous oxygen supply at a bioreactor lab scale. Initially, experiments and modeling for parameter estimations of KLa and the individual enzymes were conducted. Then, experiments and modeling for the GOx‐CAT system were performed for final model tuning. Additionally, the model quality was evaluated, allowing for a deeper understanding of the system phenomenology.
RESULTS
From the oxygen transport model tuning, a highly accurate KLa estimation was obtained (R2>0.98 and confidence interval <2%). The highest oxygen transport rate was obtained for the combined system Buffer‐antifoam‐GOx‐CAT that was 2.5 times larger than that obtained for DI water. Kinetic models for the individual enzymes were very accurate and the parameters were fully identifiable. For the integrated system, the gluconic acid evolution was properly predicted and there was a loss of predictive power for the oxygen model. Parameter identifiability analysis showed that kcatCAT and KMHPCAT interpretability was compromised. However, the sensitivity analysis indicated that the model must not be simplified.
CONCLUSION
Herein its has been demonstrated that KLa is a complex parameter to be estimated for multi‐enzymatic systems due to its dependency on medium composition, particularly with GOx. Nonetheless, based on the acceptable model predictive power, the calculated parameters could be used for studies on the process design phase. © 2023 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/jctb.7374</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-7868-8736</orcidid><orcidid>https://orcid.org/0000-0003-1419-542X</orcidid><orcidid>https://orcid.org/0000-0001-6471-166X</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Acid production Bioreactors Biotechnology Catalase Chemical technology Confidence intervals Dissolved oxygen Enzymes Gluconic acid Glucose oxidase GOx‐CAT kinetic parameters KLa estimation Mathematical models Modelling oxidoreductase Oxygen Parameter estimation Parameter identification Phenomenology Sensitivity analysis Substrates Transport rate Tuning |
| title | Modeling and tuning of glucose oxidase‐catalase system incorporating dissolved oxygen concentration |
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