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Structured population balances to support microalgae-based processes: Review of the state-of-art and perspectives analysis
Design and optimization of microalgae processes have traditionally relied on the application of unsegregated mathematical models, thus neglecting the impact of cell-to-cell heterogeneity. However, there is experimental evidence that the latter one, including but not limited to variation in mass/size...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9918424/ https://www.ncbi.nlm.nih.gov/pubmed/36789264 http://dx.doi.org/10.1016/j.csbj.2023.01.042 |
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author | Usai, Alessandro Theodoropoulos, Constantinos Di Caprio, Fabrizio Altimari, Pietro Cao, Giacomo Concas, Alessandro |
author_facet | Usai, Alessandro Theodoropoulos, Constantinos Di Caprio, Fabrizio Altimari, Pietro Cao, Giacomo Concas, Alessandro |
author_sort | Usai, Alessandro |
collection | PubMed |
description | Design and optimization of microalgae processes have traditionally relied on the application of unsegregated mathematical models, thus neglecting the impact of cell-to-cell heterogeneity. However, there is experimental evidence that the latter one, including but not limited to variation in mass/size, internal composition and cell cycle phase, can play a crucial role in both cultivation and downstream processes. Population balance equations (PBEs) represent a powerful approach to develop mathematical models describing the effect of cell-to-cell heterogeneity. In this work, the potential of PBEs for the analysis and design of microalgae processes are discussed. A detailed review of PBE applications to microalgae cultivation, harvesting and disruption is reported. The review is largely focused on the application of the univariate size/mass structured PBE, where the size/mass is the only internal variable used to identify the cell state. Nonetheless, the need, addressed by few studies, for additional or alternative internal variables to identify the cell cycle phase and/or provide information about the internal composition is discussed. Through the review, the limitations of previous studies are described, and areas are identified where the development of more reliable PBE models, driven by the increasing availability of single-cell experimental data, could support the understanding and purposeful exploitation of the mechanisms determining cell-to-cell heterogeneity. |
format | Online Article Text |
id | pubmed-9918424 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-99184242023-02-13 Structured population balances to support microalgae-based processes: Review of the state-of-art and perspectives analysis Usai, Alessandro Theodoropoulos, Constantinos Di Caprio, Fabrizio Altimari, Pietro Cao, Giacomo Concas, Alessandro Comput Struct Biotechnol J Review Design and optimization of microalgae processes have traditionally relied on the application of unsegregated mathematical models, thus neglecting the impact of cell-to-cell heterogeneity. However, there is experimental evidence that the latter one, including but not limited to variation in mass/size, internal composition and cell cycle phase, can play a crucial role in both cultivation and downstream processes. Population balance equations (PBEs) represent a powerful approach to develop mathematical models describing the effect of cell-to-cell heterogeneity. In this work, the potential of PBEs for the analysis and design of microalgae processes are discussed. A detailed review of PBE applications to microalgae cultivation, harvesting and disruption is reported. The review is largely focused on the application of the univariate size/mass structured PBE, where the size/mass is the only internal variable used to identify the cell state. Nonetheless, the need, addressed by few studies, for additional or alternative internal variables to identify the cell cycle phase and/or provide information about the internal composition is discussed. Through the review, the limitations of previous studies are described, and areas are identified where the development of more reliable PBE models, driven by the increasing availability of single-cell experimental data, could support the understanding and purposeful exploitation of the mechanisms determining cell-to-cell heterogeneity. Research Network of Computational and Structural Biotechnology 2023-01-31 /pmc/articles/PMC9918424/ /pubmed/36789264 http://dx.doi.org/10.1016/j.csbj.2023.01.042 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Usai, Alessandro Theodoropoulos, Constantinos Di Caprio, Fabrizio Altimari, Pietro Cao, Giacomo Concas, Alessandro Structured population balances to support microalgae-based processes: Review of the state-of-art and perspectives analysis |
title | Structured population balances to support microalgae-based processes: Review of the state-of-art and perspectives analysis |
title_full | Structured population balances to support microalgae-based processes: Review of the state-of-art and perspectives analysis |
title_fullStr | Structured population balances to support microalgae-based processes: Review of the state-of-art and perspectives analysis |
title_full_unstemmed | Structured population balances to support microalgae-based processes: Review of the state-of-art and perspectives analysis |
title_short | Structured population balances to support microalgae-based processes: Review of the state-of-art and perspectives analysis |
title_sort | structured population balances to support microalgae-based processes: review of the state-of-art and perspectives analysis |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9918424/ https://www.ncbi.nlm.nih.gov/pubmed/36789264 http://dx.doi.org/10.1016/j.csbj.2023.01.042 |
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