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Lookup NU author(s): Dr Rebeca Gonzalez-Cabaleiro, Anca Mitchell, Dr Wendy Smith, Professor Anil Wipat, Dr Dana OfiteruORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2017 González-Cabaleiro, Mitchell, Smith, Wipat and Ofiteru. Cellular heterogeneity influences bioprocess performance in ways that until date are not completely elucidated. In order to account for this phenomenon in the design and operation of bioprocesses, reliable analytical and mathematical descriptions are required. We present an overview of the single cell analysis, and the mathematical modeling frameworks that have potential to be used in bioprocess control and optimization, in particular for microbial processes. In order to be suitable for bioprocess monitoring, experimental methods need to be high throughput and to require relatively short processing time. One such method used successfully under dynamic conditions is flow cytometry. Population balance and individual based models are suitable modeling options, the latter one having in particular a good potential to integrate the various data collected through experimentation. This will be highly beneficial for appropriate process design and scale up as a more rigorous approach may prevent a priori unwanted performance losses. It will also help progressing synthetic biology applications to industrial scale.
Author(s): Gonzalez-Cabaleiro R, Mitchell AM, Smith W, Wipat A, Ofiteru ID
Publication type: Review
Publication status: Published
Journal: Frontiers in Microbiology
Year: 2017
Volume: 8
Online publication date: 20/09/2017
Acceptance date: 05/09/2017
ISSN (electronic): 1664-302X
Publisher: Frontiers Media S.A.
URL: https://doi.org/10.3389/fmicb.2017.01813
DOI: 10.3389/fmicb.2017.01813
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