Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling

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 ce...

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Main Authors: Rebeca González-Cabaleiro, Anca M. Mitchell, Wendy Smith, Anil Wipat, Irina D. Ofiţeru
Format: Article
Language:English
Published: Frontiers Media S.A. 2017-09-01
Series:Frontiers in Microbiology
Subjects:
Online Access:http://journal.frontiersin.org/article/10.3389/fmicb.2017.01813/full
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spelling doaj-d179ba75a50d4db78ada60cc7a8d53362020-11-25T00:14:01ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2017-09-01810.3389/fmicb.2017.01813291259Heterogeneity in Pure Microbial Systems: Experimental Measurements and ModelingRebeca González-Cabaleiro0Anca M. Mitchell1Wendy Smith2Anil Wipat3Irina D. Ofiţeru4School of Engineering, Chemical Engineering, Newcastle UniversityNewcastle upon Tyne, United KingdomSchool of Engineering, Chemical Engineering, Newcastle UniversityNewcastle upon Tyne, United KingdomInterdisciplinary Computing and Complex BioSystems (ICOS), School of ComputingNewcastle University, Newcastle upon Tyne, United KingdomInterdisciplinary Computing and Complex BioSystems (ICOS), School of ComputingNewcastle University, Newcastle upon Tyne, United KingdomSchool of Engineering, Chemical Engineering, Newcastle UniversityNewcastle upon Tyne, United KingdomCellular 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.http://journal.frontiersin.org/article/10.3389/fmicb.2017.01813/fullpopulation heterogeneitysingle cell analysisflow cytometrypopulation balance modelsindividual based models
collection DOAJ
language English
format Article
sources DOAJ
author Rebeca González-Cabaleiro
Anca M. Mitchell
Wendy Smith
Anil Wipat
Irina D. Ofiţeru
spellingShingle Rebeca González-Cabaleiro
Anca M. Mitchell
Wendy Smith
Anil Wipat
Irina D. Ofiţeru
Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling
Frontiers in Microbiology
population heterogeneity
single cell analysis
flow cytometry
population balance models
individual based models
author_facet Rebeca González-Cabaleiro
Anca M. Mitchell
Wendy Smith
Anil Wipat
Irina D. Ofiţeru
author_sort Rebeca González-Cabaleiro
title Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling
title_short Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling
title_full Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling
title_fullStr Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling
title_full_unstemmed Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling
title_sort heterogeneity in pure microbial systems: experimental measurements and modeling
publisher Frontiers Media S.A.
series Frontiers in Microbiology
issn 1664-302X
publishDate 2017-09-01
description 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.
topic population heterogeneity
single cell analysis
flow cytometry
population balance models
individual based models
url http://journal.frontiersin.org/article/10.3389/fmicb.2017.01813/full
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