Experimental methods and modeling techniques for description of cell population heterogeneity

Publikationstyp
Review Article
Date Issued
2011-11
Sprache
English
Author(s)
Fernandes, Rita Lencastre
Nierychlo, Marta
Lundin, Luisa  
Pedersen, Anders Elm  
Puentes Tellez, Pilar Eliana
Dutta, Abhishek  
Carlquist, Magnus
Bolic, Andrijana
Schäpper, Daniel
Brunetti, Anna Chiara
Helmark, Søren
Heins, Anna-Lena  
Bioprozess- und Biosystemtechnik V-1  
Jensen, Anker Degn  
Nopens, Ingmar
Rottwitt, Karsten
Szita, Nicolas
Elsas, Jan Dirk van
Nielsen, Per H.  
Martinussen, Jan
Sørensen, Søren  
Lantz, Anna Eliasson
Gernaey, Krist  
TORE-URI
https://hdl.handle.net/11420/42631
Journal
Biotechnology advances  
Volume
29
Issue
6
Start Page
575
End Page
599
Citation
Biotechnology Advances 29 (6) : 575-599 (2011-11)
Publisher DOI
10.1016/j.biotechadv.2011.03.007
Scopus ID
2-s2.0-80053439474
PubMed ID
21540103
Publisher
Elsevier
With the continuous development, in the last decades, of analytical techniques providing complex information at single cell level, the study of cell heterogeneity has been the focus of several research projects within analytical biotechnology. Nonetheless, the complex interplay between environmental changes and cellular responses is yet not fully understood, and the integration of this new knowledge into the strategies for design, operation and control of bioprocesses is far from being an established reality. Indeed, the impact of cell heterogeneity on productivity of large scale cultivations is acknowledged but seldom accounted for. In order to include population heterogeneity mechanisms in the development of novel bioprocess control strategies, a reliable mathematical description of such phenomena has to be developed. With this review, we search to summarize the potential of currently available methods for monitoring cell population heterogeneity as well as model frameworks suitable for describing dynamic heterogeneous cell populations. We will furthermore underline the highly important coordination between experimental and modeling efforts necessary to attain a reliable quantitative description of cell heterogeneity, which is a necessity if such models are to contribute to the development of improved control of bioprocesses.
Subjects
Cell heterogeneity
Computational fluid dynamics
Flow cytometry
Microbioreactors
Microscopy
Population balance models
Raman spectroscopy
Reporter systems
DDC Class
570: Life Sciences, Biology