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Experimental methods and modeling techniques for description of cell population heterogeneity

Lencastre Fernandes, R.; Nierychlo, M.; Lundin, L; Pedersen, Henrik A. E.; Puentes Tellez, P. E.; Dutta, A. K.; Carlquist, M. LU ; Bolic, A.; Schäpper, D. and Brunetti, A. C., et al. (2011) In Biotechnology Advances 29(6). p.575-599
Abstract

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... (More)

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.

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publication status
published
subject
keywords
Cell heterogeneity, Computational fluid dynamics, Flow cytometry, Microbioreactors, Microscopy, Population balance models, Raman spectroscopy, Reporter systems
in
Biotechnology Advances
volume
29
issue
6
pages
25 pages
publisher
Elsevier
external identifiers
  • scopus:80053439474
ISSN
0734-9750
DOI
10.1016/j.biotechadv.2011.03.007
language
English
LU publication?
no
id
b5b94213-7dc0-432c-a044-69b811d93021
date added to LUP
2017-02-02 12:44:23
date last changed
2017-11-05 05:13:01
@article{b5b94213-7dc0-432c-a044-69b811d93021,
  abstract     = {<p>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.</p>},
  author       = {Lencastre Fernandes, R. and Nierychlo, M. and Lundin, L and Pedersen, Henrik A. E. and Puentes Tellez, P. E. and Dutta, A. K. and Carlquist, M. and Bolic, A. and Schäpper, D. and Brunetti, A. C. and Helmark, Soren and Heins, Anna-Lena and Jensen, A. D. and Nopens, I and Rottwitt, K. and Szita, N. and van Elsas, J. D. and Nielsen, P H and Martinussen, J. and Sørensen, S. J. and Lantz, A. E. and Gernaey, K. V.},
  issn         = {0734-9750},
  keyword      = {Cell heterogeneity,Computational fluid dynamics,Flow cytometry,Microbioreactors,Microscopy,Population balance models,Raman spectroscopy,Reporter systems},
  language     = {eng},
  number       = {6},
  pages        = {575--599},
  publisher    = {Elsevier},
  series       = {Biotechnology Advances},
  title        = {Experimental methods and modeling techniques for description of cell population heterogeneity},
  url          = {http://dx.doi.org/10.1016/j.biotechadv.2011.03.007},
  volume       = {29},
  year         = {2011},
}