TY - JOUR
T1 - Experimental methods and modeling techniques for description of cell population heterogeneity
AU - Lencastre Fernandes, Rita
AU - Nierychlo, M.
AU - Lundin, L.
AU - Pedersen, Anne Egholm
AU - PuentesTellez, P. E.
AU - Dutta, A.
AU - Carlqvist, Magnus
AU - Bolic, Andrijana
AU - Schäpper, Daniel
AU - Brunetti, Anna Chiara
AU - Helmark, Søren
AU - Heins, Anna-Lena
AU - Jensen, Anker Degn
AU - Nopens, I.
AU - Rottwitt, Karsten
AU - Szita, Nicolas
AU - van Elsas, J. D.
AU - Nielsen, P. H.
AU - Martinussen, Jan
AU - Sørensen, S. J.
AU - Eliasson Lantz, Anna
AU - Gernaey, Krist
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
U2 - 10.1016/j.biotechadv.2011.03.007
DO - 10.1016/j.biotechadv.2011.03.007
M3 - Journal article
SN - 0734-9750
VL - 29
SP - 575
EP - 599
JO - Biotechnology Advances
JF - Biotechnology Advances
IS - 6
ER -