Metabolomics - a useful tool for prediction of protein production and processing?

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MEETING ABSTRACTOpen Access
Metabolomics - a useful tool for prediction of
protein production and processing?
Jennifer Kronthaler1,2*, Timo Schmidberger2, Christine Heel2
From 22nd European Society for Animal Cell Technology (ESACT) Meeting on Cell Based Technologies
Vienna, Austria. 15-18 May 2011
Introduction
Although CHO cells are widely used as hosts for recom-
binant protein production, still only little is known
regarding the interaction of metabolic alterations and
protein production and processing. Therefore, a more
sophisticated look into the cellular metabolism might
lead to a more efficient use of the production medium
resulting in high quantities of the protein with the
desired product quality. For intracellular metabolite
quantification the sample preparation including quench-
ing of cells is a very critical step strongly affecting sub-
sequent results. A simple and straightforward protocol,
not needing special equipment, was investigated focus-
ing on the efficiency of stopping metabolic activities and
the potential metabolic leakage due to losses in mem-
brane integrity. In a next attempt, the comparison
between the producer cell line and the corresponding
mock cell line using targeted mass spectrometry
approaches for intra- and extracellular metabolite quan-
tification was performed. The influence of the increased
protein production capacity and the need of a complex
glycosylation machinery on metabolite profiles was
assessed. In order to find a link between the determined
output parameters, detailed data evaluation including
multivariate data analysis tools was implemented.
Materials and methods
CHO producer cell line as well as corresponding mock
cell line (transfected with an empty plasmid) were culti-
vated as a fed-batch process in serum-free, chemically
defined in-house medium, comprising insulin. For the
experiments 15L bioreactors were used. Conditions were
36,5°C and ph 6,9. Sampling for subsequent metabolite
quantification (intra- as well as extracellular) took place
at various time points throughout cultivation.
Targeted metabolomic analysis was performed for cell
culture supernatants as well as for cell lysates using
freeze/thaw cycles after resuspension in phosphate buf-
fer for extraction. For the quantification of amino acids,
hexose and biogenic amines commercially available
AbsoluteIDQ KIT plates were used. This fully auto-
mated assay was based on PITC (phenylisothiocyanate)-
derivatization in the presence of internal standards fol-
lowed by LC-MS/MS detection using a AB SCIEX 4000
QTrap™ mass spectrometer with electrospray ionization
[1]. For the quantitative analysis of energy metabolism
intermediates (glycolysis, citrate cycle, urea cycle), a
hydrophilic interaction liquid chromatography (HILIC)-
ESI-MS/MS method in highly selective negative MRM
detection mode was used. Intracellular amounts of
nucleotides and nucleotide sugars were analyzed by
liquid chromatography-electrospray ionization-mass
spectrometry on surface-conditioned porous graphitic
carbon as described by Pabst et al. [2].
Results
The comparison between a CHO producer cell line and
the corresponding mock cell line enabled the assessment
of increased protein production capacity and the need of
a complex glycosylation machinery influencing metabo-
lite profiles. Multivariate data analysis using a PLS (par-
tial least square) model on all quantified compounds
showed similar progress throughout fermentation for all
four cultivations (producer and mock in duplicates).
Changes between different sampling points, which
represent different stages of cultivation showed the
strongest impact. Thus, differences between tested cell
lines have to be evaluated for each phase individually as
no overall alteration is detectable.
* Correspondence: jennifer.kronthaler@sandoz.com
1University of Innsbruck, Innsbruck, Austria
Full list of author information is available at the end of the article
Kronthaler et al. BMC Proceedings 2011, 5(Suppl 8):P80
http://www.biomedcentral.com/1753-6561/5/S8/P80
© 2011 Kronthaler et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.

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Nucleotide sugars which play important key roles
within the mammalian glycosylation pathway showed
the major variance between producer and mock cell
line, as shown in figure 1: Early phase represents data
within exponential phase (up to and including day 7)
whereas late phase shows averaged data of day 10 and
12. The increased glycosylation processing in producer
cells seemed to lead to higher intracellular concentra-
tions of required precursors due to increased stimula-
tion of the overall glycosylation machinery. Otherwise,
an increased consumption by producer cells should have
led to lower concentrations or even to limiting bottle-
necks. The increased amounts of intracellular nucleotide
sugars at late stage for both cell lines were evident, but
an adequate explanation with respect to cell- and pro-
cess knowledge is still missing.
Moreover, within exponential phase (sampling on day
3-7) specific consumption/production rates of divers
metabolites were different between producer and mock
cell line. Mostly, amino acids were affected. Mock cells
showed an increased energy demand reflected by higher
specific consumption rates. Thus, especially the slightly
higher growth rate of mock cells seemed to be of rele-
vance resulting in a differentiation between proliferating
and producing cells. However, detailed investigation of
impacts of involved pathways on recombinant protein
production and processing is still ongoing.
Conclusion and outlook
Within this study the application of detailed metabolite
data to mammalian process development was evaluated
preliminarily. Just marginal differences between
producer and mock cells were detectable. However,
further pathway-based investigations are still ongoing.
Author details
1University of Innsbruck, Innsbruck, Austria.2Sandoz Biopharmaceuticals,
Langkampfen, Austria.
Published: 22 November 2011
References
1.Freepatentsonline.com: 2007 [http://www.freepatentsonline.com/
20070004044.html].
2.Pabst M, Grass J, Fischl R, Leonard R, Jin C, Hinterkorner G, et al: Nucleotide
and nucleotide sugar analysis by liquid chromatography-electrospray
ionization-mass spectrometry on surface-conditioned porous graphitic
carbon. Anal Chem 2010, 82:9782-9788.
doi:10.1186/1753-6561-5-S8-P80
Cite this article as: Kronthaler et al.: Metabolomics - a useful tool for
prediction of protein production and processing? BMC Proceedings 2011
5(Suppl 8):P80.
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Figure 1 Intracellular nucleotide sugar concentrations
Kronthaler et al. BMC Proceedings 2011, 5(Suppl 8):P80
http://www.biomedcentral.com/1753-6561/5/S8/P80
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