Automated Suspension Cell Monitoring in Stirred Bioreactors
Continuous Suspension Cell Culture Monitoring in Bioreactors
Abstract Cell monitoring in large scale suspension cell cultures often relies on sampling followed by a staining procedure. An estimation of the cell count and cell viability are traditionally performed once a day using a Trypan-Blue cell exclusion method or other. These off-line techniques require manual operations and the stained samples are destroyed after measurement (creating toxic waste). It often requires weekend work too. Differential Digital Holographic Microscopy (DDHM) is a new quantitative imaging technique that allows cell counting as well as cell viability monitoring in a continuous, label-free set-up. No need for sampling (eliminating the risk of contamination) or staining, results are available in nearly real-time and this over the whole run as the OsOne software plots the cell growth curves live on the screen. Moreover, OsOne also shows real-time images of the cells, offering to the experienced eye a convenient way to have a look at the culture. In this study, we compared the results generated by the iLine-F with 2 reference methods applying Trypan-Blue staining: a) manual counting and b) the off-line counter Vi-Cell XR (Beckman Coulter). The iLine-F was set to generate 2 cell count cycles per hour and the culture was left to grow in batch mode for a total of 13 days. In addition to the benefits of having a continuous monitoring of the culture, a correlation factor R² of 0.93 was obtained for the viable cell density demonstrating that the results achieved with the label-free DDHM method are in line with current methods applying Trypan-Blue staining.
Advantages • Full traceability at single cell level • Continuous monitoring • User independent, improving
reproducibility • No sampling, no staining • No toxic waste • Ready for automation
• Increased insight in your culture process
• Adds cluster information as clusters are not disrupted during sample preparation
• More than just cell density and viability: up to 16 morphologic parameters are recorded
Materials & Methods • iLine-F DDHM device • BioConnect: autoclavable and
disposable closed-loop interface with the bioreactor.
• Reusable pump engine with automated flushing (in case air bubbles or large aggregates are detected, patent pending).
• OsOne Acquisition & Analysis software (developed in-house by OVIZIO), version 3.8.
• Applikon 3 liters glass bioreactor controlled by ez-Control.
• CHO cells inoculated at 0.3x106 viable cells/mL in CD-OptiCHO™ medium (Life Technologies), batch culture.
Jérémie Barbau & Joël Henneghien
OVIZIO Imaging Systems SA/NV, Brussels, Belgium
Contacts: [email protected], [email protected]
Results
a b
Future Developments
§ The availability of full data, per cell, for the whole experiment allows to envision the use of iLine F for a PAT approach. Indeed the large amount of data produced can be used to perform various statistical analysis on the cell population in order to define and control critical parameters of the process.
§ One possibility is also to link the iLine F with the bioreactor controller in order to control for instance the feeding, based on the cell density, or the harvest time after a viral infection, based on the viability of the culture. There is virtually no limitation to automate your cell culture process.
§ One next step for us would be to have a central control server that collects data from several iLine-F simultaneously. Thus a centralized computer could perform all the calculations while only the microscope occupies valuable space in the lab.
§ Furthermore, smartphones could connect to the central control server and cell data could become accessible anywhere, anytime.
§ Finally, an API (Application Programming Interface) is currently in development in order to integrate into other Processes Information Management Systems.
§ Very good correlation (R² = 0.93) of the cell density and cell viability compared to classic staining methods applying sampling and Trypan-Blue staining. This also proves that the label-free approach is equivalent to extensively validated reference methods.
§ Availability of full data per cell, for the whole experiment, for validation, QC, audit, etc.
Conclusions
Correlation between Vi-Cell XR and iLine F for cell viability counting
iLine F generated results: (a) growth curve plotting Viability, Total Cell Density (TCD) and Viable Cell Density (VCD) over time (b) cell viability monitoring, accessible at single cell level (showing a dead cell plotted on the screen and on the dot plot, with below its morphologic data) (c) results comparative assay: measurements with OsOne are fitting with those performed offline by Vi-Cell XR or by Trypan-Blue manual counting.
c b
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