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Cell Assessment by At-line Microscopy

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1104))

Abstract

This protocol regards a microscopic application and software for image-guided monitoring of mammalian cells which grow in suspension cultures. It has been developed in order to establish an automated microscopic application for in situ and at-line cell monitoring in bioreactors (Akin et al., Biosens Bioelectron 26:4532–4537, 2011; Babitzky et al., At-line microscopic analysis of suspension cell cultures. In: ECCE/ECAB, the first joint European Congress of chemical engineering and applied biotechnology, September 25–29, 2011, Berlin, Germany, 2011. http://www.tci.uni-hannover.de, Poster). The application aims to assess the analysis of an appropriated sample volume of mammalian cell cultivation medium. The sample is injected into a microfluidic slide which is suitable for transmitted light microscopy and is attached to an automated microscope device, the at-line microscope. The major attribute of microscope automation ascribes to the camera software, which enables sequential image capturing and storing. Image analysis and cell detection are performed by the software that is based on the edge detection algorithm developed by Canny (IEEE Trans Pattern Anal Mach Intell 8:679–698, 1986; Finding edges and lines in images.Technical Report 720, MIT Artificial Intelligence Laboratory, 1983). The analysis results are cell count, morphological characteristics, and grayscale values of the detected cells. The presented setup can be applied to low-volume cultivations and has been successfully tested for monitoring CHO-K1 cell cultivation processes.

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References

  1. Graphic Analyzer. http://www.tci.uni-hannover.de

  2. Akin M, Prediger A, Scheper T et al (2011) A new set up for multi-analyte sensing: at-line bio-process monitoring. Biosens Bioelectron 26(11):4532–4537

    Article  CAS  Google Scholar 

  3. Babitzky A, Lindner P, Scheper T et al (2011) Atline microscopic analysis of suspension cell cultures. In: ECCE/ECAB, the first joint European Congress of chemical engineering and applied biotechnology, September 25–29, 2011, Berlin, Germany. http://www.tci.uni-hannover.de, Poster

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    Book  Google Scholar 

  9. Canny JF (1986) A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell 8(6):679–698

    Article  CAS  Google Scholar 

  10. Canny JF (1983) Finding edges and lines in images. Technical report 720, MIT Artificial Intelligence Laboratory

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Acknowledgments

The work on this project was granted by BMBF and was performed in case of the project SysCompart.

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Babitzky, A., Lindner, P., Scheper, T. (2014). Cell Assessment by At-line Microscopy. In: Pörtner, R. (eds) Animal Cell Biotechnology. Methods in Molecular Biology, vol 1104. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-733-4_21

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  • DOI: https://doi.org/10.1007/978-1-62703-733-4_21

  • Published:

  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-732-7

  • Online ISBN: 978-1-62703-733-4

  • eBook Packages: Springer Protocols

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