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An automated continuous monitoring system: a useful tool for monitoring neuronal differentiation of human embryonic stem cells

Tuomas Tapani Huttunen, Maria Sundberg, Harri Pihlajamäki, Riitta Suuronen, Heli Skottman, Riikka Äänismaa, Susanna Narkilahti
  • Tuomas Tapani Huttunen
    Regea - Institute for Regenerative Medicine, University of Tampere and Tampere University Hospital, Tampere, Finland
  • Maria Sundberg
    Regea - Institute for Regenerative Medicine, University of Tampere and Tampere University Hospital, Tampere, Finland
  • Harri Pihlajamäki
    Centre for Military Medicine, Helsink, Finland
  • Riitta Suuronen
    Regea - Institute for Regenerative Medicine, University of Tampere and Tampere University Hospital; Department of Eye, Ear and Oral Diseases, Tampere University Hospital, Tampere; Department of Biomedical Engineering, Tampere University of Technology, Tampere, Finland
  • Heli Skottman
    Regea - Institute for Regenerative Medicine, University of Tampere and Tampere University Hospital, Tampere, Finland
  • Riikka Äänismaa
    Regea - Institute for Regenerative Medicine, University of Tampere and Tampere University Hospital, Tampere, Finland
  • Susanna Narkilahti
    Regea - Institute for Regenerative Medicine, University of Tampere and Tampere University Hospital, Tampere, Finland | susanna.narkilahti@uta.fi

Abstract

The currently used cell culturing and differentiation procedures are both time- and laborintensive. Automation of some of these procedures will increase the efficiency of commonly used cell differentiation protocols. We used a particular cell culture platform to rapidly and efficiently screen the neuronal differentiation of human embryonic stem cells (hESC). Continuous live monitoring and analysis of non-labeled cells using this system allowed us to characterize neuronal populations over the entire neuronal differentiation process. The differentiation of individual cells from early progenitor cells to neurons and glial cells could be monitored continuously using this system with sub-confluent cell cultures. The imaged data was collected and analyzed with a specially designed cell recognition protocol, which resulted in a quantitative neuronal cell count. The analysis results were confirmed using conventional laboratory methods such as manual counting and flow cytometry. Our findings suggest that an automated culture platform combined with automated monitoring and analysis systems is a reliable method for developing enhanced cell differentiation procedures or as part of an automated quality control system for existing protocols.

Keywords

human embryonic stem cells, neural differentiation, automated imaging, machine vision.

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Submitted: 2011-05-27 08:08:00
Published: 2011-08-22 14:06:59
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Copyright (c) 2011 Tuomas Tapani Huttunen, Maria Sundberg, Harri Pihlajamäki, Riitta Suuronen, Heli Skottman, Riikka Äänismaa, Susanna Narkilahti

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