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Statistical Modeling of Single Target Cell Encapsulation

Author

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  • SangJun Moon
  • Elvan Ceyhan
  • Umut Atakan Gurkan
  • Utkan Demirci

Abstract

High throughput drop-on-demand systems for separation and encapsulation of individual target cells from heterogeneous mixtures of multiple cell types is an emerging method in biotechnology that has broad applications in tissue engineering and regenerative medicine, genomics, and cryobiology. However, cell encapsulation in droplets is a random process that is hard to control. Statistical models can provide an understanding of the underlying processes and estimation of the relevant parameters, and enable reliable and repeatable control over the encapsulation of cells in droplets during the isolation process with high confidence level. We have modeled and experimentally verified a microdroplet-based cell encapsulation process for various combinations of cell loading and target cell concentrations. Here, we explain theoretically and validate experimentally a model to isolate and pattern single target cells from heterogeneous mixtures without using complex peripheral systems.

Suggested Citation

  • SangJun Moon & Elvan Ceyhan & Umut Atakan Gurkan & Utkan Demirci, 2011. "Statistical Modeling of Single Target Cell Encapsulation," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-11, July.
    • Handle: RePEc:plo:pone00:0021580
    DOI: 10.1371/journal.pone.0021580
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    References listed on IDEAS

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    1. Sangjun Moon & Yun-Gon Kim & Lingsheng Dong & Michael Lombardi & Edward Haeggstrom & Roderick V Jensen & Li-Li Hsiao & Utkan Demirci, 2011. "Drop-on-Demand Single Cell Isolation and Total RNA Analysis," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-10, March.
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