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Statistical modeling of single target cell encapsulation.

Moon S, Ceyhan E, Gurkan UA, Demirci U - PLoS ONE (2011)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Demirci Bio-Acoustic-MEMS in Medicine Laboratory, Center for Bioengineering, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.

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.

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The plot of single cell encapsulation probability versus number of target cells per droplet (a), and percentage of target cells in a reservoir (b) PDFs for a single target cell encapsulation, P(Xs) were shown with combined PDFs for selected cases: (a) Poisson distribution for 1.0×105 cells/ml cell concentration for four different target cell concentrations, and (b) cell encapsulation probability compared with experimental results from 10% to 50% target cell mixture.Modeled PDFs showed 5% error compared to the experimental results using specific parameters, μ, σ, and p.
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pone-0021580-g006: The plot of single cell encapsulation probability versus number of target cells per droplet (a), and percentage of target cells in a reservoir (b) PDFs for a single target cell encapsulation, P(Xs) were shown with combined PDFs for selected cases: (a) Poisson distribution for 1.0×105 cells/ml cell concentration for four different target cell concentrations, and (b) cell encapsulation probability compared with experimental results from 10% to 50% target cell mixture.Modeled PDFs showed 5% error compared to the experimental results using specific parameters, μ, σ, and p.

Mentions: For the overall process PDF for a single target cell encapsulation as in (eq. 3.6), Fig. 6 shows PDFs for the random variable, Xs, and conditional PDF for selected cases of 1.0×105 cells/ml (Fig. 6a) and 10% target cell mixture (Fig. 6b). The combined PDF is similar to Poisson distribution, since the overall probability of single target cell encapsulation (considering empty droplets) is also low. The error in the fit of the modeled Poisson PDFs is within 5%, when the experimental results are compared using specific parameter values of μ, σ, and p.


Statistical modeling of single target cell encapsulation.

Moon S, Ceyhan E, Gurkan UA, Demirci U - PLoS ONE (2011)

The plot of single cell encapsulation probability versus number of target cells per droplet (a), and percentage of target cells in a reservoir (b) PDFs for a single target cell encapsulation, P(Xs) were shown with combined PDFs for selected cases: (a) Poisson distribution for 1.0×105 cells/ml cell concentration for four different target cell concentrations, and (b) cell encapsulation probability compared with experimental results from 10% to 50% target cell mixture.Modeled PDFs showed 5% error compared to the experimental results using specific parameters, μ, σ, and p.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3140975&req=5

pone-0021580-g006: The plot of single cell encapsulation probability versus number of target cells per droplet (a), and percentage of target cells in a reservoir (b) PDFs for a single target cell encapsulation, P(Xs) were shown with combined PDFs for selected cases: (a) Poisson distribution for 1.0×105 cells/ml cell concentration for four different target cell concentrations, and (b) cell encapsulation probability compared with experimental results from 10% to 50% target cell mixture.Modeled PDFs showed 5% error compared to the experimental results using specific parameters, μ, σ, and p.
Mentions: For the overall process PDF for a single target cell encapsulation as in (eq. 3.6), Fig. 6 shows PDFs for the random variable, Xs, and conditional PDF for selected cases of 1.0×105 cells/ml (Fig. 6a) and 10% target cell mixture (Fig. 6b). The combined PDF is similar to Poisson distribution, since the overall probability of single target cell encapsulation (considering empty droplets) is also low. The error in the fit of the modeled Poisson PDFs is within 5%, when the experimental results are compared using specific parameter values of μ, σ, and p.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Demirci Bio-Acoustic-MEMS in Medicine Laboratory, Center for Bioengineering, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.

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.

Show MeSH
Related in: MedlinePlus