Development of a novel cell sorting method that samples population diversity in flow cytometry

Osborne, Geoffrey W., Andersen, Stacey B. and Battye, Francis L. (2015) Development of a novel cell sorting method that samples population diversity in flow cytometry. Cytometry Part A, 87 11: 1047-1051. doi:10.1002/cyto.a.22678

Author Osborne, Geoffrey W.
Andersen, Stacey B.
Battye, Francis L.
Title Development of a novel cell sorting method that samples population diversity in flow cytometry
Journal name Cytometry Part A   Check publisher's open access policy
ISSN 1552-4930
Publication date 2015
Sub-type Article (original research)
DOI 10.1002/cyto.a.22678
Volume 87
Issue 11
Start page 1047
End page 1051
Total pages 5
Place of publication Hoboken, NJ, United States
Publisher John Wiley & Sons
Collection year 2016
Language eng
Abstract Flow cytometry based electrostatic cell sorting is an important tool in the separation of cell populations. Existing instruments can sort single cells into multi-well collection plates, and keep track of cell of origin and sorted well location. However currently single sorted cell results reflect the population distribution and fail to capture the population diversity. Software was designed that implements a novel sorting approach, "Slice and Dice Sorting," that links a graphical representation of a multi-well plate to logic that ensures that single cells are sampled and sorted from all areas defined by the sort region/s. Therefore the diversity of the total population is captured, and the more frequently occurring or rarer cell types are all sampled. The sorting approach was tested computationally, and using functional cell based assays. Computationally we demonstrate that conventional single cell sorting can sample as little as 50% of the population diversity dependant on the population distribution, and that Slice and Dice sorting samples much more of the variety present within a cell population. We then show by sorting single cells into wells using the Slice and Dice sorting method that there are cells sorted using this method that would be either rarely sorted, or not sorted at all using conventional single cell sorting approaches. The present study demonstrates a novel single cell sorting method that samples much more of the population diversity than current methods. It has implications in clonal selection, stem cell sorting, single cell sequencing and any areas where population heterogeneity is of importance.
Keyword Index sorting
Key terms
Single cell sorting
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

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