Image-based single cell sorting automation in droplet microfluidics
File(s) 2020Sesen_ImageBasedSorting_SciRep.pdf (3.65 MB)
Published version
Author(s)
Sesen, Muhsincan
Whyte, Graeme
Type
Journal Article
Abstract
The recent boom in single-cell omics has brought researchers one step closer to understanding the biological mechanisms associated with cell heterogeneity. Rare cells that have historically been obscured by bulk measurement techniques are being studied by single cell analysis and providing valuable insight into cell function. To support this progress, novel upstream capabilities are required for single cell preparation for analysis. Presented here is a droplet microfluidic, image-based single-cell sorting technique that is flexible and programmable. The automated system performs real-time dual-camera imaging (brightfield & fluorescent), processing, decision making and sorting verification. To demonstrate capabilities, the system was used to overcome the Poisson loading problem by sorting for droplets containing a single red blood cell with 85% purity. Furthermore, fluorescent imaging and machine learning was used to load single K562 cells amongst clusters based on their instantaneous size and circularity. The presented system aspires to replace manual cell handling techniques by translating expert knowledge into cell sorting automation via machine learning algorithms. This powerful technique finds application in the enrichment of single cells based on their micrographs for further downstream processing and analysis.
Date Issued
2020-05-26
Date Acceptance
2020-05-06
Citation
Scientific Reports, 2020, 10 (1), pp.1-14
ISSN
2045-2322
Publisher
Nature Publishing Group
Start Page
1
End Page
14
Journal / Book Title
Scientific Reports
Volume
10
Issue
1
Copyright Statement
© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000540472300056&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
LABEL-FREE
HIGH-THROUGHPUT
ABSOLUTE QUANTIFICATION
SEPARATION
TECHNOLOGIES
FLUORESCENCE
ENCAPSULATION
CAPTURE
DEVICE
BLOOD
Publication Status
Published
Article Number
ARTN 8736
Date Publish Online
2020-05-26
