Stochastic Particle Barcoding for Single-Cell Tracking and Multiparametric Analysis

• Main Authors: Castellarnau, Marc (Contributor), Su, Hao-wei (Contributor), Tokatlian, Talar (Contributor), Voldman, Joel (Contributor), Szeto, Gregory (Author), Love, John C (Author), Irvine, Darrell J (Author)
• Other Authors: Massachusetts Institute of Technology. Department of Biological Engineering (Contributor), Massachusetts Institute of Technology. Department of Chemical Engineering (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Ragon Institute of MGH, MIT and Harvard (Contributor), Koch Institute for Integrative Cancer Research at MIT (Contributor), Szeto, Gregory Lee (Contributor), Love, J. Christopher (Contributor), Irvine, Darrell J. (Contributor)
• Format: Article
• Language: English
• Published: Wiley Blackwell, 2015-10-23T17:49:49Z.
• Subjects: Article
• Online Access: Get fulltext

 This study presents stochastic particle barcoding (SPB), a method for tracking cell identity across bioanalytical platforms. In this approach, single cells or small collections of cells are co-encapsulated within an enzymatically-degradable hydrogel block along with a random collection of fluorescent beads, whose number, color, and position encode the identity of the cell, enabling samples to be transferred in bulk between single-cell assay platforms without losing the identity of individual cells. The application of SPB is demonstrated for transferring cells from a subnanoliter protein secretion/phenotyping array platform into a microtiter plate, with re-identification accuracies in the plate assay of 96±2%. Encapsulated cells are recovered by digesting the hydrogel, allowing subsequent genotyping and phenotyping of cell lysates. Finally, a model scaling is developed to illustrate how different parameters affect the accuracy of SPB and to motivate scaling of the method to thousands of unique blocks.