Single-cell analysis and sorting using droplet-based microfluidics

We present a droplet-based microfluidics protocol for high-throughput analysis and sorting of single cells. Compartmentalization of single cells in droplets enables the analysis of proteins released from or secreted by cells, thereby overcoming one of the major limitations of traditional flow cytometry and fluorescence-activated cell sorting. As an example of this approach, we detail a binding assay for detecting antibodies secreted from single mouse hybridoma cells. Secreted antibodies are detected after only 15 min by co-compartmentalizing single mouse hybridoma cells, a fluorescent probe and single beads coated with anti-mouse IgG antibodies in 50-pl droplets. The beads capture the secreted antibodies and, when the captured antibodies bind to the probe, the fluorescence becomes localized on the beads, generating a clearly distinguishable fluorescence signal that enables droplet sorting at ∼ 200 Hz as well as cell enrichment. The microfluidic system described is easily adapted for screening other intracellular, cell-surface or secreted proteins and for quantifying catalytic or regulatory activities. In order to screen ∼ 1 million cells, the microfluidic operations require 2–6 h; the entire process, including preparation of microfluidic devices and mammalian cells, requires 5–7 d.

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Acknowledgements

We are grateful to R. Sperling for the kind gift of surfactant and D. Aubrecht for his help in developing droplet detection and sorting methods. This work was supported by the National Science Foundation (NSF) (DMR-1006546), the National Institutes of Health (NIH) (P01GM096971 and 5R01EB014703-02), the Harvard Materials Science Research and Engineering Center (DMR-0820484) and the Lithuanian Research Council (MIP-048/2012). W.L.U. acknowledges support from a Canadian National Sciences and Engineering Research Council (NSERC) Postgraduate Scholarship (PGS D). J.A.H. and J.G. were supported by NIH SBIR grant no. 1R43AI082861-01. This work was performed in part at the Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Infrastructure Network (NNIN), which is supported by the NSF under award no. ECS-0335765. CNS is part of Harvard University.

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Authors and Affiliations

  1. School of Engineering and Applied Sciences (SEAS), Harvard University, Cambridge, Massachusetts, USA Linas Mazutis, W Lloyd Ung, David A Weitz & John A Heyman
  2. Institute of Biotechnology, Vilnius University, Vilnius, Lithuania Linas Mazutis
  3. HabSel Inc. Cambridge, Massachusetts, USA John Gilbert & John A Heyman
  4. École Supérieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI ParisTech), Centre National de la Recherche Scientifique (CNRS) UMR 7084, Paris, France., Andrew D Griffiths
  1. Linas Mazutis