A single-cell translocation and secretion assay (TransSeA)

Wei Cai, Yu Jui Chiu, Valya Ramakrishnan, Yihuan Tsai, Clark Chen, Yu Hwa Lo

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Understanding biological heterogeneity at the single cell level is required for advancing insights into the complexity of human physiology and diseases. While advances in technological and analytical methods have afforded unprecedented glimpses of this heterogeneity, the information captured to date largely represents one-time "snap" shots of single cell physiology. To address the limits of existing methods and to accelerate discoveries from single cell studies, we developed a single-cell translocation and secretion assay (TransSeA) that supports time lapse analysis, enables molecular cargo analysis of secretions such as extracellular vesicles (EVs) from single cells, allows massively parallel single cell transfer according to user-defined cell selection criteria, and supports tracking of phenotypes between parental and progeny cells derived from single cells. To demonstrate the unique capabilities and efficiencies of the assay, we present unprecedented single cell studies related to cell secretions, EV cargos and cell intrinsic properties. Although used as examples to demonstrate the feasibility and versatility of the technology, the studies already provided insights into key unanswered questions such as the microRNAs carried by EVs, the relationships between EV secretion rates and gene expressions, and the spontaneous, trans-generational phenotypic changes in EV secretion between parental and progeny cells.

Original languageEnglish (US)
Pages (from-to)3154-3162
Number of pages9
JournalLab on a chip
Volume18
Issue number20
DOIs
StatePublished - Oct 21 2018

Bibliographical note

Funding Information:
This work was performed in part at the San Diego Nanotechnology Infrastructure (SDNI) of UCSD, a member of the National Nanotechnology Coordinated Infrastructure, which is supported by the National Science Foundation (Grant ECCS-1542148). The research reported in this publication was partially supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) of the National Institutes of Health under award number 1R43EB021129-01. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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