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Issue 21, 2020
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μCB-seq: microfluidic cell barcoding and sequencing for high-resolution imaging and sequencing of single cells

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Abstract

Single-cell RNA sequencing (scRNA-seq) enables the investigation of complex biological processes in multicellular organisms with high resolution. However, many phenotypic features that are critical to understanding the functional role of cells in a heterogeneous tissue or organ are not directly encoded in the genome and therefore cannot be profiled with scRNA-seq. Quantitative optical microscopy has long been a powerful approach for characterizing diverse cellular phenotypes including cell morphology, protein localization, and chemical composition. Combining scRNA-seq with optical imaging has the potential to provide comprehensive single-cell analysis, allowing for functional integration of gene expression profiling and cell-state characterization. However, it is difficult to track single cells through both measurements; therefore, coupling current scRNA-seq protocols with optical measurements remains a challenge. Here, we report microfluidic cell barcoding and sequencing (μCB-seq), a microfluidic platform that combines high-resolution imaging and sequencing of single cells. μCB-seq is enabled by a novel fabrication method that preloads primers with known barcode sequences inside addressable reaction chambers of a microfluidic device. In addition to enabling multi-modal single-cell analysis, μCB-seq improves gene detection sensitivity, providing a scalable and accurate method for information-rich characterization of single cells.

Graphical abstract: μCB-seq: microfluidic cell barcoding and sequencing for high-resolution imaging and sequencing of single cells

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Supplementary files

Article information


Submitted
18 Feb 2020
Accepted
23 Aug 2020
First published
15 Sep 2020

This article is Open Access

Lab Chip, 2020,20, 3899-3913
Article type
Paper

μCB-seq: microfluidic cell barcoding and sequencing for high-resolution imaging and sequencing of single cells

T. N. Chen, A. Gupta, M. D. Zalavadia and A. Streets, Lab Chip, 2020, 20, 3899
DOI: 10.1039/D0LC00169D

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