Issue 21, 2020

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

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

Supplementary files

Article information

Article type
Paper
Submitted
18 Feb 2020
Accepted
23 Aug 2020
First published
15 Sep 2020
This article is Open Access
Creative Commons BY-NC license

Lab Chip, 2020,20, 3899-3913

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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