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Time-resolved assessment of single-cell protein secretion by sequencing

ABSTRACT: Secreted proteins play critical roles in cellular communication. Methods enabling concurrent measurement of cellular protein secretion, phenotypes and transcriptomes are still unavailable. Here, we describe Time-Resolved Assessment of Protein Secretion from single cells by sequencing (TRAPS-seq). Released proteins are trapped onto cell surface and probed by oligonucleotide-barcoded antibodies before simultaneously sequenced with transcriptomes in single cells. TRAPS-seq unravels the phenotypic and transcriptional determinants of the secretion of pleiotropic Th1 cytokines (IFN-γ, IL-2 and TNF-α) in activated T cells. We further demonstrate the use of TRAPS-seq to track dynamic secretion of multiple cytokines over time, uncovering unique molecular signatures that govern the preservation or transition of single-cell cytokine secretions. Our results revealed that early central memory T cells with CD45RA expression (TCMRA) are important in both the production and maintenance of polyfunctional cytokines. TRAPS-seq presents a unique tool for seamless integration of secretomics measurement with multi-omics profiling in single cells.

ORGANISM(S): Homo sapiens

PROVIDER: GSE200690 | GEO | 2023/01/11

REPOSITORIES: GEO

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Project description:Single-cell whole-transcriptome analysis is a powerful tool for quantifying gene expression heterogeneity in populations of cells. Many techniques have, thus, been recently developed to perform transcriptome sequencing (RNA-Seq) on individual cells. To probe subtle biological variation between samples with limiting amounts of RNA, more precise and sensitive methods are still required. We adapted a previously developed strategy for single-cell RNA-Seq that has shown promise for superior sensitivity and implemented the chemistry in a microfluidic platform for single-cell whole transcriptome analysis. In this approach, single cells are captured and lysed in a microfluidic device, where mRNAs with poly(A) tails are reverse-transcribed into cDNA. Double-stranded cDNA is then collected and sequenced using a next-generation sequencing platform. We prepared 94 libraries consisting of single mouse embryonic cells and technical replicates of extracted RNA and thoroughly characterized the performance of this technology. Microfluidic implementation increased mRNA detection sensitivity as well as improved measurement precision compared with tube-based protocols. With 0.2M reads per cell, we were able to reconstruct a majority of the bulk transcriptome with 10 single cells. We also quantified variation between and within different types of mouse embryonic cells and found that enhanced measurement precision, detection sensitivity, and experimental throughput aided the distinction between biological variability and technical noise. With this work, we validated the advantages of an early approach to single-cell RNA-Seq and showed that the benefits of combining microfluidic technology with high-throughput sequencing will be valuable for large-scale efforts in single-cell transcriptome analysis. We investigated gene expression in mouse embryonic cells using microfluidic-facilitated RNA-Seq to analyze 56 single mouse ES cell (mESC) transcriptomes and 6 single mouse embryonic fibroblast (MEF) transcriptomes. To quantitatively evaluate the sensitivity and precision of our technique, we also sequenced 23 libraries from extracted mESC RNA, representing three sets of technical replicates with varying starting amounts of material.

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Time-resolved assessment of single-cell protein secretion by sequencing

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