Droplet-based microfluidics has shown potential in high throughput single cell assays by encapsulating individual cells in water-in-oil emulsions. Ordering cells in a micro-channel is necessary to encapsulate individual cells into droplets further enhancing the assay efficiency. This is typically limited due to the difficulty of preparing high-density cell solutions and maintaining them without cell aggregation in long channels (>5 cm). In this study, we developed a short pinched flow channel (5 mm) to separate cell aggregates and to form a uniform cell distribution in a droplet-generating platform that encapsulated single cells with >55% encapsulation efficiency beating Poisson encapsulation statistics. Using this platform and commercially available Sox substrates (8-hydroxy-5-(N,N-dimethylsulfonamido)-2-methylquinoline), we have demonstrated a high throughput dynamic single cell signaling assay to measure the activity of receptor tyrosine kinases (RTKs) in lung cancer cells triggered by cell surface ligand binding. The phosphorylation of the substrates resulted in fluorescent emission, showing a sigmoidal increase over a 12 h period. The result exhibited a heterogeneous signaling rate in individual cells and showed various levels of drug resistance when treated with the tyrosine kinase inhibitor, gefitinib.
Quantifying cell-to-cell variability in drug response dynamics is important when evaluating therapeutic efficacy. For example, optimizing latency reversing agents (LRAs) for use in a clinical “activate-and-kill” strategy to purge the latent HIV reservoir in patients requires minimizing heterogeneous viral activation dynamics. To evaluate how heterogeneity in latent HIV activation varies across a range of LRAs, we tracked drug-induced response dynamics in single cells via live-cell imaging using a latent HIV–GFP reporter virus in a clonal Jurkat T cell line. To enable these studies in suspension cells, we designed a simple method to capture an array of single Jurkat T cells using a passive-flow microfluidic device. Our device, which does not require external pumps or tubing, can trap hundreds of cells within minutes with a high retention rate over 12 hours of imaging. Using this device, we quantified heterogeneity in viral activation stimulated by transcription factor (TF) activators and histone deacetylase (HDAC) inhibitors. Generally, TF activators resulted in both faster onset of viral activation and faster rates of production, while HDAC inhibitors resulted in more uniform onset times, but more heterogeneous rates of production. Finally, we demonstrated that while onset time of viral gene expression and rate of viral production together predict total HIV activation, rate and onset time were not correlated within the same individual cell, suggesting that these features are regulated independently. Overall, our results reveal drug-specific patterns of noisy HIV activation dynamics not previously identified in static single-cell assays, which may require consideration for the most effective activate-and-kill regime.
Development is a complex process that requires the precise modulation of regulatory gene networks controlled through dynamic changes in the epigenome. Single-cell -omic technologies provide an avenue for understanding the mechanisms of these processes by capturing the progression of epigenetic cell states during the course of cellular differentiation using in vitro or in vivo models 1 . However, current single-cell epigenomic methods are limited in the information garnered per individual cell, which in turn limits their ability to measure chromatin dynamics and state shifts. Single-cell combinatorial indexing (sci-) has been applied as a strategy for identifying single-cell -omic originating libraries and removes the necessity of single-cell, single-compartment chemistry 2 . Here, we report an improved sci-assay for transposase accessible chromatin by sequencing (ATAC-seq), which utilizes the small molecule inhibitor Pitstop 2™ (scip-ATAC-seq) 3 . We demonstrate that these improvements, which theoretically could be applied to any in situ transposition method for single-cell library preparation, significantly increase the ability of transposase to enter the nucleus and generate highly complex singlecell libraries, without altering biological signal. We applied sci-ATAC-seq and scip-ATAC-seq to characterize the chromatin dynamics of developing forebrain-like organoids, an in vitro model of human corticogenesis 4 . Using these data, we characterized novel putative regulatory elements, compared the epigenome of the organoid model to human cortex data, generated a high-resolution pseudotemporal map of chromatin accessibility through differentiation, and measured epigenomic changes coinciding with a neurogenic fate decision point. Finally, we combined transcription factor motif accessibility with gene activity (GA) scores to directly observe the dynamics of complex regulatory programs that regulate neurogenesis through developmental pseudotime. Overall, scip-ATAC-seq increases information content per cell and bolsters the potential for future single-cell studies into complex developmental processes. F.J.S. and R.R. are employees of Illumina Inc. Data and software availabilityA wrapper for the entire analysis (scitools) as well as custom scripts used will be made available on github.com/adeylab/organoid. All sequence read data for CIRM lines will be made available on dbGAP, with processed data available on GEO. Extended Data Fig 1. | Fluorescent microscopy analysis of transposome complex. a, Representative fluorescent images of DAPI stained fixed nuclei with Cy3 complexed transposomes without Pitstop 2 treatment. Scale bar is 10 μm. b, Representative fluorescent images of DAPI stained fixed nuclei with Cy3 complexed transposomes and treated with 70 μM Pitstop 2. Scale bar is 10 μm. c, 3D reconstruction of DAPI and ATAC-see signal showing blend projection function of Imaris Software. Nuclear blebbing as well as bursting of a 150 μM Pitstop 2 treated nuclei and diffusion of DAPI+ DNA into the environment is visualized in ...
The transcription factor nuclear factor (NF)-kB promotes inflammatory and stress-responsive gene transcription across a range of cell types in response to the cytokine tumor necrosis factor (TNF). Although NF-kB signaling exhibits significant variability across single cells, some target genes supporting high levels of TNF-inducible transcription exhibit fold-change detection of NF-kB, which may buffer against stochastic variation in signaling molecules. It is unknown whether fold-change detection is maintained at NF-kB target genes with low levels of TNF-inducible transcription, for which stochastic promoter events may be more pronounced. Here, we used a microfluidic cell-trapping device to measure how TNF-induced activation of NF-kB controls transcription in single Jurkat T cells at the promoters of integrated HIV and the endogenous cytokine gene IL6, which produce only a few transcripts per cell. We tracked TNF-stimulated NF-kB RelA nuclear translocation by live-cell imaging and then quantified transcript number by RNA FISH in the same cell. We found that TNF-induced transcript abundance at 2 h for low-and high-abundance target genes correlates with similar strength with the fold change in nuclear NF-kB. A computational model of TNF-NF-kB signaling, which implements fold-change detection from competition for binding to kB motifs, could reproduce fold-change detection across the experimentally measured range of transcript outputs. However, multiple model parameters affecting transcription had to be simultaneously varied across promoters to maintain fold-change detection while also matching other trends in the single-cell data for low-abundance transcripts. Our results suggest that cells use multiple biological mechanisms to tune transcriptional output while maintaining robustness of NF-kB fold-change detection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.