Date Published: April 19, 2019
Publisher: Public Library of Science
Author(s): Daniel M. Kalb, Samantha H. Adikari, Elizabeth Hong-Geller, James H. Werner, James P. Brody.
The heterogeneity of mRNA and protein expression at the single-cell level can reveal fundamental information about cellular response to external stimuli, including the sensitivity, timing, and regulatory interactions of genes. Here we describe a fully automated system to digitally count the intron, mRNA, and protein content of up to five genes of interest simultaneously in single-cells. Full system automation of 3D microscope scans and custom image analysis routines allows hundreds of individual cells to be automatically segmented and the mRNA-protein content to be digitally counted. Single-molecule intron and mRNA content is measured by single-molecule fluorescence in-situ hybridization (smFISH), while protein content is quantified though the use of antibody probes. To mimic immune response to bacterial infection, human monocytic leukemia cells (THP-1) were stimulated with lipopolysaccharide (LPS), and the expression of two inflammatory genes, IL1β (interleukin 1β) and TNF-α (tumor necrosis factor α), were simultaneously quantified by monitoring the intron, mRNA, and protein levels over time. The simultaneous labeling of cellular content allowed for a series of correlations at the single-cell level to be explored, both in the progressive maturation of a single gene (intron-mRNA-protein) and comparative analysis between the two immune response genes. In the absence of LPS stimulation, mRNA expression of IL1β and TNF-α were uncorrelated. Following LPS stimulation, mRNA expression of the two genes became more correlated, consistent with a model in which IL1β and TNF-α upregulation occurs in parallel through independent mechanistic pathways. This smFISH methodology can be applied to different complex biological systems to provide valuable insight into highly dynamic gene mechanisms that determine cell plasticity and heterogeneity of cellular response.
Gene and protein expression in response to external stimuli have been most commonly observed at the ‘bulk’ level, resulting in average values of expression over large numbers of individual cells. While these studies can be informative, understanding the heterogeneity of gene expression at the single-cell level provides increased contextual information about the kinetics and fundamental regulatory mechanisms of these genes. Additionally, single-cell measurements are critical for applications where rare cells, or heterogeneity of gene expression within a population of cells, can lead to drastically different biological outcomes such as cellular response to cancer treatment and host immunity to pathogen infection.[2, 3]
We have developed an automated platform for the quantification of gene expression to examine the response of IL1β and TNF-α to LPS over time at the single-cell level. Our results with THP-1 immune cells demonstrate a rapid immune response to LPS stimulation and a complex relation between the genes. As expected, the first sign of gene expression for both IL1β and TNF-α is visible at the intron bursting sites located in the cell nuclei, followed by subsequent expression as mature mRNA predominantly in the cytoplasm. Additionally, the correlations of mRNA-mRNA content at the single-cell level demonstrate that IL1β and TNF-α are uncorrelated without LPS stimulation, but become more correlated as gene expression peaks (~1hr). This switch in correlation over time suggests that the external stimulus (LPS) independently activates both IL1β and TNF-α upstream, with these genes initially having little interplay between each other.
An automated platform for acquisition and quantification of gene expression at the single-cell level has been developed and demonstrated. The kinetic expression of IL1β and TNF-α content is measured with the quantification of intron bursting sites, single-molecule mRNA counting, and protein content. When exposed to LPS, we see a rapid ON time of intron bursting sites (~15 min) followed by an increase in mRNA expression (max at 1hr TNF-α, 4hr IL1β). While initially uncorrelated, the mRNA expression of IL1β and TNF-α at the single-cell level become correlated as gene expression peaks, a result that suggests that the regulation of each gene is independent of each other. This automated platform has the potential to be applied to a variety of single-cell assays where ultrasensitive and quantitative measurement of genes is critical such as cancer cell development, drug response, and persistent bacterial infection.