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Updated: Jan 26, 2026

In Vitro Synthesis of Modified mRNA for Induction of Protein Expression in Human Cells
Published on: November 13, 2014
Single-cell correlations of mRNA and protein content in a human monocytic cell line after LPS stimulation
Daniel M Kalb1, Samantha H Adikari2, Elizabeth Hong-Geller2
1Center for Integrated Nanotechnologies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
Abstract:
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.
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