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Title: Single-cell correlations of mRNA and protein content in a human monocytic cell line after LPS stimulation

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, mRNAmore » 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.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Univ. of California, Irvine, CA (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1511628
Report Number(s):
LA-UR-19-20143
Journal ID: ISSN 1932-6203
Grant/Contract Number:  
89233218CNA000001
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
PLoS ONE
Additional Journal Information:
Journal Volume: 14; Journal Issue: 4; Journal ID: ISSN 1932-6203
Publisher:
Public Library of Science
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Kalb, Daniel M., Adikari, Samantha Hiroshini, Hong-Geller, Elizabeth, Werner, James Henry, and Brody, James P. Single-cell correlations of mRNA and protein content in a human monocytic cell line after LPS stimulation. United States: N. p., 2019. Web. doi:10.1371/journal.pone.0215602.
Kalb, Daniel M., Adikari, Samantha Hiroshini, Hong-Geller, Elizabeth, Werner, James Henry, & Brody, James P. Single-cell correlations of mRNA and protein content in a human monocytic cell line after LPS stimulation. United States. doi:10.1371/journal.pone.0215602.
Kalb, Daniel M., Adikari, Samantha Hiroshini, Hong-Geller, Elizabeth, Werner, James Henry, and Brody, James P. Fri . "Single-cell correlations of mRNA and protein content in a human monocytic cell line after LPS stimulation". United States. doi:10.1371/journal.pone.0215602. https://www.osti.gov/servlets/purl/1511628.
@article{osti_1511628,
title = {Single-cell correlations of mRNA and protein content in a human monocytic cell line after LPS stimulation},
author = {Kalb, Daniel M. and Adikari, Samantha Hiroshini and Hong-Geller, Elizabeth and Werner, James Henry and Brody, James P.},
abstractNote = {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.},
doi = {10.1371/journal.pone.0215602},
journal = {PLoS ONE},
issn = {1932-6203},
number = 4,
volume = 14,
place = {United States},
year = {2019},
month = {4}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Figures / Tables:

Fig 1 Fig 1: Automated cell segmentation process. The bright-field image (A) and nucleus data from a DAPI stain (B) are utilized to segment the cells. The combination of the DAPI data, the smFISH channel, and the phase congruency filtered bright field data (C) are utilized to create a binary image (D).more » A watershed from the nucleus data and the binary image are utilized to create the final segmented image (E).« less

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