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. 2017 Apr 12;7(1):838.
doi: 10.1038/s41598-017-00828-y.

Global analysis of glycoproteins identifies markers of endotoxin tolerant monocytes and GPR84 as a modulator of TNFα expression

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Global analysis of glycoproteins identifies markers of endotoxin tolerant monocytes and GPR84 as a modulator of TNFα expression

Mario M Müller et al. Sci Rep. .

Abstract

Exposure of human monocytes to lipopolysaccharide (LPS) induces a temporary insensitivity to subsequent LPS challenges, a cellular state called endotoxin tolerance. In this study, we investigated the LPS-induced global glycoprotein expression changes of tolerant human monocytes and THP-1 cells to identify markers and glycoprotein targets capable to modulate the immunosuppressive state. Using hydrazide chemistry and LC-MS/MS analysis, we analyzed glycoprotein expression changes during a 48 h LPS time course. The cellular snapshots at different time points identified 1491 glycoproteins expressed by monocytes and THP-1 cells. Label-free quantitative analysis revealed transient or long-lasting LPS-induced expression changes of secreted or membrane-anchored glycoproteins derived from intracellular membrane coated organelles or from the plasma membrane. Monocytes and THP-1 cells demonstrated marked differences in glycoproteins differentially expressed in the tolerant state. Among the shared differentially expressed glycoproteins G protein-coupled receptor 84 (GPR84) was identified as being capable of modulating pro-inflammatory TNFα mRNA expression in the tolerant cell state when activated with its ligand Decanoic acid.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
TNFα mRNA expression in naïve and LPS-reprogrammed monocytes indicates tolerance. Monocytes (A) and THP-1 cells (B) were pretreated for 24 or 48 h with fresh medium or 50 ng/ml LPS in fresh medium, washed, and either left untreated or re-challenged with 50 ng/ml LPS for 2 h. RNA was isolated, reversed transcribed, and analyzed by RT-qPCR. Shown are fold changes of TNFα mRNA production normalized to the house-keeping gene PPIB and compared to unstimulated control samples (mean of three independent experiments (THP-1) or three independent donors (monocytes) ± SE). ***p ≤ 0.001, *p ≤ 0.05.
Figure 2
Figure 2
Glycoprotein identification in CD14+ monocytes and THP-1 cells by LC-MS/MS. (A,B) Gene ontology-based cellular component analysis of all glycoproteins identified in CD14+ monocytes (A, unique glycoproteins + soluble isoforms) and THP-1 cells (B, unique glycoproteins). Numbers of glycoproteins in manually selected cellular components are given. (C,D) Distribution of glycoproteins identified in CD14+ monocytes (C) and THP-1 cells (D) with predicted transmembrane helices identified in the two data sets. Upper part: glycoproteins with ≥1 or 0 predicted transmembrane helices, lower part: distribution of glycoproteins according to the number of predicted transmembrane domains. (E) Overlap between the 1491 annotated unique glycoproteins identified in THP-1 cells (1189) and CD14+ monocytes (1109).
Figure 3
Figure 3
LPS regulated glycoproteins in CD14+ monocytes and THP-1 cells. (A,B) Volcano plot (A) and heat map (B) of differentially expressed glycoproteins in CD14+ monocytes. (C,D) Volcano plot (C) and heat map (D) of differentially expressed glycoproteins in THP-1 cells. (A,C) Volcano plots show the t-test p-value plotted against the glycoprotein expression fold change of all identified glycoproteins in CD14+ monocytes and THP-1 cells at 24 h (left) and 48 h (right) of LPS treatment. Data points in lower center area of the plots (grey) display unchanged or glycoproteins with no significant fold change, whereas data points in the upper left and upper right quadrants indicate glycoproteins (red) with significant negative (left) and positive (right) changes in protein abundances, respectively. For illustration gene names are given. (B,D) Black boxes in heat maps indicate no fold change at the given time point. Green, yellow, red indicate upregulation and blue indicates down regulation according to the legend. For illustration gene names are given. (E,F) Numbers of significantly changed glycoproteins after LPS treatment in selected cellular components at different time points in CD14+ monocytes (E) and THP-1 cells (F); 4 h = light grey bars, 24 h = dark grey bars, and 48 h = black bars.
Figure 4
Figure 4
Comparison of differently expressed glycoproteins identified in CD14+ monocytes and THP-1 cells. (A + B) Venn diagrams showing the overlap between differently expressed glycoproteins identified in monocytes and THP-1 cell at 24 h (A) and 48 h (B) of LPS stimulation.
Figure 5
Figure 5
Verification of proteomic results by flow cytometry and qPCR. Cell surface expression of ICAM1/CD54 and SIGLEC1/CD169 on CD14+ monocytes (A) and THP-1 cells (B). (A) Monocytes were either left untreated or stimulated for 24 h or 48 h with 50 ng/ml LPS. White graphs: isotype controls, in light grey: expression at the indicated time point of unstimulated controls, in dark grey: expression at the indicated time points after LPS treatment. The data shown are representative of two different donors independently analyzed. Depicted are the intensity levels of the indicated proteins expressed on the CD14+ cell population (B) THP-1 cells were either left untreated or stimulated with 50 ng/ml LPS for 4 h, 24 h, and 48 h. White graphs: expression in unstimulated controls at t = (0), in light grey expression at the indicated time point of unstimulated controls, in dark grey: expression at the indicated time points after LPS treatment. The data shown are representative of three independent experiments. (C,D) Gene expression changes of selected glycoproteins induced by LPS treatment revealed by qPCR. (C) Monocyte mRNA expression changes of GPR84, MMP9, LAMP3, DPEP2, and ITGB8 at different time points after LPS treatment of naïve (pre: no), or 24 h LPS pre-stimulated (pre: LPS) monocytes re-stimulated with LPS for the indicated time points. (D) THP-1 mRNA expression changes of GPR84, MMP9, IL4i1, EBI3, and STEAP4 at different time points after LPS treatment of naïve (pre: no), or 24 h LPS pre-stimulated (pre: LPS) THP-1 cells re-stimulated with LPS for the indicated time points. (C + D) Plotted are fold changes normalized to the house-keeping gene PPIB (monocytes) or HPRT (THP-1) and compared to naïve unstimulated control cells at t = (0). Samples (mean of three independent experiments (THP-1 cells) or three independent donors (monocytes) ± SE) *p < 0.05, **p < 0.01, ***p < 0.001.
Figure 6
Figure 6
TNF-alpha mRNA production in the LPS pre-stimulated tolerant state is modulated by Capric acid treatment. (A,B) Monocytes (A) and THP-1 cells (B) were pretreated for 24 h with fresh medium or 50 ng/ml LPS in fresh medium. Two hours after the initial stimulation Capric acid (500 µM) was added to some samples (CA). After 24 h cells were re-stimulated with 50 ng/ml LPS for 2 h or left untreated. RNA was isolated, reversed transcribed, and analyzed by RT-qPCR with primers specific for PPIB and TNFα. Shown are the fold changes of TNFα mRNA normalized to the house-keeping gene PPIB (monocytes) or HPRT (THP-1 cells) and compared to unstimulated control samples (mean of three independent experiments (THP-1 cells) or 5 different donors (monocytes) ± SE). *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001.

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References

    1. Dube DH, Bertozzi CR. Glycans in cancer and inflammation–potential for therapeutics and diagnostics. Nature reviews. Drug discovery. 2005;4:477–488. doi: 10.1038/nrd1751. - DOI - PubMed
    1. Hopkins AL, Groom CR. The druggable genome. Nature reviews. Drug discovery. 2002;1:727–730. doi: 10.1038/nrd892. - DOI - PubMed
    1. Josic D, Clifton JG. Mammalian plasma membrane proteomics. Proteomics. 2007;7:3010–3029. doi: 10.1002/pmic.200700139. - DOI - PubMed
    1. Macher BA, Yen TY. Proteins at membrane surfaces-a review of approaches. Molecular bioSystems. 2007;3:705–713. doi: 10.1039/b708581h. - DOI - PubMed
    1. Cao L, Clifton JG, Reutter W, Josic D. Mass spectrometry-based analysis of rat liver and hepatocellular carcinoma Morris hepatoma 7777 plasma membrane proteome. Analytical chemistry. 2013;85:8112–8120. doi: 10.1021/ac400774g. - DOI - PMC - PubMed

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