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Defining TNF-α- and LPS-induced gene signatures in monocytes to unravel the complexity of peripheral blood transcriptomes in health and disease

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Abstract

Several genome-wide transcriptome studies have shown that chronic inflammatory responses generally taking place in the inflamed tissue are also reflected at the level of peripheral blood leukocytes. Blood monocytes are highly sensitized cell type continuously activated under inflammatory conditions. For a better understanding of the transcriptional imprinting influenced by a multitude of pro- and anti-inflammatory mediators, we established a whole blood in vitro system to explore cell- and stimulus-specific gene expression signatures in peripheral monocytes. In an explorative study, whole blood from healthy donors was stimulated with tumour necrosis factor-alpha (TNF-α) or lipopolysaccharide (LPS) for 1.5 h. Subsequently, monocytes were isolated with a purity of >99% by high-speed fluorescence activated cell sorting. Transcriptional changes were explored by whole genome Affymetrix arrays using highly validated filtering algorithm to identify differentially expressed genes. In vitro stimulation of whole blood samples with TNF-α and LPS resulted in 4,529 and 5,036 differentially expressed genes, respectively. Although both stimuli induced similar inflammatory profiles in monocytes, TNF-α- or LPS-specific gene signatures were characterized. Functional classification identified significant numbers of differentially expressed cytokines, cytokine receptors and apoptosis-associated genes. To our knowledge, this is the first study presenting cell- and stimulus-specific gene expression signatures that can be used to decipher complex disease specific profiles of acute and chronic inflammation. Once a library of signatures from the most important inflammatory mediators is defined, it can be helpful to identify those signatures, which are predominantly driving the disease pathogenesis and which are of potential interest for a therapeutical intervention.

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Acknowledgments

We are grateful to Heidi Schliemann responsible for generating gene expression data. The work was supported by the German Ministry of Education and Research (BMBF) within the National Genome Research Network NGFN (01GS0413) and by the European Union’s Sixth Framework Programme (project AutoCure; LSHB-CT-2006-018861).

Disclosure of potential conflict of interests

The authors declare no conflict of interests related to this study.

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Authors and Affiliations

  1. Deutsches Rheuma-Forschungszentrum Berlin (DRFZ),a Leibniz Institute, Charitéplatz 1, 10117, Berlin, Germany

    Biljana Smiljanovic, Joachim R. Grün, Andreas Radbruch, Andreas Grützkau & Ria Baumgrass

  2. Rheumatology, Charité, Humboldt-University Berlin, Berlin, Germany

    Marta Steinbrich-Zöllner, Bruno Stuhlmüller, Thomas Häupl & Gerd R. Burmester

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  1. Biljana Smiljanovic
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Corresponding author

Correspondence to Andreas Grützkau.

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Author Contributions

Conceived and designed the experiments: AG, GRB, RB, AR. Performed the experiments: BSm, AG. Analyzed the data: BSm, AG, JG, TH, BSt, MSZ. Wrote the paper: BSm, AG, RB, JG.

Andreas Grützkau and Ria Baumgrass contributed equally to this work

Supported by the German Federal Ministry of Education and Research (BMBF) through the National Genome Research Network (Infection and Inflammation Network SIPAGE, grant 01GS0413) and by the European Union's Sixth Framework Programme (project AutoCure; LSHB-CT-2006-018861)

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary File 1

This file includes a description how to get access to the publically available array data using BioRetis database. Furthermore, filtering criteria are described for the selection of differentially expressed genes. (PDF 15 kb)

Supplementary Table 1

with sheet 1-9. These tables include Signal values, p values, Signal Log Ratio (SLR), Fold Change (FC) of differentially expressed probe sets that distinguish unstimulated monocytes but incubated, TNF-α- and LPS-stimulated monocytes from Unstimulated and immediately processed monocytes. (XLS 8343 kb)

Supplementary Table 2

with sheet 1-3. These tables include the probe sets that discriminate TNF-α- from LPS-stimulated monocytes. Beside 1,824 probe sets that are TNF-α specific and 3,214 probe sets specific for LPS, there are 94 probe sets that are common for TNF and LPS stimulation but they are regulated in opposite direction by these two stimuli. (XLS 789 kb)

Supplementary Table 3

with sheet 1-2. These tables include the probe sets that describe the cytokine–cytokine receptor profile in monocytes. Altogether 182 probe sets are differentially expressed in monocytes stimulated with TNF-α or LPS for 1.5 h compared with unstimulated cells. 120 genes out of 182 probe sets that are differentially expressed are presented with average signals and average fold changes. (XLS 80 kb)

Supplementary Table 4

with sheet 1-2. These tables include the probe sets of the genes that describe the apoptosis-survival profile in monocytes. Altogether 419 probe sets are differentially expressed and involved in apoptosis and survival in monocytes after 1.5 h of incubation in the presence of TNF-α or LPS compared with unstimulated cells. 240 genes out of 419 differentially expressed probe sets were presented with average signals and average fold changes. (XLS 163 kb)

Supplementary Table 5

with sheet 1-3. These tables include Signal values, p values, Signal Log Ratio (SLR), Fold Change (FC) of 471 differentially expressed probe sets that distinguish monocytes from RA patients that responded to anti-TNF-α therapy, before and after treatment (sheet 1 and 2). These probe sets were revealed as significantly increased or decreased in 80% of pair-wise comparisons. Sheet 3 includes 179 probe sets with FC that are common for in vitro stimulated monocytes by TNF-α and monocytes from RA patients treated with anti-TNF-α, and which showed opposite direction of changes. Affymetrix arrays used for analysis of in vitro stimulated monocytes belong to HG-U133 Plus 2.0 platform and for analysis of anti-TNF treated RA patients to HG-U133A 2.0. (XLS 287 kb)

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Smiljanovic, B., Grün, J.R., Steinbrich-Zöllner, M. et al. Defining TNF-α- and LPS-induced gene signatures in monocytes to unravel the complexity of peripheral blood transcriptomes in health and disease. J Mol Med 88, 1065–1079 (2010). https://doi.org/10.1007/s00109-010-0648-8

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