RNA-Seq Reveals Activation of Both Common and Cytokine-Specific Pathways following Neutrophil Priming

<div><p>Neutrophils are central to the pathology of inflammatory diseases, where they can damage host tissue through release of reactive oxygen metabolites and proteases, and drive inflammation via secretion of cytokines and chemokines. Many cytokines, such as those generated during inflammation, can induce a similar “primed” phenotype in neutrophils, but it is unknown if different cytokines utilise common or cytokine-specific pathways to induce these functional changes. Here, we describe the transcriptomic changes induced in control human neutrophils during priming <i>in vitro</i> with pro-inflammatory cytokines (TNF-α and GM-CSF) using RNA-seq. Priming led to the rapid expression of a common set of transcripts for cytokines, chemokines and cell surface receptors (CXCL1, CXCL2, IL1A, IL1B, IL1RA, ICAM1). However, 580 genes were differentially regulated by TNF-α and GM-CSF treatment, and of these 58 were directly implicated in the control of apoptosis. While these two cytokines both delayed apoptosis, they induced changes in expression of different pro- and anti-apoptotic genes. Bioinformatics analysis predicted that these genes were regulated via differential activation of transcription factors by TNF-α and GM-CSF and these predictions were confirmed using functional assays: inhibition of NF-κB signalling abrogated the protective effect of TNF-α (but not that of GM-CSF) on neutrophil apoptosis, whereas inhibition of JAK/STAT signalling abrogated the anti-apoptotic effect of GM-CSF, but not that of TNF-α (p<0.05). These data provide the first characterisation of the human neutrophil transcriptome following GM-CSF and TNF-α priming, and demonstrate the utility of this approach to define functional changes in neutrophils following cytokine exposure. This may provide an important, new approach to define the molecular properties of neutrophils after <i>in vivo</i> activation during inflammation.</p> </div

The 58 apoptosis-related genes which had significantly different expression levels in TNF-α and GM-CSF treated neutrophils (FDR adjusted q-value ≤0.05).

<p>Table shows the gene expression (RPKM) value of each gene following priming for 1 h with TNF-α or GM-CSF.</p

Neutrophil yield using density gradient isolation or negative selection.

<p>(A) Neutrophil yield (10⁶/mL) from whole blood isolated by Polymorphprep and negative selection (Beads). Data represents n = 5 paired neutrophil isolations (**p<0.01). (B) Neutrophil yield (10⁶/mL) from whole blood isolated by Ficoll-Paque (Ficoll) and negative selection (Beads). Data represent n = 5 experiments in which neutrophil enrichment from the Ficoll-Paque granulocyte pellet was carried out using negative selection (**p<0.01).</p

Validation of expression values of a selection of genes measured by RNA-seq and real-time PCR.

<p>(A–C) Expression levels of a selection of genes with a range of RPKM values across the two NGS platforms (⋄ SOLiD, n = 1, •▴ Illumina, n = 2) in (A) untreated, (B) TNF-α-treated and (C) GM-CSF-treated neutrophils. Symbols overlap at some datapoints due to highly similar RPKM values. (D,E) Fold change in expression of genes in (D) TNF-α and (E) GM-CSF-treated neutrophils compared to unstimulated, measured by real-time PCR (grey bar, n = 3) and RNA-seq (open bar, n = 3).</p

Genes up-regulated at least 10-fold in TNF-α and/or GM-CSF treated neutrophils compared to untreated neutrophils.

<p>Table shows fold change in gene expression (RPKM) compared to level expressed in untreated neutrophils. Change in gene expression is significant with a 5% FDR (NS = not significant).</p

Neutrophil purity after isolation using Polymorphprep or negative-selection (magnetic beads).

<p>(A) Percentage of leukocytes in each preparation from each donor. Cells quantified by cell morphology and staining properties using cytospins (calculated from 4 separate fields of view, counting > 100 cells per field per donor). (B) Representative cytospins of neutrophil preparations following Polymorphprep (Poly) or negative selection (Beads) isolation protocols from Donor 1 (top) and Donor 2 (bottom). White arrows highlight non-neutrophil cells. (C) Flow cytometry scatterplots of neutrophil preparations by Polymorphprep (Poly) or negative selection (Beads) isolation protocols. Plotted by green fluorescence (CD16 positive, X-axis) and forward-scatter (Y-axis). Donor 1 (left panels) and Donor 2 (right panels). Numbers shown are percentage of cells in each of the two quadrants shown. (D) Levels of expression of cell surface markers in neutrophils isolated by Polymorphprep (Poly) or by negative selection (Beads). Geometric mean fluorescence (GMF) of CD16 (N = 5), CD15 (N = 3), CD11b (N = 3) and CD64 (N = 4) was measured by flow cytometry and normalised to an appropriate isotype control. Error bars represent SEM.</p

Expression levels of non-neutrophil genes in neutrophil preparations.

<p>RPKM values for non-neutrophil genes of the antigen targets in the StemCell magnetic bead negative selection isolation kit (A) and (B) non-neutrophil specific genes associated with T and B cells, monocytes, and eosinophils. Neutrophils were either isolated by negative selection (Bead, circle) or by Polymorphprep (Poly, square) from Donor 1 (1) and Donor 2 (2). Neutrophils were treated with 5 ng/mL GM-CSF (shaded grey), 10ng/mL TNFα (shaded white) or untreated (shaded black) for 1h. Horizontal dotted lines represent RPKM expression threshold of 0.3. Horizontal bars represent mean value. (C) The number of read fragments mapping to non-neutrophil genes and (D) neutrophil-specific genes in each library. Data is shown as the average (±SEM) across three treatment conditions (UT, TNFα, GM-CSF) for each Donor and each isolation protocol. (E) The number of mapped reads in each dataset.</p

Hierarchical cluster analysis of genes expressed (RPKM ≥10) in untreated and cytokine treated neutrophils.

<p>RPKM values are represented on a log₁₀ scale, where green is low expression and red is high expression. An expanded heat map of highly expressed genes (red bar) is also shown. These highly-expressed transcripts include genes that can be categorised as cytokines/chemokines, cell-surface receptors, interferon-induced genes, Major Histocompatibility Complex (MHC) proteins, calcium binding proteins, apoptosis regulators and adhesion molecules.</p

Effect of GM-CSF and TNF-α on neutrophil priming.

<p>(A,B) Neutrophils were primed with (A) GM-CSF (5 ng/mL) or (B) TNF-α (10 ng/mL), and the respiratory burst was stimulated by fMLP (10 µM). A rapid respiratory burst was observed in primed cells (♦) but not in unprimed cells (Δ). (C–G) Flow cytometry analysis of adhesion molecule expression following priming with GM-CSF (black line) or TNF-α (dashed line) compared to unprimed neutrophils (grey line). (C) CD11b and (E) CD18 expression was up-regulated following priming with both GM-CSF and TNF-α but showed a greater level of up-regulation after GM-CSF priming. (D) L-selectin showed significant shedding following priming with GM-CSF, but only moderate shedding after TNF-α priming. (F) FcγRIIA (CD32) expression did not change following priming with either cytokine, and (G) FcγRIIIB expression was maintained by priming with either cytokine compared to the level of expression in untreated neutrophils from which the receptor was shed during 1 h incubation.</p

Comparison of sequencing platform variation and biological variation.

<p>(A) RPKM values (≥0.3) for untreated neutrophils from the same donor sequenced on the SOLiD v4.0 and Illumina HiSeq 2000 platforms (Rs = 0.784, Pearson Correlation). (B) RPKM values (≥0.3) for untreated neutrophils from two different biological donors sequenced on the Illumina HiSeq 2000 platform (Rs = 0.947, Pearson Correlation). (C,D) Correlation between the fold change in RPKM value for genes up-regulated by (C) TNF-α (Rs = 0.885) and (D) GM-CSF (Rs = 0.831) measured in neutrophils from the same donor on the SOLiD v4.0 and Illumina HiSeq 2000 platforms.</p