Neutrophil transcriptional profile changes during transit from bone marrow to sites of inflammation

Abstract

It has recently been established that neutrophils, the most abundant leukocytes, are capable of changes in gene expression during inflammatory responses. However, changes in the transcriptome as the neutrophil leaves the bone marrow have yet to be described. We hypothesized that neutrophils are transcriptionally active cells that alter their gene expression profiles as they migrate into the vasculature and then into inflamed tissues. Our goal was to provide an overview of how the neutrophil's transcriptome changes as they migrate through different compartments using microarray and bio-informatic approaches. Our study demonstrates that neutrophils are highly plastic cells where normal environmental cues result in a site-specific neutrophil transcriptome. We demonstrate that neutrophil genes undergo one of four distinct expression change patterns as they move from bone marrow through the circulation to sites of inflammation: (i) continuously increasing; (ii) continuously decreasing; (iii) a down-up-down; and (iv) an up-down-up pattern. Additionally, we demonstrate that the neutrophil migration signaling network and the balance between anti-apoptotic and pro-apoptotic signaling are two of the main regulatory mechanisms that change as the neutrophil transits through compartments.

Figure 1

Confirmation of microarray identified genes by qRT-PCR. (a) Genes with increased expression levels in neutrophils identified by microarray analysis: 10 regulated genes were assessed in samples from BM, blood and PE by qRT-PCR. The graphic illustrates fold change expression of PE (□) and blood (▪) relative to BM expression. *P≤0.001; **P≤0.003; ***P≤0.02; n=3. (b) Relationship between mean expression of the selected genes in a obtained by microarray (X-axis) and qRT-PCR (Y-axis) by Pearson linear correlation analysis of BM vs. blood expression. Each dot represents log fold change of one selected gene. The diagonal line represents the ideal correspondence trend (R²=0.718, P-<0.01). Similar trends were observed for PE vs. BM comparison. BM, bone marrow; PE, peritoneal exudates; qRT-PCR, quantitative real-time PCR.

Figure 2

Microarray transcriptome analysis of neutrophilsreveals four specific expression patterns. (a) Genes, which are continuously increasing, (b) genes which are Continuously decreasing in their pattern of gene expression. (c) with a down-up-down pattern and (d) up-down-up pattern. Relative fold change of gene expression is shown expressed in a.u. (e) Cluster analysis performed by applying a K-mean clustering algorithm of the most highly differentially expressed transcripts identified in the three neutrophils subsets, represented in this heatmap, demonstrates a up-down-up pattern with decreased regulation in PMN-B (full list can be found in Supplementary Table 5 and DAVID analysis of each cluster can be found in Supplementary Table 7). Green represents downregulation and red upregulation. a.u., arbitrary units; BM, bone marrow; PE, peritoneal exudate.

Figure 3

Analysis of the fMLP receptor signaling pathway. IPA canonical pathway analysis of fMLP receptor signaling pathway, (a1) in PMN-BM vs. PMN-B and (a2) PMN-B vs. PMN-PE. Red represents upregulated genes, green are downregulated genes and white symbols depict neighbouring genes in this analysis. Box highlight genes that were further evaluated by western blot analysis. (b) Graphical representation of gene regulatory patterns of CDC42, WASp and ARP2 by microarray analysis. (c1) Representative western blot of CDC42, WASp and ARP2 protein levels. PMN cell lysates from BM, blood and PE (15 µg of total protein per lane) were subjected to SDS–PAGE, transferred to nitrocellulose and probed with a monoclonal antibody against CDC42, WASp or ARP2. Expression was normalized to β-actin used as internal control. Graphs of densitometry analysis of western blots are shown in c2, c3 and c4. Neutrophil migration toward fMLP was assessed using Zigmond chambers. (d1) The proportion of neutrophils oriented towards the fMLP source (leading edge within 180° of the source) and (d2) and absolute speed of migration after 10 min exposure are shown. Graphs represent mean±s.e.m. of 3–5 independent experiments (ND, no difference; *P<0.001; **P<0.05). BM, bone marrow; fMLP, N-formyl-Met-Leu-Phe; PE, peritoneal exudate; WASp, Wiskott–Aldrich syndrome protein. A(a) and A(b) have been granted permission by Ingenuity Systems, Inc. to use copyrighted figures generated from Ingenuity Pathways Analysis in this publication.

Figure 4

Analysis of death receptor pathway. (a) Graphic representation of death receptor pathway using IPA canonical pathway analysis. Green represents downregulation and red upregulation (a1) in PMN-BM vs. PMN-B and (a2) PMN-B vs. PMN-PE. Box highlights genes that were further evaluated by western blot analysis. (b) Graphical representation of gene regulatory patterns of Bcl-xL, caspase 9, MCL-1 and ANXA1 by microarray analysis. (c1) Representative western blot of caspase 9 and Bcl-xL protein levels. PMN cell lysates from BM, blood and PE (15 µg of total protein per lane) were subjected to SDS–PAGE, transferred to nitrocellulose and probed with a monoclonal antibody against caspase 9 and Bcl-xL. Protein expression was normalized to β-actin as an internal control. Graphs of densitometry analysis of western blots are shown in c2 and c3. Apoptosis was assessed using flow cytometry analysis. The percentage of early apoptotic (Annexin V⁺, eFluor 506⁺) and late apoptotic cells (Annexin V⁺, eFluor 506⁻) (d1) and caspase 9 activation (d2) were measured by FACS analysis. Graphs represent mean±s.e.m. of 3–5 independent experiments (ND, no difference; *P<0.01; **P<0.05). a.u., arbitrary units; BM, bone marrow; IPA, Ingenuity Pathway Analysis; MFI, median fluorescence intensity; PE, peritoneal exudate. A(a) and A(b) have been granted permission by Ingenuity Systems, Inc. to use copyrighted figures generated from Ingenuity Pathways Analysis in this publication.