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

RESEARCH ARTICLE

Neutrophil transcriptional profile changes during transitfrom bone marrow to sites of inflammation

Flavia S Lakschevitz1,2, Michelle B Visser2,3, Chunxiang Sun2 and Michael Glogauer;1,2

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 transcriptomechangesas 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.

Cellular & Molecular Immunology advance online publication, 00 Month 2014; doi:10.1038/cmi.2014.37

Keywords: fMLP signaling pathway; microarray; neutrophil; transcriptome

INTRODUCTION

As the main cellular component of the innate immune system,

neutrophils are responsible for responding to bacterial infec-

tions. They are rapidly recruited to sites of infection where they

eliminate bacteria through both reactive oxygen dependent and

independent mechanisms.1 Their removal from the inflammat-

ory site alongside elimination of deleterious stimulus is indis-

pensable for maintaining host health.1,2 It has been established

that neutrophils are capable of changes in gene expression dur-

ing inflammatory responses.3 Subrahmanyam demonstrated

that while neutrophils synthesize lower levels of protein and

RNA, they are able to markedly change their gene expression

following bacterial exposure.4 The concept that neutrophils are

static quiescent cells that merely kill bacteria has been replaced

by the idea that neutrophils play a more active role in the host

response. For example, activated neutrophils are able to secrete

a variety of cytokines,5 act as antigen-presenting cells expressing

MHC Class II,6 allow activation of T cells7 and play an active

regulatory role in angiogenesis8 and tumoural fate.9

Neutrophils undergo spontaneous apoptosis in order to

maintain homeostasis, but also to regulate efficient resolution

of inflammation.2,10,11 Impaired clearance as well as delays in

apoptotic events is critical to the progression of chronic inflam-

mation.3,12,13 A complex signaling interaction regulates neu-

trophil apoptosis and is initiated by two distinct pathways: the

extrinsic pathway (death receptor pathway) and the intrinsic

pathway (mitochondria pathway), where both pathways lead

to activation of the characteristic caspase cascade4,10 It is very

likely that tight regulation of neutrophil apoptosis at different

locations is a key feature of normal neutrophil function.

To investigate gene expression profiles in the mouse neutro-

phil, as they leave the bone marrow (BM), enter the circulation,

and finally arrive in the site of inflammation, we used three

approaches: first using microarrays we identified differences

in the gene expression profile of neutrophils as they transit

through different compartments. Secondly, using a bioinfor-

matics approach, we examined whether the differences in gene

expression are associated with specific pathways. Finally, we

Cellular & Molecular Immunology cmi201437.3d 16/5/14 20:45:14

1Department of Periodontology, Faculty of Dentistry, University of Toronto, Toronto, Ont., Canada; 2Matrix Dynamics Group, Faculty of Dentistry, Universityof Toronto, Toronto, Ont., Canada and 3Current address: Department of Oral Biology, School of Dental Medicine, University at Buffalo, The State University ofNew York, Buffalo, NY, USACorrespondence: Dr. M Glogauer, Faculty of Dentistry, University of Toronto, Room 221 Fitzgerald Building, 150 College Street, Toronto, Ont. M5S 3E2,Canada.E-mail: [email protected]: 17 October 2013; Revised: 2 May 2014; Accepted: 2 May 2014

Cellular & Molecular Immunology (2014), 1–13� 2014 CSI and USTC. All rights reserved 1672-7681/14 $32.00

www.nature.com/cmi

www.nature.com/cmi

sought to investigate if these different gene expression profiles

result in differences in the neutrophil phenotype. Using a

combination of transcriptomic, bio5informatic and func-

tional approaches, we highlight the importance of altered gene

expression in the apoptosis pathway and N-formyl-Met-Leu-

Phe (fMLP) receptor pathways as the neutrophil migrates from

storage compartments into inflamed sites.

MATERIAL AND METHODS

Mice

Experiments were carried out in accordance with the Guide for the

Humane Use and Care of Laboratory Animals and were approved

by the University of Toronto Animal Care Committee (protocol #

20009597). C57BL/6 male mice (Charles River< ), 8–12 weeks of age,

were housed in the animal facility at the University of Toronto,

and fed mouse chow and water ad libitum.

Neutrophil isolation

We sought to identify the best neutrophil isolation method for

each compartment in mice that would result in adequate yield,

viability and purity. With that in mind, we tested different

methods for each of the three compartments: For isolation of

PMN-BM and PMN-B we used Percoll gradient separation14 or

immunomagnetic separation.15Additionally, for PMN-B we

used the FACS-sorted samples, while peritoneal exudate (PE)

PMN were collected with or without Percoll purification as

detailed below.

Preparation of BM PMN (PMN-BM)

Percoll gradient separation was performed as previously

described. In brief, BM cells were resuspended14 in 4 ml of a-

MEM and overlaid on Percoll gradients (82%/65%/55%). After

centrifugation (2500 r.p.m., 4 uC, 30 min) the lower band was

collected and washed with PBS. Erythrocytes were eliminated

by addition of 5 ml of Pharm Lysis buffer (BD Biosciences,

Mississauga, ON, Canada) followed by centrifugation

(2500 r.p.m., 4 uC, 5 min) as per manufacturer’s instructions.

Immunomagnetic negative selection using a Mouse Neutrophil

Enrichment Kit (Stemcell Technology, Vancouver, BC,

Canada) was also performed following the manufacturer’s

instructions, on either the whole BM cell or cell populations

following Percoll gradient separation. Sample purity was con-

firmed by flow cytometry. Neutrophils were identified based on

the following gating strategy: FSC vs. SSC, then Singlet1, fol-

lowed by eFluor 5062 and CD11b1Ly6G1. Flow cytometry

gating was performed based on fluorescence-minus one con-

trols (Supplementary Figures 1 and 2). Viability was confirmed

using eFluor 506 (eBioscience, San Diego, CA, USA), which

stains necrotic cells, during flow cytometric analysis and/ortry-

pan blue exclusion test. Following gradient separation alone, a

yield of 93106 cells/mouse with a purity of 85%63% and

95%65% viability. Negative selection from BM cell resulted

in purity similar to the Percoll gradient alone (80%65%) while

negative selection following Percoll resulted in the highest pur-

ity (98%62%) (Table 1). However, it produced a very low cell

yield (1623106 cells/mouse), which is in accordance with the

literature.15 For microarray analysis and functional assays, we

used the Percoll method alone for neutrophil isolation. For

Quantitative real-time PCR (qRT-PCR) analysis and western

blot analysis, Percoll gradient followed by additional purifica-

tion using immunomagnetic negative selection was performed.

Preparation of blood PMN

Methods similar to those for PMN-BM were performed for

isolation of blood neutrophils (PMN-B). Blood from twelve

mice were pooled to obtain appropriate numbers of cells.

Mice were anesthetized by intraperitoneal injection of keta-

mine (Ketaset 125 mg/kg) and xylazine (10 mg/kg). Blood

(1 ml) was collected by cardiac puncture using a sodium citrate

coated syringe and transferred to a 15 ml falcon tube with 100ml

of sodium citrate. Erythrocyte lysis was immediately performed

by addition of 5 ml of Pharm Lysis buffer (BD Biosciences) as

described above. The cell pellet was resuspended in 2 ml of a-

MEM and laid on the top of a three-layer Percoll gradient, as

described for PMN-BM isolation. Following gradient separa-

tion, a yield of 0.53106 cells/mouse with purity of 85% and

viability of 95% was obtained. Purity and viability was assessed

as described for PMN-BM. Additionally, we used flow cyto-

metric analysis to sort cells based on expression of Ly6G (1A8).

Gating was performed based on fluorescence-minus one con-

trols. Neutrophils were identified based on the following gating

strategy: FSC vs. SSC, then Singlet1, followed by eFluor 5062

and CD11b1Ly6G1. Cells were kept on ice during all proce-

dures. For microarray analysis and functional assays, we used

Percoll separation alone for neutrophil isolation. For qRT-PCR

analysis and western blot analysis, FACS-sorted and Percoll

gradient separation with and without an additional purification

by negative selection, was performed as described for PMN-

BM. After immunomagnetic separation, a yield of 0.33106

cells/mouse with purity of 98% and viability of .95% was


Table 1 Neutrophil isolation and purity (%6s.d.)

Compartment (%)

BM Blood PE

Isolation method Percoll only 85.263.6 84.763.6 95.961.7

Percoll1negative selection 97.662.1 98.264.4 n/a

Negative selection only 80.165.1 73.968.6 93.764.1

FACS 93.965.2 94.462.2 92.063.7

Abbreviations: BM, bone marrow; PE, peritoneal exudate.

Neutrophil gene expression profiles changes

FS Lakschevitz et al

2

Cellular & Molecular Immunology

obtained. For FACS-sorted cells, we obtain a yield of 0.13106

cells/mouse with purity of 94% and viability of .95%.

Preparation of PE PMN

Inflammation was induced by injecting 1 ml of 5 mM sodium

periodate (Sigma, Oakville, ON, Canada) solution into the

peritoneal cavity of the mouse. Similar to thioglycollate,

sodium periodate induces cell death in the peritoneum which

is the triggering event for neutrophil recruitment, which is

highly relevant for neutrophil recruitment in diseases with

underlying endogenously triggered inflammation including

myocardial infarction, atherosclerosis, type 2 diabetes mellitus

and some autoimmune diseases.16,17 PE cells were harvested 3 h

after injection by two lavages of the peritoneal cavity with 5 ml

of cold PBS (Sigma). Collected cells were then washed by cent-

rifugation (2500 r.p.m., 5 min, 4 uC), followed by erythrocyte

lysis with Pharm Lysis buffer (BD Biosciences). Additional

purification was performed by resuspending collected cells in

100% Percoll solution and ultracentrifugation (23 000 r.p.m.,

20 min, 4 uC). PMN were collected from the lower opaque layer

and washed twice by adding 10 ml of PBS then centrifuged at

2500 r.p.m. for 5 min at 4 uC. Purity and viability was assessed

as described above. Sodium periodate injection into peritoneal

cavity gave a yield of 13106 cells/mouse with PMN purity of

95% and viability .95%. For neutrophil chemotaxis and apop-

tosis assays, we collected peritoneal cells without further puri-

fication. Microarray and qRT-PCR analysis was performed

with cells isolated with Percoll purification. All the other

experiments were carried out as described. For some experi-

ments, purification was performing using negative selection as

described for PMN-BM.

RNA isolation from purified PMN

Neutrophils (1.03107 cells) from BM, PE and blood from sepa-

rate pools of up to 12 C57BL/6 male mice were immediately

prepared for RNA isolation, to avoid degradation, with MirVana

kit (Ambion, Austin, TX, USA) as described by the manufac-

turer. RNAse free techniques were utilized during all procedures

with surface and equipment decontamination by a surface

decontamination solution (RNAse Zap solution; Ambion).

Genomic DNA was eliminated by RNase-free DNase I digestion

(Qiagen, Mississauga, ON, Canada) during the isolation proced-

ure. Isolated total RNA was stored at 280 uC and later analyzed

on an Agilent 2100 bioanalyzer using a RNA 6000 picolabchip

kit (Agilent Technologies, Santa Clara, CA, USA) to certify that

all samples are with minimal degradation as possible. Isolated

RNA presenting RIN above 8 was selected for further analysis.18

Microarray analysis

Total RNA was measured for gene expression by microarray

using the Illumina Mouse-6 v2 Expression BeadChip (48 000

gene transcripts) at the Centre for Applied Genomics (Sick

Kids Hospital, Toronto, ON, Canada), and all experiments

were performed in triplicate.

Raw mouse microarray data were analyzed using lumi R

package. Background correction was done in Beadstudio

(Illumina, San Diego, CA, USA). The quantile normalization

method implemented in lumi R package was used to normalize

the data. We use LIMMA (linear models for microarray data)

to identify differentially expressed genes. To compare gene

expression in multiple groups, we used an empirical Bayes

approach to assess differentially expressed genes, allowing for

multiple testing adjustments. This method does not require the

data to be normally distributed.19 Briefly, it starts by fitting a

linear model for each gene in the data, and then empirical Bayes

method is used to moderate the standard errors for estimating

the moderated t-statistics for each gene, which shrinks the

standard errors towards a common value. The corresponding

P-values for the modified t-statistics were adjusted using the

multiple testing procedures developed by Benjamini and

Hochberg.20 Genes of interest were selected by setting the false

discovery rate at the level of 0.01 and by fold change of 2.

Further analyses were carried out using Ingenuity Pathway

Analysis (IPA—http://www.ingenuity.com) software (Ingenuity

Systems, Redwood City, CA, USA). Additional analysis were

performed using DAVID 6.7 (http://david.abcc.ncifcrf.gov)

(the database for annotation, visualization and integrated dis-

covery) bioinformatics resources as described elsewhere21 and

using GOEAST (http://omicslab.genetics.ac.cn/GOEAST/)

(Gene Ontology Enrichment Analysis Software Toolkit) bioin-

formatics tools.22 For cluster analysis and to generate heat-

maps, we used MultiExperiment Viewer (http://www.tm4.

org/mev/).23,24

Accession codes

The microarray data complies with MIAME guidelines, and the

data set was deposited at Gene Expression Omnibus (National

Center for Biotechnology Information), accession number

GSE43513.

qRT-PCR

Selected genes were analyzed using quantitative RT-PCR on

the same RNA samples used for microarray analysis. qRT-

PCR was performed in triplicates using a CFX96TM Real-

Time System (Bio-Rad, Hercules, CA, USA). The protocol

was followed according to Wang et al.,25 with a slight modi-

fication. Total RNA (0.12 mg) was reverse transcribed into

cDNA using Superscript II (Invitrogen Life Technologies,

Burlington, ON, Canada) and Oligo dT18VN primer (ACGT

Corp., Toronto, ON, Canada) in a 20 ml reaction volume. Two

negative controls were used to ensure there was no contam-

inating DNA: one without template RNA and another lacking

the reverse transcriptase. A reaction mixture was also prepared

containing: 5 ml of template cDNA, 15 ml of master mix (1 ml of

forward and 1 ml of reverse primer (both 10 mM stock), 10 ml of

BioRadSsofastEvaGreen Super Mix (BioRad) and 3 ml of

RNase-free distilled water was used. Primers were designed

from the PrimerBank ID number (Supplementary Table 2)

and GAPDH was used to normalize the expression data. For

data analysis, CFX manager software (Bio-Rad) was used. To

investigate the effect of neutrophil isolation method on gene

expression profiles, we compared gene expression of selected




3


genes across multiple methods (Supplementary Tables 2 and 3).

Comparisons performed included: BM isolation by Percoll vs.

immunoselection, FACS-sorted blood-PMN isolation with min-

imal manipulation vs. Percoll and FACS-sorted blood-PMN from

mice with and without induction of peritonitis (Supplementary

Table 4). Results are reported using the DCt method, which cal-

culates the difference between the reference and target Ct values

for each sample. First, we determined the relative expression of

each gene for each compartment (BM, blood and PE) using the

following equation: 2(Ct(GAPDH)2Ct(Target gene))5relative express-

ion. Then, the ratio of expression was determined by dividing

the relative expression of each target gene from each site (blood

or PE) to the relative expression of each target gene from BM

samples. The graphic illustrates the relationships of obtained from

Blood to BM and PE to BM.

Western blots

Protein lysates from neutrophils were prepared with SDS

buffer. The lysates were clarified by centrifugation (5 min,

13 000 r.p.m. at 4 uC). Total protein concentration was mea-

sured with a BCA protein assay kit (Pierce= ). Fifteen micrograms

of heat-denatured protein was loaded on a 12% polyacrylamide

gel followed by transfer to nitrocellulose membrane (Amersham> ).

After transfer,the membrane was incubated for 1 h in blocking

buffer (5% nonfat milk powder in Tris-buffered saline and

0.1% Tween 20 (TBST)). The membrane was incubated over-

night in primary antibody in TBST with 5% bovine serum

albumin, washed with TBST (3310 min) and incubated for

60 min in horseradish peroxidase-conjugated secondary anti-

body/5% nonfat milk powder/TBST at room temperature.

After washing with TBST (3310 min), the membrane was

developed with Western Lightning solution (PerkinElmer? )

and exposure to film (Kodak@ ). Images obtained were quanti-

tated using ImageJ software as described elsewhere.26 The fol-

lowing antibodies were purchased from Cell SignalingA : ARP2,

Wiskott–Aldrich syndrome protein (WASp), CDC42, caspase-

9 and Bcl-xL.

Neutrophil chemotaxis assays

Neutrophils from the three compartments (BM, blood and PE)

were suspended in HBSS with 1% gelatin. Neutrophils (13106/

ml) were allowed to attach to bovine serum albumin-coated

glass coverslips (22340 mm) at 37 uC for 15 min. The coverslip

was inverted onto a Zigmond chamber, and 100 ml HBSS media

was added to the left chamber with 100 ml HBSS media contain-

ing fMLP (1026) was added to the right chamber. Time-lapse

video microscopy was used to examine neutrophil movement

in Zigmond chambers. The microscope (Nikon Eclipse E400)

was equipped with differential interference contrast optics and

a 320 objective. Images were captured at 15-s intervals for

10 min with a Nikon Coolpix 995 camera. Cell-tracking soft-

ware (Retrac version 2.1.01 Freeware) was used to characterize

cellular chemotaxis and the percentage of cells migrating

toward chemoattractant source was calculated from the cap-

tured images.

Quantification of neutrophil apoptosis

Neutrophil apoptosis was quantified in the three different

compartments by flow cytometry using FlowJo software for

analysis. Neutrophils were identified based on the following

gating strategy: FSC vs. SSC, then Singlet1, followed Ly6G1.

Apoptotic cells were gated based on exclusion of eFluor506

staining and Annexin V staining. Cells, which stained positive

for Annexin V only, were considered early apoptotic and cells

that stained for eFluor506 and Annexin V were considered late

apoptotic events.

Caspase 9 cleavage Assay

Neutrophils were isolated from each compartment (BM, blood

and PE) and cultured overnight in complete medium to induce

apoptosis, followed by a 30 minutes incubation using Fluo-

rescein Active Caspase-9 Staining kit (eBioscience). Cells were

then harvested, washed and stained with Annexin V. Finally,

the cells were analyzed in the presence of DAPI Staining

Solution. Viable cells were gated based on exclusion of DAPI

staining and then these gated events were analyzed for staining

of Annexin V and Fluorescein Active Caspase-9.

Statistical analysis

For experiments in which there were multiple observations per

sample, numerical results were expressed as mean6s.e.m. Each

experiment was performed at least three times, and within

each experiment, each data point had a sample size of no3.

Statistical analysis was performed using Student’s two-tailed t-

test, unless specified otherwise. Pf0.05 was considered statist-

ically significant, by GraphPad B(http://www.graphpad.com).

RESULTS

Neutrophil isolation and purity

Neutrophils from BM, blood and inflamed tissues are part of

mixed cell populations. Since transcriptome profiling and phe-

notyping assays could be influenced by contaminating cell

populations we optimized our neutrophil isolation protocols

(Table 1) and verified that the isolation protocols and contam-

inating cells themselves did not significantly alter the gene

expression profiles of the isolated neutrophils. qRT-PCR ana-

lyses were performed to evaluate how the method of PMN

isolation may affect the neutrophil transcriptome. Com-

parison of PMN-BM isolated by Percoll gradient separation

with immunomagnetic separation, PMN-B FACS sorted (to

minimize manipulation) with Percoll gradient separation yielded

no significant differences in gene expression (Supplementary

Tables 2 and 3).

The neutrophil is a transcriptionally active cell that alters its

gene expression profile as it migrates from storage

compartments into sites of inflammation

Following purification of neutrophils from the three compart-

ments in mice (BM, blood and PE) (Supplementary Figures 1

and 2) we performed gene expression analysis using an Illu-

mina gene array. Of the 45 282 probe sets, we identified 1216

genes that were differentially expressed when we compared




4


neutrophils from BM (PMN-BM) with neutrophils isolated from

blood (PMN-B), 1468 genes when we compared PMN-B and

neutrophils from PE (PMN-PE) and 1545 genes when comparing

PMN-BM vs. PMN-PE, using a cutoff of twofold change (FC)

and a P-value of 0.001 (Table 2 and Supplementary Table 1). We

confirmed these results using a second statistical approach, the

significance analysis of microarray technique, and similar gene

numbers and significance levels were found (data not shown).

Confirmation of microarray data by qRT-PCR

To validate the microarray data, changes in expression of 10

selected genes were assessed by qRT-PCR, in samples taken

from the three different compartments (Figure 1a). From our

initial microarray analysis using IPA software, we identified

several pathways that were differentially regulated as neutro-

phils transit through compartments. For validation of our

microarray data, we selected cell migration due to its high

significance value (P51.8531026) and the high frequency of

these genes appearing in the array results. For theneutrophil

chemotaxis pathway 12 genes were differentially regulated:

C5AR1, CCL3, CXCL1, CXCL2, CXCL3, fMLP receptor 1,

IL-1B, Lilrb3, MAPKAPK2, NOD2, PDE4B and TLR4. From

those 12 genes, we selected the 10 genes with the highest fold

change for further analysis. These initial data were confirmed

by correlating the signal intensities of the microarray with qRT-

PCR experiments using the Pearson linear correlation test to

measure the relationship between microarray and qRT-PCR

results. The results were highly concordant for the majority

of genes selected (r250.7180), although some minor differ-

ences were found in the magnitude of the change (Figure 1b).

Additional qRT-PCR analyses were also performed to evaluate

if the PMN-B transcriptome would be altered by peritonitis.

We found that the transcriptome of PMN-B was not altered by

the presence of peritonitis (Supplementary Table 4).

Microarray transcriptome analysis through the neutrophil

migration cycle reveals four different gene regulation patterns

During our analysis, we could clearly divide genes based on

their expression patterns through the three compartments:

1. Continuously increasing: Overall, 69 genes were consis-

tently increased in their expression from BM through

blood through to the peritoneum. Gene ontology analysis

indicates over representation of processes involved in the

regulation of apoptosis and cell death, cytokine–cytokine

receptor interaction, and cell adhesion and activation in

this category (Figure 2a and Supplementary Table 9).

2. Continuously decreasing: We found 170 genes in which

their expression decreased as they migrated from the BM

to the blood and into the inflamed tissue. Cell cycle func-

tions were among the pathways enriched within this cat-

egory (Figure 2b and Supplementary Table 10).

3. Down-up-down pattern: This group consisted of 617

genes being low in the BM, then upregulated in PMN-B

with subsequent downregulation in PMN-PE; cell adhe-

sion molecules, antigen processing and presentation, and

inflammation mediated by chemokine and cytokine sig-

naling pathway were upregulated in this group (Figure 2c

and Supplementary Table 11).

4. Up-down-up pattern: This group consisted of 360 genes

that are upregulated in PMN-BM, downregulated in

PMN-B and later upregulated in PMN-PE. Regulation

of actin cytoskeleton and the PI3/kinase pathway were

among those downregulated in PMN-B (Figure 2d and

Supplementary Table 12). We confirmed the expression

pattern groupings using Cluster analysis with a K-mean

clustering algorithm of the high differentially expressed

transcripts identified in the three neutrophil subsets. The

up-down-up pattern with decreased regulation in PMN-B

is represented by the heat map found in Figure 2e; addi-

tional clusters, demonstrating an up- or downregulatory

pattern, can be found in Supplementary Table 5—pat-

terns of expression.

Location of neutrophils significantly influences the gene

regulation pattern

Using IPA software to identify the main biological processes

with changing gene expression as neutrophils leave circulation


Table 2 The neutrophil is a transcriptionally active cell that alters its gene expression profile as it migrates from sterile

compartments into sites of inflammation. Bone marrow neutrophils (PMN-BM) were compared with blood neutrophils (PMN-

B), PMN-B were compared with peritoneal exudate neutrophils (PMN-PE) and PMN-BM were compared with PMN-PE, using a

cutoff of fivefold change (FC) and a P-value of 0.001. For a complete list of genes for each comparison, see Supplementary Table

1

BM vs. blood BM vs. PE Blood vs. PE

Fold change # of genes Fold change # of genes Fold change # of genes

BM f15 39 BM f15 52 Blood f15 19

10–15 75 10–15 46 10–15 33

5–10 249 5–10 168 5–10 145

Blood 5–10 638 PE 5–10 311 PE 5–10 346

10–15 81 10–15 70 10–15 106

f15 82 f15 126 f15 144

Total 1164 Total 773 Total 793

Abbreviations: BM, bone marrow; PE, peritoneal exudate.



5


and enter a site of inflammation, we grouped differentially

expressed genes into known molecular and cellular functions.

Molecular functions such as antigen presentation, cell-to-cell

signaling and interaction and cell death were differentially

regulated in both comparisons (PMN-BM vs. PMN-B and

PMN-B vs. PMN-PE), while cellular movement and cell signal-

ing were upregulated only when comparing PMN-B vs. PMN-

PE. Cellular morphology and cellular compromise were found

to be upregulated only in the PMN-BM vs. PMN-B comparison

(Supplementary Table 6—IPA Summary).

Additionally, pathway analysis was performed with DAVID,

a web-based software package that organizes genes based on

GO Terms, and interrelationship between genes of inquiry.

Among the altered pathways in both PMN-BM vs. PMN-B

and PMN-B vs. PMN-PE are inflammation mediated by che-

mokine and cytokine inflammation signaling pathway, the

MAPK signaling pathway, antigen processing and presentation

and T cell activation (Supplementary Table 7A). Pathways that

are altered in PMN-BM vs. PMN-B analysis only are: regulation

of actin cytoskeleton, PI3/kinase pathway and integrin signal-

ing pathway (Supplementary Table 7B). Finally, we found Toll-

like receptor signaling pathway, NOD-like receptor signaling

pathway, oxidative stress response, caspase cascade in apopto-

sis and regulation of BAD phosphorylation among the path-

ways that are enriched when PMN-B were compared with

PMN-PE (Supplementary Table 7C). Since multiple leukocyte

migration and apoptosis containing pathways were upregu-

lated in both comparisons we chose to further explore cell

movement and cell death categories in the neutrophils from

the three compartments.

Evaluation of leukocyte migration—fMLP receptor

signaling and actin

As cell migration was one function differentially regulated

between sites we chose to further analyze components of this

pathway. As a first step toward better understanding neutrophil

chemotaxis following exposure to fMLP, we analyzed the fMLP

receptor signaling pathway and specific key components

involved in chemotaxis. It is known that activation of cell sur-

face receptors initiates intracellular signal transduction path-

ways, leading to responses including superoxide production,

actin reorganization and cell migration.27

Through our microarray analysis and subsequent additional

protein expression analysis, we observed upregulation of the

Rho family small GTPase CDC42 and actin binding protein

ARP2 in PMN-PE compared with PMN-B, yet no expression

difference was found for WASp. CDC42 regulates actin poly-

merization through its direct binding to WASp, which subse-

quently activates the Arp2/3 complex leading to de novo actin

assembly28 (Figure 3a–c).

To verify if these signalling regulation differences translate to

functional differences, we also analysed neutrophil chemotaxis

in a gradient of fMLP using Zigmond chambers. Neutrophils

from BM migrated with increased speed compared with PMN-

PE (8.8660.271 mm/min vs. 6.1260.103 mm/min, Pf0.0001),

while no difference was found between PMN-BM when com-

pared with PMN-B (8.8660.271 mm/min vs. 8.5160.322 mm/

min, P50.4542) (Figure 3d1). However, when we analyzed the

direction of migration (chemotaxis compass), after 10 minutes

of fMLP stimulation, we found that 87.7%63.2% of PMN-PE

were migrating towards fMLP vs. 69%65.9% of PMN-B

(P50.0495) and 59.5%64.0% of PMN-BM (P50.0029)

(Figure 3d2 and Supplementary Figure 4).

Death receptor pathway

Our microarray analysis demonstrated enrichment of apoptosis

associated pathways as neutrophils migrates through different

sites. It is widely recognized that neutrophils undergo apopto-

siseven in the absence of any extracellular stimuli.4,10,29,30 The

Bcl-2 family, which we observed in our microarray analysis to


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Figure 1 Confirmation of microarray identified genes by qRT-PCR. (a) Genes with increased expression levels in neutrophils identified by microarrayanalysis: 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. *Pf0.001; **Pf0.003; ***Pf0.02; n53. (b) Relationship between mean expression of theselected genes in a obtained by microarray (X-axis) and qRT-PCR (Y-axis) by Pearson linear correlation analysis of BM vs. blood expression. Eachdot represents log fold change of one selected gene. The diagonal line represents the ideal correspondence trend (R250.718, P-,0.01). Similartrends were observed for PE vs. BM comparison. BM, bone marrow; PE, peritoneal exudates; qRT-PCR, quantitative real-time PCR.



6


be differentially expressed between compartments, is an impor-

tant regulator of neutrophil apoptosis.5,31 Here we found a

mixed pattern with both pro-apoptosis and pro-survival genes

with altered regulation, as neutrophils leave the circulation and

arrive at the site of inflammation with downregulation of FasL,

CR3 (Mac-1), caspase 2 and 9 and upregulation of Fas, Daxx,

cIAP and NfkB. Additionally, members of the TLR family

including TLR2 and TLR4 were decreased in PMN-PE

(Figure 4a and b and Supplementary Table 13). Interestingly,

MCL-1 (Bcl2L11), a known regulator of neutrophil apopto-

sis,6,32 is highly expressed in all three compartments, but with

no difference in its regulation. Another major regulator of neu-

trophil apoptosis is Annexin-A1.7,33 Expression of Annexin-A1

in neutrophils, promotes pro-apoptotic mechanisms8,34 and

promote the removal of cells that have undergone apoptosis.9,35

From our data, we observed a downregulation of Annexin-A1

suggesting the balance between anti-apoptotic and pro-apopto-

tic signaling is active as these cells migrate through compart-

ments and is an essential element of cellular innate immunity.

In order to extend our microarray results, selected apoptosis

proteins were also analyzed by western blot or flow cytometry

(Figure 4c and d). We quantified protein expression of caspase

9 and Bcl-xL (Bcl2L1) and found that consistent with the

microarray data, PMN-PE presented with decreased expression

of full-length caspase 9 and increased expression of Bcl-xL. To

confirm results from western blot analysis, we also used a flow

cytometry-based assay to detect active Caspase 9 in neutrophils

from the three compartments (Figure 4d2). Apoptosis among

sites was also measured by Annexin V expression with

2.2%60.91% in the PMN-BM, 8.7%62.27% in the PMN-B

and 3.8%60.72% in PMN-PE (vs. PMN-BM, P50.0333; vs.

PMN-B, P50.05) (Figure 4d1). PMN-PE presented with the

lowest active caspase 9 activity with median fluorescence intens-

ity (MFI)58.41310661.113106 (vs. PMN-BM, P50.01; vs.

PMN-B, P50.01), PMN-BM with MFI51.43310761.003106

and PMN-B with MFI51.34310766.453105 (Figure 4d2).

DISCUSSION

It has been demonstrated that neutrophils produced in the BM,

enter the circulation and finally arrive at the site of inflam-

mation/infection.1,2,10,11,36–38 Although previous studies have

shown that neutrophils can undergo rapid changes in gene

expression upon bacterial challenge3,4,12,13,39 or exposure to

endotoxin,3,4,10,40 it was previously unknown if and to what

extent the neutrophil alters its transcriptome as it transits from

the BM through the circulation and into sites of inflammation.

Microarrays have significantly enhanced our knowledge of

neutrophils by providing a general indication of the number of

transcripts involved in their biology.14,41In analyzing the tran-

scriptome of murine neutrophils from BM, blood and PE, we


14

12

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a.u.

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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 themost 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 inSupplementary Table 7). Green represents downregulation and red upregulation. a.u., arbitrary units; BM, bone marrow; PE, peritoneal exudate.



7



fMLP

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8


noted a significant alteration in the neutrophil transcriptome

as these cells migrate through compartments, characterized by

four distinct gene expression patterns: a continuously increas-

ing, a continuously decreasing, a down-up-down and an up-

down-up pattern. Our demonstration that neutrophils

undergo transcriptome changes as they transition through

compartments suggest that (i) neutrophils are able to alter their

transcriptome as required after leaving the BM; (ii) unique

neutrophil phenotypes may be found within different environ-

ments; and (iii) careful consideration is required when deter-

mining the experimental source of cells when carrying out

neutrophil studies.

The need to obtain a highly purified neutrophil population is

important for many studies, especially when dealing with more

sensitive molecular biology techniques.15,42–44 The neutrophil

literature contains numerous methodologies for neutrophil

purification; ranging from density gradient centrifugation to

immunomagnetic selection, cell sorting and culture mod-

els.14,41,45–47 In this study, obtaining high-quality mRNA from

neutrophils for all three compartments was the greatest obs-

tacle and required the most amount of refining. While the

current optimal method for obtaining pure neutrophils is

immunomagnetic negative selection,15,43,48 this approach

resulted in very low cell yields (loss of up to 90% of neutro-

phils—see the section on ‘Materials and methods’) and low

mRNA quality. Both of these drawbacks made microarray

impossible with this method. Since neutrophils synthesize

low levels of mRNA, we opted to use a Percoll gradient, which

we manipulated to allow us to obtain a high yield and viability,

with minimallevels of contaminating cell lineages. Interes-

tingly, western blot analysis of neutrophils isolated by either

Percoll gradients or negative immunomagnetic selection yielded

identical results, supporting the use of the gradient isolation

approach for these experiments (data not shown). We also

obtained similar results by qRT-PCR analysis for FACS-sorted

samples and samples isolated using the gradient method, also

confirming the validity of our isolation method and data

obtained. Additionally, to further confirm the low frequency

of non-granulocytic cells in the isolated populations, microarray

analysis failed to detect transcripts encoding lineage-specific

genes highly expressed in T and B cells (CD4, CD19), monocytes

(M-CSFR, CD16) and eosinophils (IL-5R) in any of the com-

partment isolates. Of particular relevance is the triggering event

for neutrophil recruitment to the peritoneum. We used sodium

periodate, a model of sterile inflammation that induces cell

death without bacterial byproducts. This system is highly rel-

evant for neutrophil recruitment in diseases with underlying

endogenously triggered inflammation including myocardial

infarction, atherosclerosis, type 2 diabetes mellitus and some

autoimmune diseases.16,17 As a result, we believe that the gene

changes here in the sterile inflammation model may also be

consistent with changes in these other inflammatory responses.

To perform gene expression analysis, we used a bioinfor-

matics approach that allowed us to organize the neutrophil

transcriptome into known molecular functions, cellular

components and canonical pathways. Using these tools, we

demonstrated that the three populations of neutrophils are

significantly different in their gene expression profiles. To bet-

ter understand these differences, we carried out bio-informatic

investigations on those traditionally associated neutrophil

functions, such as chemotaxis and apoptosis, as well as identify

less well-established functions such as cell-mediated immune

response and cell-to-cell interaction (Supplementary Table 7).

When analyzing functions involved in neutrophil chemotaxis,

such as cell movement and leukocyte migration, our results

were the opposite of what has been previously reported in

neutrophils found in tumors.16,17,49 We found enrichment of

leukocyte migration and cell movement in tissue neutrophils

(PMN-PE), while Fridlender et al.18,49 reported downregula-

tion of the same pathways in neutrophils in tumoral tissue. This

differencelikely reflects differences in tumor-associated neu-

trophils and tissue neutrophils, where at a tumor site, once

neutrophils arrive, they lose their ability to leave the area and

therefore no longer require the cell migration apparatus.19,49

Not surprisingly, highlighted by DAVID analysis, we also

found upregulation of neutrophil responses, such as Toll-like

receptor signaling, NOD-like receptor signaling and the oxid-

ative stress response in PMN-PE when compared with PMN-B.

These are all key pathways involved in the neutrophil response

at inflammatory sites, allowing for detection of invading patho-

gens and induction of host antimicrobial defense.

Neutrophil chemotaxis is tightly regulated by a group of

receptors divided into two main groups: non-classical and clas-

sical chemotactic receptors.20,50 The classical chemotactic

receptors belong to the G-protein coupled receptor family

and are also capable of inducing additional immune functions

of neutrophils. These receptors include the N-formylated pep-

tide (N-formyl-L-methionyl-L-leucyl-phenylalanine) fMLP

receptor.21,51 Low concentration of fMLP induces change of

shape (polarization), formation of pseudopod extension and


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 neighbouringgenes in this analysis. Box highlight genes that were further evaluated by western blot analysis. (b) Graphical representation of gene regulatorypatterns of CDC42, WASp and ARP2 by microarray analysis. (c1) Representative western blot of CDC42, WASp and ARP2 protein levels. PMN celllysates from BM, blood and PE (15 mg of total protein per lane) were subjected to SDS–PAGE, transferred to nitrocellulose and probed with amonoclonal antibody against CDC42, WASp or ARP2. Expression was normalized to b-actin used as internal control. Graphs of densitometryanalysis of western blots are shown in c2, c3 and c4. Neutrophil migration toward fMLP was assessed using Zigmond chambers. (d1) Theproportion of neutrophils oriented towards the fMLP source (leading edge within 180u of the source) and (d2) and absolute speed of migration after10 min exposure are shown. Graphs represent mean6s.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.



9



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10


ultimately chemotaxis of neutrophils22,52 through activation of

downstream signaling pathways including small GTPase-

associated pathways and subsequent cytoskeletal rearrange-

ments, while higher concentrations also induce degranulation

and generation of oxygen-derived free radicals.23,24,53 In this

study, we selected the fMLP pathway to further investigate its

regulation during neutrophil migration through different

compartments. Our bio-informatic approaches identified

fMLP receptor 1 to be upregulated in PMN-PE. fMLP receptor

1 mediates fMLP-induced actin polymerization and chemo-

taxis.25,54 It has recently been reported that the CDC42/

WASp axis downstream of the fMLP receptor mediates neu-

trophil polarity,26,48 where CDC42 controls WASp activation,

which in turn induces CD11b clustering, related cytoskeletal

stabilization, cell polarity and efficient migration. Here we also

found the actin regulatory protein, ARP2 to be upregulated

likely allowing for increased directionality in PMN-PE, where

neutrophil polarization is critical. Our microarray analysis sug-

gested that the regulation of cell migration may be altered as the

neutrophils transit through compartments. We therefore

looked at the protein levels for some of the key proteins in this

pathway and assayed chemotaxis. Since ARP2 is key element of

actin mediated cell migration and was upregulated as the neu-

trophil migrates from blood into the peritoneum, we assayed

expression of this protein as well as the small GTPase CDC42

and WASp. In agreement with the microarray data, the express-

ion of ARP2 was increased as the neutrophils enter the peri-

toneum. This result is consistent with data from other cells

where ARP2 is required for normal directional movement.55

In agreement with the microarray data, WASp showed signifi-

cantly altered expression in the peritoneum compared to the

blood (Figure 3).

Apoptosis plays an important role in the neutrophil cycle with

involvement in continuation or resolution of the inflammatory

response. Our microarray data highlighted a shift in the balance

between pro-apoptosis and anti-apoptosis molecules between

compartments. Although we recognize that our microarray

analysis only shows that the regulation of the death receptor

pathway is significantly altered as the neutrophils enter the

tissue compartment, our flow cytometry data further confirm

increased apoptosis in blood and tissue as demonstrated by

increased membrane alterations measured by Annexin V

expression. Previously, a microarray-based approach analyzed

differences in neutrophil gene expression during spontaneous

apoptosis after extended culture (12–24 h) with and without

GM-CSF.32 Similar to our study, they observed changes in cas-

pase 9, as well as Fas and Bcl2 members. Interestingly, we show

that the expression of these pro-apoptotic genes and pro-

survival genes is also altered as the cell arrives at the site of

inflammation. Importantly, our data highlight that regulatory

mechanisms of neutrophil apoptosis in vivo are differently regu-

lated than in vitro.32 It is well recognized that delay in neutrophil

apoptosis coincides with preservation of their functions.11,56

Another interesting finding that is worth to mention, is the

variability of Annexin-A1 expression found in our microarray

analysis. During an inflammatory insult, Annexin-A1 is known

to reduce inflammation of tissues by interacting with Annexin-

A1 receptors on neutrophils. In turn, upon the activation of these

receptors, leukocytes are directed to the site of infection and

target the source of inflammation directly.34,57 Consequently, this

inhibits neutrophils extravasation and downregulates the mag-

nitude of the inflammatory response. Without Annexin-A1 in

mediating this response, neutrophil extravasation is highly

active.33 Our data demonstrate increased early apoptotic events

in the blood, characterized by increased Annexin-V expression,

which likely represents a safety mechanism to promote a smooth

turnover of cells, since apoptotic cells suppress the production of

pro-inflammatory cytokines.56 Further, a shift occurs in periton-

eal neutrophils with reduced apoptosis rate, reflecting that pre-

servation of neutrophil functions is required at inflammatory

sites.

Consistent with our previous report, where neutrophils

altered their transcriptome and phenotype as they transited

from circulation into the oral cavity in humans,58,59 we also

observed pathways not traditionally associated with neutrophil

biology such as cell-to-cell signaling and interaction, IL-17

signaling and regulation of T-cell activation to be enriched in

murine blood when compared with BM and the peritoneum. A

large number of genes commonly expressed in T cells can also

be expressed by neutrophils. For example, ZAP70, a compon-

ent of the T-cell receptor complex, as well as CXCL9 and

CXCL10, which are known chemoattractant to T cells, is highly

regulated in neutrophils, and to finalize some activators of T

cell, pathways such as CCL2 and CCL20 can be expressed and

produced by activated neutrophils. More importantly, this

supports the idea that innate7,60 and adaptive immunity do

not function independently of each other, and neutrophils play

an important role in these interactions.7

Our data presented here is supported by de Kleijn et al.,61

where they looked at neutrophil subsets in humans, based

on expression of CD16/CD62L. After inducing endotoxemia,

they observed upregulation of genes involved in regulation of

immune responses and apoptosis. This upregulation of apop-

tosis associated pathways in both our murine model and their

human model allow us to speculate that similar mechanisms

drive changes in the neutrophil transcriptome in a mice model

of inflammation and an induced endotoxemia model in

humans.61 Interestingly, analysis of blood neutrophils from

trauma patients also identified the death receptor pathway,

antigen presentation pathway and oxidative phosphorylation

to be upregulated,41 similar to our results presented in this

study. These are significant observations, considering the dif-

fering species and study designs, method of PMN isolation and

microarray platforms.41

Our study demonstrates that neutrophils are highly plastic

cells where compartment cues determine a site-specific neutro-

phil transcriptome. The differences in the cell functions

between the three compartments allow us to suggest that the

neutrophil has a site-specific phenotype in each compartment.

This study focused on gene expression changes in response to a




11


sterile injury, which suggests that these responses may also be

extrapolated to other inflammatory models, including contact

hypersensitivity and autoimmune diseases, although further

studies will be required to confirm this.

AUTHOR CONTRIBUTIONS

FL designed, conducted experiments, analyzed data, inter-

preted experiments and wrote the paper; MV conducted

experiments and wrote the paper; CS conducted experiments;

and MG designed, interpreted experiments and wrote the

paper.

COMPETING CONFLICTS OF INTEREST

The authors declare no competing financial interests.

ACKNOWLEDGEMENTSThis work was funded by an operating grant from The Canadian

Institutes of Health Research (CIHR, Ottawa, ON, Canada) to MG. FL

is supported by CIHR Training Fellowship, TGF-53877 and the

Harron scholarship (Faculty of Dentistry, University of Toronto).

The authors give special thanks to Dionne White from The Flow

Cytometric Facility of the Immunology Department, Faculty of

Medicine of University of Toronto for assistance with flow cytometric

analysis, also to Guillermo Casallo and Pingzhao Hu of the Centre for

Applied Genomics, The Hospital for Sick Children, Toronto, Canada,

for assistance with microarray analysis and statistical analysis

respectively.

Supplementary Information accompanies the paper on Cellular &

Molecular Immunology’s website. (http://www.nature.com/cmi).

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

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