Microarray analysis of lipopolysaccharide-treated human neutrophils

Kenneth C. Malcolm1, Patrick G. Arndt1,2, Elizabeth J. Manos3, David A. Jones3, and G. Scott Worthen1,2

1 Department of Medicine, National Jewish Medical and Research Center, Denver 80206; 2 University of Colorado Health Sciences Center, Denver, Colorado 80262; and 3 The Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah 84112


    ABSTRACT
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ABSTRACT
INTRODUCTION
METHODS
RESULTS AND DISCUSSION
REFERENCES

Neutrophils respond to infection by degranulation, release of reactive oxygen intermediates, and secretion of chemokines and cytokines; however, activation of neutrophil transcriptional machinery has been little appreciated. Recent findings suggest that gene expression may represent an additional neutrophil function after exposure to lipopolysaccharide (LPS). We performed microarray gene expression analysis of 4,608 mostly nonredundant genes on LPS-stimulated human neutrophils. Analysis of three donors indicated some variability but also a high degree of reproducibility in gene expression. Twenty-eight verifiable, distinct genes were induced by 4 h of LPS treatment, and 13 genes were repressed. Genes other than cytokines and chemokines are regulated; interestingly, genes involved in cell growth regulation and survival, transcriptional regulation, and interferon response are among those induced, whereas genes involved in cytoskeletal regulation are predominantly repressed. In addition, we identified monocyte chemoattractant protein-1 as a novel LPS-regulated chemokine in neutrophils. Included in these lists are five clones with no defined function. These data suggest molecular mechanisms by which neutrophils respond to infection and indicate that the transcriptional potential of neutrophils is greater than previously thought.

cellular activation; gene regulation; Toll-like receptor; host defense


    INTRODUCTION
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ABSTRACT
INTRODUCTION
METHODS
RESULTS AND DISCUSSION
REFERENCES

THE INNATE IMMUNE RESPONSE is initiated by recognition of microbial surface or secreted components (1), typified by the lipopolysaccharides (LPS) of gram-negative bacteria. To contend with invading microorganisms, the innate response utilizes a number of mechanisms including: 1) generation of reactive oxygen intermediates, 2) release of antimicrobial peptides, 3) phagocytosis, and 4) production and release of cytokines and chemokines. The latter mechanism, relying on transcriptional and translational controls, acts to recruit additional immune cells to the site of infection to amplify and regulate the response.

Polymorphonuclear leukocytes (neutrophils) are important components of innate immunity. Neutrophils alone can effectively limit infection and, by production of chemokines, recruit and activate other immune cells that aid in clearance of the infectious agents and mount an adaptive immune response. An experimental model of neutrophil response to infection involves exposure of cells to soluble LPS. Soluble LPS, found in the circulation and at sites of infection, is recognized by the Toll-like receptors (TLRs) present on immune cells and has been identified as the initial signaling event in the response to LPS (4, 6, 25, 34, 49). TLRs belong to the interleukin (IL)-1 family of receptors (4, 34, 39) and signal through the cascade of MyD88, interleukin receptor-associated kinase (IRAK), and tumor necrosis factor (TNF) receptor-associated factor 6 to activate NF-kappa B and MAP kinases (4, 34). Although neutrophils are known to respond to LPS by production of reactive oxygen intermediates, release of lipid mediators and cytokines, adhesion, and phagocytosis, the genomic response of the neutrophil to infection has been believed to be somewhat static. Recent studies indicate a robust transcriptional response (32), especially of cytokines, indicating that the neutrophil contributes more than the release of premade mediators and formation of bactericidal agents. For example, it is well documented that neutrophils produce cytokines such as IL-1beta , IL-8, and TNF-alpha and that this production can depend on both transcriptional and translational regulation (35). Therefore, general mechanisms exist for regulation of gene expression in neutrophils after exposure to LPS.

Previous studies screening for changes in gene expression in experimental situations include subtractive hybridization and sequencing, coupled with Northern blot and PCR-based analysis. Recent advances in microarray analysis have allowed the screening of a large number of changes in mRNA expression. In this way, thousands of genes can be screened in an unbiased fashion for transcript abundance and changes in expression levels. Such genomic screens in mammalian cells have involved altered expression profiles in response to agonists (11) and drug action (24) and during cell cycle progression (22). Furthermore, microarray analysis can suggest pathways important in cell function that otherwise would be difficult to unmask by traditional methods. We reasoned that neutrophil gene expression changes are not limited to cytokine production and that a more detailed examination of gene expression in stimulated neutrophils will display novel gene expression profiles with potential consequences in functional characteristics. As an initial step to test this hypothesis, we have utilized microarray technology. Furthermore, we have recognized that neutrophil life span is enhanced at sites of infection (by inhibition of spontaneous apoptosis), and, therefore, time points other than those immediately after stimulation may provide clues into neutrophil function. Thus we have examined gene expression after prolonged (4 h) stimulation with LPS.

Analysis of gene expression microarrays of naïve and LPS-stimulated neutrophils confirmed the production of chemokine and cytokine (e.g., IL-1beta ) mRNAs among the 28 distinct gene products found to be induced by LPS, including monocyte chemoattractant protein (MCP)-1, described here for the first time as induced by LPS in neutrophils. Surprisingly, a number of genes involved in distinct cellular processes were also induced including those involved in transcriptional regulation (e.g., NFKB) and cell signaling (e.g., cot). Likewise, repression of diverse genes, including those important for cytoskeletal regulation [e.g., tubulin, Rho guanine nucleotide dissociation inhibitor (GDI)beta ], was found to occur. Finally, changes in the expression levels of several expressed sequence tags were induced or repressed. The changes observed using cDNA arrays complement our previous findings using oligonucleotide arrays and include gene expression changes not previously noted (15). Our results establish that neutrophils actively regulate gene expression levels and suggest that, in addition to the well-known regulation of cytokine and chemokine expression, their exposure to infectious agents may modify several classes of genes. Furthermore, the gene expression profile of stimulated neutrophils provides a "fingerprint" of their activation state and information on intracellular signaling events. We believe these findings present a better understanding of the role neutrophils play in inflammation and immunity and provide evidence for molecular mechanisms of neutrophil function after exposure to LPS.


    METHODS
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ABSTRACT
INTRODUCTION
METHODS
RESULTS AND DISCUSSION
REFERENCES

Cell preparation and stimulation. Neutrophils were isolated from citrated blood from healthy donors and purified on a Percoll gradient, as described previously (20). Cells (25 × 106 cells/ml) were resuspended in RPMI containing 1% heat-inactivated platelet-poor plasma and 10 mM HEPES, pH 7.6, and divided into 1.5-ml tubes. Each condition for microarray analysis utilized 120 × 106 cells. Cells were stimulated with 100 ng/ml LPS (Escherichia coli 0111:B4; List Biological) and rotated continuously at 37°C for 4 h. For microarray analysis, nonstimulated and 4-h-treated cells were used from three separate donors. More detailed time courses after LPS exposure were performed for analysis by PCR and ELISA using 20 × 106 neutrophils.

Extraction of RNA and isolation of mRNA. Cell suspensions were centrifuged briefly, and cell supernatants were retained for analysis by ELISA. Cell pellets were solubilized in 0.5 ml of RNA Trizol (GIBCO) per 25 × 106 cells, and total RNA was extracted as described in the manufacturer's protocol. Briefly, 0.1 ml of chloroform was added to the Trizol suspension, shaken, incubated at room temperature for 10 min, and centrifuged for 15 min at 12,000 g. The aqueous upper phase was carefully removed, RNA was precipitated with 0.25 ml of isopropanol, and the precipitate was washed in 75% ethanol before being dried and resuspended in RNase-free water. RT-PCR was performed routinely to determine the integrity of RNA, the quiescence of neutrophils at baseline, and their responsiveness to LPS. Total RNA from each condition was pooled, and poly(A)RNA was obtained from these samples by Oligotex Mini Kit (Qiagen).

cDNA probe synthesis, hybridization to microarray, and scanning. A detailed account of hybridization of cDNA probes to microarray has been described previously in detail (24). Briefly, cDNA probes were generated by reverse transcription of mRNA (1 µg) with SuperScript II (GIBCO) in the presence of Cy3-dCTP or Cy5-dCTP (Amersham Pharmacia). Isolated single-strand cDNAs were denatured and incubated on duplicate arrayed slides in 30 ml 5× SSC, 0.1% SDS, 0.1 mg/ml salmon sperm DNA, and 50% formamide. The array was composed of 4,608 minimally redundant cDNAs from the UniGene set (24, 33). Labeled cDNA probes were allowed to hybridize overnight at 42°C in a humidified chamber. Slides were washed and dried before being scanned on the Avalanche dual-laser confocal scanner (Molecular Dynamics). Fluorescent intensities were quantified with ARRAYVISION 4.0 (Imaging Research, St. Catherine's, ON, Canada).

Data analysis. We normalized data for the individual experiments by dividing the fluorescence intensity (for both Cy3 and Cy5) of each element by the total fluorescence for each fluorophore. Ratios of the normalized values of LPS-stimulated (Cy3) to nonstimulated (Cy5) elements were calculated with Excel (Microsoft). We performed regression analysis (SigmaPlot) to determine the mean fluorescence ratio for the 4,608 elements. Significant changes in gene expression were taken as two standard deviations above the mean (induced) and less than one-half the mean (repressed). The average ratio for each element in the three experiments was calculated, and significant changes (P < 0.05) were determined by t-test. Data were deposited in the Gene Expression Omnibus database (http://www.ncbi.nlm.nih.gov/geo/) (accession numbers: GSM3033, GSM3034, GSM3035, GSM3038, GSM3039, GSM3040).

RT and PCR. cDNA was prepared by reverse transcription using 2 µg of total RNA. PCR was performed using specific primers for TNF-alpha (5'-AGCCCATGTTGTAGCAAACC-3', 5'-TTTGGGAAGGTTGGATGTTC-3'), MCP-1 (5'-TCTGTGCCTGCTGCTCATAGC-3', 5'-GGGTAGAACTGTGGTTCAAGAGG-3'), A1 (5'-GATGACTGACTGTGAATTTGG-3', 5'-TGGAGTGTCCTTTCTGGTCA-3'), Mx-1 (5'-TGTGCAGCCAGTATGAGGAG-3', 5'-CTCAGCTGGTCCTGGATCTC-3'), S100A4 (5'-TTCTTTCTTGGTTTGATCCT-3', 5'-CATCAGAGGAGTTTTCATTTC-3'), and GAPDH (5'-TCATCCATGACAACTTTGGTATCG-3', 5'-TGGCAGGTTTTTCTAGACGGC-3').

ELISA. Secretion of IL-1beta , MCP-1, macrophage inflammatory protein (MIP)-1alpha , and MIP-1beta was quantified by ELISA kits (R&D), using undiluted supernatant, as directed by the manufacturer.


    RESULTS AND DISCUSSION
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ABSTRACT
INTRODUCTION
METHODS
RESULTS AND DISCUSSION
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Human neutrophils were left untreated or incubated in the presence of 100 ng/ml LPS for 4 h. We used the 4-h time point in appreciation of the ability of LPS to inhibit spontaneous apoptosis and to explore the possibility that long-term changes in gene expression were important in neutrophil activation. Initially, to confirm that the neutrophils were not activated and that LPS resulted in normal stimulation, we performed PCR for TNF-alpha . Little TNF-alpha expression was seen in nonstimulated cells, whereas LPS treatment led to a significant increase in expression in each of the donors subsequently used for microarray analysis (data not shown; see Fig. 3A).

Microarrays were hybridized simultaneously with fluorescent cDNA probes derived from mRNAs of nonstimulated (Cy5-labeled) and LPS-stimulated (Cy3-labeled) neutrophils. A sample grid from one donor is shown in Fig. 1A. Predominately red spots indicate induction, green spots indicate repression, and yellow indicates no change in gene expression; areas of undetectable fluorescence indicate that the gene is not expressed or is expressed below the level of detection. The fluorescence intensities at each element were normalized to the total fluorescence for each fluorophore, and the ratio of stimulated to nonstimulated fluorescence was determined. The ratio for each element was subjected to regression analysis, and the mean fluorescence ratio for the entire set was determined. Furthermore, we searched cDNA arrays for monocyte markers to determine whether monocyte contamination would complicate the analysis. RNA for the macrophage-colony stimulatory factor receptor was not expressed in nonstimulated neutrophils, and CD14, which is expressed at higher levels in monocytes compared with neutrophils, was barely detectable. These observations are consistent with the low contamination (<5%) of monocytes when neutrophils are isolated (20).


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Fig. 1.   Changes in gene expression by LPS in neutrophils by microarray. Purified mRNA from neutrophils left untreated or treated with LPS (100 ng/ml) for 4 h were treated as described in METHODS and hybridized to a cDNA array. A: a sample quadrant of a microarray displaying changes in gene expression. Those genes predominately upregulated are stained bright red; downregulated genes are stained green; expressed gene that do not change are yellow; and underexpressed genes are stained lightly, or not at all. B: a scatter plot of the average fluorescence ratio from 3 experiments for each element. The average fluorescence ratio regression is shown as a white line (1.00 ± 0.51 SD). Ratios of >2 SD (top dashed line) above the mean are shown as red circles (induced); ratios of 1/2 the mean (bottom dashed line) are shown as green circles (repressed).

Reproducibility of genes induced by LPS in neutrophils. Because of the inherent variability of primary human cells, we wished to determine the reproducibility of changes detected on gene expression microarrays. Analysis of microarray data for each donor indicates that 36-48 nonredundant genes (average 40.0) were induced by greater than two standard deviations from the mean fluorescence ratio for the entire gene set as determined by regression analysis (Fig. 2A). We wished to compare the reproducibility of gene induction between any two experiments by comparing the number of common genes induced. When those genes upregulated by any two donors were assessed, 22-25 genes (average 23.7) were induced, corresponding to ~60% of the genes induced in each experiment. All three donors shared 18 upregulated genes (~45%). Therefore, microarray analysis conveys both the complexity of human genetic response and the potential to establish common events in primary human cells, since all three donors shared almost 50% of the induced changes. Although neutrophil preparations provide a highly purified cell population, the variability of the response may be explained by donor variability, previous activation state of the neutrophils, cell maturity, and differences in the time course of the response.


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Fig. 2.   Analysis of number and reproducibility of gene expression changes. A: induced genes. Open bars indicate the number of genes upregulated in each of 3 experiments (1, 2, or 3); hatched bars indicate the number of upregulated genes that are shared between the indicated experiments; mottled bars indicate the number of genes upregulated in all 3 experiments (1, 2, 3). The solid bar indicates the number of genes upregulated in the average of the 3 experiments. Genes whose ratio was >2 SD above the mean were taken as upregulated. B: repressed genes. Bars are as indicated as in A for genes downregulated in 3, or combinations of, experiments. Genes whose ratio was 1/2 the mean were taken as downregulated.

Reproducibility of genes repressed by LPS in neutrophils. The number and reproducibility of genes repressed by LPS treatment were also analyzed. The criterion for genes negatively regulated by LPS was a fluorescence ratio less than one-half of the average fluorescence ratio (Fig. 1B, green circles). The concordance for genes repressed among the individual donors, and between the individual and averaged experiment, was less than that for the induced genes. The three donors downregulated 49-68 genes (average 56.0), but any pair of individuals shared only 23, 24, and 25 (average 24.0) repressed genes (representing ~43% of the total in the individual experiments), and there were eight genes (~27%) shared by all three donors (Fig. 2B). When the average data were analyzed there were 18 genes determined to be repressed.1 Therefore, a greater variability in response was found with repressed genes, although several common changes were reproducibly observed.

The averages of the fluorescence ratios from the three experiments were determined. By this method, a fuller picture of changes in gene expression could be formed. However, the use of three donors may mask significant changes in some genes. Thus, the data presented here are conservative in their appraisal of LPS-regulated genes, and the list of genes provided likely includes only those genes whose regulation is most profound. Those genes whose ratios were, on average, greater than the threshold of two standard deviations of the average mean fluorescence (1.00 ± 0.51 SD) were further analyzed. A scatter plot of the average ratios for each of the 4,608 genes is shown in Fig. 1B. In all, 32 different gene products2 were found to be induced (Fig. 1B, red circles); redundant appearance of some genes on the array accounts for the 50 elements induced in Fig. 1B. Of the 32 genes upregulated, 24-27 genes (average 25.3, or 79%) were upregulated by each donor. Although some variability in array data was observed, we believe this is due largely to donor differences and is not inherent in the array analysis itself. In fact, the data described here are likely to represent robust changes in gene expression. Thus microarray analysis is a reproducible means of determining changes in gene expression in primary human neutrophils. Individual genes induced in LPS-stimulated neutrophils will be described below.

Genes differentially expressed in LPS-stimulated neutrophils: upregulated genes. Genes whose expression changed after LPS treatment were verified by sequencing, PCR, ELISA, or additional array experiments and were required to be significantly changed. As expected, the genes for several cytokines and chemokines were upregulated by LPS treatment of neutrophils. These include IL-1beta , IL-8, MIP-1alpha , and MIP-1beta (Table 1). Upregulation of these inflammatory mediators is well documented in neutrophils exposed to LPS and in animal models of LPS-induced sepsis syndrome and acute respiratory distress syndrome, a neutrophil-mediated illness (23, 44). PCR was performed to confirm and substantiate the results from the microarray analysis (Fig. 3A). Analysis of selected genes indicates that the time course for changes can be rapid or delayed but parallels the changes found in the array at the 4-h time point (Fig. 3A), thus confirming expression changes found using cDNA arrays. However, the possibility arises that transient changes in gene expression were missed because only the later time point was used. Secretion of IL-1beta , MIP-1alpha , and MIP-1beta were confirmed by ELISA (data not shown). Finally, mRNAs for IL-1 receptor antagonist (RA) and TSG-6, a known TNF-alpha -induced gene (28), were also induced in LPS-treated neutrophils.

                              
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Table 1.   Genes induced by 4 h of LPS treatment in human neutrophils



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Fig. 3.   Confirmation of changes observed in microarrays by PCR and ELISA. A: cDNA was made from total RNA from neutrophils stimulated for the indicated time with LPS (100 ng/ml). PCR was performed using specific primers for the indicated genes. MCP, monocyte chemoattractant protein. B: neutrophils were left untreated (NS) or stimulated for 4 h with LPS (LPS), and MCP-1 secretion into the supernatant was determined by ELISA; error bars indicate SE of 5 experiments.

In addition to the upregulation of known LPS-regulated cytokines and chemokines, cDNA microarray analysis detected an increase in the expression of MCP-1. The CC chemokine MCP-1 is an important monocyte chemoattractant. LPS-stimulated induction of MCP-1 in neutrophils is a novel finding and extends the number of chemokines regulated by neutrophils. RT-PCR analysis of LPS-stimulated cells confirmed the induction of MCP-1 RNA (Fig. 3A) and indicates that MCP-1 mRNA induction is delayed. To determine whether induction of MCP-1 RNA by LPS correlated with expression and secretion of MCP-1 protein, we performed an ELISA for MCP-1. Whereas nonstimulated neutrophils secrete little MCP-1, LPS-stimulated neutrophils secrete substantial MCP-1 protein (Fig. 3B). Therefore, the secretion of MCP-1 by stimulated neutrophils may provide a mechanism by which monocyte accumulation follows neutrophil accumulation. Yamashiro et al. (48) suggested that late-phase MCP-1 secretion in response to stimulated monocyte medium is dependent on TNF-alpha production. However, in our system, MCP-1 transcript expression is not inhibited by a p38 inhibitor (data not shown), a condition in which TNF-alpha secretion is eliminated (35). Overall, gene expression analysis of LPS-stimulated neutrophils identified both known and novel cytokines.

A well-described effect of LPS is its ability to inhibit spontaneous neutrophil apoptosis (27). Neutrophils readily undergo spontaneous apoptosis involving nuclear condensation, activation of caspase-3, and externalization of phosphatidylserine (14, 27, 38). Complete cell death can occur within 24 h, consistent with their short half-life in vivo. As LPS treatment inhibits spontaneous apoptosis, changes in gene expression indicated by microarray analysis may provide insights to explain cell survival in response to infection. Several of the genes identified by gene expression arrays that were induced by neutrophils after exposure to LPS have been implicated in the regulation of apoptosis, including A1, 14-3-3 eta, NF-kappa B components, and superoxide dismutase (SOD) 2. The upregulation of A1, a bcl-2-like protein that inhibits apoptosis (19, 46), was confirmed by PCR (Fig. 3A) and has been characterized previously in monocytes (29) and neutrophils (7). Likewise, 14-3-3 proteins, including the LPS-regulated gene 14-3-3 eta, bind to the proapoptotic bcl-2 homolog Bad (21) and suppress Bad-induced apoptosis. Furthermore, other genes upregulated by LPS, including NF-kappa B components and SOD2, have been implicated in antiapoptotic regulation (31, 47), although hypoxia-inducible factor (HIF)-1alpha has been implicated in hypoxia-induced apoptosis (5). Therefore, components of cell survival pathways are upregulated by LPS, and these gene products may be involved in maintaining neutrophil viability.

Genes implicated in cell cycle regulation were also induced. p19INK4d is an inhibitor of the cell cycle-dependent kinases cdk4/6, which control entry into S phase (17), although no evidence supports the expression of cdk4/6 in neutrophils; p19INK4d may maintain neutrophils in a quiescent state and limit their ability to undergo otherwise unproductive cell cycle events. Other investigators have observed high expression levels of another cdk inhibitor, p21CIP1/waf1, in neutrophils (13). Likewise, the products of the cot and BTG2 genes have been implicated in proliferative pathways (2, 40). The role of these cell cycle-associated gene products is unclear in postmitotic neutrophils but may involve the interaction of growth control and apoptotic signals (18, 36).

Interestingly, a number of transcriptional regulators were induced, including transcription factors of the NF-kappa B family. Induction of NF-kappa B genes was previously described in monocytes (10). This raises the possibility that LPS treatment changes the subsequent responsiveness to NF-kappa B-dependent stimuli by altering the levels or ratios of NF-kappa B components.

Other upregulated genes fall into three major categories: synthetic or metabolic enzymes, signaling molecules, and those with various functions (Table 1), some of which were discussed previously in the context of cell survival and apoptosis. Interestingly, two interferon-alpha /beta -regulated genes (Mx-1 and a 56-kDa protein) were detected; LPS-induced interferon-alpha /beta production has not been reported (50), and interferons or other interferon-regulated genes on the array were not significantly affected (data not shown). We have recently described the upregulation of interferon-regulated genes by LPS that is dependent on p38 kinase activity (15). Further study will be necessary to clarify the regulation of these genes. Three genes that have no defined function were also detected.

The activation of NF-kappa B by LPS through the TLR/MyD88/IRAK/IKK pathway has been recently described (1, 4, 34). NF-kappa B is the only transcriptional factor known to be regulated by LPS in neutrophils, and the transcriptional NF-kappa B complex has been implicated in the regulation of 10 of the 28 genes induced by LPS in this study. Among the neutrophil genes upregulated by LPS, NF-kappa B is implicated in the expression of IL-1beta , MIP-1alpha , MIP-1beta , IL-1RA, IL-8, MCP-1, NFKB1, NFKB2, A1, and SOD2 (8-10, 16, 26, 30, 37, 41, 43, 51). However, we have identified genes induced by LPS whose regulation is unknown or that is through non-NF-kappa B-dependent pathways (e.g., Mx-1 and ISG56). Therefore, gene expression profiling has identified potentially novel signaling pathways induced by LPS in neutrophils, and these studies indicate that transcriptional regulation of LPS-responsive genes represents an important area for future study.

Genes differentially expressed in LPS-stimulated neutrophils: downregulated genes. Genes downregulated by LPS again provide enticing information on neutrophil function in the face of infection. There were several genes whose products are structural in nature (e.g., alpha 2-actin, coronin, tubulin) (Table 2) and suggest that neutrophil motile response is repressed in the face of infection (45). The downregulation of Rho GDIbeta , involved in the regulation of the actin cytoskeleton, is also consistent with this suggestion, as are our data indicating upregulation of the adhesion molecule CD44 (Table 1). The calcium-binding protein S100A4, downregulated in LPS-treated neutrophils (Table 2), has been implicated in cell motility and metastasis (3). Furthermore, LPS is known to increase adhesion and cell rigidity and decrease chemotaxis (45). Thus gene expression array analysis has identified genes involved in cell motility and suggests a genetic basis for structural and motile changes induced by LPS. These findings complement the cell survival signals suggested previously to prolong neutrophil residency at sites of infection.

                              
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Table 2.   Genes repressed by 4 h of LPS treatment in human neutrophils

A recent publication described the gene expression changes by cDNA display of human neutrophils exposed to E. coli (42). Many of the expression changes found in LPS-stimulated neutrophils were also described in bacteria-exposed neutrophils, suggesting that the LPS model system accurately describes exposure of neutrophils to infection. These include the upregulated genes for BTG2, NFKB1, HIF-1alpha , IL-8, MIP-1alpha , MIP-1beta , CD44, and A1 and the downregulated genes for S100A9 and Rho GDIbeta . cDNA microarray analysis also identified the regulation of several genes without a known function. Furthermore, the concordance of gene expression in the two systems indicates that many of the gene expression changes seen in bacterial infection are mediated by TLR4, which is the major LPS-detecting receptor (1). We have described LPS-induced changes in neutrophil gene expression using a different array platform (15) and found many similar gene changes. Importantly, the gene coverage in the two systems is different, and as a result, unique changes were also observed. Together, a more comprehensive coverage of the human genome is obtainable. In addition, we find that the Affymetrix oligonucleotide arrays have a somewhat greater sensitivity than the cDNA arrays used here. This is due in part to the more robust analysis by the Affymetrix software compared with the conservative combination of a t-test with a cutoff of two standard deviations above the mean.

Analysis by cDNA array is a powerful tool to determine changes in gene expression; however, this type of analysis does not discriminate between de novo synthesis of RNA and stability of already present RNA species. Furthermore, changes in gene expression do not guarantee a concordant change in protein expression, although a parallel control of cytokine expression is well established. Our recent publication compared the gene expression and protein expression profiles in LPS-stimulated neutrophils (15); although some genes and proteins were concordantly expressed, poor correlation was observed, as described in other systems. Gene expression under the relatively simple system described here (a single stimulus and cell type) is most useful in describing isolated signaling pathways and suggesting novel functional responses.

Widespread regulation of numerous noncytokine/chemokine genes in neutrophils is a novel finding, as is the identification of MCP-1 as a neutrophil product. These data suggest that gene expression is an important mechanism by which neutrophils respond acutely to infection and help elucidate the biological consequences of LPS signaling in neutrophils. Although gene expression analysis by cDNA microarray does not distinguish between transcriptional regulation and mRNA stabilization or in the ultimate change in protein levels or posttranslational modifications of proteins, these results indicate the importance of gene expression in neutrophil activation and suggest signaling pathways activated by LPS.

The information from this study suggests several mechanisms involved in neutrophil activation. The alteration in components of the NF-kappa B and of other transcriptional regulators implies that one of the responses to LPS exposure is to modify subsequent nuclear signaling events. Another hypothesis derived from these observations is that downregulation of genes coding for proteins involved in cell motility affects cell function; this provides an explanation for the known ability of LPS to inhibit chemotaxis, although nongenetic responses are also recognized as significant to these functions. The upregulation of genes whose products are involved in cell survival and proliferation suggests mechanisms by which neutrophils exposed to LPS prolong viability at sites of infection. Of additional interest is the upregulation of B7-H1, a gene whose product is implicated in T cell activation (12). B7 family members CD80 and CD86 bind CD28 and enhance antigen-dependent T cell proliferation. B7-H1 is able to costimulate T cell proliferation in the presence of anti-CD3 (12). These observations suggest that activated neutrophils can modulate T cells function and support the interaction between the innate and adaptive immune systems.

This study highlights the importance of the regulation of gene expression in a model of infection and suggests genetic mechanisms for the biological effects of LPS on neutrophils; furthermore, these data indicate the activation of signal transduction systems previously not associated with LPS exposure. With the expanding identification of genes in the human genome and advances in microarray technology, the utility of gene expression profiling will grow. This study indicates that even with the screening of a limited number of genes, gene expression analysis will be a useful tool to characterize the response of specific cells to stimuli. In addition, these techniques could help identify potential genetic markers of neutrophil activation in infection and inflammation and possible targets to control or assist in the resolution of inflammation.


    FOOTNOTES

Address for reprint requests and other correspondence: K. C. Malcolm, National Jewish Medical and Research Center, 1400 Jackson St., Denver, CO 80206 (E-mail: malcolmk{at}njc.org).

1  We were unable to verify the sequence of one of these genes.

2  We were unable to verify the sequence of five of these genes.

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

First published December 20, 2002;10.1152/ajplung.00094.2002

Received 29 March 2002; accepted in final form 11 December 2002.


    REFERENCES
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ABSTRACT
INTRODUCTION
METHODS
RESULTS AND DISCUSSION
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