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Originally published online as doi:10.1189/jlb.0705421 on May 12, 2006

Published online before print May 12, 2006
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(Journal of Leukocyte Biology. 2006;80:164-173.)
© 2006 by Society for Leukocyte Biology

Comparative gene expression analysis of NKT cell subpopulations

Henry Lin*,1, Mie Nieda{dagger}, Jonathon F. Hutton{ddagger}, Vladislav Rozenkov* and Andrew J. Nicol*

* Department of Medicine, University of Queensland, Brisbane, Australia;
{dagger} School of Medicine, Yokohama City University, Japan; and
{ddagger} The Hematology and Oncology Program, CHRI, Adelaide, Australia

1 Correspondence: Centre for Immune and Targeted Therapy, Department of Medicine, University of Queensland, Greenslopes Private Hospital, Newdegate St., Greenslopes, QLD 4120, Australia. E-mail: hlin{at}soms.uq.edu.au or anic9909{at}bigpond.net.au


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Natural killer T (NKT) cells are a lymphocyte lineage, which has diverse immune regulatory activities in many disease settings. Most previous studies have investigated the functions of this family of cells as a single entity, but more recent evidence highlights the distinct functional and phenotypic properties of NKT cell subpopulations. It is likely that the diverse functions of NKT cells are regulated and coordinated by these different NKT subsets. Little is known about how NKT subsets differ in their interactions with the host. We have undertaken the first microarray analysis comparing the gene expression profiles of activated human NKT cell subpopulations, including CD8+ NKT cells, which have often been overlooked. We describe the significant gene expression differences among NKT cell subpopulations and some of the molecules likely to confer their distinct functional roles. Several genes not associated previously with NKT cells were shown to be expressed differentially in specific NKT cell subpopulations. Our findings provide new insights into the NKT cell family, which may direct further research toward better manipulation of NKT cells for therapeutic applications.

Key Words: human • microarray • {alpha}-galactosylceramide


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Natural killer T (NKT) cells are a unique lymphocyte lineage characterized by the expression of an invariant T cell receptor (V{alpha}24J{alpha}Q paired with Vß11 in human), which recognizes glycolipids presented by CD1d molecules. Upon stimulation, NKT cells have the ability to produce large amounts of T helper (Th)1 and Th2 cytokines [1 2 3 4 5 6 ]. The production of these cytokines by NKT cells has been demonstrated to play a significant role in a wide range of immune activities associated with malignancies, infections, and autoimmune diseases in mouse and human studies [7 8 9 10 11 12 13 ].

There are significant, functional differences between the effects of NKT cells in different situations. NKT cell activities can be beneficial [7 , 11 , 14 15 16 ] or detrimental [17 18 19 ] in different disease settings, resulting from Th1- or Th2-biased, immune activities. The diverse immune activities of NKT cells could result from differences between the regulation and tissue distribution (including in response to infection, inflammation, or malignancy) of the different NKT cell subpopulations. Subsets of human NKT cells have been characterized according to their expression of CD4 or CD8 surface molecules. Recent studies have highlighted the distinct Th1 and Th2 cytokine profiles of human NKT cell subpopulations [20 21 22 23 24 ]. The CD4+CD8– NKT cells (CD4 NKT cells) produce Th1 and Th2 cytokines [21 22 23 24 ], and the CD4– NKT cells produce predominantly Th1 cytokines [22 , 24 ]. The CD4– NKT cells can be divided further into CD4–CD8+ (CD8) and CD4–CD8– NKT cells {double-negative (DN) NKT cells [20 , 23 ]}. These two CD4– NKT cell subsets share similar cytokine profiles and were evaluated previously as a single family of cells rather than as distinct entities.

Interest in the potential to manipulate NKT cells for therapeutic purposes has increased since the demonstration that human NKT cells are stimulated, markedly expanded, and functionally altered, for example, resulting in secretion of large amounts of Th1 and Th2 cytokines [1 , 7 ], in response to the glycolipid {alpha}-galactosylceramide ({alpha}-GalCer) [3 , 5 , 25 , 26 ]. We have observed that {alpha}-GalCer ubiquitously activates all human NKT cell subsets (unpublished data). Depending on the extent to which NKT cell subpopulations differ, it is likely that nonselective activation of all NKT cells could result in unwanted immunological outcomes for the intended therapeutic use. For example, CD4 NKT cells have been shown to suppress antitumor response in mouse models [18 , 19 ], and activation of this NKT cell subset could be detrimental for antitumor therapy. We have shown previously that human NKT cell subpopulations can be expanded in vitro and that subpopulations of NKT cells can be manipulated by altering the cytokine environment upon which NKT cells are stimulated [27 ]. A greater understanding of the differences among human NKT cell subpopulations than currently available is necessary to optimize the potential for therapeutic benefit to be derived from NKT cell manipulation.

Microarray technology can be used to compare thousands of genes among cell populations and represents a useful tool to screen for previously unknown or undetected biological differences among NKT cell subpopulations. In this study, we compared the gene expression patterns of activated human NKT cell subpopulations, including the CD4, CD8, and DN NKT cells, to identify key, important genes expressed differentially among NKT cell subpopulations. The data described here are valuable for future research of NKT cells and will provide important insight for the design of therapies tailoring the potential of NKT cell subpopulations.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Study population
The Australian Red Cross Blood Service collected peripheral blood with informed consent from four healthy donors. Blood from one donor was used to generate allogenic monocyte-derived dendritic cells (Mo-DC). To obtain sufficient NKT cells, donors were chosen selectively based on their having peripheral blood NKT cell levels greater than 0.03% of all T cells. The Human Research Ethics Committee of the Royal Brisbane Hospital and the Queensland Institute of Medical Research Human Research (Brisbane, Australia) approved the study.

Antibodies used in flow cytometry
The flurochrome-conjugated monoclonal antibodies (mAb) used in flow cytometry included fluorescein isothiocyanate-labeled antibodies against V{alpha}24, CD3, CD19, CD72, CD1d 42.1, and interferon-{gamma} (IFN-{gamma}); phycoerythrin (PE)-labeled antibodies against Vß11, CD3, CD16, CD40, CD86, interleukin (IL)-4, CC chemokine ligand 7 (CCL7), NKG2C, and NKG2D; PE-cyanine 5-labeled antibodies against CD3, CD8, and CD14; and Texas Red ethyl cysteinate dimer-labeled streptavidine and antibodies against CD4, biotinylated Vß11, and the relevant isotype controls.

Isolation of peripheral blood mononuclear cells (PBMC) and generation of NKT cell lines
PBMC were obtained by density gradient centrifugation using Ficoll Paque Plus (Amersham Biosciences, UK). For expansion of NKT cells, PBMC were cultured in complete media containing AIM-V medium (Gibco-BRL, Grand Island, NY) supplemented with 10% of fetal calf serum (JRH Biosciences, Lenexa, KS), 100 ng/ml {alpha}-GalCer (Pharmaceutical Division, Kirin Brewery, Tokyo, Japan), and 10 ng/ml each IL-7 and IL-15 (R&D Systems, Minneapolis, MN) for 7 days. On Day 7, purified NKT cells were obtained by positive magnetic sorting of V{alpha}24+ cells using V{alpha}24 mAb (Beckman Coulter, Fullerton, CA) and rat anti-mouse immunoglobulin G 1 microbeads (Miltenyi Biotec, Auburn, CA). The purity of the NKT cells obtained after magnetic sorting was confirmed using antibodies against V{alpha}24, Vß11, and CD3. Further expansion of NKT cells was achieved by stimulating the purified NKT cells with {alpha}-GalCer-pulsed, allogenic Mo-DC at a NKT:DC ratio of 10:1 for 7 days. Allogenic Mo-DC were obtained from PBMC of a normal donor by 1-h adherence in a tissue-culture flask to deplete lymphocytes, followed by culture of the adhered monocytes in complete media with 500 U/ml human recombinant (hr)IL-4 (R&D Systems) and 400 U/ml hr granulocyte macrophage-colony stimulating factor (CSF; Schering-Plough, Kenilworth, NJ) for 5 days. On Day 4, 100 ng/ml {alpha}-GalCer was added to the culture for specific stimulation of NKT cells. The Mo-DC were identified as lineage-negative cells using antibodies against CD3, CD19, and CD14 (Beckman Coulter). The phenotypes of the Mo-DC were assessed using antibodies against CD1d (a gift from Dr. Stephen Porcelli, Albert Einstein College of Medicine, Bronx, NY), CD40, and CD86 (all from Beckman Coulter). The allogenic Mo-DC were irradiated at 3000 rads before use. On Day 7, following stimulation of NKT cells with allogenic Mo-DC, subpopulations of NKT cells were isolated by flow cytometric cell sorting using the MoFlo flow sorter (DakoCytomation, Denmark) with antibodies against CD4 and CD8 (all from Beckman Coulter). Three NKT cell subpopulations, CD4+CD8–, CD4–CD8+, and CD4–CD8– NKT cells, were isolated.

Cytokine profiles of NKT cell subpopulations
Intracellular IFN-{gamma} and IL-4 expression of NKT cell subpopulations were assessed on the flow cytometer (FC500, Beckman Coulter) using isolated NKT cells after positive magnetic sorting. Briefly, purified NKT cells were labeled with antibodies against CD4 and CD8 and then fixed and permeabilized using the IntraPrep permeabilization reagent kit (Beckman Coulter), according to the manufacturer’s specifications. The permeabilized cells were labeled with antibodies against IFN-{gamma} and IL-4 (Beckman Coulter) and then analyzed on the flow cytometer.

RNA extraction
Total cellular RNA from three different donors was isolated from the purified NKT cell subpopulations using RNeasy Mini Prep kit (Qiagen, Valencia, CA), per the manufacturer’s instructions, and then used in separate microarray experiments. The quality of the total RNA was verified by 1% Tris-acetate EDTA agarose gel electrophoresis. RNA concentrations and purity were assessed spectrophotometrically (Thermospectronics, Rochester, NY).

RNA amplification and labeling
Amplified and Cy-dye-labeled RNA was obtained using the amino allyl MessageAmp aRNA kit, according to the manufacturer’s specifications. Briefly, a minimum of 2 µg RNA was reverse-transcribed to cDNA and then subjected to in vitro transcription in the presence of the modified nucleotide, 5-(3-aminoallyl)-uridine 5'-triphosphate to allow chemical coupling of the Cy-dyes. The aRNA was labeled with Cy3 or Cy5 monoreactive dye in duplicate with a dye swap (Amersham Biosciences) and then purified before hybridization with the microarray chip.

Hybridization and washing
Samples from three different donors were hybridized to the microarray chips separately in duplicate experiments with dye labels alternated (i.e., dye-swap experiments). The dye-swap experiments help to compensate signal correlation bias of the Cy3 and Cy5 dye pairs. Before hybridization, the volume of the probes (labeled aRNA) was reduced and then combined with 4x saline sodium citrate (SSC), 50% deionizer formamide, and 0.5% sodium dodecyl sulfate (SDS). The mixed solution was then heated at 95°C for 5 min and incubated at 45°C for 60 min. The probe-hybridization mixture was cooled and then placed over a glass microarray slide. The microarray chips were made in-house and obtained from the Queensland Institute of Medical Research. The microarray chip contained 4608 genes, which were spotted in duplicates on the same slide. The microarray slide was covered with a coverslip and then incubated at 45°C for 16 h. The microarray slides were washed for 3 min in 0.2x SSC and 0.05% SDS solutions at 37°C and then dried by centrifugation.

Image analysis
The microarray slides were scanned using a GMS-418 confocal scanner (Genetic MicroSystems, Woburn, MA). Care was taken to ensure that a majority of the signals was within the linear detection range of the instrument, as determined by the pseudo-coloring of the signal intensities. Images were generated for Cy3 and Cy5 signals and then imported into Imagene 5.5 (BioDiscovery, El Segundo, CA). The mean signal pixel intensities were determined after subtracting the individual mean signal backgrounds. Spots with poor/absent signal were flagged at this stage before further analysis.

Data analysis
The image files containing the Cy3 or Cy5 signals were combined into a single file using Microsoft Excel (Microsoft, Redmond, WA). Two files were generated from the microarray experiments. The first file contained gene expression data for the Cy3-labeled sample and the Cy5-labeled reference. The second file contained data for the duplicated experiment with the dye-swap, which contained the Cy5-labeled sample and the Cy3-labeled reference. These image data files were then imported into GeneSpring 6.2 (Silicon Genetics, Redwood City, CA) and normalized by Lowes intensity normalization procedure. The data were filtered to remove all genes that did not have at least one good spot (containing data) or a mean pixel intensity of at least 200. A ratio-to-ratio plot was generated using the data files of the duplicated experiments (e.g., Cy3-A-Cy5-B vs. Cy3-B-Cy5-A). Those genes that showed at least twofold gene expression changes in at least two out of three samples analyzed defined differential gene expression. Similar gene expression levels refer to those genes that showed less than a twofold increase or decrease in at least two out of three samples analyzed. A list of genes that displayed differential gene expression levels among NKT cell subpopulations was generated using the Venn diagram. To supplement the computer-generated microarray data, genes that showed similar expression levels but important for immune regulatory functions such as cytokines, chemokines, and adhesion molecules were manually examined. The data were interpreted using the Expression Analysis Systematic Explorer software and annotation tools provided by database for Annotation, Visualization and Integrated Discovery [28 ].

Quantitative polymerase chain reaction (QPCR)
QPCR was performed on selected genes to confirm the validity of the microarray data. RNA was treated with DNase I (Ambion, Austin, TX), reverse-transcribed using Moloney murine leukemia virus reverse transcriptase (Qiagen) and random octamer primer (Geneworks, Hindmarsh, SA, Australia), and then quantitated by real-time PCR using Taq polymerase (Amplitaq Gold, Applied Biosystems, Foster City, CA) with the addition of SYBR Green (Molecular Probes, Eugene, OR) on a Rotorgene 2000 thermal cycler (Corbett Research, Mortlake, NSW, Australia). Quantitation and statistical analysis of results were performed according to ref. [29 ]. Primers were designed with a melting temperature of ~65°C as follows: cyclophilin-A (5'-GGTTGGATGGCAAGCATGTG-3' and 3'-TGCTGGTCTTGCCATTCCTG-5'), CXC 3 chemokine receptor 1 (CX3CR1; 5'-CCCTGAATCAGTGACAGAAAACT-3' and 3'-ACGGAGTAGAATATGGACAGGAA-5'), colony stimulating factor (CSF-1) (5'-GCGAGCAGGAGTATCACCG-3' and 3'-AGGTCTCCATCTGACTGTCAAT-5'), signal transducer and activator of transcription (STAT)4 (5'-TGGAAATTCGGCATCTGTTGG-3' and 3'-GGAAACACGACCTAACTGTTCAT-5'), CD16 (5'-CCTCCTGTCTAGTCGGTTTGG-3' and 3'-TCGAGCACCCTGTACCATTGA-5'), Killer cell lectin-like receptor subfamily K, member 1 (KLRK1) (5'-CCTTGACCGAAAGTTACTGTGG-3' and 3'-GGCTGGCATTTTGAGACATACAA-5'), natural cytotoxicity triggering receptor 3 (NCR3; 5'-CTTGCTTCTTCCCGTTTCCTC-3' and 3'-ATTCCCTGTCCCGACACCAA-5'); STAT5B (5'-GAACACCCGCAATGATTACAGT-3' and 3'-ACGGTCTGACCTCTTAATTCGT-5'), death-associated protein 6 (DAXX; 5'-GCGGAGTTCTGCAACATC-3' and 3'-AGGTGTGTGGGAGGGTTATTC-5'), Killer cell lectin-like receptor subfamily C, member 2 (KLRC2) (5'-GCCAGCATTTTACCTTCCTCA-3' and 3'-ACTGCACAGTTAAGTTCAGCAT-5'), Bradykinin receptor B2 (BDKRB2; 5'-GTCTGTTCGTGAGGACTCCG-3' and 3'-CTGGGCAAAGGTCCCGTTAAG-5') ; CC chemokine receptor 6 (CCR6; 5'-GGGGAATCAATGAATTTCAGCGA-3' and 3'-CGGTACAAATAGCCTGGAGAAC-5'), CD72 (5'-TCCTCCTACCGGGTTCTCC-3' and 3'-AGCACCATGACTTGCCCTG-5'), chemokine ligand 7 (CCL7) (5'-CGGGAAGCTGTAATCTTCAAGAC-3' and 3'-AACCACTCTGAGAAAGGACAGG-5'). PCR reactions were cycled at 60°C for 10 min followed by 38 cycles of 72°C for 30 s, 60°C for 30 s, and 95°C for 30 s. PCR products were analyzed by melt curve and run on ethidium agarose gels to ascertain specificity.

Confirmation of microarray data by flow cytometry
To confirm the validity of the microarray data at protein level, flow cytometric analysis of NKT cell subpopulations was performed using selected mAb. Purified NKT cells were labeled with antibodies against CD4 and CD8 (all from Beckman Coulter) to identify the specific NKT cell subpopulations, and the expression of other surface molecules was assessed using antibodies against CD72 (Chemicon, El Segundo, CA), CCL7 (BD Biosciences, San Jose, CA), NKG2C (R&D Systems), NKG2D (R&D Systems), and CD16 (Miltenyi Biotec). Cells were analyzed by four-color flow cytometry (FC500, Cytomics, France).

Statistical analysis
Statistical analyses were performed using Student’s t-tests. P < 0.05 was considered significant.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Characteristics and quality of NKT cells before microarray experiments
Stimulation of PBMC with {alpha}-GalCer, IL-7, and IL-15 resulted in a 50- to 400-fold expansion of NKT cells after 7 days culture. NKT cells were first isolated by positive magnetic sorting (Fig. 1A ) and then stimulated for a further 7 days to obtain a minimum of 1 x 108 cells for subsequent isolation of NKT cell subpopulations. Three NKT cell subpopulations (CD4, CD8, and DN NKT cells) were obtained from each of the three donors, and the purity of these cells was greater than 95% (Fig. 1B) . Assessment of the cytokine expression profiles of the NKT cell subpopulations showed that all cells expressed IFN-{gamma}, and the CD4 NKT cells were the only NKT cell subset that expressed significant levels of IL-4 (Fig. 1C) . These observations were consistent with previous studies [20 21 22 23 24 ]. Using the highly purified NKT cell subpopulations, we were able to extract sufficient RNA templates for microarray studies. The quality of the RNA is shown in Figure 1D .


Figure 1
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  		Figure 1. Characteristics and quality of NKT cells before microarray analysis. (A) Purity of NKT cells after positive magnetic selection of V{alpha}24+ cells. The purified cells were stained with V{alpha}24, Vß11, and CD3 antibodies. NKT cells were gated through CD3, and the percentage of V{alpha}24+Vß11+CD3+ cells was shown. All purified NKT cells used in this study had a purity of >95%. (B) Representative plots showing the purity of NKT cell subpopulations after flow sorting. Microarray analyses were undertaken on these three cell populations (CD4+CD8–, CD4–CD8+, and CD4–CD8– DN NKT cells). All NKT cell subpopulations used in this study had a purity of >95%. (C) Representative plots showing the cytokine profiles of NKT cell subpopulations. CD4 NKT cells produce IFN-{gamma} and IL-4, and CD8 and DN NKT cells produce predominantly IFN-{gamma}. (D) Representative figure of gel electrophoresis of the extracted RNA from the NKT cell subpopulations specified. The visibility of the strong 28S rRNA and the weaker 18S rRNA bands is a feature of intact RNA. These RNA also have a A260:A280 ratio between 1.9 and 2.1, demonstrating high purity of the extracted RNA.

 
Gene expression pattern of cytokine receptors, chemokine receptors, chemokines, and adhesion molecules of NKT cell subpopulations
Analysis of a range of genes involved in immune regulatory functions, including cytokines, chemokines, and adhesion molecules, showed that among the 28 genes in these function groups included in the study, three genes were expressed differentially, 10 genes were similarly expressed, and the remaining 15 genes showed inconsistent or insignificant gene expression levels among NKT cell subpopulations (Supplemental Table 1). The three genes encoding for chemokine receptors and chemokines differentially expressed among NKT cell subpopulations are CCR6, CX3CR1, and CCL7. Genes encoding for cytokine receptors IL-2 receptor ß (IL-2Rß), IL-10R{alpha}, and IL-10Rß; CCR1 and CCR2; CCL3, CCL4, and CCL5; and adhesion molecules intercellular adhesion molecule 2 (ICAM-2) and ICAM-3 were expressed similarly among NKT cell subpopulations. Genes that showed inconsistent or insignificant gene expression levels among NKT cell subpopulations will not be discussed.

Genes differentially expressed among NKT cell subpopulations
Among the 4608 genes analyzed, 75 genes between CD4 and CD8 NKT cells, 95 genes between CD8 and DN NKT cells, and 104 genes between CD4 and DN NKT cells were expressed differentially. Supplemental Tables 2–4 show the complete list of these genes in their functional categories. Genes with multiple functions are included in multiple, functional categories. We selected several genes of particular interest from the microarray data for further evaluation. These genes were up-regulated differentially in the NKT cell subpopulations specified (Supplemental Table 5). The genes of interest up-regulated in the CD4 NKT cells included the BDKRB2 and CSF-1. In the CD8 NKT cells, these included CD16, NKG2C, NKG2D, CX3CR1, CCL7, STAT4, STAT5B, and CD72. Genes of particular interest up-regulated in the DN NKT cells included the NCR3, CCR6, and the DAXX.

Confirmation of microarray data
The expression differences of the selected genes of interest (as shown in Supplemental Table 5) among NKT cell subpopulations were confirmed by QPCR (Fig. 2 ). In all cases, the gene expression differences among NKT cell subsets were statistically significant (P<0.05, n=3). In the 13 genes analyzed, the microarray data correlated well with the QPCR results (Fig. 2) . To investigate the identified gene expression differences among NKT cell subpopulations at protein level, assessment of surface expression of NKG2D, NKG2C, CD72, CCL7, CCR6, and CD16 was performed by flow cytometry. Consistent with the microarray data, the expression of NKG2D, NKG2C, CD72, and CCL7 was highest in CD8 NKT cells compared with other NKT cell subsets, and the expression of CCR6 on DN NKT cells was higher than CD4 NKT cells (Fig. 3 ). The expression of CD16 on NKT cells was undetectable by flow cytometry. The signal intensity of CD16 detected on microarray and QPCR was considerably lower than other molecules such as the NKG2D (data not shown). This may explain the lack of surface expression of this molecule on NKT cells. Taken together, the results here suggest that the microarray data are reliable and correlated well with the QPCR results, and in most cases, the gene expression differences identified among NKT cell subpopulations were also observed at protein level.


Figure 2
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  		Figure 2. Comparison of the gene expression differences between NKT cell subpopulations assessed by microarray and QPCR. Comparison of the gene expression differences between NKT cell subpopulations determined by microarray (open bars) and QPCR analyses (solid bars). (A) Genes up-regulated in CD4 NKT cells; (B) genes up-regulated in CD8 NKT cells; (C) genes up-regulated in DN NKT cells relative to other NKT cell subsets as indicated.

 

Figure 3
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  		Figure 3. The expression of NKG2D, NKG2C, CD72, CCL7, and CCR6 on NKT cell subpopulations. Representative flow cytometry histograms showing the expression of NKG2D, NKG2C, CD72, CCL7, and CCR6 on NKT cell subpopulations. Purified NKT cells were labeled with CD4, CD8, NKG2D, NKG2C, CD72, CCL7, and CCR6 mAb. NKT cell subpopulations were identified by the presence or absence of coexpression of CD4 and/or CD8 surface molecules. The expression of various proteins indicated on unsorted NKT cells was shown with the relevant isotype control-stained NKT cells. Comparisons of the expression levels of these proteins among NKT cell subpopulations were shown in the overlay plots. The CD8 NKT cells showed the highest expression of NKG2D, NKG2C, CD72, and CCL7 (A–D). The DN NKT cells showed greater expression of CCR6 compared with CD4 NKT cells (E). These results were consistent with those observed in the microarray analysis.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
In the past, it has been difficult to isolate sufficient NKT cells required for gene expression studies because of their extremely low frequencies in human tissues (often less than 0.1% of total T cells in the peripheral blood [22 , 30 , 31 ]). In this study, we used {alpha}-GalCer stimulation as a method to obtain large numbers of NKT cells from human peripheral blood. There may be some differences in the functions of NKT cells in different tissue sites; however, this has remained largely uninvestigated because of the technical difficulties to obtain human NKT cells from other tissues. The use of synthetic glycolipid in this study may not completely reflect the physiological functions of NKT cells, as the natural ligands for human NKT cells have not been fully elucidated. Nevertheless, the data provided here might be more relevant in therapeutic settings that involve {alpha}-GalCer-activated NKT cells.

Our results reveal a number of genes differentially expressed among the three major human NKT cell subsets. As was expected, we also demonstrated many similarities among the subpopulations, particularly in gene expression levels of cytokine receptors, chemokine receptors, chemokines, and adhesion molecules.

NKT cell subpopulations share similar expression patterns of many cytokine receptors, chemokines receptors, chemokines, and adhesion molecules
Cytokine receptors
Similar gene expression levels were found for cytokine receptors IL-10R{alpha}, IL-10Rß, and IL-2Rß in all NKT cell subpopulations (Supplemental Table 1). Surface expression level of IL-2Rß has previously been shown to be similar between CD4 and CD8 NKT cells, although the expression levels of IL-2Rß on DN NKT cells were not examined [22 ]. In contrast, the expression of IL-10Rs on NKT cells has not been examined previously, and the data here suggest that all NKT cell subsets may be equally responsive to IL-10.

Chemokine receptors
Among the chemokine receptors analyzed, the expression of CCR1 and CCR2 was similar among NKT cell subpopulations. Both of these receptors are expressed in immune cells that migrate and infiltrate the site of inflammation [28 ]. The surface expression of CCR1 and CCR2 on NKT cells has been documented previously, showing different expression patterns among NKT cell subsets [30 , 32 ]. The differences between our data and these studies may be related to the biological differences of the stimulated NKT cells used in this study and the nonstimulated NKT cells analyzed in other studies.

Chemokines
This is the first study documenting the similar expression pattern of chemokines CCL3, CCL4, and CCL5 on all NKT cell subpopulations. These chemokines have inflammatory and chemokinetic properties and function as chemoattractants for monocytes, DC, and T cells involved in inflammatory processes [28 ]. It is important that CCL3 and CCL4 are ligands for CCR1 and CCR5, the chemokine receptors that have been observed previously on NKT cells [30 , 32 ]. It will be interesting to investigate the role of these chemokines and chemokine receptors in the trafficking of specific NKT cell subpopulations to the site of inflammation.

Adhesion molecules
The expression level of adhesion molecules ICAM-2 and ICAM-3 was similar among NKT cell subpopulations (Supplemental Table 1). ICAM-2 and ICAM-3 are adhesion molecules that bind to the leukocyte adhesion lymphocyte function-associated antigen-1 protein. They mediate adhesive interactions important for antigen-specific immune responses, NK cell-mediated clearance, lymphocyte recirculation, and other cellular interactions [28 ]. The data here suggest that human NKT cell subpopulations have the ability to interact with other effector cells via direct cell-to-cell contact through ICAM-2 and ICAM-3 in addition to the cytokinetic pathways described previously [33 ].

CD4 NKT cells show up-regulated expression of BDKRB2
BDKRB2 is a receptor that mediates bronchoconstriction in asthma [34 ]. A previous study has reported the role of mouse NKT cells in potentiating airway hyper-reactivity (AHR), which results in asthmatic bronchoconstriction [35 ]. It was not confirmed whether specific NKT cell subpopulation(s) may be responsible in these activities. The microarray data here postulate that the observed action of NKT cells in AHR may be facilitated by the response of CD4 NKT cells to bradykinin.

CD4 NKT cells show up-regulated expression of CSF-1
Expression of CSF-1 transcript has been shown previously in T cells [36 ], but no studies have reported its expression in NKT cells. CSF-1 controls the function of macrophages and monocytes and can also induce production of other immunoregulatory cytokines that indirectly regulate various T cell immune responses [36 ]. Previous mouse studies have demonstrated the role of NKT cells in regulating T cell immune responses through CD1d and CD40-CD40 ligand interactions with DC [37 38 39 ]. Our results suggest that up-regulated expression of CSF-1 in CD4 NKT cells may provide an additional mechanism through which human NKT cells can regulate other immune cells.

CD8 NKT cells show up-regulated expression of cytotoxic cell-associated receptors CD16, NKG2C, and NKG2D
It is known that CD16 is expressed primarily on NK cells; however, some studies have reported the expression of CD16 on a low percentage of T cells, which possess functions similar to NK and T cells [40 , 41 ]. Surface expression of CD16 on NKT cells was not detected in our study, and it remains to be investigated whether the expression of this molecule can be induced, especially on CD8 NKT cells, before its functional significance can be evaluated.

The expression of NKG2C has been observed in cytotoxic T cells [42 , 43 ] and activated NK cells [44 ] but has never been investigated in NKT cells. In contrast, the expression of NKG2D has been documented in mouse [45 ] and human NKT cells [22 ], and the human study shows higher expression of NKG2D in CD4– NKT cells compared with CD4+ NKT cells [22 ]. Our data extend these observations and show that NKG2C and NKG2D are up-regulated differentially in CD8 NKT cells in comparison with other NKT cell subsets. The NKG2C and NKG2D are involved in mediating the cytolytic function of effector cells such as T and NK cells [41 , 42 , 44 ]. Up-regulated expression of these receptors in CD8 NKT cells suggests that this NKT cell subset has biological functions resembling those of cytotoxic effector cells.

CD8 NKT cells show up-regulated expression of chemokines CX3CR1 and CCL7
The chemokine receptor CX3CR1 is expressed in terminally differentiated Th1 T cells and highly expressed in CD8+ T cells [46 ]. A previous report showed CX3CR1 expression at low levels on CD4 and DN NKT cells but the expression level of this receptor on CD8 NKT cells was not examined [32 ].

The data here show that CD8 NKT cells have higher expression of the chemokine CCL7 in comparison with other NKT cell subsets. This chemokine is chemotactic for T lymphocytes and can attract monocytes, macrophages, and neutrophils [47 , 48 ]. Expression of CCL7 on NKT cells has never been reported. It is unclear why CD8 NKT cells show up-regulated CCL7 expression but not other chemokines in the same family (CCL3, CCL4, and CCL5), which are similarly expressed in all NKT cell subpopulations.

CD8 NKT cells show up-regulated expression of signal transducers STAT4 and STAT5B
The up-regulated expression of STAT4 in CD8 NKT cells observed here is consistent with a recent microarray study reporting the overexpression of STAT4 in IL-4 null NKT cell clones, which included the CD8 NKT cells [49 ]. STAT4 is essential for all biological functions of IL-12, including differentiation into Th1 cells, IFN-{gamma} production, and NK cell cytotoxicity [50 , 51 ]. STAT5B is expressed in T cells [52 ], regulates NK cell activity [53 ], and has a role in human immunodeficiency virus infection [52 ] and immune response in malignancy [54 ]. NKT cells have been shown to participate in these biological events [7 , 31 , 55 56 57 ]. Our results suggest that the CD8 NKT cell subpopulation may play the greatest role in these activities through STAT4- and STAT5B-mediated pathways

CD8 NKT cells show up-regulated expression of CD72
An unexpected finding of the microarray data was expression and up-regulation of the CD72 antigen on CD8 NKT cells. This was confirmed by flow cytometry at the protein level (Fig. 3) . The expression of CD72 was previously thought to be restricted in the B cell lineage responsible for the differentiation and proliferation of B cells; however, one report has described the expression of CD72 on mouse T cells [58 ]. It has been shown that CD72 is a natural ligand for CD5, a glycoprotein expressed on all mature T lymphocytes, and a subpopulation of B cells [59 , 60 ]. The CD72-CD5 interactions provide positive signals for activation and proliferation of T and B cells [60 ]. In several mouse studies, NKT cells have been demonstrated to activate T and B cells in a cytokine-dependent manner [61 62 63 64 ]. In humans, B cells can also be activated by NKT cells in a CD1d-dependent manner [65 ]. Clinically, secondary activation of T and B cells was observed after stimulation of NKT cells, although the precise mechanisms involved were unclear [66 ]. The expression of CD72 on NKT cells, in particular, the CD8 NKT cell subset, suggests a previously unidentified contact-dependent pathway of T and B cell activation by NKT cells.

DN NKT cells show up-regulated expression of NCR3
NCR3 is a human NK cell receptor involved directly in the natural cytotoxic functions of NK cells including antitumor responses [67 ]. This receptor is also responsible for the recognition and killing of DC for generation of optimal cytotoxic T lymphocyte responses [44 ]. The data shown here are of particular interest in view of a previous study demonstrating the cytotoxic activity of DN NKT cells against DC [68 ]. Our data suggest that the expression of NCR3 may be an additional mechanism through which the cytotoxic actions of DN NKT cells modulate the functions of DC. As it is unknown whether CD4 and CD8 NKT cells also have cytotoxicity against DC, we cannot be certain whether the up-regulation of NCR3 on DN NKT relates to an immune-regulatory role specific to this subpopulation.

DN NKT cells show up-regulated expression of CCR6
Expression of CCR6 has been shown by flow cytometry on human NKT cells [24 , 30 , 32 ]. Our study is in agreement with these studies demonstrating elevated CCR6 surface expression on DN NKT cells compared with CD4 NKT cells. The chemokine receptor CCR6 is associated with the regulation of DC and T cells during inflammation [30 , 32 ]. They are commonly expressed by T cells with the potential to home to nonlymphoid tissues. A ligand for CCR6, known as liver and activation-regulated chemokine, is expressed mainly in the human liver [69 ]. Of particular interest, human hepatic NKT cells showed greater frequencies of the DN NKT cell subset than the CD4 NKT cells [70 ]. It is possible that the relative abundance of the DN NKT cells in the liver was attributed to their up-regulated expression of CCR6.

DN NKT cells show up-regulated expression of DAXX
DAXX is a protein that binds to Fas and enhances Fas-induced apoptosis in the cytoplasm of target cells [71 , 72 ]. Higher expression of DAXX on DN NKT cells suggests that this NKT cell subset may be more susceptible to Fas-induced apoptosis compared with other NKT cell subsets during immune regulation. However, as DAXX acts downstream of Fas activation [71 ], it remains to be determined whether the DN NKT cells also show up-regulated expression of Fas.

Significance of gene expression differences between CD8 and DN NKT cell subpopulations
Previously, human CD8 and DN NKT cells have been examined as a single group of cells as a result of the similarities in their cytokine expression profiles and difficulties evaluating CD8 NKT cells because of their low numbers [27 , 73 ]. This is the first study examining the gene expression patterns of CD8 NKT cells, and it demonstrates that there are significant gene expression differences between CD8 NKT cells and other NKT cell subpopulations. CD8 NKT cells showed higher expression of genes encoding for several receptors (i.e., CD16, NKG2C, NKG2D) characteristically found on cells with cytolytic effector function (such as NK cells). In addition, the CD8 NKT cells expressed signal transducers STAT4 and STAT5B, important for Th1 immune activities and CX3CR1 (expressed on Th1 cells). Our data suggest that CD8 NKT cells are a significantly Th1-biased cytotoxic effector cell population. Although DN NKT cells also expressed receptors associated with cytolytic function (NCR3), their coexpression of CCR6 suggests they have additional roles in regulating T cell and DC responses, possibly in extranodal sites. Furthermore, the expression of NCR3 on DN NKT cells implies that the regulatory activities of these cells may involve direct elimination of DC, as has been proposed previously [68 ]. Previous studies on the cytokine profiles of human NKT cell subpopulations provided strong evidences that CD4– NKT cell subsets are significantly biased toward Th1 function [20 21 22 23 24 ]. Our study is the first to delineate differences between the two CD4– NKT cell subsets and confirms that these two NKT cell subpopulations are functionally distinct.

This report summarizes the first available microarray data demonstrating similarities and differences in gene expression among the three major CD1d-restricted human NKT cell subpopulations, including the rare CD8 NKT cells. Our data confirm similarities among all NKT cell subpopulations for certain cytokine receptors, chemokine receptors, chemokines, and adhesion molecules. Our study also identified significant gene expression differences among NKT cell subpopulations. The gene expression patterns of CD8 NKT cells differ significantly from other NKT cell subsets and suggest that this NKT cell subset represents a Th1-biased cytotoxic effector cell population. Future functional studies based on the microarray, especially on the genes not previously known to be expressed by NKT cells (e.g., BDKRB2, CSF-1, CCL7, CD72, STAT4, STA5B, DAXX, and NCR3 receptors), will enhance our capacity to manipulate NKT cells for therapeutic benefits.

Received July 29, 2005; revised February 28, 2006; accepted March 17, 2006.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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