Mol Cell Toxicol (2012) 8:139-148DOI 10.1007/s13273-012-0017-5

Abstract Microglia constitutes the first line of de-fense against infection and injury in the brain. We pre-viously demonstrated that activated microglia expressthe Foxp3 gene. However, the role of Foxp3 in cellsother than Treg is generally unknown. Therefore, thisstudy was conducted to determine the effects of Foxp3in LPS-induced activation of microglial cells. The eff-ects of Foxp3 on gene expression profiles in activatedmicroglial cells were evaluated by microarray analysis,which revealed that the Warburg effect, cytokine-cyto-kine receptor interaction, immune and inflammatoryresponse, Jak-STAT signaling pathway, MAPK signal-ing pathway, cell adhesion molecules, p53 signalingpathway, and Wnt signaling pathway-related geneswere up-regulated in LPS-treated Foxp3-deficient mi-croglial cells. These findings indicate that Foxp3 mi-ght regulate the Warburg effect and inflammatory res-ponse in activated microglial cells.

Keywords Foxp3, Gene expression profile, Warburgeffect, Microglia

Chronic neurodegeneration is associated with an infla-mmatory response that is primarily mediated by thebrain macrophage population, the microglia. Microglia,which are the primary immune effector cells in thecentral nervous system (CNS), constitute the first lineof defense against infection and injury in the brain1,2.Activated microglia release neurotoxic factors (e.g.,

nitric oxide (NO)), cytokines and chemokines (e.g.,interleukin (IL)-1β, IL-6, tumor necrosis factor (TNF)-α, and MIP-1α)3-5. Accordingly, studies of the role ofmicroglia in promoting or attenuating proinflamma-tory processes in the brain influence the mechanismsof many pathophysiologies of the CNS.

We previously demonstrated a microglial responsein LPS-treated BV 2 cells. Specifically, these microgliaexpressed the Foxp3 gene. Elsewhere, the Foxp3 geneis expressed in epithelial cells6. To the best of ourknowledge, this study provides the first evidence ofFoxp3 expression in lung epithelial cells6. Foxp3 is atranscription factor that is predominantly expressed inCD4+CD25+ Treg cells and is a master regulator ofthe development and function of Treg cells7-9. Tregshave the potential to undergo function reprogrammingto acquire helper/effector phenotypes in certain phys-iological settings. Additionally, Tregs have been foundto lose Foxp3 expression when converted into proin-flammatory helper cells or CD4+ follicular helper cells.Additionally, ex-Tregs found at the sites of autoim-mune inflammation no longer express Foxp310-12. How-ever, the role of Foxp3 in cells other than Tregs is most-ly unknown.

In normal nerve cells, glucose is converted to pyru-vate, which is then converted into acetyl-CoA by pyru-vate dehydrogenase. Acetyl-CoA is subsequently fedinto the TCA cycle13. However, cancer cells producelactate from glucose, even under non-hypoxic condi-tions, in a process that has come to be known as theWarburg effect or aerobic glycolysis14. To better under-stand the role of the Foxp3 gene in the microglia, infor-mation regarding the mechanism by which it is ex-pressed and metabolized is needed. Therefore, thisstudy was conducted to determine the effects of Foxp3on LPS-induced activation in microglial cells by micro-array analysis.

ORIGINAL PAPER

The effects of Foxp3 on gene expression profiles in activatedmicroglial cells

Sung-Hwa Sohn1,*, Jun-Ho Lee1,*, Hwan-Suck Chung1,*, Hyo-Eun Lee1, Jin-Moo Lee2 & Hyunsu Bae1

Received: 13 July 2011 / Accepted: 8 November 2011�The Korean Society of Toxicogenomics and Toxicoproteomics and Springer 2012

1Department of Physiology, College of Oriental Medicine, Kyung HeeUniversity, 1 Hoegidong, Dongdaemun-gu, Seoul 130-701, Korea2Department of Gynecology, East-West Neo Medical Center, KyungHee University, 149 Sangil-dong, Gangdong-gu, Seoul 134-727, Korea*These authors contributed equally to this workCorrespondence and requests for materials should be addressed to H. Bae ( hbae@khu.ac.kr)

140 Mol Cell Toxicol (2012) 8:139-148

Figure 1. Gene ontology classifications of up- and down-regulated genes based on comparison of gene expression betweenexperimental and control microglia. (a) and (b) wild-type vs. Foxp3sf microglia, (c) and (d) Foxp3sf vs. LPS treated Foxp3sf, (e)and (f) LPS treated wild-type vs. LPS treated Foxp3sf. Red color: over-expressed genes, blue color: under-expressed genes. * Foxp3sf: microglia of Foxp3 mutant mice.

The others38%

The others31%

The others38%

The others74%

The others33%

The others42%

Metabolism12%

Transcription6%

Transcription5%

Transcription6%

Transcription1%

Transcription8%

Transcription7%

Metabolism8%

Metabolism8%

Metabolism12% Metabolism

6%

Metabolism10%

Signaltransduction

15%Cell cycle

3%

Cell cycle1%

Cell cycle3%

Cell cycle2%

Cell cycle5%

Cell cycle2%

Transport15%

Transport8%

Transport15%

Transport3%

Transport16%

Transport8%

Development3%

Development3%

Development3%

Development2%

Development5%

Translation9%

Translation1%

Translation9%

Translation1%

Translation2%

Adhesion1%

Adhesion4%

Adhesion1%

Adhesion2%

Adhesion2%

Adhesion7%

Proliferation1%

Proliferation1%

Proliferation1%

Apoptosis1%

Apoptosis2%

Apoptosis1%

Apoptosis1%

Apoptosis2%

Biologicalprocess

7%

Biologicalprocess

3%

Biologicalprocess

3%

Biologicalprocess

7%

Biologicalprocess

2%

Signaltransduction

4%

Signaltransduction

22%

Signaltransduction

4% Signaltransduction

8%

Signaltransduction

18%

Immune &inflammation

1%

Immune &inflammation

11%

Immune &inflammation

3%

Immune &inflammation

1%

(a) (b)

(c) (d)

(e) (f)

Gene expression profiles in LPS-treated Foxp3mutant microglial cells

Gene expression profiles were significantly up- ordown-regulated in the experimental groups (LPS ornon-treated Foxp3 knock out microglial cells) whencompared with the control (non-treated or Foxp3 knockout microglial cells). When the microglial cells weretreated with LPS and Foxp3 knock out were evaluatedusing approximately 45,100 oligonucloetide probesseveral genes involved in various functional categorieswere found to be induced in the experimental groupswhen compared with those in the control (Figure 1).Gene ontology annotation of these gene was then per-formed using the KEGG database, after which thegenes were placed into one of 13 biological processcategories including immune and inflammation, meta-bolism, signal transduction, transcription, cell cycle,transport, apoptosis, biological processes, development,cell adhesion and migration, translation, proliferationand other (Figure 1). Immune and inflammation geneswere significantly up-regulated in LPS treated Foxp3sf

microglia when compared to non-treated Foxp3sf mic-roglia (Figure 1c). However, transport genes were sig-nificantly down-regulated in LPS treated Foxp3sf mic-roglia when compared to non-treated Foxp3sf microglia(Figure 1d). Additionally, signal transduction geneswere down-regulated in LPS treated wild-type micro-glia when compared to LPS treated Foxp3sf microglia(Figure 1f). Genes showing highly altered expressionlevels were aligned according to the magnitude of thealtered expression. The genes that showed the greatestdifference in expression are listed in Tables 1-3, whichshows a comparison of the expression levels of a vari-ety of genes between the experimental group and thecontrol. All genes were grouped into pathway catego-ries based on the KEGG database. These genes wereinvolved in pathways including glucose metabolism(Warburg effect), cytokine-cytokine receptor interac-tion, immune and inflammatory response, cell adhesionmolecules and the p53 signaling pathway, mTOR sig-naling pathway, MAPK signaling pathway, Jak-STATsignaling pathway and Wnt signaling pathway (Tables1-3).

Discussion

The microarray method is qualitative as well as quan-titative because it is capable of detecting changes inthe levels of expression in the investigated cells whencompared with the control samples16,17. An understan-ding of these molecular processes can then be used todevelop more advanced therapies for neurodegenera-tive disease.

During a search for new therapeutic targets of neu-roinflammation disease using microarray analysis, theFoxp3 gene was found to be up-regulated in LPS treat-ed BV-2 microglial cells. In addition, we found thatinflammatory responses increased in Foxp3-deficientmicroglia18. However, the signaling events involvedin LPS-induced Foxp3-mutant microglial activationare not completely understood. To better understandthe role of the Foxp3 gene in microglia, we used themicroglia of mice with a loss of function mutation inFoxp3. To accomplish this, the effects of Foxp3-defi-ciency on the gene expression profiles of microglialcells were evaluated.

In the presence of oxygen, glucose in normal nervecells is converted into pyruvate, which is subsequentlyfed into the TCA cycle, ultimately producing energyvia oxidative phosphorylation13. The results of thisstudy revealed that oxidative phosphorylation-relatedgenes are up-regulated in the microglia of Foxp3 mu-tant mice (Foxp3sf) (Table 1), which suggests that func-tional mitochondria are required for the survival ofFoxp3-deficient microglia to elicit a detoxic effect.

Hypoxia-inducible factor-1 (HIF-1) is involved inapoptosis, cell proliferation, aging, tumor angiogene-sis, CNS disorders, innate immune responses, infec-tion, and ischemic and inflammatory diseases19-24.HIF-1 is mediates the critical cellular metabolic adap-tation to hypoxia through activation of several glyco-lytic genes, including Ldha25,26. In addition, HIF-1mediates the increased conversion of pyruvate to lac-tate. HIF-1 has been shown to actively suppress mito-chondrial respiration27,28. In this study, we found thatthe Hif1a and Ldha genes were up-regulated in LPS-stimulated Foxp3sf microglia when compared to LPS-stimulated wild-type microglia and non-stimulatedFoxp3sf microglia (Tables 2 and 3).

Naïve CD4++ T cells differentiate into Th1, Th2, andTh17 cells characterized by the cytokines29,30. Cyto-kines that activate the STAT family of transcriptionfactors have been shown to play crucial roles in theinduction and maintenance of Th cell differentiation30.Th17 cell development is dependent on STAT3, andthe STAT3 activator IL-23 is produced by innateimmune cells and has critical functions in promotionof the early and late stages of Th17 cell differentiation.Moreover, another STAT3 activator, IL-21, is preferen-tially expressed by Th17 cells and is involved in themaintenance of Th17 cell differentiation31-33. Th17cell development is known to drive autoimmune dis-eases such as experimental autoimmune encephalo-myelitis34,35. The results of this study revealed that theIl23a and Il21 genes were up-regulated in LPS-stimu-lated Foxp3sf microglia (Table 2).

The MAPK pathways are deeply involved in signal-

Mol Cell Toxicol (2012) 8:139-148 141

ing for various immune responses such as apoptosis.Each of the MAPKs has been implicated in neuroin-flammatory events and the MAPK pathways have beenlinked to mediation of many of the physiological res-

ponses to NO. NO is a signaling molecule, neurotrans-mitter, and immune effector that is produced by theactivity of the family of enzymes known as nitrix-oxidesynthases (NOSs)36-38. The results of this study indicat-

142 Mol Cell Toxicol (2012) 8:139-148

Table 1. Up- and down-regulation of genes based on comparison of gene expression between Foxp3sf (microglia of Foxp3 mutantmice) and WT (wild-type microglia).

Gene Regulation profile

Gene description symboland fold change-ratio

WT vs Foxp3sf

Oxidative phosphorylationcytochrome c oxidase, subunit VIIa 2cytochrome c oxidase, subunit VIcubiquinol-cytochrome c reductase binding proteinATP synthase, H++ transporting, mitochondrial F0 complex, subunit c (subunit 9), isoform 3ubiquinol-cytochrome c reductase binding proteinNADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 12ubiquinol-cytochrome c reductase binding proteinNADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 2cytochrome c oxidase, subunit VIIccytochrome c oxidase subunit VIIbATP synthase, H++ transporting, mitochondrial F0 complex, subunit dcytochrome c oxidase subunit VIb polypeptide 2ATP synthase, H++ transporting, mitochondrial F0 complex, subunit gNADH dehydrogenase (ubiquinone) 1 beta subcomplex 3NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 7Metabolismdeubiquitinating enzyme 2aglutathione S-transferase, pi 1Neurodegenerative Disorderssuperoxide dismutase 1, solublecaspase 6prion proteinmTOR signaling pathwayRAS-homolog enriched in brainp53 signaling pathwayring finger and CHY zinc finger domain containing 1growth arrest and DNA-damage-inducible 45 alphadamage specific DNA binding protein 2MAPK signaling pathwaynerve growth factor, beta (Ngfb), mRNARAS-related protein-1aHarvey rat sarcoma oncogene, subgroup Rmitogen-activated protein kinase kinase 1 interacting protein 1dual specificity phosphatase 14stathmin 1Calcium signaling pathwayvoltage-dependent anion channel 3peptidylprolyl isomerase D (cyclophilin D)Cell cycleE2F transcription factor 3Cytokine-cytokine receptor interactionchemokine (C-X-C motif) receptor 6Jak-STAT signaling pathwaysuppressor of cytokine signaling 4The otherslamin B receptorfibrillin 2LIM domain only 7

Cox7a2Cox6cUqcrbAtp5g3Uqcrb

Ndufa12UqcrbNdufc2Cox7cCox7bAtp5h

Cox6b2Atp5l

Ndufb3Ndufb7

Dub2aGstp1

Sod1Casp6Prnp

Rheb

Rchy1Gadd45a

Ddb2

NgfbRap1aRras

Map2k1ip1Dusp14Stmn1

Vdac3Ppid

E2f3

Cxcr6

Socs4

LbrFbn2Lmo7

4.473.912.642.592.492.442.292.131.931.931.741.741.721.701.67

16.392.20

2.882.511.52

2.68

2.271.881.55

2.191.951.841.731.611.58

2.061.87

1.81

1.81

1.67

0.390.420.52

Mol Cell Toxicol (2012) 8:139-148 143

Table 2. Up- and down-regulation of genes based on comparison of gene expression between Foxp3sf-LPS (microglia of Foxp3mutant mice with LPS) and Foxp3sf (microglia of Foxp3 mutant mice).

Gene Regulation profile

Gene description symboland fold change-ratio

Foxp3sf vs Foxp3sf-LPS

Cytokine-cytokine receptor interactionchemokine (C-X-C motif) ligand 5chemokine (C-X-C motif) ligand 11chemokine (C-X-C motif) ligand 3CD40 antigentumor necrosis factor (ligand) superfamily, member 10thymic stromal lymphopoietinchemokine (C-X-C motif) ligand 9interleukin 15 receptor, alpha chaintumor necrosis factor receptor superfamily, member 1bchemokine (C-C motif) ligand 22interleukin 18oncostatin M receptorinterleukin 10tumor necrosis factor receptor superfamily, member 14interleukin 19bone morphogenetic protein 2chemokine (C-C motif) ligand 19interleukin 23, alpha subunit p19tumor necrosis factor receptor superfamily, member 11bImmune and inflammatory responseT-cell specific GTPaseinterferon induced with helicase C domain 1guanylate nucleotide binding protein 3guanylate nucleotide binding protein 2nitric oxide synthase 2, inducible, macrophagecomplement factor BDEAD (Asp-Glu-Ala-Asp) box polypeptide 58interleukin 1 receptor antagonistserine (or cysteine) peptidase inhibitor, clade A, member 3Fproteasome (prosome, macropain) subunit, beta type 8nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, epsilonnuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, zetainterleukin 1 receptor-like 1interleukin 1 receptor accessory protein-like 2complement component 1, r subcomponentTANK-binding kinase 1Traf3 interacting protein 2Apoptosiscaspase 4, apoptosis-related cysteine peptidasenuclear factor of kappa light chain gene enhancer in B-cells inhibitor, alphaCASP8 and FADD-like apoptosis regulatorpromyelocytic leukemia (Pml), transcript variant 2Jak-STAT signaling pathwayJanus kinase 2signal transducer and activator of transcription 5Ainterleukin 21interleukin 20 receptor betacolony stimulating factor 3 receptor (granulocyte)MAPK signaling pathwayplatelet derived growth factor, B polypeptideRAS-related C3 botulinum substrate 2guanine nucleotide binding protein (G protein), gamma 12dual specificity phosphatase 10Cell adhesion moleculesintercellular adhesion moleculeCD86 antigen

Cxcl5Cxcl11Cxcl3Cd40

Tnfsf10Tslp

Cxcl9Il15ra

Tnfrsf1bCcl22Il18

OsmrIl10

Tnfrsf14Il19

Bmp2Ccl19Il23a

Tnfrsf11b

TgtpIfih1Gbp3Gbp2Nos2Cfb

Ddx58Il1rn

Serpina3fPsmb8NfkbieNfkbizIl1rl1

Il1rapl2C1r

Tbk1Traf3ip2

Casp4NfkbiaCflarPml

Jak2Stat5aIl21

Il20rbCsf3r

PdgfbRac2

Gng12Dusp10

Icam1Cd86

30.1618.9817.2214.9013.3412.527.844.814.714.023.592.982.572.512.452.242.202.161.61

23.3317.1316.5512.3011.496.906.585.444.384.043.893.883.811.601.571.571.53

8.925.302.622.41

3.582.071.541.531.53

3.261.861.661.52

6.813.44

144 Mol Cell Toxicol (2012) 8:139-148

icos ligandintegrin alpha Lsyndecan 4protein tyrosine phosphatase, receptor type, Cintegrin alpha 5 (fibronectin receptor alpha)histocompatibility 2, M region locus 10.6histocompatibility 2, M region locus 10.1p53 signaling pathwaygrowth arrest and DNA-damage-inducible 45 betaCD82 antigenF11 receptormTOR signaling pathwayhypoxia inducible factor 1, alpha subunitWnt signaling pathwayfrizzled homolog 1 (Drosophila)MAD homolog 3 (Drosophila)Huntington’s diseasehuntingtin-associated protein 1caspase 1The othersinterferon-induced protein with tetratricopeptide repeats 1thymidylate kinase family LPS-inducible membersimilar to interferon-induced protein with tetratricopeptide repeats 3serum amyloid A 3interferon activated gene 203matrix metallopeptidase 13lipocalin 2macrophage activation 2 likeG protein-coupled receptor 84interferon gamma inducible protein 47matrix metallopeptidase 3interferon regulatory factor 1interferon activated gene 204TNFAIP3 interacting protein 3interleukin 27superoxide dismutase 2, mitochondrialTNFAIP3 interacting protein 1pentraxin related genemetallothionein 2katanin p60 (ATPase-containing) subunit A1prostaglandin-endoperoxide synthase 2lymphocyte antigen 9TRAF family member-associated Nf-kappa B activatorcollagen, type V, alpha 3human immunodeficiency virus type I enhancer binding protein 3T-cell lymphoma invasion and metastasis 1matrix metallopeptidase 1a (interstitial collagenase)NADPH oxidase 1solute carrier family 40 (iron-regulated transporter), member 15-hydroxytryptamine (serotonin) receptor 2Bkelch-like 6 (Drosophila)RAB3A interacting protein (rabin3)-like 1inositol polyphosphate-5-phosphatase Dregulator of G-protein signaling 2CD200 receptor 1hepatitis A virus cellular receptor 2cystinosis, nephropathicarylacetamide deacetylase-like 1

IcoslItgalSdc4PtprcItga5

H2-M10.6H2-M10.1

Gadd45bCd82F11r

Hif1a

Fzd1Smad3

Hap1Casp1

Ifit1Tyki

LOC667370Saa3Ifi203

Mmp13Lcn2

Mpa2lGpr84Ifi47

Mmp3Irf1

Ifi204Tnip3Il27Sod2Tnip1Ptx3Mt2

Katna1Ptgs2Ly9Tank

Col5a3Hivep3Tiam1Mmp1aNox1

Slc40a1Htr2bKlhl6

Rab3il1Inpp5dRgs2

Cd200r1Havcr2

CtnsAadacl1

3.132.292.061.721.671.581.51

2.241.951.56

1.75

1.921.86

3.152.84

72.0461.7252.9540.1920.5415.0113.1211.8810.088.046.356.256.055.615.264.154.063.503.142.482.352.071.891.831.791.771.591.520.150.260.270.280.300.400.430.440.440.44

Table 2. Continued.

Gene Regulation profile

Gene description symboland fold change-ratio

Foxp3sf vs Foxp3sf-LPS

ed that the MAPK signaling pathway-, immune andinflammatory response-, apoptosis-related genes, andNos2 gene were up-regulated in LPS-stimulated Foxp3sf

microglia (Table 2). Taken together, these results indicate that Foxp3 may

have potential efficacy for immune-therapy of inflam-mation disease and other neurodegenerative diseasesthrough anti-neuroinflammation, suppression of Th17development and the Warburg effect. The microarray-based genomic survey has been of interest in mecha-nism studies because it can quickly identify putative

therapy targets of specific diseases based on their char-acteristic expression profiles and the generated pro-files can also be used to identify putative mechanismsof action.

Materials & Methods

Materials

LPS (Escherichia coli serotype 0111:B4) was obtainedfrom Sigma (St. Louis, MO, USA), while FBS was

Mol Cell Toxicol (2012) 8:139-148 145

Table 3. Up- and down-regulation of genes based on comparison of gene expression between Foxp3sf-LPS (microglia of Foxp3mutant mice with LPS) and WT-LPS (wild-type microglia with LPS).

Gene Regulation profile and

Gene description symbolfold change-ratio

WT-LPS vs Foxp3sf-LPS

mTOR signaling pathwayRAS-homolog enriched in brainribosomal protein S6Neurodegenerative Disorderssuperoxide dismutase 1, solublecaspase 6heat shock protein 5prion proteinMAPK signaling pathwaynerve growth factor, betastathmin 1Harvey rat sarcoma oncogene, subgroup RRAS-related protein-1adual specificity phosphatase 1guanine nucleotide binding protein (G protein), gamma 12cell division cycle 42 homolog (S. cerevisiae)dual specificity phosphatase 10dual specificity phosphatase 14protein phosphatase 1A, magnesium dependent, alpha isoformp53 signaling pathwayring finger and CHY zinc finger domain containing 1growth arrest and DNA-damage-inducible 45 betaserine (or cysteine) peptidase inhibitor, clade E, member 1cyclin D2insulin-like growth factor binding protein 3reprimo, TP53 dependent G2 arrest mediator candidatephorbol-12-myristate-13-acetate-induced protein 1serine (or cysteine) peptidase inhibitor, clade B, member 5Cytokine-cytokine receptor interactionchemokine (C-C motif) ligand 22chemokine (C-X-C motif) ligand 12tumor necrosis factor receptor superfamily, member 11b Cell adhesion moleculessyndecan 4Glycolysisaldolase 1, A isoformglyceraldehyde-3-phosphate dehydrogenasealdehyde dehydrogenase family 3, subfamily A1lactate dehydrogenase Aphosphoglycerate kinase 1acylphosphatase 1, erythrocyte (common) type

RhebRps6

Sod1Casp6Hspa5Prnp

Stmn1Rras

Rap1aDusp1Gng12Cdc42Dusp10Dusp14Ppm1a

Rchy1Gadd45bSerpine1Ccnd2Igfbp3Rprm

Pmaip1Serpinb5

Ccl22Cxcl12

Tnfrsf11b

Sdc4

AldoaGapdh

Aldh3a1LdhaPgk1

Acyp1

3.022.10

3.912.461.621.60

2.482.302.292.121.911.881.651.571.561.52

2.242.131.901.831.661.651.531.53

2.011.681.68

2.00

2.031.991.961.721.631.60

obtained from Hyclone (Logan, UT, USA). Additio-nally, 0.2μm syringe filters, 96 and 24 well tissue cul-ture plates, and 100-mm diameter dishes were purchas-ed from Corning Inc. (Corning, NY, USA). DMEM/F12was obtained from Gibco-BRL (Invitrogen Co., NY,USA) and 0.25% trypsin was obtained from WelGENE(Korea).

Animals

Scurfy (B.Cg-Foxp3sf/J) mice were purchased fromJackson Laboratories (MA, USA). All mice weremaintained in the Kyung Hee University animal facil-ity and cared for in accordance with institutional guide-lines.

Cell cultures

Mouse primary microglial cultures were prepared bymild trypsinization as previously described, with minormodifications15. Briefly, cerebral cortices of 0 to 3 day-old Scurfy or wide-type mice were chopped and dis-sociated by mechanical disruption using a nylon mesh,after which the cells were seeded in culture dishes.After in vitro culture for 10-14 days, microglial cellswere isolated from these mixed glial cultures by mildtrypsinization. The mixed glial cultures were then in-cubated with trypsin solution [0.25% trypsin, 1 mMEDTA in HBS] diluted 1 : 3 in DMEM/F12 for 30-60min. This resulted in detachment of an upper layer ofastrocytes in one piece, while the microglia remainedattached to the bottom of the culture flask. The detach-ed layer of astrocytes was aspirated, and the microgliawere used in our experiments.

RNA preparation

RNA was isolated from the microglial cells using anRneasy® mini kit (Qiagen GmbH, Hilden, Germany)according to the manufacturer’s instructions. The iso-lated RNA was then quantified using NanoDrop (NanoDrop Technologies, Inc ND-1000; Wilmington, DEUSA).

Oligonucleotide chip microarray

An oligonucleotide chip microarray was conducted us-ing single round RNA amplification protocols accord-ing to Affimetrix’s specifications (Affimetrix GeneChipExpression Analysis Technical Manual). Briefly, 3 μgof total RNA were used to synthesize the first-strandcomplementary DNA (cDNA) using oligonucleotideprobes with 24 oligo-dT plus T7 promoter as a primer(Proligo LLC, Boulder, CO) and the Superscript ChoiceSystem (Life Technologies, Invitrogen, Milan, Italy).After double-stranded cDNA synthesis, the products

were purified by phenol-chloroform extraction, andbiotinylated antisense complimentary RNA (cRNA)was generated through in vitro transcription using theBioArray RNA High-Yield Transcript Labeling kit(ENZO Life Sciences Inc., Farmingdale, NY). Next,the biotinylated labeled cRNA was fragmented, and10μg of the total fragmented cRNA was subsequentlyhybridized to the Affymetrix Mouse 430 2.0 GeneChiparray (P/N900470, Affymetrix Inc., USA). An Affime-trix Fluidics Station 400 was then used to wash andstain the chips, which removed the nonhybridized tar-get. Next, the chips were incubated with a streptavidin-phycoerythrin conjugate to stain the biotinylated cRNA.The staining was then amplified using goat IgG as ablocking reagent and biotinylated antistreptavidin anti-body (goat), followed by a second staining step with astreptavidin-phycoerythrin conjugate. Fluorescencewas detected using the Genechip System ConfocalScanner (Hewlett-Packard), and data analysis of eachGeneChip was conducted through the GeneChip 3.1software from Affymetrix, using the standard defaultsettings. For comparison among chips, global scalingwas used with all probe sets scaled to a user-definedtarget intensity of 150.

Data analysis

The MAS5 algorithm was used for expression sum-mary and signal calculation of the Affymetrix Mouse430 2.0 data. Global scaling normalization was con-ducted and the normalized data were then log-trans-formed with base 2. Fold change was applied to selectthe differentially expressed genes (DEGs) using a foldchange threshold of 1.5-fold and a significance levelof P⁄0.05. Furthermore, probe sets with all A callsin the compared groups were removed to filter falsepositives. Each probe set of the Affymetrix GeneChipdata had a detection call that was defined as follows:P, present call considered good quality; M, marginalcall considered intermediate quality; A, absent callconsidered to be of relatively low reliability. The 1.5-fold DEGs were clustered using hierarchical clusteringwith Pearson’s correlation as a similarity measure andcomplete linkage as a linkage method. The GenPlexTM

v2.4 software (ISTECH Inc., Korea) was utilized forcluster analysis. The gene ontology significance analy-sis was then conducted to investigate the functionalrelationships among the 1.5-fold DEGs using high-throughput GoMiner. The 1.5-fold DEGs were thenmapped to the relevant pathways using the GenPlexTM

v2.4 software (ISTECH Inc., Korea). The pathway re-sources are provided by the KEGG database.

Acknowledgements This work was supported by theKyungHee University grant funded (No. 20090503).

146 Mol Cell Toxicol (2012) 8:139-148

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