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Molecular Immunology 51 (2012) 112– 127

Contents lists available at SciVerse ScienceDirect

Molecular Immunology

j ourna l ho me pag e: www.elsev ier .com/ locate /mol imm

d14 SNPs regulate the innate immune response�

ong-Hsing Liua,1, Yajing Hua, Ming Zhenga, Megan M. Suhoskib, Edgar G. Englemanb,avid L. Dill c, Matt Hudnall a, Jianmei Wangd, Rosanne Spolskie, Warren J. Leonarde, Gary Peltze,∗

Department of Anesthesia, Stanford University School of Medicine, Stanford, CA 94305, USADepartment of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USADepartment of Computer Science, Stanford University, Stanford, CA 94305, USADepartment of Genetics & Genomics, Roche, Palo Alto, 3431 Hillview Ave., Palo Alto, CA 94304-1397, USALaboratory of Molecular Immunology and the Immunology Center, NHLBI, 10 Center Dr, Building 10, Bethesda, MD 20892-1674, USA

r t i c l e i n f o

rticle history:eceived 30 January 2012ccepted 6 February 2012vailable online 23 March 2012

a b s t r a c t

CD14 is a monocytic differentiation antigen that regulates innate immune responses to pathogens. Here,we show that murine Cd14 SNPs regulate the length of Cd14 mRNA and CD14 protein translation effi-ciency, and consequently the basal level of soluble CD14 (sCD14) and type I IFN production by murinemacrophages. This has substantial downstream consequences for the innate immune response; the level

eywords:D14onocyteenetics

of expression of at least 40 IFN-responsive murine genes was altered by this mechanism. We also observedthat there was substantial variation in the length of human CD14 mRNAs and in their translation effi-ciency. sCD14 increased cytokine production by human dendritic cells (DCs), and sCD14-primed DCsaugmented human CD4T cell proliferation. These findings may provide a mechanism for exploring thecomplex relationship between CD14 SNPs, serum sCD14 levels, and susceptibility to human infectiousand allergic diseases.

. Introduction

Since only ∼1% of the human genome is located within exonsVenter et al., 2001), the vast majority of polymorphisms are sin-le nucleotide polymorphisms (SNPs) located within non-codingegions. Approximately 40% of the ∼1200 SNPs identified in humanenome-wide disease association studies are not located withinxons and thus are regulatory SNPs (Visel et al., 2009). Severalegulatory SNPs (rSNPs) have been identified that cause humanenetic diseases by known mechanisms, including: including:halassaemias, preaxial polydactyly, and Hirschsprung’s disease

reviewed in Brem et al., 2002; Buckland, 2004; Visel et al., 2009).

small number of rSNPs are located within transcription fac-or binding sites, and may affect disease susceptibility through a

Abbreviations: HBCGM, haplotype-based computational genetic mapping;SNPs, regulatory SNPs.� G.P. was partially supported by funding from a transformative RO1 award1R01DK090992-01) from the NIDDK. This work was also supported in part by theivision of Intramural Research, National Heart, Lung, and Blood Institute, National

nstitutes of Health (R.S. and W.J.L.).∗ Corresponding author at: Stanford University, 300 Pasteur Drive Lane, Buildingoom 232, Stanford, CA 94305, USA. Tel.: +1 650 721 2487; fax: +1 650 721 2420.

E-mail address: gpeltz@stanford.edu (G. Peltz).1 Current address: Pediatrics Department of EnChuKong Hospital, New Taipei City,

aiwan.

161-5890/$ – see front matter © 2012 Elsevier Ltd. All rights reserved.oi:10.1016/j.molimm.2012.02.112

© 2012 Elsevier Ltd. All rights reserved.

cis-genetic effect on gene expression (Helms et al., 2003; Knightet al., 1999; Ozaki et al., 2002; Prokunina et al., 2002; Tokuhiroet al., 2003). However, the functional effects of most rSNPs havenot been characterized, including their effects on gene regulation.Genetic analyses in organisms ranging from yeast (Brem et al.,2005; Yvert et al., 2003) to mice (Schadt et al., 2003) have demon-strated that most gene expression differences arise from geneticvariation located outside of a pre-selected interval containing thedifferentially expressed gene, which is referred to as a trans-actinggenetic effect. Moreover, the levels of expression of most mRNAsare regulated by more than one genetic locus (Brem et al., 2005), andeach locus may have a small individual tissue or context-specificeffect (Dimas et al., 2009; Knight, 2005).

In order to understand how the vast majority of our geneticdifferences contribute to phenotypic differences, we must iden-tify and characterize the effects that trans-acting rSNPs haveon gene expression, but this is currently a complex and time-consuming undertaking (Buckland, 2006; Knight, 2005). Wepreviously demonstrated that haplotype-based computationalgenetic mapping (HBCGM) (Liao et al., 2004; Wang and Peltz, 2005)could be used to analyze microarray-generated gene expressiondata obtained from a panel of inbred mouse strains, and a novel

cis-acting enhancer element contributing to the tissue-specific pat-tern of differential H2-Ea mRNA expression was identified (Liaoet al., 2004). Other analysis methods have been used to analyzegene expression differences in rodents (Tesson and Jansen, 2009),

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umans (Franke and Jansen, 2009) or plants (Jansen et al., 2009).enetic changes exerting a local effect on target gene expression

in cis) often have a strong influence that is replicable. However,istal (trans) genetic associations that were identified by theseethods have more subtle effects, which have proven to be more

ifficult to validate (Majewski and Pastinen, 2010). Therefore, wexplored whether a different approach for the identification ofenetic factors with a trans effect on gene expression would beroductive. We wanted to determine if we could identify groupsf genes with a common pattern of differential expression in lym-hocytes, and then use HBCGM to investigate whether there was

common genetic basis for the differential expression of a geneluster. This approach was used because a genetic factor affectinghe expression of a cluster of downstream genes is more likely tompact phenotypes related to immunological diseases. Since B cellslay an important role in immune responses, the genetic basis forn expression cluster of 40 genes with a similar expression pro-le in murine B cells was investigated. rSNPs located near the Cd14ranscriptional start site were shown to alter basal CD14 proteinecretion and macrophage type I IFN production by a novel mech-nism. Because the variable length of human CD14 transcripts alsoffected human CD14 protein translation efficiency, we investi-ated the impact that sCD14 has on cytokine production by humanCs and on human CD4T cell responses.

. Materials and methods

.1. B cell and chondrocyte isolation

Mice were obtained from Jackson Labs, and were used in thexperiments at 8–10 weeks of age. Spleen cells were independentlyrepared from three female mice of the following 11 inbred strains:29/SvJ, A/J, AKR/J, BALB/cJ, C3H/HeJ, C57BL/6J, DBA/2J, MRL/MpJ,ZB/BinJ, NZW/LaC, SMJ. Single-cell suspensions of spleen cellsere prepared by lysis in ACK buffer (Cambrex, East Rutherford,.J.). B cells were positively selected using B220 magnetic beads

Miltenyi Biotec, Auburn, CA) on LS cell separation columns (Mil-enyi Biotec, Auburn, CA), and then plated at 4 × 106 cells/ml inomplete RPMI-1640 medium prior to freezing. Murine costalhondrocytes were isolated from rib cages obtained from 3 dayld newborn mice using published methods (Gosset et al., 2008)rom the following strains: A/J, AKR/J, BALB/cJ, BALB/cByJ, C3H/HeJ,57BL/6J, and DBA/2J. The isolated cells were frozen from 3 inde-endent preparations for each strain, and stored at −80 ◦C beforese.

.2. Microarray expression analysis

RNA was purified and oligonucleotide microarray data wasenerated using the Affymetrix GeneChip Mouse Genome 430.0 Array (∼39,000 transcripts) for all samples using previouslyescribed methods (Guo et al., 2007). There were 69 B cell sam-les, obtained from 11 mouse strains (129/SvJ, A/J, AKR/J, BALB/cJ,3H/HeJ, C57BL/6J, DBA/2J, MRL/MpJ, NZB/BinJ, NZW/LaC, SMJ)hat were exposed to 2 treatment conditions: (1) control and (2)nti-IgM and CD40 stimulation. There were 3–4 independent sam-les analyzed for each strain and treatment condition. The sameicroarrays were used to analyze gene expression in chondrocyte

ultures, and 3 independent preparations were analyzed for eachtrain.

.3. B cell data processing and statistical analysis

The probe intensity data generated from all 69 arrays wereead into the R software environment (http://www.R-project.org)irectly from the .CEL files using the R/affy package (Gautier et al.,

nology 51 (2012) 112– 127 113

2004), which was also used to extract and manipulate probe leveldata to assess data quality and to create expression summary mea-sures. The array data were also checked for quality using GCOS(Gene Chip Operating Software) from Affymetrix. Normalizationwas carried out using the robust multiarray average (RMA) method(Irizarry et al., 2003) to generate one expression measure for eachprobe set on each array.

The arrays have 45,100 probesets correspond to ∼39,000 tran-scripts. The following analyses were applied to each probeset toidentify probesets that are differentially expressed among strainswith large fold change. A one-way ANOVA (Analysis of Variance)model was applied to test the whether a gene was differentiallyexpressed among the mouse strains; the basal and stimulated Bcell conditions were analyzed separately. The average expressionlevel for each probeset was calculated for each strain. Since RMAsignals are on a log2 scale, the fold change was defined as 2 to thepower of the maximum average expression level minus the min-imum expression level. Probesets with an ANOVA p-value < 10−10

and a fold change greater than 10 were identified as genes thatwere highly significantly differentially expressed. There were 257and 243 such probesets that corresponded to 183 and 179 genesfor the basal and stimulated B cells, respectively. The differentiallyexpressed probesets were selected for further cluster analysis.

K-mean cluster analysis was used to group the differentiallyexpressed probesets into groups with similar expression profiles.Each probeset is associated with an 11 dimensional vector that cor-responds to the average expression levels in the 11 mouse strains.The distance between each pair of probesets is measured by the cor-relation coefficient of the two vectors. When two probesets havea strong positive correlation, they are considered to have similarprofiles. The K-mean clustering algorithm is an unsupervised clas-sification algorithm that separates the probesets into a predefinednumber of groups; and each group contains probesets with similarprofiles. Since the number of clusters must be pre-specified (beforethe analysis is complete), different numbers were tested. The num-ber of genes within a cluster with a representative profile should belarge enough to allow identification of genes that are regulated bya common factor, yet not so large that genes with distinct profilesare clustered together. Through empirical testing, we found thatspecification of 40 clusters each for the B cell basal and stimulatedconditions, met this criteria. The cluster analysis was performedusing Spotfire DecisionSite 8.2.1 (http://www.spotfire.com/) soft-ware.

2.4. Haplotype-based computational genetic mapping

The average gene expression profile for genes within cluster24 was used as the input data. Then, genes with a haplotypic pat-tern that matched this gene expression were identified using thepreviously described haplotype mapping method (Wang and Peltz,2005). To cover the entire genome, the haplotype blocks were pro-duced by analysis of 8.3 million SNPs among 16 inbred mousestrains that were identified in the NIEHS database (Frazer et al.,2007). Of note, CAST/EiJ, MOLF/EiJ, PWD/PhJ, WSB/EiJ are wild-derived strains, which we could not productively incorporate into ahaplotype map structure that is useful for computational mapping(Wang et al., 2005). Therefore, the genome-wide haplotype mapwas constructed using the 3.4 M SNPs that are polymorphic amongthe 12 other strains (Frazer et al., 2007). Within a haplotypic block,the SNPs display a limited level of variation that can be quantifiedby measuring the linkage-disequilibrium (LD) among the SNPs. Inbrief, our previously described methods (Liao et al., 2004; Wang

et al., 2005) were used to partition a chromosome into a set ofhaplotype blocks that maximize the within-block LD measure andminimize the between-block LD measure. The average pair-wiseLD measure among the component SNPs was used to represent the

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egree of within-block LD, and√

n · (n − 1) times the average LDeasure was used as the score for a candidate block; where n is the

umber of SNPs in that block. For partitioning a chromosome into set of haplotype blocks, the total score for a candidate partitionas the sum of the scores of the individual blocks within the parti-

ion. The optimal partition was identified through maximizing thecore. The haplotype blocks in this optimal partition were those thataximize the within-block LD measure and minimize the between-

lock LD measure. There were 228,885 haplotype blocks producedy this method. The average number of SNPs and haplotypes perlock was 12.02 and 2.86, respectively. According to our previousethod (Liao et al., 2004), only the 141,014 (61.6%) blocks that hadore than 3 SNPs were used for genetic mapping. Available phe-

otypic datasets (Liao et al., 2004) (MHC, aromatic hydrocarbonesponse, H2-Ea gene expression) were used to assess computa-ional mapping results generated using this extended haplotype

ap. In all cases, the genetic loci that were known to be responsibleor the inter-strain differences were identified with the expandedatabase.

.5. Candidate gene selection

First, we determined which of the 2222 correlated genes werexpressed in chondrocytes, which were used as a surrogate foracrophages. For this analysis, we used a gene expression dataset

repared from chondrocytes isolated from 7 different strains.hondrocytes and macrophages are derived from a common mes-nchymal stem cell (Caplan, 1991); and chondrocytes have beenhown to have a common pattern of chemokine production (Borzit al., 1999), antigen expression (Summers et al., 1995) andmportant functional properties (class II histocompatibility anti-en expression, antigen presentation to lymphocytes, induction ofixed and autologous lymphocyte stimulation, production of reac-

ive oxygen intermediates) that are specifically associated withacrophages (Rathakrishnan and Tiku, 1993; Tiku et al., 1985).oreover, chondrocytes have been shown to respond to IFN�, and

heir response is of importance to inflammatory arthritis (Corrt al., 2011; Palmer et al., 2004). To do this, the MAS5 calls for thehondrocyte gene expression data were analyzed using the R/affyackage (Gautier et al., 2004). If a probe set was determined toe “present” for all 3 replicates of that strain, the probe set was

abeled as expressed in this strain. For this analysis, a probe setas labeled as expressed if it was present in at least one of the 7

trains analyzed. Secondly, we identified the genes with a uniqueattern of expression in C3H/HeJ chondrocytes. To do this, we usedn ANOVA model to identify genes whose absolute expression levelas at least 2-fold different in C3H/HeJ chondrocytes relative to

he average level of expression in the other 6 strains. This ANOVAodel had a nested feature that was written as: gene expressionisC3H + strain (isC3H), where the primary variable of interest is aariable to indicate whether the strain is C3H and different mousetrains are nested within the primary variable. To identify the geneshat were commonly found in the different gene lists, all gene sym-ols were converted to Entrez Gene ID using the IDconverter (Alibest al., 2007) program. Then, the genes that were expressed in bothists with common gene identifiers were selected using R (www.r-roject.org).

.6. B cell analysis

B cells were purified from splenic cells using a Miltenyi

iotec B Cell Isolation Kit (Cat. # 130-090-862). The cell den-ity was adjusted using complete media (RPMI-1640 with 10%eat-inactivated FBS, P/S, non-essential amino acids, pyruvate, and-Gln). Cells were incubated at 37 ◦C, 5% CO2. After purification, cells

ology 51 (2012) 112– 127

were adjusted to 0.8 × 106/ml. 1 h later, cells were stimulated withindicated concentrations of recombinant mouse interferon-� (R&D,Cat. # 12400-1). At indicated time points, cells were harvested foreither real-time PCR analyses or Western Blot. For real-time PCRanalysis, total RNA was extracted using the Qiagen RNeasy Mini Kit(Valencia, CA, Cat. # 74104) and QIAshredder (Cat. # 79654). 2 �gtotal RNA from each sample was used for 1st-strand cDNA synthesisthat was performed using Invitrogen SuperScript III (Carlsbad, CACat. # 18080-051). 0.5 �l cDNA each sample was used for realtimePCR (Qiagen SYBR GreenER, Cat. # 56465). The data were collectedand analyzed using an Applied Biosystems 7900HT, and all valueswere normalized relative to the expression level of �-Actin. Thefollowing primer sequences were used: Isg20 5′-TCC CTG AGG CTGCTG TGT AAG-3′, 5′-TGG GGG AGT GTT CTT GGT TTT-3′; Zbp1 5′-GTAGCC CCC AGA CCA CAG AAC-3′, 5′-GCA-AGG-TCG-GTT-CCA-CTT-CTT-3′; Mx1 5′-GCC AGG ACC AGG TTT ACA AGG-3′, 5′-TCC AGGAAC CAG CTG CAC TTA-3′; Irf7 5′-CAC CCC CAT CTT CGA CTT CAG-3′, 5′-GAC CCA GGT CCA TGA GGA AGT-3′; Bst2 5′-GCT GGA GAA TCTGAG GAT CCA A-3′, 5′-AAG CAG AAC TCC CTC CCC ACT-3′; �-Actin5′-TGA CGT TGA CAT CCG TAA AGA CC-3′, 5′-AAG GGT GTA AAACGC AGC TCA-3′. For western blotting, the cells were lysed in 1×SDS loading buffer, boiled, and the viscosity was reduced by incu-bation with Benzonase (Novagen, Gibbstown N.J., Cat. # 70664) at4 ◦C for 1 h before further analyses.

2.7. Antibodies for Western blot

IRF7 (Santa Cruz Biotechnology, Santa Cruz CA, clone H-246),pSTAT1 (Cell Signaling, clone Tyr701), �-Actin (Cell Signaling,Boston MA, clone 13E5), and CD14 (BD, clone rmC5-3). Alkaline-phosphatase-conjugated secondary antibodies were Promega orSanta-Cruz Biotechnology.

2.8. Macrophage stimulation with polyI:C or Toll-like receptorligands

CD11b+ peritoneal macrophages were purified from C3H/HeJ orC57BL/6 mice using Miltenyi Biotec CD11b MicroBeads (AuburnCA, Cat #. 130-049-601), and the cells were adjusted to a finaldensity of 3.75 × 105 cells per ml in a 96-well plate. Each wellcontained 60,000 cells that were stimulated in the presence orabsence of recombinant soluble CD14 (Cell Sciences, Canton MA,Cat. # CRCC03) and the following TLR ligands for 24 h: Pam3CSK4for TLR1/2; HKLM (heat killed Listeria monocytogenes) for TLR2;polyI:C for TLR3; LPS-EK for TLR4; ST-FLA (flagellin from Salmonellatyphimurium) for TLR5; FSL1 (Pam2CGDPKHPKSF) for TLR6/2;ssRNA40 for TLR7; CpG ODN1826 for TLR9. After 24 h, media werecollected for either Western blot or EIA analyses. Poly I:C wasobtained from Amersham Biosciences (Pittsburgh, PA) and theother Toll-like receptor ligands were from Invivogen (Cat. # tlrl-kit1m).

2.9. Enzyme immmunoassays

Mouse interferon-� was measured using the PBL VeriKine kit(Piscataway, NJ, Cat. #, 42400-1), and IL-6 was quantified usingthe R&D Systems kit (Cat. # M6000B). For analysis of sCD14 anal-ysis, 3 ml of serum from the following strains were purchasedfrom Jackson Laboratory: A/J (12 weeks); AKR/J (9 weeks); C3H/HeJ(12 weeks); and C57BB6 (12 weeks). The sera were analyzed usinga CD14 EIA kit (Cell Sciences Cat. #: CKM034).

2.10. Rapid amplification of cDNA ends (RACE) for murine CD14

Cd14 RACE was performed using the Clontech (Mountain View,CA) SMARTer RACE cDNA Amplification Kit (Cat. # 634923). Primer

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equences were as following: 5′-outer 5′-CGC ACC GTA AGC CGCTT AAG GAC-3′, 5′-inner 5′-CTT CCG TGT CCA CAC GCT TTA-3′; 3′-uter 5′-AGC CAG ATT GGT CCA GCG CTT TC-3′, 3-inner 5′-GGC AGAGT GGA ATT GTA CGG-3′.

.11. In vitro transcription-translation

Cd14 RNA mutants were prepared using T7 polymerase (Thermocientific, Cat. # 88856) acting on 200 ng of agarose-fractionatedNA templates, which were PCR-amplified from strain-specificDNA clones using purified forward primers (sequences below) and

common reverse primer (5′-TTA AAC AAA GAG GCG ATC TCC-3′):57BL/6 (5′-GGA AGG AAG GAA GAG ATA ATA CGA CTC ACT ATA GGA GAA CAC CAC CGC TGT AAA G-3′ with a C57BL/6 clone); C3H-L

5′-GGA AGG AAG GAA GAG ATA ATA CGA CTC ACT ATA GAG ACGAA TTA GAA TTC ACA GAG with a C3H clone); C3H-S (5′-GGA AGGAG GAA GAG ATA ATA CGA CTC ACT ATA GAA CAA GCC CGT GGACC TG-3′ with a C3H clone); and 5′-UU-3′ (5′-GGA AGG AAG GAAAG ATA ATA CGA CTC ACT ATA GAG AGA ACA CCA TCG CTGTAAG-3′ with a C3H clone). The resulting RNA was precipitated withmmonium acetate, and re-suspended with nuclease-free water;

�g RNA was used for in vitro translation (Thermo Scientific, Cat. #8856); and at the indicated time points, a fixed portion of eacheaction was analyzed by immunoblotting with anti-CD14 anti-odies. Reactions from 1 �g of pCFE-GFP (Thermo Scientific, Cat. #8856) were used as a positive control for in vitro transcription, ands a negative control for immunoblotting after in vitro translation.

.12. Nucleic acid extraction from human blood cells

Blood was obtained from anonymous donors at the Stanfordniversity Blood Bank after informed consent was obtained. 100 �lf whole blood was placed in 1 ml PBS/2 mM EDTA, and the solu-ion was centrifuged and re-suspended in 1 ml 1× RBC lysis bufferBiolegend, San Diego, CA, catalogue #420301). The solution wasivided in half, and used for either total RNA or genomic DNAxtraction. Total RNA was prepared using the QIAGEN RNeasy Miniit (Cat. # 74104). Genomic DNA was obtained by lysing the cells in00 �l SDS buffer (100 mM Tris pH 7.4, 5 mM EDTA, 200 mM NaCl,.2% SDS, 100 �g/ml Proteinase K) at 55 C for 10 min. The DNA wasrecipitated with 500 �l isopropanol, washed with 70% Ethanol,nd genomic DNA was re-suspended in 100 �l TE1/10 buffer andtored at 4 ◦C before use.

.13. Human CD14 genotyping at SNP rs2569190

The genomic region spanning SNP rs2569190 was amplifiedprimers: 5′-TCC TGG GGA GAG AGC AGA GGT-3′ and 5′-TTT GGTGC AGG AGA TCA ACA-3′) using the following PCR conditions:5 ◦C 5 min, 35 cycles of 95 ◦C 30 s, 60 ◦C 30 s, 72 ◦C 1 min, plus anal 72 ◦C 10 min cycle. The amplified products were subject tova II digestion; which digests amplicons containing the A (but not

he G) allele. The allelic determinations were confirmed by A- or-allele specific PCR performed using the following primers: 5′-CC TGG GGA GAG AGC AGA GGT-3′ and 5′-CAG AAT CCT TCC TGTAC GGT-3′ for A allele; 5′-TCC TGG GGA GAG AGC AGA GGT-3′ and′-CAG AAT CCT TCC TGT TAC GGC-3′ for G allele. The PCR ampli-cations were performed as follows: 95 ◦C 5 min, 5 cycles of 95 ◦C0 s, 68 ◦C 30 s, 72 ◦C 30 s, another 5 cycles of 95 ◦C 30 s, 65 ◦C 30 s,2 ◦C 30 s, and 25 cycles of 95 ◦C 30 s, 63 ◦C 30 s, 72 ◦C 30 s, plus thenal 72 ◦C 10 min.

.14. Cloning and sequencing of the 5′ UTR of human CD14 mRNA

First strand cDNA from total RNA was synthesized usinghe Clontech SMARTer RACE Kit (Cat. # 634923) and human

nology 51 (2012) 112– 127 115

CD14-specific primers. 5′-AAG GTT CTG GCG TGG TCG CAG AG-3′

and 5′-CGG GTG CCG CTG TGT AGG AAA G-3′ were used for 5′-RACE and 3′-RACE, respectively, according to the manufacturer’srecommended PCR conditions. The 5′-RACE product was subject toa second round of PCR amplification (primer pair: 5′-ACT GAT GAGCTC AAG CAG TGG TAT CAA CGC AGA GT-3′/5′-AGC AGC AGC AGCAAC AAG CAG-3′) under the following PCR parameters: 95 ◦C for5 min, 35 cycles of 95 ◦C for 30 s, 65 ◦C for 30 s, 72 ◦C for 2 min, anda final 72 ◦C for 10 min. Purified DNA was subject to Sac I digestionand ligated onto pcDNA 3.1+ (Invitrogen) for sequencing. At least 8independent clones were analyzed for each blood sample.

2.15. In vitro transcription and translation of human CD14

A full length human CD14 construct was produced by ligatingthe longest 5′-RACE fragment from each of the above donors onto a3′-RACE human CD14 clone at the Sac I site (located 25 bp 5′ of theinitiator ATG) in pcDNA 3.1+ (Invitrogen) vector. The structure ofall resulting constructs was confirmed by full-length sequencing.The DNA templates for T7-driven human CD14 transcripts werePCR-amplified from the full-length clone using a common reverseprimer (5′-ACT GAT GTT TAA ACT GGG GCA AAG GGT TGA ATT GGTC-3′ in one experiment and 5′-TTA CTT GTC GTC ATC GTC TTT GTAGTC GGC AAA GCC CCG GGC CCC TTG G-3′ in the other experiment)and the following forward primers:

5′-GGA AGG AAG GAA GAG ATA ATA CGA CTC ACT ATA GAGGAT TAC ATA AAC TGT CAG AGG CAG-3′ for −142 from ATG, 5′-GGA AGG AAG GAA GAG ATA ATA CGA CTC ACT ATA GCA GCCGAA GAG TTC ACA AGT GTG AAG-3′ for −119 from ATG, 5′-GGAAGG AAG GAA GAG ATA ATA CGA CTC ACT ATA GTC ACA AGT GTGAAG CCT GGA AGC CGG-3′ for −107 from ATG, and 5′-GGA AGGAAG GAA GAG ATA ATA CGA CTC ACT ATA GAC AAG TGT GAA GCCTGG AAG CCG GCG-3′ for −105 from ATG. The in vitro transcriptionand translation experiments were performed as described for themurine CD14 experiments. The amount of in vitro translated humanCD14 was measured by enzyme immunoassay (R&D, Cat. # DC140)according to the manufacturer’s instructions. The capture step wasperformed with an overnight incubation at 4 ◦C, and the colorwas developed for 1 h. Two independent experiments producedsimilar results.

2.16. Human DC preparation and stimulation

After informed consent was provided, peripheral bloodwas obtained from healthy donors the Stanford Blood Cen-ter and monocytes were enriched using RosetteSep® HumanMonocyte Enrichment Cocktail (STEMCELL Technologies, Cat. #15028) followed by ficoll-hypaque density gradient centrifu-gation. Monocytes were further purified using MACS® CD14microbeads (Miltenyi Biotec, Cat. # 130-050-201), and cultured at1 × 106 cells/ml in DC media (Iscove’s Modified Dulbecco’s Medium(Gibco) containing 10% human AB serum, 100 �g/ml Penicillin-Streptomycin, 2 mM l-glutamine, and 50 �M 2-ME) supplementedwith recombinant human cytokines GM-CSF (100 ng/ml, BerlexLaboratories Inc) and IL-4 (20 ng/ml, Peprotech) for 6 days at37 ◦C/10% CO2. These cytokines were replenished on days 2 and5 of culture. On day 6, the monocyte-derived DCs were assessedfor conventional morphology by light microscopy and harvestedvia gentle scraping with cold 5 mM EDTA in PBS. DCs or freshlyisolated monocytes were stained with DAPI (Invitrogen), fluores-cently conjugated mAbs against CD14, HLA-DR (Biolegend), CD209

(BD Biosciences), or appropriate isotype control mAbs. Their cellsurface phenotype was assessed using a BD LSRII (BD Biosciences)instrument, and the data was analyzed using FlowJo software(TreeStar, Inc).

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Viable DCs were re-suspended in DC stimulation media in theresence or absence of 1–5 �g/ml sCD14 (R&D Systems, Cat. # 383-D-050-CF) at 1 × 106 cells/ml overnight at 37 ◦C/10%CO2. The DCtimulation media contained different TLR agonists (Invitrogen),ncluding LPS (TLR4), PolyI:C (TLR3), Flagellin (TLR5), or Pam3Csk4-TLR1/2) at a range of concentrations. Supernatants and medianly controls were collected 24 h post stimulation, centrifugedo remove cellular debris, and stored in 96-well plates at −80 ◦Cor EIA. DCs were prepared from at least 4 healthy donors, andere used in two independent experiments that produced similar

esults. Human TNF-�, IL-10, IL-12, and IL-6 were analyzed using&D Systems EIA kits (Cat. # DTA00C, D1000B, D1200, D6050).uman IFN� and IFN� were measured using PBL VeriKine kits (Cat.

41100, 41410). For statistical analysis, the background-correctedL-10 measurements were log-transformed, and an ANOVA model

as used to assess the effect of sCD14. A fixed effect variable rep-esenting the presence or absence of sCD14 in the media as well aswo random effect variables representing the donors and dosage ofPS, respectively, were included in the model. The model was eval-ated and the significance of the effect of sCD14 was calculatedsing SAS 9.1 (Cary, NC).

.17. Mixed lymphocyte reaction

DC were isolated as described above. On day 6 of culture, DCere harvested and stimulated with LPS in the absence or pres-

nce of 1 �g/ml sCD14 for 24 h and washed 4× with PBS to removeesidual stimulants. Bulk CD4T cells were enriched from peripherallood from an allogeneic healthy donor using Rosette Sep cocktailStemCell Technologies), and naïve CD4T cells were further puri-ed using MACs negative selection kit (Miltenyi Biotec). Naïve CD4Tells were labeled with CFSE or CellTrace Violet tracking dyes (Invit-ogen) prior to addition to washed DC for 7 days (2 T and 4 T toDC ratios). The T cells were re-suspended in fresh media and re-timulated with PMA (200 ng/ml) and Ionomycin (1 �g/ml) in theresence of Brefeldin A for 15 h and stained with Live Dead Aquaixable Dead cell stain for viability (Invitrogen), anti-human mAbsD3 FITC, TNFalpha PE-CY7, IL-10 APC (BD Biosciences), CD3 APC-Y7, IL-17A PerCP Cy5.5, IFN� AF700, IL-13 PE, FOXP3 Pacific Blue,-bet PerCP Cy5.5 (Biolegend), RORg(t) APC (eBiosciences) accord-ng to manufacturer’s protocols. For data analysis: the p-values

ere calculated using a standard ANOVA model. When the effectf adding sCD14 with different LPS concentrations was assessed, aariable representing the donor and another variable representinghether sCD14 was added and their interaction was included in theNOVA model. When data for all concentrations of LPS were com-ined, another variable representing the LPS concentration as wells its interaction with the other variables was added to the model.n both cases, the p values for the main effect of adding sCD14 wereeported.

. Results

.1. A trans-genetic locus regulates an IFN-responsive genexpression cluster

Microarrays were used to measure the level of mRNA expressionn un-stimulated splenic B cells purified from 11 different inbred

ouse strains that were cultured for 24 h. Using highly stringentriteria (ANOVA p-value < 10−10 and a fold change >10 across the 11trains analyzed), we identified 183 differentially expressed genes

hat could be separated into 40 groups with similar expression pro-les across the inbred strains using K-mean cluster analysis, which

s as an un-supervised (non-biased) analysis method (Fig. 1A).lthough several clusters had interesting expression patterns,

ology 51 (2012) 112– 127

cluster 24 (Fig. 1B) was particularly interesting for several reasons.(i) It had the largest number of genes (n = 40) of any cluster. (ii) Thelevel of expression of each of the 40 cluster 24 genes in C3H/HeJB cells was at least 10-fold below that in the other 10 strains. (iii)All of the genes in cluster 24 were known to be induced by typeI interferons (Table S1). All of these features suggested that therecould be common genetic basis for this expression pattern.

3.2. The causative factor is extrinsic to B cells

A missense (ProHis712) mutation within the 3rd exon of the Tlr4gene is uniquely found in C3H/HeJ mice, which causes defectiveTLR4 signaling and LPS unresponsiveness (Hoshino et al., 1999).Proline is highly conserved at this position throughout the Toll-like receptor (TLR) protein family; the His712 allele is not foundin other inbred strains, including the closely related C3H/OuJ andC3H/HeN sub-strains (Poltorak et al., 1998). Since this mutationcould be responsible for the decreased expression in C3H/HeJ Bcells, we also examined the level of expression of 5 of these mRNAs(Irf7, Mx1, Zpb1, Isg20, and Bst2) in B cells purified from C3H/OuJmice, which have a normal Tlr4 allele on a genetic background thatis otherwise identical to C3H/HeJ. C3H/OuJ B cells had reduced basallevels of expression of these mRNAs (not shown); but stimulationwith increasing concentrations of IFN� increased their expressionto a level that was comparable to that in other strains (Fig. 2A).Moreover, C3H/HeJ and C3HOuJ B cells, regardless of Tlr4 mutationstatus, had similarly reduced levels of IRF7 protein, which was sig-nificantly below that in C57B6 B cells (Fig. 2B). It was also possiblethat a genetic difference within a cluster 24 gene could be causative.For example, Irf7 is a transcription factor, which is a member of theinterferon regulatory factor gene family, that plays a major rolein virally induced IFN�/� production and in immune cell devel-opment (reviewed in Chau et al., 2008; Zhang and Pagano, 2002).However, neither Irf7 nor any other cluster 24 gene was amongstthose with a C3H/HeJ-specific allele (see Table S2). Thus, neither theTlr4 mutation nor a cis-genetic difference was responsible for thecluster 24-gene expression pattern. We also investigated the pos-sibility that C3H/HeJ B cells had a defect in the proximal IFN�/�signaling pathway by measuring the amount of phosphorylatedSTAT1 protein in cultured B cells after IFN� stimulation. SplenicB cells purified from C3H/HeJ, C3H/OuJ, C57B6 and DBA/2J miceexhibited comparable STAT1 phosphorylation after IFN� stimula-tion (Fig. 2C).

These analyses demonstrated that: (1) neither the Tlr4 mutation,nor a cis-genetic difference within a cluster 24 gene were causative;(2) the proximal (STAT1 phosphorylation) and distal segments(mRNA induction) of the type I IFN signaling pathway in C3H/HeJB cells were intact; and (3) exogenous IFN� increased cluster 24gene expression in C3H/HeJ B cells to the same level as in the otherstrains. This indicated that the causative factor was extrinsic to Bcells, and suggested that the decreased type I interferon productionby C3H/HeJ mice could be responsible for the differences in expres-sion. Therefore, we measured the amount of IFN� produced bypurified CD11b+ peritoneal macrophages after exposure to poly(IC),a synthetic mimic of viral dsRNA used to induce IFN�/� production(Majde, 2000). C3H/HeJ macrophages produced substantially less(2–2.5 fold) IFN� than C57BL/6 macrophages after stimulation witha range of poly(IC) concentrations (1–10 �g/ml), but produced com-parable amounts of IL-6 after stimulation with poly(IC) or multipleother agents that act via TLR receptors, except for lipopolysaccha-ride (LPS), which acts via Tlr4 (Fig. 2D, see legend for the TLR used byeach agent). Consistent with their inactivating His712 Tlr4 muta-

tion, C3H/HeJ macrophages produced much less IL-6 in response toa TLR4 agonist (LPS) than C57BL/6 macrophages. Decreased IFN�production by C3H/HeJ macrophages could account for the cluster24 gene expression pattern in B cells.

H.-H. Liu et al. / Molecular Immunology 51 (2012) 112– 127 117

Fig. 1. (A) Microarrays were used to measure the level of global mRNA expression (39,000 probes) in (B220+) splenic B cells purified from 11 different inbred mouse strainsthat were cultured under basal or stimulated conditions for 24 h. Using highly stringent criteria (ANOVA p-value < 10−10 and a fold change >10 across the 11 strains analyzed),183 and 179 B cell genes were differentially expressed after basal or stimulated culture, respectively. K-mean cluster analysis was used as an un-supervised (non-biased)method to identify the 40 groups of genes with similar expression profiles across the inbred strains that are shown here. (B) The levels of expression of 40 cluster 24 mRNAs( resenm J B ce

3

2tfgt

indicated in Table S1) in B cells isolated from 11 inbred mouse strains. Each line repeasurements, and all mRNAs are expressed at a ≥10-fold reduced level in C3H/He

.3. Identification of Cd14 as a candidate genetic factor

Haplotype-based computational genetic mapping (Liao et al.,004; Wang and Peltz, 2005) with an expanded genetic database

hat covered all genes in the mouse genome was used to searchor the causative factor. This analysis identified 2222 differentenes whose pattern of genetic variation correlated with the clus-er 24 gene expression pattern (Table S2). The large number of

ts one gene in the cluster, each data point represents the average of 3 independentlls.

genetically correlated genes was not surprising, since this is the firsttime that a large (3.2 million SNPs) database that covers all genesin the mouse genome was used and C3H/HeJ mice had a uniquephenotype (reduced gene expression), so that the computational

analysis identified many genomic regions where C3H/HeJ micehave unique alleles. We have previously demonstrated (Li et al.,2010; Sato et al., 2004; Zhang et al., 2011) that gene expression datacan be used to reduce the number of genetically correlated genes

118 H.-H. Liu et al. / Molecular Immunology 51 (2012) 112– 127

Fig. 2. (A) Purified splenic B cells from 4 inbred strains were stimulated with the indicated concentration of interferon-� for 20 h prior to cell harvest, and the level ofexpression of 5 mRNAs (Irf7, Mx1, Zpb1, Isg20, and Bst2) was determined by RT-PCR analysis. All values were normalized relative to �-Actin, and are presented as themean ± standard error (n = 3). Although these mRNAs were hardly detectable under basal conditions in C3H/HeJ B cells, IFN� exposure increased their expression to a levelthat was equivalent to that in the other strains. (B) The amount of IRF7 in cell extracts prepared from purified splenic B cells purified from the indicated mouse strains weremeasured by immunoblotting. B cells from both C3H substrains (HeJ and OuJ), regardless of Tlr4 mutation status, had significantly reduced amounts of endogenous IRF7relative to C57B6 B cells. (C) The amount of phosphorylated STAT1 protein (pSTAT1) in B cells cultured in the presence or absence of 100 IU/ml interferon-� for 30 min priorto preparing cell extracts was measured. All 4 strains had comparable amounts of phosphorylated STAT1. �-Actin was used as a normalization control in both immunoblots.(D) TLR-stimulated interferon-� and IL-6 production by macrophages. CD11b+ peritoneal macrophages (60,000 cells per well) were purified from C3H/HeJ and C57BL/6 mice,and stimulated with poly I:C or the following TLR ligands (TLR receptors are indicated within parenthesis) for 24 h: Pam3CSK4 (TLR1, TLR2); HKLM (heat killed Listeriamonocytogenes, TLR2); poly(IC) (TLR3); LPS-EK (TLR4); FSL1 (Pam2CGDPKHPKSF), TLR6, TLR2; ssRNA40 (TLR7); CpG ODN1826 (TLR9). The amount of interferon-� or IL-6released into the supernatant (mean ± SEM) from 2 independent experiments is shown.

H.-H. Liu et al. / Molecular Immunology 51 (2012) 112– 127 119

Fig. 3. Analysis of Cd14 mRNA expression. (A) The level of expression of 4 candidate genes in chondrocytes isolated from 7 inbred strains. The gene symbol, number of C3H-unique SNPs within the gene; and the relative expression difference (fold-change) between the strain with the highest and lowest expression values is shown in the insertedtable. Each value represents the mean (±SEM) of 3 independent experiments. (B) The positions of 7 rSNPs (Table S3) with C3H/HeJ unique alleles and the transcriptional starts airs rs dicatet pts.

feS4(gloTl

rditabKftoifiwunlmtisaatcg

ites of 3 different Cd14 mRNAs (C3H-L, C3H-S and C57BL/6) are indicated in base pequencing of Cd14 mRNA isolated from purified macrophages (inserted image) inranscripts; the faint upper bands appearing in both lanes were un-spliced transcri

or further consideration. Therefore, we used a two-tiered genexpression-based strategy to identify the likely causative genes.ince C3H/HeJ macrophages produced less IFN�/�, we first selected55 correlated genes that were expressed in macrophage-like cellsTable S2), and then further limited the number of candidates to theenes that were differentially expressed in C3H/HeJ macrophage-ike cells (≥2-fold absolute difference from the average value of thether strains). Only 4 genes met this expression criterion (Cd14,hbs1, Wtap, and 1110018M03Rik) and had a C3H/HeJ-specific hap-otype (Fig. 3A).

Because of its known biological role in the innate immuneesponse to viral and other pathogens, Cd14 was an obvious can-idate. CD14 is a monocytic differentiation antigen that is an

mportant regulator of innate immune responses to pathogenshrough an effect on TLR function (reviewed in Akashi-Takamurand Miyake, 2008). CD14 is a high affinity receptor that can bindacterial LPS (Labeta et al., 1993), viruses (Compton et al., 2003;urt-Jones et al., 2000; Pauligk et al., 2004) or poly(IC); thereby

acilitating its internalization and enhancing intracellular activa-ion and cytokine production (Lee et al., 2006). Re-sequencingf genomic DNA identified 7 rSNPs with alleles uniquely foundn C3H/HeJ mice that are located near the previously identi-ed Cd14 transcriptional start site (Table S3 and Fig. 3B). Theseere the only SNPs present in CD14 where C3H/HeJ had anique allele among the classical inbred strains, and there wereo non-synonymous coding changes found. Therefore, we ana-

yzed the 5′ ends of Cd14 transcripts in C3H/HeJ and C57BL/6acrophages. C3H/HeJ macrophages expressed 2 different Cd14

ranscripts; in contrast, C57BL/6 macrophages, whose genotypes shared with the 9 other strains analyzed, had only one tran-cript. The shorter Cd14 C3H/HeJ transcript (C3H-S) had 83 bpt its 5′ end truncated relative to the larger transcript (C3H-L),

nd the C57BL/6 transcript was 26 bp smaller than the C3H-Sranscript (Figs. 3B and S3). Cd14 transcripts did not have codonhanges, and there were no other C3H/HeJ-unique SNPs within thisene.

elative to the (AUG) translation start site. Rapid amplification of cDNA 5′-ends andd that C57BL/6 macrophages had one, while C3H/HeJ macrophages had two Cd14

3.4. Soluble CD14 modulates IFN ̌ production by C3H/HeJmacrophages

CD14 is a 56-kDa glycosylphosphatidylinositol (GPI)-anchoredreceptor that is expressed on the surface of monocytic cells. Puri-fied C3H/HeJ macrophages had the same amount of cellular CD14as macrophages obtained from 3 other strains (Fig. 4A). However,there are at least two soluble forms of CD14 (sCD14) that arepresent in sera, which are produced by different mechanisms. Inresponse to various activating stimuli, sCD14 is released by matrixmetalloproteinase-mediated cleavage of the GPI-linked membraneform (Bazil and Strominger, 1991; Bufler et al., 1995; Mira et al.,2004). sCD14 can also be produced by direct secretion of CD14with an intact COOH-terminal sequence that is not linked to a GPImoiety (Bufler et al., 1995). Irrespective of the method of produc-tion, sCD14 can bind ligand, and act as a co-ligand to alter cytokineproduction by endothelial, epithelial, vascular smooth muscle orglial cells (Cauwels et al., 1999; Yin et al., 2009). Sera obtainedfrom C3H/HeJ mice had significantly less sCD14 than sera fromother strains (Fig. 4B). To investigate the basis for this difference,purified peritoneal macrophages were cultured for 24 h in the pres-ence or absence of poly(IC), and the amounts of membrane CD14and sCD14 in the supernatant were measured. Under basal con-ditions, C3H/HeJ macrophages reproducibly generated a minimalamount of sCD14, which was below that produced by C57BL/6macrophages (Fig. 4A, lower panel). However, after poly(IC) acti-vation, C3H/HeJ macrophages produced a similar level of sCD14 asC57BL/6 macrophages.

Since sCD14 was decreased in C3H/HeJ sera, and C3H/HeJ Bcells had decreased expression of an IFN-responsive gene cluster,we investigated whether sCD14 affected type I IFN production.The effect of sCD14 on poly(IC)-stimulated IFN� production by

macrophages was examined. Although exogenous sCD14 did notincrease IFN� production by C57BL/6 macrophages; it increasedIFN� production by C3H/HeJ macrophages up to the same levelas produced by C57BL/6 macrophages (Fig. 4C). Thus, under

120 H.-H. Liu et al. / Molecular Immunology 51 (2012) 112– 127

Fig. 4. C3H/HeJ macrophages produce less sCD14. (A) Upper panel: Peritoneal macrophages from 4 strains were cultured under basal conditions, and the amount of sCD14released into the media and cellular CD14 was measured. �-Actin was used as a normalization control. Lower panel: C3H/HeJ or C57BL/6 CD11b+ macrophages were incubatedin the absence (−) or presence (+) of poly I:C (10 �g/ml) for 24 h, and sCD14 release into the supernatant was quantitated by immunoblotting. Although they had similaramounts of endogenous CD14 in the lysates and produced the same amount of sCD14 after poly I:C stimulation, C3H/HeJ macrophages produced much less sCD14 in thebasal state. (B) The amount of sCD14 in the sera of 4 strains (8 sera per strain) was analyzed by EIA. The p-value relative to C3H/HeJ is indicated: *<0.001; or **<0.02. (C)I �g/ms unt oi

esm

3t

2iAi1idCtctdee(otl

3e

C

the many of the others were matched with other known CD14 vari-ants (NM 001040021.2, NM 001174104.1, NM 001174105.1). Thedominant TSS was located at −104 bp (relative to the ATG initiation

nterferon-� production by C57BL/6 or C3H/HeJ macrophages after 24 h poly(IC) (5eparate experiments. Although C3H/HeJ macrophages produced ∼50% of the amonterferon-� production by C3H/HeJ macrophages.

xperimental conditions that mimic viral stimulation, exogenousCD14 restored IFN� production by C3H/HeJ macrophages to a nor-al level.

.5. Cd14 rSNPs have a coupled effect on transcription andranslation

As noted above, the C3H-L and C3H-S transcripts are 109 bp and6 bp longer, respectively, than the C57BL/6 transcript. Interest-

ngly, there are have two SNPs located near (49 and 75 bp 5′ of) theUG translation start site (Figs. 5A and S1). Since the 5′UTR plays an

mportant role in regulating protein translation (Gray and Wickens,998; van der Velden and Thomas, 1999), we used a T7-dependent

n vitro transcription-translation system to investigate whether theifferent transcripts exhibit differences in protein translation. Both3H-L and C3H-S transcripts had lower translation efficiency thanhe C57BL/6 transcript (Fig. 5B); quantitative densitometry indi-ated that they had ∼50% of the translation efficiency of the C57/BL6ranscript (data not shown). Since this could be caused by a length-ependent or SNP-dependent mechanism, the in vitro translationfficiency of length-altered mutant forms of Cd14 transcripts wasxamined. Truncation to the same length as the C57BL/6 transcript5′U-U3′ construct) (see Fig. 5A) increased the translation efficiencyf the C3H/HeJ transcripts (Fig. 5C). Thus, the Cd14 rSNPs affectedhe length of the 5′ UTR of Cd14 mRNA, and there was a transcriptength-dependent effect on CD14 protein translation efficiency.

.6. Human CD14 mRNA transcription and protein translation

fficiency

It was possible that a genetic mechanism affecting solubleD14 production that was similar to that identified in mouse

l) stimulation in the presence of 0–5 �g/ml of exogenous sCD14 was measured inf IFN� produced by C57BL/6 macrophages; addition of exogenous sCD14 restored

could be operative in humans. Therefore, we analyzed the 5′ UTRregion (-599 to the initiating ATG) of the human CD14 gene (from139,992,841–139,993,439 on Chromosome 5, NCBI B36) using dataobtained from the International HapMap2 and 1000 GenomesProject3 (June 2011). Of note, there was only a single SNP (C/T,rs2569190) in this region with a minor allele frequency (MAF) of>1%. SNP rs2569190, which is located 260 bp 5′ of the human CD14translation initiation (ATG) codon, had MAFs of 48%, 50%, 49% and32% in the CEU (n = 174 individuals), CHB (n = 86), JPT (n = 89) andYRI (n = 176) populations, respectively, in the International HapMapProject data. This SNP has been widely investigated; alleles havebeen associated with alterations in transcription (LeVan et al., 2001;Mertens et al., 2009) and in serum sCD14 levels (Kabesch et al.,2004; LeVan et al., 2006; Levan et al., 2008). Thus, a survey of over>500 individuals revealed that there is only one significant SNP inthe human population in the 5′ UTR region of CD14.

Next, the 5′ UTR of human CD14 mRNAs, which were isolatedfrom the peripheral blood of 14 normal donors that were geno-typed at SNP rs2569190, were analyzed by PCR amplification andsequencing. CD14 mRNAs from all donors utilized more than onetranscriptional start site, with a total of 19 different transcrip-tion start sites (TSS) being identified (Fig. 6). The TSS were bestmatched to reference CD14 mRNA variant 1 (NM 000591.3), while

2 http://hapmap.ncbi.nlm.nih.gov/downloads/genotypes/latest phaseII+III ncbib36/forward/non-redundant/.

3 ftp://ftptrace.ncbi.nih.gov/1000genomes/ftp/pilot data/release/2010 07/lowcoverage/snps/.

H.-H. Liu et al. / Molecular Immunology 51 (2012) 112– 127 121

Fig. 5. The effect of Cd14 rSNPs was analyzed using an in vitro transcription-translation system. (A) The 5′UTR of Cd14 transcripts and the location of 3 SNPs (numberedrelative to the translation initiation site) are shown. The 5′-UU-3′ mutant was prepared by truncating the 5′ end of the C3H-S transcript to the same length as the C57BL/6transcript. (B) Cd14 variants were transcribed and translated in vitro, and the amount of CD14 protein was determined by immunoblotting. The C57BL/6 transcript hadhigher protein translation efficiency than either C3H/HeJ transcript. A GFP-expressing plasmid was used as the negative control. (C) This system was also used to analyze thetranslation efficiency of a truncation mutant. Truncation of the C3H/HeJ transcript (5′-UU-3′) increased its translation efficiency.

Fig. 6. (A) Histogram of the transcriptional start sites for human CD14 mRNAs. The 5′ UTR of human CD14 mRNAs isolated from the blood of 14 different donors, which weregenotyped at SNP rs2569190, were analyzed by PCR amplification and sequencing. The sequence of the 5′ UTR regions (based upon reference sequence NM 000591.3) isshown; and the location and clone counts for each transcriptional start site were marked relative to the donor’s genotype. While the predominant transcription initiationsite was at position −104 bp (relative to the ATG translation initiation codon), there was substantial variability in the length of the 5′ UTR. All donors utilized more than onetranscription initiation site; the longest CD14 transcript was initiated at −353 bp, while the shortest began at −79 bp. (B) The 5′ UTR length affects human CD14 translationefficiency. The in vitro translation efficiency of 3 human CD14 transcripts with different 5′ UTR lengths (−141, −118, and −104 bp) was measured. Each bar represents theaverage (±SE) of 2 independent assays. The longest transcript (-141 bp) had the highest translation efficiency, which was around double that of the other two transcripts. AStudent’s t-test was used to compare the results at the 3 and 5-h time points for the −141 and −104 transcripts. *p = 0.003 and **p = 0.002.

1 Immun

ctolpab

c3spilcnpeltUa

3a

ioicDtg1wTapmhTt(nIaewobcdtamswiofsa

cd

under basal conditions, and release normal amounts of sCD14 afterstimulation (via proteolytic cleavage of membrane CD14). Sincethere are at least 161 GPI-linked proteins in mammalian cells4

22 H.-H. Liu et al. / Molecular

odon); but the TSS ranged from −353 to −79 bp, indicating thathere is substantial variability (>274 bp) in the length of the 5′ UTRf human CD14 mRNA. Most of the TSS of the CD14 mRNAs wereocated between the −141 bp and −105 bp positions. No polymor-hisms were identified within the 5′ UTR region of the CD14 mRNAsnalyzed from these 14 donors, and there was no correlationetween the TSS and SNP rs2569190 genotype in these donors.

To investigate whether CD14 transcript length affected the effi-iency of protein translation, the 5′ UTR of CD14 transcripts with

different TSS (−141, −118, and −104 bp) were ligated into theame full-length human CD14 clone. The amount of human CD14roduced by each construct was measured using the T7-dependent

n vitro transcription-translation system (Fig. 6B). Surprisingly, theongest CD14 transcript (-141 bp) had the highest translation effi-iency; statistically significant differences (p = 0.003 or less) wereoted at the 3 and 5-h time points in the amount of CD14 proteinroduced relative to the other two transcripts, whose translationalfficiency was ∼50% of that of the −141 bp variant. Although theonger human CD14 transcript had a higher translational efficiency,hese results indicate that there is variability in the length of the 5′

TR of CD14 mRNAs in mouse and man, and the length of the 5′ UTRffects the efficiency of CD14 protein translation in both species.

.7. sCD14 affects cytokine production by human DCs andugments human CD4T cell proliferation

Since DCs initiate the innate immune response to a nascentnfection, we examined the effect that physiologic concentrationsf sCD14 (1–5 �g/ml) had on cytokine production by human DCs

n vitro. Human myeloid DCs isolated from peripheral blood andultured in the presence of IL4 and GM-CSF express conventionalC markers CD209 and HLA-DR, but ∼60-fold less membrane CD14

han freshly isolated monocytes (Fig. 7A). Since sCD14 might have areater impact on cells with less membrane CD14, we examined IL-2, IL-10, IL-6, TNF-�, IFN� and IFN� production by DCs after theyere stimulated with different concentrations of microbial-derived

LR agonists, including: flagellin (TLR5), LPS (TLR4), poly(IC) (TLR3),nd Pam3csk4 (TLR1/2). These ligands did not stimulate DCs toroduce bioactive IL-12p70, IFN�, or IFN� under multiple experi-ental conditions tested (data not shown). In the presence of the

ighest LPS concentration tested, sCD14 did not alter the amount ofNF-� produced by DCs; while at the lowest (0.5 ng/ml) LPS concen-ration tested, sCD14 induced a 4-fold increase in TNF-� productionFig. 7B). At 5.0 and 0.5 ng/ml LPS, sCD14 caused a statistically sig-ificant increase in TNF-� (ANOVA model p-value = 0.0058) and

L-10 production (Fig. 7A). This effect was particularly pronouncedt the 5.0 and 0.5 ng/ml LPS concentrations, where the aggregateffect of exogenous sCD14 on IL-10 production in all tested donorsas statistically significant (p value = 0.0017). Unexpectedly, physi-

logic concentrations of sCD14 potently stimulated IL-6 productiony DCs (Fig. 7C); the amount of sCD14-induced IL-6 production wasomparable to the maximal amounts induced by the microbial-erived TLR5, TLR4, and TLR1/2 agonists (Fig. 7C). In contrast, underhe same experimental conditions, these 3 microbial-derived TLRgonists (tested across a 3-log range of concentrations) induceduch more TNF-� production than did sCD14 (Fig. 7D). Of note,

ince human DCs were cultured in the presence of human serum,hich contains sCD14, the effect of sCD14 could be underestimated

n these in vitro experiments. Indeed, we observed that the effectsf sCD14 on cytokine production were increased when the DCsrom some donors were cultured for a short period without humanerum (Fig. 7E). Thus, sCD14 has a potent and relatively specific

bility to stimulate IL-6 production by DCs.

We wanted to determine if the effects of sCD14 on DCsould impact lymphocyte responses. Since it was previouslyemonstrated that proliferation and cytokine production by human

ology 51 (2012) 112– 127

T cells was inhibited when they were incubated with sCD14 (ReyNores et al., 1999), we used a modified protocol, where the DCswere incubated with CD14 prior to co-culture with lymphocytes,to investigate to investigate this possibility. Purified human DCswere initially cultured in the presence or absence of sCD14, and0, 0.5 or 5.0 ng/ml LPS for 24 h. After washing, these DCs wereused to stimulate mixed lymphocyte reactions with purified humanCD4+ T cells. Under all of the conditions tested, the sCD14-treatedDCs stimulated a (adjusted ANOVA p value = 0.0000003) 3-foldincrease in CD4+ T cell proliferation relative to that induced bycontrol DCs (adjusted ANOVA p value = 0.0000003). The % of pro-liferating T cells increased from 1.09 ± 0.12% in the control DCcultures to 3.06 ± 0.43% in the sCD14-stimulated cultures, and thesCD14-stimulated increases were statistically significant at all 3LPS concentrations tested (Fig. 8). Thus, through an effect on DCs,sCD14 can augment the human T cell response.

4. Discussion

The genetic and experimental analyses in mice demonstrate thatCd14 rSNPs affect basal sCD14 secretion through a coupled effecton the Cd14 transcript length and protein translation efficiency.This novel genetic effecter mechanism has substantial downstreamconsequences for the innate immune response; it altered type I IFNproduction by macrophages, and consequently, the level of expres-sion of at least 40 IFN-responsive mRNAs in B cells, many of which(e.g. Irf7, Mx1, and Mx2) play important roles in the innate immuneresponse. Although CD14 was initially identified as an LPS receptor(Wright et al., 1990) that initiated the immune response to bacte-rial infections, CD14 also plays a significant role in host responses toviruses (Pauligk et al., 2004; Compton et al., 2003; Kurt-Jones et al.,2000) and fungi (Yauch et al., 2004). Given the importance of thisinnate immune response pathway, it is likely that these Cd14 rSNPsaffect other phenotypes of biomedical importance. The availabilityof transgenic mice expressing high levels of sCD14 (Higuchi et al.,2002; Tamura et al., 1999; Jacque et al., 2006) should enable theimpact that changes in sCD14 levels have on biomedical traits to beevaluated.

We propose a novel mechanism to explain how Cd14 rSNPsmight alter basal sCD14 production. Cells utilize a complexenzymatic process to produce GPI-anchored cell membraneproteins (reviewed in Fujita and Kinoshita, 2010), with at leasteleven steps being required to synthesize the GPI precursor. Amembrane-bound multi-subunit enzyme (the GPI transamidase)must recognize nascent proteins bearing the COOH-terminal GPIattachment signal, cleave this signal sequence, and link it with theGPI precursor (Ramalingam et al., 1996). Of note, the pattern ofgenetic variation within the genes involved in GPI synthesis andprotein linkage would not explain the selective decrease in sCD14in C3H/HeJ, nor would it explain the cluster 24-gene expressionpattern. Since any enzyme-mediated process can be saturated, agenetic factor altering the translational efficiency of a nascent sub-strate protein could affect the efficiency of the GPI linkage pathway.By this proposed mechanism (‘overload hypothesis’), nascent CD14protein that is not incorporated into the GPI-linkage pathway willbe directly secreted. This model could explain why: C3H/HeJ micehave decreased basal levels of serum sCD14; C3H/HeJ macrophageshave normal levels of membrane CD14 but produce less sCD14

and soluble forms of many GPI proteins are present in serum, it is

4 SwissProt database as of 5/11/10.

H.-H. Liu et al. / Molecular Immunology 51 (2012) 112– 127 123

Fig. 7. Exogenous sCD14 stimulates cytokine production by human DCs. (A) Top panel: Cell surface expression of CD14, CD209 (DC-SIGN), and HLA DR were measured onun-stimulated dendritic cells staining with fluorochrome conjugated anti-human CD14, CD209 (DC-SIGN), HLA DR (shaded) or appropriate isotype control antibodies (open)using flow cytometry. Data represents dendritic cells prepared from one of four donors. Bottom panel: Dendritic cells have decreased CD14, and increased CD209 (DC-DIGN)and HLA DR expression relative to freshly isolated monocytes. The fold increase was calculated by dividing the geometric mean for each marker by the geometric mean ofeach respective isotype control. Each graph represents the average fold-increase in marker expression on freshly isolated monocytes (gray, n = 3 donors) or dendritic cells(DC, black, n = 4 donors). (B) Human DCs (1 × 106 cells/well) from different donors were incubated in the absence (control) or presence of 1 �g/ml human sCD14, and theindicated LPS concentrations for 24 h. Cell free supernatants were harvested and the amount of TNF-� or IL-10 produced was measured by EIA. (C,D) Exogenous sCD14 directlystimulates IL-6 production by DCs. Human DCs were incubated as above with 0, 1, 3 or 5 �g/ml of sCD14. Cell free supernatants were collected after 24 h and the amountof IL-6 and TNF-� produced was measured by EIA. In (B), the 0 and 1 �g/ml sCD14 data represent the average results (±SEM) obtained from DCs prepared from 3 differentdonors, while the 3 and 5 �g/ml sCD14 data represent the average results (±SEM) from 2 different donors. In (D), The amount of TNF-� and IL-6 produced after DCs from 2donors were incubated with the indicated concentrations of sCD14 or the TLR4 agonist LPS; the TLR1/2 agonist Pamcyk4 (0.5 �g/ml), the TLR4/5 agonist flagellin (5.0 �g/ml),or the TLR3 agonist poly(IC) (10 �g/ml). (E) The effect of sCD14 on DC cytokine production is increased in serum-free medium. DCs were prepared from peripheral bloodmonocytes, harvested on day 6 of culture and re-suspended at 1 × 106 cells/ml in fresh medium containing either 10% heat-inactivated human serum or 0.5% human serumalbumin. The cells were then stimulated with the indicated LPS concentration for 24 h in the absence (blue) or presence of 1 �g/ml sCD14 (red) and the amount of cytokinesproduced was measured by EIA.

124 H.-H. Liu et al. / Molecular Immunology 51 (2012) 112– 127

ig. 7.

co

sblsit

F

onceivable that rSNPs in other GPI-linked proteins could impactther biomedical phenotypes through this mechanism.

We did not identify a human allelic difference that alteredCD14 production. However, the analysis of cytokine productiony human DCs and alloantigen-induced human CD4T cell pro-

iferation demonstrates how a subtle genetic alteration in basalCD14 secretion can have a significant downstream impact on thennate immune response. DCs function as sentinels that initiatehe innate immune response to pathogens (Liu, 2005). Physiologic

concentrations of human sCD14 had a dual effect on DCs. First,sCD14 functioned as a signal-amplifier, enabling DCs to respondto low concentrations of microbial products, which is consistentwith similar findings by other investigators (Cauwels et al., 1999;Chase and Bosio, 2010; de Buhr et al., 2009). Second, sCD14 stim-

ulated IL-6 production by human DCs. IL-6 has pleotropic effectson virtually all organ systems, including an important role in qual-itatively regulating T cell responses (Kimura and Kishimoto, 2010).IL-6 promotes the differentiation of Th17 cells (when combined

H.-H. Liu et al. / Molecular Immunology 51 (2012) 112– 127 125

Fig. 8. The human CD4+ T cell proliferative response is augmented after DCs are exposed to sCD14. Left panels: Purified DCs from 2 donors were stimulated with the indicatedLPS concentrations for 24 h in the absence or presence of 1 �g/ml sCD14. After washing, allogeneic naïve CD4+ T cells were added to the DC cultures for 7 days, and the percentof proliferating T cells was assessed via flow cytometry. The bar graphs represent the % proliferating T cells (mean for triplicate conditions ± SEM) for each of two differentdonors with assays using the indicated ratio of T cells to DCs. Right panel: Graph showing the % proliferating CD4+ T cells measured after stimulation with control or 1 �g/mls left pd mparf

wp2s1hd1ttOomsti(asiIrt

ip

secretion may explain the discrepant results obtained in differ-ent human populations, and the variable outcomes emerging from

CD14-stimulated DCs (in the presence of 0, 0.5 or 5.0 ng/ml LPS) as measured in theonors is indicated by a different symbol. The p-values (adjusted for donor effect) coor control DCs at each LPS concentration are shown.

ith TGF�), which are crucial for immune defense against multi-le pathogens, it suppresses Treg cell development (Kimura et al.,007; Zhou et al., 2007), and can stimulate cytolytic T cells whenmall amounts of antigen presenting cells are present (Ming et al.,992). It is likely that sCD14 acts at least in part via TLR2, as sCD14as been shown to be an agonist of TLR2-mediated cytokine pro-uction (Bsibsi et al., 2007; Iwaki et al., 2005; Kirschning et al.,998; Nakata et al., 2006). sCD14 also promoted IL-10 produc-ion by DCs, which can limit the extent and qualitatively shapehe host immune response to a pathogen (reviewed in Saraiva and’Garra, 2010). This dual effect may explain the discrepant resultsbtained when exogenous sCD14 was administered in two experi-ental murine models of infection. Interestingly, when exogenous

CD14 was administered in the context of Streptococcus (meningi-is) infection, there was increased cytokine production within thenfected organ even though the bacterial load was not diminishedCauwels et al., 1999), nor did exogenous sCD14 improve survivalfter Franciscella tularensis infection (Chase and Bosio, 2010). Theignal amplifying effect would explain why sCD14 caused a local-zed increase in cytokine production. However, if sCD14 promotedL-10 and IL-6 production by DCs, this would alter the immuneesponse to these pathogens, which explains why it failed to alter

he outcome after these infections.

Over 500 publications have measured the amount of sCD14n human serum in relation to a disease condition, and 281ublications have investigated an association between a CD14 5′

anel. Each of 3 different experiments performed with DCs obtained from 2 differenting the CD14-stimulated increase in the T cell proliferative response relative to that

rSNP and susceptibility to asthma, allergy, sarcoidosis, biliary atre-sia, or acute otitis media5. Moreover, a rSNP (C/T, rs2569190)located 260 bp 5′ of the human CD14 translational start site has beenshown to affect serum sCD14 levels in multiple human populations(Baldini et al., 1999; Inoue et al., 2007; Kabesch et al., 2004; LeVanet al., 2006; Levan et al., 2008), and is associated with infant suscep-tibility to respiratory syncytial virus (RSV)-induced bronchiolitis(Inoue et al., 2007). This is of interest since CD14 plays an essen-tial role in the innate immune responses to RSV (Kurt-Jones et al.,2000) and other viruses (Compton et al., 2003; Pauligk et al., 2004).It is noteworthy that the allelic effect on sCD14 levels was seen ininfants (LeVan et al., 2006) and in adults under basal conditions, butwas eliminated in human subjects after experimental LPS exposure(Levan et al., 2008). These findings are strikingly similar to our char-acterization of sCD14 production by murine macrophages. IFN�production by C3H/HeJ macrophage in response to an experimentalviral stimulus was selectively restored after addition of exogenoussCD14 at concentrations (1–5 �g/ml) equivalent to those present inhuman serum (Baldini et al., 1999; Kabesch et al., 2004; LeVan et al.,2006). The selective impact of murine Cd14 rSNPs on basal sCD14

association studies for CD14 rSNPs in atopic diseases that develop

5 Pubmed search as of 5/10/10.

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26 H.-H. Liu et al. / Molecular

fter infancy (Baldini et al., 1999; Campos et al., 2007; Kabesch et al.,004). These associations may be explained, at least in part, by theelective impact of allelic differences on basal sCD14 levels and byhe dual effects that sCD14 exerts on human DCs. Although theength of the 5′ UTR of CD14 mRNA was not determined by the SNPs2569190 allele in the small number of individuals analyzed here,t is conceivable that other SNPs could alter the CD14 transcrip-ional start site or protein translation efficiency. Further studies arelso required to determine if human sCD14 secretion is regulatedy a mechanism that is similar to that observed in the mouse.

cknowledgement

We thank Dr. Robert Lewis for helpful discussions.

ppendix A. Supplementary data

Supplementary data associated with this article can be found, inhe online version, at doi:10.1016/j.molimm.2012.02.112.

eferences

kashi-Takamura, S., Miyake, K., 2008. TLR accessory molecules. Curr. Opin.Immunol. 20, 420–425.

libes, A., Yankilevich, P., Canada, A., Diaz-Uriarte, R., 2007. IDconverter andIDClight: conversion and annotation of gene and protein IDs. BMC Bioinformatics8, 9.

aldini, M., Lohman, I.C., Halonen, M., Erickson, R.P., Holt, P.G., Martinez, F.D., 1999.A polymorphism* in the 5′ flanking region of the CD14 gene is associated withcirculating soluble CD14 levels and with total serum immunoglobulin E. Am. J.Respir. Cell Mol. Biol. 20, 976–983.

azil, V., Strominger, J.L., 1991. Shedding as a mechanism of down-modulation ofCD14 on stimulated human monocytes. J. Immunol. 147, 1567–1574.

orzi, R.M., Mazzetti, I., Macor, S., Silvestri, T., Bassi, A., Cattini, L., Facchini, A.,1999. Flow cytometric analysis of intracellular chemokines in chondrocytes invivo: constitutive expression and enhancement in osteoarthritis and rheuma-toid arthritis. FEBS Lett. 455, 238–242.

rem, R.B., Storey, J.D., Whittle, J., Kruglyak, L., 2005. Genetic interactions betweenpolymorphisms that affect gene expression in yeast. Nature 436, 701–703.

rem, R.B., Yvert, G., Clinton, R., Kruglyak, L., 2002. Genetic dissection of transcrip-tional regulation in budding yeast. Science 296, 752–755.

sibsi, M., Bajramovic, J.J., Van Duijvenvoorden, E., Persoon, C., Ravid, R., Van Noort,J.M., Vogt, M.H., 2007. Identification of soluble CD14 as an endogenous ago-nist for Toll-like receptor 2 on human astrocytes by genome-scale functionalscreening of glial cell derived proteins. Glia 55, 473–482.

uckland, P.R., 2004. Allele-specific gene expression differences in humans. Hum.Mol. Genet. 13 (Spec No. 2), R255–R260.

uckland, P.R., 2006. The importance and identification of regulatory polymor-phisms and their mechanisms of action. Biochim. Biophys. Acta 1762, 17–28.

ufler, P., Stiegler, G., Schuchmann, M., Hess, S., Kruger, C., Stelter, F., Eckerskorn,C., Schutt, C., Engelmann, H., 1995. Soluble lipopolysaccharide receptor (CD14)is released via two different mechanisms from human monocytes and CD14transfectants. Eur. J. Immunol. 25, 604–610.

ampos, E., Shimojo, N., Inoue, Y., Arima, T., Suzuki, S., Tomiita, M., Matsuura, T., Hata,A., Suzuki, Y., Aoyagi, M., Kohno, Y., 2007. No association of polymorphisms inthe 5′ region of the CD14 gene and food allergy in a Japanese population. Allergol.Int. 56, 23–27.

aplan, A.I., 1991. Mesenchymal stem cells. J. Orthop. Res. 9, 641–650.auwels, A., Frei, K., Sansano, S., Fearns, C., Ulevitch, R., Zimmerli, W., Landmann,

R., 1999. The origin and function of soluble CD14 in experimental bacterialmeningitis. J. Immunol. 162, 4762–4772.

hase, J.C., Bosio, C.M., 2010. The presence of CD14 overcomes evasion of innateimmune responses by virulent Franciscella tularensis in human dendritic cellsin vitro and pulmonary cells in vivo. Infect. Immun. 78, 154–167.

hau, T.L., Gioia, R., Gatot, J.S., Patrascu, F., Carpentier, I., Chapelle, J.P., O’Neill, L.,Beyaert, R., Piette, J., Chariot, A., 2008. Are the IKKs and IKK-related kinases TBK1and IKK-epsilon similarly activated? Trends Biochem. Sci. 33, 171–180.

ompton, T., Kurt-Jones, E.A., Boehme, K.W., Belko, J., Latz, E., Golenbock, D.T.,Finberg, R.W., 2003. Human cytomegalovirus activates inflammatory cytokineresponses via CD14 and Toll-like receptor 2. J. Virol. 77, 4588–4596.

orr, M., Boyle, D.L., Ronacher, L.M., Lew, B.R., van Baarsen, L.G., Tak, P.P., Firestein,G.S., 2011. Interleukin 1 receptor antagonist mediates the beneficial effects ofsystemic interferon beta in mice: implications for rheumatoid arthritis. Ann.

Rheum. Dis. 70, 858–863.

e Buhr, M.F., Hedrich, H.J., Westendorf, A.M., Obermeier, F., Hofmann, C.,Zschemisch, N.H., Buer, J., Bumann, D., Goyert, S.M., Bleich, A., 2009. Analysis ofCd14 as a genetic modifier of experimental inflammatory bowel disease (IBD)in mice. Inflamm. Bowel Dis. 15, 1824–1836.

ology 51 (2012) 112– 127

Dimas, A.S., Deutsch, S., Stranger, B.E., Montgomery, S.B., Borel, C., Attar-Cohen, H.,Ingle, C., Beazley, C., Gutierrez Arcelus, M., Sekowska, M., Gagnebin, M., Nisbett,J., Deloukas, P., Dermitzakis, E.T., Antonarakis, S.E., 2009. Common regulatoryvariation impacts gene expression in a cell type-dependent manner. Science325, 1246–1250.

Franke, L., Jansen, R.C., 2009. eQTL analysis in humans. Methods Mol. Biol. 573,311–328.

Frazer, K.A., Eskin, E., Kang, H.M., Bogue, M.A., Hinds, D.A., Beilharz, E.J., Gupta, R.V.,Montgomery, J., Morenzoni, M.M., Nilsen, G.B., Pethiyagoda, C.L., Stuve, L.L., John-son, F.M., Daly, M.J., Wade, C.M., Cox, D.R., 2007. A sequence-based variation mapof 8.27 million SNPs in inbred mouse strains. Nature 448, 1050–1053.

Fujita, M., Kinoshita, T., 2010. Structural remodeling of GPI anchors during biosyn-thesis and after attachment to proteins. FEBS Lett. 584, 1670–1677.

Gautier, L., Moller, M., Friis-Hansen, L., Knudsen, S., 2004. Alternative mapping ofprobes to genes for Affymetrix chips. BMC Bioinformatics 5, 111.

Gosset, M., Berenbaum, F., Thirion, S., Jacques, C., 2008. Primary culture and pheno-typing of murine chondrocytes. Nat. Protoc. 3, 1253–1260.

Gray, N.K., Wickens, M., 1998. Control of translation initiation in animals. Annu. Rev.Cell Dev. Biol. 14, 399–458.

Guo, Y.Y., Liu, P., Zhang, X., Weller, P.M.M., Wang, J., Liao, G., Zhang, Z., Hu, J., Allard, J.,Shafer, S., Usuka, J., Peltz, G., 2007. In vitro and in silico pharmacogenetic analysisin mice. Proc. Natl. Acad. Sci. U. S. A. 104, 17735–17740.

Helms, C., Cao, L., Krueger, J.G., Wijsman, E.M., Chamian, F., Gordon, D., Heffernan,M., Daw, J.A., Robarge, J., Ott, J., Kwok, P.Y., Menter, A., Bowcock, A.M., 2003. Aputative RUNX1 binding site variant between SLC9A3R1 and NAT9 is associatedwith susceptibility to psoriasis. Nat. Genet. 35, 349–356.

Higuchi, Y., Hijiya, N., Matsuura, K., Yasui, A., Uchida, T., Yamamoto, S., 2002. Mousesoluble CD14 truncated at amino acid 71 in transgenic mice: preventive effecton endotoxin-mediated toxic shock. Pathobiology 70, 103–114.

Hoshino, K., Takeuchi, O., Kawai, T., Sanjo, H., Ogawa, T., Takeda, Y., Takeda, K., Akira,S., 1999. Cutting edge: toll-like receptor 4 (TLR4)-deficient mice are hypore-sponsive to lipopolysaccharide: evidence for TLR4 as the Lps gene product. J.Immunol. 162, 3749–3752.

Inoue, Y., Shimojo, N., Suzuki, Y., Campos Alberto, E.J., Yamaide, A., Suzuki, S., Arima,T., Matsuura, T., Tomiita, M., Aoyagi, M., Hoshioka, A., Honda, A., Hata, A., Kohno,Y., 2007. CD14 −550 C/T, which is related to the serum level of soluble CD14, isassociated with the development of respiratory syncytial virus bronchiolitis inthe Japanese population. J. Infect. Dis. 195, 1618–1624.

Irizarry, R.A., Bolstad, B.M., Collin, F., Cope, L.M., Hobbs, B., Speed, T.P., 2003. Sum-maries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 31, e15.

Iwaki, D., Nishitani, C., Mitsuzawa, H., Hyakushima, N., Sano, H., Kuroki, Y., 2005.The CD14 region spanning amino acids 57–64 is critical for interaction with theextracellular Toll-like receptor 2 domain. Biochem. Biophys. Res. Commun. 328,173–176.

Jacque, B., Stephan, K., Smirnova, I., Kim, B., Gilling, D., Poltorak, A., 2006. Miceexpressing high levels of soluble CD14 retain LPS in the circulation and areresistant to LPS-induced lethality. Eur. J. Immunol. 36, 3007–3016.

Jansen, R.C., Tesson, B.M., Fu, J., Yang, Y., McIntyre, L.M., 2009. Defining gene and QTLnetworks. Curr. Opin. Plant Biol. 12, 241–246.

Kabesch, M., Hasemann, K., Schickinger, V., Tzotcheva, I., Bohnert, A., Carr, D., Baldini,M., Hackstein, H., Leupold, W., Weiland, S.K., Martinez, F.D., Mutius, E., Bein, G.,2004. A promoter polymorphism in the CD14 gene is associated with elevatedlevels of soluble CD14 but not with IgE or atopic diseases. Allergy 59, 520–525.

Kimura, A., Kishimoto, T., 2010. IL-6: regulator of Treg/Th17 balance. Eur. J. Immunol.40, 1830–1835.

Kimura, A., Naka, T., Kishimoto, T., 2007. IL-6-dependent and -independent path-ways in the development of interleukin 17-producing T helper cells. Proc. Natl.Acad. Sci. U. S. A. 104, 12099–12104.

Kirschning, C.J., Wesche, H., Merrill Ayres, T., Rothe, M., 1998. Human toll-like recep-tor 2 confers responsiveness to bacterial lipopolysaccharide. J. Exp. Med. 188,2091–2097.

Knight, J.C., 2005. Regulatory polymorphisms underlying complex disease traits. J.Mol. Med. 83, 97–109.

Knight, J.C., Udalova, I., Hill, A.V., Greenwood, B.M., Peshu, N., Marsh, K., Kwiatkowski,D., 1999. A polymorphism that affects OCT-1 binding to the TNF promoter regionis associated with severe malaria. Nat. Genet. 22, 145–150.

Kurt-Jones, E.A., Popova, L., Kwinn, L., Haynes, L.M., Jones, L.P., Tripp, R.A., Walsh,E.E., Freeman, M.W., Golenbock, D.T., Anderson, L.J., Finberg, R.W., 2000. Patternrecognition receptors TLR4 and CD14 mediate response to respiratory syncytialvirus. Nat. Immunol. 1, 398–401.

Labeta, M.O., Durieux, J.J., Spagnoli, G., Fernandez, N., Wijdenes, J., Herrmann, R.,1993. CD14 and tolerance to lipopolysaccharide: biochemical and functionalanalysis. Immunology 80, 415–423.

Lee, H.K., Dunzendorfer, S., Soldau, K., Tobias, P.S., 2006. Double-stranded RNA-mediated TLR3 activation is enhanced by CD14. Immunity 24, 153–163.

LeVan, T.D., Bloom, J.W., Bailey, T.J., Karp, C.L., Halonen, M., Martinez, F.D., Vercelli,D., 2001. A common single nucleotide polymorphism in the CD14 promoterdecreases the affinity of Sp protein binding and enhances transcriptional activ-ity. J. Immunol. 167, 5838–5844.

LeVan, T.D., Guerra, S., Klimecki, W., Vasquez, M.M., Lohman, I.C., Martinez, F.D.,Halonen, M., Wright, A.L., 2006. The impact of CD14 polymorphisms on the

development of soluble CD14 levels during infancy. Genes Immun. 7, 77–80.

Levan, T.D., Michel, O., Dentener, M., Thorn, J., Vertongen, F., Beijer, L., Martinez,F.D., 2008. Association between CD14 polymorphisms and serum soluble CD14levels: effect of atopy and endotoxin inhalation. J. Allergy Clin. Immunol. 121,434–440, e1.

Immu

L

L

L

M

M

M

M

M

N

O

P

P

P

P

R

R

R

S

S

S

H.-H. Liu et al. / Molecular

i, X., Sahbaie, P., Zheng, M., Ritchie, J., Peltz, G., Mogil, J.S., Clark, J.D., 2010. Expressiongenetics identifies spinal mechanisms supporting formalin late phase behaviors.Mol. Pain 6, 11.

iao, G., Wang, J., Guo, J., Allard, J., Cheng, J., Ng, A., Shafer, S., Puech, A., McPherson,J.D., Foernzler, D., Peltz, G., Usuka, J., 2004. In Silico genetics: identification of afunctional element regulating H2-Ea gene expression. Science 306, 690–695.

iu, Y.J., 2005. IPC: professional type 1 interferon-producing cells and plasmacytoiddendritic cell precursors. Annu. Rev. Immunol. 23, 275–306.

ajde, J.A., 2000. Viral double-stranded RNA, cytokines, and the flu. J. InterferonCytokine Res. 20, 259–272.

ajewski, J., Pastinen, T., 2010. The study of eQTL variations by RNA-seq: from SNPsto phenotypes. Trends Genet. 27, 72–79.

ertens, J., Bregadze, R., Mansur, A., Askar, E., Bickeboller, H., Ramadori, G., Mihm,S., 2009. Functional impact of endotoxin receptor CD14 polymorphisms on tran-scriptional activity. J. Mol. Med.

ing, J.E., Steinman, R.M., Granelli-Piperno, A., 1992. IL-6 enhances the generationof cytolytic T lymphocytes in the allogeneic mixed leucocyte reaction. Clin. Exp.Immunol. 89, 148–153.

ira, E., Lacalle, R.A., Buesa, J.M., de Buitrago, G.G., Jimenez-Baranda, S., Gomez-Mouton, C., Martinez, A.C., Manes, S., 2004. Secreted MMP9 promotesangiogenesis more efficiently than constitutive active MMP9 bound to the tumorcell surface. J. Cell Sci. 117, 1847–1857.

akata, T., Yasuda, M., Fujita, M., Kataoka, H., Kiura, K., Sano, H., Shibata, K., 2006.CD14 directly binds to triacylated lipopeptides and facilitates recognition of thelipopeptides by the receptor complex of Toll-like receptors 2 and 1 withoutbinding to the complex. Cell. Microbiol. 8, 1899–1909.

zaki, K., Ohnishi, Y., Iida, A., Sekine, A., Yamada, R., Tsunoda, T., Sato, H., Hori, M.,Nakamura, Y., Tanaka, T., 2002. Functional SNPs in the lymphotoxin-alpha genethat are associated with susceptibility to myocardial infarction. Nat. Genet. 32,650–654.

almer, G., Mezin, F., Juge-Aubry, C.E., Plater-Zyberk, C., Gabay, C., Guerne, P.A.,2004. Interferon beta stimulates interleukin 1 receptor antagonist productionin human articular chondrocytes and synovial fibroblasts. Ann. Rheum. Dis. 63,43–49.

auligk, C., Nain, M., Reiling, N., Gemsa, D., Kaufmann, A., 2004. CD14 is required forinfluenza A virus-induced cytokine and chemokine production. Immunobiology209, 3–10.

oltorak, A., He, X., Smirnova, I., Liu, M.Y., Huffel, C.V., Du, X., Birdwell, D., Alejos,E., Silva, M., Galanos, C., Freudenberg, M., Ricciardi-Castagnoli, P., Layton, B.,Beutler, B., 1998. Defective LPS signaling in C3H/HeJ and C57BL/10ScCr mice:mutations in Tlr4 gene. Science 282, 2085–2088.

rokunina, L., Castillejo-Lopez, C., Oberg, F., Gunnarsson, I., Berg, L., Magnusson,V., Brookes, A.J., Tentler, D., Kristjansdottir, H., Grondal, G., Bolstad, A.I., Sve-nungsson, E., Lundberg, I., Sturfelt, G., Jonssen, A., Truedsson, L., Lima, G.,Alcocer-Varela, J., Jonsson, R., Gyllensten, U.B., Harley, J.B., Alarcon-Segovia,D., Steinsson, K., Alarcon-Riquelme, M.E., 2002. A regulatory polymorphism inPDCD1 is associated with susceptibility to systemic lupus erythematosus inhumans. Nat. Genet. 32, 666–669.

amalingam, S., Maxwell, S.E., Medof, M.E., Chen, R., Gerber, L.D., Udenfriend, S.,1996. COOH-terminal processing of nascent polypeptides by the glycosylphos-phatidylinositol transamidase in the presence of hydrazine is governed by thesame parameters as glycosylphosphatidylinositol addition. Proc. Natl. Acad. Sci.U. S. A. 93, 7528–7533.

athakrishnan, C., Tiku, M.L., 1993. Lucigenin-dependent chemiluminescence inarticular chondrocytes. Free Radic. Biol. Med. 15, 143–149.

ey Nores, J.E., Bensussan, A., Vita, N., Stelter, F., Arias, M.A., Jones, M., Lefort, S.,Borysiewicz, L.K., Ferrara, P., Labeta, M.O., 1999. Soluble CD14 acts as a negativeregulator of human T cell activation and function. Eur. J. Immunol. 29, 265–276.

araiva, M., O’Garra, A., 2010. The regulation of IL-10 production by immune cells.Nat. Rev. Immunol. 10, 170–181.

ato, N., Meijer, L., Skaltsounis, L., Greengard, P., Brivanlou, A.H., 2004. Maintenanceof pluripotency in human and mouse embryonic stem cells through activationof Wnt signaling by a pharmacological GSK-3-specific inhibitor. Nat. Med. 10,

55–63.

chadt, E., Monks, S.A., Drake, T.A., Lusis, A.J., Che, N., Colinayo, V., Ruff, T.G., Mil-ligan, S.B., Lamb, J.R., Cavet, G., Mao, M., Stoughton, R.B., Friend, S.H., 2003.Genetics of gene expression surveyed in maize, mouse and man. Nature 422,297–302.

nology 51 (2012) 112– 127 127

Summers, K.L., O’Donnell, J.L., Hoy, M.S., Peart, M., Dekker, J., Rothwell, A., Hart, D.N.,1995. Monocyte-macrophage antigen expression on chondrocytes. J. Rheuma-tol. 22, 1326–1334.

Tamura, Y., Higuchi, Y., Kataoka, M., Akizuki, S., Matsuura, K., Yamamoto, S., 1999.CD14 transgenic mice expressing membrane and soluble forms: comparisonsof levels of cytokines and lethalities in response to lipopolysaccharide betweentransgenic and non-transgenic mice. Int. Immunol. 11, 333–339.

Tesson, B.M., Jansen, R.C., 2009. eQTL analysis in mice and rats. Methods Mol. Biol.573, 285–309.

Tiku, M.L., Liu, S., Weaver, C.W., Teodorescu, M., Skosey, J.L., 1985. Class II his-tocompatibility antigen-mediated immunologic function of normal articularchondrocytes. J. Immunol. 135, 2923–2928.

Tokuhiro, S., Yamada, R., Chang, X., Suzuki, A., Kochi, Y., Sawada, T., Suzuki, M.,Nagasaki, M., Ohtsuki, M., Ono, M., Furukawa, H., Nagashima, M., Yoshino,S., Mabuchi, A., Sekine, A., Saito, S., Takahashi, A., Tsunoda, T., Nakamura, Y.,Yamamoto, K., 2003. An intronic SNP in a RUNX1 binding site of SLC22A4, encod-ing an organic cation transporter, is associated with rheumatoid arthritis. Nat.Genet. 35, 341–348.

van der Velden, A.W., Thomas, A.A., 1999. The role of the 5′ untranslated region of anmRNA in translation regulation during development. Int. J. Biochem. Cell Biol.31, 87–106.

Venter, J.C., Adams, M.D., Myers, E.W., Li, P.W., Mural, R.J., Sutton, G.G., Smith, H.O.,Yandell, M., Evans, C.A., Holt, R.A., Gocayne, J.D., Amanatides, P., Ballew, R.M.,Huson, D.H., Wortman, J.R., Zhang, Q., Kodira, C.D., Zheng, X.H., Chen, L., Skup-ski, M., Subramanian, G., Thomas, P.D., Zhang, J., Gabor Miklos, G.L., Nelson, C.,Broder, S., Clark, A.G., Nadeau, J., McKusick, V.A., Zinder, N., Levine, A.J., Roberts,R.J., Simon, M., Slayman, C., Hunkapiller, M., Bolanos, R., Delcher, A., Dew, I.,Fasulo, D., Flanigan, M., Florea, L., Halpern, A., Hannenhalli, S., Kravitz, S., Levy,S., Mobarry, C., Reinert, K., Remington, K., Abu-Threideh, J., Beasley, E., Bid-dick, K., Bonazzi, V., Brandon, R., Cargill, M., Chandramouliswaran, I., Charlab,R., Chaturvedi, K., Deng, Z., Di Francesco, V., Dunn, P., Eilbeck, K., Evangelista, C.,Gabrielian, A.E., Gan, W., Ge, W., Gong, F., Gu, Z., Guan, P., Heiman, T.J., Higgins,M.E., Ji, R.R., Ke, Z., Ketchum, K.A., Lai, Z., Lei, Y., Li, Z., Li, J., Liang, Y., Lin, X., Lu,F., Merkulov, G.V., Milshina, N., Moore, H.M., Naik, A.K., Narayan, V.A., Neelam,B., Nusskern, D., Rusch, D.B., Salzberg, S., Shao, W., Shue, B., Sun, J., Wang, Z.,Wang, A., Wang, X., Wang, J., Wei, M., Wides, R., Xiao, C., Yan, C., et al., 2001. Thesequence of the human genome. Science 291, 1304–1351.

Visel, A., Rubin, E.M., Pennacchio, L.A., 2009. Genomic views of distant-actingenhancers. Nature 461, 199–205.

Wang, J., Liao, G., Chang, J., Nguyen, A., Guo, J., Chou, S., Hu, S., Bach, C., Allard, J.,Shafer, S., Puech, A., McPherson, J.D., Foernzler, D., Peltz, G., Usuka, J., 2005.Haplotypic structure of the mouse genome. In: Computational Genetics andGenomics: New Tools for Understanding Disease. Humana Press Inc., Totowa,New Jersey, pp. 71–83.

Wang, J., Peltz, G., 2005. Haplotype-based computational genetic analysis in mice. In:Computational Genetics and Genomics: New Tools for Understanding Disease.Humana Press Inc., Totowa, New Jersey, pp. 51–70.

Wright, S.D., Ramos, R.A., Tobias, P.S., Ulevitch, R.J., Mathison, J.C., 1990. CD14, areceptor for complexes of lipopolysaccharide (LPS) and LPS binding protein.Science 249, 1431–1433.

Yauch, L.E., Mansour, M.K., Shoham, S., Rottman, J.B., Levitz, S.M., 2004. Involvementof CD14, toll-like receptors 2 and 4, and MyD88 in the host response to the fungalpathogen Cryptococcus neoformans in vivo. Infect. Immun. 72, 5373–5382.

Yin, G.N., Jeon, H., Lee, S., Lee, H.W., Cho, J.Y., Suk, K., 2009. Role of soluble CD14in cerebrospinal fluid as a regulator of glial functions. J. Neurosci. Res. 87,2578–2590.

Yvert, G., Brem, R.B., Whittle, J., Akey, J.M., Foss, E., Smith, E.N., Mackelprang, R.,Kruglyak, L., 2003. Trans-acting regulatory variation in Saccharomyces cere-visiae and the role of transcription factors. Nat. Genet. 35, 57–64.

Zhang, L., Pagano, J.S., 2002. Structure and function of IRF-7. J. Interferon CytokineRes. 22, 95–101.

Zhang, X., Liu, H.-H., Weller, P., Tao, W., Wang, J., Liao, G., Zheng, M., Monshouwer,M., Peltz, G., 2011. In silico and in vitro pharmacogenetics: aldehyde oxidase

rapidly metabolizes a p38 kinase inhibitor. Pharmacogenomics J. 11, 15–24.

Zhou, L., Ivanov, I.I., Spolski, R., Min, R., Shenderov, K., Egawa, T., Levy, D.E., Leonard,W.J., Littman, D.R., 2007. IL-6 programs T(H)-17 cell differentiation by promot-ing sequential engagement of the IL-21 and IL-23 pathways. Nat. Immunol. 8,967–974.