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Biochemical and Biophysical Research Communications 366 (2008) 352–359

Functional grouping of osteoclast genes revealed throughmicroarray analysis

Guozhe Yang a,*, Mone Zaidi a,*, Weijia Zhang b, Ling-Ling Zhu a, Jianhua Li a,Jameel Iqbal a, Alex Varbanov c, Gary Gross c, Roger Phipps c, Bruce R. Troen d, Li Sun a

a Mount Sinai Bone Program, Mount Sinai School of Medicine, New York, NY 10029, USAb Bioinformatics Laboratory of Personalized Medicine Research Program, Department of Medicine, Mount Sinai School of Medicine, NY, USA

c Procter and Gamble Pharmaceuticals, Mason, OH, USAd Miami VAMC Geriatric Research Education and Clinical Center and Research Service, Department of Medicine,

University of Miami Miller School of Medicine, Miami, FL, USA

Received 14 November 2007Available online 3 December 2007

Abstract

We describe for the first time functional clusters of genes that are modulated during the differentiation of osteoclasts. Pathway anal-ysis was applied to gene array data generated from affymetrix chips hybridized to RNA isolated from RAW264.7 cells exposed toRANK-ligand (RANK-L) for 5 days. This analysis revealed major functional gene clusters that were either up- or down-regulated duringosteoclastogenesis. Some of the genes within the clusters have known functions, while others do not. We discuss herein the relevance ofthese functional gene clusters and their modulation to biological processes underlying the formation, function, and fate of osteoclasts.� 2007 Elsevier Inc. All rights reserved.

Keywords: Osteoclast; Microarray; Osteoclastogenesis; RANK-L

An osteoclast is formed from the hematopoetic stem cellthat initially committed its fate to become a monocyticlineage precursor, after which it is directed towards eitheran osteoclastic lineage, whereby highly multinucleated,resorption capable cells are formed, or the monocyte–mac-rophage lineage that is responsible for immune regulation[1,2]. The transcription factor c-fos is a key lineage-specificregulator, such that the deletion of c-fos selectively abro-gates osteoclast formation, while maintaining normal mac-rophage populations [3,4]. Downstream of this lineagediscrimination is the action of RANK-L, which directlyacts on the committed precursor to stimulate its differenti-ation to mature osteoclasts [5,6]. In this respect, anothercytokine, M-CSF, promotes the proliferation, and survival

0006-291X/$ - see front matter � 2007 Elsevier Inc. All rights reserved.

doi:10.1016/j.bbrc.2007.11.106

* Corresponding authors. Fax: +1 212 426 8312.E-mail addresses: guozhe.yang@mssm.edu (G. Yang), mone.zaidi@

mssm.edu (M. Zaidi).

of committed precursors, hence increasing the size of theprecursor pool for subsequent RANK-L action [5,6].

Once an osteoclast is formed, it attaches to bone matrixvia the interaction between its aVb3 receptor and RGDpeptides of collagen and non-collagenous proteins [7], fol-lowing which its ventral surface is thrown into complexfolds to form the ruffled border [8]. A number of criticalmolecular interactions involving c-src, cbl, and pyk2 under-lie subsequent osteoclast polarization [9]. Thereafter, allsecretory activities, including acid and enzyme release,become concentrated at the ruffled border, and the secre-tion of these products into the closed hemivacuole createsan acid-optimal pH for hydroxyapatite dissolution andmatrix degradation by the secreted cathepsins and metallo-proteinases [10]. While the broad significance of key molec-ular signals has been established in mediating these events,mainly through gene knockout studies, the intricate path-ways that regulate osteoclastogenesis and bone resorptionhave still not been completely elucidated.

G. Yang et al. / Biochemical and Biophysical Research Communications 366 (2008) 352–359 353

Several gene array studies have been carried out oneither maturing or mature osteoclasts. Most critical is thedescription of gene expression profiles in primary mouseosteoclasts treated with M-CSF and thereafter with M-CSF and RANK-L for up to 6 days [11]. The key outcomefrom this study was the demonstration that M-CSF up-reg-ulated mainly those genes, including the RANK receptor,which prime osteoclast precursors to RANK-L-induceddifferentiation. In addition, a multitude of genes encodingcytokines, chemokines, growth factors, signaling mole-cules, receptors, and transcription factors were shown tobe either up- or down-regulated by RANK-L in the pres-ence of M-CSF.

Here, we use the RAW264.7 cell line, which is uniquein that does not require exogenous M-CSF to assist inprecursor proliferation and survival. Instead, one canuse RANK-L alone, in the basal state, to examine effectson gene expression that are over and beyond thoseexerted by endogenously produced M-CSF. Using thesecells, and unlike previous studies, we have clusteredosteoclast genes based on the functionality of their prod-ucts. This has revealed five distinct sets of genes, ofwhich four are up-regulated and one is down-regulatedby RANK-L. These clusters include genes encoding for:(a) osteoclast differentiation and functional markers; (b)growth factors and chemokine receptors and ligands;(c) the immune responses; (d) processes involved inattachment, movement, and vesicular trafficking; and(e) the oxidative phosphorylation pathway. Some ofthese genes have well known functions, while others arebeing described for the first time, with tentativefunctions.

Materials and methods

Cell culture and RNA preparation. RAW264.7 cells were cultured at37 �C in 5% CO2 in a-MEM (Cellgro, VA) containing 10% fetal bovineserum (HyClone, UT). Cells (3 · 104) were seeded in six-well plates, andafter 2 h, were cultured with RANK-L (60 ng/mL) for 5 days. Total RNAwas isolated using the RNeasy Mini Kit (QIAGEN).

Microarrays and data analysis. cDNA was prepared from duplicateextracts of cells harvested at day 5 that were treated with RANK-L orvehicle. They were then hybridized to Affymetrix U74Av2 mouse genomearrays. Affymetrix probe sets with ‘‘Absent Calls’’ across all conditionswere eliminated from further statistical analysis. This excluded 5678 out of12422 probe sets. An ANOVA model with log (base 2) of the Affymetrixsignal as a response was fitted for each one of the 6744 Affymetrix probesets that remained after excluding Affymetrix Absent Calls. The modelparameter estimates were used in creating a list with differentiallyexpressed (DE) probe sets. The NLOGP quantity was equal to –log10 (P-value), where P-value is a summary measure of statistical test for differ-ential expression. The higher the NLOGP value, the stronger is the sta-tistical significance of the differential expression. A gene was considered tobe differentially expressed for a given comparison only if its NLOGPmeasure was greater than 3 and there was at least 1 (out of 2) AffymetrixPresent calls for the over-expressed condition in the comparison. Thedifferentially expressed genes were annotated with biological functions orcanonical pathways using the GAMA (Gene Annotator for MicroarrayAnalysis) annotation tool developed at the Bioinformatics Laboratory ofPersonalized Medicine Research Program at Mount Sinai School ofMedicine.

Quantitative real-time PCR. Gene expression levels were validated byquantitative real-time RT-PCR. Five micrograms of total RNA wasreverse transcribed into first strand cDNA. Three-step PCR (40 cycles)was performed in an ABI 7900HT (Applied Biosystems, Foster City, CA)in 20 mM Tris, pH 8.4, 50 mM KCl, 3 mM MgCl2, 200 lM dNTPs, 0.5·SYBR Green I (Molecular Probes, Eugene, OR), 200 nM each primer and0.5 U Platinum Taq (Invitrogen). Amplicon size and reaction specificitywere confirmed by agarose gel electrophoresis. Each transcript in eachsample was assayed three times and the median values were used to cal-culate the fold change ratios between experimental and control samples foreach gene used in this analysis. The results were calculated as the differencebetween each normalized reporter signal in a treated sample versus that inthe control.

Results and discussion

Eliminating probe sets with absent calls across all condi-tions removed 5678 of the 12422 probe sets on the chip. Ofthe remaining 6744 probe sets, we found 844 where theNLOGP values were >3 (NLOGP = log10 (P-value)) weredifferentially expressed. Of this, we first selected 15 knownosteoclast gene markers in order to validate the affymetrixassay. Fig. 1A shows that all of these genes, includingMMP-9, TRAP, cathepsin K, calcitonin receptor, macro-phage stimulating receptor 1, integrin b3, NFATc1 andothers were dramatically and expectedly up-regulated bybetween 2.65- and 133-fold. Real-time PCR of seven ofthese genes revealed up-regulation at both 3 and 5 daysof culture, confirming the array data Fig. 1B.

Our premise from the very outset was that, as an osteo-clast precursor begins to acquire resorption machinery;genes involved in bone remodeling will be up-regulated,while those related to immune functions will be down-mod-ulated, considering that the cells have the potential ofdiverting to become macrophages. Thus, genes that wereup-regulated included those that encode molecules with apotential role in osteoclastic bone resorption, namely che-motaxis of osteoblasts and osteoclasts; attachment, move-ment, and vesicular trafficking in osteoclasts duringresorption; energy production through oxidative phos-phorylation during active acid secretion and enzymerelease; as well as regulatory receptor subunits.

Fig. 2A shows a functional cluster that incorporatesgenes whose products are involved in inducing the che-motaxis of osteoclasts, as well as of osteoblasts to thesite of osteoclastic resorption. Most notable is the detec-tion by microarray of PGDFa, PGDFb, VEGFB, andVEGFC, which have never previously been reported inosteoclasts, but have known chemotactic properties.Interestingly, however, VEGFA, which has been reportedto be expressed by osteoclast [12–14] and has an estab-lished role in endochondral bone formation and osteo-clast chemotaxis, was not similarly detected. PGDFsare thought classically to be released from bone matrixupon osteoclastic bone resorption as chemotactic andgrowth signals for incoming osteoblasts [15]. Expressionof PDGFb has been detected in osteoclasts [16], butthe expression of PDGFa has not, to our knowledge,been reported previously. Derived from osteoclasts, these

Fig. 1. Osteoclast molecular and functional marker genes up-regulated by RANK-L. As described in Materials and methods, mouse RAW264.7 cells werestimulated by RANK-L and the differentiated cells were collected for RNA extraction and then reverse transcribed into cDNA, which was used for thesubsequent microarray analysis and real-time PCR. (A) Osteoclast markers and functional genes were up-regulated in microarray analysis. (B)Osteoclastogenesis was validated by real-time PCR of the RAW264.7 cells that were stimulated by RANK-L for 3 and 5 days.

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molecules could have identical roles to that seen in othertissues, but their precise function are likely to be estab-lished only through the use of inducible osteoclast-spe-cific knockout mice. A high expression of chemokine(C–C motif) receptor 1 (Ccr1) is nevertheless not unex-pected in view of its recently established function in pro-moting the migration of osteoclasts through an actiondownstream of NFATc1 [17]. Ccr1 activation also under-lies the profound osteoclastogenesis and extensive osteol-ysis in multiple myeloma via its interaction with theabundantly produced ligand MIP1a [18]. The modest,2-fold up-regulation of chemokine (C–X–C motif) recep-tor 3 (Cxcr3) is again not unexpected, as its expressiondeclines in human osteoclasts cultured on calcium phos-phate substrate [19]. Other Cxcrs and their ligands, pre-viously detected in human osteoclasts [19], were notup-regulated in RAW 264.7 cells. Likewise, the role ofother molecules within this functional cluster, namelythe dramatically up-regulated macrophage stimulating 1receptor (Mst1r) (c-met-related tyrosine kinase) and themore modestly stimulated growth hormone receptor(Ghr) and TNF receptor associated factor 1 (TRAF1)are speculative at best. Mst1r is a tyrosine kinase relatedto c-met, which is the receptor for hepatocyte growthfactor (HGF) and is expressed by osteoclasts [20,21].Since HGF can substitute for M-CSF in supportingosteoclastogenesis [21], it is possible that the increasedexpression of Mst1r may mediate enhanced responsive-ness of osteoclast progenitors to growth factors similarto HGF. The TRAF family of molecules, in particular

TRAF2, TRAF5, and TRAF6, has been shown to medi-ate RANK-L stimulated signaling pathways in osteo-clasts [22]; our data raise the possibility that TRAF1may also be important in the response to RANK-L dur-ing osteoclastogenesis.

Fig. 2B depicts a functional cluster of genes that areknown to be involved in osteoclasts and other cells in theprocesses of cell attachment, motility and vesicular traffick-ing. Notable is the up-regulation of both exclusively uti-lized av and b3 receptor integrins which mediate thetightly adhesive seal between the osteoclast’s underfaceand the bone matrix proteins [7]. After its attachment, anosteoclast undergoes intense motility. Components ofosteoclast motility have been documented earlier, whichcomprise mainly those that contribute to cell movement,margin ruffling, and granule extrusion [7,8]. Extrusion ofgranules requires precise cytoskeletal remodeling involvingproteins such as actinin a1, vinculin, and gelsolin. Gelsolin,for example, is known to complex with Pyk2, Src, and PI-3-kinase during podosome formation [23,24]. The genetic dis-ruption of gelsolin in mice thus results in reduced podo-some formation and osteoclasts with poor resorptiveactivity [25]. Other proteins, such as destrin, coronin, andscinderin, may have similar activities during podosome for-mation and actin remodeling.

There is a dramatic �20-fold increase in expression ofnon-muscle myosins 1D and X, which is surprising. Todate, myosin II isoforms have been described in osteoclastssubjected to calcitonin-induced retraction or the R effect[26–28]. Likewise, the intracytoplasmic microinjection of

Fig. 2. Gene expression profiles through pathway analysis shows (A) signaling proteins and receptors that are involved in growth, survival, andchemotaxies and (B) proteins involved in attachment, movement, and vesicular trafficking that were up-regulated in differentiated RAW264.7 cells.

G. Yang et al. / Biochemical and Biophysical Research Communications 366 (2008) 352–359 355

anti myosin II antibodies inhibits osteoclastic bone resorp-tion [27]. On the other hand, kinesins are ubiquitously dis-tributed in cells undergoing intense vesicular trafficking,where they associate with microtubules. Despite the intensemotility and granule movement that characterize osteoclas-tic resorption, there no reports yet, but for our own, for arole for any kinesin in the osteoclast. We find a modest, butsignificant elevation of kinesins 3C and 1C, as well as theirbinding partner, Trak2, in mature cells. In contrast, thereare only few reports for the existence of transferrin recep-tors in the osteoclast [29]. Further functional studies aretherefore required to understand the role of the expressed

myosins, kinesins, and the transferring receptor in osteo-clast formation and function.

Fig. 3 shows the functional cluster of genes responsi-ble for oxidative phosphorylation, which to our knowl-edge, have never been described in osteoclast. Thevarious components of osteoclast motility involve energyexpenditure, as does the active, ATP-dependent secretionof H+ ions via vacuolar H+-ATPase. In order to dropthe pH to 4 U within a resorptive hemivacuole unre-stricted acid secretion is required. This low pH is alsoa requisite for the action of acid-optimal proteolyticenzymes, namely cathepsin K, MMP-9 and others. Here,

Fig. 3. The key enzymes in all five complexes of the oxidative pathway and the vesicular ATPases involved in acid secretion were up-regulated indifferentiated RAW264.7 cells. (A) A representation of the mitochondrial oxidative pathway. The important functional components in all five complexesof the oxidative pathway were up-regulated that are indicated in red. (B) Incorporated gene expression profile through pathway analysis shows that keyenzymes in oxidative pathway and the vesicular H+ATPase involved in acid secretion were up-regulated.

356 G. Yang et al. / Biochemical and Biophysical Research Communications 366 (2008) 352–359

we show through pathway analysis that key enzymes forall five mitochondrial complexes are up-regulated by�2-fold (Fig. 3A). In addition, in line with the require-ment for hemivacuole acidification, the acid-secretingapparatus of the osteoclast is also up-regulated by upto �5-fold. Most notably, components of both subunitsof the V-ATPase, V1 and V0 (Fig. 3B), as well as the

H+–Cl� antiporter, Clcn7 (Fig. 1A), are all up-regulated.

Finally, consistent with our original hypothesis thatimmune-related molecules should in fact decline withprecursor differentiation towards an osteoclast and awayfrom a macrophage phenotype, we delineated a func-tional cluster that would contain all immune receptors

Fig. 4. Gene expression profile through pathway analysis demonstrates that molecules involved in immune responses were down-regulated indifferentiated RAW264.7 cells.

G. Yang et al. / Biochemical and Biophysical Research Communications 366 (2008) 352–359 357

and ligands and that showed a >2-fold decrement inexpression with RANK-L (Fig. 4). The most prominentdeclines were seen in the CD14 antigen, toll-like recep-tor-6, TNF, and its receptor TNF receptor 1B, Fcreceptor 11b, STAT-1, and several interferon-inducedproteins, all of which are critical modulators of macro-phage function. Some have roles in osteoclast activation,although the physiologic relevance of these cytokines inbone remodeling remains uncertain. For example,STAT-1 acts downstream of gp130, the co-receptor forboth osteoclastogenic cytokines, IL-6 and IL-11 [30].Nonetheless, while both IL-11 and IL-6 are osteoclasto-genic, their role in physiologic osteoclastogenesis ispoorly understood. IL-6- or IL-6 receptor-deficient micehave been found not to reveal a basal skeletal pheno-type, indicating their non-essential function in physio-logic osteoclast formation [31]. However, excessive IL-6production in multiple myeloma and Gorham-Stout’sdisease causes profound bone loss [32,33]. Likewise,the action of TNF via the TNF receptor 1 is osteoclas-togenic; it stimulates precursor proliferation directly andosteoclast differentiation by synergizing with RANK-L[34]. These roles are however not primary, but are sig-nificant in pathologic states. When TNF production

rises in rheumatoid arthritis and Crohn’s disease, unre-stricted bone resorption and bone loss ensue [35]. Thedown-regulation of interferon-related proteins, interferonreceptors, and interleukin-18 are all consistent with theirexpected roles in osteoclast physiology. Interferon cinhibits osteoclast differentiation by promoting the deg-radation of TRAF-6 and also inhibits cathepsin Kexpression [36], while interleukin 18 does so by inducingGM-CSF production [37]. Finally, signaling through theFc receptor c (I and III) on the osteoclast serves topotentiate RANK-L effects. Fc receptor c IIb plays aninhibitory role in cartilage destruction during arthritis[38]; however, its expression during normal and diseasestates needs to be further addressed. Thus, not unex-pectedly, all immune-related molecules that we couldcapture on microarray declined by several-fold as afunction of osteoclast maturation.

In summary, our data lay the foundation for futureexperiments that should, using knockout mice and shRNAtechnologies, provide evidence or not, of a potential rolefor novel molecular targets identified in this study. Thismight ultimately lead to the development of agents thatcould modify such targets in a way to reduce resorptionin states of pathologic bone loss.

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Acknowledgments

This study was supported by the National Institutes ofHealth (AG14197, DK70526, AG23176, to M.Z.) and bythe Alliance for Better Bone Health.

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