The generation and properties of human macrophage ... - CiteSeerX

Uncorrected Version. Published on January 30, 2009 as DOI:10.1189/jlb.1108689

The generation and properties of human macrophage populations from hemopoietic stem cells Kerrie J. Way,* Hang Dinh,* Martin R. Keene,* Kirby E. White,* Felix I. L. Clanchy,* Patricia Lusby,† John Roiniotis,* Andrew D. Cook,* A. Ian Cassady,† David Curtis,‡ and John A. Hamilton*,1 *Department of Medicine and CRC for Chronic Inflammatory Diseases, The University of Melbourne, Royal Melbourne Hospital, Parkville, Victoria, Australia; †Department of Biochemistry and Molecular Biology and CRC for Chronic Inflammatory Diseases, Institute for Molecular Biosciences, The University of Queensland, Brisbane, Queensland, Australia; and ‡Clinical Hematology and Medical Oncology, Bone Marrow Transplant Unit, Royal Melbourne Hospital, Parkville, Victoria, Australia

Abstract: Information about the development and function of human macrophage lineage populations, such as osteoclasts, is limited because of the lack of defined in vitro systems for their largescale generation. Two M-CSF-containing cytokine cocktails were found under serum-free conditions to expand dramatically and to differentiate over time human CD34ⴙ hemopoietic stem cells into nonadherent and adherent macrophage populations. These populations exhibited increasing degrees of maturity over a 3-week period characterized by morphology, surface marker expression (CD11b, CD86, CD64, CD14, and c-Fms), phagocytic function, and gene-expression profiling using quantitative PCR and microarray analysis (principal component analysis, k-means clustering, and gene ontology classification). As assessed by the last criterion, the adherent population obtained at 3 weeks from the one protocol tested had high similarity to the well-studied peripheral blood monocyte-derived macrophages. The one population tested could be induced to differentiate into osteoclasts in the presence of M-CSF and receptor activator of NF-␬B ligand, as judged by morphology, gene expression, and bone-resorbing ability. In addition to the large numbers of macrophage lineage cells able to be produced, this replicating system may be suitable for the molecular analysis of macrophage lineage commitment and progression and for gene targeting and delivery. J. Leukoc. Biol. 85: 000 – 000; 2009. Key Words: M-CSF 䡠 differentiation 䡠 gene expression profile

tion and differentiation. The molecular mechanisms governing the developmental program for human macrophage populations are not well understood, as there are inadequate in vitro systems capable of their generation in large numbers under defined conditions. PBMCs have been the most commonly used source of CD14⫹ monocytes, from which primary human macrophages for in vitro study have been produced, usually using serum-containing cultures; however, only a small percentage of circulating monocytes is capable of expansion [3–5]. M-CSF (or CSF-1) is often used for such maturation, as there is evidence that it is an important regulator of tissue macrophage development [6, 7]. Depending on the milieu, certain monocyte/macrophage populations can also be converted into other functional phenotypes, such as dendritic cells (DCs) and osteoclasts, but again, the mechanisms controlling these developmental changes have not been clarified. The use of CD34⫹ human hemopoietic stem cells (HSCs) from bone marrow, cord blood, or mobilized adult blood as an effective precursor cell source has been demonstrated, and depending on the cytokine and culture conditions adopted, various hemopoietic lineage cell populations can be generated [8 –11]. The in vitro expansion of human CD34⫹ HSCs into immature and mature DC subsets has been studied with, for example, GM-CSF, TNF, IL-4, stem cell factor (SCF), and fetal liver tyrosine kinase 3 ligand (Flt3L) in the presence of FBS, directing differentiation along this pathway [8, 10, 12, 13]. Although such select cytokine/culture conditions for the production of DCs from CD34⫹ cells have been described, a similar analysis of cell growth, phenotype, and function of CD34⫹-derived human macrophages has been limited. Unlike in the mouse, where adherent and highly purified macrophages can be generated rapidly in vitro from bone marrow progenitors by proliferation and differentiation, simply following culture in M-CSF alone [14, 15], human precursor cells cultured under

INTRODUCTION Monocytes/macrophages are heterogeneous populations that play key roles, for example, in innate immunity, chronic inflammation, wound-healing, and tumor progression [1, 2]. They are derived in turn from bone marrow precursors by prolifera-

0741-5400/09/0085-0001 © Society for Leukocyte Biology

1 Correspondence: University of Melbourne, Department of Medicine, Royal Melbourne Hospital, Clinical Sciences Building, Royal Parade, Parkville, Victoria, 3050, Australia. E-mail: [email protected] Received November 11, 2008; revised December 22, 2008; accepted December 30, 2008. doi: 10.1189/jlb.1108689

Journal of Leukocyte Biology Volume 85, May 2009

Copyright 2009 by The Society for Leukocyte Biology.

1

similar conditions tend to differentiate rather than expand [16]. Thus, other cytokines/growth factors, such as SCF and Flt3, will be needed as additional stimuli [8, 9, 11–13, 16 –19] if reasonable numbers of macrophage lineage populations are to be derived from the limited supply of human progenitors available from sources such as bone marrow and mobilized blood; however, such studies with CD34⫹ HSCs have also usually reported that such “homogeneous” or restricted differentiation was associated with relatively limited expansion of the progeny [16 –19]. The main goal of the research described below was to generate and characterize large numbers of human macrophage lineage populations that would be appropriate for subsequent analysis into the regulatory control mechanisms governing this developmental program, including conversion to related cell phenotypes such as osteoclasts. We also wanted to develop a serum-free system, which should lead to better reproducibility, a clearer understanding of the contribution of specific stimuli, and “cleaner” populations for any subsequent in vivo studies that may eventuate. Our approach was to assess the effects of diverse cocktails containing certain hemopoietic regulators. Based on literature findings and our own preliminary studies, we tested in detail certain combinations of multilineage and more restricted hemopoietic growth factors. We report that we were able to define two media and culture conditions that generated large numbers of replicating macrophage lineage populations with different degrees of maturity, which we characterized by surface marker expression, classical macrophage functions, gene expression profiling, and differentiation into osteoclasts. Encouragingly, we were able to produce cells with a gene-expression profile similar to that for peripheral blood monocyte-derived macrophages (MDM).

MATERIALS AND METHODS CD34⫹ cell isolation Leukapheresis product was obtained from adult donors or oncology patients receiving G-CSF treatment to mobilize bone marrow cells into the peripheral circulation. Informed consent was obtained from all participants, and The Royal Melbourne Hospital Human Research Ethics Committee (Australia) approved the studies. Mononuclear cells were isolated by Ficoll-Paque separation. Cells were resuspended in X-VIVO 10 (serum-free with gentamicin; BioWhittaker, Walkersville, MD, USA) containing 1% Buminate (human albumin; Baxter, Deerfield, IL, USA) for overnight storage at 4°C. CD34⫹ cells were then isolated by MACS using an indirect CD34 microbead kit (Miltenyi Biotec, Auburn, CA, USA). Greater than 90% of cells were CD34⫹ (flow cytometry).

present. After nonadherent cell collection, adherent cells were collected by incubation with cold PBS containing 1% FBS and 1 mM EDTA for 20 min on ice. This step was repeated until adherent cells were removed. X-VIVO 10 medium with 0.5% Buminate was used as the “Base medium”, to which the following recombinant human cytokines/growth factors were added as required: M-CSF (5000 U/ml; Chiron, Emeryville, CA, USA), GMCSF (0.03 ␮g/ml; R&D Systems, Minneapolis, MN, USA), SCF (200 ng/ml; Amgen, Thousand Oaks, CA, USA), IL-3 (10 ng/ml; Amgen), IL-6 (10 ng/ml; Chemicon International, El Segundo, CA, USA), and Flt3L (50 ng/ml; R&D Systems). Medium A was made up of Base medium with added M-CSF, IL-3, IL-6, SCF, and Flt3L (for 7 days only). Medium B consisted of added M-CSF, GM-CSF, IL-6, SCF, and Ft3L.

Peripheral blood MDM Buffy packs from healthy volunteers were obtained from the Australian Red Cross Blood Service. Mononuclear cells were obtained (Ficoll Paque) and CD14⫹ cells isolated by MACS using the StemSep human CD14⫹ isolation cocktail (Stem Cell Technologies, Canada). For MDM preparation, CD14⫹ cells (4⫻106) were plated onto 10 cm tissue-culture plates in RPMI medium (Invitrogen, Carlsbad, CA, USA) containing 10% FBS (Invitrogen), penicillin/ streptomycin (100 U/ml), Gluta-Max-1 (2 mM; Invitrogen), and 5000 U/ml M-CSF. Adherent cells (MDM) were harvested at Day 10.

Differential cell staining and light microscopy Cells were centrifuged onto a glass microscope slide (cytospins). Differential staining was performed using a Diff Quik stain set. Cell cultures were viewed with a Zeiss Axioskop 2 microscope.

Flow cytometric analysis Surface marker analysis was as before [4]. Data acquisition was performed using a FACSCalibur flow cytometer (Becton Dickinson, San Jose, CA, USA), set to collect a minimum of 104 events, and data analyzed using Becton Dickinson CellQuest Pro 5.1.1 software. Forward-scatter versus side-scatter dot profiles were used to gate out dead cells and debris. The following mAb were used (all BD Biosciences, San Jose, CA, USA): CD34-FITC, CD11b-PE, CD86-PE, CD64-FITC, CD14-FITC, CD1a-allophycocyanin, CD83-PE, CD15-PE, and CD3-PE. The binding of M-CSF (CSF-1) to its receptor c-Fms can result in receptor internalization [20, 21], and we found this may reduce the intensity of surface staining. Therefore, prior to staining for c-Fms-PE (3-4A4; Santa Cruz Biotechnology Inc., Santa Cruz, CA, USA), cells were fixed and permeabilized using a Cytofix/Cytoperm kit (BD Biosciences), such that surface and intracellular c-Fms staining could be assessed.

Phagocytosis assay The phagocytic ability of was assessed by flow cytometry by the ability to phagocytose fluorescent microspheres (1 ␮m; Molecular Probes, Eugene, OR, USA). Analyses were performed using histogram plots (fluorescence 2 vs. cell counts), and Peaks 1– 4 represent cells that had consumed the equivalent number of beads, and the remaining peak(s) indicate cells containing more than four beads. Values shown are the sum of all cells that had engulfed beads, the majority of which consisted of cells that had more than four beads/cell.

CD34⫹ cell culture and media preparation

RNA isolation and real-time PCR

CD34⫹ cells were plated at a density of 5 ⫻ 104 cells in 1 ml medium using 24-well bacteriological plates (Iwaki, Holliston, MA, USA) and incubated for 1 week at 37°C before collection for counting and replating. Some cells were replated at a density of 1 ⫻ 105/well using a 24-well plate or 1.2 ⫻ 106/10 cm plate. From Day 7, the medium was exchanged every 2–3 days by demidepletion. From Week 2 onward, medium was exchanged by demi-depletion leading to removal of half of the nonadherent cells. In general, the cell population was nonadherent for up to 2 weeks, and from 2 to 3 weeks, adherent cells became apparent. By 3 weeks, nonadherent and adherent cells were

RNA was isolated as before [15]. For some experiments, RNA was collected and purified according to the manufacturer’s protocol outlined for the RNeasy Mini Kit (Qiagen, Valencia, CA, USA). The concentration of RNA and the 260:280-nm ratio were determined using a NanoDrop ND-1000 spectrophotometer. cDNA was prepared from total RNA as before [15]. Real-time quantitative PCR (qPCR) was performed on 10 ng cDNA/reaction using the following Taqman gene expression assays (Applied Biosystems, Foster City, CA, USA): CD11b, receptor activator of NF-␬B (RANK), M-CSF, c-fms, vitronectin receptor [integrin, ␣ V (ITGAV)], tartrate-resistant acid phosphatase (TRAP),

2


http://www.jleukbio.org

cathepsin K, calcitonin receptor, and NFATc1 with 18S as the control gene. Plates (384-well) were read on an ABI Prism 7900H sequence detection system, followed by analysis using ABI Prism SDS 2.1 software. The comparative threshold method for relative quantification was used and results expressed as fold change.

Microarray hybridization, quantification, and analysis Microarray experiments were performed following recommended protocols supplied by Agilent Technologies (Santa Clara, CA, USA). RNA was isolated from three independent cell preparations, each derived from a single donor. Adherent CD34⫹-derived macrophages at 3 weeks (Medium B-derived) were compared with CD14⫹-derived macrophages at Day 10 (MDM). RNA integrity was analyzed using an Experion automated electrophoresis station (Bio-Rad, Hercules, CA, USA). Total RNA (1 ␮g) was used as starting material, which was amplified using the Low RNA Input Linear Amplification Kit (Agilent Technologies). The labeled cDNA was purified using an RNeasy Mini Kit (Qiagen), and eluted, labeled cRNA was quantified using a NanoDrop ND1000 spectrophotometer. Following fragmentation, the cRNA was hybridized to a whole human genome microarray (Agilent Technologies) containing 43,376 probes corresponding to 41,264 transcripts. Microarrays were then scanned using a DNA microarray scanner, Model G2565A (Agilent Technologies). Data extraction was conducted using analysis software, Feature Extraction (Agilent Technologies), and then analyzed using Genespring GX software, Version 7.3.1 (Agilent Technologies). Normalization was performed according to the Agilent Feature Extraction One-Color Protocol. Filtering was applied, whereby probes that were considered “absent” in at least seven of the 15 samples were excluded, generating a list of 27,164 genes. Principal component analysis (PCA) [22], hierarchical, and k-means clustering [23] were performed to determine expression trends, with squared Pearson correlation as similarity measurement. Genes showing greater than twofold differences and statistical significance with a false discovery rate of 0.05 were identified as being differentially expressed, and differentially expressed genes were subjected to Gene Ontology (GO) analysis for biological process and molecular function at Levels 3 and 4 [24]. Significant ontologies were calculated using a Fisher exact test, and P values ⬍0.05 are reported. The dataset and technical information compliant with minimum information about a microarray experiment (MIAME) [25] can be found at the Gene Expresion Omnibus website (www.ncbi.nlm.nih. gov.geo), Accession Number GSE8934.

Osteoclast differentiation and assay Nonadherent Medium B-derived CD34⫹ cells at 2 weeks were replated at 4 ⫻ 105 cells/well on a 24-well plate. Cells were cultured in the indicated medium (500 ␮l) with or without RANK ligand (RANKL; 50 ng/ml; Peprotech, Rocky Hill, NJ, USA). Cultures were demi-depleted every 2–3 days and fresh RANKL applied. Following 2 weeks of culture when multinucleated cells could be seen, adherent cells were harvested for RNA or stained for TRAP, which was performed as before [26]. TRAP⫹-multinucleated cells (more than two nuclei) were assessed using light microscopy. The presence of functional osteoclasts was assessed by the ability of cells to resorb bone. Fresh slices of bovine cortical bone (4⫻4 mm) were obtained using a diamond-toothed saw and were stored at –20°C until use. Prior to use, bones were polished on wet/dry sandpaper, followed by alum powder, and then cleaned by sonication. Nonadherent Medium B-derived CD34⫹ cells at 2 weeks were replated at 2 ⫻ 105 cells/well on a 48-well plate containing the bone slices, which were recovered after 5 weeks, and resorption pits were revealed by application of permanent black ink followed by rubbing the bone surface on paper toweling. The number of pits formed per slice was counted manually using light microscopy.

RESULTS Cytokine-induced expansion and differentiation of CD34⫹ cells into monocyte/macrophage-like cells Cytokine cocktails

The selection of cytokine combinations to promote CD34⫹ cell expansion and differentiation into macrophages was determined initially by cell counting, adherent cell formation, and differential cell staining. It is known that stem cell expansion is enhanced when several hemopoietic growth factors are used together (e.g., SCF, Flt3L, IL-3). In contrast, cellular differentiation may only require the presence of one or two select factors (e.g., M-CSF). Our preliminary studies showed that the greater the number of such cytokines included within the cocktail, the greater the expansion of the population (data not shown). However, more cell expansion per se did not necessarily reflect the potential to generate adherent cells, i.e., most likely macrophages. We observed that some cytokine combinations (e.g., GM-CSF, IL-3, SCF, IL-6, Flt3L) induced a large expansion into a mononuclear population (466-fold at Day 12) but without generating adherent cells, and alternatively, other combinations gave rise to an adherent mononuclear population but with poor expansion (e.g., M-CSF, SCF, and IL-6; data not shown). Cell expansion

Using the background information listed above, we selected two medium cocktails for a detailed comparison, namely Medium A (M-CSF, SCF, IL-3, IL-6, and Flt3L), and Medium B (M-CSF, GM-CSF, IL-6, SCF, and Flt3L). M-CSF was included in both cocktails, as it promotes macrophage differentiation and as we wanted to compare our generated populations to blood MDM. GM-CSF was included in the latter, as it has strong, proliferative effects on CD34⫹ cells, has been reported to prime cells for M-CSF responses to form CFU-macrophage [27], and can generate efficient osteoclast precursors in the mouse [26]; in addition to the substitution of GM-CSF for IL-3 in Medium B, Flt3L was continually present in the latter but for only 1 week in Medium A. After 1 week, there was comparable expansion in both cocktails, and after 2 weeks, Medium B enhanced the nonadherent cells by 180-fold compared with a 64-fold increase with Medium A (P⬍0.05; Fig. 1A). At 3 weeks, nonadherent and adherent populations were present in the culture dishes, and the total cell numbers were still increasing. At this time-point, a significantly larger number of adherent cells was generated in Medium B (2.5⫾0.9⫻106/10 cm plate) compared with Medium A (3.3⫻105⫾0.5/10 cm plate; P⬍0.05; Fig. 1B). These results suggest that Medium B is capable of producing more adherent cells than Medium A as a result of its ability to expand the precursor population better, from 1 week onward.

Statistics Morphology Statistical comparisons between groups were performed using unpaired Student’s t-test or two-way ANOVA, followed by Bonferroni or Dunnetts post-test (GraphPad Prism 4 software). P values ⬍0.05 indicate significance. All values shown are mean ⫾ SEM for n number of patient cell sets.

Regarding morphology, the small CD34⫹ blast-like cells at the start of the cultures developed by 3 weeks in Medium A partly into a relatively heterogeneous population of nonadherent cells

Way et al. CD34ⴙ-derived macrophage lineage cells

3

(monocyte-, macrophage-, and promyelocyte-like), and in Medium B, the equivalent population was more homogenous, consisting mainly of monocyte-like cells and with the occasional macrophage-like cell present (Fig. 1C). For both media, the adherent populations were similar, consisting of many large-spread cells and the occasional elongated cell (Fig. 1D). Macrophage lineage marker analysis

After 3 weeks culture in both media, the expression of some macrophage lineage markers was measured in nonadherent and adherent populations; surface CD34 could not be detected to any significant extent at this time-point in any population (Fig. 2, A and B). For the nonadherent cells, culture in Medium B led to more (P⬍0.05) CD11b, CD86, CD64, CD14, and c-Fms expression than for culture in Medium A, measured as percentpositive cells (Fig. 2A) and mean fluorescence intensity (geometric mean ratio; Fig. 2B); similar findings for the two conditions were observed for the adherent cell populations. c-Fms (M-CSFR) is required for macrophage development [28 –30], and for its expression, there was a trend toward a difference between the media for both populations; in any case, it is possible that its levels may be underestimated as a result of internalization by exogenous and/or endogenous M-CSF [20, 21]. In support of this suggestion, increased M-CSF mRNA expression was observed in 3 week-adherent cells (Fig. 3A), and secreted M-CSF was detected (ELISA) from 3 weekadherent cells from Medium B cultures following medium replacement with Base medium alone (data not shown). c-fms and CD11b mRNA expression levels over a time-course for nonadherent cells and for the adherent cells at 3 weeks can be seen in Figure 3, B and C, respectively, and are consistent with the surface levels (Fig. 2, A and B), and the adherent population from Medium B cultures tend to have the highest expression, particularly for CD11b. Given that some of the above markers may be expressed to some degree on granulocytic and DCs, additional staining for CD1a, CD83, CD15, and CD3 was performed. Little to no staining was observed for cells derived from culture in either medium (Fig. 2, A and B). These results support the conclusion that monocyte/macrophage-like cells are formed in our cultures and to a greater degree in Medium B. Phagocytosis

Fig. 1. Cytokine effects on cell expansion and differentiation. (A) Expansion of CD34⫹ cells in Medium A (M-CSF, SCF, IL-3, IL-6, and Flt3L) compared with Medium B (M-CSF, GM-CSF, SCF, IL-6, and Flt3L) over 2 weeks. Data are expressed as fold-change from the cell number plated at Day 0 (105 cells at Day 0; Materials and Methods). (B) Adherent cell number/10 cm plate after 3 weeks. (A and B) Values are mean ⫾ SEM for n ⫽ 5– 6 patient samples; *, P ⬍ 0.05, versus Medium A group. (C) Nonadherent cells at Day 0 and at 3 weeks were differentially stained following centrifugation. Arrows indicate examples of macrophage-like cells; 300⫻ original magnification. (D) Adherent cell morphology on culture plates at 3 weeks as viewed by light microscopy; 100⫻ original magnification.

4


Macrophage-like function was also assessed by phagocytic activity. As measured by fluorescent latex bead uptake, the percentage of phagocytic cells increased dramatically in the nonadherent population, particularly after culture in Medium B, as well as in the adherent populations for both media (Fig. 3D).

Microarray comparison of the transcriptional profile of CD34⫹cell-generated adherent cells with human blood monocytes and MDM To gain further evidence for the “macrophage-like” nature of our CD34⫹-generated cells and also to characterize them more thoroughly, we performed a microarray analysis comparison of 2 week-nonadherent, 3 week-nonadherent, and 3 week-adherent populations with human blood monocytes and with MDM;


Fig. 2. Flow cytometric analysis of cell phenotype. Nonadherent and adherent cells derived from Medium A and Medium B at 3 weeks were stained with the indicated surface markers for flow cytometric analysis (Materials and Methods). Data are expressed as (A) percent-positive cells or (B) ratios of the geometric mean fluorescence. Values are mean ⫾ SEM for n ⫽ 3–7 patient samples; *, P ⬎ 0.05, versus the corresponding Medium A group.

the latter is a widely used model for human macrophages, and they are often generated by culturing monocytes for a few days in M-CSF (see, for example, ref. [7]). In total, 26,374 genes were assessed as being present following detection call and spot assessment analysis (Materials and Methods). PCA revealed that although generated quite differently, MDM and 3 week-adherent cells were the most similar in gene expression profiles (Fig. 4); there was only a 3% difference in the genes expressed by these cell populations (data not shown). Similarly, 2 week- and 3 week-nonadherent populations shared marked similarities in their transcriptional program. We performed k-means clustering to determine expression trends, using all differentially expressed genes. Three main clusters were identified (Fig. 5), which contained genes that were differentially expressed, compared with all other sample groups, in CD14⫹ monocytes (Cluster 1), in 2 week- and 3 week-nonadherent cells (Cluster 2), or in 3 week-adherent cells and MDM (Cluster 3). These clusters confirm the trends identified in Figure 4. We then examined the GO classifications of the genes identified in these clusters, focusing on biological processes and molecular function categories that have been described as associated with macrophage differentiation [7, 30] (Fig. 6).

These categories include transcription, lipid metabolism, membrane receptors, cell cycle, carbohydrate metabolism, immune response, and macromolecule biosynthesis. Examination of these GO categories from three separate CD34⫹-derived preparations and three separate experiments involving monocyteto-MDM conversion revealed distinct patterns of gene expression in MDM that were closely matched in 3 week-adherent cells, as well as trends in the differentiation of monocytes-toMDM that appear to be reflected in the progression from 2 week-nonadherent to 3 week-adherent cells (Figs. 1 and 2). Importantly, these trends concurred with previous reports for the monocyte-to-MDM transition, wherein genes belonging to GO classifications, such as transcription, were down-regulated with macrophage differentiation, whereas those, such as lipid metabolism, were up-regulated [7, 30]. The overall concordance of the patterns between the different experiments can also be noted. In Table 1, a list is compiled of the most differentially expressed genes between MDM and monocytes, along with the relative expression among our three CD34⫹ cell-generated populations and the monocytes. The categories chosen to be represented are from the above GO classifications and from key functions of macrophage populations, which change with mat-


5

Fig. 3. qPCR analysis of macrophage-associated genes and phagocytic activity. (A–C) qPCR analysis of nonadherent (NAD) and adherent (AD) cells derived from Medium A (open bars) and Medium B (closed bars) over a 3-week time-course (see Fig. 1, A and B, for culture conditions). Expression levels for the indicated genes are shown relative to levels measured at Day 0. Values are mean ⫾ SEM for n ⫽ 4 patient samples; *, P ⬍ 0.05, versus the corresponding Medium A group at that time-point. (D) The phagocytic ability of nonadherent and adherent cells to engulf fluorescent beads was determined by flow cytometry (Materials and Methods). The same culture conditions as Figure 1, A and B, were used. The percentage of the population that had phagocytosed one or more beads is shown. Values are mean ⫾ SEM for n ⫽ 3–5 patient samples; *, P ⬍ 0.05, versus the corresponding Medium A group.

uration, such as adhesion and phagocytosis. It can be seen, in general, that consistent with the data in Figures 4 – 6, the values for the ratio of 3 week-adherent cells:monocytes are closest to the values for the ratio of MDM:monocytes compared with those for the ratios of 2 week- and 3 week-nonadherent cells:monocytes. Of note, the mRNA expression of the transcription factors CEBPA and MAF, which are implicated in the control of macrophage differentiation [30, 31] (see Discussion), was up-regulated and expressed most highly in the more mature 3 week-adherent cells and MDM compared with CD14⫹ monocytes; on the other hand, other transcription factors, such as MAFF, CEBPB, and HIF1A, were down-regulated (see also ref. [30]). It can also be seen that genes associated with lipid and fatty acid metabolism (for example, LRP5, PTGDS, and

Fig. 4. PCA of the transcriptional profiles of monocyte/macrophage populations. PCA was carried out on the 26,374-filtered genes to examine the variability in the dataset for monocytes, MDM, and CD-34⫹ cell-derived populations: 2 week-nonadherent, 3 week-nonadherent, and 3 week-adherent. Shown are PC 1 and 2, which account for 42.1% and 16.1% of the total variance, respectively. Each data point represents the mean of the three donors within each sample group, and bars denote the SD.

6


APOE; see also refs. [7, 30]), cell adhesion, and phagocytosis showed increased expression upon differentiation. Although gene expression for certain proinflammatory cytokines, such as IL-8 and TNF, decreased with the proposed maturation sequence, the 3 week-adherent cells from Media A and B could respond to LPS to secrete TNF (data not shown).

Osteoclast generation As in the mouse, M-CSF- and GM-CSF-generated macrophage populations can be converted rapidly and efficiently into osteoclasts in the presence of M-CSF and RANKL [26, 32], and we determined whether our CD34⫹ cell-generated, macrophagelike cells might also be directed along the osteoclast lineage. As an indication of their osteoclastogenic potential, we showed above that c-Fms (M-CSFR) expression increased following culture of the CD34⫹ cells (Figs. 2 and 3B), as M-CSF is a critical cytokine for osteoclastogenesis [33]. The microarray analysis also indicated that the expression of a number of genes associated with osteoclastogenesis, for example, cathepsin K, RANK, TRAP, calcitonin receptor, osteoclast-associated receptor, microphthalmia-associated transcription factor, and chloride channel 7, was detected in Weeks 2 and 3 populations (data not shown). As a result, we chose to examine such potential for 2 week-nonadherent cells, reasoning from the data above that they are proliferating rapidly and may have more plasticity by being relatively immature. For this purpose, we cultured this population in M-CSF, with or without RANKL, again in serum-free medium. Following a further 2–5 weeks of culture, no strong evidence for the formation of osteoclast-like cells was seen, as determined by adherent cell morphology (data not shown), qPCR (Fig. 7, A–D), and resorption of bone (Fig. 7E). Given that the majority of the protocols that use human PBMCs or CD14⫹ monocytes in vitro as osteoclast precursors requires the presence of FBS, together with M-CSF


removed, but FBS removal did not influence its expression (P⬎0.05; Fig. 7D). The presence of functional osteoclasts was confirmed by the formation of resorption pits on slices of bovine cortical bone by 5 weeks (Fig. 7E). Approximately 660 ⫾ 225 pits/slice (n⫽10) were observed following culture in the presence of M-CSF, RANKL, and FBS. Resorption pits were identified collectively as individual pits of varying size or larger multilobular areas (Materials and Methods). The distribution of pitting tended to vary between slices, with some showing even pitting over the entire surface and others showing a concentration in an area. This finding, when considered with the known surface characteristics of cortical bone (i.e., canals and lacunae), which are also revealed by pit-staining, indicated that manual calculation of pit number, as adopted here, would provide the most accurate assessment of osteoclast function, as opposed to using image analysis of the stained area. The dependence of resorption also on the presence of RANKL and FBS was confirmed by the lack of resorption pits seen when either of these components was removed (Fig. 7E). Another commonly used assessment for osteoclast formation is the presence of TRAP⫹multinucleated cells alone; such analysis is limited, as macrophages are capable of forming multinucleated polykaryons in the absence of osteoclastogenic factors, and mono- and multinucleated cells can stain positively for TRAP. Indeed, we noted that in the absence of RANKL or FBS, cells still showed staining for TRAP, although only in the presence of either of these factors alone were some larger, multinucleated cells observed (Fig. 7E).

DISCUSSION In this study, we have defined new cytokine and serum-free culture conditions, incorporating cell expansion and differen-

Fig. 5. k-means clustering of differentially expressed genes. All genes that were differentially expressed between any two sample groups were subjected to k-means clustering (Materials and Methods). Shown are the three main clusters that were identified. The x-axis corresponds to the samples and the y-axis, the normalized expression values. Each line represents a gene that is color-coded based on its expression in CD14⫹ monocytes (Cluster 1), 2 week- and 3 week-nonadherent (Cluster 2), or 3 week-adherent and MDM (Cluster 3) samples (red for high expression; green for low expression).

and RANKL [33–36], we assessed if addition of 10% FBS to the cultures containing M-CSF ⫹ RANKL could promote osteoclast differentiation. Expression of the osteoclast-associated genes, namely cathepsin K, vitronectin receptor, and NFATc1, increased significantly following 2 weeks of culture in the presence of M-CSF, RANKL, and FBS, compared with the groups cultured without FBS or RANKL (P⬍0.05; Fig. 7, A–C). Gene expression of TRAP was reduced if RANKL were

Fig. 6. Hierarchical clustering and GO analysis of differentially expressed genes. Data mining was per Materials and Methods. Shown are seven significant and nonredundant classifications at Levels 3 and 4 for biological process and molecular function.


7

TABLE 1.

Gene Symbol Transcription factors IRF1 KLF9 IRF7 IRF2 MAFF CEBPB MDM2 CREM NFKB1 KLF2 KLF13 NFKB2 MEF2A REL KLF11 JUNB HIF1A FOXO3A FOS RUNX1 KLF5 KLF4 SMAD3 CEBPA MAF Lipid metabolism IMPA2 DGKD LRP8 HIBCH FDPS PCCA ALOX5AP LIPE AACS HMGCS1 ACACA HADHSC PLB1 LPL SULT2B1 SCD5 PBP FASN GGTLA1 PLTP DHCR7 SCD LTC4S LRP5 PLA2G6 PTGDS SLC27A2 ELOVL6 HPGD APOE Cytokines/chemokines and receptors IL8 CXCL11 CCL4 CXCL5 IL1RN

8

Differentially Expressed Genes in GO Categories

Description

Wk2NA: Mono

Wk3NA: Mono

Wk3A: Mono

MDM: Mono

IFN regulatory factor 1 Kruppel-like factor 9 IFN regulatory factor 7 IFN regulatory factor 2 v-maf musculoaponeurotic fibrosarcoma oncogene homolog F CCAAT/enhancer binding protein, ␤ Mdm2, transformed 3T3 cell double minute 2, p53-binding protein cAMP-responsive element modulator NF of ␬ light polypeptide gene enhancer in B cells 1 Kruppel-like factor 2 Kruppel-like factor 13 NF of ␬ light polypeptide gene enhancer in B cells 2 MADS box transcription enhancer factor 2, polypeptide A v-rel reticuloendotheliosis viral oncogene homolog Kruppel-like factor 11 jun B proto-oncogene hypoxia-inducible factor 1, ␣ subunit forkhead box O3A v-fos FBJ murine osteosarcoma viral oncogene homolog runt-related transcription factor 1 Kruppel-like factor 5 Kruppel-like factor 4 mad protein homolog mRNA CCAAT/enhancer-binding protein, ␣ v-maf musculoaponeurotic fibrosarcoma oncogene homolog

–15.8 –5.7 –40.0 –3.7 –1.4 –2.6 –2.9 –2.7 –4.5 –3.2 –5.0 –4.1 –2.1 –2.7 –2.8 –2.1 –1.1 –2.5 –9.0 –4.2 –3.9 1.0 –2.5 6.3 15.1

–15.5 –6.5 –13.0 –5.8 1.1 –4.2 –5.0 –3.4 –4.6 –11.3 –4.9 –2.0 –1.5 –3.1 –2.1 –1.6 –1.9 –2.1 –2.4 –2.7 –1.2 –2.7 2.9 3.9 15.3

–16.4 –14.8 –7.6 –6.1 –5.6 –7.0 –5.2 –4.7 –5.8 –4.6 –3.9 –2.4 –2.4 –2.9 –2.1 –1.8 –2.3 –2.1 –1.6 –2.2 1.0 1.3 3.2 9.1 38.9

–15.2 –14.3 –10.5 –8.8 –7.2 –6.8 –5.0 –4.9 –4.1 –3.6 –3.4 –3.4 –3.2 –2.9 –2.9 –2.8 –2.8 –2.4 –2.0 –1.8 1.3 2.1 4.6 8.3 20.9

–1.6 –1.3 1.0 2.2 1.4 3.1 1.5 1.5 1.5 1.7 1.5 5.9 2.6 1.5 2.7 1.3 15.2 3.6 1.1 13.4 11.4 26.4 1.2 1.5 6.0 36.5 –1.3 8.0 32.6 5.4

–2.8 –3.0 1.7 2.2 2.3 3.7 1.2 1.4 3.2 4.6 2.8 8.6 7.8 2.3 3.1 5.0 12.0 9.4 6.5 20.0 23.2 43.7 8.9 23.7 7.7 93.1 11.4 24.1 99.9 7.6

–6.1 –4.4 1.9 2.4 2.5 3.5 5.3 2.5 3.9 5.2 4.4 8.3 12.7 5.4 11.8 13.8 15.3 9.1 28.4 46.8 24.9 37.0 37.9 37.7 64.1 107.7 53.0 69.4 180.1 109.5

–8.5 –2.1 2.4 2.5 3.1 3.5 4.1 4.1 5.7 6.5 6.7 8.6 11.4 12.1 12.8 13.2 13.2 15.0 22.2 27.7 33.1 33.4 37.5 50.7 53.0 59.2 79.6 111.1 140.0 144.4

–4.2 3.2 2.2 –26.8 1.6

–23.7 –8.0 –8.9 –20.9 –1.6

–32.8 –25.3 –21.2 –20.6 –9.7

–72.5 –27.7 –27.5 –23.5 –15.9

inositol(myo)-1 (or 4)-monophosphatase 2 diacylglycerol kinase, 130 kDa low-density lipoprotein receptor-related protein B 3-hydroxyisobutyryl-Coenzyme A hydrolase farnesyl diphosphate synthase propionyl coenzyme A carboxylase, ␣ polypeptide arachidonate 5-lipoxygenase-activating protein lipase, hormone-sensitive acetoacetyl-CoA synthetase 3-hydroxy-3-methylglutaryl-Coenzyme A synthase 1 acetyl-Coenzyme A carboxylase ␣ L-3-hydroxyacyl-Coenzyme A dehydrogenase, short chain phospholipase B1 lipoprotein lipase sulfotransferase family, cytosolic, 2B, member 1 acyl-CoA-desaturase prostatic-binding protein fatty acid synthase ␥-glutamyltransferase-like activity 1 phospholipid transfer protein 7-dehydrocholesterol reductase stearoyl-CoA desaturase leukotriene C4 synthase low-density lipoprotein receptor-related protein 5 phospholipase A2, group VI PGD2 synthase 21 kDa solute carrier family 27, member 2 ELOVL family member 6, elongation of long-chain fatty acids hydroxy-PG dehydrogenase 15-(NAD) Apolipoprotein E IL8 chemokine (C-X-C motif) ligand 11 chemokine (C-C motif) ligand 4 chemokine (C-X-C motif) ligand 5 IL-1R antagonist



TABLE 1. Gene Symbol CCR5 CXCL10 TNF IL3RA CXCL3 CCL5 IL1B CX3CR1 CCL22 CCL20 CXCL13 CXCR4 CXCL9 CCR1 CCL19 CCR2 CCL17 CCL13 CCL23 IL7 PPBP CCL18 PF4 Phagocytosis and lysosomal enzymes CLEC4G CAMP DEFB105A LY96 CLEC1A DEFA3 CD276 FCER2 ADORA2B SPN UMOD CD36 LGALS3BP MRC1L1 MRC2 CLEC11A SPP1 KLRG1 CLEC3B FCER1A FCGR2B PTMS COLEC12 COLEC12 BPI AZU1 ELA2 Cell adhesion TGM2 CD151 SCARF1 CYFIP2 COL18A1 COL24A1 CDH26 ITGA6 PAPLN CPXM DLL1

(Continued)

Description chemokine (C-C motif) receptor 5 chemokine (C-X-C motif) ligand 10 TNF (superfamily, member 2) IL-3R␣ chemokine (C-X-C motif) ligand 3 chemokine (C-C motif) ligand 5 IL-1␤ chemokine (C-X3-C motif) receptor 1 chemokine (C-C motif) ligand 22 chemokine (C-C motif) ligand 20 chemokine (C-X-C motif) ligand 13 chemokine (C-X-C motif) receptor 4 chemokine (C-X-C motif) ligand 9 chemokine (C-C motif) receptor 1 chemokine (C-C motif) ligand 19 chemokine (C-C motif) receptor 2 chemokine (C-C motif) ligand 17 chemokine (C-C motif) ligand 13 chemokine (C-C motif) ligand 23 IL-7 pro-platelet basic protein chemokine (C-C motif) ligand 18 platelet factor 4 C-type lectin superfamily 4, member G cathelicidin antimicrobial peptide defensin, ␤ 105A lymphocyte antigen 96 C-type lectin domain family 1, member A defensin, ␣ 3, neutrophil-specific CD276 antigen Fc fragment of IgE, low-affinity II, receptor for adenosine A2b receptor Sialophorin Uromodulin CD36 antigen lectin, galactoside-binding, soluble, 3-binding protein mannose receptor, C type 1-like 1 mannose receptor, C type 2 C-type lectin domain family 11, member A secreted phosphoprotein 1 killer cell lectin-like receptor subfamily G, member 1 C-type lectin domain family 3, member B Fc fragment of IgE, high-affinity I, receptor for; ␣ polypeptide Fc fragment of IgG, low-affinity IIb, receptor Parathymosin collectin subfamily member 12 collectin subfamily member 12 bactericidal permeability-increasing protein azurocidin 1 elastase 2, neutrophils transglutaminase 2 CD151 antigen scavenger receptor class F, member 1 cytoplasmic FMR1-interacting protein 2 collagen, type XVIII, ␣ 1 collagen, type XXIV, ␣ 1 cadherin-like 26 integrin, ␣ 6 papilin, proteoglycan-like-sulfated glycoprotein carboxypeptidase X ␦-like 1

Wk2NA: Mono

Wk3NA: Mono

Wk3A: Mono

MDM: Mono

1.9 2.2 1.3 15.6 2.4 2.9 3.0 2.2 169.8 2.3 1.2 –1.1 4.2 2.2 1.0 –3.0 1.9 –18.7 –0.3 1.1 –559.2 1.9 –17.1

–7.2 –4.5 –12.1 –2.6 –3.6 –12.5 –2.8 –3.8 1.2 –3.2 1.5 –2.0 1.2 1.6 –1.1 –31.2 –1.8 –2.2 –1.4 2.0 –693.0 6.5 –41.9

–7.9 –10.3 –12.3 –11.8 –8.6 –6.6 –2.5 –107.4 –4.8 –3.3 –3.0 –2.8 –2.7 –1.2 –2.0 –40.9 –2.4 5.0 1.5 5.8 –18.2 8.1 –1.3

–9.6 –9.2 –9.1 –8.6 –6.6 –5.6 –4.9 –4.8 –4.3 –3.0 –2.7 –2.4 –2.1 –2.0 –1.7 –10.7 –1.6 1.4 1.5 3.4 4.0 7.3 61.6

–2.5 –5.7 1.4 1.7 1.1 –45.3 11.8 –2.9 1.6 3.3 4.9 1.3 4.1 1.5 3.1 8.7 31.8 9.9 10.6 1.1 6.4 29.2 15.8 15.8 50.2 8.4 1.1

–2.0 –1.2 2.2 1.7 –1.2 –45.3 23.7 1.7 2.7 3.2 4.5 5.0 4.5 2.7 4.5 8.4 26.4 11.5 7.8 3.2 9.2 28.9 14.2 14.2 61.1 2.6 1.3

–1.2 1.2 2.2 2.4 2.6 3.8 4.0 4.0 5.6 5.7 5.9 6.1 6.2 6.2 7.2 15.3 17.3 18.2 21.0 27.7 30.6 36.6 54.1 54.1 135.5 243.2 2143.4

2.2 1.8 3.4 3.2 2.6 2.6 2.5 4.2 6.1 6.3 9.3 5.8 2.4 5.7 10.1 27.0 8.6 18.3 17.2 31.8 25.1 23.2 33.1 33.1 94.0 475.5 2983.5

11.8 –1.2 –1.7 –3.2 1.6 1.0 1.0 2.2 1.8 –1.5 –4.2

5.7 –1.2 1.3 –1.2 1.9 1.2 1.4 11.6 6.7 –1.1 –1.4

–1.7 1.5 1.5 2.1 2.2 2.3 2.4 2.5 3.0 3.3 3.4

–2.8 1.6 1.5 2.9 2.7 2.7 4.3 3.1 1.9 11.1 1.8


9

TABLE 1. Gene Symbol SELPLG VTN ITGB3BP CELSR2 CHST10 SIGLEC12 VWA1 FCGBP ITGB3 PPFIBP1 AMICA1 DCBLD2 BCAR1 ROBO1 COL6A2

(Continued)

Description selectin P ligand Vitronectin integrin ␤ 3-binding protein cadherin, EGFLAG seven-pass G-type receptor 2 carbohydrate sulfotransferase 10 sialic acid-binding lg-like lectin 12 von Willebrand factor A domain containing 1 Fc fragment of IgG-binding protein integrin ␤ 3 PTPRF-interacting protein, binding protein 1 adhesion molecule, interacts with CXADR antigen 1 discoidin, CUB and LCCL domain-containing 2 breast cancer anti-estrogen resistance 1 roundabout, axon guidance receptor, homolog 1 collagen, type VI, ␣ 2

Wk2NA: Mono

Wk3NA: Mono

Wk3A: Mono

MDM: Mono

2.3 2.7 1.8 2.4 3.3 –3.0 4.3 4.9 3.0 21.8 7.2 9.1 49.7 7.1 6.8

2.0 2.3 2.9 4.2 3.5 –1.4 6.1 5.3 6.2 55.1 8.0 13.9 106.0 25.9 127.7

3.9 4.8 4.8 4.9 5.4 5.8 7.8 11.4 14.5 18.0 18.9 30.6 33.8 64.6 356.6

3.3 3.5 6.4 4.9 9.2 8.3 9.4 9.4 19.4 9.4 13.5 18.7 20.4 60.2 476.3

WK2NA, Week 2-nonadherent; W1C3A, Week 3-adherent; Mono, monocyte. Ratios indicate fold-change difference between sample groups, where a negative number equates to an inverse fold-change.

tiation for the generation of large numbers of macrophage lineage populations from mobilized human peripheral blood CD34⫹ HSCs. By monitoring the development of these populations over a 3-week period, we were able to identify a progression in maturity by surface marker expression and by using a microarray analysis comparison with MDM and monocytes. In terms of relative expression of genes related to macrophage function, the 3 week-adherent population was found to be most like the MDM when compared with the 2 week- and 3 week-nonadherent counterparts. We were also able to show that as an example of the potential, at least of the system to generate large numbers of other functional phenotypes, the 2 week-nonadherent population could be induced to differentiate into osteoclasts. With our protocol, we have estimated that in Medium B, 1 ⫻ 106 CD34⫹ HSCs, which are obtained readily from small volumes of mobilized blood, can generate 180 ⫻ 106-nonadherent cells of monocytic morphology within 2 weeks and that the system is capable of generating at least 360 ⫻ 106adherent macrophage-like cells. This latter figure is likely to be an underestimate, as the nonadherent population continues to proliferate beyond the 2-week time-point and as the number of cells that adhere may be limited by the size of the culture vessel. Previous studies using CD34⫹ cells to generate macrophage populations have generally been on a small scale and usually in the presence of serum [16 –18, 37– 42]. This paper is the first to report the generation of large numbers of macrophages under serum-free conditions, a detailed comparison of adherent and nonadherent populations developing over time from HSCs, and the high overlap for HSC-derived macrophages to the gene expression profile of a widely used human macrophage population, namely MDM. Also, our serum-free conditions allow better control over the system, as it removes one variable and in addition, allows a clearer analysis of the effects of individual cytokines to be made. The latter advantage is particularly important, as a variety of cytokine cocktails can influence macrophage lineage maturation [10, 16 –19, 38].

10


We used surface marker expression as one criterion of macrophage lineage development. However, for such human populations, no one marker or feature can be used definitively to confirm the phenotype. The microarray approach was therefore included, and it allowed us to show that the 3 weekadherent population had a gene expression profile that was close to that for MDM but relatively distant from that for freshly isolated peripheral blood monocytes; the similarity between the two former cell sets is interesting, given that they were derived from a different precursor source and under different cytokine/ culture conditions. This approach also indicated that 2 weekand 3 week-nonadherent populations were further removed from the MDM phenotype, an observation consistent with their presumed relative immaturity. M-CSF and RANKL are sufficient to form bone-resorbing osteoclasts in vitro from mononuclear macrophage lineage precursors [33–35]. Cultures of murine macrophage populations generated from bone marrow in the presence of M-CSF or GM-CSF display high osteoclastogenic potential [26]. In contrast, for human osteoclast generation, their precursors represent only a small proportion in PBMC [34, 36] and also in HSC cultures, even following cytokine-induced differentiation to enrich for such precursors in the latter [39, 43– 48]. We were also able to demonstrate that the 2-week-nonadherent population could act as osteoclast precursors, indicating that there is still the capability within the system for the development of other lineages. In addition to M-CSF and RANKL, a requirement for serum was noted. It would be interesting to determine the extent of this type of capability within the other populations that we generated for osteoclastogenesis and for the differentiation into other phenotypes such as DCs. An accurate determination of the osteoclastogenic potential of our culture system is difficult for several reasons. Our protocol for osteoclast generation above the number of potential osteoclast precursors is known only at the 2-week time-point when the cells are treated with M-CSF ⫹ RANKL; the proliferating, nonadherent cells are demi-depopulated, thereby making it impossible to


Fig. 7. Osteoclast generation. (A–D) qPCR analysis of osteoclast-associated genes. CD34⫹-derived cells (Medium B) at 2 weeks were cultured ⫾ RANKL (50 ng/ml) for a further 2 weeks in X-VIVO 10 media containing M-CSF (5000 U/ml) ⫾ 10% FBS. qPCR analysis was performed on the adherent cell population. Expression levels for the indicated genes were expressed relative to the no RANKL group. Values are mean ⫾ SEM for n ⫽ 3–7 patient samples; *, P ⬍ 0.05, versus the no RANKL group; #, P ⬍ 0.05, for the no FBS group versus with RANKL, with FBS group. (E) Evidence for bone resorption and TRAP staining. CD34⫹ cells, expanded for 2 weeks in Medium B, were replated on bone slices or culture plates in X-VIVO 10 medium containing the following: (i) and (iv) M-CSF (5000 U/ml), RANKL (50 ng/ml), and 10% FBS; (ii) and (v) M-CSF and 10% FBS, i.e., no RANKL; (iii) and (vi) M-CSF and RANKL, i.e., no FBS. Photomicrographs showing resorption of the bone surface were obtained 5 weeks after plating (i–iii, 125⫻ original magnification). Single pits of varying size can be seen stained with black ink, along with the surface indentations of the cortical bone (i.e., canals and lacunae). Following 2 weeks of culture, adherent cells on culture plates were stained with TRAP (iv–vi, 200⫻ original magnification). TRAP-stained multi- and mononucleated cells are shown.

quantitate the osteoclast precursors. Also, non-bone-resorbing, multinucleated TRAP⫹ cells can be observed in cultures, even in the absence of RANKL (Fig. 7), an observation consistent with the literature [32, 43]. Gene expression analysis of our cell populations indicated enhanced progression over time of RANK expression. Recently, Atkins and co-workers [43] demonstrated that PBMC sorting by FACS yielded RANK⫹/CD14⫹ cells with high osteoclastogenic potential. If such antibodies become available, then such osteoclast precursor cells could be enriched from our populations. We suggest that if the osteoclast differentiation conditions are optimized, it may be possible for the first time to generate large numbers of human osteoclasts for molecular analysis. Regarding possible molecular mechanisms for the control of our differentiation system, c-Fms and C/EBP␣ are known to be critical for cytokine-driven macrophage differentiation [28 –31]. For both of their respective genes, our data for

increased relative expression in our CD34⫹ cell-derived macrophages (Table 1) and in MDM (Table 1; [30]) are similar, as is the gene expression for c-Maf (Table 1; [30]). The silencing of the genes for c-Fms and C/EBP␣ by small interfering RNA during the conversion of monocytes to MDM confirmed their importance in this process [30], and by analogy, they are also presumed to be important for the development of our CD34⫹ cell-derived macrophages. c-Maf could likewise play a role, as its expression can induce monocyte/macrophage differentiation in progenitor cells [49]. We propose that we have developed a convenient and large-scale system to understand the molecular mechanisms underlying the commitment and progression toward human macrophage differentiation and also, the function of these cells. The other potentially convenient feature of the system is that unlike the monocyte-to-MDM conversion, for example, for which there is little cell proliferation, it is a


11

replicating system opening up wider possibilities for genetargeting and even gene-delivery systems for therapy.

ACKNOWLEDGMENTS This work is supported by a grant and Senior Principal Research Fellowship (to J. A. H) from the National Health and Medical Research Council of Australia and by the Cooperative Research Centre for Chronic Inflammatory Diseases. We thank C. Dowsing, G. Bueno, J. Hicks, and J. Szer (Royal Melbourne Hospital) for procuring the leukapheresis product and D. Haylock and P. Simmons for helpful discussions.

REFERENCES 1. Chitu, V., Stanley, E. R. (2006) Colony-stimulating factor-1 in immunity and inflammation. Curr. Opin. Immunol. 18, 39 – 48. 2. Mantovani, A., Sica, A., Locati, M. (2007) New vistas on macrophage differentiation and activation. Eur. J. Immunol. 37, 14 –16. 3. Cheung, D. L., Hamilton, J. A. (1992) Regulation of human monocyte DNA synthesis by colony-stimulating factors, cytokines, and cyclic adenosine monophosphate. Blood 79, 1972–1981. 4. Clanchy, F. I., Holloway, A. C., Lari, R., Cameron, P. U., Hamilton, J. A. (2006) Detection and properties of the human proliferative monocyte subpopulation. J. Leukoc. Biol. 79, 757–766. 5. Finnin, M., Hamilton, J. A., Moss, S. T. (1999) Characterization of a CSF-induced proliferating subpopulation of human peripheral blood monocytes by surface marker expression and cytokine production. J. Leukoc. Biol. 66, 953–960. 6. Cecchini, M. G., Dominguez, M. G., Mocci, S., Wetterwald, A., Felix, R., Fleisch, H., Chisholm, O., Hofstetter, W., Pollard, J. W., Stanley, E. R. (1994) Role of colony stimulating factor-1 in the establishment and regulation of tissue macrophages during postnatal development of the mouse. Development 120, 1357–1372. 7. Martinez, F. O., Gordon, S., Locati, M., Mantovani, A. (2006) Transcriptional profiling of the human monocyte-to-macrophage differentiation and polarization: new molecules and patterns of gene expression. J. Immunol. 177, 7303–7311. 8. Caux, C., Dezutter-Dambuyant, C., Schmitt, D., Banchereau, J. (1992) GM-CSF and TNF-␣ cooperate in the generation of dendritic Langerhans cells. Nature 360, 258 –261. 9. Haylock, D. N., To, L. B., Dowse, T. L., Juttner, C. A., Simmons, P. J. (1992) Ex vivo expansion and maturation of peripheral blood CD34⫹ cells into the myeloid lineage. Blood 80, 1405–1412. 10. Santiago-Schwarz, F., Belilos, E., Diamond, B., Carsons, S. E. (1992) TNF in combination with GM-CSF enhances the differentiation of neonatal cord blood stem cells into dendritic cells and macrophages. J. Leukoc. Biol. 52, 274 –281. 11. Sato, N., Sawada, K., Koizumi, K., Tarumi, T., Ieko, M., Yasukouchi, T., Yamaguchi, M., Takahashi, T. A., Sekiguchi, S., Koike, T. (1993) In vitro expansion of human peripheral blood CD34⫹ cells. Blood 82, 3600 – 3609. 12. Canque, B., Camus, S., Yagello, M., Gluckman, J. C. (1998) IL-4 and CD40 ligation affect differently the differentiation, maturation, and function of human CD34⫹ cell-derived CD1a⫹CD14 – and CD1a–CD14⫹ dendritic cell precursors in vitro. J. Leukoc. Biol. 64, 235–244. 13. Strobl, H., Bello-Fernandez, C., Riedl, E., Pickl, W. F., Majdic, O., Lyman, S. D., Knapp, W. (1997) Flt3 ligand in cooperation with transforming growth factor-␤1 potentiates in vitro development of Langerhanstype dendritic cells and allows single-cell dendritic cell cluster formation under serum-free conditions. Blood 90, 1425–1434. 14. Vairo, G., Hamilton, J. A. (1985) CSF-1 stimulates Na⫹K⫹-ATPase mediated 86Rb⫹ uptake in mouse bone marrow-derived macrophages. Biochem. Biophys. Res. Commun. 132, 430 – 437. 15. Fleetwood, A. J., Lawrence, T., Hamilton, J. A., Cook, A. D. (2007) Granulocyte-macrophage colony-stimulating factor (CSF) and macrophage CSF-dependent macrophage phenotypes display differences in cytokine profiles and transcription factor activities: implications for CSF blockade in inflammation. J. Immunol. 178, 5245–5252.

12


16. Kamps, A. W., Hendriks, D., Smit, J. W., Vellenga, E. (1999) Role of macrophage colony-stimulating factor in the differentiation and expansion of monocytes and dendritic cells from CD34⫹ progenitor cells. Med. Oncol. 16, 46 –52. 17. Bot, F. J., van Eijk, L., Broeders, L., Aarden, L. A., Lowenberg, B. (1989) Interleukin-6 synergizes with M-CSF in the formation of macrophage colonies from purified human marrow progenitor cells. Blood 73, 435– 437. 18. Gabbianelli, M., Pelosi, E., Montesoro, E., Valtieri, M., Luchetti, L., Samoggia, P., Vitelli, L., Barberi, T., Testa, U., Lyman, S., et al. (1995) Multi-level effects of flt3 ligand on human hematopoiesis: expansion of putative stem cells and proliferation of granulomonocytic progenitors/ monocytic precursors. Blood 86, 1661–1670. 19. Ziegler, B., Testa, U., Condorelli, G., Vitelli, L., Valtieri, M., Peschle, C. (1998) Unilineage hematopoietic differentiation in bulk and single cell culture. Stem Cells 16 (Suppl. 1), 51–73. 20. Hamilton, J. A. (1997) CSF-1 signal transduction. J. Leukoc. Biol. 62, 145–155. 21. Panterne, B., Zhou, Y. Q., Hatzfeld, J., Li, M. L., Levesque, J. P., Clark, S. C., Hatzfeld, A. (1993) CSF-1 control of C-FMS expression in normal human bone marrow progenitors. J. Cell. Physiol. 155, 282–289. 22. Wang, A., Gehan, E. A. (2005) Gene selection for microarray data analysis using principal component analysis. Stat. Med. 24, 2069 –2087. 23. Eisen, M. B., Spellman, P. T., Brown, P. O., Botstein, D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14863–14868. 24. Blake, J. A., Harris, M. A. (2002) The Gene Ontology (GO) project: structured vocabularies for molecular biology and their application to genome and expression analysis. Curr. Protoc. Bioinformatics Chapter 7, Unit 7 2. 25. Brazma, A., Hingamp, P., Quackenbush, J., Sherlock, G., Spellman, P., Stoeckert, C., Aach, J., Ansorge, W., Ball, C. A., Causton, H. C., Gaasterland, T., Glenisson, P., Holstege, F. C., Kim, I. F., Markowitz, V., Matese, J. C., Parkinson, H., Robinson, A., Sarkans, U., Schulze-Kremer, S., Stewart, J., Taylor, R., Vilo, J., Vingron, M. (2001) Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat. Genet. 29, 365–371. 26. Lari, R., Fleetwood, A. J., Kitchener, P. D., Cook, A. D., Pavasovic, D., Hertzog, P. J., Hamilton, J. A. (2007) Macrophage lineage phenotypes and osteoclastogenesis— complexity in the control by GM-CSF and TGF-␤. Bone 40, 323–336. 27. Caracciolo, D., Shirsat, N., Wong, G. G., Lange, B., Clark, S., Rovera, G. (1987) Recombinant human macrophage colony-stimulating factor (MCSF) requires subliminal concentrations of granulocyte/macrophage (GM)CSF for optimal stimulation of human macrophage colony formation in vitro. J. Exp. Med. 166, 1851–1860. 28. Dai, X. M., Ryan, G. R., Hapel, A. J., Dominguez, M. G., Russell, R. G., Kapp, S., Sylvestre, V., Stanley, E. R. (2002) Targeted disruption of the mouse colony-stimulating factor 1 receptor gene results in osteopetrosis, mononuclear phagocyte deficiency, increased primitive progenitor cell frequencies, and reproductive defects. Blood 99, 111–120. 29. Hamilton, J. A., Whitty, G., Masendycz, P., Wilson, N. J., Jackson, J., De Nardo, D., Scholz, G. M. (2008) The critical role of the colony-stimulating factor-1 receptor in the differentiation of myeloblastic leukemia cells. Mol. Cancer Res. 6, 458 – 467. 30. Liu, H., Shi, B., Huang, C. C., Eksarko, P., Pope, R. M. (2008) Transcriptional diversity during monocyte to macrophage differentiation. Immunol. Lett. 117, 70 – 80. 31. Wang, D., D’Costa, J., Civin, C. I., Friedman, A. D. (2006) C/EBP␣ directs monocytic commitment of primary myeloid progenitors. Blood 108, 1223–1229. 32. Quinn, J. M., Whitty, G. A., Byrne, R. J., Gillespie, M. T., Hamilton, J. A. (2002) The generation of highly enriched osteoclast-lineage cell populations. Bone 30, 164 –170. 33. Quinn, J. M., Elliott, J., Gillespie, M. T., Martin, T. J. (1998) A combination of osteoclast differentiation factor and macrophage-colony stimulating factor is sufficient for both human and mouse osteoclast formation in vitro. Endocrinology 139, 4424 – 4427. 34. Fujikawa, Y., Quinn, J. M., Sabokbar, A., McGee, J. O., Athanasou, N. A. (1996) The human osteoclast precursor circulates in the monocyte fraction. Endocrinology 137, 4058 – 4060. 35. Matsuzaki, K., Udagawa, N., Takahashi, N., Yamaguchi, K., Yasuda, H., Shima, N., Morinaga, T., Toyama, Y., Yabe, Y., Higashio, K., Suda, T. (1998) Osteoclast differentiation factor (ODF) induces osteoclast-like cell formation in human peripheral blood mononuclear cell cultures. Biochem. Biophys. Res. Commun. 246, 199 –204.


36. Shalhoub, V., Elliott, G., Chiu, L., Manoukian, R., Kelley, M., Hawkins, N., Davy, E., Shimamoto, G., Beck, J., Kaufman, S. A., Van, G., Scully, S., Qi, M., Grisanti, M., Dunstan, C., Boyle, W. J., Lacey, D. L. (2000) Characterization of osteoclast precursors in human blood. Br. J. Haematol. 111, 501–512. 37. Grande, A., Montanari, M., Tagliafico, E., Manfredini, R., Marani, T. Z., Siena, M., Tenedini, E., Gallinelli, A., Ferrari, S. (2002) Physiological levels of 1␣, 25 dihydroxyvitamin D3 induce the monocytic commitment of CD34⫹ hematopoietic progenitors. J. Leukoc. Biol. 71, 641– 651. 38. Montesoro, E., Castelli, G., Morsilli, O., Nisini, R., Stafsnes, M. H., Care, A., Peschle, C., Chelucci, C. (2006) Unilineage monocytopoiesis in hematopoietic progenitor culture: switching cytokine treatment at all Mo developmental stages induces differentiation into dendritic cells. Cell Death Differ. 13, 250 –259. 39. Sawano, A., Iwai, S., Sakurai, Y., Ito, M., Shitara, K., Nakahata, T., Shibuya, M. (2001) Flt-1, vascular endothelial growth factor receptor 1, is a novel cell surface marker for the lineage of monocyte-macrophages in humans. Blood 97, 785–791. 40. Stec, M., Weglarczyk, K., Baran, J., Zuba, E., Mytar, B., Pryjma, J., Zembala, M. (2007) Expansion and differentiation of CD14⫹CD16(–) and CD14⫹ ⫹CD16⫹ human monocyte subsets from cord blood CD34⫹ hematopoietic progenitors. J. Leukoc. Biol. 82, 594 – 602. 41. Suzuki, K., Kiyokawa, N., Taguchi, T., Takenouchi, H., Saito, M., Shimizu, T., Okita, H., Fujimoto, J. (2007) Characterization of monocyte-macrophage-lineage cells induced from CD34⫹ bone marrow cells in vitro. Int. J. Hematol. 85, 384 –389. 42. Willems, R., Henckaerts, E., Lenjou, M., Nijs, G., Rodrigus, I., Moulijn, A. C., Slegers, H., Berneman, Z. N., Van Bockstaele, D. R. (2001) Establishment of serum-free pre-colony forming unit assays for differentiation of primitive hematopoietic progenitors: serum induces early mac-

43.

44. 45.

46.

47.

48.

49.

rophage differentiation and inhibits early erythroid differentiation of CD34⫹⫹CD38 – cells. Ann. Hematol. 80, 17–25. Atkins, G. J., Kostakis, P., Welldon, K. J., Vincent, C., Findlay, D. M., Zannettino, A. C. (2005) Human trabecular bone-derived osteoblasts support human osteoclast formation in vitro in a defined, serum-free medium. J. Cell. Physiol. 203, 573–582. Huang, S., Terstappen, L. W. (1994) Lymphoid and myeloid differentiation of single human CD34⫹, HLA-DR⫹, CD38 – hematopoietic stem cells. Blood 83, 1515–1526. Kurihara, N., Chenu, C., Miller, M., Civin, C., Roodman, G. D. (1990) Identification of committed mononuclear precursors for osteoclast-like cells formed in long term human marrow cultures. Endocrinology 126, 2733–2741. Matayoshi, A., Brown, C., DiPersio, J. F., Haug, J., Abu-Am, Y., Liapis, H., Kuestner, R., Pacifici, R. (1996) Human blood-mobilized hematopoietic precursors differentiate into osteoclasts in the absence of stromal cells. Proc. Natl. Acad. Sci. USA 93, 10785–10790. Mbalaviele, G., Jaiswal, N., Meng, A., Cheng, L., Van Den Bos, C., Thiede, M. (1999) Human mesenchymal stem cells promote human osteoclast differentiation from CD34⫹ bone marrow hematopoietic progenitors. Endocrinology 140, 3736 –3743. Pierelli, L., Scambia, G., d’Onofrio, G., Ciarli, M., Fattorossi, A., Bonanno, G., Menichella, G., Battaglia, A., Benedetti Panici, P., Tommasi, M., Mancuso, S., Leone, G. (1997) Generation of multinuclear tartrate-resistant acid phosphatase positive osteoclasts in liquid culture of purified human peripheral blood CD34⫹ progenitors. Br. J. Haematol. 96, 64 – 69. Hegde, S. P., Zhao, J., Ashmun, R. A., Shapiro, L. H. (1999) c-Maf induces monocytic differentiation and apoptosis in bipotent myeloid progenitors. Blood 94, 1578 –1589.


13