bigbio/linnaeus · Datasets at Hugging Face

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0	pmcA1805739	[ { "id": "pmcA1805739__text", "type": "Article", "text": [ "Embryonic sympathoblasts transiently express TrkB in vivo and proliferate in response to brain-derived neurotrophic factor in vitro\nAbstract\nBackground\nNerve growth factor and neurotrophin-3 are involved in the development of sympathetic neurons; however, whether brain derived neurotrophic factor also plays a role is not known. The purpose of this study was to determine whether BDNF and its receptor, TrkB, are expressed during the development of paravertebral sympathetic ganglia in vivo and to determine the effect of BDNF in vitro.\n\nResults\nAs neural crest cells coalesce to form sympathetic ganglia, TrkB-positive cells are seen in both chicken and mouse embryos. In chicken embryos, TrkB-expressing cells first appear at Hamburger-Hamilton Stage (St) 27 and they co-express HNK-1, confirming that they are migrating neural crest cells. The TrkB-positive cells lack neural markers at this stage; however, they migrate with other neurally differentiating cells that are TrkA and TrkC-positive. By St. 29/30, TrkB-positive cells begin to express the neural specific markers Hu C/D and Islet-1; eventually, all TrkB positive cells commence neural differentiation. By St. 34, TrkB and TrkC staining are lost. BDNF transcript expression parallels that of TrkB. In the mouse, TrkB-positive cells surround newly formed sympathetic ganglia and a small number of TrkB positive cells that co-express tyrosine hydroxylase are seen within ganglia between E13.5-15. In cell culture, many cells from St. 29–30 chicken lumbar sympathetic ganglia express neural markers and are dividing, indicating that they are sympathoblasts. Sympathoblasts and neurons require both nerve growth factor and neurotrophin-3 for survival. BDNF increases the number of cells expressing neural markers in culture by increasing number of cells that incorporate bromodeoxyuridine. In contrast, most TrkB-positive sympathetic cells in vivo are not actively proliferating between E6–E8.\n\nConclusion\nDeveloping paravertebral sympathetic ganglia in avian and murine embryos contain a subpopulation of sympathoblasts that transiently express TrkB and ultimately commence neuronal differentiation. These TrkB expressing sympathoblasts are not actively dividing in vivo; yet, when placed in vitro, will divide in response to BDNF. This suggests that the availability of BDNF in vivo fails to reach a threshold necessary to induce proliferation. We suggest that excess TrkB stimulation of sympathoblasts in vivo may lead to the genesis of neuroblastoma.\n\n\n\nBackground\nNeural crest cells destined to become paravertebral sympathetic neurons proliferate and differentiate during migration and gangliogenesis. In chicken embryos, migrating neural crest cells express catecholamines at Hamburger/Hamilton Stage (St.) 19, and these cells form the primary sympathetic chain dorsolateral to the aorta at St. 22 (E3.5) [1]. Between St. 23 (E4) and St. 28 (E6), these cells disperse and undergo a secondary migration to form the paravertebral sympathetic chain that resides ventral to the spinal cord and dorsal root ganglion [1]. After ganglia coalesce, sympathoblasts express markers of neuronal differentiation, such as Q211 and tyrosine hydroxylase (TH), at a time when they also incorporate [3H]-thymidine [2]. Time lapse photography has shown that cultured E15.5–E16.5 sympathetic neurons from rat embryos extend axons while they divide [3-5]. Although proliferation appears to be an important process to expand the sympathetic neuron population during differentiation, the mechanisms that guide sympathoblast proliferation have not been identified.\nThe development of sympathetic neurons is guided by neurotrophins. Neurotrophin-3 (NT-3) binds to its receptor, TrkC, to promote the survival of cultured sympathoblasts from early lumbar paravertebral ganglia [6]. Nerve growth factor (NGF) signals through its receptor, TrkA, to promote the survival of sympathetic neurons upon target innervation [7]. There are severe sympathetic defects in the superior cervical ganglion of individual NT-3 and NGF knockout mice [8-10]. Furthermore, there is no additional cell death in the superior cervical ganglion of NT-3 and NGF double knockout mouse embryos, suggesting that all of the neurons are dependent on both neurotrophins for survival [11]. There is also an increase in sympathetic neuron cell death in TrkA knockout mice [12]. However, in TrkB and BDNF knockout mice, there is no apparent phenotype in the superior cervical ganglion, and there is little evidence that TrkB or BDNF is expressed in sympathetic ganglia. Thus, it is generally thought that TrkB and BDNF have little or no roles in guiding the development of sympathetic neurons.\nIn addition to their developmental functions, neurotrophin receptors regulate cell behavior in neuroblastoma, a tumor found in sympathetic ganglia and adrenal medulla. Tumors that express TrkA often spontaneously regress, while those that express TrkB and its ligand, brain-derived neurotrophic factor (BDNF), grow aggressively, are invasive, and fail to respond to chemotherapeutic agents [13]. The presence of TrkA in neuroblastoma tumors is consistent with its expression in developing sympathetic neurons, and suggests that regressive neuroblastoma tumors arise from early sympathetic neurons that express TrkA. The function of TrkB in early sympathetic development is unknown, which makes understanding the etiology of aggressive neuroblastoma tumors difficult. Based on its function in neuroblastoma tumors, we hypothesize that BDNF and TrkB expression in differentiating sympathoblasts is responsible for expanding the neuronal population through proliferation.\nWe sought to determine whether BDNF and TrkB are involved in sympathetic development. We report that during early embryonic development, TrkB is expressed in a subset of differentiating sympathoblasts in both avian and murine embryos. We also find that BDNF promotes the proliferation of TrkB-positive sympathoblasts in cell culture. However, the majority of TrkB positive cells in vivo fail to take up bromodeoxyuridine (BrdU) over a 24 hr period, suggesting that endogenous BDNF concentrations do not reach a threshold necessary to stimulate proliferation of sympathoblasts. Shortly after all of the TrkB positive cells commence neuronal differentiation, TrkB immunoreactivity is lost. These results suggest that prolonged expression and/or activation of TrkB signaling at these early stages may be an early event triggering the formation of neuroblastoma.\n\nResults\nTrkB is expressed during migration of neural crest cells to sympathetic ganglia\nWe first determined whether TrkB is expressed in neural crest-derived cells in the region ventral to the spinal cord and dorsal root ganglia where sympathetic ganglia coalesce between Hamburger/Hamilton Stages (St.) 25–28/29. To identify cells that have commenced neuronal differentiation, transverse sections of the lumbar spinal column region were stained with antibodies against Hu C/D [14], a neuronal-specific RNA-binding protein, or Islet-1, a transcription factor found in sympathetic neurons [15]. We found that Hu C/D and Islet-1 are expressed in the same cells both in vivo and in vitro throughout sympathetic development. In experiments done between St. 25 and 28, Islet-1 staining appeared weaker than Hu C/D staining, and thus we used Hu C/D to identify differentiating neurons at these stages. At later stages, Islet-1 was used to facilitate the identification of neurons because of the nuclear location of its immunoreactivity.\nCells expressing Hu C/D are first detected at St. 25 ventral to the spinal cord and dorsal root ganglion and lateral to the dorsal aorta (Figure 1A, 1B). By St. 26, the number of cells that express Hu C/D in this region increases dramatically (Figure 1C). TrkB-expressing cells first appear at St. 27 in the same region and are adjacent to Hu C/D-positive cells (Figure 1D, 2A, 2H). TrkB-positive cells co-localize with a neural crest marker, HNK-1 (Figures 2B, 2C, 2D). The Hu C/D-positive cells in this region are likely to be sympathetic neurons, since they appear in the region where sympathetic ganglia form and express tyrosine hydroxylase, a rate-limiting enzyme in the synthesis of catecholamines (Figures 2E, 2F, 2G). At St. 28/29, the cells begin to coalesce ventral to the dorsal root ganglion and the Hu C/D-positive cells and TrkB-positive cells remain as two separate cell populations (Figure 1E); however, shortly afterwards, all of the TrkB-positive cells begin to express Islet-1 (Figure 3B) and Hu C/D (data not shown).\n\nDevelopmental regulation of TrkA, TrkB, TrkC, and BDNF expression\nIn contrast to TrkB, the other neurotrophin receptors, TrkA and TrkC, are co-expressed in both Hu C/D-positive and Hu C/D-negative cells at St. 27 (Figures 2I, 2J). We find that approximately 30% of the Islet-1-positive cells express TrkA (Figure 3A), while 50% express TrkB (Figure 3B) and 100% express TrkC (Figure 3C) at St. 29/30 (E6.5). Thus, all developing neurons express TrkC in combination with either TrkA or TrkB. By St. 31 (E7), the number of TrkA-positive, Islet-1-positive cells increases to 100% (Figure 3D) and immunoreactivities for both TrkB and TrkC appear dispersed (Figure 3E, 3F). By St. 34 (E8), TrkA expression is well-sustained (Figure 3G) and TrkB and TrkC immunoreactivities are lost (Figure 3H, 3I). We also examined the early development of murine sympathetic ganglia (Figure 4). At E13, the newly formed lumbar sympathetic ganglia can be observed ventral to the spinal cord and notochord by their staining for Hu C/D and TH (Figure 4A). TrkB-positive cells can be seen surrounding developing ganglia, as well as in occasional cells within the ganglia (Figure 4C, D). These TrkB-positive cells within the ganglia co-express TH and are seen at a frequency of 1–2 cells per section starting at E13 (Figure 4A–D) and are still present at E15.5 (data not shown).\nIn neuroblastoma cells, BDNF is co-expressed with TrkB, suggesting that autocrine stimulation is a means by which proliferation is sustained in the transformed cells. To test whether BDNF, the ligand for TrkB, was present in embryonic chick sympathetic ganglia, we used quantitative real-time PCR with TaqMan probes to determine the relative abundance of BDNF transcripts in total RNA extracted from lumbar sympathetic ganglia at St. 29/30 (E6.5), St. 31 (E7), St. 34 (E8), and E9. BDNF expression within the ganglia parallels that of TrkB: BDNF mRNA expression levels are highest at St 29/30 (E6.5), and these levels decrease 2-fold at St. 31 (E7) and St. 34 (E8; Figure 5). By E9, BDNF levels are 7 times lower than at St. 29/30 (E6.5; Figure 5).\n\nNT3 and NGF promote survival of differentiating sympathetic neurons in culture\nTo determine the effect of neurotrophins, we cultured cells dispersed from lumbar sympathetic ganglia at St. 29/30 (E6.5) because, at this stage, ganglion formation is complete, the number of TrkA-, TrkB-, and TrkC-positive cells have peaked, and all Trk-expressing cells have initiated neural differentiation. First, we identified markers expressed by acutely isolated cells. As shown in Table 1, 80–91% of the cells are p75 neurotrophin receptor (NTR)-positive, indicating that most of the cells are neural crest-derived and little mesenchymal contamination is introduced by the isolation procedure. In addition, 28–33% of the cultured cells express the neural marker Hu C/D. Approximately half of these Hu C/D-positive cells express TrkB. Conversely, all of the TrkB positive cells express Hu C/D. These TrkB-positive cells comprise approximately 14–17% of the total cell population.\nWe then determined how many of the acutely isolated cells were proliferating by incubating them for 12 hrs in BrdU-containing medium. For these experiments, we identified differentiating neurons with the transcription factor Islet-1 because this marker labels nuclei, thus it co localizes with any BrdU that has been incorporated into the DNA, allowing us to determine whether the cell had undergone S-phase of the cell cycle. After 12 hrs in BrdU, 59% of Islet-1-positive nuclei stain for BrdU immunoreactivity. Thus, cultures of St. 29/30 sympathetic ganglia contain many cells that proliferate while exhibiting markers of neuronal differentiation, confirming previous observations [2]. We call these dividing neuronal precursors sympathoblasts. The remaining non-BrdU incorporating, Islet-1 positive cells are likely to be post mitotic neurons.\nFinally, we determined the trophic requirements of St. 29/30 (E6.5) sympathetic neurons and sympathoblasts. We monitored cultures over a three day period after plating and counted the number of phase bright cells with neurites, a morphological feature of both neurons and sympathoblasts. In the absence of trophic factors, more than 2/3 of the cells die by 24 hours in culture and BDNF, NT-3, or NGF alone is not sufficient to promote survival (Figure 6). However, NGF together with NT-3 supports the survival of a significantly larger number of cells (Figure 6). For the subsequent experiments, all neurons were cultured with 25 ng/ml NT-3 and 1 μg/ml 7S NGF to optimize survival.\n\nBDNF promotes proliferation of TrkB-positive sympathetic neurons in culture\nTo determine the effects of BDNF, cultures of cells from St. 29/30 (E6.5) sympathetic ganglia were supplemented with 200 ng/ml BDNF and the number of neurons and sympathoblasts were counted at 24, 48, and 72 hours using phase microscopy (Figure 7A). A 1.6-fold increase in the number of neurons due to BDNF is observed by 24 hours and this number does not increase further at 48 or 72 hours. This effect of BDNF is concentration-dependent with an EC50 of 75 ng/ml (Figure 7B).\nTo test whether the increase in the number of neurons and sympathoblasts caused by BDNF is due to the differentiation of pluripotent neural crest cells, we quantified the effects of BDNF on the number of neurally differentiating cells (Hu C/D-positive) versus the number of non-neuronal cells (Hu C/D-negative) after identifying all neural crest-derived cells by staining for p75NTR in St. 29/30 (E6.5) cultures. If BDNF increases the number of neurons and sympathoblasts by inducing a non-neuronal cell to express Hu C/D, then we expected that the total cell number would remain the same and that there would be a decrease in the number of non-neuronal cells as well as a corresponding increase in the number of neurons. After 24 hours, BDNF significantly increases the number of p75NTR-positive cells as well as the number of Hu C/D-positive cells (Figure 8A). However, there was no statistically significant change in the number of non-neuronal cells. Thus, it is unlikely that BDNF increases the number of neurons and sympathoblasts by inducing differentiation of non-neuronal cells.\nTo determine whether the increase in the total number of neurons and sympathoblasts is caused by BDNF-induced proliferation, control and BDNF-treated sympathetic cultures were exposed to BrdU for 12 hours after plating, and the number of cells that incorporated BrdU into their DNA was determined after 24 hours in culture. Even in the control condition, a number of cells in the culture are dividing, giving a high baseline of BrdU incorporation (Figure 8B). When BDNF is added, the total number of BrdU positive cells increases approximately 1.6-fold (Figure 8B). This BDNF-induced increase in the total number of BrdU positive cells occurs in sympathoblasts because the number of Islet-1-positive nuclei from control cultures that label with BrdU is 268 ± 59 and BDNF treatment raises this number to 424 ± 80, which corresponds to an increase of 1.6-fold. This accounts for the 1.6-fold increase in total neuron number and total BrdU-positive cells described above. We then confirmed that BDNF acts on TrkB-positive cells: BDNF increases the number of TrkB-expressing cells that incorporate BrdU 2.6 – 4-fold over control (Table 2) and it also increases the overall number of TrkB-positive cells 2 – 2.5-fold over control (Table 2). BDNF does not increase the number of BrdU-positive, TrkB-negative cells or the overall number of TrkB-negative cells (Table 2). In further support that BDNF acts directly on TrkB-expressing cells, an antibody directed against the extracellular domain of TrkB completely prevents the effect of BDNF in promoting proliferation of TrkB-positive, but not TrkB-negative cells (compare Figure 9A to 9B). Thus, the effect of BDNF is restricted to the population that expresses TrkB, which are developing sympathoblasts.\nTo determine whether TrkB-positive cells are actively proliferating in vivo, embryos were injected with BrdU at St. 27 and harvested at St. 29, approximately 24 hrs later. The majority (85–90%) of TrkB-positive cells do not incorporate BrdU into their nuclei under basal conditions in vivo (Figure 10), although a few TrkB positive cells with labeled nuclei could be observed (arrows). This contrasts with our observation that 71–76% of TrkB-positive cells incorporate BrdU in culture after treatment with BDNF (Table 2), suggesting that endogenous BDNF does not achieve a threshold sufficient to support a high level of sympathoblast proliferation in vivo.\n\n\nDiscussion\nWe report that the neurotrophin receptor TrkB is expressed in a subset of embryonic sympathoblasts during the early development of lumbar paravertebral sympathetic ganglia in chicken and mouse embryos. In the chicken, TrkB expression is transient, and completely lost by St 34 (E8). Since BDNF induces the proliferation of sympathoblasts in cell culture, yet in vivo there is little proliferation observed in TrkB-positive cells in nascent ganglia, we propose that if TrkB activation becomes unregulated by excess BDNF or constitutive phosphorylation of TrkB [16], this transient population of TrkB-positive sympathoblasts may trigger the genesis of neuroblastoma, a childhood tumor found in the paravertebral chain and adrenal medulla.\nThe two populations of sympathoblasts that we observe support previous findings of heterogeneity among developing sympathetic neurons and neural crest cells. Early sympathetic ganglia contain at least two subpopulations: early differentiating neurons that lack TrkB expression and express TrkA and TrkC, and late differentiating sympathoblasts that express TrkB. Explant cultures of sympathetic ganglia from E16 chick embryos give rise to two neuronal populations: one that remains close to the explant, and one that migrates away from the explant [1]. In addition, early neuronal subpopulations have been observed in cultures of neural crest cells from St. 13/14 quail embryos as evidenced by the expression of neuronal cell type-specific gangliosides [17]. Perhaps these different subpopulations will ultimately give rise to the two neurochemically distinct populations found in lumbar sympathetic ganglia: the noradrenergic, NPY-containing neurons that innervate internal organs and enteric ganglia and the cholinergic, VIP-containing neurons that innervate vasculature in the hind limbs.\nThe effects of BDNF and TrkB deletion and over expression have been studied on superior cervical ganglion and preganglionic neurons in thoracic segments of the spinal column, but not on paravertebral sympathetic neurons. In the superior cervical ganglion, an increase in the number of neurons of BDNF null mice is likely due to apoptosis induced by BDNF via p75NTR [18]. In contrast, the responses of paravertebral sympathetic neurons to BDNF are complex and subtype dependent. Over expression of BDNF leads to an increase in the number of noradrenergic fibers innervating the erector pilli muscles of hair follicles, while noradrenergic fibers innervating blood vessels were unaffected [19]. If our results indicating that BDNF promotes proliferation of TrkB-positive sympathoblasts in the chicken embryo can be extrapolated to the subset of TrkB-positive sympathoblasts in murine ganglia, then these TrkB-positive cells may be neurons destined to innervate the erector pilli. In other studies, TrkB null mice showed no changes in morphology or cell number in superior cervical ganglia [12] or in the intermediolateral column [20]; but this may not be predictive of a phenotype in the lumbar paravertebral chain. It is thus possible that BDNF/TrkB signaling could play a specific role in other regions of the paravertebral sympathetic chain, such as the lumbar region. However, if TrkB-positive cells are not normally actively proliferating in vivo, then it would not be surprising that the development of the paravertebral sympathetic chain is not disrupted in TrkB or BDNF null mice. It may be more informative to examine mice that over express BDNF on a promoter that targets expression to embryonic lumbar ganglia. Unfortunately, such mice do not exist.\nOur findings that the St. 29/30 (E6.5) sympathoblasts are dependent on both NT-3 and NGF for survival in culture are consistent with previous work on mouse sympathoblasts from the superior cervical ganglion [11]. In these studies, NT-3 and NGF deletion separately led to a decrease in the number of sympathetic neurons at E17.5 compared to control. Deletion of both NT-3 and NGF together did not enhance cell death. In contrast, cultured rat superior cervical ganglion sympathetic neurons respond to NT-3 at E14.5 and then to NGF at E19.5, although time points in between were not analyzed [6].\nIn addition to promoting survival, NT-3, NGF, and BDNF also induce proliferation of various neuronal precursors at different stages of development. NT-3 can promote the incorporation of [3H]-thymidine into cultured quail neural crest cells from the trunk region [21,22], Later in rat sympathetic development, NT-3 supports survival of neurons, but does not promote proliferation [6], which is consistent with our results. NGF promotes an increase in BrdU incorporation from 25% to 35% in the DRG cervical segment 2 in the chick embryo [23]. In chicken embryos that are treated with NGF in ovo at St. 18 and 21, there is an increase in BrdU uptake after formation of the primary sympathetic chain at St. 23 [24]. Since NGF does not appear to affect proliferation of St. 29/30 (E6.5) chick sympathoblasts, NGF may only promote proliferation in primary, but not secondary chain sympathoblasts. Motor neuron progenitors in the ventral neural tube from the chick embryo express TrkB and when ventral neural tube explants are treated with BDNF, there is an increase in the number of motor neurons produced and BrdU incorporation [25]. BDNF also promotes the proliferation of cultured neuroblastoma cells [13]. Taken together, these results are consistent with our findings that NT-3 and NGF do not promote proliferation of St. 29/30 (E6.5) sympathoblasts, and support the assertion that BDNF promotes proliferation of TrkB-positive sympathoblasts in culture.\nOur observations suggest a transient function of TrkB during early sympathetic development in supporting proliferation of this early subpopulation of sympathoblasts. However, the in vivo labeling suggests that only a minority (10–20%) of this population is dividing during the window that TrkB is expressed. In light of the very strong proliferative effect produced in cell culture, these TrkB expressing cells could respond more strongly if endogenous BDNF rises to higher levels, or if the mechanism that down regulates TrkB expression becomes nonfunctional. Such events could trigger an early proliferative event that leads to a cascade of changes that initiates transformation of cells to neuroblastoma. Thus, these early TrkB expressing cells help solve the puzzle as to why TrkB is expressed in aggressive and invasive forms of neuroblastoma, particularly because BDNF induces cultured neuroblastoma cells to become more proliferative, invasive, angiogenic, and resistant to chemotherapeutic reagents than untreated cultures [13]. Future studies will determine whether constitutive expression of BDNF and TrkB in the chick embryo sustains proliferation of differentiating sympathoblasts.\n\nConclusion\nWe have identified a time point during development when differentiating lumbar sympathetic neurons transiently express TrkB and proliferate in response to high concentrations of BDNF in culture. These studies suggest that elevated BDNF expression above basal levels and signaling through TrkB may be a mechanism that contributes to the onset of neuroblastoma. A further understanding of the two populations of sympathetic neurons and the fate of the TrkB-positive cells will provide additional insight into the development of paravertebral sympathetic ganglia and the genesis of neuroblastoma.\n\nMethods\nPreparation of tissue for immunohistochemistry\nThe lumbar spinal column and surrounding tissues were dissected from chicken embryos at the indicated stages and placed in Zamboni's fixative (4% (w/v) paraformaldehyde, 15% (v/v) picric acid in 0.1 M sodium phosphate buffer, pH 7.4) for two hours at room temperature. Mouse embryos at 13–15 days post-coitus were collected according to an IACUC-approved protocol to Dr. L. Sherman at the Oregon Health and Science University. The mouse embryos were immersion-fixed in Zamboni's fixative overnight at 4 degrees C then washed with phosphate buffered saline (PBS; 130 mM NaCl, 20 mM sodium phosphate buffer, pH 7.4). Fixed tissues were equilibrated in 30% sucrose in 1× phosphate-buffered saline (PBS). Fixed mouse embryos were shipped to Vermont in sucrose. Transverse 30 μM sections of the spinal columns were cut at on a Microm HM cryostat (knife temperature: 16°C; object temperature: 23°C) and collected on Superfrost Plus slides (Fisher). Sections were dried at room temperature, washed in 1× PBS and incubated overnight in blocking buffer (1× PBS consisting of 10% (v/v) heat-inactivated horse serum (Invitrogen/Gibco), 0.5% Triton X-100 (Sigma), and 0.1% sodium azide (Fisher)).\n\nImmunohistochemistry\nSections were incubated with primary antibodies overnight at 4°C, followed by incubation with secondary antibodies for 2 hours at room temperature. Primary antibodies used were: rabbit anti-p75 (1:1500, generous gift from Louis Reichardt, UCSF [26]), mouse IgG2b anti-Hu C/D, (1:250, Molecular Probes); mouse IgG1 anti-Islet-1, (1:10, Developmental Studies Hybridoma Bank); rabbit anti-chicken TrkA (1:500); rabbit anti-chicken TrkB (1:500); rabbit anti-chicken TrkC (1:500) (all Trk antibodies were generous gifts of Dr. Louis Reichardt, UCSF [26-28]); mouse anti-HNK-1 (1:50, Developmental Studies Hybridoma Bank); mouse IgG2a anti-tyrosine hydroxylase (1:10, Developmental Studies Hybridoma Bank), sheep anti-BrdU (1:100, Biodesign International), rabbit anti-tyrosine hydroxylase (1:100, Chemicon), and goat anti-TrkB (1:1000, R&D Systems). Immunofluorescence was imaged using a Nikon C1 confocal mounted on a Nikon Eclipse E800 microscope with a 10× Plan Apo (NA 0.785) air objective or a 60× Plan Apo (NA 1.4) oil objective lens, E7-C1 software, and UV, Argon, and He/Ne lasers exciting at 408, 488, and 543 nm and emitting at 404 500–530, and 555–615 nm, respectively. A Nikon Eclipse E800 microscope in the nearby COBRE Molecular/Cellular Core Facility was used for counting immunofluorescent cells at 200× using epifluorescence optics.\n\nRNA Extraction/cDNA synthesis\nSympathetic ganglia were removed from chick embryos and RNA was isolated using TriReagent (Molecular Research Center), an acidified guanidinium with phenol extraction method [29]. RNA was transcribed to cDNA using oligo-dT with Superscript II Reverse Transcriptase (Invitrogen) at 42°C for 1 hour.\n\nReal-time PCR\nRelative RNA levels were determined using quantitative real-time PCR with an ABI 7500 Fast Real Time PCR System. TaqMan probes were used to quantify the progression of the PCR reaction and reactions were normalized using the constitutively expressed gene chick ribosomal binding protein s17 (CHRPS). The sequences were used for primer/probes sets: for BDNF: forward: 5'-AGCCCAGTGAGGAAAACAAG-3', reverse: 5'-ACTCCTCGAGCAGAAAGAGC-3', probe: 5'-[6-FAM]-TACACATCCCGAGTCATGCTGAGCA-[BHQ]-3'; for CHRPS (chick ribosomal binding protein S-17): 5'AACGACTTCCACACCAACAA3', reverse: 5'CTTCATCAGGTGGGTGACAT3', probe: 5'-[6-FAM]-CGCCATCATCCCCAGCAAGA [BHQ]-3'. Primers and probes were synthesized by Operon Technologies, Inc (Alameda, CA). The primers for BDNF were validated against primers for CHRPS according to an Applied BioSystems protocol by serially diluting the target cDNA 1:10, determining the cycle threshold (Ct) for each reaction, and plotting the Ct versus log concentration. Slopes of the resulting lines were calculated and primers were accepted if their Ct slopes were between -3.2 and -3.4 (a perfect efficiency of 1.0 yields a slope of -3.3). To analyze the data, the delta Ct method of relative quantification was used, where the Ct of Chrps was subtracted from the Ct of the gene of interest (Delta Ct) and the arbitrary units of mRNA were expressed as 10000/2^(Delta Ct).\n\nCell culture\nSympathetic neurons were cultured as previously described [30] with a few modifications. Sympathetic ganglia were removed from the lumbar region of the paravertebral chain of St. 29/30 (E6.5) chick embryos and placed in Modified Puck's solution with glucose (MPG). The cells were dissociated by incubation of sympathetic ganglia with 0.1% trypsin in MPG at 37°C for 10 minutes followed by triturating with a fire polished 9\" Pasteur pipette. Cells were then resuspended in Dulbecco's Modified Eagle Medium (DMEM) consisting of 10% horse serum, 2% fetal calf serum, and 10 mg/ml penicillin/streptomycin. For neurotrophin studies, the culture medium was supplemented with 25 ng/ml NT-3 (R & D Systems) and 1 μg/ml 7S NGF (Alomone Labs) upon plating, and 50 ng/ml, 100 ng/ml, or 200 ng/ml BDNF (R & D Systems) once the cells adhered to the wells. Cells were plated on poly-D-lysine/laminin coated wells or cover slips (Fisher) as previously described [30].\n\nQuantification of neurons and sympathoblasts using phase microscopy\nEmbryonic sympathoblasts and neurons are small, phase bright cells with neurites. The total number of cells with neurites the length of two cell bodies were counted in 10 non-overlapping fields of view evenly spaced in a grid-like pattern across the bottom of a well from a 24 well plate at 200× using a Nikon Eclipse TE200 microscope.\n\nBrdU labeling\nFor in vitro studies, approximately 2 hours after plating cells from St. 29/30 (E6.5) sympathetic ganglia, cells were labeled with 10 μM bromodeoxyuridine (BrdU, Sigma) for 12 hours at 37°C. Following this labeling period, cells were incubated in complete medium without BrdU for an additional 10 hrs. Cells were then fixed in Zamboni's fixative for 30 min at room temperature and rinsed with 1× PBS. For in vivo studies, 25 μg BrdU was injected into the amnion of chick embryos at St. 27. The cells and sections were denatured with 2 N HCl at 37°C for 1 hr, and were then neutralized with 0.1 M borate buffer, pH 8.5, for 10 min at room temperature. Immunochemistry was performed as described above.\n\n\nAbbreviations\nBDNF, brain-derived neurotrophic factor; BrdU, Bromodeoxyuridine; DA, dorsal aorta; DMEM, Dulbecco's Modified Eagle's Medium; DRG, dorsal root ganglion; E, embryonic day; HS, horse serum; MPG, Modified Puck's solution with glucose; NGF, nerve growth factor; NC, notochord; NT, neural tube; NT-3, neurotrophin-3; NTR, neurotrophin receptor; PBS, phosphate-buffered saline; SC, spinal cord; SCG, superior cervical ganglion; SEM, standard error of the mean; SG, sympathetic ganglion; St., stage; w/v, weight/volume; v/v, volume/volume.\n\nAuthors' contributions\nJAS designed the experiments, performed the experiments, analyzed the data, and wrote the manuscript. GLSS contributed intellectually to the conception and design of this study, and assisted in the interpretation of the results. RN supervised the study, participated in the design of experiments, edited the manuscript, and obtained funding for the project. All authors read and approved the final manuscript.\n\n\n" ], "offsets": [ [ 0, 32104 ] ] } ]	[ { "id": "pmcA1805739__T0", "type": "species", "text": [ "chicken" ], "offsets": [ [ 644, 651 ] ], "normalized": [ { "db_name": "ncbi", "db_id": "9031" } ] }, { "id": "pmcA1805739__T1", "type": "species", "text": [ "mouse" ], "offsets": [ [ 656, 661 ] ], "normalized": [ { "db_name": "ncbi", "db_id": "10090" } ] }, { "id": "pmcA1805739__T2", "type": "species", "text": [ "chicken" ], "offsets": [ [ 674, 681 ] ], "normalized": [ { "db_name": "ncbi", "db_id": "9031" } ] }, { "id": "pmcA1805739__T3", "type": "species", "text": [ "mouse" ], "offsets": [ [ 1270, 1275 ] ], "normalized": [ { "db_name": "ncbi", "db_id": "10090" } ] }, { "id": "pmcA1805739__T4", "type": "species", "text": [ "chicken" ], "offsets": [ [ 1503, 1510 ] ], "normalized": [ { "db_name": "ncbi", "db_id": "9031" } ] }, { "id": "pmcA1805739__T5", "type": "species", "text": [ "chicken" ], "offsets": [ [ 2672, 2679 ] ], 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1	pmcA1779441	[ { "id": "pmcA1779441__text", "type": "Article", "text": [ "Identification of a human peripheral blood monocyte subset that differentiates into osteoclasts\nAbstract\nIncreased bone resorption mediated by osteoclasts causes various diseases such as osteoporosis and bone erosion in rheumatoid arthritis (RA). Osteoclasts are derived from the monocyte/macrophage lineage, but the precise origin remains unclear. In the present study, we show that the purified CD16- human peripheral blood monocyte subset, but not the CD16+ monocyte subset, differentiates into osteoclast by stimulation with receptor activator of NF-κB ligand (RANKL) in combination with macrophage colony-stimulating factor (M-CSF). Integrin-β3 mRNA and the integrin-αvβ3 heterodimer were only expressed on CD16- monocytes, when they were stimulated with RANKL + M-CSF. Downregulation of β3-subunit expression by small interfering RNA targeting β3 abrogated osteoclastogenesis from the CD16- monocyte subset. In contrast, the CD16+ monocyte subset expressed larger amounts of tumor necrosis factor alpha and IL-6 than the CD16- subset, which was further enhanced by RANKL stimulation. Examination of RA synovial tissue showed accumulation of both CD16+ and CD16- macrophages. Our results suggest that peripheral blood monocytes consist of two functionally heterogeneous subsets with distinct responses to RANKL. Osteoclasts seem to originate from CD16- monocytes, and integrin β3 is necessary for osteoclastogenesis. Blockade of accumulation and activation of CD16- monocytes could therefore be a beneficial approach as an anti-bone resorptive therapy, especially for RA.\n\nIntroduction\nRheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammation and proliferation of the synovium in multiple joints. A large number of inflammatory cells, including T cells, B cells, macrophages and dendritic cells, accumulate in the affected synovium, and these inflammatory cells, together with fibroblast-like synoviocytes, express various cytokines, such as tumor necrosis factor alpha (TNFα), IL-6 and receptor activator of NF-κB ligand (RANKL), which are known to induce differentiation and activation of osteoclasts. The inflammatory synovial tissue, known as pannus, invades the articular bone and causes focal bone erosion, which is the hallmark of RA. Histopathologically, osteoclasts are present at the interface of the pannus and bone. Interestingly, the deletion of RANKL or c-Fos gene, which is important for osteoclastogenesis, results in minimal bone destruction in mouse models of arthritis [1,2]. Furthermore, other studies indicated that inhibition of osteoclastogenesis by osteoprotegerin, a decoy receptor for RANKL, limits bone destruction in experimental models of arthritis. These studies suggest that osteoclasts are involved in focal bone erosion in RA [3].\nOsteoclasts are derived from the monocyte/macrophage lineage. It is reported that osteoclast precursors reside in human peripheral blood monocytes [4,5]. A marked increase of the circulating osteoclast precursors was demonstrated in patients with erosive psoriatic arthritis as well as in arthritic TNFα transgenic mice [6,7]. It was also shown that peripheral monocytes differentiate into osteoclasts when seeded on RANKL/osteoclast differentiation factor-producing RA synovial fibroblasts [8]. In addition, RA synovial macrophages thought to originate from peripheral blood monocytes were shown to differentiate into osteoclasts [9,10]. Monocytes are therefore involved not only in synovial inflammation, but also in bone remodeling as potential precursors for synovial macrophages and osteoclasts.\nHuman peripheral blood monocytes consist of two major subsets, CD16+ and CD16-, comprising 5–10% and 90–95% of the monocytes, respectively. These two subsets exhibit different chemotaxis activities and potential of cytokine production [11,12]. Moreover, activation of the Toll-like receptor induces distinct subsets, CD1b+ dendritic cells and DC-SIGN+ (dendritic cell-specific C-type lectin ICAM-3-grabbing nonintegrin) macrophages from CD16+ and CD16- monocytes, respectively [13]. It has not been revealed, however, which monocyte subset develops into osteoclasts.\nIn the present study, we determined the human peripheral blood monocyte subset that differentiates into osteoclasts, and revealed that each subset exhibits a different response for osteoclastogenic stimuli.\n\nMaterials and methods\nPurification of peripheral blood monocytes\nPeripheral blood monocytes from healthy donors were collected using Ficoll-Conray (Imuuno-Biological Laboratories, Gunma, Japan) gradient centrifugation. Negative selection of monocytes was performed using MACS microbeads (Miltenyi Biotec, Auburn, CA, USA) according to the protocol supplied by the manufacturer.\nThe purified monocytes were separated into two subsets, CD16+ and CD16- monocytes, using CD16 MicroBeads (Miltenyi Biotec). Flow cytometry analysis using FITC-conjugated mouse anti-CD14 mAb (MY4; Bechman Coulter, Fullerton, CA, USA) and phycoerythin-conjugated mouse anti-CD16 mAb (3G8; BD Biosciences, San Jose, CA, USA) showed that the purities of the CD16+ and CD16- monocytes were more than 90% and 92%, respectively.\nFor the other experiment, monocytes were purified using CD14 MicroBeads (Miltenyi Biotec), and then stained either with FITC-conjugated mouse anti-CD33 mAb (MY9; Bechman Coulter) or phycoerythin-conjugated mouse anti-CD16 mAb (3G8). Cell sorting of the stained cells was performed using a FACS Vantage cytometer (BD Biosciences) or a MoFlo cell sorter (Dako, Glostrup, Denmark).\n\nOsteoclast differentiation\nPurified CD16+ and CD16- monocytes (5 × 104 cells/well) were incubated in 96-well plates in αMEM (Sigma, St Louis, MO, USA) with heat-inactivated 10% fetal bovine serum (FBS) (Sigma) or with Ultra-Low IgG FBS (IgG < 5 μg/ml; Invitrogen, Carlsbad, CA, USA), and where indicated with M-CSF + RANKL (Peprotech, Rocky Hill, NJ, USA).\nFor the other experiments, varied numbers of CD16+ monocytes (1 × 103, 2.5 × 103, 5 × 103) were mixed with CD16- monocytes (5 × 104 cells/well), and were cultured in 96-well plates in αMEM with heat-inactivated 10% FBS. The medium was replaced with fresh medium 3 days later, and after incubation for 7 days the cells were stained for tartrate-resistant acid phosphatase (TRAP) expression using a commercial kit (Hokudo, Sapporo, Japan). The number of TRAP-positive multinucleated cells (MNC) in three randomly selected fields examined at 100× magnification or the total number of TRAP-positive MNC per well was counted under light microscopy.\n\nResorption assay\nMonocytes were seeded onto plates coated with calcium phosphate thin films (Biocoat Osteologic; BD Biosciences) and were incubated with RANKL (40 ng/ml) + M-CSF (25 ng/ml) for 7 days. The cells were then lysed in bleach solution (6% NaOCl, 5.2% NaCl). The resorption lacunae were examined under light microscopy.\n\nEnzyme-linked immunosorbent assay\nPurified monocytes were cultured in 96-well plates where indicated either with RANKL or M-CSF for 24 hours. Concentrations of TNFα and IL-6 in the culture supernatant were measured with an ELISA kit (BioSourse International, Camarillo, CA, USA). For experiments of matrix metalloproteinase (MMP)-9 and TRAP-5b, culture supernatants were collected on day 7 and the concentrations of these enzymes were measured using an MMP-9 ELISA kit (Amersham Biosciences, Piscataway, NJ, USA) or a TRAP-5b ELISA kit (Suomen, Turku, Finland).\n\nReverse transcriptase-polymerase chain reaction\nMonocytes (1 × 106 cells/well) were cultured in six-well plates with M-CSF alone or with M-CSF + RANKL for 3 days. Total RNA was extracted using RNeasy Micro (Qiagen, Valencia, CA, USA). The RNA was then treated with DNase I (Qiagen). The oligo(dT)-primed cDNA was synthesized using Superscript II reverse transcriptase (Invitrogen). The amount of cDNA for amplification was adjusted by the amount of RNA measured by an optical density meter and also by β-actin or GAPDH PCR products. One microliter of cDNA was amplified in a 50 μl final volume containing 25 pmol appropriate primer pair, 10 pmol each of the four deoxynucleotide triphosphates, and 5 units FastStart Taq DNA Polymerase (Roche, Manheim, Germany) in a thermal cycler (PTC-200; MJ GeneWorks, Waltham, MA, USA).\nThe PCR conditions were 25–40 cycles of denaturation (95°C for 30 s), annealing (60–62°C for 1 min) and extension (72°C for 1 min). The sequences of the primers are presented in Table 1. The PCR products were separated by electrophoresis through 2% agarose gel.\n\nWestern immunoblot analysis\nPurified monocytes were cultured for 3 days in the presence of 40 ng/ml M-CSF with or without 25 ng/ml RANKL. Cells were lysed in RIPA Lysis buffer (upstate, Lake Placid, NY, USA) containing protease inhibitors (Roche) for 15 min at 4°C. A total of 20 μg protein was boiled in the presence of 6 × sodium dodecyl sulfate sample buffer, and was separated on 7.5% or 10% sodium dodecyl sulfate-polyacrylamide gel (ATTO, Tokyo, Japan). Proteins were then electrotransferred to a polyvinylidene fluoride microporous membrane (Millipore, Billerica, MA, USA) in a semidry system. Membranes were incubated in 10% skim milk prepared in phosphate-buffered saline (PBS) containing 0.1% Tween 20, and were subjected to immunoblotting. Antibodies used were goat anti-RANK antibody (Techne Corporation, Minneapolis, MN, USA), goat anti-c-fms antibody (R&D systems, Minneapolis, MN, USA), and mouse anti-β-actin mAb (AC-15; Sigma). Peroxidase-conjugated rabbit anti-goat IgG antibody (Dako) or peroxidase-conjugated rabbit anti-mouse IgG antibody (Dako) was used as the second antibody. The signals were visualized by chemiluminescence reagent (ECL; Amersham Biocsiences, Little Chalfont, UK).\n\nCell surface expression of c-fms\nThe following mAbs were used for analysis of c-fms expression: Alexa 647-conjugated anti-CD14 mAb (UCHM1; Serotec, Oxford, UK), FITC-conjugated anti-CD16 mAb (3G8; Bechman Coulter) and phycoerythin-conjugated anti-c-fms mAb (61708; R&D systems). Alexa 647-conjugated mouse IgG2a (Serotec), FITC-conjugated mouse IgG1 (BD Biosciences) and phycoerythin-conjugated mouse IgG1 (Bechman Coulter) were used as isotype controls. Peripheral blood monocytes (1 × 105 cells) were incubated with 1 μg human IgG for 15 minutes, and were then stained with three fluorochrome-labeled mAbs for 45 minutes on ice. The stained cells were analyzed with a FACS Calibur (BD Biosciences).\n\nImmunofluorescent staining\nMonocytes (8 × 104 cells/well) were allowed to adhere on 96-well plates overnight or were cultured with M-CSF and RANKL for 2–4 days. The cells were fixed in acetone and then stained with anti-αvβ3 mAb (LM609; Chemicon, Temecula, CA, USA) or mouse IgG1 (11711; R&D Systems) as an isotype-matched control. Alexa fluor546-conjugated goat anti-mouse IgG1 antibody (Molecular Probes, Eugene, OR, USA) was used as the second antibody. TOTO-3 (Molecular Probes) was used for nuclear staining.\n\nFlow cytometric analysis of p38 MAPK and ERK1/2 phosphorylation\nPurified monocytes were cultured in the presence of 25 ng/ml M-CSF for 3 days, and were either left unstimulated or were stimulated with 40 ng/ml RANKL at 37°C. Stimulations were stopped by adding an equal volume of PhosFlow Fix Buffer I solution (BD Biosciences) to the cell culture. After incubation for 10 minutes at 37°C, the cells were permeabilized by washing twice at room temperature in PhosFlow Perm/Wash Buffer I (BD Biosciences). A total of 1 × 105 cells was then Fc blocked with 1 μg human IgG for 15 minutes, and was stained with Alexa Fluor 647-conjugated mAb either to phospho-p38 MAPK (T180/Y182) or to phospho-ERK1/2 (T202/Y204) (BD Biosciences) for 30 minutes at room temperature. Alexa Fluor 647-conjugated mouse IgG1 (BD Biosciences) was used as an isotype control. The cells were washed in PhosFlow Perm/Wash Buffer I, and were analyzed by flow cytometry, as already described.\n\nRNA interference\nRNA oligonucleotides (iGENE, Tsukuba, Japan) were designed based on the algorithm that incorporates single nucleotide polymorphism and homology screening to ensure a target-specific RNA interference effect. The following sense and antisense oligonucleotides were used: integrin β3, 5'-GCU UCA AUG AGG AAG UGA AGA AGC A-AG and 3'-UA-CGA AGU UAC UCC UUC ACU UCU UCG U; randomized control, 5'-CGA UUC GCU AGA CCG GCU UCA UUG C-AG and 3'-UA-GCU AAG CGA UCU GGC CGA AGU AAC G; and lamin, 5'-GAG GAA CUG GAC UUC CAG AAG AAC A-AG and 3'-UA-CUC CUU GAC CUG AAG GUC UUC UUG U.\nCD16- monocytes (8 × 104 cells/well) were incubated in 96-well plates in optimem (Invitrogen). After 1 hour, siRNAs were transfected into the cells using oligofectamine (Qiagen) based on the method recommended by the manufacturer. After 2 hours, the cells were washed once with PBS, followed by the addition of αMEM supplemented with 10% FBS, M-CSF and RANKL. After a 2-day incubation, the β3 mRNA expression was analyzed by RT-PCR with different PCR cycles, as described earlier. Immunofluorescent staining for the αvβ3 heterodimer was also performed as described above, and numbers of αvβ3-positive cells were counted in randomly selected three fields at 100× magnification. Seven days after the transfection of siRNAs, the number of TRAP-positive MNC in five fields examined at 100× magnification was counted under light microscopy.\n\nInhibition of osteoclastogenesis with cyclic RGDfV peptide\nCD16- monocytes were incubated in 96-well plates with M-CSF + RANKL for 2 days. A medium containing either cyclic RGDfV peptide (Arg-Gly-Asp-D-Phe-Val) (Calbiochem, San Diego, CA, USA) or dimethyl sulfoxide was then added. After incubation for a further 5 days, the number of TRAP-positive MNC in five fields examined at 100× magnification was counted under light microscopy.\n\nImmunohistochemistry\nSynovial tissue samples were obtained during total knee joint replacement surgery from four RA patients. Signed consent forms were obtained before the operation. The experimental protocol was approved by the ethics committee of the Tokyo Medical and Dental University. RA was diagnosed according to the American College of Rheumatology criteria [14].\nDouble immunofluorescent staining for CD68 and CD16 antigens was conducted on optimal cutting temperature-embedded sections of frozen synovial samples. Eight-micrometer-thick cryostat sections of RA synovium were fixed in acetone for 3 minutes and were then rehydrated in PBS for 5 minutes. The samples were incubated in 5 μg/ml proteinase K (Roche), 50 mM ethylenediamine tetraacetic acid, 100 mM Tris–HCl, pH 8.0, for 15 minutes at room temperature followed by a wash in PBS. The samples were then blocked with 10% goat serum in PBS for 60 minutes at room temperature, and were incubated with anti-CD16 mAb (3G8; Immunotech, Marseille, France) or mouse IgG1 (11711) as an isotype-matched control in 1% bovine serum albumin/PBS for 60 minutes at room temperature. The samples were then washed three times in PBS, for 5 minutes each, and incubated with Alexa fluor546-conjugated goat anti-mouse IgG1 antibody (Molecular Probes) in 1% bovine serum albumin/PBS for 60 minutes at room temperature. The samples were then sequentially stained for CD68 antigen in a manner similar to that used for CD16 staining. The samples were stained with anti-CD68 mAb (PGM1; Immunotech) or mouse IgG3 (6A3; MBL, Nagoya, Japan) followed by labeling with Alexa fluor488-conjugated goat anti-mouse IgG3 antibody (Molecular Probes). The samples were examined by confocal laser scanning microscope (Olympus, Tokyo, Japan).\n\nStatistical analysis\nData are expressed as the mean ± standard error of the mean. A nonpaired Student's t test was used for comparison, using the StatView program (Abacus Concepts, Berkeley, CA, USA). P < 0.05 was considered statistically significant.\n\n\nResults\nInduction of osteoclasts from CD16- peripheral blood monocytes\nTo identify the monocyte subset that differentiates into osteoclasts, we examined osteoclast formation from CD16+ and CD16- human peripheral blood monocytes. The monocyte subsets were purified using magnetic beads. Incubation with M-CSF alone did not induce osteoclast formation from either subset (Figure 1a). Culture with M-CSF + RANKL induced a significant number of TRAP-positive MNC from the CD16- subset, whereas only few CD16+ monocytes differentiated into TRAP-positive MNC (Figure 1a,b). We then assessed the bone resorptive ability by culturing cells on calcium phosphate-coated plates with M-CSF + RANKL. Resorption lacunae were detected only in the CD16- subset (Figure 1c), indicating the TRAP-positive CD16--derived MNC possessed the osteoclast phenotype.\nSimilar results were obtained using purified monocytes by FACS sorting (purities: CD16+, 96%; CD16-, 97%). The number of TRAP-positive MNC induced were 36 ± 3 cells/well and 348 ± 13 cells/well from CD16+ and CD16- monocytes, respectively. To exclude the possibility that the anti-CD16 antibody used for isolation of CD16+ monocytes inhibits osteoclast formation, we separated the two subsets, CD33low monocytes and CD33high monocytes, using anti-CD33 mAb and a fluorescent cell sorter, since it was reported that CD33low monocytes correspond to CD16+, and that CD33high correspond to CD16- monocytes [15]. On average, the CD33low population contained CD16- (10.2%)/CD16+ (89.8%) monocytes, and the CD33high population contained CD16- (86.3%)/CD16+ (13.7%) monocytes.\nCulture with M-CSF + RANKL induced TRAP-positive MNC from CD33high monocytes, whereas no or few CD33low monocytes differentiated into TRAP-positive MNC (CD33low vs CD33high, 2 ± 1 vs 192 ± 71 cells/well; n = 3). TRAP-5b and MMP-9 in the culture supernatants, both of which are known to be produced by osteoclasts, were measured by ELISA. The concentrations of both enzymes were significantly higher in the culture supernatant of CD16- monocytes than in that of CD16+ monocytes (Figure 1d). These results suggest that the CD16- peripheral blood monocyte subset, but not the CD16+ subset, differentiate into osteoclasts by incubation with RANKL + M-CSF.\n\nCD16+ monocytes do not affect the osteoclastogenesis from CD16- monocytes\nTo examine whether CD16+ monocytes affect osteoclastogenesis from CD16- monocytes, varied numbers of CD16+ monocytes were mixed with CD16- monocytes (5 × 104 cells/well), and were cultured for 7 days in the presence of M-CSF + RANKL. The number of TRAP-positive MNC was not altered by the presence of CD16+ monocytes (Figure 2). The results indicated that CD16+ monocytes did not hamper or enhance the osteoclastogenesis from CD16- monocytes.\n\nDifferences in cytokine production by RANKL-stimulated or M-CSF-stimulated CD16+ and CD16- monocytes\nTo compare the biological response of CD16+ and CD16- subsets with either RANKL or M-CSF stimulation, we measured the amount of TNFα and IL-6 production after exposure of cells to various concentrations of RANKL or M-CSF with an ELISA. Without RANKL the CD16+ subset produced a significant amount of TNFα and IL-6, whereas the CD16- subset produced undetectable levels (Figure 3a). RANKL stimulation increased TNFα production from both subsets in a dose-dependent manner, although the CD16+ subset produced more TNFα than did the CD16- subset. RANKL stimulation also enhanced IL-6 production from the CD16+ subset, but not from the CD16- subset. M-CSF stimulation increased TNFα and IL-6 production from both subsets, although the CD16+ subset produced more than the CD16- subset (Figure 3b).\nThese results suggest that CD16+ monocytes also respond both to RANKL and M-CSF stimulation, although such stimulation does not result in differentiation into osteoclasts. CD16+ monocytes were also noted to express higher amounts of inflammatory cytokines compared with CD16- monocytes with or without RANKL or M-CSF stimulation.\n\nComparison of expression levels of molecules involved in osteoclastogenesis between CD16+ and CD16- monocytes\nDiverse molecules are involved in RANKL/RANK and its costimulatory signal transduction pathways [16]. The different response to RANKL + M-CSF stimulation between the CD16+ monocyte subset and the CD16- monocytes subset might be explained by the expression profiles of these molecules. We therefore examined the mRNA levels of the following molecules: receptor activator of NF-κB (RANK), the receptor for RANKL; c-fms, the receptor for M-CSF; tumor necrosis factor receptor-associated factor 6 (TRAF-6), the adaptor protein for RANK; c-Fos and nuclear factor of activated T cells c1 (NFATc1), transcription factors that are essential for osteoclastogenesis; DNAX-activation protein 12 (DAP12) and Fc receptor γ chain (FcRγ), adaptor proteins known to deliver costimulatory signals in RANKL-induced osteoclastogenesis; signal regulatory protein β1 (SIRP-β1), triggering receptor expressed on myeloid cells 2 (TREM-2) and osteoclast-associated receptor (OSCAR), transmembrane receptors that associate with either DAP12 or FcRγ; and αv and β3, integrins known to be expressed as the αvβ3 heterodimer on osteoclasts.\nThe mRNA levels of RANK, c-fms, TRAF-6, DAP12 and SIRP-β1 under the baseline condition (no stimulation) varied between the donors; however, we did not find consistent differences in the mRNA levels of these molecules between the CD16+ monocyte subset and the CD16- monocyte subset among three to six donors (Figure 4a). The mRNA levels of other molecules, apart from integrin β3, were similar between the two subsets under the no-stimulation condition. Although the mRNA levels of RANK, c-fms, DAP12, FcRγ, TREM-2 and OSCAR increased in response to M-CSF alone or M-CSF + RANKL in both subsets, the expression levels were not significantly different between the two subsets. Expressions of TRAF-6, c-Fos and SIRP-β1 mRNA did not change following stimulation with M-CSF + RANKL. Of note, the expression of NFATc1 mRNA was enhanced by M-CSF + RANKL treatment only in the CD16- subset. Furthermore, expression of integrin αv in both subsets was enhanced by M-CSF with or without RANKL; however, the expression level was greater in the CD16- subset. It was noted that integrin-β3 mRNA was detected only in the CD16- subset and was increased by M-CSF + RANKL stimulation, but not by M-CSF alone. The protein expression of RANK under the baseline condition was weakly detected in both subsets, and the levels were varied between donors by western immunoblotting.\nThe protein expression of c-fms was weakly detected in unstimulated CD16+ monocytes, but not in CD16- monocytes (Figure 4b). Flow cytometry analysis of c-fms in fresh monocytes, however, showed that both subsets express the molecule on the cell surface (Figure 4c). Expressions of both RANK and c-fms were upregulated by M-CSF alone and by M-CSF + RANKL, and we did not find consistent differences in the protein levels of these molecules between the two monocyte subsets. The profiles of expression levels of molecules involved in RANKL/RANK and its costimulatory pathways are similar between the two subsets, except for NFATc1, integrin αv and integrin β3. We therefore assumed that the distinct induction of NFATc1, integrin αv and integrin β3 in response to RANKL stimulation among the two monocyte subsets might explain the differences in their abilities to differentiate into osteoclasts.\n\nRANKL stimulation induces αvβ3 expression on CD16- monocytes\nThe integrin-β3 subunit binds to integrin αv only and is expressed as the heterodimeric protein αvβ3 on monocytes and osteoclasts [17]. We examined the expression of αvβ3 on CD16+ and CD16- monocytes by immunofluorescent staining. Neither unstimulated nor M-CSF-stimulated monocyte subsets expressed αvβ3 (Figure 4d and data not shown). After 48 and 72 hours of treatment with M-CSF + RANKL, αvβ3-positive mononuclear cells were observed in CD16- monocyte cultures but not in CD16+ monocyte cultures. At 96 hours, both αvβ3-positive mononuclear cells and multinucleated cells were present in the CD16- monocyte culture. The results indicated that αvβ3 was selectively expressed on CD16- monocytes in the presence of M-CSF + RANKL, and the expression was revealed before the cells differentiate into typical multinucleated osteoclasts.\n\nRANKL activates ERK and p38 kinases only in CD16- monocytes\nSince ERK and p38 MAPK are essential in RANKL-induced osteoclastogenesis [18-20], we next examined whether these kinases were activated differently in CD16+ monocytes and in CD16- monocytes. Purified monocytes were precultured with 25 ng/ml M-CSF for 3 days to enhance RANK expression, and were then treated with RANKL. The RANKL treatment induced phosphorylation of both ERK and p38 MAPK in CD16- monocytes at 5 minutes postexposure, although the p38 MAPK phosphorylation was weak. Both phosphorylations declined to a basal level within 20 minutes (Figure 5). In contrast, ERK and p38 MAPK were not detectably phosphorylated in CD16+ monocytes with RANKL.\n\nsiRNA targeting integrin β3 inhibits osteoclastogenesis from CD16- monocytes\nThe integrin-β3 cytoplasmic domain is essential for activation of intracellular signals from αvβ3 heterodimers [17]. We therefore examined the involvement of αvβ3 in RANKL + M-CSF-induced osteoclastogenesis in human CD16- monocytes using siRNA targeting the integrin-β3 subunit. The integrin-β3 siRNA or control randomized siRNA were transfected into CD16- monocytes. At 48 hours post-transfection, we determined the integrin-β3 mRNA level and αvβ3 heterodimer protein expression. The integrin-β3 mRNA level was reduced in the integrin-β3 siRNA-transfected monocytes compared with control siRNA-transfected monocytes (Figure 6a). The αvβ3 heterodimer expression was evaluated by immunofluorescent staining. The number of αvβ3-positive cells was significantly decreased in integrin-β3 siRNA-transfected monocytes compared with that in control siRNA (Figure 6b).\nAfter 7 days of incubation, the number of TRAP-positive MNC was counted. Transfection with integrin-β3 siRNA significantly reduced the number of TRAP-positive MNC in a dose-dependent manner compared with control siRNA transfection (Figure 6c). In addition, the use of siRNA directed toward a different site of integrin-β3 mRNA also inhibited osteoclast formation from CD16- monocytes (data not shown). On the other hand, siRNA that targeted lamin, which was used as a negative control, did not inhibit the induction of osteoclasts (data not shown). These results indicate the importance of integrin β3 in RANKL-induced osteoclast formation from CD16- peripheral blood monocytes.\n\nCyclic RGDfV peptide inhibits the osteoclastogenesis from CD16- monocytes\nIntegrin αvβ3 recognizes a common tripeptide sequence, RGD (Arg-Gly-Asp), which is present in bone matrix proteins such as vitronectin and fibronectin [21]. Cyclic RGDfV peptide (Arg-Gly-Asp-D-Phe-Val) inhibits binding of the RGD-containing molecules to αvβ3 [22]. To investigate the role of ligand binding to the αvβ3 heterodimer in the osteoclastogenesis, we examined whether cyclic RGDfV peptide inhibits the formation of osteoclasts. Cyclic RGDfV peptide significantly reduced the number of TRAP-positive MNC in a dose-dependent manner (Figure 6d). The results imply possible involvement of ligand bindings to αvβ3 in the osteoclastogenesis.\n\nKnockdown of integrin β3 did not affect the expression of NFATc1 mRNA\nIn the next step, we determined whether integrin-β3-siRNA-induced inhibition of the osteoclastogenesis reflects downregulation of NFATc1, which is a key transcription factor in osteoclastogenesis [23]. For this purpose, we compared NFATc1 mRNA levels between integrin β3 and control siRNA-transfected monocytes. Interestingly, integrin-β3 knockdown did not alter the NFATc1 mRNA level (Figure 7), suggesting that signal transduction mediated by integrin β3 does not affect the expression of NFATc1.\n\nDetection of CD16+ and CD16- macrophages in synovium of RA patients\nRA synovial macrophages are derived from peripheral blood monocytes, and their recruitment into the synovium is facilitated by various adhesion molecules and chemokines [24]. To analyze CD16 expression on synovial macrophages, RA synovial tissues were double-stained for CD16 and a macrophage marker, CD68. CD16-/CD68+ macrophages were widespread in the synovium. Although less frequent, CD16+/CD68+ macrophages were also observed both in the synovial intima and subintima (Figure 8). The presence of two subsets of macrophages, CD16+ and CD16-, in RA synovium indicates that both CD16+ and CD16- peripheral blood monocytes are recruited into the synovium.\n\n\nDiscussion\nHuman peripheral blood monocytes are a heterogeneous population, and they are divided into two subsets based on the expression of CD16. The CD16+ and CD16- monocyte subsets show functional differences in migration, cytokine production and differentiation into macrophages or dendritic cells [11-13,15]. We focused on the heterogeneity of the monocytes, and the primary question addressed in this study was which monocyte subset could be the source of osteoclasts. The results demonstrated that CD16- peripheral blood monocytes, but not CD16+ monocytes, differentiated in vitro into osteoclasts by treatment with RANKL + M-CSF.\nTo investigate the molecular mechanisms of the different response to RANKL and the differentiation into osteoclasts between CD16+ and CD16- monocytes, we examined the expression of molecules known to be involved in osteoclastogenesis. The expression profiles of integrin αv, integrin β3 and NFATc1 were different between the two subsets. Integrin αvβ3 heterodimer was expressed only on RANKL and M-CSF-stimulated CD16- monocytes. It is known that αvβ3 expressed on osteoclasts is important in bone resorption as well as in attachment of osteoclasts to the bone matrix [25].\nIt was recently reported that bone marrow macrophages of integrin-β3-deficient mice could not differentiate into mature osteoclasts in vitro, suggesting that αvβ3 is involved not only in activation, but also in differentiation, of osteoclasts in mice [26,27]. The authors also showed that αvβ3 and c-fms share a common intracellular signaling pathway, including the activation of ERK and the induction of c-Fos [27], both of which are essential for osteoclastogenesis [28,29]. In addition, it was reported that echistatin, an αvβ3 antagonist, inhibited osteoclast formation of mouse bone marrow cells [30].\nIn accordance with these reports, our data showed that knockdown of integrin-β3 expression resulted in downregulation of the αvβ3 heterodimer, and abrogated osteoclastogenesis from human peripheral blood CD16- monocytes. We also showed that blocking of adhesive ligands to bind to αvβ3 by RGDfV peptide inhibited osteoclast formation from CD16- monocytes. Taken together, the process of ligand binding to αvβ3 may be involved in the osteoclastogenesis. Blockade of αvβ3 could therefore be a therapeutically beneficial approach to modulate osteoclastogenesis. Indeed, integrin αvβ3 antagonists effectively treated osteoporosis in mice, rats and humans, and protected bone destruction in rat adjuvant-induced arthritis in vivo [31-34]. Of note, it is reported that patients with Iraqi-Jewish-type Glanzmann thrombasthenia who are deficient in integrin β3 do not develop osteopetrosis because of the upregulation of α2β1 expression on osteoclasts, although the bone-resorptive ability of the osteoclasts was decreased in vitro [35]. The function of αvβ3 in vivo in osteoclast formation and resorptive function could therefore be partially compensated by other integrins.\nAlthough all the multinucleated osteoclasts expressed αvβ3 (Figure 4d) [36], a small number of M-CSF + RANKL-stimulated mononuclear CD16- monocytes expressed αvβ3 (Figure 4d). Multinucleated osteoclasts are formed by fusion of osteoclast precursor cells [37]. It was reported that αvβ3 is involved in the migration of osteoclast precursors [30]. The αvβ3-positive cells could therefore be forced to migrate by the ligands and may fuse with closed αvβ3-negative cells. Alternatively, only αvβ3-positive cells may be fused with each other.\nIt is possible to consider that signaling from CD16 by anti-CD16 mAb-coated magnetic beads, which were used for the cell separation, or by IgG contained in FBS might inhibit osteoclastogenesis from CD16+ monocytes. We therefore separated the two subsets using anti-CD33 mAb and a fluorescent cell sorter, and stimulated the cells with M-CSF + RANKL. The results showed that CD33low monocytes, which correspond to CD16+ monocytes, still could not differentiate into osteoclasts. CD16 is a heterodimer consisting of FcγIIIa and Fcγ, and has low affinity for the Fc region of IgG. Aggregation of CD16 by immune complexes leads to transmission of activating signals via the immunoreceptor tyrosine-based activation motif in the γ chain [38]. We also assessed osteoclastogenesis from the two monocyte subsets using IgG-depleted bovine serum. Even in the IgG-free medium, CD16- monocytes but not CD16+ monocytes differentiated into osteoclasts (data not shown). We could therefore exclude the possibility that signal transduction through CD16 inhibits osteoclastogenesis from CD16+ monocytes.\nNFATc1 is a key transcription factor in osteoclastogenesis [16]. In the present study, stimulation with M-CSF + RANKL increased the NFATc1 mRNA expression in the CD16- subset only, similar to integrin αv and integrin β3. The differences in NFATc1 induction might therefore also explain the difference in osteoclastogenesis between the two monocyte subsets. It is of interest that knockdown of integrin β3 did not lower the mRNA level of NFATc1. This result supports the notion that NFATc1 is located upstream of integrin-β3 expression [39]. It is also possible that parallel activation of two signaling pathways mediated by integrin β3 and NFATc1 contributes to osteoclastogenesis independently or cooperatively. Further studies are needed to determine the mechanisms of integrin β3 involvement in RANKL/RANK-mediated osteoclast differentiation.\nIt has been demonstrated that MAPK families, ERK and p38 MAPK, were activated by RANKL-induced intracellular signalings in osteoclasts and osteoclast precursors [18,19]. In addition, these kinases are involved in the differentiation of osteoclasts [20]. We showed that RANKL stimulation induced phosphorylation of ERK and p38 MAPK only in CD16- monocytes. It is suggested that differential activation of these kinases may partially explain the distinct properties of the two monocyte subsets upon RANKL stimulation.\nOur results showed that CD16+ monocytes produce higher levels of inflammatory cytokines including TNFα and IL-6 compared with CD16- monocytes. These results are consistent with the previous report showing that CD16+ monocytes produced larger amounts of TNFα upon lipopolysaccharide or lipopeptide stimulation than did CD16- monocytes [40]. Interestingly, we showed that stimulation either with RANKL or M-CSF upregulated the TNFα and IL-6 production by CD16+ monocytes. A marked increase of CD16+ monocytes in peripheral blood is reported in inflammatory diseases, such as infection, malignancy, Kawasaki disease and RA [41-44]. Taken together, CD16+ monocytes may be an important source of inflammatory cytokines.\nIn mice, peripheral blood Ly-6Chigh monocytes, which are thought to correspond to human CD16- monocytes, increase in inflammatory conditions, and these cells are recruited into sites of inflammation [45]. In contrast, Ly-6Clow monocytes, which are thought to correspond to human CD16+, migrate into noninflamed tissues [12]. These data on mouse monocytes seem to be in contrast to the data on human monocytes, which show expansion of CD16+ monocytes in inflammatory conditions where they produce larger amounts of inflammatory cytokines. At present, it is not clear whether mouse monocyte subsets, Ly-6Clow/Ly-6Chigh, represent human monocyte subsets, CD16+/CD16- monocytes, and whether the biologic functions of mouse monocytes are analogous to those of human monocytes.\nIn mice, blood monocytes newly released from the bone marrow are exclusively Ly-6Chigh and the level of Ly-6C is downregulated while in circulation [45]. It is thus suggested that in mice the two monocyte subsets differing in Ly-6C expression represent different stages in the maturation pathway. In the human, transition from CD16- monocytes to CD16+ monocytes is observed upon culture with IL-10, M-CSF and transforming growth factor beta in vitro [42,46]. Similar to mouse monocytes, therefore, human peripheral blood CD16- monocytes may also maturate into CD16+ monocytes.\nIt is reported that a significant number of RA synovial cells in the intima express CD16, suggesting that CD16+ cells are synovial macrophages [47]. We confirmed that both CD16+ and CD16- macrophages accumulate in the RA synovium by double-color immunohistochemical staining for CD68 and CD16. A number of chemokines are abundantly expressed in the RA synovium [24,48]. Among these cytokines, MCP-1, MIP-1α, SDF-1, RANTES and fractalkine can induce migration of CD16- monocytes in vitro ([11,12] and unpublished data). On the other hand, migration of CD16+ monocytes is induced only by fractalkine. These chemokines therefore seem to play an important role in recruitment of CD16+ and CD16- monocytes from the circulating pool into the RA synovium.\nThe osteoclast inducers are also produced in the RA synovium. RANKL is expressed by synovial fibroblasts and activated T cells [49-51], while M-CSF is expressed on RA synovial macrophages and fibroblasts [52,53].\nTNFα and IL-6, which are mainly expressed on RA synovial macrophages and fibroblasts, respectively, could also enhance osteoclast differentiation [54]. Collectively, it is probable that the recruited CD16- monocytes/macrophages differentiate into osteoclasts in the RA synovium, and contribute to bone destruction. On the other hand, CD16+ monocytes/macrophages might also be involved in RA pathogenesis by producing inflammatory cytokines including TNFα and IL-6. Since TNFα and IL-6 enhance osteoclast formation [54,55], CD16+ monocytes/macrophages may also contribute to osteoclastogenesis in RA synovium.\n\nConclusion\nWe have shown that human peripheral blood monocytes consist of two functionally heterogeneous subsets with distinct response to osteoclastogenic stimuli. Osteoclasts seem to originate from CD16- monocytes, and integrin β3 is necessary for the osteoclastogenesis. The blockade of accumulation and activation of CD16- monocytes could therefore be a beneficial approach as an anti-bone resorptive therapy, especially for RA.\n\nAbbreviations\nDAP = DNAX-activation protein; ELISA = enzyme-linked immunosorbent assay; FBS = fetal bovine serum; FcRγ = Fc receptor γ chain; IL = interleukin; FITC = fluorescein isothiocianate; mAb, monoclonal antibody; M-CSF = macrophage colony-stimulating factor; MEM = modified Eagle's medium; MMP = matrix metalloproteinase; MNC = multinucleated cells; NF = nuclear factor; OSCAR = osteoclast-associated receptor; PBS = phosphate-buffered saline; PCR = polymerase chain reaction; RA = rheumatoid arthritis; RANK = receptor activator of NF-κB; RANKL = receptor activator of NF-κB ligand; RT = reverse transcriptase; siRNA = small interfering RNA; SIRP-β1 = signal regulatory protein-β1; TNFα = tumor necrosis factor alpha; TRAF = tumor necrosis factor receptor-associated factor; TRAP = tartrate-resistant acid phosphatase; TREM = triggering receptor expressed on myeloid cells.\n\nCompeting interests\nThe authors declare that they have no competing interests.\n\nAuthors' contributions\nYK participated in the design of the study, carried out the experiments and statistical analysis, and drafted the manuscript. KH and KT participated in the design of the study and its coordination. TN and NM conceived of the study, participated in its design and coordination, and helped to draft the manuscript. All authors read and approved the final manuscript.\n\n\n" ], "offsets": [ [ 0, 39944 ] ] } ]	[ { "id": "pmcA1779441__T0", "type": "species", "text": [ "human" ], "offsets": [ [ 20, 25 ] ], "normalized": [ { "db_name": "ncbi", "db_id": "9606" } ] }, { "id": "pmcA1779441__T1", "type": "species", "text": [ "human" ], "offsets": [ [ 403, 408 ] ], "normalized": [ { "db_name": "ncbi", "db_id": "9606" } ] }, { "id": "pmcA1779441__T2", "type": "species", "text": [ "mouse" ], "offsets": [ [ 2499, 2504 ] ], "normalized": [ { "db_name": "ncbi", "db_id": "10090" } ] }, { "id": "pmcA1779441__T3", "type": "species", "text": [ "human" ], "offsets": [ [ 2915, 2920 ] ], "normalized": [ { "db_name": "ncbi", "db_id": "9606" } ] }, { "id": "pmcA1779441__T4", "type": "species", "text": [ "patients" ], "offsets": [ [ 3034, 3042 ] ], "normalized": [ { "db_name": "ncbi", "db_id": "9606" } ] }, { "id": "pmcA1779441__T5", "type": "species", "text": [ "mice" ], "offsets": [ [ 3116, 3120 ] ], "normalized": [ { 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2	pmcA2556924	[ { "id": "pmcA2556924__text", "type": "Article", "text": [ "Are there sensitive subgroups for the effects of airborne particles?\nAbstract\nRecent studies have shown that particulate air pollution is a risk factor for hospitalization for heart and lung disease; however, little is known about what subpopulations are most sensitive to this pollutant. We analyzed Medicare hospital admissions for heart disease, chronic obstructive pulmonary disorders (COPD) and pneumonia in Chicago, Cook County, Illinois, between 1985 and 1994. We examined whether previous admissions or secondary diagnoses for selected conditions predisposed persons to having a greater risk from air pollution. We also considered effect modification by age, sex, and race. We found that the air-pollution-associated increase in hospital admissions for cardiovascular diseases was almost doubled in subjects with concurrent respiratory infections. The risk was also increased by a previous admission for conduction disorders. For COPD and pneumonia admissions, diagnosis of conduction disorders or dysrhythmias increased the risk of particulate matter < 10 microm in aerodynamic diameter (PM(10))-associated admissions. Persons with asthma had twice the risk of a PM(10)-associated pneumonia admission and persons with heart failure had twice the risk of PM(10)-induced COPD admissions. The PM(10) effect did not vary by sex, age, and race. These results suggest that patients with acute respiratory infections or defects in the electrical control of the heart are a risk group for particulate matter effects.\nArticles \n\n Are There Sensitive Subgroups for the Effects of Airborne Particles? Antonella Zanobetti,1 Joel Schwartz,1,2 and Diane Gold1,2 1Environmental \n\n Epidemiology Program, Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA; 2Channing Laboratory, Department of Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston, Massachusetts, USA \n\n Recent studies have shown that particulate air pollution is a risk factor for hospitalization for heart and lung disease; however, little is known about what subpopulations are most sensitive to this pollutant. We analyzed Medicare hospital admissions for heart disease, chronic obstructive pulmonary disorders (COPD) and pneumonia in Chicago, Cook County, Illinois, between 1985 and 1994. We examined whether previous admissions or secondary diagnoses for selected conditions predisposed persons to having a greater risk from air pollution. We also considered effect modification by age, sex, and race. We found that the air-pollution-associated increase in hospital admissions for cardiovascular diseases was almost doubled in subjects with concurrent respiratory infections. The risk was also increased by a previous admission for conduction disorders. For COPD and pneumonia admissions, diagnosis of conduction disorders or dysrhythmias increased the risk of particulate matter < 10 �m in aerodynamic diameter (PM10)-associated admissions. Persons with asthma had twice the risk of a PM10-associated pneumonia admission and persons with heart failure had twice the risk of PM10-induced COPD admissions. The PM10 effect did not vary by sex, age, and race. These results suggest that patients with acute respiratory infections or defects in the electrical control of the heart are a risk group for particulate matter effects. Key words: effect modification, hospital admissions, particulate air pollution. Environ Health Perspect 108:841�845 (2000). [Online 28 July 2000] http://ehpnet1.niehs.nih.gov/docs/2000/108p841-845zanobetti/abstract.html \n\n Particulate air pollution has been associated with increases in daily deaths and hospital admissions in studies all over the world (1�15). These associations are now well documented but little is known, as yet, of the characteristics of persons that put them at increased risk of adverse events related to particulate air pollution. This has been identified as a key data gap (16). Schwartz and Dockery (17) reported that persons older than 65 years of age had a somewhat increased risk of death, and this has been confirmed in other studies (18). A more detailed examination of particulate matter-related risk by deciles of age (19) showed the risk beginning to increase at approximately 40 years of age and reaching its maximum for those 75 years of age and older. In addition to age, several studies suggest that persons with respiratory illness are at increased risk for cardiovascular effects associated with air pollution. An examination of death certificates on high- and low-air pollution days reported a substantial difference in the proportion of deaths from cardiovascular causes that had respiratory disease as a contributing cause of death (19). A recent follow-up study of a cohort of persons with chronic obstructive pulmonary disease (COPD) in Barcelona, Spain, found an association between particulate air pollution and all-cause mortality in the cohort (20). The magnitude of the risk per microgram per cubic meter of exposure was substantially greater than that for the general population. Environmental Health Perspectives \n\n Controlled exposure of animals with chronic bronchitis and control animals to concentrated air particles also demonstrated a potentiating effect of chronic lung disease in the response to airborne particles (21). This has led to the hypothesis that the cardiovascular effects of air pollution are predominantly in persons with chronic lung disease. There has been even less done to examine potential modifiers of the effects of airborne particles on hospital admissions. The existing literature on comorbidity shows that comorbidity per se seems to increase the risk of adverse outcomes (22�30). Little is known about the role of these comorbidities as effect modifiers for the effects of air pollution. This study uses data from the Medicare system to examine potential short-term and long-term medical conditions that may increase a person's risk of hospital admissions associated with particulate air pollution. In addition, we examine potential effect modification by age, race, and sex. \n\n Materials and Methods Health data. The Health Care Financing Administration (Baltimore, MD) maintains records of every hospital admission for Medicare participants in the United States. Persons in this database have a unique identifier. Using this identifier, we traced every hospital admission for heart and lung disease for each person in Cook County, Illinois, between 1985 and 1994. We chose Cook County because it is the most populous \n\n county in the United States with daily monitoring for particulate matter with aerodynamic diameter < 10 �m (PM10). The data were then analyzed to look at effect modification by concurrent and preexisting conditions as well as by age, race, and sex. To establish a baseline risk, we computed daily counts of hospital admissions for cardiovascular disease (CVD) [International Classification of Disease, 9th edition, World Health Organization, Geneva (ICD-9) code 390�429], pneumonia (ICD-9 code 480�487), and COPD (ICD-9 code 490�496, excluding 493). The association between these daily counts and PM10 was examined for the years 1988�1994, when daily PM10 monitoring data were available in Chicago. Once our baseline risks were established, we examined three classes of potential effect modifiers. First, we looked at whether previous admissions for selected conditions predisposed persons to having a greater risk from air pollution. For each of the three admission categories (CVD, pneumonia, and COPD), we considered 10 causes (defined by a previous admission) as effect modifiers: COPD (ICD-9 code 490�496 except 493), asthma (ICD-9 code 493), acute bronchitis (ICD-9 code 466), acute respiratory illness (ICD-9 code 460�466), pneumonia (ICD-9 code 480�487), CVD (ICD-9 code 390�429), myocardial infarction (ICD-9 code 410), congestive heart failure (ICD-9 code 428), conduction disorders (ICD-9 code 426), and dysrhythmias (ICD9 code 427). To test the hypothesis that persons with these conditions had higher risks of subsequent PM10-related admissions, we computed separate daily counts of admissions for our three target causes, stratified by whether or not the person admitted had been previously admitted for the hypothesized predisposing condition. Separate analyses were then performed within each strata to see if the effects of PM10 differed by strata. Address correspondence to A. Zanobetti, Department of Environmental Health, Environmental Epidemiology Program, Harvard School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA. Telephone: (617) 4324642. Fax: (617) 277-2382. E-mail: azanob@ sparc6a.harvard.edu Supported by NIEHS grant ES07937. Received 18 January 2000; accepted 18 April 2000. \n\n � VOLUME 108 \| NUMBER 9 \| September 2000 \n\n 841 \n\n \fArticles \n\n � \n\n Zanobetti et al. \n\n The second set of potential predisposing conditions included secondary diagnoses associated with the index admission. These could represent the presence of a chronic condition (e.g., COPD) that has not resulted in a previous hospital admission. They could also represent acute conditions that may have increased the subjects' sensitivity to air pollution. For example, if respiratory infections modified the effect of particulate matter on the cardiovascular health of persons with underlying heart disease, then the risk of a hospital admission for heart disease might be different in persons with infections. If this were true, then the risk ratio of a 10-�g/m3 increase of PM10 on cardiovascular admissions of persons with a concurrent respiratory infection would be different from the ratio in persons without respiratory infection. To test these hypotheses, we computed separate daily counts of admissions for events with and without the concurrent conditions hypothesized to increase sensitivity to air pollution. These were taken as the same 10 conditions in the first analysis with certain exclusions for pairing that would be illogical. That is, the concurrent diagnosis of a specific cardiac condition was not treated as an effect modifier for admissions for any cardiovascular condition. Likewise, pneumonia and COPD were not possible concurrent conditions for each other. The third set of predisposing conditions considered was being older than 75 years of age, nonwhite, and female. These were examined for all three outcomes. We obtained weather data for O'Hare Airport from the EarthInfo CD-ROM (EarthInfo CD NCDC Surface Airways, EarthInfo Inc., Boulder, CO), and we obtained air pollution data from the U.S. Environmental Protection Agency Aerometric Information Retrieval System network (31). \n\n running-line smoother, loess (35), was chosen to estimate the smooth function. To control for weather variables and day of the week, we chose the smoothing parameter that minimized the Akaike's information criterion (36). To model seasonality we chose the smoothing parameter that minimized the sum of the autocorrelation of the residuals while removing seasonal patterns. Two autoregressive terms (37) were added in the model to eliminate the remaining serial correlation from the residuals. We used the mean of PM10 on the day of the admission and the day before the admission as our exposure variable. This gives results that are similar to those obtained fitting a full distributed lag model (38). PM10 was treated linearly. Our baseline models used the daily counts of CVD, pneumonia, and COPD admissions as outcomes. We then subdivided those counts by the presence or absence of the potential effect modifier and reestimated our regressions on those subgroups. We considered effect modification to be indicated when the estimates of PM10 in the group with the condition was outside of the 95% confidence interval (CI) of the effect estimate in persons without the condition. \n\n Results Table 1 shows the mean daily admissions for COPD, cardiovascular, and pneumonia both overall and in the presence of the potential effect modifiers. For some effect modifiers such as conduction disorders or myocardial infarctions, the counts in conjunction with our respiratory outcomes are \n\n low, which limits power. In general, the numbers are lower for examining effect modification by previous admissions than for effect modification by concurrent diagnosis. This is as expected because many clinically relevant comorbidities may never have resulted in a hospital admission. Table 2 shows the 25th, 50th, and 75th percentile values for the environmental variables. The mean value for PM10 is 33 �g/m3. The daily values for PM10 were computed as the average of 10 monitors, two of which measured PM10 almost every day and the others less frequently (38). Table 3 shows the mean daily counts of CVD, COPD, and pneumonia by sex, age groups, and race. The distribution by sex is almost even, although the counts of admissions for males are generally lower (approximately 10%) than for females, particularly for cardiovascular diseases. The counts of CVD, COPD, and pneumonia admissions were similar for people 65�75 or 75 years of age and older. Tables 4�6 show the results for the effect PM10 overall and stratifying by concurrent diagnosis and previous admissions. These are expressed as the percentage increase for 10 �g/m3 PM10. Table 4 shows the results for CVD. A 10-�g/m3 increase in PM10 was associated with a 1.31% (5% CI, 0.97%; 95% CI, 1.66%) increase in hospital admissions for heart disease in all elderly persons. A concurrent (not previous) diagnosis of COPD modified the risk of PM10-associated admissions for heart disease. However, significant associations were still seen between PM10 \n\n Table 1. Mean daily counts of admissions, Chicago 1986�1994, for COPD, CVD, and pneumonia overall and by concurrent diagnosis and by previous admissions. By concurrent diagnosis COPD CVD Pneumonia Overall Respiratory disease Acute bronchitis Acute respiratory infections Pneumonia Asthma COPD Cardiovascular disease CVD Conduction disorders Cardiac dysrhythmias Congestive heart failure Myocardial infarction NA, not applicable. \n\n By previous admissions COPD CVD Pneumonia 7.8 0.8 0.9 1.6 0.9 2.7 2.1 0.0 0.4 0.9 0.3 102.1 1.6 1.8 7.3 1.5 2.0 54.7 1.0 9.9 24.2 11.4 26.5 0.9 1.0 6.4 0.7 1.4 7.2 0.2 1.5 3.1 1.0 \n\n Methods We analyzed the data with a generalized additive robust Poisson regression model (32). This approach has become the norm in such studies (14,33,34). In the generalized additive model the outcome is assumed to depend on a sum of nonparametric smooth functions for each variable that models the potential nonlinear dependence of daily admission on weather and season. The model is of the form: log[E(Yt)] = 0+ S1 (X1 )+... + Sp (Xp) where E(Yt) is the expected value of the daily count of admissions Yt and Si are the smooth functions of the covariates Xi. We examined temperature, previous day's temperature, relative humidity, barometric pressure, and day of week covariates. The locally weighted \n\n 7.8 0.1 0.3 0.4 0.1 NA 4.7 0.2 1.4 1.8 0.1 \n\n 102.1 0.9 1.3 4.0 1.8 13.4 NA NA NA NA NA \n\n 26.5 0.3 0.3 NA 0.9 6.9 14.7 0.6 4.6 7.3 0.4 \n\n Table 2. 25th, 50th, and 75th percentile values for the environmental variables in Chicago, 1988�1994. Temperature (�F) 35 51 67 Relative humidity 62 70 79 Barometric pressure 29.2 29.3 29.4 PM10 (�g/m3) 23 33 46 \n\n Table 3. Mean daily counts of admissions by sex, race, and age groups, Chicago, 1986�1994. Group Overall Female Nonwhite Age > 75 years COPD 7.8 4.2 1.6 3.7 CVD 102.1 59.4 21.0 55.1 Pneumonia 26.5 14.7 5.2 17.4 \n\n 842 \n\n VOLUME \n\n 108 \| NUMBER 9 \| September 2000 � Environmental Health Perspectives \n\n \fArticles \n\n � \n\n Effects of particles on sensitive subgroups \n\n and heart disease admissions in persons without COPD listed as either a comorbidity or a cause of previous admission (Table 4). A significant association was also seen in persons without any respiratory disease as a concurrent diagnosis, although the risk is much lower than in persons with respiratory disease. However, the risk associated with PM10 was roughly doubled in subjects with concurrent respiratory infections and the risk estimates in those subjects were outside the 95% CI of the risk in patients without concurrent respiratory infections. A previous admission for conduction disorders (e.g., heart block) increased the risk of a PM10-related subsequent admission for any heart condition, and a weaker indication of effect modification was seen for persons with previous admission for dysrhythmias. In contrast heart failure and previous myocardial infarctions were highly insignificant as effect modifiers. Table 5 shows the results for COPD. Overall, there is a 1.89% (95% CI, 0.8�3.0) increase in COPD admissions for a 10�g/m3 increase in PM10. The results of the stratified analysis suggest that preexisting heart disease modifies Table 4. Percentage increase in hospital admissions for CVD in all persons and by concurrent diagnosis and previous admissions. PM10 2.5% CI 97.5% CI All persons 1.31 By concurrent diagnosis Respiratory disease All respiratory disease With 1.65 Without 0.98 Acute bronchitis With 2.50 Without 1.07 Acute respiratory infections With 2.71 Without 1.06 Pneumonia With 1.95 Without 1.03 COPD With 1.59 Without 1.08 By previous admissions Respiratory disease All respiratory disease With 1.18 Without 1.08 COPD With 1.48 Without 1.09 Asthma With 1.71 Without 1.08 Cardiovascular disease Conduction disorders With 2.89 Without 1.07 Cardiac dyshrethmias With 1.61 Without 1.04 0.97 1.66 \n\n the risk of COPD admissions on high particle days. Previous admissions for any cardiovascular disease increased the risk of a PM10associated COPD admission approximately 2.5-fold. A previous heart failure admission caused an even more striking increase in the PM10 effect. Previous admissions for dysrhythmias and conduction defects were rare (Table 1) with no power to examine effect modifications. Listings as concurrent diagnoses were more common and here they joined heart failure in increasing the risk of PM 10 -associated COPD admissions. For COPD there was also some indication that concurrent pneumonia or an acute respiratory infection admission in the last year increased risk. The low numbers made these estimates less precise, however. The percentage increase in pneumonia admission (Table 6) for 10 �g/m3 PM10 is higher than for COPD or CVD with an increase of 2.34% (95% CI, 1.66�3.0). As with COPD, persons with heart disease appeared at higher risk of pneumonia hospital admissions associated with particulate air pollution. Here diagnoses suggestive of impaired autonomic control of the heart, such as conduction disorders or dysrhythmias, were associated with increased risk for PM 10 effects on pneumonia admissions. Unlike COPD, no difference was seen for congestive heart failure. Persons with asthma Table 5. Percentage increase in hospital admissions for COPD in all persons and by concurrent diagnosis and previous admissions. PM10 2.5% CI 97.5% CI All persons 1.89 By concurrent diagnosis Respiratory disease Pneumonia With 4.00 Without 1.51 Cardiovascular disease Conduction disorders With 2.34 Without 1.60 Cardiac dysrhythmias With 3.09 Without 1.43 Congestive heart failure With 2.90 Without 1.39 By previous admissions Respiratory disease Acute respiratory infections With 3.20 Without 1.70 Cardiovascular disease CVD With 2.90 Without 1.18 Congestive heart failure With 4.37 Without 1.14 Within 1 year 6.04 0.80 2.99 \n\n had twice the risk of a PM10-induced pneumonia admission as persons without asthma. Table 7 shows the results by sex, age, and race. None of the effect size estimates for any of the stratification variables were outside of the 95% CI for the opposite strata. There was a tendency for the effect of PM10 on CVD admissions to be higher for females, whereas the effect on pneumonia admissions was higher for males. In general, we found somewhat larger effects on whites compared to nonwhites, and for persons older than 75 years of age compared to younger persons. \n\n Discussion In this analysis we examined whether the effect of PM10 on the risk of hospital admission for heart and lung disease was different depending on the presence of comorbidities. We found that PM10 was associated with hospital admissions for all three causes (CVD, COPD, and pneumonia) and we found not a general increase in PM10 related risk with comorbidities, but a specific pattern that is suggestive of potential mechanisms and consistent with other recent epidemiologic and toxicologic findings. One major finding of this study is that preexisting cardiovascular disease, particularly impaired autonomic control (conduction defects and dysrhythmias) and heart failure, substantially increased the risk of respiratory admissions associated with airborne particles. In fact, recent human studies have shown that exposure to particulate air pollution is a risk factor for reduced heart rate variability (39�41). Reduced heart rate variability is an adverse response and a risk factor for arrhythmia. A new study of defibrillator discharges in patients with implanted cardioverter defibrillators found that discharges were associated with air pollution (42). Exposure to combustion Table 6. Percentage increase in hospital admissions for pneumonia in all persons and by concurrent diagnosis and previous admissions. PM10 All persons By concurrent diagnosis Respiratory disease Asthma With Without Cardiovascular disease Conduction disorders With Without Cardiac dysrhythmias With Without By previous admissions Cardiovascular disease Cardiac dysrhythmias With Without 2.34 2.5% CI 97.5% CI 1.66 3.02 \n\n 1.10 0.64 �0.47 0.76 0.18 0.76 0.55 0.72 0.85 0.75 \n\n 2.20 1.33 5.55 1.37 5.30 1.37 3.36 1.35 2.34 1.41 \n\n �0.45 0.47 �4.42 0.58 0.64 0.33 0.77 0.24 \n\n 8.65 2.57 9.59 2.64 5.60 2.55 5.08 2.55 \n\n 0.45 0.76 �0.40 0.78 �0.43 0.77 0.22 0.76 0.75 0.72 \n\n 1.91 1.41 3.40 1.40 3.89 1.39 5.63 1.38 2.48 1.36 \n\n 4.18 2.07 7.92 1.99 � � \n\n 1.01 1.46 4.28 1.37 � � \n\n 7.46 2.69 11.69 2.61 � � \n\n �1.38 0.66 0.99 �0.01 1.43 0.05 2.10 \n\n 8.01 2.76 4.85 2.39 7.40 2.24 10.14 \n\n 3.47 2.08 \n\n 1.21 1.45 \n\n 5.79 2.71 \n\n Increases are for a 10-�g/m3 increase in PM10. \n\n Increases are for a 10-�g/m3 increase in PM10. \n\n Increases are for a 10-�g/m3 increase in PM10. \n\n Environmental Health Perspectives \n\n � VOLUME 108 \| NUMBER 9 \| September 2000 \n\n 843 \n\n \fArticles \n\n � \n\n Zanobetti et al. \n\n Table 7. Effect modification by sex, race, and age groups for 10 �g/m3 PM10. % All persons Male Female White Non-white Age > 75 Age 75 1.89 1.34 2.19 1.65 1.07 2.20 1.33 COPD (95% CI) (0.80, 2.99) (�0.14, 2.84) (0.81, 3.59) (0.51, 2.81) (�1.11, 3.3) (0.72, 3.69) (0.03, 2.65) % 1.31 1.07 1.21 1.20 0.70 1.28 0.93 CVD (95% CI) (0.97, 1.66) (0.62, 1.51) (0.83, 1.6) (0.86, 1.55) (0.1, 1.3) (0.88, 1.69) (0.51, 1.35) % 2.34 2.65 1.91 2.45 1.91 2.12 2.52 Pneumonia (95% CI) (1.66, 3.02) (1.81, 3.5) (1.11, 2.72) (1.77, 3.14) (0.69, 3.14) (1.38, 2.86) (1.57, 3.48) \n\n Figures shown are the percentage increase in admissions (95% CI). \n\n particles has also been associated with arrhythmia in an animal model (43) and changes in ST segments have been noted as well (44). This is the first study to suggest persons with defects in the electrical control of the heart are also at higher risk of respiratory illness after exposure to airborne particles. These data also suggest that persons admitted to hospitals for pneumonia during an air pollution episode may be at high risk for clinically significant conduction disorders during that hospital admission. Patients with congestive heart failure were at greater risk of hospital admissions for COPD in association with airborne particles. Heart failure and COPD is not an uncommon combination. The finding that these patients are at higher risk for admissions associated with particulate air pollution is new but is also consistent with several other recent reports. The spontaneous hypertensive rat develops a model of heart failure, and recent studies have reported greater sensitivity to particulate air pollution in these rats. These include both electrocardiogram abnormalities (44) and pulmonary toxicity (45,46). Similarly, in an epidemiologic study, Hoek et al. (47), found a higher relative risk of death with an increase in PM10 for congestive heart failure deaths than other deaths. The potential role of COPD in those heart failure deaths was not examined. Another consistent pattern in our data is of acute respiratory infections increasing susceptibility to airborne particles. Acute bronchitis, or more generally acute upper respiratory illnesses, as well as pneumonia, increased susceptibility to particle-associated admissions for CVD and COPD. The notion that air pollution exacerbates acute respiratory infections is well supported by studies which report associations between airborne particles and hospital admissions for respiratory infections (48,49). Zelikoff et al. (50) exposed rats infected with streptococcus to concentrated air particles and reported a significant increase in bacterial burdens and in the extent of pneumonia compared to animals exposed to filtrated air. This suggests an impaired immune response. Similarly, exposure to combustion \n\n particles enhances influenza infections in mice (51). An impaired defense to respiratory infection is a major reason that persons with COPD require hospital admission. If airborne particles result in further impairment the effect modification we observe makes good sense. The effect modification for heart disease admissions is more relevant. This modification is consistent with the earlier report of Schwartz (19), who found greater reports of respiratory complications on death certificates with an underlying cause of heart disease if the death occurred on a day with high levels of airborne particles. Although airborne particle exposure has been associated with increased exacerbation of asthma (2,12,48,52�59), this paper is the first to suggest that asthmatics are more susceptible to PM10-induced pneumonia exacerbation or to cardiovascular effects. The effects on pneumonia admissions are plausible, given the impaired ability to fight off infections in asthmatics with mucus plugs and the evidence the airborne particles impair the lungs' ability to fight off bacterial and viral infections, as noted earlier. The increased cardiovascular sensitivity, albeit weaker, is interesting. If airborne particles affect the cardiovascular system via the role of the lung in autonomic control, it is possible that asthmatics would be more sensitive to those effects. Animal models of asthma showed that combustion particles enhance the asthmatic response to aeroallergen challenges (59). This suggests an enhancement of pulmonary response in asthmatics. On the other hand, the diagnosis of asthma is problematic in the elderly, and crossover with COPD is possible. The possibility that this explains our results is reduced by our failure to find previous hospital admission for COPD was an effect modifier for the effect of particles on cardiovascular admissions. We must acknowledge several potential limitations of this study. First, we considered only previous admissions that occurred within Cook County. Hence persons with previous admissions elsewhere would be misclassified to our reference group. The effect of this would be to reduce the difference in PM 10 effect between the two groups. VOLUME \n\n Nevertheless, we identified some interesting interactions. We cannot exclude the possibility that there are areas we missed for this reason. We also examined interactions in a log relative risk model, which is inherently multiplicative. Although we believe this is justified because doubling the population exposed would be expected to double the pollution associated admissions, it results in a more conservative definition of interaction than would an additive risk model. Finally, our exposure is clearly measured with error. Most of this error is Berkson error (60) and hence will introduce no bias, and Zeger et al. (60) showed that the remaining error would have to have pathologic correlations with other variables to result in an upward bias. Another important result from this study, of course, is an estimate of the magnitude of the effect of airborne particles on public health. The PM10 concentrations in Chicago during this period were associated with approximately 1,600 additional admissions per year for heart disease, 740 additional admissions per year for pneumonia, and 170 additional admissions per year for COPD. These are not trivial increases in serious morbidity. 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3	pmcA1474674	[ { "id": "pmcA1474674__text", "type": "Article", "text": [ "Physiological and chemical characterization of cyanobacterial metallothioneins.\nAbstract\nTechniques have been developed for detection, quantitation, and isolation of bacterial metallothioneins (MTs) from cyanobacterial species. These methods involve differential pulse polarography and reverse-phase high-performance liquid chromatography (HPLC) and have allowed detection of picomole quantities of these high sulfhydryl content proteins. The prokaryotic molecule was found to be induced in the presence of Cd or Zn salts with regulation at the level of transcription. Cu was not found to induce synthesis of the prokaryotic MT. Exposure to the former metals resulted in a growth lag followed by simultaneous induction of MT synthesis and onset of growth. Amino acid analysis and N-terminal sequence analysis indicated that the bacterial MTs from cyanobacteria are unique, having many aromatic and aliphatic residues and no apparent association of hydroxylated or basic amino acids with cysteines. Although the characteristic Cys-X-Cys sequences were present, no apparent amino acid sequence homology with the eukaryotic MTs was found in the first 42 residues.\n\n\n\n\n Environmental Health Perspectives Vol. 65, pp. 71-75, 1986 \n\n Physiological and Chemical \n\n Characterization of Cyanobacterial Metallothioneins \n\n by Robert W. Olafson* \n\n Techniques have been developed for detection, quantitation, and isolation of bacterial metallothioneins (MTs) from cyanobacterial species. These methods involve differential pulse polarography and reverse-phase high-performance liquid chromatography (HPLC) and have allowed detection of picomole quantities of these high sulfhydryl content proteins. The prokaryotic molecule was found to be induced in the presence of Cd or Zn salts with regulation at the level of transcription. Cu was not found to induce synthesis of the prokaryotic MT. Exposure to the former metals resulted in a growth lag followed by simultaneous induction of MT synthesis and onset of growth. Amino acid analysis and N-terminal sequence analysis indicated that the bacterial MTs from cyanobacteria are unique, having many aromatic and aliphatic residues and no apparent association of hydroxylated or basic amino acids with cysteines. Although the characteristic CysX-Cys sequences were present, no apparent amino acid sequence homology with the eukaryotic MTs was found in the first 42 residues. \n\n Introduction \n\n Metallothioneins have now been isolated and characterized from a large variety of eukaryotic organisms (1) and shown to be involved in heavy metal detoxification and/or homeostasis (2-4). These proteins are highly homologous with respect to amino acid sequence and complex metals in characteristic metal-thiolate cluster arrangements, the structures of which have been recently \n\n investigated by 113Cd-NMR (6). \n\n Although metallothionein (MT) is found throughout the eukaryotic world, few reports of the presence of this type of high sulfhydryl content metal-binding protein exist for prokaryotes. We earlier reported the presence of a prokaryotic MT in cyanobacteria (7,8) and have recently provided primary sequence evidence substantiating these data. This manuscript is intended to summarize the present state of knowledge regarding the physiological and chemical characterization of these bacterial MTs, with an emphasis on the techniques employed in such studies. \n\n Analytical Procedure \n\n In order to facilitate rapid detection, isolation, and quantitation of MT from various sources, we have routinely employed a differential pulse polarographic tech\n\n Department of Biochemistry and Microbiology, University of Victoria, Victoria, British Columbia V8W 2Y2, Canada. \n\n nique first described by Brdicka (9-11). This procedure avoids use of radioisotopes and circumvents problems such as species specificity and metal stoichiometric assumptions associated with radioimmunoassays and metal binding assays. Figure 1 shows a typical polarographic wave for MT using the Brdicka procedure. Measurement of the wave height can be performed from either the \n\n 0.20\n\n glJ MT-1 \n\n O 0.15\n\n E \n\n 0 0.10 0 \n\n E 0.05 _ _ \n\n -1.35 -1.45 -1.55 -1.65 \n\n V vs Agt/AgC1 \n\n FIGURE 1. Differential pulse polarographic wave for murine MT-1. \n\n Wave heights were calculated from the broken tangent line between minima rather than the supporting electrolyte baseline at the bottom of the figure. \n\n R. W OLAFSON \n\n supporting electrolyte baseline or a tangent to the minima as shown in the preceding figure. In the cobalt hexaminechloride supporting electrolyte, the half-wave potential for all MTs studied to date is approximately -1.45 V versus a Ag/AgCl reference electrode. This electrochemical reaction results in highly reproducible and linear current responses which can be used with samples containing picomole levels of MT (Fig. 2). Since this is an exceedingly sensitive instrument, attention to detail is particularly important for successful use of the Brdicka procedure (11). Routine use of a reference standard MT is highly recommended to compensate for small day-today variations in response. For absolute values, standards must be identical to the species of protein quantitated; otherwise commercially available standard is adequate. Although certain tissues and cellular types can be shown to have no other polarographically active material other than MT, with samples from new species, it is necessary to evaluate this potential problem by gelperneation chromatography and, if necessary, take steps to remove contaminants before assaying. In most cases, \n\n 0 \n\n E i \n\n m 0 \n\n 0 E \n\n 0.31 \n\n 0.11 \n\n O 0.1 0.3 0.5 \n\n MT (nanomoles) \n\n FIGURE 2. Standard curve for polarographic determination of me\n\n tallothionein. \n\n FIGURE 3. Cyclic voltamogram obtained by equilibration at -1.0 V \n\n for 4 min followed by cyclic scanning to OV and -1.4 V at a scan rate of 200 mV/sec with a PAR Model 303 static mercury drop electrode in the hanging drop mode. The mercury drop electrode was set in the large drop position producing a drop of 0.0226 cm3. The supporting electrolyte was 20 mM HEPES buffer, pH 7.3. The dotted line is the equilibrium trace. Adapted Olafson and Sim (10). \n\n this is easily managed by heat denaturation, if care is taken to assess the degree of MT losses due to coprecipitation. Such losses later can usually be minimized to less than 10% by adjustment of the tissue homogenate density prior to denaturation. \n\n It should be indicated that additional utility can be found with a polarographic analyzer beyond application of the Brdicka procedure. For example, metal levels can be readily determined by using differential pulse or anodic stripping voltametry procedures (10), while Figure 3 shows a cyclic voltamogram of bacterial MT. The latter technique is potentially useful in assessing metal speciation and integrity of the protein tertiary structure near metal clusters, particularly after metal reconstitution studies. \n\n E \n\n 'C2A- E 24 \n\n 0 30 40 E0 \n\n ~~~~~~~~~~~~ \n\n o C~~~~~~~~~~~~~~~~~~~~C \n\n Fraction Number (18ml) \n\n FIGURE 4. Sephadex G-75 chromatography profile of bacterial cell \n\n lysate applied to a 5 x 100 cm column and eluted with 10 mM anunoium bicarbonate, 5 mM mercaptoethanol (7). \n\n Elution Time (min) \n\n FIGURE 5. Reverse-phase high-performance chromatography profile \n\n of Sephadex G-75 fractionated bacterial MT. The 300 A pore size propyl column was eluted with 20 mM triethylamine phosphate, pH 7.0, by using an acetonitrile organic modifier (phase B). Column effluent was monitored at 250 nm with a sensitivity of 1.0 AUFS (12). \n\n 72 \n\n CYANOBACTERIAL METALLOTHIONEINS \n\n Isolation of Cyanobacterial MT \n\n Synechococcus strain Tx-20 cyanobacteria were maintained in axenic culture on BG-11 medium (7) and harvested from aerated 20 L cultures grown at 280C under fluorescent light. Cells were broken in a French pressure cell at 0?C in 0.5 M Tris-HCI, pH 8.6, and the lysate exposed to 10 ,uCi of 109CdCl. The 40,000g supernatant was applied to a Sephadex G-75 column developed with 10 mM ammonium bicarbonate and 5 mM mercaptoethanol resulting in the profile shown in Figure 4. Polarographic activity and radionuclide binding were coincident with a 10,000 MW ultraviolet absorbing fraction. Further purification of this material could be undertaken by DEAE-cellulose chromatography or isoelectric focusing but maximum resolution of isoproteins was best attained by reverse-phase high-performance liquid chromatogra\n\n 0 5 \n\n DAYS \n\n I0 \n\n 5 \n\n phy. Figure 5 shows such a separation performed on a 300 A pore size C-3 column (Beckman Instruments). Four baseline resolved MT peaks appear between 40 and 70 min. Peaks eluting at 80 min contain at least four additional MT components resolvable by adjustment of the applied organic modifier ramp. Preliminary evidence indicates that these isoproteins are microheterogeneous with respect to both amino acid composition and metal speciation resulting in the observed reverse-phase separation. \n\n Physiological Characteristics of Cyanobacterial MT \n\n Using the Brdicka polarographic procedure, it is possible to measure basal MT levels in Synechococcus strain \n\n 5 \n\n DAYS \n\n 10 \n\n 15 \n\n FIGURE 6. Cell numbers and MT concentrations as a function of time after inoculation of wild-type cyanobacteria in the presence and absence \n\n of (A) 22.5 ,uM CdCl2; (B) control; (C) 50 ,uM ZnSO4; (D) 50 ,uM CuCl2 (8). \n\n 73 \n\n 74 ~~~~~~~~~~R. W OLAFSON \n\n Table 1. Amino acid compositions of cyanobacterial \n\n metallothioneins compared with eukaryotic metallothioneins. \n\n Nearest integer residues per molecule Human (MT-2) Crab (MT-2) Tx-20t CysA 20 18 9.5 Asx 4 6 5.7 Thr 2 3 4.8 Ser 8 5 3.8 Glx 2 5 2.0 Gly 5 3 8.0 Ala 7 1 4.0 Val 1 - 2.3 Met 1 - \n\n Ile 1 -1.1 \n\n Leu Tyr Phe His Lys Arg Pro \n\n 8 2 \n\n 8 2 6 \n\n 2.9 2.3 \n\n 2.8 2.6 1.0 1.9 \n\n RRIMP NI cells cultured in the absence of added metal, as shown in Figure 6B (8). Comparison with cultures exposed to cadmium chloride (Fig. 6A) or zinc sulfate (Fig. 6C) showed that introduction of metal salts resulted in a growth lag and that resumption of growth occurred coincident with an increase in cellular levels of MT. In addition, it should be noted that, like mammalian MT, cadmium appears to be a more potent inducer than zinc. Twice as much cadmium-thionein was synthesized on exposure to half as much metal as was used in the zinc induction experiment. A further interesting finding was that copper exposure resulted in an even greater growth lag than observed with cadmium, but on resumption of growth in the presence copper, MT synthesis was not noted (Fig. 6D). Recent results suggest that this copper resistance is manifest via a membrane exclusion mechanism (unpublished results). \n\n HOURS \n\n FIGURE 7. Inhibition of cadmium induced synthesis by actinomycin \n\n D (hatched bar) and chloramphenicol (solid bar). Control cells are shown by unmarked bars. \n\n In order that the level of regulation of metal induction be determined for cyanobacteria, logarithmically growing cultures were exposed to cadmium and MT concentrations measured at several time intervals thereafter. Two cultures were exposed to either chloramphenicol or actinomycin D 30 min prior to introduction of metal, while a third culture was used as a control. The results of this experiment are shown in Figure 7 and indicate induction at the level of transcription, as was found in eukaryotic organisms. \n\n The assumption at this stage in these investigations was that the growth lag observed in cultures exposed to \n\n Table 2. Amino acid sequence analysis. \n\n Amino acid \n\n 1 10 20 30 Cyanobacteria T S T T L V K C A C E P C L C N V D P S K A I D R N G L Y Y Scylla P DP C C NDK C DC K EG EC KT GC K CT S C Human Ac MD P NC S C AA G DS CT C AG S C KC KE C KC T S C \n\n Neurospora \n\n G D C G C S G A S S C N C G S G C S C S N \n\n C G S K \n\n Table 2. Continued. \n\n Amino acid \n\n 40 50 60 C C EAC A H GHT G G \n\n R CP PC EQ C S SGC K CA NK E DC RK TC SK PC SCC P K K SCC S CCP V GC A KCA Q BC I C K GA SDK C S CC A \n\n 74 \n\n I \n\n II \n\n I I \n\n CYANOBACTERIAL METALLOTHIONEINS 75 \n\n cadmium or zinc was due to a rather protracted time of MT induction, perhaps associated with toxic burden. If the above cadmium-resistant cells were transferred into fresh media in the absence of cadmium and allowed to grow up between three successive transfers, levels of MT dropped to near basal values as synthesis was repressed in the absence of metal. However, when these cells were now transferred into cadmium-containing media, instead of the predicted growth lag, they grew immediately. Thus, these cells were truly cadmium resistant. Since 50 tubes of wild-type cells at a dilution of 104 grew, after the usual lag on exposure to cadmium-containing media, the acquisition of cadmium resistance in this strain of Synechococcus was therefore considered unlikely to be related to a chromosomal mutational event. Such a mutation frequency would be unreasonably high. Although no direct evidence exists at this time, this metal resistance phenomenon is best explained by the amplification of an extrachromosomal gene, especially since this strain is known to have plasmids. \n\n Structure of Cyanobacterial MT \n\n The structural determination of cyanobacterial MT is not yet complete, although a substantial amount of information is now known. For example, Table 1 compares the amino acid composition of a Synechococcus TX-20 isoprotein with two eukaryotic MTs. These data indicate that the bacterial form is unique. While cysteine was still the predominant amino acid in this protein, levels of the amino acid were half that seen in the eukaryotes. In addition, the bacterial protein had two tyrosines, three histidines, and five long-chain aliphatics-all residues rarely found in eukaryotic MTs. Thus, the amino acid composition indicates that prokaryotic MTs are not as structurally homologous with eukaryotes as they are physiologically homologous. This was further exemplified on amino terminal amino acid sequence analysis (12). With the exception of the typical Cys-X-Cys sequences, the first 42 residues of the prokaryotic MT were essentially without homology on comparison with the crab (Scylla), human, or Neurospora crassa MTs (Table 2). Of the above-mentioned uncommon MT residues, two tyrosines were found together in positions 29 and 30, all five of the long-chain aliphatic amino acids were located in the first 28 residues, and two histidines were situated at positions 37 and 39. Perhaps of greater interest was the complete lack of association of basic residues or hydroxylated residues with cysteines, as is found in eukaryotes (11). Instead, a block of four hydroxylated amino acids was found at the amino terminus. \n\n The sequence of this unique MT is now nearing completion, opening the way for an X-ray crystallographic investigation. However, the degree of similarity between the metal cluster arrangement of these bacterial molecules with the eukaryotic structures will initially be undertaken spectroscopically. Reliable interpretation of the 113Cd-NMR data for this molecule will be dependent upon adequate isolation of isoproteins using RP-HPLC and assessment of conformational integrity of metal reconstituted molecules, using procedures such as cyclic voltametry. Studies along these lines are presently underway in this laboratory \n\n The author gratefully acknowledges the financial support of the Australian Institute of Marine Science and the National Science and Engineering Research Council of Canada. Excellent technical assistance was provided by R. G. Sim and S. Kielland in carrying out the polarographic and sequence analyses, respectively. \n\n REFERENCES \n\n 1. Kagi, J. H. R., and Nordberg, M. (Eds.). Metallothionein. Birk\n\n hauser Verlag, Basel, 1979, pp. 5-55. \n\n 2. Olafson, R. W Differential pulse polarographic determination of \n\n murine metallothionein induction kinetics. J. Biol. Chem. 256:12631268 (1981). \n\n 3. Olafson, R. W Intestinal metallothionein: effect of parenteral and \n\n enteral zinc exposure on tissue levels of mice on controlled zinc diets. J. Nutr. 113: 268-275 (1983). \n\n 4. McCarter, J.A., and Roch, M. Chronic exposure of Coho salmon \n\n to sublethal concentrations of copper. III. Kinetics of metabolism of metallothionein. Comp. Biochem. Physiol. 77C: 83-87 (1984). \n\n 5. Lerch, K., Ammer, D., and Olafson, R. W Crab metallothionein\n\n primary structures of metallothioneins 1 and 2. J. Biol. Chem. 257: 2420-2426 (1982). \n\n 6. Otvos, J. D., Olafson, R.W, and Armitage, I. M. Structure of an \n\n invertebrate metallothionein from Scylla serrata. J. Biol. Chem. 257: 2427-2431 (1982). \n\n 7. Olafson, R. W, Abel, K., and Sim, R. G. Prokaryotic metallothi\n\n onein: preliminary characteristics of a blue-green alga heavy metalbinding protein. Biochem. Biophys. Res. Commun. 89: 36-40 (1979). 8. Olafson, R. W, Loya, S., and Sim, R. G. Physiological parameters \n\n of prokaryotic metallothionein induction. Biochem. Biophys. Res. Commun. 95: 1495-1503 (1980). \n\n 9. Brdicka, R. Pblarographic studies with the dropping mercury ka\n\n thode.-Part XXXI.-A new test for proteins in the presence of cobalt salts in ammoniacal solutions of ammonium chloride. Collect. Czech. Chem. Commun. 5: 112-128 (1933). \n\n 10. Olafson, R. W, and Sim, R. G. An electrochemical approach to \n\n quantitation and characterization of metallothionein. Anal. Biochem. 100: 343-351 (1979). \n\n 11. Olafson, R. W Differential pulse polarographic determination of \n\n murine metallothionein induction kinetics. J. Biol. Chem. 256: 12631268 (1981). \n\n 12. Olafson, R. W Prokaryotic metallothionein: amino terminal se\n\n quence analysis of a unique metallothionein. Int. J. Peptide Protein Res. 24: 303-308 (1984). 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pmcA1805739

[ { "id": "pmcA1805739__text", "type": "Article", "text": [ "Embryonic sympathoblasts transiently express TrkB in vivo and proliferate in response to brain-derived neurotrophic factor in vitro\nAbstract\nBackground\nNerve growth factor and neurotrophin-3 are involved in the development of sympathetic neurons; however, whether brain derived neurotrophic factor also plays a role is not known. The purpose of this study was to determine whether BDNF and its receptor, TrkB, are expressed during the development of paravertebral sympathetic ganglia in vivo and to determine the effect of BDNF in vitro.\n\nResults\nAs neural crest cells coalesce to form sympathetic ganglia, TrkB-positive cells are seen in both chicken and mouse embryos. In chicken embryos, TrkB-expressing cells first appear at Hamburger-Hamilton Stage (St) 27 and they co-express HNK-1, confirming that they are migrating neural crest cells. The TrkB-positive cells lack neural markers at this stage; however, they migrate with other neurally differentiating cells that are TrkA and TrkC-positive. By St. 29/30, TrkB-positive cells begin to express the neural specific markers Hu C/D and Islet-1; eventually, all TrkB positive cells commence neural differentiation. By St. 34, TrkB and TrkC staining are lost. BDNF transcript expression parallels that of TrkB. In the mouse, TrkB-positive cells surround newly formed sympathetic ganglia and a small number of TrkB positive cells that co-express tyrosine hydroxylase are seen within ganglia between E13.5-15. In cell culture, many cells from St. 29–30 chicken lumbar sympathetic ganglia express neural markers and are dividing, indicating that they are sympathoblasts. Sympathoblasts and neurons require both nerve growth factor and neurotrophin-3 for survival. BDNF increases the number of cells expressing neural markers in culture by increasing number of cells that incorporate bromodeoxyuridine. In contrast, most TrkB-positive sympathetic cells in vivo are not actively proliferating between E6–E8.\n\nConclusion\nDeveloping paravertebral sympathetic ganglia in avian and murine embryos contain a subpopulation of sympathoblasts that transiently express TrkB and ultimately commence neuronal differentiation. These TrkB expressing sympathoblasts are not actively dividing in vivo; yet, when placed in vitro, will divide in response to BDNF. This suggests that the availability of BDNF in vivo fails to reach a threshold necessary to induce proliferation. We suggest that excess TrkB stimulation of sympathoblasts in vivo may lead to the genesis of neuroblastoma.\n\n\n\nBackground\nNeural crest cells destined to become paravertebral sympathetic neurons proliferate and differentiate during migration and gangliogenesis. In chicken embryos, migrating neural crest cells express catecholamines at Hamburger/Hamilton Stage (St.) 19, and these cells form the primary sympathetic chain dorsolateral to the aorta at St. 22 (E3.5) [1]. Between St. 23 (E4) and St. 28 (E6), these cells disperse and undergo a secondary migration to form the paravertebral sympathetic chain that resides ventral to the spinal cord and dorsal root ganglion [1]. After ganglia coalesce, sympathoblasts express markers of neuronal differentiation, such as Q211 and tyrosine hydroxylase (TH), at a time when they also incorporate [3H]-thymidine [2]. Time lapse photography has shown that cultured E15.5–E16.5 sympathetic neurons from rat embryos extend axons while they divide [3-5]. Although proliferation appears to be an important process to expand the sympathetic neuron population during differentiation, the mechanisms that guide sympathoblast proliferation have not been identified.\nThe development of sympathetic neurons is guided by neurotrophins. Neurotrophin-3 (NT-3) binds to its receptor, TrkC, to promote the survival of cultured sympathoblasts from early lumbar paravertebral ganglia [6]. Nerve growth factor (NGF) signals through its receptor, TrkA, to promote the survival of sympathetic neurons upon target innervation [7]. There are severe sympathetic defects in the superior cervical ganglion of individual NT-3 and NGF knockout mice [8-10]. Furthermore, there is no additional cell death in the superior cervical ganglion of NT-3 and NGF double knockout mouse embryos, suggesting that all of the neurons are dependent on both neurotrophins for survival [11]. There is also an increase in sympathetic neuron cell death in TrkA knockout mice [12]. However, in TrkB and BDNF knockout mice, there is no apparent phenotype in the superior cervical ganglion, and there is little evidence that TrkB or BDNF is expressed in sympathetic ganglia. Thus, it is generally thought that TrkB and BDNF have little or no roles in guiding the development of sympathetic neurons.\nIn addition to their developmental functions, neurotrophin receptors regulate cell behavior in neuroblastoma, a tumor found in sympathetic ganglia and adrenal medulla. Tumors that express TrkA often spontaneously regress, while those that express TrkB and its ligand, brain-derived neurotrophic factor (BDNF), grow aggressively, are invasive, and fail to respond to chemotherapeutic agents [13]. The presence of TrkA in neuroblastoma tumors is consistent with its expression in developing sympathetic neurons, and suggests that regressive neuroblastoma tumors arise from early sympathetic neurons that express TrkA. The function of TrkB in early sympathetic development is unknown, which makes understanding the etiology of aggressive neuroblastoma tumors difficult. Based on its function in neuroblastoma tumors, we hypothesize that BDNF and TrkB expression in differentiating sympathoblasts is responsible for expanding the neuronal population through proliferation.\nWe sought to determine whether BDNF and TrkB are involved in sympathetic development. We report that during early embryonic development, TrkB is expressed in a subset of differentiating sympathoblasts in both avian and murine embryos. We also find that BDNF promotes the proliferation of TrkB-positive sympathoblasts in cell culture. However, the majority of TrkB positive cells in vivo fail to take up bromodeoxyuridine (BrdU) over a 24 hr period, suggesting that endogenous BDNF concentrations do not reach a threshold necessary to stimulate proliferation of sympathoblasts. Shortly after all of the TrkB positive cells commence neuronal differentiation, TrkB immunoreactivity is lost. These results suggest that prolonged expression and/or activation of TrkB signaling at these early stages may be an early event triggering the formation of neuroblastoma.\n\nResults\nTrkB is expressed during migration of neural crest cells to sympathetic ganglia\nWe first determined whether TrkB is expressed in neural crest-derived cells in the region ventral to the spinal cord and dorsal root ganglia where sympathetic ganglia coalesce between Hamburger/Hamilton Stages (St.) 25–28/29. To identify cells that have commenced neuronal differentiation, transverse sections of the lumbar spinal column region were stained with antibodies against Hu C/D [14], a neuronal-specific RNA-binding protein, or Islet-1, a transcription factor found in sympathetic neurons [15]. We found that Hu C/D and Islet-1 are expressed in the same cells both in vivo and in vitro throughout sympathetic development. In experiments done between St. 25 and 28, Islet-1 staining appeared weaker than Hu C/D staining, and thus we used Hu C/D to identify differentiating neurons at these stages. At later stages, Islet-1 was used to facilitate the identification of neurons because of the nuclear location of its immunoreactivity.\nCells expressing Hu C/D are first detected at St. 25 ventral to the spinal cord and dorsal root ganglion and lateral to the dorsal aorta (Figure 1A, 1B). By St. 26, the number of cells that express Hu C/D in this region increases dramatically (Figure 1C). TrkB-expressing cells first appear at St. 27 in the same region and are adjacent to Hu C/D-positive cells (Figure 1D, 2A, 2H). TrkB-positive cells co-localize with a neural crest marker, HNK-1 (Figures 2B, 2C, 2D). The Hu C/D-positive cells in this region are likely to be sympathetic neurons, since they appear in the region where sympathetic ganglia form and express tyrosine hydroxylase, a rate-limiting enzyme in the synthesis of catecholamines (Figures 2E, 2F, 2G). At St. 28/29, the cells begin to coalesce ventral to the dorsal root ganglion and the Hu C/D-positive cells and TrkB-positive cells remain as two separate cell populations (Figure 1E); however, shortly afterwards, all of the TrkB-positive cells begin to express Islet-1 (Figure 3B) and Hu C/D (data not shown).\n\nDevelopmental regulation of TrkA, TrkB, TrkC, and BDNF expression\nIn contrast to TrkB, the other neurotrophin receptors, TrkA and TrkC, are co-expressed in both Hu C/D-positive and Hu C/D-negative cells at St. 27 (Figures 2I, 2J). We find that approximately 30% of the Islet-1-positive cells express TrkA (Figure 3A), while 50% express TrkB (Figure 3B) and 100% express TrkC (Figure 3C) at St. 29/30 (E6.5). Thus, all developing neurons express TrkC in combination with either TrkA or TrkB. By St. 31 (E7), the number of TrkA-positive, Islet-1-positive cells increases to 100% (Figure 3D) and immunoreactivities for both TrkB and TrkC appear dispersed (Figure 3E, 3F). By St. 34 (E8), TrkA expression is well-sustained (Figure 3G) and TrkB and TrkC immunoreactivities are lost (Figure 3H, 3I). We also examined the early development of murine sympathetic ganglia (Figure 4). At E13, the newly formed lumbar sympathetic ganglia can be observed ventral to the spinal cord and notochord by their staining for Hu C/D and TH (Figure 4A). TrkB-positive cells can be seen surrounding developing ganglia, as well as in occasional cells within the ganglia (Figure 4C, D). These TrkB-positive cells within the ganglia co-express TH and are seen at a frequency of 1–2 cells per section starting at E13 (Figure 4A–D) and are still present at E15.5 (data not shown).\nIn neuroblastoma cells, BDNF is co-expressed with TrkB, suggesting that autocrine stimulation is a means by which proliferation is sustained in the transformed cells. To test whether BDNF, the ligand for TrkB, was present in embryonic chick sympathetic ganglia, we used quantitative real-time PCR with TaqMan probes to determine the relative abundance of BDNF transcripts in total RNA extracted from lumbar sympathetic ganglia at St. 29/30 (E6.5), St. 31 (E7), St. 34 (E8), and E9. BDNF expression within the ganglia parallels that of TrkB: BDNF mRNA expression levels are highest at St 29/30 (E6.5), and these levels decrease 2-fold at St. 31 (E7) and St. 34 (E8; Figure 5). By E9, BDNF levels are 7 times lower than at St. 29/30 (E6.5; Figure 5).\n\nNT3 and NGF promote survival of differentiating sympathetic neurons in culture\nTo determine the effect of neurotrophins, we cultured cells dispersed from lumbar sympathetic ganglia at St. 29/30 (E6.5) because, at this stage, ganglion formation is complete, the number of TrkA-, TrkB-, and TrkC-positive cells have peaked, and all Trk-expressing cells have initiated neural differentiation. First, we identified markers expressed by acutely isolated cells. As shown in Table 1, 80–91% of the cells are p75 neurotrophin receptor (NTR)-positive, indicating that most of the cells are neural crest-derived and little mesenchymal contamination is introduced by the isolation procedure. In addition, 28–33% of the cultured cells express the neural marker Hu C/D. Approximately half of these Hu C/D-positive cells express TrkB. Conversely, all of the TrkB positive cells express Hu C/D. These TrkB-positive cells comprise approximately 14–17% of the total cell population.\nWe then determined how many of the acutely isolated cells were proliferating by incubating them for 12 hrs in BrdU-containing medium. For these experiments, we identified differentiating neurons with the transcription factor Islet-1 because this marker labels nuclei, thus it co localizes with any BrdU that has been incorporated into the DNA, allowing us to determine whether the cell had undergone S-phase of the cell cycle. After 12 hrs in BrdU, 59% of Islet-1-positive nuclei stain for BrdU immunoreactivity. Thus, cultures of St. 29/30 sympathetic ganglia contain many cells that proliferate while exhibiting markers of neuronal differentiation, confirming previous observations [2]. We call these dividing neuronal precursors sympathoblasts. The remaining non-BrdU incorporating, Islet-1 positive cells are likely to be post mitotic neurons.\nFinally, we determined the trophic requirements of St. 29/30 (E6.5) sympathetic neurons and sympathoblasts. We monitored cultures over a three day period after plating and counted the number of phase bright cells with neurites, a morphological feature of both neurons and sympathoblasts. In the absence of trophic factors, more than 2/3 of the cells die by 24 hours in culture and BDNF, NT-3, or NGF alone is not sufficient to promote survival (Figure 6). However, NGF together with NT-3 supports the survival of a significantly larger number of cells (Figure 6). For the subsequent experiments, all neurons were cultured with 25 ng/ml NT-3 and 1 μg/ml 7S NGF to optimize survival.\n\nBDNF promotes proliferation of TrkB-positive sympathetic neurons in culture\nTo determine the effects of BDNF, cultures of cells from St. 29/30 (E6.5) sympathetic ganglia were supplemented with 200 ng/ml BDNF and the number of neurons and sympathoblasts were counted at 24, 48, and 72 hours using phase microscopy (Figure 7A). A 1.6-fold increase in the number of neurons due to BDNF is observed by 24 hours and this number does not increase further at 48 or 72 hours. This effect of BDNF is concentration-dependent with an EC50 of 75 ng/ml (Figure 7B).\nTo test whether the increase in the number of neurons and sympathoblasts caused by BDNF is due to the differentiation of pluripotent neural crest cells, we quantified the effects of BDNF on the number of neurally differentiating cells (Hu C/D-positive) versus the number of non-neuronal cells (Hu C/D-negative) after identifying all neural crest-derived cells by staining for p75NTR in St. 29/30 (E6.5) cultures. If BDNF increases the number of neurons and sympathoblasts by inducing a non-neuronal cell to express Hu C/D, then we expected that the total cell number would remain the same and that there would be a decrease in the number of non-neuronal cells as well as a corresponding increase in the number of neurons. After 24 hours, BDNF significantly increases the number of p75NTR-positive cells as well as the number of Hu C/D-positive cells (Figure 8A). However, there was no statistically significant change in the number of non-neuronal cells. Thus, it is unlikely that BDNF increases the number of neurons and sympathoblasts by inducing differentiation of non-neuronal cells.\nTo determine whether the increase in the total number of neurons and sympathoblasts is caused by BDNF-induced proliferation, control and BDNF-treated sympathetic cultures were exposed to BrdU for 12 hours after plating, and the number of cells that incorporated BrdU into their DNA was determined after 24 hours in culture. Even in the control condition, a number of cells in the culture are dividing, giving a high baseline of BrdU incorporation (Figure 8B). When BDNF is added, the total number of BrdU positive cells increases approximately 1.6-fold (Figure 8B). This BDNF-induced increase in the total number of BrdU positive cells occurs in sympathoblasts because the number of Islet-1-positive nuclei from control cultures that label with BrdU is 268 ± 59 and BDNF treatment raises this number to 424 ± 80, which corresponds to an increase of 1.6-fold. This accounts for the 1.6-fold increase in total neuron number and total BrdU-positive cells described above. We then confirmed that BDNF acts on TrkB-positive cells: BDNF increases the number of TrkB-expressing cells that incorporate BrdU 2.6 – 4-fold over control (Table 2) and it also increases the overall number of TrkB-positive cells 2 – 2.5-fold over control (Table 2). BDNF does not increase the number of BrdU-positive, TrkB-negative cells or the overall number of TrkB-negative cells (Table 2). In further support that BDNF acts directly on TrkB-expressing cells, an antibody directed against the extracellular domain of TrkB completely prevents the effect of BDNF in promoting proliferation of TrkB-positive, but not TrkB-negative cells (compare Figure 9A to 9B). Thus, the effect of BDNF is restricted to the population that expresses TrkB, which are developing sympathoblasts.\nTo determine whether TrkB-positive cells are actively proliferating in vivo, embryos were injected with BrdU at St. 27 and harvested at St. 29, approximately 24 hrs later. The majority (85–90%) of TrkB-positive cells do not incorporate BrdU into their nuclei under basal conditions in vivo (Figure 10), although a few TrkB positive cells with labeled nuclei could be observed (arrows). This contrasts with our observation that 71–76% of TrkB-positive cells incorporate BrdU in culture after treatment with BDNF (Table 2), suggesting that endogenous BDNF does not achieve a threshold sufficient to support a high level of sympathoblast proliferation in vivo.\n\n\nDiscussion\nWe report that the neurotrophin receptor TrkB is expressed in a subset of embryonic sympathoblasts during the early development of lumbar paravertebral sympathetic ganglia in chicken and mouse embryos. In the chicken, TrkB expression is transient, and completely lost by St 34 (E8). Since BDNF induces the proliferation of sympathoblasts in cell culture, yet in vivo there is little proliferation observed in TrkB-positive cells in nascent ganglia, we propose that if TrkB activation becomes unregulated by excess BDNF or constitutive phosphorylation of TrkB [16], this transient population of TrkB-positive sympathoblasts may trigger the genesis of neuroblastoma, a childhood tumor found in the paravertebral chain and adrenal medulla.\nThe two populations of sympathoblasts that we observe support previous findings of heterogeneity among developing sympathetic neurons and neural crest cells. Early sympathetic ganglia contain at least two subpopulations: early differentiating neurons that lack TrkB expression and express TrkA and TrkC, and late differentiating sympathoblasts that express TrkB. Explant cultures of sympathetic ganglia from E16 chick embryos give rise to two neuronal populations: one that remains close to the explant, and one that migrates away from the explant [1]. In addition, early neuronal subpopulations have been observed in cultures of neural crest cells from St. 13/14 quail embryos as evidenced by the expression of neuronal cell type-specific gangliosides [17]. Perhaps these different subpopulations will ultimately give rise to the two neurochemically distinct populations found in lumbar sympathetic ganglia: the noradrenergic, NPY-containing neurons that innervate internal organs and enteric ganglia and the cholinergic, VIP-containing neurons that innervate vasculature in the hind limbs.\nThe effects of BDNF and TrkB deletion and over expression have been studied on superior cervical ganglion and preganglionic neurons in thoracic segments of the spinal column, but not on paravertebral sympathetic neurons. In the superior cervical ganglion, an increase in the number of neurons of BDNF null mice is likely due to apoptosis induced by BDNF via p75NTR [18]. In contrast, the responses of paravertebral sympathetic neurons to BDNF are complex and subtype dependent. Over expression of BDNF leads to an increase in the number of noradrenergic fibers innervating the erector pilli muscles of hair follicles, while noradrenergic fibers innervating blood vessels were unaffected [19]. If our results indicating that BDNF promotes proliferation of TrkB-positive sympathoblasts in the chicken embryo can be extrapolated to the subset of TrkB-positive sympathoblasts in murine ganglia, then these TrkB-positive cells may be neurons destined to innervate the erector pilli. In other studies, TrkB null mice showed no changes in morphology or cell number in superior cervical ganglia [12] or in the intermediolateral column [20]; but this may not be predictive of a phenotype in the lumbar paravertebral chain. It is thus possible that BDNF/TrkB signaling could play a specific role in other regions of the paravertebral sympathetic chain, such as the lumbar region. However, if TrkB-positive cells are not normally actively proliferating in vivo, then it would not be surprising that the development of the paravertebral sympathetic chain is not disrupted in TrkB or BDNF null mice. It may be more informative to examine mice that over express BDNF on a promoter that targets expression to embryonic lumbar ganglia. Unfortunately, such mice do not exist.\nOur findings that the St. 29/30 (E6.5) sympathoblasts are dependent on both NT-3 and NGF for survival in culture are consistent with previous work on mouse sympathoblasts from the superior cervical ganglion [11]. In these studies, NT-3 and NGF deletion separately led to a decrease in the number of sympathetic neurons at E17.5 compared to control. Deletion of both NT-3 and NGF together did not enhance cell death. In contrast, cultured rat superior cervical ganglion sympathetic neurons respond to NT-3 at E14.5 and then to NGF at E19.5, although time points in between were not analyzed [6].\nIn addition to promoting survival, NT-3, NGF, and BDNF also induce proliferation of various neuronal precursors at different stages of development. NT-3 can promote the incorporation of [3H]-thymidine into cultured quail neural crest cells from the trunk region [21,22], Later in rat sympathetic development, NT-3 supports survival of neurons, but does not promote proliferation [6], which is consistent with our results. NGF promotes an increase in BrdU incorporation from 25% to 35% in the DRG cervical segment 2 in the chick embryo [23]. In chicken embryos that are treated with NGF in ovo at St. 18 and 21, there is an increase in BrdU uptake after formation of the primary sympathetic chain at St. 23 [24]. Since NGF does not appear to affect proliferation of St. 29/30 (E6.5) chick sympathoblasts, NGF may only promote proliferation in primary, but not secondary chain sympathoblasts. Motor neuron progenitors in the ventral neural tube from the chick embryo express TrkB and when ventral neural tube explants are treated with BDNF, there is an increase in the number of motor neurons produced and BrdU incorporation [25]. BDNF also promotes the proliferation of cultured neuroblastoma cells [13]. Taken together, these results are consistent with our findings that NT-3 and NGF do not promote proliferation of St. 29/30 (E6.5) sympathoblasts, and support the assertion that BDNF promotes proliferation of TrkB-positive sympathoblasts in culture.\nOur observations suggest a transient function of TrkB during early sympathetic development in supporting proliferation of this early subpopulation of sympathoblasts. However, the in vivo labeling suggests that only a minority (10–20%) of this population is dividing during the window that TrkB is expressed. In light of the very strong proliferative effect produced in cell culture, these TrkB expressing cells could respond more strongly if endogenous BDNF rises to higher levels, or if the mechanism that down regulates TrkB expression becomes nonfunctional. Such events could trigger an early proliferative event that leads to a cascade of changes that initiates transformation of cells to neuroblastoma. Thus, these early TrkB expressing cells help solve the puzzle as to why TrkB is expressed in aggressive and invasive forms of neuroblastoma, particularly because BDNF induces cultured neuroblastoma cells to become more proliferative, invasive, angiogenic, and resistant to chemotherapeutic reagents than untreated cultures [13]. Future studies will determine whether constitutive expression of BDNF and TrkB in the chick embryo sustains proliferation of differentiating sympathoblasts.\n\nConclusion\nWe have identified a time point during development when differentiating lumbar sympathetic neurons transiently express TrkB and proliferate in response to high concentrations of BDNF in culture. These studies suggest that elevated BDNF expression above basal levels and signaling through TrkB may be a mechanism that contributes to the onset of neuroblastoma. A further understanding of the two populations of sympathetic neurons and the fate of the TrkB-positive cells will provide additional insight into the development of paravertebral sympathetic ganglia and the genesis of neuroblastoma.\n\nMethods\nPreparation of tissue for immunohistochemistry\nThe lumbar spinal column and surrounding tissues were dissected from chicken embryos at the indicated stages and placed in Zamboni's fixative (4% (w/v) paraformaldehyde, 15% (v/v) picric acid in 0.1 M sodium phosphate buffer, pH 7.4) for two hours at room temperature. Mouse embryos at 13–15 days post-coitus were collected according to an IACUC-approved protocol to Dr. L. Sherman at the Oregon Health and Science University. The mouse embryos were immersion-fixed in Zamboni's fixative overnight at 4 degrees C then washed with phosphate buffered saline (PBS; 130 mM NaCl, 20 mM sodium phosphate buffer, pH 7.4). Fixed tissues were equilibrated in 30% sucrose in 1× phosphate-buffered saline (PBS). Fixed mouse embryos were shipped to Vermont in sucrose. Transverse 30 μM sections of the spinal columns were cut at on a Microm HM cryostat (knife temperature: 16°C; object temperature: 23°C) and collected on Superfrost Plus slides (Fisher). Sections were dried at room temperature, washed in 1× PBS and incubated overnight in blocking buffer (1× PBS consisting of 10% (v/v) heat-inactivated horse serum (Invitrogen/Gibco), 0.5% Triton X-100 (Sigma), and 0.1% sodium azide (Fisher)).\n\nImmunohistochemistry\nSections were incubated with primary antibodies overnight at 4°C, followed by incubation with secondary antibodies for 2 hours at room temperature. Primary antibodies used were: rabbit anti-p75 (1:1500, generous gift from Louis Reichardt, UCSF [26]), mouse IgG2b anti-Hu C/D, (1:250, Molecular Probes); mouse IgG1 anti-Islet-1, (1:10, Developmental Studies Hybridoma Bank); rabbit anti-chicken TrkA (1:500); rabbit anti-chicken TrkB (1:500); rabbit anti-chicken TrkC (1:500) (all Trk antibodies were generous gifts of Dr. Louis Reichardt, UCSF [26-28]); mouse anti-HNK-1 (1:50, Developmental Studies Hybridoma Bank); mouse IgG2a anti-tyrosine hydroxylase (1:10, Developmental Studies Hybridoma Bank), sheep anti-BrdU (1:100, Biodesign International), rabbit anti-tyrosine hydroxylase (1:100, Chemicon), and goat anti-TrkB (1:1000, R&D Systems). Immunofluorescence was imaged using a Nikon C1 confocal mounted on a Nikon Eclipse E800 microscope with a 10× Plan Apo (NA 0.785) air objective or a 60× Plan Apo (NA 1.4) oil objective lens, E7-C1 software, and UV, Argon, and He/Ne lasers exciting at 408, 488, and 543 nm and emitting at 404 500–530, and 555–615 nm, respectively. A Nikon Eclipse E800 microscope in the nearby COBRE Molecular/Cellular Core Facility was used for counting immunofluorescent cells at 200× using epifluorescence optics.\n\nRNA Extraction/cDNA synthesis\nSympathetic ganglia were removed from chick embryos and RNA was isolated using TriReagent (Molecular Research Center), an acidified guanidinium with phenol extraction method [29]. RNA was transcribed to cDNA using oligo-dT with Superscript II Reverse Transcriptase (Invitrogen) at 42°C for 1 hour.\n\nReal-time PCR\nRelative RNA levels were determined using quantitative real-time PCR with an ABI 7500 Fast Real Time PCR System. TaqMan probes were used to quantify the progression of the PCR reaction and reactions were normalized using the constitutively expressed gene chick ribosomal binding protein s17 (CHRPS). The sequences were used for primer/probes sets: for BDNF: forward: 5'-AGCCCAGTGAGGAAAACAAG-3', reverse: 5'-ACTCCTCGAGCAGAAAGAGC-3', probe: 5'-[6-FAM]-TACACATCCCGAGTCATGCTGAGCA-[BHQ]-3'; for CHRPS (chick ribosomal binding protein S-17): 5'AACGACTTCCACACCAACAA3', reverse: 5'CTTCATCAGGTGGGTGACAT3', probe: 5'-[6-FAM]-CGCCATCATCCCCAGCAAGA [BHQ]-3'. Primers and probes were synthesized by Operon Technologies, Inc (Alameda, CA). The primers for BDNF were validated against primers for CHRPS according to an Applied BioSystems protocol by serially diluting the target cDNA 1:10, determining the cycle threshold (Ct) for each reaction, and plotting the Ct versus log concentration. Slopes of the resulting lines were calculated and primers were accepted if their Ct slopes were between -3.2 and -3.4 (a perfect efficiency of 1.0 yields a slope of -3.3). To analyze the data, the delta Ct method of relative quantification was used, where the Ct of Chrps was subtracted from the Ct of the gene of interest (Delta Ct) and the arbitrary units of mRNA were expressed as 10000/2^(Delta Ct).\n\nCell culture\nSympathetic neurons were cultured as previously described [30] with a few modifications. Sympathetic ganglia were removed from the lumbar region of the paravertebral chain of St. 29/30 (E6.5) chick embryos and placed in Modified Puck's solution with glucose (MPG). The cells were dissociated by incubation of sympathetic ganglia with 0.1% trypsin in MPG at 37°C for 10 minutes followed by triturating with a fire polished 9\" Pasteur pipette. Cells were then resuspended in Dulbecco's Modified Eagle Medium (DMEM) consisting of 10% horse serum, 2% fetal calf serum, and 10 mg/ml penicillin/streptomycin. For neurotrophin studies, the culture medium was supplemented with 25 ng/ml NT-3 (R & D Systems) and 1 μg/ml 7S NGF (Alomone Labs) upon plating, and 50 ng/ml, 100 ng/ml, or 200 ng/ml BDNF (R & D Systems) once the cells adhered to the wells. Cells were plated on poly-D-lysine/laminin coated wells or cover slips (Fisher) as previously described [30].\n\nQuantification of neurons and sympathoblasts using phase microscopy\nEmbryonic sympathoblasts and neurons are small, phase bright cells with neurites. The total number of cells with neurites the length of two cell bodies were counted in 10 non-overlapping fields of view evenly spaced in a grid-like pattern across the bottom of a well from a 24 well plate at 200× using a Nikon Eclipse TE200 microscope.\n\nBrdU labeling\nFor in vitro studies, approximately 2 hours after plating cells from St. 29/30 (E6.5) sympathetic ganglia, cells were labeled with 10 μM bromodeoxyuridine (BrdU, Sigma) for 12 hours at 37°C. Following this labeling period, cells were incubated in complete medium without BrdU for an additional 10 hrs. Cells were then fixed in Zamboni's fixative for 30 min at room temperature and rinsed with 1× PBS. For in vivo studies, 25 μg BrdU was injected into the amnion of chick embryos at St. 27. The cells and sections were denatured with 2 N HCl at 37°C for 1 hr, and were then neutralized with 0.1 M borate buffer, pH 8.5, for 10 min at room temperature. Immunochemistry was performed as described above.\n\n\nAbbreviations\nBDNF, brain-derived neurotrophic factor; BrdU, Bromodeoxyuridine; DA, dorsal aorta; DMEM, Dulbecco's Modified Eagle's Medium; DRG, dorsal root ganglion; E, embryonic day; HS, horse serum; MPG, Modified Puck's solution with glucose; NGF, nerve growth factor; NC, notochord; NT, neural tube; NT-3, neurotrophin-3; NTR, neurotrophin receptor; PBS, phosphate-buffered saline; SC, spinal cord; SCG, superior cervical ganglion; SEM, standard error of the mean; SG, sympathetic ganglion; St., stage; w/v, weight/volume; v/v, volume/volume.\n\nAuthors' contributions\nJAS designed the experiments, performed the experiments, analyzed the data, and wrote the manuscript. GLSS contributed intellectually to the conception and design of this study, and assisted in the interpretation of the results. RN supervised the study, participated in the design of experiments, edited the manuscript, and obtained funding for the project. All authors read and approved the final manuscript.\n\n\n" ], "offsets": [ [ 0, 32104 ] ] } ]

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{ "db_name": "ncbi", "db_id": "9796" } ] } ]

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1

pmcA1779441

[ { "id": "pmcA1779441__text", "type": "Article", "text": [ "Identification of a human peripheral blood monocyte subset that differentiates into osteoclasts\nAbstract\nIncreased bone resorption mediated by osteoclasts causes various diseases such as osteoporosis and bone erosion in rheumatoid arthritis (RA). Osteoclasts are derived from the monocyte/macrophage lineage, but the precise origin remains unclear. In the present study, we show that the purified CD16- human peripheral blood monocyte subset, but not the CD16+ monocyte subset, differentiates into osteoclast by stimulation with receptor activator of NF-κB ligand (RANKL) in combination with macrophage colony-stimulating factor (M-CSF). Integrin-β3 mRNA and the integrin-αvβ3 heterodimer were only expressed on CD16- monocytes, when they were stimulated with RANKL + M-CSF. Downregulation of β3-subunit expression by small interfering RNA targeting β3 abrogated osteoclastogenesis from the CD16- monocyte subset. In contrast, the CD16+ monocyte subset expressed larger amounts of tumor necrosis factor alpha and IL-6 than the CD16- subset, which was further enhanced by RANKL stimulation. Examination of RA synovial tissue showed accumulation of both CD16+ and CD16- macrophages. Our results suggest that peripheral blood monocytes consist of two functionally heterogeneous subsets with distinct responses to RANKL. Osteoclasts seem to originate from CD16- monocytes, and integrin β3 is necessary for osteoclastogenesis. Blockade of accumulation and activation of CD16- monocytes could therefore be a beneficial approach as an anti-bone resorptive therapy, especially for RA.\n\nIntroduction\nRheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammation and proliferation of the synovium in multiple joints. A large number of inflammatory cells, including T cells, B cells, macrophages and dendritic cells, accumulate in the affected synovium, and these inflammatory cells, together with fibroblast-like synoviocytes, express various cytokines, such as tumor necrosis factor alpha (TNFα), IL-6 and receptor activator of NF-κB ligand (RANKL), which are known to induce differentiation and activation of osteoclasts. The inflammatory synovial tissue, known as pannus, invades the articular bone and causes focal bone erosion, which is the hallmark of RA. Histopathologically, osteoclasts are present at the interface of the pannus and bone. Interestingly, the deletion of RANKL or c-Fos gene, which is important for osteoclastogenesis, results in minimal bone destruction in mouse models of arthritis [1,2]. Furthermore, other studies indicated that inhibition of osteoclastogenesis by osteoprotegerin, a decoy receptor for RANKL, limits bone destruction in experimental models of arthritis. These studies suggest that osteoclasts are involved in focal bone erosion in RA [3].\nOsteoclasts are derived from the monocyte/macrophage lineage. It is reported that osteoclast precursors reside in human peripheral blood monocytes [4,5]. A marked increase of the circulating osteoclast precursors was demonstrated in patients with erosive psoriatic arthritis as well as in arthritic TNFα transgenic mice [6,7]. It was also shown that peripheral monocytes differentiate into osteoclasts when seeded on RANKL/osteoclast differentiation factor-producing RA synovial fibroblasts [8]. In addition, RA synovial macrophages thought to originate from peripheral blood monocytes were shown to differentiate into osteoclasts [9,10]. Monocytes are therefore involved not only in synovial inflammation, but also in bone remodeling as potential precursors for synovial macrophages and osteoclasts.\nHuman peripheral blood monocytes consist of two major subsets, CD16+ and CD16-, comprising 5–10% and 90–95% of the monocytes, respectively. These two subsets exhibit different chemotaxis activities and potential of cytokine production [11,12]. Moreover, activation of the Toll-like receptor induces distinct subsets, CD1b+ dendritic cells and DC-SIGN+ (dendritic cell-specific C-type lectin ICAM-3-grabbing nonintegrin) macrophages from CD16+ and CD16- monocytes, respectively [13]. It has not been revealed, however, which monocyte subset develops into osteoclasts.\nIn the present study, we determined the human peripheral blood monocyte subset that differentiates into osteoclasts, and revealed that each subset exhibits a different response for osteoclastogenic stimuli.\n\nMaterials and methods\nPurification of peripheral blood monocytes\nPeripheral blood monocytes from healthy donors were collected using Ficoll-Conray (Imuuno-Biological Laboratories, Gunma, Japan) gradient centrifugation. Negative selection of monocytes was performed using MACS microbeads (Miltenyi Biotec, Auburn, CA, USA) according to the protocol supplied by the manufacturer.\nThe purified monocytes were separated into two subsets, CD16+ and CD16- monocytes, using CD16 MicroBeads (Miltenyi Biotec). Flow cytometry analysis using FITC-conjugated mouse anti-CD14 mAb (MY4; Bechman Coulter, Fullerton, CA, USA) and phycoerythin-conjugated mouse anti-CD16 mAb (3G8; BD Biosciences, San Jose, CA, USA) showed that the purities of the CD16+ and CD16- monocytes were more than 90% and 92%, respectively.\nFor the other experiment, monocytes were purified using CD14 MicroBeads (Miltenyi Biotec), and then stained either with FITC-conjugated mouse anti-CD33 mAb (MY9; Bechman Coulter) or phycoerythin-conjugated mouse anti-CD16 mAb (3G8). Cell sorting of the stained cells was performed using a FACS Vantage cytometer (BD Biosciences) or a MoFlo cell sorter (Dako, Glostrup, Denmark).\n\nOsteoclast differentiation\nPurified CD16+ and CD16- monocytes (5 × 104 cells/well) were incubated in 96-well plates in αMEM (Sigma, St Louis, MO, USA) with heat-inactivated 10% fetal bovine serum (FBS) (Sigma) or with Ultra-Low IgG FBS (IgG < 5 μg/ml; Invitrogen, Carlsbad, CA, USA), and where indicated with M-CSF + RANKL (Peprotech, Rocky Hill, NJ, USA).\nFor the other experiments, varied numbers of CD16+ monocytes (1 × 103, 2.5 × 103, 5 × 103) were mixed with CD16- monocytes (5 × 104 cells/well), and were cultured in 96-well plates in αMEM with heat-inactivated 10% FBS. The medium was replaced with fresh medium 3 days later, and after incubation for 7 days the cells were stained for tartrate-resistant acid phosphatase (TRAP) expression using a commercial kit (Hokudo, Sapporo, Japan). The number of TRAP-positive multinucleated cells (MNC) in three randomly selected fields examined at 100× magnification or the total number of TRAP-positive MNC per well was counted under light microscopy.\n\nResorption assay\nMonocytes were seeded onto plates coated with calcium phosphate thin films (Biocoat Osteologic; BD Biosciences) and were incubated with RANKL (40 ng/ml) + M-CSF (25 ng/ml) for 7 days. The cells were then lysed in bleach solution (6% NaOCl, 5.2% NaCl). The resorption lacunae were examined under light microscopy.\n\nEnzyme-linked immunosorbent assay\nPurified monocytes were cultured in 96-well plates where indicated either with RANKL or M-CSF for 24 hours. Concentrations of TNFα and IL-6 in the culture supernatant were measured with an ELISA kit (BioSourse International, Camarillo, CA, USA). For experiments of matrix metalloproteinase (MMP)-9 and TRAP-5b, culture supernatants were collected on day 7 and the concentrations of these enzymes were measured using an MMP-9 ELISA kit (Amersham Biosciences, Piscataway, NJ, USA) or a TRAP-5b ELISA kit (Suomen, Turku, Finland).\n\nReverse transcriptase-polymerase chain reaction\nMonocytes (1 × 106 cells/well) were cultured in six-well plates with M-CSF alone or with M-CSF + RANKL for 3 days. Total RNA was extracted using RNeasy Micro (Qiagen, Valencia, CA, USA). The RNA was then treated with DNase I (Qiagen). The oligo(dT)-primed cDNA was synthesized using Superscript II reverse transcriptase (Invitrogen). The amount of cDNA for amplification was adjusted by the amount of RNA measured by an optical density meter and also by β-actin or GAPDH PCR products. One microliter of cDNA was amplified in a 50 μl final volume containing 25 pmol appropriate primer pair, 10 pmol each of the four deoxynucleotide triphosphates, and 5 units FastStart Taq DNA Polymerase (Roche, Manheim, Germany) in a thermal cycler (PTC-200; MJ GeneWorks, Waltham, MA, USA).\nThe PCR conditions were 25–40 cycles of denaturation (95°C for 30 s), annealing (60–62°C for 1 min) and extension (72°C for 1 min). The sequences of the primers are presented in Table 1. The PCR products were separated by electrophoresis through 2% agarose gel.\n\nWestern immunoblot analysis\nPurified monocytes were cultured for 3 days in the presence of 40 ng/ml M-CSF with or without 25 ng/ml RANKL. Cells were lysed in RIPA Lysis buffer (upstate, Lake Placid, NY, USA) containing protease inhibitors (Roche) for 15 min at 4°C. A total of 20 μg protein was boiled in the presence of 6 × sodium dodecyl sulfate sample buffer, and was separated on 7.5% or 10% sodium dodecyl sulfate-polyacrylamide gel (ATTO, Tokyo, Japan). Proteins were then electrotransferred to a polyvinylidene fluoride microporous membrane (Millipore, Billerica, MA, USA) in a semidry system. Membranes were incubated in 10% skim milk prepared in phosphate-buffered saline (PBS) containing 0.1% Tween 20, and were subjected to immunoblotting. Antibodies used were goat anti-RANK antibody (Techne Corporation, Minneapolis, MN, USA), goat anti-c-fms antibody (R&D systems, Minneapolis, MN, USA), and mouse anti-β-actin mAb (AC-15; Sigma). Peroxidase-conjugated rabbit anti-goat IgG antibody (Dako) or peroxidase-conjugated rabbit anti-mouse IgG antibody (Dako) was used as the second antibody. The signals were visualized by chemiluminescence reagent (ECL; Amersham Biocsiences, Little Chalfont, UK).\n\nCell surface expression of c-fms\nThe following mAbs were used for analysis of c-fms expression: Alexa 647-conjugated anti-CD14 mAb (UCHM1; Serotec, Oxford, UK), FITC-conjugated anti-CD16 mAb (3G8; Bechman Coulter) and phycoerythin-conjugated anti-c-fms mAb (61708; R&D systems). Alexa 647-conjugated mouse IgG2a (Serotec), FITC-conjugated mouse IgG1 (BD Biosciences) and phycoerythin-conjugated mouse IgG1 (Bechman Coulter) were used as isotype controls. Peripheral blood monocytes (1 × 105 cells) were incubated with 1 μg human IgG for 15 minutes, and were then stained with three fluorochrome-labeled mAbs for 45 minutes on ice. The stained cells were analyzed with a FACS Calibur (BD Biosciences).\n\nImmunofluorescent staining\nMonocytes (8 × 104 cells/well) were allowed to adhere on 96-well plates overnight or were cultured with M-CSF and RANKL for 2–4 days. The cells were fixed in acetone and then stained with anti-αvβ3 mAb (LM609; Chemicon, Temecula, CA, USA) or mouse IgG1 (11711; R&D Systems) as an isotype-matched control. Alexa fluor546-conjugated goat anti-mouse IgG1 antibody (Molecular Probes, Eugene, OR, USA) was used as the second antibody. TOTO-3 (Molecular Probes) was used for nuclear staining.\n\nFlow cytometric analysis of p38 MAPK and ERK1/2 phosphorylation\nPurified monocytes were cultured in the presence of 25 ng/ml M-CSF for 3 days, and were either left unstimulated or were stimulated with 40 ng/ml RANKL at 37°C. Stimulations were stopped by adding an equal volume of PhosFlow Fix Buffer I solution (BD Biosciences) to the cell culture. After incubation for 10 minutes at 37°C, the cells were permeabilized by washing twice at room temperature in PhosFlow Perm/Wash Buffer I (BD Biosciences). A total of 1 × 105 cells was then Fc blocked with 1 μg human IgG for 15 minutes, and was stained with Alexa Fluor 647-conjugated mAb either to phospho-p38 MAPK (T180/Y182) or to phospho-ERK1/2 (T202/Y204) (BD Biosciences) for 30 minutes at room temperature. Alexa Fluor 647-conjugated mouse IgG1 (BD Biosciences) was used as an isotype control. The cells were washed in PhosFlow Perm/Wash Buffer I, and were analyzed by flow cytometry, as already described.\n\nRNA interference\nRNA oligonucleotides (iGENE, Tsukuba, Japan) were designed based on the algorithm that incorporates single nucleotide polymorphism and homology screening to ensure a target-specific RNA interference effect. The following sense and antisense oligonucleotides were used: integrin β3, 5'-GCU UCA AUG AGG AAG UGA AGA AGC A-AG and 3'-UA-CGA AGU UAC UCC UUC ACU UCU UCG U; randomized control, 5'-CGA UUC GCU AGA CCG GCU UCA UUG C-AG and 3'-UA-GCU AAG CGA UCU GGC CGA AGU AAC G; and lamin, 5'-GAG GAA CUG GAC UUC CAG AAG AAC A-AG and 3'-UA-CUC CUU GAC CUG AAG GUC UUC UUG U.\nCD16- monocytes (8 × 104 cells/well) were incubated in 96-well plates in optimem (Invitrogen). After 1 hour, siRNAs were transfected into the cells using oligofectamine (Qiagen) based on the method recommended by the manufacturer. After 2 hours, the cells were washed once with PBS, followed by the addition of αMEM supplemented with 10% FBS, M-CSF and RANKL. After a 2-day incubation, the β3 mRNA expression was analyzed by RT-PCR with different PCR cycles, as described earlier. Immunofluorescent staining for the αvβ3 heterodimer was also performed as described above, and numbers of αvβ3-positive cells were counted in randomly selected three fields at 100× magnification. Seven days after the transfection of siRNAs, the number of TRAP-positive MNC in five fields examined at 100× magnification was counted under light microscopy.\n\nInhibition of osteoclastogenesis with cyclic RGDfV peptide\nCD16- monocytes were incubated in 96-well plates with M-CSF + RANKL for 2 days. A medium containing either cyclic RGDfV peptide (Arg-Gly-Asp-D-Phe-Val) (Calbiochem, San Diego, CA, USA) or dimethyl sulfoxide was then added. After incubation for a further 5 days, the number of TRAP-positive MNC in five fields examined at 100× magnification was counted under light microscopy.\n\nImmunohistochemistry\nSynovial tissue samples were obtained during total knee joint replacement surgery from four RA patients. Signed consent forms were obtained before the operation. The experimental protocol was approved by the ethics committee of the Tokyo Medical and Dental University. RA was diagnosed according to the American College of Rheumatology criteria [14].\nDouble immunofluorescent staining for CD68 and CD16 antigens was conducted on optimal cutting temperature-embedded sections of frozen synovial samples. Eight-micrometer-thick cryostat sections of RA synovium were fixed in acetone for 3 minutes and were then rehydrated in PBS for 5 minutes. The samples were incubated in 5 μg/ml proteinase K (Roche), 50 mM ethylenediamine tetraacetic acid, 100 mM Tris–HCl, pH 8.0, for 15 minutes at room temperature followed by a wash in PBS. The samples were then blocked with 10% goat serum in PBS for 60 minutes at room temperature, and were incubated with anti-CD16 mAb (3G8; Immunotech, Marseille, France) or mouse IgG1 (11711) as an isotype-matched control in 1% bovine serum albumin/PBS for 60 minutes at room temperature. The samples were then washed three times in PBS, for 5 minutes each, and incubated with Alexa fluor546-conjugated goat anti-mouse IgG1 antibody (Molecular Probes) in 1% bovine serum albumin/PBS for 60 minutes at room temperature. The samples were then sequentially stained for CD68 antigen in a manner similar to that used for CD16 staining. The samples were stained with anti-CD68 mAb (PGM1; Immunotech) or mouse IgG3 (6A3; MBL, Nagoya, Japan) followed by labeling with Alexa fluor488-conjugated goat anti-mouse IgG3 antibody (Molecular Probes). The samples were examined by confocal laser scanning microscope (Olympus, Tokyo, Japan).\n\nStatistical analysis\nData are expressed as the mean ± standard error of the mean. A nonpaired Student's t test was used for comparison, using the StatView program (Abacus Concepts, Berkeley, CA, USA). P < 0.05 was considered statistically significant.\n\n\nResults\nInduction of osteoclasts from CD16- peripheral blood monocytes\nTo identify the monocyte subset that differentiates into osteoclasts, we examined osteoclast formation from CD16+ and CD16- human peripheral blood monocytes. The monocyte subsets were purified using magnetic beads. Incubation with M-CSF alone did not induce osteoclast formation from either subset (Figure 1a). Culture with M-CSF + RANKL induced a significant number of TRAP-positive MNC from the CD16- subset, whereas only few CD16+ monocytes differentiated into TRAP-positive MNC (Figure 1a,b). We then assessed the bone resorptive ability by culturing cells on calcium phosphate-coated plates with M-CSF + RANKL. Resorption lacunae were detected only in the CD16- subset (Figure 1c), indicating the TRAP-positive CD16--derived MNC possessed the osteoclast phenotype.\nSimilar results were obtained using purified monocytes by FACS sorting (purities: CD16+, 96%; CD16-, 97%). The number of TRAP-positive MNC induced were 36 ± 3 cells/well and 348 ± 13 cells/well from CD16+ and CD16- monocytes, respectively. To exclude the possibility that the anti-CD16 antibody used for isolation of CD16+ monocytes inhibits osteoclast formation, we separated the two subsets, CD33low monocytes and CD33high monocytes, using anti-CD33 mAb and a fluorescent cell sorter, since it was reported that CD33low monocytes correspond to CD16+, and that CD33high correspond to CD16- monocytes [15]. On average, the CD33low population contained CD16- (10.2%)/CD16+ (89.8%) monocytes, and the CD33high population contained CD16- (86.3%)/CD16+ (13.7%) monocytes.\nCulture with M-CSF + RANKL induced TRAP-positive MNC from CD33high monocytes, whereas no or few CD33low monocytes differentiated into TRAP-positive MNC (CD33low vs CD33high, 2 ± 1 vs 192 ± 71 cells/well; n = 3). TRAP-5b and MMP-9 in the culture supernatants, both of which are known to be produced by osteoclasts, were measured by ELISA. The concentrations of both enzymes were significantly higher in the culture supernatant of CD16- monocytes than in that of CD16+ monocytes (Figure 1d). These results suggest that the CD16- peripheral blood monocyte subset, but not the CD16+ subset, differentiate into osteoclasts by incubation with RANKL + M-CSF.\n\nCD16+ monocytes do not affect the osteoclastogenesis from CD16- monocytes\nTo examine whether CD16+ monocytes affect osteoclastogenesis from CD16- monocytes, varied numbers of CD16+ monocytes were mixed with CD16- monocytes (5 × 104 cells/well), and were cultured for 7 days in the presence of M-CSF + RANKL. The number of TRAP-positive MNC was not altered by the presence of CD16+ monocytes (Figure 2). The results indicated that CD16+ monocytes did not hamper or enhance the osteoclastogenesis from CD16- monocytes.\n\nDifferences in cytokine production by RANKL-stimulated or M-CSF-stimulated CD16+ and CD16- monocytes\nTo compare the biological response of CD16+ and CD16- subsets with either RANKL or M-CSF stimulation, we measured the amount of TNFα and IL-6 production after exposure of cells to various concentrations of RANKL or M-CSF with an ELISA. Without RANKL the CD16+ subset produced a significant amount of TNFα and IL-6, whereas the CD16- subset produced undetectable levels (Figure 3a). RANKL stimulation increased TNFα production from both subsets in a dose-dependent manner, although the CD16+ subset produced more TNFα than did the CD16- subset. RANKL stimulation also enhanced IL-6 production from the CD16+ subset, but not from the CD16- subset. M-CSF stimulation increased TNFα and IL-6 production from both subsets, although the CD16+ subset produced more than the CD16- subset (Figure 3b).\nThese results suggest that CD16+ monocytes also respond both to RANKL and M-CSF stimulation, although such stimulation does not result in differentiation into osteoclasts. CD16+ monocytes were also noted to express higher amounts of inflammatory cytokines compared with CD16- monocytes with or without RANKL or M-CSF stimulation.\n\nComparison of expression levels of molecules involved in osteoclastogenesis between CD16+ and CD16- monocytes\nDiverse molecules are involved in RANKL/RANK and its costimulatory signal transduction pathways [16]. The different response to RANKL + M-CSF stimulation between the CD16+ monocyte subset and the CD16- monocytes subset might be explained by the expression profiles of these molecules. We therefore examined the mRNA levels of the following molecules: receptor activator of NF-κB (RANK), the receptor for RANKL; c-fms, the receptor for M-CSF; tumor necrosis factor receptor-associated factor 6 (TRAF-6), the adaptor protein for RANK; c-Fos and nuclear factor of activated T cells c1 (NFATc1), transcription factors that are essential for osteoclastogenesis; DNAX-activation protein 12 (DAP12) and Fc receptor γ chain (FcRγ), adaptor proteins known to deliver costimulatory signals in RANKL-induced osteoclastogenesis; signal regulatory protein β1 (SIRP-β1), triggering receptor expressed on myeloid cells 2 (TREM-2) and osteoclast-associated receptor (OSCAR), transmembrane receptors that associate with either DAP12 or FcRγ; and αv and β3, integrins known to be expressed as the αvβ3 heterodimer on osteoclasts.\nThe mRNA levels of RANK, c-fms, TRAF-6, DAP12 and SIRP-β1 under the baseline condition (no stimulation) varied between the donors; however, we did not find consistent differences in the mRNA levels of these molecules between the CD16+ monocyte subset and the CD16- monocyte subset among three to six donors (Figure 4a). The mRNA levels of other molecules, apart from integrin β3, were similar between the two subsets under the no-stimulation condition. Although the mRNA levels of RANK, c-fms, DAP12, FcRγ, TREM-2 and OSCAR increased in response to M-CSF alone or M-CSF + RANKL in both subsets, the expression levels were not significantly different between the two subsets. Expressions of TRAF-6, c-Fos and SIRP-β1 mRNA did not change following stimulation with M-CSF + RANKL. Of note, the expression of NFATc1 mRNA was enhanced by M-CSF + RANKL treatment only in the CD16- subset. Furthermore, expression of integrin αv in both subsets was enhanced by M-CSF with or without RANKL; however, the expression level was greater in the CD16- subset. It was noted that integrin-β3 mRNA was detected only in the CD16- subset and was increased by M-CSF + RANKL stimulation, but not by M-CSF alone. The protein expression of RANK under the baseline condition was weakly detected in both subsets, and the levels were varied between donors by western immunoblotting.\nThe protein expression of c-fms was weakly detected in unstimulated CD16+ monocytes, but not in CD16- monocytes (Figure 4b). Flow cytometry analysis of c-fms in fresh monocytes, however, showed that both subsets express the molecule on the cell surface (Figure 4c). Expressions of both RANK and c-fms were upregulated by M-CSF alone and by M-CSF + RANKL, and we did not find consistent differences in the protein levels of these molecules between the two monocyte subsets. The profiles of expression levels of molecules involved in RANKL/RANK and its costimulatory pathways are similar between the two subsets, except for NFATc1, integrin αv and integrin β3. We therefore assumed that the distinct induction of NFATc1, integrin αv and integrin β3 in response to RANKL stimulation among the two monocyte subsets might explain the differences in their abilities to differentiate into osteoclasts.\n\nRANKL stimulation induces αvβ3 expression on CD16- monocytes\nThe integrin-β3 subunit binds to integrin αv only and is expressed as the heterodimeric protein αvβ3 on monocytes and osteoclasts [17]. We examined the expression of αvβ3 on CD16+ and CD16- monocytes by immunofluorescent staining. Neither unstimulated nor M-CSF-stimulated monocyte subsets expressed αvβ3 (Figure 4d and data not shown). After 48 and 72 hours of treatment with M-CSF + RANKL, αvβ3-positive mononuclear cells were observed in CD16- monocyte cultures but not in CD16+ monocyte cultures. At 96 hours, both αvβ3-positive mononuclear cells and multinucleated cells were present in the CD16- monocyte culture. The results indicated that αvβ3 was selectively expressed on CD16- monocytes in the presence of M-CSF + RANKL, and the expression was revealed before the cells differentiate into typical multinucleated osteoclasts.\n\nRANKL activates ERK and p38 kinases only in CD16- monocytes\nSince ERK and p38 MAPK are essential in RANKL-induced osteoclastogenesis [18-20], we next examined whether these kinases were activated differently in CD16+ monocytes and in CD16- monocytes. Purified monocytes were precultured with 25 ng/ml M-CSF for 3 days to enhance RANK expression, and were then treated with RANKL. The RANKL treatment induced phosphorylation of both ERK and p38 MAPK in CD16- monocytes at 5 minutes postexposure, although the p38 MAPK phosphorylation was weak. Both phosphorylations declined to a basal level within 20 minutes (Figure 5). In contrast, ERK and p38 MAPK were not detectably phosphorylated in CD16+ monocytes with RANKL.\n\nsiRNA targeting integrin β3 inhibits osteoclastogenesis from CD16- monocytes\nThe integrin-β3 cytoplasmic domain is essential for activation of intracellular signals from αvβ3 heterodimers [17]. We therefore examined the involvement of αvβ3 in RANKL + M-CSF-induced osteoclastogenesis in human CD16- monocytes using siRNA targeting the integrin-β3 subunit. The integrin-β3 siRNA or control randomized siRNA were transfected into CD16- monocytes. At 48 hours post-transfection, we determined the integrin-β3 mRNA level and αvβ3 heterodimer protein expression. The integrin-β3 mRNA level was reduced in the integrin-β3 siRNA-transfected monocytes compared with control siRNA-transfected monocytes (Figure 6a). The αvβ3 heterodimer expression was evaluated by immunofluorescent staining. The number of αvβ3-positive cells was significantly decreased in integrin-β3 siRNA-transfected monocytes compared with that in control siRNA (Figure 6b).\nAfter 7 days of incubation, the number of TRAP-positive MNC was counted. Transfection with integrin-β3 siRNA significantly reduced the number of TRAP-positive MNC in a dose-dependent manner compared with control siRNA transfection (Figure 6c). In addition, the use of siRNA directed toward a different site of integrin-β3 mRNA also inhibited osteoclast formation from CD16- monocytes (data not shown). On the other hand, siRNA that targeted lamin, which was used as a negative control, did not inhibit the induction of osteoclasts (data not shown). These results indicate the importance of integrin β3 in RANKL-induced osteoclast formation from CD16- peripheral blood monocytes.\n\nCyclic RGDfV peptide inhibits the osteoclastogenesis from CD16- monocytes\nIntegrin αvβ3 recognizes a common tripeptide sequence, RGD (Arg-Gly-Asp), which is present in bone matrix proteins such as vitronectin and fibronectin [21]. Cyclic RGDfV peptide (Arg-Gly-Asp-D-Phe-Val) inhibits binding of the RGD-containing molecules to αvβ3 [22]. To investigate the role of ligand binding to the αvβ3 heterodimer in the osteoclastogenesis, we examined whether cyclic RGDfV peptide inhibits the formation of osteoclasts. Cyclic RGDfV peptide significantly reduced the number of TRAP-positive MNC in a dose-dependent manner (Figure 6d). The results imply possible involvement of ligand bindings to αvβ3 in the osteoclastogenesis.\n\nKnockdown of integrin β3 did not affect the expression of NFATc1 mRNA\nIn the next step, we determined whether integrin-β3-siRNA-induced inhibition of the osteoclastogenesis reflects downregulation of NFATc1, which is a key transcription factor in osteoclastogenesis [23]. For this purpose, we compared NFATc1 mRNA levels between integrin β3 and control siRNA-transfected monocytes. Interestingly, integrin-β3 knockdown did not alter the NFATc1 mRNA level (Figure 7), suggesting that signal transduction mediated by integrin β3 does not affect the expression of NFATc1.\n\nDetection of CD16+ and CD16- macrophages in synovium of RA patients\nRA synovial macrophages are derived from peripheral blood monocytes, and their recruitment into the synovium is facilitated by various adhesion molecules and chemokines [24]. To analyze CD16 expression on synovial macrophages, RA synovial tissues were double-stained for CD16 and a macrophage marker, CD68. CD16-/CD68+ macrophages were widespread in the synovium. Although less frequent, CD16+/CD68+ macrophages were also observed both in the synovial intima and subintima (Figure 8). The presence of two subsets of macrophages, CD16+ and CD16-, in RA synovium indicates that both CD16+ and CD16- peripheral blood monocytes are recruited into the synovium.\n\n\nDiscussion\nHuman peripheral blood monocytes are a heterogeneous population, and they are divided into two subsets based on the expression of CD16. The CD16+ and CD16- monocyte subsets show functional differences in migration, cytokine production and differentiation into macrophages or dendritic cells [11-13,15]. We focused on the heterogeneity of the monocytes, and the primary question addressed in this study was which monocyte subset could be the source of osteoclasts. The results demonstrated that CD16- peripheral blood monocytes, but not CD16+ monocytes, differentiated in vitro into osteoclasts by treatment with RANKL + M-CSF.\nTo investigate the molecular mechanisms of the different response to RANKL and the differentiation into osteoclasts between CD16+ and CD16- monocytes, we examined the expression of molecules known to be involved in osteoclastogenesis. The expression profiles of integrin αv, integrin β3 and NFATc1 were different between the two subsets. Integrin αvβ3 heterodimer was expressed only on RANKL and M-CSF-stimulated CD16- monocytes. It is known that αvβ3 expressed on osteoclasts is important in bone resorption as well as in attachment of osteoclasts to the bone matrix [25].\nIt was recently reported that bone marrow macrophages of integrin-β3-deficient mice could not differentiate into mature osteoclasts in vitro, suggesting that αvβ3 is involved not only in activation, but also in differentiation, of osteoclasts in mice [26,27]. The authors also showed that αvβ3 and c-fms share a common intracellular signaling pathway, including the activation of ERK and the induction of c-Fos [27], both of which are essential for osteoclastogenesis [28,29]. In addition, it was reported that echistatin, an αvβ3 antagonist, inhibited osteoclast formation of mouse bone marrow cells [30].\nIn accordance with these reports, our data showed that knockdown of integrin-β3 expression resulted in downregulation of the αvβ3 heterodimer, and abrogated osteoclastogenesis from human peripheral blood CD16- monocytes. We also showed that blocking of adhesive ligands to bind to αvβ3 by RGDfV peptide inhibited osteoclast formation from CD16- monocytes. Taken together, the process of ligand binding to αvβ3 may be involved in the osteoclastogenesis. Blockade of αvβ3 could therefore be a therapeutically beneficial approach to modulate osteoclastogenesis. Indeed, integrin αvβ3 antagonists effectively treated osteoporosis in mice, rats and humans, and protected bone destruction in rat adjuvant-induced arthritis in vivo [31-34]. Of note, it is reported that patients with Iraqi-Jewish-type Glanzmann thrombasthenia who are deficient in integrin β3 do not develop osteopetrosis because of the upregulation of α2β1 expression on osteoclasts, although the bone-resorptive ability of the osteoclasts was decreased in vitro [35]. The function of αvβ3 in vivo in osteoclast formation and resorptive function could therefore be partially compensated by other integrins.\nAlthough all the multinucleated osteoclasts expressed αvβ3 (Figure 4d) [36], a small number of M-CSF + RANKL-stimulated mononuclear CD16- monocytes expressed αvβ3 (Figure 4d). Multinucleated osteoclasts are formed by fusion of osteoclast precursor cells [37]. It was reported that αvβ3 is involved in the migration of osteoclast precursors [30]. The αvβ3-positive cells could therefore be forced to migrate by the ligands and may fuse with closed αvβ3-negative cells. Alternatively, only αvβ3-positive cells may be fused with each other.\nIt is possible to consider that signaling from CD16 by anti-CD16 mAb-coated magnetic beads, which were used for the cell separation, or by IgG contained in FBS might inhibit osteoclastogenesis from CD16+ monocytes. We therefore separated the two subsets using anti-CD33 mAb and a fluorescent cell sorter, and stimulated the cells with M-CSF + RANKL. The results showed that CD33low monocytes, which correspond to CD16+ monocytes, still could not differentiate into osteoclasts. CD16 is a heterodimer consisting of FcγIIIa and Fcγ, and has low affinity for the Fc region of IgG. Aggregation of CD16 by immune complexes leads to transmission of activating signals via the immunoreceptor tyrosine-based activation motif in the γ chain [38]. We also assessed osteoclastogenesis from the two monocyte subsets using IgG-depleted bovine serum. Even in the IgG-free medium, CD16- monocytes but not CD16+ monocytes differentiated into osteoclasts (data not shown). We could therefore exclude the possibility that signal transduction through CD16 inhibits osteoclastogenesis from CD16+ monocytes.\nNFATc1 is a key transcription factor in osteoclastogenesis [16]. In the present study, stimulation with M-CSF + RANKL increased the NFATc1 mRNA expression in the CD16- subset only, similar to integrin αv and integrin β3. The differences in NFATc1 induction might therefore also explain the difference in osteoclastogenesis between the two monocyte subsets. It is of interest that knockdown of integrin β3 did not lower the mRNA level of NFATc1. This result supports the notion that NFATc1 is located upstream of integrin-β3 expression [39]. It is also possible that parallel activation of two signaling pathways mediated by integrin β3 and NFATc1 contributes to osteoclastogenesis independently or cooperatively. Further studies are needed to determine the mechanisms of integrin β3 involvement in RANKL/RANK-mediated osteoclast differentiation.\nIt has been demonstrated that MAPK families, ERK and p38 MAPK, were activated by RANKL-induced intracellular signalings in osteoclasts and osteoclast precursors [18,19]. In addition, these kinases are involved in the differentiation of osteoclasts [20]. We showed that RANKL stimulation induced phosphorylation of ERK and p38 MAPK only in CD16- monocytes. It is suggested that differential activation of these kinases may partially explain the distinct properties of the two monocyte subsets upon RANKL stimulation.\nOur results showed that CD16+ monocytes produce higher levels of inflammatory cytokines including TNFα and IL-6 compared with CD16- monocytes. These results are consistent with the previous report showing that CD16+ monocytes produced larger amounts of TNFα upon lipopolysaccharide or lipopeptide stimulation than did CD16- monocytes [40]. Interestingly, we showed that stimulation either with RANKL or M-CSF upregulated the TNFα and IL-6 production by CD16+ monocytes. A marked increase of CD16+ monocytes in peripheral blood is reported in inflammatory diseases, such as infection, malignancy, Kawasaki disease and RA [41-44]. Taken together, CD16+ monocytes may be an important source of inflammatory cytokines.\nIn mice, peripheral blood Ly-6Chigh monocytes, which are thought to correspond to human CD16- monocytes, increase in inflammatory conditions, and these cells are recruited into sites of inflammation [45]. In contrast, Ly-6Clow monocytes, which are thought to correspond to human CD16+, migrate into noninflamed tissues [12]. These data on mouse monocytes seem to be in contrast to the data on human monocytes, which show expansion of CD16+ monocytes in inflammatory conditions where they produce larger amounts of inflammatory cytokines. At present, it is not clear whether mouse monocyte subsets, Ly-6Clow/Ly-6Chigh, represent human monocyte subsets, CD16+/CD16- monocytes, and whether the biologic functions of mouse monocytes are analogous to those of human monocytes.\nIn mice, blood monocytes newly released from the bone marrow are exclusively Ly-6Chigh and the level of Ly-6C is downregulated while in circulation [45]. It is thus suggested that in mice the two monocyte subsets differing in Ly-6C expression represent different stages in the maturation pathway. In the human, transition from CD16- monocytes to CD16+ monocytes is observed upon culture with IL-10, M-CSF and transforming growth factor beta in vitro [42,46]. Similar to mouse monocytes, therefore, human peripheral blood CD16- monocytes may also maturate into CD16+ monocytes.\nIt is reported that a significant number of RA synovial cells in the intima express CD16, suggesting that CD16+ cells are synovial macrophages [47]. We confirmed that both CD16+ and CD16- macrophages accumulate in the RA synovium by double-color immunohistochemical staining for CD68 and CD16. A number of chemokines are abundantly expressed in the RA synovium [24,48]. Among these cytokines, MCP-1, MIP-1α, SDF-1, RANTES and fractalkine can induce migration of CD16- monocytes in vitro ([11,12] and unpublished data). On the other hand, migration of CD16+ monocytes is induced only by fractalkine. These chemokines therefore seem to play an important role in recruitment of CD16+ and CD16- monocytes from the circulating pool into the RA synovium.\nThe osteoclast inducers are also produced in the RA synovium. RANKL is expressed by synovial fibroblasts and activated T cells [49-51], while M-CSF is expressed on RA synovial macrophages and fibroblasts [52,53].\nTNFα and IL-6, which are mainly expressed on RA synovial macrophages and fibroblasts, respectively, could also enhance osteoclast differentiation [54]. Collectively, it is probable that the recruited CD16- monocytes/macrophages differentiate into osteoclasts in the RA synovium, and contribute to bone destruction. On the other hand, CD16+ monocytes/macrophages might also be involved in RA pathogenesis by producing inflammatory cytokines including TNFα and IL-6. Since TNFα and IL-6 enhance osteoclast formation [54,55], CD16+ monocytes/macrophages may also contribute to osteoclastogenesis in RA synovium.\n\nConclusion\nWe have shown that human peripheral blood monocytes consist of two functionally heterogeneous subsets with distinct response to osteoclastogenic stimuli. Osteoclasts seem to originate from CD16- monocytes, and integrin β3 is necessary for the osteoclastogenesis. The blockade of accumulation and activation of CD16- monocytes could therefore be a beneficial approach as an anti-bone resorptive therapy, especially for RA.\n\nAbbreviations\nDAP = DNAX-activation protein; ELISA = enzyme-linked immunosorbent assay; FBS = fetal bovine serum; FcRγ = Fc receptor γ chain; IL = interleukin; FITC = fluorescein isothiocianate; mAb, monoclonal antibody; M-CSF = macrophage colony-stimulating factor; MEM = modified Eagle's medium; MMP = matrix metalloproteinase; MNC = multinucleated cells; NF = nuclear factor; OSCAR = osteoclast-associated receptor; PBS = phosphate-buffered saline; PCR = polymerase chain reaction; RA = rheumatoid arthritis; RANK = receptor activator of NF-κB; RANKL = receptor activator of NF-κB ligand; RT = reverse transcriptase; siRNA = small interfering RNA; SIRP-β1 = signal regulatory protein-β1; TNFα = tumor necrosis factor alpha; TRAF = tumor necrosis factor receptor-associated factor; TRAP = tartrate-resistant acid phosphatase; TREM = triggering receptor expressed on myeloid cells.\n\nCompeting interests\nThe authors declare that they have no competing interests.\n\nAuthors' contributions\nYK participated in the design of the study, carried out the experiments and statistical analysis, and drafted the manuscript. KH and KT participated in the design of the study and its coordination. TN and NM conceived of the study, participated in its design and coordination, and helped to draft the manuscript. All authors read and approved the final manuscript.\n\n\n" ], "offsets": [ [ 0, 39944 ] ] } ]

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2

pmcA2556924

[ { "id": "pmcA2556924__text", "type": "Article", "text": [ "Are there sensitive subgroups for the effects of airborne particles?\nAbstract\nRecent studies have shown that particulate air pollution is a risk factor for hospitalization for heart and lung disease; however, little is known about what subpopulations are most sensitive to this pollutant. We analyzed Medicare hospital admissions for heart disease, chronic obstructive pulmonary disorders (COPD) and pneumonia in Chicago, Cook County, Illinois, between 1985 and 1994. We examined whether previous admissions or secondary diagnoses for selected conditions predisposed persons to having a greater risk from air pollution. We also considered effect modification by age, sex, and race. We found that the air-pollution-associated increase in hospital admissions for cardiovascular diseases was almost doubled in subjects with concurrent respiratory infections. The risk was also increased by a previous admission for conduction disorders. For COPD and pneumonia admissions, diagnosis of conduction disorders or dysrhythmias increased the risk of particulate matter < 10 microm in aerodynamic diameter (PM(10))-associated admissions. Persons with asthma had twice the risk of a PM(10)-associated pneumonia admission and persons with heart failure had twice the risk of PM(10)-induced COPD admissions. The PM(10) effect did not vary by sex, age, and race. These results suggest that patients with acute respiratory infections or defects in the electrical control of the heart are a risk group for particulate matter effects.\nArticles \n\n Are There Sensitive Subgroups for the Effects of Airborne Particles? Antonella Zanobetti,1 Joel Schwartz,1,2 and Diane Gold1,2 1Environmental \n\n Epidemiology Program, Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA; 2Channing Laboratory, Department of Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston, Massachusetts, USA \n\n Recent studies have shown that particulate air pollution is a risk factor for hospitalization for heart and lung disease; however, little is known about what subpopulations are most sensitive to this pollutant. We analyzed Medicare hospital admissions for heart disease, chronic obstructive pulmonary disorders (COPD) and pneumonia in Chicago, Cook County, Illinois, between 1985 and 1994. We examined whether previous admissions or secondary diagnoses for selected conditions predisposed persons to having a greater risk from air pollution. We also considered effect modification by age, sex, and race. We found that the air-pollution-associated increase in hospital admissions for cardiovascular diseases was almost doubled in subjects with concurrent respiratory infections. The risk was also increased by a previous admission for conduction disorders. For COPD and pneumonia admissions, diagnosis of conduction disorders or dysrhythmias increased the risk of particulate matter < 10 �m in aerodynamic diameter (PM10)-associated admissions. Persons with asthma had twice the risk of a PM10-associated pneumonia admission and persons with heart failure had twice the risk of PM10-induced COPD admissions. The PM10 effect did not vary by sex, age, and race. These results suggest that patients with acute respiratory infections or defects in the electrical control of the heart are a risk group for particulate matter effects. Key words: effect modification, hospital admissions, particulate air pollution. Environ Health Perspect 108:841�845 (2000). [Online 28 July 2000] http://ehpnet1.niehs.nih.gov/docs/2000/108p841-845zanobetti/abstract.html \n\n Particulate air pollution has been associated with increases in daily deaths and hospital admissions in studies all over the world (1�15). These associations are now well documented but little is known, as yet, of the characteristics of persons that put them at increased risk of adverse events related to particulate air pollution. This has been identified as a key data gap (16). Schwartz and Dockery (17) reported that persons older than 65 years of age had a somewhat increased risk of death, and this has been confirmed in other studies (18). A more detailed examination of particulate matter-related risk by deciles of age (19) showed the risk beginning to increase at approximately 40 years of age and reaching its maximum for those 75 years of age and older. In addition to age, several studies suggest that persons with respiratory illness are at increased risk for cardiovascular effects associated with air pollution. An examination of death certificates on high- and low-air pollution days reported a substantial difference in the proportion of deaths from cardiovascular causes that had respiratory disease as a contributing cause of death (19). A recent follow-up study of a cohort of persons with chronic obstructive pulmonary disease (COPD) in Barcelona, Spain, found an association between particulate air pollution and all-cause mortality in the cohort (20). The magnitude of the risk per microgram per cubic meter of exposure was substantially greater than that for the general population. Environmental Health Perspectives \n\n Controlled exposure of animals with chronic bronchitis and control animals to concentrated air particles also demonstrated a potentiating effect of chronic lung disease in the response to airborne particles (21). This has led to the hypothesis that the cardiovascular effects of air pollution are predominantly in persons with chronic lung disease. There has been even less done to examine potential modifiers of the effects of airborne particles on hospital admissions. The existing literature on comorbidity shows that comorbidity per se seems to increase the risk of adverse outcomes (22�30). Little is known about the role of these comorbidities as effect modifiers for the effects of air pollution. This study uses data from the Medicare system to examine potential short-term and long-term medical conditions that may increase a person's risk of hospital admissions associated with particulate air pollution. In addition, we examine potential effect modification by age, race, and sex. \n\n Materials and Methods Health data. The Health Care Financing Administration (Baltimore, MD) maintains records of every hospital admission for Medicare participants in the United States. Persons in this database have a unique identifier. Using this identifier, we traced every hospital admission for heart and lung disease for each person in Cook County, Illinois, between 1985 and 1994. We chose Cook County because it is the most populous \n\n county in the United States with daily monitoring for particulate matter with aerodynamic diameter < 10 �m (PM10). The data were then analyzed to look at effect modification by concurrent and preexisting conditions as well as by age, race, and sex. To establish a baseline risk, we computed daily counts of hospital admissions for cardiovascular disease (CVD) [International Classification of Disease, 9th edition, World Health Organization, Geneva (ICD-9) code 390�429], pneumonia (ICD-9 code 480�487), and COPD (ICD-9 code 490�496, excluding 493). The association between these daily counts and PM10 was examined for the years 1988�1994, when daily PM10 monitoring data were available in Chicago. Once our baseline risks were established, we examined three classes of potential effect modifiers. First, we looked at whether previous admissions for selected conditions predisposed persons to having a greater risk from air pollution. For each of the three admission categories (CVD, pneumonia, and COPD), we considered 10 causes (defined by a previous admission) as effect modifiers: COPD (ICD-9 code 490�496 except 493), asthma (ICD-9 code 493), acute bronchitis (ICD-9 code 466), acute respiratory illness (ICD-9 code 460�466), pneumonia (ICD-9 code 480�487), CVD (ICD-9 code 390�429), myocardial infarction (ICD-9 code 410), congestive heart failure (ICD-9 code 428), conduction disorders (ICD-9 code 426), and dysrhythmias (ICD9 code 427). To test the hypothesis that persons with these conditions had higher risks of subsequent PM10-related admissions, we computed separate daily counts of admissions for our three target causes, stratified by whether or not the person admitted had been previously admitted for the hypothesized predisposing condition. Separate analyses were then performed within each strata to see if the effects of PM10 differed by strata. Address correspondence to A. Zanobetti, Department of Environmental Health, Environmental Epidemiology Program, Harvard School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA. Telephone: (617) 4324642. Fax: (617) 277-2382. E-mail: azanob@ sparc6a.harvard.edu Supported by NIEHS grant ES07937. Received 18 January 2000; accepted 18 April 2000. \n\n � VOLUME 108 | NUMBER 9 | September 2000 \n\n 841 \n\n \fArticles \n\n � \n\n Zanobetti et al. \n\n The second set of potential predisposing conditions included secondary diagnoses associated with the index admission. These could represent the presence of a chronic condition (e.g., COPD) that has not resulted in a previous hospital admission. They could also represent acute conditions that may have increased the subjects' sensitivity to air pollution. For example, if respiratory infections modified the effect of particulate matter on the cardiovascular health of persons with underlying heart disease, then the risk of a hospital admission for heart disease might be different in persons with infections. If this were true, then the risk ratio of a 10-�g/m3 increase of PM10 on cardiovascular admissions of persons with a concurrent respiratory infection would be different from the ratio in persons without respiratory infection. To test these hypotheses, we computed separate daily counts of admissions for events with and without the concurrent conditions hypothesized to increase sensitivity to air pollution. These were taken as the same 10 conditions in the first analysis with certain exclusions for pairing that would be illogical. That is, the concurrent diagnosis of a specific cardiac condition was not treated as an effect modifier for admissions for any cardiovascular condition. Likewise, pneumonia and COPD were not possible concurrent conditions for each other. The third set of predisposing conditions considered was being older than 75 years of age, nonwhite, and female. These were examined for all three outcomes. We obtained weather data for O'Hare Airport from the EarthInfo CD-ROM (EarthInfo CD NCDC Surface Airways, EarthInfo Inc., Boulder, CO), and we obtained air pollution data from the U.S. Environmental Protection Agency Aerometric Information Retrieval System network (31). \n\n running-line smoother, loess (35), was chosen to estimate the smooth function. To control for weather variables and day of the week, we chose the smoothing parameter that minimized the Akaike's information criterion (36). To model seasonality we chose the smoothing parameter that minimized the sum of the autocorrelation of the residuals while removing seasonal patterns. Two autoregressive terms (37) were added in the model to eliminate the remaining serial correlation from the residuals. We used the mean of PM10 on the day of the admission and the day before the admission as our exposure variable. This gives results that are similar to those obtained fitting a full distributed lag model (38). PM10 was treated linearly. Our baseline models used the daily counts of CVD, pneumonia, and COPD admissions as outcomes. We then subdivided those counts by the presence or absence of the potential effect modifier and reestimated our regressions on those subgroups. We considered effect modification to be indicated when the estimates of PM10 in the group with the condition was outside of the 95% confidence interval (CI) of the effect estimate in persons without the condition. \n\n Results Table 1 shows the mean daily admissions for COPD, cardiovascular, and pneumonia both overall and in the presence of the potential effect modifiers. For some effect modifiers such as conduction disorders or myocardial infarctions, the counts in conjunction with our respiratory outcomes are \n\n low, which limits power. In general, the numbers are lower for examining effect modification by previous admissions than for effect modification by concurrent diagnosis. This is as expected because many clinically relevant comorbidities may never have resulted in a hospital admission. Table 2 shows the 25th, 50th, and 75th percentile values for the environmental variables. The mean value for PM10 is 33 �g/m3. The daily values for PM10 were computed as the average of 10 monitors, two of which measured PM10 almost every day and the others less frequently (38). Table 3 shows the mean daily counts of CVD, COPD, and pneumonia by sex, age groups, and race. The distribution by sex is almost even, although the counts of admissions for males are generally lower (approximately 10%) than for females, particularly for cardiovascular diseases. The counts of CVD, COPD, and pneumonia admissions were similar for people 65�75 or 75 years of age and older. Tables 4�6 show the results for the effect PM10 overall and stratifying by concurrent diagnosis and previous admissions. These are expressed as the percentage increase for 10 �g/m3 PM10. Table 4 shows the results for CVD. A 10-�g/m3 increase in PM10 was associated with a 1.31% (5% CI, 0.97%; 95% CI, 1.66%) increase in hospital admissions for heart disease in all elderly persons. A concurrent (not previous) diagnosis of COPD modified the risk of PM10-associated admissions for heart disease. However, significant associations were still seen between PM10 \n\n Table 1. Mean daily counts of admissions, Chicago 1986�1994, for COPD, CVD, and pneumonia overall and by concurrent diagnosis and by previous admissions. By concurrent diagnosis COPD CVD Pneumonia Overall Respiratory disease Acute bronchitis Acute respiratory infections Pneumonia Asthma COPD Cardiovascular disease CVD Conduction disorders Cardiac dysrhythmias Congestive heart failure Myocardial infarction NA, not applicable. \n\n By previous admissions COPD CVD Pneumonia 7.8 0.8 0.9 1.6 0.9 2.7 2.1 0.0 0.4 0.9 0.3 102.1 1.6 1.8 7.3 1.5 2.0 54.7 1.0 9.9 24.2 11.4 26.5 0.9 1.0 6.4 0.7 1.4 7.2 0.2 1.5 3.1 1.0 \n\n Methods We analyzed the data with a generalized additive robust Poisson regression model (32). This approach has become the norm in such studies (14,33,34). In the generalized additive model the outcome is assumed to depend on a sum of nonparametric smooth functions for each variable that models the potential nonlinear dependence of daily admission on weather and season. The model is of the form: log[E(Yt)] = 0+ S1 (X1 )+... + Sp (Xp) where E(Yt) is the expected value of the daily count of admissions Yt and Si are the smooth functions of the covariates Xi. We examined temperature, previous day's temperature, relative humidity, barometric pressure, and day of week covariates. The locally weighted \n\n 7.8 0.1 0.3 0.4 0.1 NA 4.7 0.2 1.4 1.8 0.1 \n\n 102.1 0.9 1.3 4.0 1.8 13.4 NA NA NA NA NA \n\n 26.5 0.3 0.3 NA 0.9 6.9 14.7 0.6 4.6 7.3 0.4 \n\n Table 2. 25th, 50th, and 75th percentile values for the environmental variables in Chicago, 1988�1994. Temperature (�F) 35 51 67 Relative humidity 62 70 79 Barometric pressure 29.2 29.3 29.4 PM10 (�g/m3) 23 33 46 \n\n Table 3. Mean daily counts of admissions by sex, race, and age groups, Chicago, 1986�1994. Group Overall Female Nonwhite Age > 75 years COPD 7.8 4.2 1.6 3.7 CVD 102.1 59.4 21.0 55.1 Pneumonia 26.5 14.7 5.2 17.4 \n\n 842 \n\n VOLUME \n\n 108 | NUMBER 9 | September 2000 � Environmental Health Perspectives \n\n \fArticles \n\n � \n\n Effects of particles on sensitive subgroups \n\n and heart disease admissions in persons without COPD listed as either a comorbidity or a cause of previous admission (Table 4). A significant association was also seen in persons without any respiratory disease as a concurrent diagnosis, although the risk is much lower than in persons with respiratory disease. However, the risk associated with PM10 was roughly doubled in subjects with concurrent respiratory infections and the risk estimates in those subjects were outside the 95% CI of the risk in patients without concurrent respiratory infections. A previous admission for conduction disorders (e.g., heart block) increased the risk of a PM10-related subsequent admission for any heart condition, and a weaker indication of effect modification was seen for persons with previous admission for dysrhythmias. In contrast heart failure and previous myocardial infarctions were highly insignificant as effect modifiers. Table 5 shows the results for COPD. Overall, there is a 1.89% (95% CI, 0.8�3.0) increase in COPD admissions for a 10�g/m3 increase in PM10. The results of the stratified analysis suggest that preexisting heart disease modifies Table 4. Percentage increase in hospital admissions for CVD in all persons and by concurrent diagnosis and previous admissions. PM10 2.5% CI 97.5% CI All persons 1.31 By concurrent diagnosis Respiratory disease All respiratory disease With 1.65 Without 0.98 Acute bronchitis With 2.50 Without 1.07 Acute respiratory infections With 2.71 Without 1.06 Pneumonia With 1.95 Without 1.03 COPD With 1.59 Without 1.08 By previous admissions Respiratory disease All respiratory disease With 1.18 Without 1.08 COPD With 1.48 Without 1.09 Asthma With 1.71 Without 1.08 Cardiovascular disease Conduction disorders With 2.89 Without 1.07 Cardiac dyshrethmias With 1.61 Without 1.04 0.97 1.66 \n\n the risk of COPD admissions on high particle days. Previous admissions for any cardiovascular disease increased the risk of a PM10associated COPD admission approximately 2.5-fold. A previous heart failure admission caused an even more striking increase in the PM10 effect. Previous admissions for dysrhythmias and conduction defects were rare (Table 1) with no power to examine effect modifications. Listings as concurrent diagnoses were more common and here they joined heart failure in increasing the risk of PM 10 -associated COPD admissions. For COPD there was also some indication that concurrent pneumonia or an acute respiratory infection admission in the last year increased risk. The low numbers made these estimates less precise, however. The percentage increase in pneumonia admission (Table 6) for 10 �g/m3 PM10 is higher than for COPD or CVD with an increase of 2.34% (95% CI, 1.66�3.0). As with COPD, persons with heart disease appeared at higher risk of pneumonia hospital admissions associated with particulate air pollution. Here diagnoses suggestive of impaired autonomic control of the heart, such as conduction disorders or dysrhythmias, were associated with increased risk for PM 10 effects on pneumonia admissions. Unlike COPD, no difference was seen for congestive heart failure. Persons with asthma Table 5. Percentage increase in hospital admissions for COPD in all persons and by concurrent diagnosis and previous admissions. PM10 2.5% CI 97.5% CI All persons 1.89 By concurrent diagnosis Respiratory disease Pneumonia With 4.00 Without 1.51 Cardiovascular disease Conduction disorders With 2.34 Without 1.60 Cardiac dysrhythmias With 3.09 Without 1.43 Congestive heart failure With 2.90 Without 1.39 By previous admissions Respiratory disease Acute respiratory infections With 3.20 Without 1.70 Cardiovascular disease CVD With 2.90 Without 1.18 Congestive heart failure With 4.37 Without 1.14 Within 1 year 6.04 0.80 2.99 \n\n had twice the risk of a PM10-induced pneumonia admission as persons without asthma. Table 7 shows the results by sex, age, and race. None of the effect size estimates for any of the stratification variables were outside of the 95% CI for the opposite strata. There was a tendency for the effect of PM10 on CVD admissions to be higher for females, whereas the effect on pneumonia admissions was higher for males. In general, we found somewhat larger effects on whites compared to nonwhites, and for persons older than 75 years of age compared to younger persons. \n\n Discussion In this analysis we examined whether the effect of PM10 on the risk of hospital admission for heart and lung disease was different depending on the presence of comorbidities. We found that PM10 was associated with hospital admissions for all three causes (CVD, COPD, and pneumonia) and we found not a general increase in PM10 related risk with comorbidities, but a specific pattern that is suggestive of potential mechanisms and consistent with other recent epidemiologic and toxicologic findings. One major finding of this study is that preexisting cardiovascular disease, particularly impaired autonomic control (conduction defects and dysrhythmias) and heart failure, substantially increased the risk of respiratory admissions associated with airborne particles. In fact, recent human studies have shown that exposure to particulate air pollution is a risk factor for reduced heart rate variability (39�41). Reduced heart rate variability is an adverse response and a risk factor for arrhythmia. A new study of defibrillator discharges in patients with implanted cardioverter defibrillators found that discharges were associated with air pollution (42). Exposure to combustion Table 6. Percentage increase in hospital admissions for pneumonia in all persons and by concurrent diagnosis and previous admissions. PM10 All persons By concurrent diagnosis Respiratory disease Asthma With Without Cardiovascular disease Conduction disorders With Without Cardiac dysrhythmias With Without By previous admissions Cardiovascular disease Cardiac dysrhythmias With Without 2.34 2.5% CI 97.5% CI 1.66 3.02 \n\n 1.10 0.64 �0.47 0.76 0.18 0.76 0.55 0.72 0.85 0.75 \n\n 2.20 1.33 5.55 1.37 5.30 1.37 3.36 1.35 2.34 1.41 \n\n �0.45 0.47 �4.42 0.58 0.64 0.33 0.77 0.24 \n\n 8.65 2.57 9.59 2.64 5.60 2.55 5.08 2.55 \n\n 0.45 0.76 �0.40 0.78 �0.43 0.77 0.22 0.76 0.75 0.72 \n\n 1.91 1.41 3.40 1.40 3.89 1.39 5.63 1.38 2.48 1.36 \n\n 4.18 2.07 7.92 1.99 � � \n\n 1.01 1.46 4.28 1.37 � � \n\n 7.46 2.69 11.69 2.61 � � \n\n �1.38 0.66 0.99 �0.01 1.43 0.05 2.10 \n\n 8.01 2.76 4.85 2.39 7.40 2.24 10.14 \n\n 3.47 2.08 \n\n 1.21 1.45 \n\n 5.79 2.71 \n\n Increases are for a 10-�g/m3 increase in PM10. \n\n Increases are for a 10-�g/m3 increase in PM10. \n\n Increases are for a 10-�g/m3 increase in PM10. \n\n Environmental Health Perspectives \n\n � VOLUME 108 | NUMBER 9 | September 2000 \n\n 843 \n\n \fArticles \n\n � \n\n Zanobetti et al. \n\n Table 7. Effect modification by sex, race, and age groups for 10 �g/m3 PM10. % All persons Male Female White Non-white Age > 75 Age 75 1.89 1.34 2.19 1.65 1.07 2.20 1.33 COPD (95% CI) (0.80, 2.99) (�0.14, 2.84) (0.81, 3.59) (0.51, 2.81) (�1.11, 3.3) (0.72, 3.69) (0.03, 2.65) % 1.31 1.07 1.21 1.20 0.70 1.28 0.93 CVD (95% CI) (0.97, 1.66) (0.62, 1.51) (0.83, 1.6) (0.86, 1.55) (0.1, 1.3) (0.88, 1.69) (0.51, 1.35) % 2.34 2.65 1.91 2.45 1.91 2.12 2.52 Pneumonia (95% CI) (1.66, 3.02) (1.81, 3.5) (1.11, 2.72) (1.77, 3.14) (0.69, 3.14) (1.38, 2.86) (1.57, 3.48) \n\n Figures shown are the percentage increase in admissions (95% CI). \n\n particles has also been associated with arrhythmia in an animal model (43) and changes in ST segments have been noted as well (44). This is the first study to suggest persons with defects in the electrical control of the heart are also at higher risk of respiratory illness after exposure to airborne particles. These data also suggest that persons admitted to hospitals for pneumonia during an air pollution episode may be at high risk for clinically significant conduction disorders during that hospital admission. Patients with congestive heart failure were at greater risk of hospital admissions for COPD in association with airborne particles. Heart failure and COPD is not an uncommon combination. The finding that these patients are at higher risk for admissions associated with particulate air pollution is new but is also consistent with several other recent reports. The spontaneous hypertensive rat develops a model of heart failure, and recent studies have reported greater sensitivity to particulate air pollution in these rats. These include both electrocardiogram abnormalities (44) and pulmonary toxicity (45,46). Similarly, in an epidemiologic study, Hoek et al. (47), found a higher relative risk of death with an increase in PM10 for congestive heart failure deaths than other deaths. The potential role of COPD in those heart failure deaths was not examined. Another consistent pattern in our data is of acute respiratory infections increasing susceptibility to airborne particles. Acute bronchitis, or more generally acute upper respiratory illnesses, as well as pneumonia, increased susceptibility to particle-associated admissions for CVD and COPD. The notion that air pollution exacerbates acute respiratory infections is well supported by studies which report associations between airborne particles and hospital admissions for respiratory infections (48,49). Zelikoff et al. (50) exposed rats infected with streptococcus to concentrated air particles and reported a significant increase in bacterial burdens and in the extent of pneumonia compared to animals exposed to filtrated air. This suggests an impaired immune response. Similarly, exposure to combustion \n\n particles enhances influenza infections in mice (51). An impaired defense to respiratory infection is a major reason that persons with COPD require hospital admission. If airborne particles result in further impairment the effect modification we observe makes good sense. The effect modification for heart disease admissions is more relevant. This modification is consistent with the earlier report of Schwartz (19), who found greater reports of respiratory complications on death certificates with an underlying cause of heart disease if the death occurred on a day with high levels of airborne particles. Although airborne particle exposure has been associated with increased exacerbation of asthma (2,12,48,52�59), this paper is the first to suggest that asthmatics are more susceptible to PM10-induced pneumonia exacerbation or to cardiovascular effects. The effects on pneumonia admissions are plausible, given the impaired ability to fight off infections in asthmatics with mucus plugs and the evidence the airborne particles impair the lungs' ability to fight off bacterial and viral infections, as noted earlier. The increased cardiovascular sensitivity, albeit weaker, is interesting. If airborne particles affect the cardiovascular system via the role of the lung in autonomic control, it is possible that asthmatics would be more sensitive to those effects. Animal models of asthma showed that combustion particles enhance the asthmatic response to aeroallergen challenges (59). This suggests an enhancement of pulmonary response in asthmatics. On the other hand, the diagnosis of asthma is problematic in the elderly, and crossover with COPD is possible. The possibility that this explains our results is reduced by our failure to find previous hospital admission for COPD was an effect modifier for the effect of particles on cardiovascular admissions. We must acknowledge several potential limitations of this study. First, we considered only previous admissions that occurred within Cook County. Hence persons with previous admissions elsewhere would be misclassified to our reference group. The effect of this would be to reduce the difference in PM 10 effect between the two groups. VOLUME \n\n Nevertheless, we identified some interesting interactions. We cannot exclude the possibility that there are areas we missed for this reason. We also examined interactions in a log relative risk model, which is inherently multiplicative. Although we believe this is justified because doubling the population exposed would be expected to double the pollution associated admissions, it results in a more conservative definition of interaction than would an additive risk model. Finally, our exposure is clearly measured with error. Most of this error is Berkson error (60) and hence will introduce no bias, and Zeger et al. (60) showed that the remaining error would have to have pathologic correlations with other variables to result in an upward bias. Another important result from this study, of course, is an estimate of the magnitude of the effect of airborne particles on public health. The PM10 concentrations in Chicago during this period were associated with approximately 1,600 additional admissions per year for heart disease, 740 additional admissions per year for pneumonia, and 170 additional admissions per year for COPD. These are not trivial increases in serious morbidity. 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3

pmcA1474674

[ { "id": "pmcA1474674__text", "type": "Article", "text": [ "Physiological and chemical characterization of cyanobacterial metallothioneins.\nAbstract\nTechniques have been developed for detection, quantitation, and isolation of bacterial metallothioneins (MTs) from cyanobacterial species. These methods involve differential pulse polarography and reverse-phase high-performance liquid chromatography (HPLC) and have allowed detection of picomole quantities of these high sulfhydryl content proteins. The prokaryotic molecule was found to be induced in the presence of Cd or Zn salts with regulation at the level of transcription. Cu was not found to induce synthesis of the prokaryotic MT. Exposure to the former metals resulted in a growth lag followed by simultaneous induction of MT synthesis and onset of growth. Amino acid analysis and N-terminal sequence analysis indicated that the bacterial MTs from cyanobacteria are unique, having many aromatic and aliphatic residues and no apparent association of hydroxylated or basic amino acids with cysteines. Although the characteristic Cys-X-Cys sequences were present, no apparent amino acid sequence homology with the eukaryotic MTs was found in the first 42 residues.\n\n\n\n\n Environmental Health Perspectives Vol. 65, pp. 71-75, 1986 \n\n Physiological and Chemical \n\n Characterization of Cyanobacterial Metallothioneins \n\n by Robert W. Olafson* \n\n Techniques have been developed for detection, quantitation, and isolation of bacterial metallothioneins (MTs) from cyanobacterial species. These methods involve differential pulse polarography and reverse-phase high-performance liquid chromatography (HPLC) and have allowed detection of picomole quantities of these high sulfhydryl content proteins. The prokaryotic molecule was found to be induced in the presence of Cd or Zn salts with regulation at the level of transcription. Cu was not found to induce synthesis of the prokaryotic MT. Exposure to the former metals resulted in a growth lag followed by simultaneous induction of MT synthesis and onset of growth. Amino acid analysis and N-terminal sequence analysis indicated that the bacterial MTs from cyanobacteria are unique, having many aromatic and aliphatic residues and no apparent association of hydroxylated or basic amino acids with cysteines. Although the characteristic CysX-Cys sequences were present, no apparent amino acid sequence homology with the eukaryotic MTs was found in the first 42 residues. \n\n Introduction \n\n Metallothioneins have now been isolated and characterized from a large variety of eukaryotic organisms (1) and shown to be involved in heavy metal detoxification and/or homeostasis (2-4). These proteins are highly homologous with respect to amino acid sequence and complex metals in characteristic metal-thiolate cluster arrangements, the structures of which have been recently \n\n investigated by 113Cd-NMR (6). \n\n Although metallothionein (MT) is found throughout the eukaryotic world, few reports of the presence of this type of high sulfhydryl content metal-binding protein exist for prokaryotes. We earlier reported the presence of a prokaryotic MT in cyanobacteria (7,8) and have recently provided primary sequence evidence substantiating these data. This manuscript is intended to summarize the present state of knowledge regarding the physiological and chemical characterization of these bacterial MTs, with an emphasis on the techniques employed in such studies. \n\n Analytical Procedure \n\n In order to facilitate rapid detection, isolation, and quantitation of MT from various sources, we have routinely employed a differential pulse polarographic tech\n\n *Department of Biochemistry and Microbiology, University of Victoria, Victoria, British Columbia V8W 2Y2, Canada. \n\n nique first described by Brdicka (9-11). This procedure avoids use of radioisotopes and circumvents problems such as species specificity and metal stoichiometric assumptions associated with radioimmunoassays and metal binding assays. Figure 1 shows a typical polarographic wave for MT using the Brdicka procedure. Measurement of the wave height can be performed from either the \n\n 0.20\n\n glJ MT-1 \n\n O 0.15\n\n E \n\n 0 0.10 0 \n\n E 0.05 _ _ \n\n -1.35 -1.45 -1.55 -1.65 \n\n V vs Agt/AgC1 \n\n FIGURE 1. Differential pulse polarographic wave for murine MT-1. \n\n Wave heights were calculated from the broken tangent line between minima rather than the supporting electrolyte baseline at the bottom of the figure. \n\n R. W OLAFSON \n\n supporting electrolyte baseline or a tangent to the minima as shown in the preceding figure. In the cobalt hexaminechloride supporting electrolyte, the half-wave potential for all MTs studied to date is approximately -1.45 V versus a Ag/AgCl reference electrode. This electrochemical reaction results in highly reproducible and linear current responses which can be used with samples containing picomole levels of MT (Fig. 2). Since this is an exceedingly sensitive instrument, attention to detail is particularly important for successful use of the Brdicka procedure (11). Routine use of a reference standard MT is highly recommended to compensate for small day-today variations in response. For absolute values, standards must be identical to the species of protein quantitated; otherwise commercially available standard is adequate. Although certain tissues and cellular types can be shown to have no other polarographically active material other than MT, with samples from new species, it is necessary to evaluate this potential problem by gelperneation chromatography and, if necessary, take steps to remove contaminants before assaying. In most cases, \n\n 0 \n\n E i \n\n m 0 \n\n 0 E \n\n 0.31 \n\n 0.11 \n\n O 0.1 0.3 0.5 \n\n MT (nanomoles) \n\n FIGURE 2. Standard curve for polarographic determination of me\n\n tallothionein. \n\n FIGURE 3. Cyclic voltamogram obtained by equilibration at -1.0 V \n\n for 4 min followed by cyclic scanning to OV and -1.4 V at a scan rate of 200 mV/sec with a PAR Model 303 static mercury drop electrode in the hanging drop mode. The mercury drop electrode was set in the large drop position producing a drop of 0.0226 cm3. The supporting electrolyte was 20 mM HEPES buffer, pH 7.3. The dotted line is the equilibrium trace. Adapted Olafson and Sim (10). \n\n this is easily managed by heat denaturation, if care is taken to assess the degree of MT losses due to coprecipitation. Such losses later can usually be minimized to less than 10% by adjustment of the tissue homogenate density prior to denaturation. \n\n It should be indicated that additional utility can be found with a polarographic analyzer beyond application of the Brdicka procedure. For example, metal levels can be readily determined by using differential pulse or anodic stripping voltametry procedures (10), while Figure 3 shows a cyclic voltamogram of bacterial MT. The latter technique is potentially useful in assessing metal speciation and integrity of the protein tertiary structure near metal clusters, particularly after metal reconstitution studies. \n\n E \n\n 'C2A- E 24 \n\n 0 30 40 E0 \n\n *~~~~~~~~~~~~ \n\n o C~~~~~~~~~~~~~~~~~~~~C \n\n Fraction Number (18ml) \n\n FIGURE 4. Sephadex G-75 chromatography profile of bacterial cell \n\n lysate applied to a 5 x 100 cm column and eluted with 10 mM anunoium bicarbonate, 5 mM mercaptoethanol (7). \n\n Elution Time (min) \n\n FIGURE 5. Reverse-phase high-performance chromatography profile \n\n of Sephadex G-75 fractionated bacterial MT. The 300 A pore size propyl column was eluted with 20 mM triethylamine phosphate, pH 7.0, by using an acetonitrile organic modifier (phase B). Column effluent was monitored at 250 nm with a sensitivity of 1.0 AUFS (12). \n\n 72 \n\n CYANOBACTERIAL METALLOTHIONEINS \n\n Isolation of Cyanobacterial MT \n\n Synechococcus strain Tx-20 cyanobacteria were maintained in axenic culture on BG-11 medium (7) and harvested from aerated 20 L cultures grown at 280C under fluorescent light. Cells were broken in a French pressure cell at 0?C in 0.5 M Tris-HCI, pH 8.6, and the lysate exposed to 10 ,uCi of 109CdCl. The 40,000g supernatant was applied to a Sephadex G-75 column developed with 10 mM ammonium bicarbonate and 5 mM mercaptoethanol resulting in the profile shown in Figure 4. Polarographic activity and radionuclide binding were coincident with a 10,000 MW ultraviolet absorbing fraction. Further purification of this material could be undertaken by DEAE-cellulose chromatography or isoelectric focusing but maximum resolution of isoproteins was best attained by reverse-phase high-performance liquid chromatogra\n\n 0 5 \n\n DAYS \n\n I0 \n\n 5 \n\n phy. Figure 5 shows such a separation performed on a 300 A pore size C-3 column (Beckman Instruments). Four baseline resolved MT peaks appear between 40 and 70 min. Peaks eluting at 80 min contain at least four additional MT components resolvable by adjustment of the applied organic modifier ramp. Preliminary evidence indicates that these isoproteins are microheterogeneous with respect to both amino acid composition and metal speciation resulting in the observed reverse-phase separation. \n\n Physiological Characteristics of Cyanobacterial MT \n\n Using the Brdicka polarographic procedure, it is possible to measure basal MT levels in Synechococcus strain \n\n 5 \n\n DAYS \n\n 10 \n\n 15 \n\n FIGURE 6. Cell numbers and MT concentrations as a function of time after inoculation of wild-type cyanobacteria in the presence and absence \n\n of (A) 22.5 ,uM CdCl2; (B) control; (C) 50 ,uM ZnSO4; (D) 50 ,uM CuCl2 (8). \n\n 73 \n\n 74 ~~~~~~~~~~R. W OLAFSON \n\n Table 1. Amino acid compositions of cyanobacterial \n\n metallothioneins compared with eukaryotic metallothioneins. \n\n Nearest integer residues per molecule Human (MT-2) Crab (MT-2) Tx-20t CysA 20 18 9.5 Asx 4 6 5.7 Thr 2 3 4.8 Ser 8 5 3.8 Glx 2 5 2.0 Gly 5 3 8.0 Ala 7 1 4.0 Val 1 - 2.3 Met 1 - \n\n Ile 1 -1.1 \n\n Leu Tyr Phe His Lys Arg Pro \n\n 8 2 \n\n 8 2 6 \n\n 2.9 2.3 \n\n 2.8 2.6 1.0 1.9 \n\n RRIMP NI cells cultured in the absence of added metal, as shown in Figure 6B (8). Comparison with cultures exposed to cadmium chloride (Fig. 6A) or zinc sulfate (Fig. 6C) showed that introduction of metal salts resulted in a growth lag and that resumption of growth occurred coincident with an increase in cellular levels of MT. In addition, it should be noted that, like mammalian MT, cadmium appears to be a more potent inducer than zinc. Twice as much cadmium-thionein was synthesized on exposure to half as much metal as was used in the zinc induction experiment. A further interesting finding was that copper exposure resulted in an even greater growth lag than observed with cadmium, but on resumption of growth in the presence copper, MT synthesis was not noted (Fig. 6D). Recent results suggest that this copper resistance is manifest via a membrane exclusion mechanism (unpublished results). \n\n HOURS \n\n FIGURE 7. Inhibition of cadmium induced synthesis by actinomycin \n\n D (hatched bar) and chloramphenicol (solid bar). Control cells are shown by unmarked bars. \n\n In order that the level of regulation of metal induction be determined for cyanobacteria, logarithmically growing cultures were exposed to cadmium and MT concentrations measured at several time intervals thereafter. Two cultures were exposed to either chloramphenicol or actinomycin D 30 min prior to introduction of metal, while a third culture was used as a control. The results of this experiment are shown in Figure 7 and indicate induction at the level of transcription, as was found in eukaryotic organisms. \n\n The assumption at this stage in these investigations was that the growth lag observed in cultures exposed to \n\n Table 2. Amino acid sequence analysis. \n\n Amino acid \n\n 1 10 20 30 Cyanobacteria T S T T L V K C A C E P C L C N V D P S K A I D R N G L Y Y Scylla P DP C C NDK C DC K EG EC KT GC K CT S C Human Ac MD P NC S C AA G DS CT C AG S C KC KE C KC T S C \n\n Neurospora \n\n G D C G C S G A S S C N C G S G C S C S N \n\n C G S K \n\n Table 2. Continued. \n\n Amino acid \n\n 40 50 60 C C EAC A H GHT G G \n\n R CP PC EQ C S SGC K CA NK E DC RK TC SK PC SCC P K K SCC S CCP V GC A KCA Q BC I C K GA SDK C S CC A \n\n 74 \n\n I \n\n II \n\n I I \n\n CYANOBACTERIAL METALLOTHIONEINS 75 \n\n cadmium or zinc was due to a rather protracted time of MT induction, perhaps associated with toxic burden. If the above cadmium-resistant cells were transferred into fresh media in the absence of cadmium and allowed to grow up between three successive transfers, levels of MT dropped to near basal values as synthesis was repressed in the absence of metal. However, when these cells were now transferred into cadmium-containing media, instead of the predicted growth lag, they grew immediately. Thus, these cells were truly cadmium resistant. Since 50 tubes of wild-type cells at a dilution of 104 grew, after the usual lag on exposure to cadmium-containing media, the acquisition of cadmium resistance in this strain of Synechococcus was therefore considered unlikely to be related to a chromosomal mutational event. Such a mutation frequency would be unreasonably high. Although no direct evidence exists at this time, this metal resistance phenomenon is best explained by the amplification of an extrachromosomal gene, especially since this strain is known to have plasmids. \n\n Structure of Cyanobacterial MT \n\n The structural determination of cyanobacterial MT is not yet complete, although a substantial amount of information is now known. For example, Table 1 compares the amino acid composition of a Synechococcus TX-20 isoprotein with two eukaryotic MTs. These data indicate that the bacterial form is unique. While cysteine was still the predominant amino acid in this protein, levels of the amino acid were half that seen in the eukaryotes. In addition, the bacterial protein had two tyrosines, three histidines, and five long-chain aliphatics-all residues rarely found in eukaryotic MTs. Thus, the amino acid composition indicates that prokaryotic MTs are not as structurally homologous with eukaryotes as they are physiologically homologous. This was further exemplified on amino terminal amino acid sequence analysis (12). With the exception of the typical Cys-X-Cys sequences, the first 42 residues of the prokaryotic MT were essentially without homology on comparison with the crab (Scylla), human, or Neurospora crassa MTs (Table 2). Of the above-mentioned uncommon MT residues, two tyrosines were found together in positions 29 and 30, all five of the long-chain aliphatic amino acids were located in the first 28 residues, and two histidines were situated at positions 37 and 39. Perhaps of greater interest was the complete lack of association of basic residues or hydroxylated residues with cysteines, as is found in eukaryotes (11). Instead, a block of four hydroxylated amino acids was found at the amino terminus. \n\n The sequence of this unique MT is now nearing completion, opening the way for an X-ray crystallographic investigation. However, the degree of similarity between the metal cluster arrangement of these bacterial molecules with the eukaryotic structures will initially be undertaken spectroscopically. Reliable interpretation of the 113Cd-NMR data for this molecule will be dependent upon adequate isolation of isoproteins using RP-HPLC and assessment of conformational integrity of metal reconstituted molecules, using procedures such as cyclic voltametry. Studies along these lines are presently underway in this laboratory \n\n The author gratefully acknowledges the financial support of the Australian Institute of Marine Science and the National Science and Engineering Research Council of Canada. Excellent technical assistance was provided by R. G. Sim and S. Kielland in carrying out the polarographic and sequence analyses, respectively. \n\n REFERENCES \n\n 1. Kagi, J. H. R., and Nordberg, M. (Eds.). Metallothionein. Birk\n\n hauser Verlag, Basel, 1979, pp. 5-55. \n\n 2. Olafson, R. W Differential pulse polarographic determination of \n\n murine metallothionein induction kinetics. J. Biol. Chem. 256:12631268 (1981). \n\n 3. Olafson, R. W Intestinal metallothionein: effect of parenteral and \n\n enteral zinc exposure on tissue levels of mice on controlled zinc diets. J. Nutr. 113: 268-275 (1983). \n\n 4. McCarter, J.A., and Roch, M. Chronic exposure of Coho salmon \n\n to sublethal concentrations of copper. III. Kinetics of metabolism of metallothionein. Comp. Biochem. Physiol. 77C: 83-87 (1984). \n\n 5. Lerch, K., Ammer, D., and Olafson, R. W Crab metallothionein\n\n primary structures of metallothioneins 1 and 2. J. Biol. Chem. 257: 2420-2426 (1982). \n\n 6. Otvos, J. D., Olafson, R.W, and Armitage, I. M. Structure of an \n\n invertebrate metallothionein from Scylla serrata. J. Biol. Chem. 257: 2427-2431 (1982). \n\n 7. Olafson, R. W, Abel, K., and Sim, R. G. Prokaryotic metallothi\n\n onein: preliminary characteristics of a blue-green alga heavy metalbinding protein. Biochem. Biophys. Res. Commun. 89: 36-40 (1979). 8. Olafson, R. W, Loya, S., and Sim, R. G. Physiological parameters \n\n of prokaryotic metallothionein induction. Biochem. Biophys. Res. Commun. 95: 1495-1503 (1980). \n\n 9. Brdicka, R. Pblarographic studies with the dropping mercury ka\n\n thode.-Part XXXI.-A new test for proteins in the presence of cobalt salts in ammoniacal solutions of ammonium chloride. Collect. Czech. Chem. Commun. 5: 112-128 (1933). \n\n 10. Olafson, R. W, and Sim, R. G. An electrochemical approach to \n\n quantitation and characterization of metallothionein. Anal. Biochem. 100: 343-351 (1979). \n\n 11. Olafson, R. W Differential pulse polarographic determination of \n\n murine metallothionein induction kinetics. J. Biol. Chem. 256: 12631268 (1981). \n\n 12. Olafson, R. W Prokaryotic metallothionein: amino terminal se\n\n quence analysis of a unique metallothionein. Int. J. Peptide Protein Res. 24: 303-308 (1984). " ], "offsets": [ [ 0, 18513 ] ] } ]

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