Comprehensive proteomic analysis of mineral nanoparticles derived from human body fluids and analyzed by liquid chromatography–tandem mass spectrometry

Analytical Biochemistry 418 (2011) 111–125

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Comprehensive proteomic analysis of mineral nanoparticles derived from human body fluids and analyzed by liquid chromatography–tandem mass spectrometry Jan Martel a,b,c,1, David Young a,d,1, Andrew Young a,1, Cheng-Yeu Wu a,c,e, Chi-De Chen b,f, Jau-Song Yu f,g, John D. Young a,c,h,i,⇑ a

Laboratory of Nanomaterials, Chang Gung University, Gueishan, Taoyuan 333, Taiwan, ROC Graduate Institute of Biomedical Sciences, Chang Gung University, Gueishan, Taoyuan 333, Taiwan, ROC c Center for Molecular and Clinical Immunology, Chang Gung University, Gueishan, Taoyuan 333, Taiwan, ROC d Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA e Research Center of Bacterial Pathogenesis, Chang Gung University, Gueishan, Taoyuan 333, Taiwan, ROC f Proteomics Core Laboratory, Chang Gung University, Gueishan, Taoyuan 333, Taiwan, ROC g Department of Cell and Molecular Biology, Chang Gung University, Gueishan, Taoyuan 333, Taiwan, ROC h Laboratory of Cellular Physiology and Immunology, Rockefeller University, New York, NY 10021, USA i Biochemical Engineering Research Center, Mingchi University of Technology, Taishan, Taipei 24301, Taiwan, ROC b

a r t i c l e

i n f o

Article history: Received 28 April 2011 Received in revised form 9 May 2011 Accepted 16 June 2011 Available online 22 June 2011 Keywords: Ectopic calcification LC–MS/MS Mineral nanoparticles Proteomics Protein corona

a b s t r a c t Mineralo-protein nanoparticles (NPs) formed spontaneously in the body have been associated with ectopic calcifications seen in atherosclerosis, chronic degenerative diseases, and kidney stone formation. Synthetic NPs are also known to become coated with proteins when they come in contact with body fluids. Identifying the proteins found in NPs should help unravel how NPs are formed in the body and how NPs in general, be they synthetic or naturally formed, interact within the body. Here, we developed a proteomic approach based on liquid chromatography (LC) and tandem mass spectrometry (MS/MS) to determine the protein composition of carbonate-apatite NPs derived from human body fluids (serum, urine, cerebrospinal fluid, ascites, pleural effusion, and synovial fluid). LC–MS/MS provided not only an efficient and comprehensive determination of the protein constituents, but also a semiquantitative ranking of the identified proteins. Notably, the identified NP proteins mirrored the protein composition of the contacting body fluids, with albumin, fetuin-A, complement C3, a-1-antitrypsin, prothrombin, and apolipoproteins A1 and B-100 being consistently associated with the particles. Since several coagulation factors, calcification inhibitors, complement proteins, immune regulators, protease inhibitors, and lipid/molecule carriers can all become NP constituents, our results suggest that mineralo-protein complexes may interface with distinct biochemical pathways in the body depending on their protein composition. We propose that LC–MS/MS be used to characterize proteins found in both synthetic and natural NPs. Ó 2011 Elsevier Inc. All rights reserved.

From a nanoengineering/nanotechnology perspective, understanding how nanoparticles (NPs) are formed and how they interact with biological tissues is of paramount importance [1].

⇑ Corresponding author. Address: Laboratory of Nanomaterials, Chang Gung University, 259 Wen-Hwa First Road, Gueishan, Taoyuan 333, Taiwan, ROC. Fax: +886 3211 8534. E-mail address: [email protected] (J.D. Young). 1 These authors contributed equally to this work. 0003-2697/$ - see front matter Ó 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.ab.2011.06.018

Synthetic NPs2 of known chemical composition have been increasingly studied in the context of their interaction with 2 Abbreviations used: ACN, acetonitrile; AMBP, a-1-microglobulin/bikunin; apo-A1, apolipoprotein A1; BSA, bovine serum albumin; Cov, coverage; CPPs, calciprotein particles; CSF, cerebrospinal fluid; DMEM, Dulbecco’s modified Eagle’s medium; DTT, dithiothreitol; EDTA, ethylenediaminetetraacetic acid; EDX, energy-dispersive X-ray spectroscopy; emPAI, exponentially modified protein abundance index; FBS, fetal bovine serum; FDR, false-discovery rate; HDL, high-density lipoproteins; HS, human serum; HSA, human serum albumin; i.d., internal diameter; Ig, immunoglobulin; IPI, International Protein Index; LC, liquid chromatography; LDL, low-density lipoproteins; MALDI-TOF, matrix-assisted laser desorption/ionization-time-of-flight; MS, mass spectrometry; MS/MS, tandem mass spectrometry; MW, molecular weight; NB, nanobacteria; NPs, nanoparticles; PE, pleural effusion; PTGDS, prostaglandin-H2 D-isomerase; SAP, serum amyloid protein; SBP1, complement cofactor protein-1; SDS–PAGE, sodium dodecyl sulfate–polyacrylamide gel electrophoresis; SF, synovial fluid; VDBP, vitamin D-binding protein.

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biological fluids and tissues [2,3]. Our own work [4–9] has demonstrated that spontaneously formed NPs are in fact found throughout nature and that they explain in their entirety the earlier spurious phenomenology represented by the so-called nanobacteria (NB)— microorganisms that are supposedly exotic, slow growing, and pleomorphic and that had earlier been associated with various humans diseases, including cancer, atherosclerosis, ectopic calcification, and kidney stone formation [10–12]. While our work disproves the NB hypothesis, we have found that nonliving mineralo-organic complexes in the form of NPs are present ubiquitously in various human body fluids and may constitute precursors of ectopic calcification and disease processes [4–9]. One important attribute common to both chemically synthesized and naturally found or spontaneously formed NPs found in the body is the propensity for proteins to coat these particles. Proteins bind strongly to synthetic NPs introduced into the body, forming a so-called ‘‘protein corona’’ [13–15]. Likewise, NPs spontaneously formed in body fluids associate with well-defined proteins originating probably from the particle-assembling fluid under study [4–9]. Understanding the protein composition of NPs as well as its underlying dynamics of change may be critical to our assessment of the biological activity, biodistribution, and clearance of NPs [13–16]. That is, proteins (along with other organic moieties) may very well confer biological specificity to NPs as well as determine their final localization and fate [9,15]. While the protein corona of various NPs has been described in the past [17], all previous studies made use of protein separations through gel electrophoresis prior to protein identification, an approach that is not only tedious but is likely to reveal at best a partial view of the protein corona under study. There is even less information regarding the protein coating of NPs that form spontaneously in the body or that persist naturally in the environment. There is thus the need for more efficient, comprehensive, and quantitative strategies to study protein–mineral interactions and NPs in general. We have developed an efficient and comprehensive proteomicsbased method to decipher the protein composition of carbonateapatite NPs based on in-solution trypsin digestion, liquid chromatography (LC), and tandem mass spectrometry (MS/MS)—a method that, to our knowledge, has not been used earlier to study the protein composition of NPs. Our analysis reveals a wide repertoire of mineral-interacting proteins as well as relevant information on how mineralo-protein NPs are spontaneously formed in the body. The proteomic analysis described in this study should be generally applicable to all NPs exposed to body fluids or proteins. Materials and methods Preparation of apatite NPs The use of human samples in the present study was approved by the Institutional Review Board of Chang Gung Memorial Hospital (Gueishan, Taiwan, Republic of China). Written informed consent was obtained from all volunteers. Human blood was obtained from healthy volunteers and serum was prepared as before [8]. Human serum (HS) and commercially available fetal bovine serum (FBS) (Biological Industries, Kibbutz Beit Haemek, Israel) were sterilized by successive filtrations through 0.2- and 0.1-lm filters (Pall Corporation, Ann Arbor, MI, USA). Urine was obtained from either healthy human volunteers or proteinuric patients while cerebrospinal fluid (CSF), ascites, pleural effusion (PE), and synovial fluid (SF) were collected from patients with various clinical conditions [5]. Urine proteins from healthy individuals were concentrated by using a centrifugal filter device with a molecular weight cutoff of 30 kDa (Millipore, Billerica, MA, USA). Apatite NPs were prepared in a final volume of 1 ml by adding both CaCl2 and NaH2PO4 at a final concentration of 3 mM each to

Dulbecco’s modified Eagle’s medium (DMEM; Gibco, Carlsbad, CA, USA) containing a body fluid at a concentration of 10% (v/v). The suspensions were incubated with end-to-end agitation for 2 h at room temperature. In addition, apatite NPs were obtained by culturing FBS and proteinuric urine under cell culture conditions for 1 month at 10% (v/v) each in DMEM, followed by centrifugation at 16,000g, two washes with DMEM, and resuspension in 50 ll of either 50 mM ethylenediaminetetraacetic acid (EDTA) (Sigma, St. Louis, MO, USA) or water [8]. Serum granules were obtained by incubating filtered HS or FBS (38 ml) with agitation overnight at room temperature, followed by ultracentrifugation at 140,000g at 4 °C for 2 h and washing steps [6]. Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS– PAGE) Apatite NPs resuspended in 50 mM EDTA were processed for gel electrophoresis under denaturing and reducing conditions [5]. For the gels shown in Figs. 3 and 4A, 14 ll of each NP sample was mixed with 2 ll of water and 4 ll of ‘‘loading buffer’’ (0.313 M Tris-HCl, pH 6.8, 10% SDS, 0.05% bromophenol blue, 50% glycerol, 12.5% b-mercaptoethanol). In-gel trypsin digestion and proteomics analysis The in-gel proteomics approach was performed as described [5]. Briefly, protein spots from Coomassie-blue-stained SDS–PAGE gels were excised with sterile truncated 200-ml pipette tips. Proteins were reduced with a solution of 25 mM NH4HCO3 containing 10 mM DTT at 56 °C for 45 min. Protein alkylation was done in 25 mM NH4HCO3 containing 55 mM iodoacetamide at room temperature for 30 min. In-gel trypsin digestion was done with 20 lg/ml sequencing-grade porcine trypsin (Promega, Madison, WI, USA) at 37 °C overnight. Extracted peptides (0.5 ll) were deposited on a MTP AnchorChip 600/384 TF (Bruker Daltonics, Bremen, Germany). Mass spectrometry (MS) and MS/MS spectra were acquired with a MALDI-TOF Ultraflex mass spectrometer (Bruker Daltonics). To confirm protein identification, three MS peaks for each protein were selected for further ionization using the LIFT method and MS/MS analysis [5]. In-solution trypsin digestion and proteomic analysis Washed NP samples were resuspended in 50 mM EDTA, reduced with DTT, alkylated with iodoacetamide, and digested with trypsin as described above. The resulting peptides were desalted using a homemade column, dried in a vacuum centrifuge, and resuspended in 0.1% formic acid, prior to loading onto a Zorbax 300SB-C18 reverse-phase LC trap column (Agilent Technologies, Wilmington, DE, USA). Peptide separation was performed on an analytical C18 column (75 lm i.d.  10 cm; New Objective, Woburn, MA, USA). Elution was done by increasing the concentration of ACN, starting with a solution of 2% ACN (v/v) in 0.1% formic acid and ending with a solution of 95% ACN. The LC column was coupled to a LTQ-Orbitrap mass spectrometer operated using the Xcalibur 2.0 software (Thermo Fisher Scientific, Waltham, MA, USA). The full-scan MS was performed in the Orbitrap from 350 to 2000 Da at a resolution of 60,000 at m/z 400. The ten data-dependent MS/MS scan events were followed by one MS scan for the ten most abundant precursor ions in the preview MS scan. The MS/MS spectra obtained from the Orbitrap were searched against either the SwissProt database (version 51.6, selected for Other Mammalia, 12,387 entries) or the IPI human sequence database (version 3.27, 67,528 entries) using Mascot (version 2.2, Matrix Science) with a fragment ion mass tolerance of 0.5 Da and a parent ion tolerance of 10 ppm. The Mascot search results were integrated to Scaffold software (Proteome Software, Portland, OR, USA) to obtain spectrum counts, sequence coverage, and

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the number of unique peptides. The criteria for protein identification included a minimum of two unique peptides identified with a Scaffold probability of 95% for both protein and peptide identifications. The calculated exponentially modified protein abundance index (emPAI) values were retrieved from ProteinCenter (version 3.2.0.9, Proxeon Bioinformatics, Thermo Fisher Scientific) and the false-discovery rate (FDR) were determined with the Scaffold software. Onemilliliter aliquots of whole body fluids diluted 10% in water were processed in the same manner. Electron microscopy and spectroscopy analyses Washed apatite NP specimens were resuspended in 50 ll of water, and aliquots were processed for either scanning or trans-

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mission electron microscopy [6]. Spectroscopy analyses were conducted as described [5]. Results Proteomics-based strategy used to unravel the protein composition of carbonate-apatite NPs Carbonate-apatite NPs had earlier been shown to assemble from various human body fluids through a slow spontaneous process of nucleation and growth, a process that can be enhanced manyfold by the exogenous addition of precipitating ions [4–9]. These NPs have been shown to be morphologically and chemically similar to each other as well as to mineral formations found within

Fig.1. Morphological and chemical properties of mineral NPs derived from human body fluids. SEM observations of NPs derived from (A) HS, (B) FBS, and (C) ascites. The NP preparations show round particles with large scatter of sizes, with most under 100 nm in diameter but that may reach upwards to 500 nm with prolonged incubation. Some NP preparations also harbor elongated platelet-like structures and tend to coalesce as shown in (C). TEM observations of NPs derived from (D) HS, (E) FBS, and (F) ascites prepared for thin sections. The NP samples shown here harbor round NPs (D and E) and ellipsoid NPs with a crystalline surface (F). Energy-dispersive X-ray spectroscopy (EDX) reveals that (G) HS-derived NPs and (H) ascites-derived NPs have largely equivalent elemental compositions. Both spectra show peaks of carbon (C), oxygen (O), sodium (Na), phosphorus (P), chloride (Cl), and calcium (Ca), indicative of the presence of carbonate apatite harboring minor additional ions. (I) HS-derived NPs and (J) ascites-derived NPs show major peaks of amide I/H2O (1660 cm 1), amide II (1550 cm 1), phosphate (575, 605, and 1000–1150 cm 1), and carbonate (875 and 1400–1430 cm 1) by FTIR. These peaks are consistent with the presence of carbonate apatite and proteins within the two samples shown (see also Refs. [5–7]). (K) HS-derived NPs show a crystalline structure equivalent to that of (L) ascites-derived NPs by X-ray diffraction analysis. Both minerals consist of calcium-phosphate crystals as seen from the molecular formula shown. Scale bars: 100 nm (A and B); 200 nm (C–F).

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calcified tissues and kidney stones and that had been mislabeled as NB (see the comparative data shown in Fig. 1; see also Refs. [10– 12]). NPs were shown to grow from nanometer sizes until they coalesce into spindles and films (Fig. 1; Refs. [5,9]). Given the physiological relevance of these NPs and our ability to control their chemical composition [5,9], we decided to use these NP constructs for protein determination. Carbonate-apatite NPs prepared in cell culture medium containing a body fluid were subjected to proteomics analyses. Several body fluids were used as sources of proteins, including HS, urine, CSF, ascites, pleural effusion, and synovial fluid. The apatite NPs were processed using two different proteomic approaches as outlined in Fig. 2. For the first approach, proteins were released by

EDTA and then separated using one-dimension SDS–PAGE, followed by in-gel trypsin digestion of the main protein bands and subsequent protein identification by MS/MS analysis (Fig. 2A). A second shotgun proteomic approach was developed by directly digesting NP-associated proteins in solution with trypsin, followed by separation of the resulting peptides by reverse-phase LC and protein identification using MS/MS (Fig. 2B). In this case, the proteins identified were ranked by relative abundance using the number of MS/MS spectra identified for each protein (i.e., spectral counting, see Ref. [18]) as well as an exponentially modified protein abundance index (emPAI, Fig. 2B; see Ref. [19]), two complementary methods that provide an estimation of the relative amount of each NP-binding proteins identified.

Fig.2. Proteomics strategies used to determine the protein composition of carbonate-apatite NPs. (A) In-gel trypsin digestion and MS/MS. NPs derived from human body fluids were treated with EDTA to release mineral-binding proteins. After separation by SDS–PAGE, the proteins were in-gel digested with trypsin and identified by matrixassisted laser desorption/ionization-time-of-flight (MALDI-TOF) MS/MS analysis. (B) In-solution trypsin digestion and LC–MS/MS. Proteins released from NPs were directly digested in solution with trypsin, and the resulting peptides were separated on a reverse-phase LC column prior to LTQ-Orbitrap MS/MS analysis.

Fig.3. SDS–PAGE gel profiles and identification of NP-associated proteins using the in-gel trypsin digestion approach. Apatite NPs derived from (A) HS, (B) urine, (C) CSF, (D) ascites, (E) pleural effusion, or (F) synovial fluid were treated with EDTA and processed for SDS–PAGE (Materials and methods). Protein spots were in-gel trypsin digested, and the resulting peptides were processed for MALDI-TOF MS/MS analysis. Experiments were performed in triplicate. SBP1, complement cofactor protein-1; Ig, immunoglobulin; SAP, serum amyloid protein.

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Identification of NP-associated proteins using in-gel trypsin digestion and MS/MS After separation of the NP-associated proteins by SDS–PAGE (Fig. 1A), we first noted that the protein profiles of apatite NPs derived from various body fluids were remarkably similar, essentially consisting of a strong band at 65–80 kDa and several other weaker bands at 27–30, 50–70, and 95–170 kDa (Fig. 3A–F; see also Ref. [5] where only the three main bands of the protein profiles were examined using in-gel trypsin digestion). When protein spots corresponding to the 65- to 80-kDa band were retrieved and analyzed by MS/MS, we observed that human serum albumin (HSA) was present at this position for all NPs tested (Fig. 3A–F). In addition, apolipoprotein A1 (apo-A1) was commonly found at 27–30 kDa, except for those NPs derived from urine (Fig. 3A–F). Some proteins were clearly unique however to the individual body fluids used for NP assembly, as exemplified by uromodulin seen with NPs derived from urine (Fig. 3B). For comparison, NPs derived from FBS were shown to display a somewhat similar protein profile with the main bands consisting of bovine serum albumin (BSA), fetuin-A, vitamin D-binding protein (VDBP), and apo-A1 and the weaker protein bands of plasminogen and serotransferrin (Fig. 4A), indicating again that their presence in the NPs may have simply mirrored the protein composition of the surrounding fluid milieu. Thus, fetuin-A, a potent calcification inhibitor and an avid apatite binder [5,20], is much more abundant in FBS than in HS and shows up as a more prominent protein band in FBS-derived NPs (Fig. 4A) compared to HS-NPs (Fig. 3A). Comprehensive determination of the protein composition of NPs using in-solution trypsin digestion and LC–MS/MS To confirm the identity of the NP-interacting proteins and to obtain a more comprehensive proteomic analysis of the particles, we used a second method that combined in-solution trypsin digestion and LC–MS/MS (Fig. 2B). As expected, this second approach greatly increased the number of NP-interacting proteins identified when compared to the in-gel digestion/MALDI-TOF MS analysis (Table 1 vs Fig. 3). Using this alternative method, 19 proteins were found for urine-derived NPs and 84 proteins for synovial-fluid-derived NPs (Table 1). Notably, with few exceptions, all the proteins identified

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using in-gel digestion were also detected by LC–MS/MS, as exemplified by HSA, apo-A1, and complement C3 which were identified in HS, ascites, and pleural-effusion NPs (Table 1). For LC–MS/MS, the proteins were identified based on stringent statistical criteria that included a minimum of two unique peptides for each protein as well as a protein and peptide identification probability equal or superior to 95% as assessed by the Scaffold software (see Materials and methods). Furthermore, the protein sequences were searched against a random database to determine an experimental FDR, which, in this case, was equal or inferior to 0.1%. This result indicated that, for each 100 protein identifications, only 0.1 of them may represent false-positives. Together, these statistical analyses confirmed the high degree of reliability of the protein and peptide identifications performed using LC–MS/MS. We also examined the protein composition of mineral NPs derived from FBS (Table 2, EDTA column). In this case, we included as additional proteomic information the percentage of protein sequence that was identified by MS analysis and the number of unique peptides identified for each FBS protein (Table 2, Cov. and Peptides columns, respectively; see also Materials and methods). These additional proteomic data confirmed, with a high level of fidelity, the protein identification and ranking achieved with the proteomic analyses performed in this study (Table 2). For the sake of brevity, even though this additional information (i.e., percentage of protein sequence identified by MS analysis and the number of unique peptides identified for each protein) was obtained for every proteomic analysis done in this study, it is included here in Table 2 only for illustration. With the exception of plasminogen, all the FBS-NP proteins identified earlier using the in-gel digestion approach were also found by LC–MS/MS (Fig. 4A vs Table 2, EDTA column). A total of 5 FBS-NP and 5 HS-NP preparations were obtained using varying amounts of serum-to-mineral ratios (i.e., serum, 0.1– 10%; calcium/phosphate ions, 0.1–3 mM), all of which gave largely comparable information for the particular serum species used. These observations not only point to the comprehensive and efficient nature with which this type of proteomics analysis can be performed using LC–MS/MS but also serve to illustrate the high fidelity with which these same data can be reproducibly obtained. In addition to detecting a large number of proteins, LC–MS/MS also provided a semiquantitative ranking of the proteins identified (Table 1). The relative protein abundance determined by this

Fig.4. Gel electrophoresis profile and enrichment of FBS-NP proteins. (A) NPs were prepared in the presence of FBS, analyzed by SDS–PAGE, and processed further for MALDITOF MS/MS as described under Materials and methods. Experiments were performed in triplicate. (B) The percentage of MS/MS spectra obtained for whole FBS proteins (black bars) and the corresponding FBS-NP proteins (gray bars) were graphed for comparison in order to assess for protein enrichment within the NP scaffold. Proteins from FBS-NPs were selected from Table 2.

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Table 1 NP-binding proteins identified by LC–MS/MS and ranked by spectral counting. No.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73

Protein identified

Accession No.

MW

Serum albumin Complement C3 Uromodulin Hemoglobin subunit b a-2-Macroglobulin Apolipoprotein A-I Ig j chain C region Apolipoprotein B-100 Serotransferrin Hemoglobin subunit a Hemoglobin subunit o Ig c-1 chain C region Complement C4B Osteopontin a-1-Acid glycoprotein 1 Haptoglobin Apolipoprotein A-IV a-1-Antitrypsin FLJ00385 protein Inter-a-trypsin inhibitor H4 Kininogen-1 Ig k locus Apolipoprotein D Ig a-1 chain C region Ceruloplasmin Fibronectin Complement factor H Prothrombin Fibrinogen c chain Vitamin D-binding protein Fetuin-A PTGDS Ig c-4 chain C region Ig l chain C region Fibrinogen b chain Complement factor B AMBP protein Clusterin Proteoglycan core protein DKFZp686I04196 Actin, cytoplasmic 1 Fibrinogen a chain Apolipoprotein E a-1-Antichymotrypsin Inter-a-trypsin inhibitor H2 Peroxiredoxin-2 Vitronectin Band 3 anion transport prot. Histone H4 Hemoglobin subunit c-1 a-1-Acid glycoprotein 2 Hemopexin Apolipoprotein A-II Spectrin b Spectrin a chain, erythro. Ankyrin-1 Transthyretin C4b-binding protein a chain b-2-Glycoprotein 1 Monocyte diff. Ag CD14 Gelsolin GAPDH Lactotransferrin Catalase Angiotensinogen b-2-Microglobulin a-2-Glycoprotein 1 a-1B-Glycoprotein Apolipoprotein C-III Complement C9 Plasminogen Phospholipid-transfer prot. Inter-a-trypsin inhibitor H1

IPI00745872 IPI00164623 IPI00013945 IPI00654755 IPI00478003 IPI00021841 IPI00430808 IPI00022229 IPI00022463 IPI00410714 IPI00473011 IPI00448925 IPI00418163 IPI00021000 IPI00022429 IPI00641737 IPI00304273 IPI00553177 IPI00168728 IPI00218192 IPI00215894 IPI00154742 IPI00006662 IPI00430842 IPI00017601 IPI00022418 IPI00029739 IPI00019568 IPI00021891 IPI00742696 IPI00022431 IPI00013179 IPI00550640 IPI00477090 IPI00298497 IPI00019591 IPI00022426 IPI00291262 IPI00024284 IPI00399007 IPI00021439 IPI00021885 IPI00021842 IPI00550991 IPI00305461 IPI00027350 IPI00298971 IPI00022361 IPI00453473 IPI00220706 IPI00020091 IPI00022488 IPI00021854 IPI00784382 IPI00220741 IPI00216697 IPI00022432 IPI00021727 IPI00298828 IPI00029260 IPI00646773 IPI00219018 IPI00789477 IPI00465436 IPI00032220 IPI00004656 IPI00166729 IPI00022895 IPI00021857 IPI00022395 IPI00019580 IPI00217778 IPI00292530

69 187 70 16 163 31 26 516 77 15 16 60 193 35 24 47 45 47 56 101 48 25 21 53 122 263 139 70 52 53 39 21 52 67 56 86 39 52 469 46 42 95 36 51 106 22 54 102 11 16 24 52 11 268 281 206 16 67 38 40 81 36 73 60 53 14 34 54 11 63 91 49 101

HS

Urine

CSF

Ascites

PE

SF

S

E

S

E

S

E

S

E

S

E

S

E

404 97 – 12 86 51 20 40 28 6 – 18 39 – – 28 14 11 11 10 15 12 2 13 23 21 29 12 – 21 5 – 10 19 – 7 3 10 – 8 – – 7 6 15 – 6 – – – – – 5 – – – 6 11 – – 1 – – – – – – 4 2 4 4 – 8

15.7 2.9 – 2.5 4.1 6.5 5.6 0.5 2.8 2.3 – 1.9 1.6 – – 3.5 2.3 1.2 1.5 0.8 2.6 4.0 0.5 1.7 1.3 0.7 1.7 1.0 – 3.5 0.6 – 1.2 2.4 – 0.4 0.7 1.2 – 1.0 – – 0.9 0.9 0.9 – 0.8 – – – – – 2.8 – – – 3.1 1.1 – – 0.2 – – – – – – 0.9 0.9 0.5 0.2 – 0.9

319 – 290 – – – 108 – – – – 11 – 97 11 – – – – 68 17 17 57 – – – – – – – 17 51 – – – – 34 11 46 – 17 – 6 – – – – – – – – – – – – – – – – 11 – – – – – – – – – – – – –

9.4 – 7.9 – – – 10.9 – – – – 1.1 – 24.0 1.5 – – – – 2.0 2.4 4.2 10.9 – – – – – – – 2.4 4.8 – – – – 2.6 1.6 0.4 – 3.4 – 0.8 – – – – – – – – – – – – – – – – 2.4 – – – – – – – – – – – – –

379 50 – 151 39 15 9 – 33 74 70 22 30 4 5 – 6 20 15 – 4 9 3 6 9 10 5 – 22 9 4 6 13 3 15 3 – 11 – 9 3 14 11 5 1 11 – – – 24 – – 4 – – – 9 1 – 2 2 2 – 9 – 5 – – – – – – –

10.1 1.3 – 12.6 2.0 1.7 3.6 – 3.3 8.1 6.1 3.7 1.2 1.8 1.1 – 0.8 2.4 1.4 – 0.5 3.0 0.8 0.8 0.6 0.2 0.2 – 2.2 1.1 0.8 1.6 0.9 0.3 1.4 0.2 – 1.4 – 1.5 0.4 0.8 1.7 0.5 0.1 4.2 – – – 2.2 – – 2.1 – – – 2.3 0.1 – 0.2 0.3 0.2

259 87 – 69 5 80 5 103 – 38 41 15 23 – 44 8 38 13 – – 28 10 3 13 – 15 – 46 8 – 21 – – – 10 – – 8 – – 5 3 – 3 5 13 15 26 18 – – 3 5 21 21 21 – 3 – – – 5 – 3 5 – – – 10 – – 8 –

10.0 1.4 – 15.3 0.1 7.0 1.8 0.8 – 5.9 5.1 1.5 0.4 – 4.4 0.3 2.8 0.8 – – 2.1 1.6 0.7 1.1 – 0.2 – 2.1 0.5 – 2.1 – – – 0.7 – – 0.6 – – 0.4 0.2 – 0.3 0.1 2.7 1.1 0.9 10.0 – – 0.1 4.1 0.2 0.3 0.4 – 0.2 – – – 0.4 – 0.2 0.4 – – – 3.2 – – 0.8 –

706 17 – 6 28 11 13 – 35 3 – 18 8 – 20 20 5 17 20 2 3 10 2 13 16 – 8 1 16 14 5 – 12 10 14 22 6 1 – 10 1 12 – 10 – – 2 – – – 19 10 2 – – – 2 1 6 – 2 – – – 6 7 5 3 – 2 – 2 –

11.4 0.8 – 2.5 2.1 2.9 3.5 – 5.4 2.9 – 2.6 0.4 – 2.9 2.9 0.8 2.7 3.5 0.2 0.5 4.0 0.8 2.3 1.5 – 0.6 0.1 2.2 3.4 0.7 – 2.4 1.4 1.8 1.2 2.1 0.1 – 2.9 0.2 1.3 – 1.7 – – 0.4 – – – 2.2 1.6 2.1 – – – 2.3 0.1 1.9 – 0.4 – – – 1.2 1.9 1.5 1.0 – 0.4 – 0.6 –

295 52 – 25 34 29 25 8 43 14 14 39 12 1 11 35 23 25 37 – 10 19 – 21 18 19 22 3 16 16 5 – 19 21 12 16 4 5 – 17 14 5 9 6 6 3 3 – 6 – 4 8 4 – – – – 1 10 2 10 8 14 2 3 1 8 5 – 6 8 – 2

7.2 1.0 – 7.7 1.2 2.6 2.6 0.1 3.4 7.7 2.8 2.1 0.3 0.2 1.4 1.9 3.0 1.3 2.6 – 1.0 3.4 – 1.7 0.7 0.4 0.9 0.1 1.0 1.6 0.5 – 1.2 1.5 1.0 0.4 0.7 0.4 – 2.8 1.5 0.2 0.9 0.7 0.2 0.5 0.2 – 3.1 – 0.7 0.6 2.6 – – – – 0.1 1.5 0.1 0.8 1.2 0.6 0.2 0.2 0.3 0.9 0.6 – 0.4 0.3 – 0.1

1.1 1.1 – – – – – – –

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Proteomic analysis of apatite nanoparticles / J. Martel et al. / Anal. Biochem. 418 (2011) 111–125 Table 1 (continued) No.

Protein identified

Accession No.

MW

HS S

74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100

Myeloperoxidase Plasma protease C1 inh. PEDF Neutrophil defensin 1 Carbonic anhydrase 1 Ig J chain Antithrombin III variant Histidine-rich glycoprotein Serum paraoxonase Histone H2AV Complement C1q Myosin-reactive Ig Heparin cofactor 2 CD5 antigen-like Transketolase Plastin-2 LDH PRBP Phosphoglycerate kinase 1 a-2-Antiplasmin Rheumatoid factor D5 Histone H2B type 2-E Protein S100-A8 a-Enolase Protein S100-A9 Afamin 14-3-3 protein f/o

IPI00007244 IPI00291866 IPI00006114 IPI00005721 IPI00215983 IPI00178926 IPI00032179 IPI00022371 IPI00218732 IPI00018278 IPI00022394 IPI00783024 IPI00292950 IPI00025204 IPI00643920 IPI00010471 IPI00219217 IPI00022420 IPI00169383 IPI00029863 IPI00816799 IPI00003935 IPI00007047 IPI00465248 IPI00027462 IPI00019943 IPI00021263

84 55 46 10 29 18 53 60 40 14 26 14 60 38 68 70 37 23 45 55 13 14 11 47 13 69 28

Urine E

– – – – – 3 2 6 4 – 2 – 6 2 – – – – – 2 2 – – – – – –

S – – – – – 1.2 0.4 0.7 0.9 – 0.4 – 0.5 0.2 – – – – – 0.3 1.1 – – – – – –

CSF E

– 6 – – – – – – – – – – – – – – – – – – – – – – – – –

S – 0.8 – – – – – – – – – – – – – – – – – – – – – – – – –

Ascites E

– – 4 2 9 – 3 – – – 3 – – – – – 4 – – – – – – – – – 1

S – – 0.5 0.8 1.8 – 0.4 – – – 0.6 – – – – – 0.6 – – – – – – – – – 0.2

PE E

– – – 5 – – – – 3 5 – – – – – – – – – – – 3 – – – – –

SF

S – – – 1.6 – – – – 0.4 2.1 – – – – – – – – – – – 0.9 – – – – –

E – – – – – 1 – – – – 2 2 – – – – – 5 – – – – – – – 2 –

S – – – – – 0.4 – – – – 0.6 0.5 – – – – – 2.4 – – – – – – – 0.2 –

E 10 4 5 2 – 4 3 2 1 3 1 4 – 4 6 6 1 – 5 3 3 2 4 4 4 2 2

0.4 0.3 0.4 1.3 – 1.0 0.3 0.2 0.1 1.9 0.2 0.7 – 0.7 0.3 0.3 0.1 – 0.2 0.3 1.3 0.7 0.7 0.4 1.2 0.1 0.3

Spectral counting values (S) were normalized by multiplying each number of spectra by the average of total spectra count for the 6 samples shown, and then dividing by the sum of spectra for the corresponding sample. Proteins were ranked based on the sum of normalized spectra counts for each row. The emPAI (E) was expressed as relative values. PTGDS, prostaglandin-H2 D-isomerase; AMBP, a-1-microglobulin/bikunin; MW, molecular weight in kDa; PE, pleural effusion; SF, synovial fluid; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; PEDF, pigment epithelium-derived factor; LDH, lactate dehydrogenase; PRBP, plasma retinol-binding protein.

Table 2 Bovine proteins identified in FBS-derived NPs using LC-MS/MS #

Protein Identified

Accession No.

MW

NPs Derived from FBS and Treated with: EDTA

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Serum albumin Fetuin-A a-1-Antitrypsin Apolipoprotein A-I Complement C3 Hemoglobin fetal subunit b Prothrombin Apolipoprotein A-II Vitamin D-binding protein a-Fetoprotein Hemoglobin subunit a Serotransferrin Coagulation factor IX Coagulation factor V Thrombospondin-1 Complement C4 Adiponectin AMBP protein Antithrombin-III a-2-Antiplasmin Vitamin K-dependent protein S Actin, cytoplasmic 1 Apolipoprotein E Coagulation factor X Clusterin Apolipoprotein C-II Kininogen-2

ALBU_BOVIN FETUA_BOVIN A1AT_BOVIN APOA1_BOVIN CO3_BOVIN HBBF_BOVIN THRB_BOVIN APOA2_BOVIN VTDB_BOVIN FETA_BOVIN HBA_BOVIN TRFE_BOVIN FA9_BOVIN FA5_BOVIN TSP1_BOVIN CO4_BOVIN ADIPO_BOVIN AMBP_BOVIN ANT3_BOVIN A2AP_BOVIN PROS_BOVIN ACTB_BOVIN APOE_BOVIN FA10_BOVIN CLUS_BOVIN APOC2_BOVIN KNG2_BOVIN

69 38 46 30 187 16 71 11 53 69 15 78 47 249 130 102 26 39 52 55 75 42 36 55 51 9 69

Without EDTA

S

E

Cov.

Peptides

S

E

Cov.

Peptides

290 147 43 39 38 23 15 13 8 8 7 7 6 5 5 4 4 4 3 2 2 2 2 2 2 2 –

16.2 19.2 6.0 9.3 2.4 9.3 2.8 7.6 1.4 1.2 7.0 1.1 1.5 0.3 0.5 0.4 2.0 1.4 0.7 0.9 0.3 0.7 0.8 0.6 0.7 5.5 –

78 56 29 59 26 72 30 56 20 14 63 16 13 4 6 8 14 14 9 5 3 9 9 5 5 68 –

60 19 12 25 34 8 14 7 6 5 5 7 5 5 5 5 3 4 3 2 2 2 2 2 2 2 –

232 74 37 69 105 84 – – 21 – 32 – – – – – – – – – – – – – – – 26

18.4 18.4 4.7 12.3 3.2 24.1 – – 1.6 – 14.3 – – – – – – – – – – – – – – – 3.0

41 25 10 29 10 54 – – 3 – 25 – – – – – – – – – – – – – – – 5

22 6 4 8 14 8 – – 2 – 3 – – – – – – – – – – – – – – – 3

FBS-NPs were either treated with EDTA or without EDTA as described in Materials and methods. Spectral counting values (S) were normalized by multiplying each number of spectra by the average of total spectra count for the two samples shown, and then dividing by the sum of spectra for the corresponding sample. Proteins were ranked based on the normalized spectra count for the EDTA-treated column. The emPAI columns (E) were expressed as relative values for each sample. The percentage of sequence coverage (Cov.) and the number of unique peptides (Peptides) identified were also shown for reference. AMBP: a-1-microglobulin/bikunin; MW: molecular weight in kDa.

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approach overlapped somewhat with the protein information obtained with the in-gel trypsin digestion technique (Fig. 3). In the case of HS-NPs, albumin, complement C3, and apo-A1 had all been detected on the gel (Fig. 3A), and they also appeared among the more abundant proteins seen with the alternative LC–MS/MS approach (Table 1, HS column), results that are mutually supportive and provide internal consistency. As expected, however, many other proteins identified and ranked as abundant by the LC–MS/ MS technique were not detected by the in-gel digestion approach (compare Fig. 3 with Table 1). In addition to using spectral counting for relative quantification, we also employed emPAI values to obtain a second quantification analysis which took into account the length of the proteins identi-

fied (Table 1, Ref. [19]). As expected, the use of emPAI resulted in several changes in ranking, mainly increasing the relative abundance of smaller proteins over that of larger ones (Table 1). These observations show that LC–MS/MS, through either spectral counting or emPAI values, provides a reliable estimation of the relative abundance of NP proteins. To assess further the degree of enrichment of proteins within the NPs, we compared the percentage of MS/MS spectra for the proteins identified in whole body fluids with the percentage of spectra obtained for the corresponding NP proteins (Fig. 5). Notably, a-2-macroglobulin, complement C3, apolipoprotein B-100, Ig l chain C region, ceruloplasmin, prothrombin, apo-A1, fetuin-A, inter-a-trypsin inhibitor H2, and albumin were found to be considerably enriched in the resultant apatite NPs (Fig. 5). In this case, enrichment of the said proteins was not seen for every NP population examined, an observation which may be attributed to differences in body fluid composition. Thus, in the case of FBS-NPs, the relative concentrations of albumin, complement C3, and apo-A1 increased with respect to whole FBS (Fig. 4B). These results indicate that the LC–MS/MS methodology presented here may be used to estimate the level of protein enrichment in NPs compared to the starting or surrounding body fluid in question. All our proteomics data were obtained following prolonged EDTA treatment of the NPs, which should have loosened or dissolved some, if not most, proteins from the NP scaffold. To study the outer protein coronas of NPs, intact NPs were also analyzed without EDTA treatment (Table 2, without EDTA column). Untreated NPs gave protein compositions similar to those obtained with EDTA treatment. However, a smaller number of proteins and MS/MS spectra were identified under these conditions (Table 2). These results indicate that LC–MS/MS reveals a wealth of information on the protein coronas of synthetic NPs that had been introduced into biological milieus [15,17]. Functional classification of the proteins found in association with apatite NPs

Fig.5. Enrichment of body fluid proteins within apatite NPs. The percentage of MS/ MS spectra for the proteins found in either untreated body fluids (black bars) or the corresponding NPs (gray bars) are shown for (A) HS, (B) ascites, and (C) pleural effusion. The proteins shown were selected from Table 1. Experiments were performed in triplicate.

The proteins that were found enriched in the mineralo-protein NPs could be segregated further into various families according to their known functions (Table 3). As expected, we identified several calcification inhibitors, including albumin, fetuin-A, matrix Gla protein, osteopontin, protein AMBP, and uromodulin (Table 3). Calcification inhibitors like fetuin-A and matrix Gla protein are known to possess respectively apatite-binding sites [21] and c-carboxyglutamate residues [22], which can account for the strong affinity of these proteins for apatite NPs. In addition, the other proteins identified may possess charged residues, including aspartate and glutamate as well as phosphorylated and glycosylated amino acids, which may provide binding sites for calcium and phosphate ions present on apatite NPs [23]. Several apolipoproteins—i.e., proteins mediating lipid transport in human body fluids—were seen to interact with mineral NPs (Table 3). Interestingly, they have consistently been detected in all our mineralized NP specimens studied to date [5–8] as well as in past analyses performed on synthetic NPs exposed to body fluids [13– 16]. Other NP-binding proteins included coagulation factors, complement proteins, immune modulators, ion/molecule transporters, and protease inhibitors, among others (Table 3). For the most part, the proteins identified appeared to be evenly distributed irrespective of the body fluids used to assemble the NPs (Fig. 6). Some NP samples, however, showed distinct protein populations, with urine-NPs, for example, harboring no complement protein (Fig. 6B) and with FBS-NPs showing a higher percentage of coagulation factors on the one hand and no immunity-related proteins on the other (Fig. 6H). Notwithstanding these differences, some proteins appeared to clearly predominate in the vast majority of NPs

Proteomic analysis of apatite nanoparticles / J. Martel et al. / Anal. Biochem. 418 (2011) 111–125

119

Table 3 Function of the main human body-fluid proteins found to interact with apatite NPs in the present study Main Function

NP-Binding Protein

Detailed Function

Blood Coagulation

a-2-Antiplasmin

Inhibition of plasmin Common pathway/zymogen Common pathway/precursor Primary hemostasis/adhesive protein Regulation of intrinsic pathway Inhibition of thrombin Intrinsic activation Precursor bradykinin/thiol protease Fibrinolysis/zymogen Common pathway/zymogen Primary hemostasis/adhesive protein Regulation/cofactor Primary hemostasis/adhesive protein Systemic calcification inhibitor/negative acute-phase protein Systemic calcification inhibitor/negative acute-phase protein Calcification inhibitor Calcification inhibitor/bone remodeling/cytokine Inhibitor of calcium oxalate crystallization Calcification inhibitor Classical pathway/binds to IgM and IgG Classical and alternative pathway/zymogen Classical pathway Classical pathway Membrane attack complex/binds to C5b/6 Membrane attack complex/polymerization Alternative pathway/zymogen Complement regulation Regulation of classical pathway Regulation of immune response Regulation of immune response Humoral immune response Humoral immune response Humoral immune response Humoral immune response Humoral immune response Humoral immune response Part of HLA class I Humoral immune response T-cell activation High density lipoprotein (HDL) High density lipoprotein (HDL) High density lipoprotein (HDL)/chylomicron Low density lipoproteins (LDL) Very low density lipoprotein (VLDL) Very low density lipoprotein (VLDL) High density lipoprotein (HDL) Very low density lipoprotein (VLDL)/chylomicron Clearance of hydrophobic debris Anticoagulant/Interacts with cardiolipin Conversion of HDL particle Acute phase protein/transport of various molecules Major transport protein/negative acute-phase protein Oxidation of ferrous iron to ferric iron Recycling of hemoglobin Oxygen transport Heme transport/iron recovery Transport of vitamin A Iron transport Transport of thyroid hormones Transport of vitamin-D sterols Inhibition of chymotrypsin/cathepsin G/serpin Inhibition of plasmin/serpin Inhibition of thrombin/serpin Inhibition of elastase/serpin Inhibition of various proteases Inhibition of various proteases Inhibition of various proteases/precursor Inhibition of complement proteins Intracellular signaling Cytoskeleton formation Angiotensin precursor Anion transporter/bind erythrocyte proteins Glycolysis Regulation of actin polymerization

Calcification Inhibitor

Complement System

Immune Response

Lipid Transport

Molecular Transport

Protease Inhibitor

Others

Coagulation factor X Fibrinogen Fibronectin b-2-Glycoprotein 1 Heparin cofactor 2 Histidine-rich glycoprotein Kininogen-1 Plasminogen Prothrombin Thrombospondin-1 Vitamin K-dependent protein S Vitronectin Albumin Fetuin-A Matrix Gla protein Osteopontin a-1-Microglobulin/bikunin (AMBP) protein Uromodulin (Tamm-Horsfall glycoprotein) Complement C1q subcomponent subunit C Complement C3 Complement C4-A Complement C4-B Complement C7 Complement C9 Complement factor B Complement factor H C4b-binding protein a chain a-1-Acid glycoprotein 2 CD5 antigen-like protein Ig a chain C region Ig c chain C region Ig j chain C region Ig k locus Ig l chain C region Lactotransferrin b-2-Microglobulin Myosin-reactive Ig Plastin-2 Apolipoprotein A-I Apolipoprotein A-II Apolipoprotein A-IV Apolipoprotein B-100 Apolipoprotein C-II Apolipoprotein C-III Apolipoprotein D Apolipoprotein E Clusterin (Apolipoprotein J) b-2-Glycoprotein 1 (Apolipoprotein H) Phospholipid-transfer protein a-1-Acid glycoprotein 1 Albumin Ceruloplasmin Haptoglobin Hemoglobin Hemopexin Retinol-binding protein Serotransferrin Transthyretin Vitamin D-binding protein a-1-Antichymotrypsin a-2-Antiplasmin Antithrombin III a-1-Antitrypsin Inter-a-trypsin inhibitor heavy chains a-2-Macroglobulin a-1-Microglobulin/bikunin (AMBP) Plasma protease C1 inhibitor 14-3-3 Protein f /o Actin, cytoplasmic 1 Angiotensinogen Band 3 anion transport protein a-Enolase Gelsolin

(continued on next page)

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Table 3 (continued) Main Function

NP-Binding Protein

Detailed Function

Glyceraldehyde-3-phosphate dehydrogenase Histones Myeloperoxidase Serum paraoxonase Peroxiredoxin-2 Protein S100-A8 Transketolase Vimentin Pigment epithelium-derived factor

Glycolysis Nucleosome formation Respiratory burst Resistance to food poisoning Antioxydant enzyme Cell cycle progression and cell differentiation Pentose phosphate pathway Cytoskeleton formation Antiangiogenic/antitumorigenic/neurotropic protein

Fig.6. Functional classification of human and bovine body fluid proteins that interact with apatite NPs. NP-associated proteins from (A) HS, (B) urine, (C) CSF, (D) ascites, (E) pleural effusion, and (F) synovial fluid are classified based mainly on the previous work of Schaller et al. [45]. The numbers shown represent the percentage of proteins corresponding to the functions displayed. (G) Classification of all NP-interacting proteins identified is also shown (‘‘Overall’’). NP-associated proteins from (H) FBS are also shown for comparison. A detailed classification of the serum proteins is presented in Table 3. Proteins with functions other than the ones listed here (see Table 3 under the section ‘‘Others’’) were excluded.

examined, and these proteins included albumin, fetuin-A, complements C3 and C4, apolipoproteins A1 and A2, clusterin, hemoglobin, serotransferrin, VDBP, and a-1-antitrypsin (Table 4). Analysis of various NP specimens using LC–MS/MS Several other types of NPs were subjected to the same proteomics analysis. Earlier, we described serum granular forms isolated from both FBS and HS that were shown to consist of mineralo-protein NPs formed spontaneously or naturally without additional ion input [6]. Compared to the in vitro assembled NPs, which require the additional input of precipitating ions for their formation, these ‘‘serum granules’’ were obtained directly from untreated serum following a simple centrifugation step (Materials and methods). As such, these serum granules can be clearly deemed to represent natural nano- and microscopic entities found in vivo and that may be expected to assume normal physiological roles. In our hands, these granules were also shown to evolve from NPs to other more complex shapes, including platelets, spindles, and films, and they are seen to represent remnants of calcium-phosphate homeostasis that may possibly become precursors of vascular calcification [6]. Using the LC–MS/MS protocol outlined here, a large number of serum proteins were identified in association with these serum granules, with the proteins found being virtually similar to NPs that had

been assembled in vitro in the presence of serum and precipitating minerals (Table 5, compare with Table 1 and Table 2). These observations indicate that the LC–MS/MS-based methodology described here may be used to determine the protein composition of a wide number of NPs that are either found preformed in the body or are assembled from human body fluids under controlled conditions. Furthermore, the marked similarities in protein composition seen with the various populations of NPs, be they assembled in vitro in the presence of body fluids or collected as preformed natural entities from serum, attest to the validity as well as the physiological relevance of the data obtained here with regard to apatite NP composition. We also examined the protein composition of ‘‘hybrid-species’’ NPs obtained under cell culture conditions in the presence of FBS and human urine proteins collected from a patient with proteinuria (see Materials and methods). We observed that the protein composition of these cultured NPs reflected the mixture of protein species present during the NP assembly, with NP-binding proteins from both fluids being represented in the final protein composition (Table 6; compare with Table 1 and Table 2). These results demonstrate the versatility and fidelity with which the protein composition of various NPs can be deciphered using the simple proteomics approach outlined here. In addition, the results described here contribute further to resolving the NB controversy

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Proteomic analysis of apatite nanoparticles / J. Martel et al. / Anal. Biochem. 418 (2011) 111–125 Table 4 Function of selected body-fluid proteins found to interact with apatite NPs Function

NP-Binding Protein

Blood Coagulation

Coagulation factors V/IX/X Fibrinogen Fibronectin b-2-Glycoprotein 1 Heparin cofactor 2 Histidine-rich glycoprotein Kininogen-1 Plasminogen Prothrombin Thrombospondin-1 Vitamin K-dependent protein S Vitronectin Albumin Fetuin-A Osteopontin a-1-Microglobulin/bikunin (AMBP) protein Complement C1q subcomponent subunit C Complement C3 Complement C4 Complement C9 Complement factor B Complement factor H C4b-binding protein a chain a-1-Acid glycoprotein 2 CD5 antigen-like protein Ig a chain C region Ig c chain C region Ig j chain C region Ig k locus b-2-Microglobulin Apolipoprotein A-I Apolipoprotein A-II Apolipoprotein A-IV Apolipoprotein B-100 Apolipoprotein C-III Apolipoprotein D Apolipoprotein E Clusterin (Apolipoprotein J) Phospholipid transfer protein a-1-Acid glycoprotein 1 Albumin Ceruloplasmin Haptoglobin Hemoglobin Hemopexin Retinol-binding protein 4 Serotransferrin Transthyretin Vitamin D-binding protein a-1-Antichymotrypsin Antithrombin III a-1-Antitrypsin Inter-a-trypsin inhibitor heavy chain a-2-Macroglobulin a-1-Microglobulin/bikunin (AMBP) protein

NPs Derived from: HS

Calcification Inhibitor

Complement System

Immune Response

Lipid Transport

Molecular Transport

Protease Inhibitor

seen earlier in the literature. There, a number of human diseases had been claimed to be linked to NB based solely on the basis of formation of NPs in vitro after long-term incubation of homogenized tissues (presumably carrying NB) under cell culture conditions and in the presence of FBS [24–26]. Our proteomics data show the contribution of the feeder FBS to the final protein composition of NPs formed, thereby challenging the previous conclusions made regarding the origin and pathogenesis of NB. Discussion The methodology presented here, allowing for the rapid, comprehensive profiling of proteins associated with mineralized NPs, should be generally applicable to help decipher the protein compo-

FBS

CSF

Pleural Effusion

X X

X

X X

X X X X X X

X X X X X X X X X X X

X X X X X X

X

X X X

X X X

X X X X X X

X X X X X

X X X

X

X X X X

X

X X X

X

X

X X X X X X X X X

X

X X X X X X X X

X X

X

X X X X X X X X X X X X X X X X X

X X

X

X X X

X X X X X X X X

X X X X X X X X

X X

X

X X X X X X X X X X X X X X X X X

sitions of comparable structures in the nano-micrometer range. The methodology makes use of currently established instrumentations and softwares that appear to confer the fidelity and consistency needed to dissect the protein composition of any complex protein mixture or template. To date, we have conducted more than 50 analyses on the various mineralized NP samples, all of which have provided comparable data that are consistent with the source of proteins used. From our data, a number of proteins appear now as excellent marker candidates for mineral particles found in or exposed to human body fluids and tissues. These include albumin, fetuin-A, complement C3, a-1-antitrypsin, prothrombin, and apolipoproteins A1 and B-100, among others. Accordingly, we are currently using these same markers to follow the pathogenesis of vascular

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Table 5 Proteomic analysis of serum granules derived from HS and FBS #

Protein Identified

MW (kDa)

Serum Granules Derived from: HS

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64

Serum albumin Serotransferrin Ig a-1 chain C region Ig j chain V2-24 Ig a-2 chain C region Haptoglobin Ig l-1 chain C region Ig k locus Vitamin D-binding protein FLJ00385 protein Ig c-4 chain C region Complement factor H Complement C3 DKFZp686I04196 b-2-Glycoprotein 1 a-1-Acid glycoprotein 1 Fetuin-A Prothrombin Complement factor B a-2-Macroglobulin Complement C4A Apolipoprotein A-II Apolipoprotein A-I Hemoglobin subunit a Ig l chain C region Plasminogen Kininogen-1 Hemopexin a-1-Antitrypsin Complement C9 Inter-a-trypsin inhibitor H2 Vitronectin Fibronectin 1 isoform 4 Apolipoprotein C-III Gelsolin Histidine-rich glycoprotein a-1B-Glycoprotein Apolipoprotein E Ceruloplasmin C4b-binding protein a chain Thrombospondin-1 Complement C4 Hemoglobin fetal subunit b Coagulation factor V Vitamin K-dependent protein S a-Fetoprotein a-1-Acid glycoprotein AMBP protein PEDF a-2-Antiplasmin Antithrombin-III Coagulation factor X Fibrinogen a chain Heat shock 70 protein 1A Adenosylhomocysteinase Secreted phosphoprotein 24 Clusterin Coagulation factor IX Fetuin-B Fibrinogen b chain GAPDH Glucose transporter type 3, brain Osteopontin Peptidyl-prolyl cis-trans isom. A

69 77 53 26 52 47 53 25 53 56 52 139 187 46 38 24 39 70 86 163 193 11 31 15 66 91 48 52 47 63 106 54 257 11 86 60 54 36 122 67 130 102 16 249 75 69 23 39 46 55 52 55 67 70 48 23 51 47 43 53 36 54 31 18

FBS

Accession No.

Spectra

emPAI

Accession No.

Spectra

emPAI

IPI00745872 IPI00022463 IPI00430842 IPI00440577 IPI00783993 IPI00641737 IPI00472610 IPI00719373 IPI00555812 IPI00168728 IPI00550640 IPI00029739 IPI00783987 IPI00399007 IPI00298828 IPI00022429 IPI00022431 IPI00019568 IPI00019591 IPI00478003 IPI00643525 IPI00021854 IPI00021841 IPI00410714 IPI00549291 IPI00019580 IPI00215894 IPI00022488 IPI00553177 IPI00022395 IPI00305461 IPI00298971 IPI00414283 IPI00021857 IPI00026314 IPI00022371 IPI00022895 IPI00021842 IPI00017601 IPI00021727 – – – – – – – – – – – – – – – – – – – – – – – –

357 53 39 26 21 19 18 16 16 16 14 14 13 11 9 8 8 8 8 8 7 6 5 5 5 4 4 4 3 3 3 3 3 3 3 3 3 2 2 2 – – – – – – – – – – – – – – – – – – – – – – – –

15.3 7.3 3.3 5.1 3.8 4.2 2.8 9.8 2.3 2.0 2.8 1.0 0.3 3.4 2.1 2.3 2.7 0.8 0.5 0.4 0.4 10.4 1.5 7.1 0.8 0.5 0.7 0.5 0.7 0.5 0.4 0.5 0.2 0.9 0.5 0.5 0.6 0.4 0.2 0.3 – – – – – – – – – – – – – – – – – – – – – – – –

ALBU_BOVIN TRFE_BOVIN – – – – – – VTDB_BOVIN – – CFAH_BOVIN CO3_BOVIN – – – FETUA_BOVIN THRB_BOVIN – – – APOA2_BOVIN APOA1_BOVIN HBA_BOVIN – PLMN_BOVIN KNG1_BOVIN – A1AT_BOVIN CO9_BOVIN – – – – – – – APOE_BOVIN – – TSP1_BOVIN CO4_BOVIN HBBF_BOVIN FA5_BOVIN PROS_BOVIN FETA_BOVIN A1AG_BOVIN AMBP_BOVIN PEDF_BOVIN A2AP_BOVIN ANT3_BOVIN FA10_BOVIN FIBA_BOVIN HS70A_BOVIN SAHH_BOVIN SPP24_BOVIN CLUS_BOVIN FA9_BOVIN FETUB_BOVIN FIBB_BOVIN G3P_BOVIN GTR3_BOVIN OSTP_BOVIN PPIA_BOVIN

106 47 – – – – – – 7 – – 10 89 – – – 32 20 – – – 5 32 17 – 25 5 – 35 10 – – – – – – – 20 – – 37 35 35 25 22 17 12 10 10 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5

10.0 3.0 – – – – – – 0.6 – – 0.3 2.2 – – – 11.8 1.2 – – – 2.9 8.2 11.8 – 1.2 0.4 – 5.2 0.7 – – – – – – – 3.7 – – 1.3 1.9 13.9 0.6 1.4 1.3 2.7 1.5 0.9 1.1 0.5 0.7 0.4 0.4 0.6 1.7 0.6 0.5 0.7 0.3 0.7 1.0 1.1 1.0

Spectral counting values were normalized by multiplying each number of spectra by the average of total spectra count for the two samples shown, and then dividing by the sum of spectra for the corresponding sample. Proteins were ranked based on the normalized spectra counts for HS granules. When both human and bovine proteins were displayed on the same row, only the molecular weight of the human protein was indicated. The emPAI was expressed as relative values. AMBP: a-1-microglobulin/bikunin; PEDF: pigment epithelium-derived factor; MW: molecular weight. GAPDH: glyceraldehyde-3-phosphate dehydrogenase.

calcification as well as stone formation. In yet other independent studies, fetuin-A, osteopontin, and a-1-antitrypsin have been used

successfully in the detection of apatite NPs in mineral deposits found in either calcified human ascites [20], arteries [27,28], or

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Proteomic analysis of apatite nanoparticles / J. Martel et al. / Anal. Biochem. 418 (2011) 111–125 Table 6 Protein identified by LC-MS/MS in hybrid NPs derived from human urine and FBS #

Protein Identified

Accession No.

MW (kDa)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Bovine serum albumin Human serum albumin Bovine serotransferrin Bovine a-1-antitrypsin Bovine a-fetoprotein Bovine apolipoprotein A-I Bovine fetuin-A Human a-1-microglobulin/bikunin (AMBP) protein Bovine complement C3 Bovine hemoglobin fetal subunit b Bovine vitamin D-binding protein Human a-2-macroglobulin Bovine a-1-acid glycoprotein Human a-1-acid glycoprotein 1 Bovine a-1B-glycoprotein Bovine prothrombin Bovine a-2-antiplasmin Bovine antithrombin-III Bovine clusterin Bovine fetuin-B Human Ig j chain C region Human inter-a-trypsin inhibitor H2 Human Ig k chain C region Bovine thrombospondin-1

ALBU_BOVIN ALBU_HUMAN TRFE_BOVIN A1AT_BOVIN FETA_BOVIN APOA1_BOVIN FETUA_BOVIN AMBP_HUMAN CO3_BOVIN HBBF_BOVIN VTDB_BOVIN A2MG_HUMAN A1AG_BOVIN A1AG1_HUMAN A1BG_BOVIN THRB_BOVIN A2AP_BOVIN ANT3_BOVIN CLUS_BOVIN FETUB_BOVIN IGKC_HUMAN ITIH2_HUMAN LAC_HUMAN TSP1_BOVIN

69 69 78 46 69 30 38 39 187 16 53 163 23 24 54 71 55 52 51 43 12 106 11 130

NPs Derived from: Human Urine + FBS Spectral Counting

emPAI

225 86 46 49 22 19 56 11 9 12 8 7 4 6 6 5 3 3 3 2 4 2 3 4

16.0 11.8 7.0 10.2 4.4 7.0 11.0 3.7 0.5 7.0 1.7 0.5 2.3 2.5 1.9 0.7 1.2 0.5 0.9 0.5 4.9 0.3 3.0 0.2

Proteins were ranked based on spectral counting values. The emPAI was expressed as relative values. MW: molecular weight.

kidney interstitium [29,30]. It should be noted that, in this context, mineralo-protein NPs have been observed in human calcified tissues [20,27–30] and in laboratory animals treated with drugs that disrupt normal calcium homeostasis [31–34]. However, other than our experiments described here and in a recent study [5] as well as the elegant work of Jahnen-Dechent and colleagues [20,21,35], the spontaneous formation of mineralo-protein NPs in the body has not been addressed, and it may now represent an important mechanism underlying the formation of ectopic calcifications seen in various degenerative diseases. The manner in which proteins and minerals interact to form amorphous NPs that undergo subsequent pleomorphic and crystalline transformation into collapsed spindles, platelets, and films remains a fascinating problem that deserves more detailed studies [5,9]. Earlier, we were able to demonstrate a similar pattern of amorphous-to-crystalline mineral conversion by using only purified proteins like albumin and fetuin-A as substrates [7]. These two proteins represent important calcification inhibitors that prevent unwanted mineralization in supersaturated human body fluids [7,20,36,37]. The presence of these two calcification inhibitors led us to propose a model to explain mineral NP formation in which proteins first prevent mineralization by intercepting calcium, carbonate, and phosphate ions, but later serve as seeds for further mineral deposition once the system has been overwhelmed by precipitating ions [5,7]. The much wider spectrum of proteins seen associated with NPs, as revealed through the profiling method used here, reveals an equally complex pattern of binding and association of proteins to the mineral scaffold. As such, identification of the proteins which interact with minerals may help explain the formation of mineral NPs in the body as well as expand our knowledge on biomineralization insofar as normal bone formation and ectopic calcification are concerned. The observation that proteins with various functions interact with NPs suggests that such mineralo-protein complexes may influence several biochemical pathways when they interact with living cells. A recent study [38] showed that while apatite NPs derived from human arteries inhibited the aggregation of activated platelets in a cell culture assay, the presence of proteins around

the particles decreased inhibition when compared to naked apatite crystals. Besides, the presence of several opsonins (i.e., immunoglobulins, complements C3-B and C4-B, fibronectin, and fetuin-A) within mineral NPs indicates that the particles may be rapidly phagocytosed by the reticuloendothelial system in the body. On the other hand, anti-opsonins such as albumin, which appears to be the main corona protein in the NPs studied, may compete against opsonins and inhibit particle clearance [39], thereby allowing NPs to build up in some pathological conditions. Similarly, the observation that mineral NPs can interact with apo-A1 and apolipoprotein B-100—i.e., proteins found respectively in high-density lipoproteins (HDL) and low-density lipoproteins (LDL)—suggests that such NPs may influence lipid transport pathways in the body, a possibility which deserves further investigations. This possibility is all the more intriguing given the earlier suggestion that these mineralo-protein particles, also referred as calciprotein particles (CPPs), resemble in many respects the circulating lipoprotein particles found in the various body fluids of the body [35]. Moving forward, the methodology described here should yield important information pertaining to the protein scaffold of mineralized particles formed spontaneously in the body. To date, most, if not all, studies detailing the fate of NPs in a biomedical context have involved synthetic particles of defined chemical composition [15,17]. These particles are known to interact with body fluids and to acquire a layer of proteins (corona) deemed to be pathophysiologically relevant. A portion of this protein corona (‘‘soft corona’’) appears to change dynamically over time whereas other high-affinity binding proteins (‘‘hard corona’’) have been shown to persist over long periods of observation [13,14,40,41]. In most studies, the protein determinations made have been tedious and no attempt has been made to obtain a comprehensive and quantitative view of NP-associated proteins. The efficient, comprehensive, and semiquantitative method of protein analysis developed here should be readily applicable to dissecting the protein corona of any given particle population that is acquired following contact with various body fluids. This method should prove useful in the context of the emerging field of nanotoxicology.

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The sequestration of calcium in the form of NPs and calcium granules is now known to occur throughout nature and not just in body fluids, as part of a more general, and perhaps ubiquitous, cycle of calcium storage, retrieval, deposition, and disposal (see Ref. [42] for Ryall’s insightful review on calcium granules). These granules are now known to be found in organisms spanning a wide range of phylogenetic complexities. In fact, a clear analogy can also be drawn between the formation of the NPs and the calcium granules studied here and the formation of mineralo-polymer gel complexes in ocean water from dissolved organic matter and calcium carbonate [43]. The crystallization of calcium carbonate inside this meshwork of carbohydrates, proteins, and lipids was elegantly explained by a Donnan effect attributed to the polyanionic nature of the organic matrix [43]. In addition to calcium, other ions are now known to complex with organic moieties that result in the creation of NPs as well as a plethora of forms that biomimetically resemble complex biological shapes—representing a general family of pleomorphic mineralo-organic forms that we have called bions [9]. Bions, polymeric sea and spring water gels, and a number of other granular forms found in nature have now been shown to carry protein constituents that can be dissected using the methodology described here [44]. It is thus expected that the simple and yet comprehensive proteomics strategy outlined here will have wide applicability in the future. Acknowledgment We thank Drs. Chih-Ching Wu, Kun-Yi Chien, and Chien-Kai Chen for help with the proteomic analyses. This work was supported by Primordia Institute of New Sciences and Medicine and by grants from Chang Gung University (FMRPD2T02), Mingchi University of Technology (0XB0), and the Ministry of Education of Taiwan, Republic of China (EMRPD190041). References [1] A. Nel, T. Xia, L. Madler, N. Li, Toxic potential of materials at the nanolevel, Science 311 (2006) 622–627. [2] M. Park, D. Lankveld, H. van Loveren, W. de Jong, The status of in vitro toxicity studies in the risk assessment of nanomaterials, Nanomedicine (Lond.) 4 (2009) 669–685. [3] A.A. Shvedova, V.E. Kagan, B. Fadeel, Close encounters of the small kind: adverse effects of man-made materials interfacing with the nano-cosmos of biological systems, Annu. Rev. Pharmacol. Toxicol. 50 (2010) 63–88. [4] J. Martel, J.D. Young, Purported nanobacteria in human blood as calcium carbonate nanoparticles, Proc. Natl. Acad. Sci. USA 105 (2008) 5549–5554. [5] J.D. Young, J. Martel, L. Young, C.Y. Wu, A. Young, D. Young, Putative nanobacteria represent physiological remnants and culture by-products of normal calcium homeostasis, PLoS ONE 4 (2009) e4417. [6] J.D. Young, J. Martel, D. Young, A. Young, C.M. Hung, L. Young, Y.J. Chao, J. Young, C.Y. Wu, Characterization of granulations of calcium and apatite in serum as pleomorphic mineralo-protein complexes and as precursors of putative nanobacteria, PLoS ONE 4 (2009) e5421. [7] C.Y. Wu, J. Martel, D. Young, J.D. Young, Fetuin-A/albumin-mineral complexes resembling serum calcium granules and putative nanobacteria: demonstration of a dual inhibition-seeding concept, PLoS ONE 4 (2009) e8058. [8] J. Martel, C.Y. Wu, J.D. Young, Critical evaluation of gamma-irradiated serum used as feeder in the culture and demonstration of putative nanobacteria and calcifying nanoparticles, PLoS ONE 5 (2010) e10343. [9] J.D. Young, J. Martel, The rise and fall of nanobacteria, Sci. Am. 302 (2010) 52– 59. [10] E.O. Kajander, N. Ciftcioglu, Nanobacteria: an alternative mechanism for pathogenic intra- and extracellular calcification and stone formation, Proc. Natl. Acad. Sci. USA 95 (1998) 8274–8279. [11] E.O. Kajander, N. Ciftcioglu, K. Aho, E. Garcia-Cuerpo, Characteristics of nanobacteria and their possible role in stone formation, Urol. Res. 31 (2003) 47–54. [12] N. Ciftcioglu, D.S. McKay, G. Mathew, E.O. Kajander, Nanobacteria: fact or fiction? Characteristics, detection, and medical importance of novel selfreplicating, calcifying nanoparticles, J. Investig. Med. 54 (2006) 385–394. [13] T. Cedervall, I. Lynch, S. Lindman, T. Berggard, E. Thulin, H. Nilsson, K.A. Dawson, S. Linse, Understanding the nanoparticle–protein corona using methods to quantify exchange rates and affinities of proteins for nanoparticles, Proc. Natl. Acad. Sci. USA 104 (2007) 2050–2055.

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