Proteomic Approaches To Characterize Surface-Bound Proteins and

Chapter 37

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Proteomic Approaches To Characterize Surface-Bound Proteins and Material-Mediated Cellular Proteins Yao Fu1 and Weiyuan John Kao*,1,2,3 1School

of Pharmacy, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705 2Department of Biomedical Engineering, College of Engineering, and School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705 3Department of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705 *E-mail: [email protected]

Proteins at the biomaterial interface include surface-adsorbed proteins and soluble proteins secreted by cells adherent or attached to biomaterial interfaces. These proteins carry multiple functions such as directing cell adhesion, proliferation, differentiation, and migration. The identification of proteins at the material interface will help elucidate the impact of proteins in mediating cell-material interaction, host response, and cell signaling pathway. The aim of this chapter is to provide an overview of the application of proteomic tools to analyze proteins at the material interface. Two main analytical methods, protein microarrays and mass spectrometry (MS), have been reviewed and their applications in proteomic study of biomaterial-related proteins were discussed in case studies. In sum, proteomics provides a viable approach to survey global proteome of surface-adsorbed proteins and soluble proteins from adherent cells at the biomaterial interface.

© 2012 American Chemical Society In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Introduction Early works on protein adsorption onto synthetic surfaces can be traced back to the 1930s (1). In the 1960s, Dr Vroman and his colleagues observed that the adsorption and desorption of serum proteins onto material surfaces followed a sequential and competitive process using ellipsometry methods (2–5). The initial adsorbed proteins such as fibrinogen were replaced by high molecular weight kininogen of higher affinity to the material surface in a timeand concentration- dependent fashion. Proteins at the biomaterial interface carry multiple functions such as directing cell adhesion, proliferation, differentiation, and migration. However, the adsorbed proteins may undergo structural changes (6–8), which may impact the subsequent cellular responses to the biomaterial. As such, materials that displayed a low degree of conformational changes (i.e., secondary structure changes) of adsorbed proteins and a low platelet adhesion are considered better candidates for blood-contacting biomedical devices (9). Bacteria adhesion onto material surfaces is also mediated by adsorbed proteins such as fibrinogen and vitronectin (10). Thus, controlling the non-specific adsorption of proteins is of crucial importance for the development of non-fouling medical devices (11). Moreover, studies showed natural killer (NK) cell-mediated mesenchymal stem/stromal cell (MSC) recruitment was modulated by fibrinogen adsorption. Thus, the incorporation of pro-inflammatory proteins such as fibrinogen into biomaterials was conducted to facilitate the rational modulation of the inflammatory response and stem cell recruitment in regulating tissue repair and regeneration (12). In addition to adsorbed proteins, soluble proteins that are secreted from adherent cells on the biomaterial surface also play an important role in directing cellular responses to the material. Macrophages for instance are one of the key players in the host inflammatory response to implanted biomaterials. Our studies revealed the effect of surface-adsorbed proteins on the intracellular protein expression in adherent macrophages, providing insights into the intracellular signaling pathways mediated by different surface adsorbed ligands through extracellular matrix (ECM)-integrin interactions (13). Therefore, detailed analysis of proteins at the material interface will help elucidate the impact of proteins in mediating cell-material interaction, host response, and cell signaling pathway. Traditional analytical methods for proteins include ellipsometry, gel electrophoresis, Fourier transform infrared spectroscopy (FT-IR), spectrophotometry, nuclear magnetic resonance (NMR), western blot, immunoprecipitation, and immunostaining. These methods can be divided into two groups: i) qualitative methods that provide composition, molecular weight and structural information, e.g., western blot, ellipsometry, FT-IR, NMR, immunoprecipitation, immunostaining, immunoblotting; and ii) quantitative methods that determine the concentration of proteins, e.g., spectroscopic methods, colorimetry, radiolabeling of proteins, and reversed phase high performance liquid chromatography (RP-HPLC). For these analytical methods, a priori knowledge of the proteins under investigation is usually required. Thus, identifying and quantifying unknown proteins using these aforementioned analytical methods is difficult and cannot be carried out efficiently in a large scale. The emergence and 810 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


development of mass spectrometry (MS) provides a powerful tool to characterize and sequence proteins without a priori knowledge of the protein identity (14). This leads to the burgeoning of a novel research field - proteomics. The term proteome was first mentioned by Marc Wilkins in 1994 in a symposium on “2D Electrophoresis: from protein maps to genomes” (15). Gygi and Aebersold defined proteomics as “the ability to systematically identify every protein expressed in a cell or tissue as well as to determine the salient properties of each protein such as abundance, state of modification, and involvement in multiprotein complexes” (16). The system-wide study of proteins thus provides an integrated understanding of biological systems (17). Its high throughput screening capability has found broad applications in the identification of biomarkers for diseases and drugs (18). Therefore, using proteomics to study proteins at the material interface may help identify important biomarkers in mediating cell-material interactions. In general, two types of proteomic analysis are involved: quantitative and functional proteomics. Specifically, a quantitative ‘proteomic analysis’ may involve measuring the abundance, modification, activity, localization and interaction of all proteins in a sample (19). While a functional proteomics aims to seek functional proteins that are involved in identifying putative substrates for enzymes or putative interactions between proteins (19). The aim of this chapter is to provide an overview of the application of proteomic tools to analyze proteins at the material interface. Protein microarrays and MS are the two main analytical methods that are extensively used. Proteins at the interface can be classified into surface-adsorbed proteins and soluble cellular proteins, and case studies for each will be provided. The challenges and limitations with current technologies in biomaterial applications will also be commented.

Proteomics and Protein Analytical Technologies Protein Microarrays A protein microarray is an affinity-based multiplex approach to identify protein-protein interactions. A microarray comprises different affinity antibodies arrayed at high spatial density on a solid support (19). Through specific binding interactions, each antibody captures its target protein from a complex mixture, and the captured proteins are subsequently detected and quantified (19). Briefly, protein microarrays can be classified into target microarrays, reverse phase protein arrays (RPP), and in situ expressed arrays (20). Two immunoassays that are commonly used in the targeted protein microarray technology are: (i) sandwich immunoassay where a primary antibody is immobilized on the solid substrate and a second labeled antibody is required for detection; (ii) antigen capture assay where an antibody is immobilized on the solid substrate and prelabeled proteins are used for detection. Such approaches are effective in determining protein expression levels, i.e., protein profiling. However, major drawbacks with target arrays include the cross-reactivity and the loss of antibody activity upon immobilization (20). The RPP array is a direct assay that does not require primary antibody immobilization, but allows target proteins to be adsorbed and then are 811 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


subjected to specific antibody binding for detection. The RPP approach has been applied to the study of post-translational modifications and signal transductions ex vivo (20). Recently, protein microarrays can be fabricated through in situ cell-free synthesis directly from corresponding DNA arrays. The in situ protein array format is mainly based on cell-free eukaryotic expression systems such as Escherichia coli 30s, rabbit reticulocyte lysates and wheat germ extracts (20, 21). Regarding content for protein in situ arrays, a library of open reading frames (ORFs) is required (20). Many different in situ protein arrays have been developed recently to improve the protein availability and long term storage, for example: Protein in situ arrays (PISA) arrays (22), printing protein arrays from DNA (DAPA) arrays and nucleic acids programmable protein arrays (NAPPA) arrays (23). Advantages with protein microarray technologies include high sensitivity, small sample volume, and high screening capability. Arrays fabricated at a high density can ensure simultaneous analysis of large numbers of immobilized proteins in a time- and cost-effective manner (24). Recently, the production of large collections of pure recombinant proteins can be achieved via in situ cell free approaches. One limitation with this technology is the competing binding from proteins of high abundance that may prevent binding of target proteins of very low abundance. Protein concentrations in biological samples display a broad dynamic range by a factor of 108 - 1010 (25, 26), which presents an analytical challenge on developing robust methods for protein identification and quantification. Thus, pretreatment of biological samples is often required to separate and enrich proteins of low abundance for proteomic study. Method sensitivity is another limitation. Protein microarrays rely on signal amplification strategies to reach sensitivity levels for application, and common amplification methods include quantum dots, fluorescence and colorimetric signals (27, 28). The sensitivity is thus affected by the complex components in the biologic samples. For example, biotin, peroxidases, alkaline phosphatases, fluorescent proteins, and immunoglobulins may substantially reduce the yield of amplification reactions (25). MS Technology MS technology is one of the most important developments in Anal. Chem. of the 20th century. MS is a highly sensitive analytical technique that has been successfully applied to analyze complex protein samples. An MS system is comprised of three major components: an ion source, a mass analyzer and a detector. MS is based upon detecting charged ions in the gas phase thus allowing the calculation of the overall molecular weight (13). Electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI) are the two most commonly used ionization methods in MS measurements and both are considered as “soft” ionization methods that minimize protein or peptide degradation (13). ESI ionizes analytes in solution that can be coupled on-line to liquid chromatographic separation systems (LC), while MALDI ionizes samples from a dry, crystalline matrix via laser pulses (29, 30). ESI-MS is usually used for the analysis of more complex samples, and MALDI-MS has been applied to analyze relatively simple peptides (29). ESI instruments coupled with LC 812 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


systems (LC/MS) provide a good resolution of complex peptide mixtures before ionization. In addition, two-dimensional gel electrophoresis, a highly resolving separation technique, is also used to fractionate protein mixtures prior to MS analysis (31). As for mass analyzers, four basic types currently in use are: ion trap, time-of-flight (TOF), quadrupole, and Fourier transform ion cyclotron (FT-MS) analyzers. Often, an ion trap analyzer is included in the ESI to capture specific peptide ions by collision-induced dissociation (CID) with an inert gas (32). CID enables compilation of detailed peptide sequence data (33). Each has its advantages and disadvantages, and therefore can be used independently or together (Table I). Although MALDI-MS cannot be used to sequence peptides directly, it allows rapid and sensitive analysis of peptide masses (13). MALDI coupled to TOF analyzers (MALDI-TOF) is usually used to measure intact peptides. Due to its excellent mass accuracy, high resolution and sensitivity, peptide mass mapping/fingerprinting via MALDI-TOF can be used to identify proteins. For peptide sequencing purposes, CID tandem mass-based spectrometry is frequently used in proteomics. In MS-based proteomics studies, two methods in use are the “bottom-up” and “top-down” strategies. The “bottom-up” strategy identifies and characterizes proteins by proteolytic and enzymatic digestion of proteins prior to MS analysis, which is now commonly used to identify protein localization, expression, and modifications (34–36). A technique, known as “shotgun proteomics”, is a method using high performance liquid chromatography (HPLC) coupled with MS or tandem MS to identify proteins (37). Usually, proteins in complex biological mixtures are digested into a collection of peptides and subjected to LC/MS/MS analysis. In contrast, the “top-down” strategy uses an ion trapping mass spectrometer to store an isolated protein ion for mass measurement and tandem MS analysis (38, 39). Unlike bottom-up methods using proteolytic digestion, protein fragmentation is accomplished via gas phase dissociation in the “top-down” approach. Thus, the “top-down” approach is a direct profiling method to identify and characterize proteins that provides critical information such as protein post-translational modifications, which might be obscured by shotgun digestion of a complex protein mixture (39). However, the application of top-down strategy is largely limited by instrument, e.g., sensitivity and the broad dynamic range. Using ESI and MALDI, protein standards were analyzed with ultrahigh sensitivity and fast acquisition of fragmentation data, but wild-type proteins were proven difficult to be analyzed (39, 40). Overall procedures for a MS-based proteomic study include sample collection, purification, separation, MS analysis, generation of an identified peptide list, and protein identification via matching with sequence database. Samples that are commonly used in proteomic studies are cell lysates and tissue homogenates that have complex components. Sample pretreatment thus provides a mean to reduce the complexity of the sample proteome and to decrease the dynamic range (41). The two main purposes of sample pretreatment for MS analysis are: (i) purification, to remove interfering components; (ii) enrichment, to increase the concentration of the target analyte that is of low abundance. For cell lysates, tissue fluids, or other biological samples, they may contain non-proteinaceous compounds which may interfere with downstream procedures (42). Thus, proteins need to be extracted from the crude biological sample. 813 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


A common procedure is desalting, which can be accomplished via dialysis, ultrafitration, gel filtration or electrophoresis, precipitation with acids or organic solvents, or solid-phase extraction (43). Organic solvents used for protein precipitation include acetone, trichloroacetic acid (TCA), ethanol, isopropanol, chloroform/methanol, and ammonium sulfate (44). Following extraction, proteins are fractionated before being subjected to MS analysis. In general, protein fractionation can be performed at either protein or peptide level. At the protein level, pre-fractionation of proteins via chromatographic methods or gel electrophoresis can help reduce the complexity of the sample (41, 45). Removing proteins of high abundance may also improve the detection sensitivity for proteins of low abundance (45, 46). For peptide-level pretreatment methods, fractionated peptides can be generated via proteolytic digestion. Furthermore, representative peptides containing rare amino acids or terminal peptides can be enriched via pre-fractionation approaches. For examples, cysteine (Cys) containing peptides can be isolated using Cys-specific tags that can specifically react with the thiol group of Cys, e.g., isotope-coded affinity tag (ICAT) (47). The Methionine (Met) containing peptides were isolated and enriched via covalently binding to Met-specific beads containing bromoacetyl functional groups (48). A specific tagging method was developed for selectively enriching peptides containing tryptophan (Trp) (49). Besides amino acid-specific tagging methods, immobilized metal affinity chromatography (IMAC), metal oxide, ion-exchange chromatography, chip-based methods, chemical modifications, and centrifugal ultrafiltration have been used for peptide enrichment (41). For example, histidine (His) containing peptides were enriched from complex peptide mixtures using (IMAC) loaded with copper II (Cu2+) (50). To sum up, the aforementioned pretreatment methods are efficient approaches to isolate and to fractionate target peptides of interests. However, it is critical to select a pretreatment method that can reduce the sample complexity yet retain the integrity of the proteome for the subsequent proteomic analysis.

Table I. Comparison of four basic mass analyzers (16, 29) Mass analyzer

Advantages

Disadvantages

Upper mass range (m/z)

The ion trap

Robust, sensitive, inexpensive, medium resolution, well-suited for tandem mass spectrometry

Low mass accuracy, limited mass range

2000

Time-of-flight (TOF)

High sensitivity, mass accuracy, resolution, fast scan speed, adaptation to MALDI

Low resolution, difficulty of adaptation to ESI

Unlimited

Continued on next page.

814 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Table I. (Continued). Comparison of four basic mass analyzers (16, 29) Mass analyzer

Advantages

Disadvantages

Upper mass range (m/z)

Quadrupole

High pressure-tolerant, ease of switching between positive/negative ions, small size

Poor adaptability to MALDI

4000

Fourier transform ion cyclotron resonance mass spectrometer (FT-MS)

High sensitivity, mass accuracy, resolution and dynamic range, well-suited for tandem mass spectrometry

High cost, operational complexity, low peptidefragmentation efficiency

10,000

Proteomic Studies of Proteins at Biomaterial Interfaces Protein adsorption has long been a subject of interest to researchers in the biomaterial field. Traditionally, SDS-PAGE, radiolabeling, and Western blot were approaches extensively used to study protein adsorption on materials for biomedical applications including Cuprophane dialysis membranes and hemodialyzers (51–53). With the rapid development in the analytical technique, more and more proteomic studies on proteins at the biomaterial interface have been reported. A thorough discussion was given by Elbert DL regarding the unbiased approaches to study protein adsorption before and after the field of proteomics emerged (54). Power KA et al discussed the application of proteomic technology to biomaterials when providing leading opinions on examination of cell-host-biomaterial interactions via high-throughput technologies (55). Griesser HJ et al presented a good review on surface-MALDI-MS in biomaterials research demonstrating its potency as a powerful tool to analyze surface-adsorbed proteins in biomaterials (56). In the following sections, proteomic studies on surface-associated proteins and soluble proteins at the biomaterial interface are reviewed. These studies generated some viable approaches on how to identify proteins and to elucidate the roles of specific protein biomarkers in implementing cell adhesion, cell activation post-adhesion, and intracellular signaling pathways involved in cell-material interaction. Surface-Associated Proteins It is well appreciated that serum proteins adsorbed on blood-contacting biomaterials play a key role in mediating cell adhesion, activation, and thrombosis and affecting the outcome of host responses to materials (14, 57). The surface adsorption of albumin, complement components, vitronectin, and fibrinogen onto various polymer-based substrates have been extensively studied (58–61). Material composition, surface properties such as hydrophobicity and ion charges, protein structure and the competitive adsorption amongst proteins are deemed 815 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


major factors that impact protein adsorption isotherm (14). Using proteomic analysis, complete adsorbed serum proteome information can be generated to provide insights into the material blood compatibility and further benefit the development of materials. Wang X et al applied MS-based proteomics to study serum protein adsorption/absorption and complement C3 activation of poly(ethylene glycol) (PEG) hydrogels (14). PEG, a hydrophilic linear polymer, is well known for its “non-fouling” and low protein adsorption properties. It is widely used in surface modifications to increase material surface hydrophilicity and improve material biocompatibility. Primary human monocytes were found to adhere onto PEG hydrogel surfaces, and considered to be mediated by serum protein adsorption (62). Thus, a thorough understanding of the adsorbed proteome on PEG hydrogels will provide significant insights into the mechanisms of the observed cellular behavior. In this study, human serum was collected from human blood and subjected to fractionation using PEG (4 kDa) to reduce proteins of high abundance, e.g., albumin. Distribution of plasma proteins using PEG fractionation method was shown in Table II.

Table II. Distribution of human serum proteins in PEG fractions as determined by ELISA* Protein distribution (%) Serum protein

*

Albumin

Fraction I (0-10% PEG) 13.4 ± 3.7

Fraction II (10-20% PEG) 16.5 ± 4.6

Fraction III (20% PEG) 70.1 ± 4.2

Thrombin

43.1 ± 6.1

51.2 ± 10.4

5.8 ± 5.0

Fibrinogen

98.3 ± 9.0

1.3 ± 0.3

0.4 ± 0.3

Complement C3

99.7 ±1.5

0.3 ± 0.0

0.1 ± 0.0

Vitronectin

31.1± 0.7

38.0 ± 0.7

30.9 ± 0.5

Reproduced with permission from reference (14). Copyright 2011 Taylor & Francis.

The procedures for serum protein adsorption study and MS analysis are shown in Figure 1. Based upon these procedures, different spectra of adsorbed proteins between PEG hydrogels and tissue culture polystyrene surface (TCPS) via MALDI-MS were generated (Table III). Using fractionated serum, the number of albumin hits on TCPS was lower compared to samples treated with whole serum. Vitronectin, fibrinogen and thrombin were demonstrated with top scores on TCPS incubated with fractionated serum. In contrast, a low number of hits for these proteins was observed for TCPS treated with whole serum due to the presence of albumin. However, PEG hydrogels incubated with fractionated serum displayed a high number of hits for albumin, and no vitronectin or thrombin was detected, indicating the adsorption of vitronectin and thrombin was inhibited by PEG hydrogels. In addition, the detection of α2-macroglobulin and α1-acid glycoprotein 1 on PEG hydrogels further demonstrated that the lectin 816 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


pathway could be involved in the macrophage response to PEG (63), which is in accordance with literature. The presence of serum amyloid P component on PEG hydrogels suggests the classic complement pathway (64). However, the presence of complement factor C3 was not detected in MALDI-MS results, which is most likely due to the low abundance of the adsorbed C3 protein and the relatively low affinity of C3 to TCPS and PEG hydrogels. Thus, the adsorption of vitronectin, thrombin, fibrinogen and complement factor C3 was further verified by enzyme linked immunosorbent assay (ELISA).

Figure 1. Schematic procedures for serum protein adsorption study via MS based proteomics. Adapted from reference (14).

Oughlis S et al developed a similar proteomic method to study protein adsorption on titanium (Ti) grafted with poly(sodium styrene sulfonate) (polyNaSS), which utilized 2D gel electrophoresis coupled with MS to analyze adsorbed proteins on various surfaces (65). Platelets rich plasma (PRP) sample was used to study protein adsorption on various titanium materials and the adsorption experiment was conducted using an affinity chromatography set-up. Specifically, various Ti-based granules were packed into columns and equilibrated with phosphate buffer saline (PBS, pH 7.4). PRP samples were first loaded and allowed to pass through the column at a flow rate of 0.3 mL/min. UV absorbance of the mobile phase was monitored at the wavelength of 280 nm. The column was then washed with PBS until stable baseline was observed. To elute the adsorbed proteins, PBS containing 3M sodium chloride (NaCl) was then used as the mobile phase. The results showed polyNaSS grafted Ti phase displayed two peaks corresponding to the flowthrough and the eluate, while non-grafted Ti phase displayed one peak corresponding to the flowthrough (Figure 2). The eluted protein fractions were further subjected to 2D gel electrophoresis and LC/MS/MS analysis (Figure 3). The results demonstrated the grafted polyNaSS/Ti surface had a higher level of protein adsorption than un-grafted titanium. The selective adsorption of complement factor B and serum albumin onto polyNaSS/Ti surface were not affected by high abundance plasma proteins such as immunoglobulin G (IgG) and α1 antitrypsin. 817 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Table III. Comparison of adsorbed proteins on PEG hydrogel (3400 Da) and TCPS incubated with fractionated (Fraction I+II) and whole human serum. (Reproduced with permission from reference (14). Copyright 2011 Taylor & Francis.)



Figure 2. Affinity chromatography profiles. Separation of PRP proteins on NaSS/Ti column (A) or TiOx column (B) equilibrated with PBS pH 7.4 at a flow rate of 0.3 mL/min. Peaks are assigned as followed: 1, 3. flowthrough, and 2. eluate. (Reproduced with permission from reference (65). Copyright 2011 Elsevier.)

To evaluate protein adsorption in a physiology-relevant condition, adherent cells should unarguably be included in the experimental setup. The extracellular matrix (ECM) mainly functions as the supporting substrates for cell adhesion, growth and proliferation, which is composed of collagen fibers, elastin fibers, glycosaminoglycans (GAGs), and water. ECM is involved in directing extensive cell-cell and cell-matrix interactions. Thus, it is of great significance to characterize ECM components at the cell-biomaterial interface both qualitatively and quantitatively. Regarding cell-material interactions, the adherence surface (AS) is defined as a biochemical structure present at the cell-material interface (66). AS is composed of the basal plasma membrane with associated structures such as the ECM on one side and the focal adherence complexes on the other, 819 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


which mediates the communication of mechanical and tectonic signals from the material to the biochemical transducers in the cells (66). The AS of mammalian cells can be isolated using techniques such as wet cleaving (67), sonication (68), controlled lysis squirting (69), isolation on poly(L-lysine)-coated beads (70), and sandwiching (71, 72). Derhami et al conducted some interesting proteomic studies on skin fibroblasts grown on titanium substrates (73, 74). In their study, human skin fibroblasts adhered to titanium substrates. The AS material was thus obtained after detachment of fibroblasts which represented the remnants of focal adhesions. A proteomic analysis was then conducted using 2D-PAGE combined with MALDI-MS. A total of 40 proteins were identified and several proteins such as albumin, α2-HS-glycoprotein, α-fetoprotein, plasminogen, thrombospondin 1, and serotransferrin were found to adsorb onto titanium substrates in relatively high concentrations as compared to TCPS. Tong W et al developed a method that can achieve large-scale isolation of AS and a quantitative proteomic method to characterize the Madin-Darby canine kidney cell (MDCK)-biomaterial interface (66). Their study provided a robust method to enrich extracellular matrix proteins, membrane and stress fiber proteins from the adherence surface (AS). Specifically, the AS purification was conducted as shown in Figure 4. 1D gel electrophoresis and LC/MS/MS were used to separate and characterize proteins enriched in the AS preparation. Stable isotope labeling with amino acids in cell culture (SILAC) is a metabolic labeling technique to quantify and compare proteome changes between biological samples (75). Two isotopes, SILAC “heavy” R6 K4 and “light” R0 K0, generated peptides labeled with isotopes of different intensities. The intensity ratio between each heavy isotope-labeled peptide and its light isotope counterpart could be measured. A total of 3478 unique peptide and 204 proteins were identified in the study. SILAC ratio was further used to classify proteins into AS-associated and non-AS associated proteins. The results showed proteins enriched in the AS at cell-biomaterial interfaces were classic ECM proteins such as laminin and fibronectin. Proteins that regulate cell adhesion and motility were also identified, e.g., the chondroitin sulfate proteoglycan and nebulin. Backovic A et al selected silicone as the material platform to study surface-adsorbed proteins both in vitro and in vivo (76). Protein identification was conducted with MS analysis, database matching, and Western blots. Silicone implant samples were collected from patients undergoing implant replacements or removal. Explanted silicone implants were washed with PBS and water at 4°C, and eluted in buffer solutions for appropriate downstream analyses. Proteins eluted were primarily analyzed by 2D gel electrophoresis. Spots of interest were then excised, proteins were digested with trypsin and analyzed by MALDI-TOF and LIFT-TOF/TOF MS/MS. A total number of 30 most abundant proteins was identified on the surface of silicone. The study provided significant insights into protein adherence to implanted silicone materials that is of great practical medical relevance. For example, the abundant presence of heat shock protein 60 (HSP60) most likely reflected the response of tissues surrounding silicone implants to mechanical stress under physiological conditions. The presence of MMP-2 is indicative of prominent remodeling processes in the protein layer. 820 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Figure 3. 2-DE profiles of PRP proteins adsorbed on polyNaSS/Ti chromatography. Proteins were separated on a linear pH 5–8 IPG strip, followed by a 8–18.5% SDS-polyacrylamidegel. Proteins were stained with silver nitrate. (1-A) 2-DE map of the eluted fraction. (1-B) 2-DE map of the flowthroughed fraction. A–F windowscorrespond to interesting areas with polypeptides interacting or not with the bioactivated biomaterial. Spots are indicated by labelled arrows for polypeptides present only in gel 1 or only in gel 2. The spots were excised and analysed by nanoLC–MS/MS. (Reproduced with permission from reference (65). Copyright 2011 Elsevier.)

As discussed previously, MALDI-MS analyzes protein samples in solution. In contrast, surface-MALDI-MS has appeared as a unique method for analyzing adsorbed proteins at the material surface. Regarding proteomic studies of adsorbed proteins on biomaterials, sample preparation for MALDI-MS analysis invovles collecting adsorbed proteins via washing steps. For surface-MALDI-MS, the analyte molecules are pre-adsorbed on the solid substrate and the matrix 821 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


solution is then added to the sample to aid matrix crystal formation (56). Kingshott P et al applied surface-MALDI-MS to directly dectect proteins adsorbed on contact lenses (77). Lysozyme and several other smaller proteins were identified on different contact lenses worn by human volumteers. McArthur S et al also characterized the worn HEMA-based contact lenses using surface-MALDI-MS (78). The presence of surface-adsorbed species were detected with molecular weights < 15 kDa and some of them were not identified as ocular proteins. This may indicate a potential conversion of proteins upon adsorption onto synthetic surfaces.

Figure 4. Experiment setup and schematic diagram of machinery used to isolate adherence surface (AS) at cell-biomaterials interface. (Reproduced with permission from reference (66). Copyright 2010. The American Society for Biochemistry and Molecular Biology.)

In addition to MS-based proteomic analysis, protein or polymer microarrays were also used to conduct studies on protein adsorption. Neto AI et al reported a new platform for high-throughput analysis of interactions between biomaterials, proteins and cells using patterned superhydrophobic substrates (79). In their study, they designed superhydrophobic flat substrates with controlled wettable spots for producing microarray chips. The platform was applied to quantitative protein adsorption analysis. Moreover, different media, different numbers/types of cells, different polymeric biomaterials could be arrayed on the platform 822 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


substrate to achieve high-throughput screening. Taylor M et al also reported a methodology for investigating protein adhesion and adsorption to microarrayed combinatorial polymers (80). Fluorescently labelled proteins were used to study protein adsorption on microarrayed synthetic polymers. However, these types of experiments cannot identify unknown proteins or characterize the complete proteome, but probe the specific material-protein interaction using known protein probes. In sum, different experimental settings were used to generate proteome samples from surface adsorbed proteins. To study protein samples in the solution, adsorbed proteins need to be washed off from material surfaces using various buffer solutions to facilitate protein recovery particularly those of relatively low abundance. Thus, protein fractionation is necessary to remove proteins of high abundance and enable detection of proteins of low abundance. In addition, adsorbed proteins on the biomaterial substrate can be mixed with the matrix solution to ensure direct analysis via surface-MALDI-MS. Compared to the array-based method, MS-based methods are potentially powerful tools to conduct comprehensive proteome survey. Soluble Proteins Cells on or adjacent to a biomaterial implant can further mediate the host response through the release of soluble chemical mediators. Monocytes, macrophages, and foreign body giant cells are known to play critical roles during the host response to the biomaterial implants. These cells can produce reactive oxygen species (ROS) to degrade the biomaterial, chemokines to recruit additional inflammatory and wound healing cells (e.g., lymphocytes, neutrophils, macrophages, and fibroblasts) to the injury site, and cytokines to activate or deactivate the inflammatory cells (81). Cytokines are known to have overlapping and redundant activities, and are frequently involved in complex intra/intercellular cross-talks. Therefore, a proteomic approach provides a robust way to investigate the cytokine network. Using protein microarray or MS-based technologies, functional proteins, chemokines, and cytokines secreted from cells can be identified and their release profiles can be generated via appropriate quantification methods. Jones J et al studied the cytokines and chemokines released from biomaterial surface-adherent macrophages and foreign body giant cells using array-based proteomic analysis (81). Biomaterials with varying surface properties such as hydrophilicity/hydrophobicity, cationic/anionic were included and subjected to culture with primary human monocytes. Cytokine screening of the cell culture supernatants was conducted using an array system of 77 cytokines/chemokines. Results showed 24 cytokines and chemokines were detected using antibody-bound membrane protein arrays. The array-based assay provided multiple cytokine/chemokine information from a single qualitative assay, but the results generated were only qualitative. Direct signal comparison between signal intensities cannot represent differences in cytokine production level due to the fact that different proteins have different concentration ranges for detection. Thus, quantification of selected proteins via ELISA was conducted to provide complementary information. 823 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Figure 5. Optimized workflow for proteomic analysis of adherent monocytic U937 cell lysates on sIPN and TCPS using (A) SDS-PAGE and LC/MS and (B) 2D-liquid chromatography and MALDI-Tof/Tof. Adapted from reference (13, 68, 91, 92).

Monocytes interact with materials through adsorbed proteins, which leads to monocyte adhesion (82), activation (83, 84), fusion to form foreign body giant cells (85, 86), and secretion of inflammatory cytokines (87). The interaction between surface adsorbed proteins and cell surface receptors such as integrin is critical to the extent and duration of the host inflammatory response to biomaterials (88–90). To address how surface-adsorbed proteins and phosphorylation inhibitor may affect adherent monocytes, Zuckerman S et al (13, 91) applied nanospray LC/MS based proteomic approaches to study the cell-material interaction (Figure 5A). The model surface was TCPS with or without pre-adsorbed proteins including albumin (Alb) or fibronectin (Fn). Cell lysates were prepared and subjected to SDS-PAGE analysis. Then, gel bands of interest were excised and peptides were collected, desalted, purified and enriched before LC/MS analysis. Studies showed phosphorylation inhibitor AG18 up- or down- regulated the expression of a set of proteins with molecular weight ranging from ~200 to ~23 kDa. Without AG18 and ligand treatment, five proteins at ~65/70 kDa, and 12 proteins at ~42 kDa were identified in cells. With 20 μM AG18 treatment, only 824 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


one phosphorylation related protein titin at ~65/70 kDa was found. No proteins at ~42 kDa was identified in cells with 20, 40, 60 μM AG18 treatment. Thus, AG18 displayed a down-regulation effect on 12 proteins in adherent cells on TCPS. At ~23kDa, 60 and 80 μM of AG18 up-regulated the expression of proteins in cells that are not present in cells treated with 0, 20, or 40 μM AG18. Cells adherent to Fn-adsorbed TCPS were further compared to cells on PBS-adsorbed TCPS to determine the effect different ligand-receptor interactions have upon intracellular protein expression. Six unique proteins were identified in cells on the Fn pre-adsorbed samples at ~42 kDa; nine proteins were identified only in cells on PBS-adsorbed TCPS at ~42 kDa. Peroxiredoxin 1, histone H1.4 and testicular H1 histone were found in the ~23 kDa samples from cells on Fn-adsorbed TCPS (Table IV). No proteins were identified from cells adherent to PBS-adsorbed TCPS at ~23 kDa. Thus, surface-adsorbed Fn was involved in regulating a particular set of proteins in the adherent U937 cells at molecular weight ranging from ~160 to ~23 kDa, demonstrating a change in cellular signaling pathway mediated by surface-adsorbed ligand.

Table IV. The effect of Fn-adsorbed TCPS upon protein expression in adherent U937 cells* Surface ligand

Molecular weight (Da)

Protein

Comparison of ~160 kDa proteins from cells on PBS- or FN-adsorbed TCPS without AG18 PBS

DNA dependent protein kinase catalytic subunit (DNA-dependent protein kinase)

FN

N/Db

99,816 —

Comparison of ~130 kDa proteins from cells on PBS- or FN-adsorbed TCPS without AG18 PBS FN

DNA topoisomerase II beta

180,501

Dedicator of cytokinesis protein 2 (DOCK2 protein)

38,436 —

N/Db

Comparison of ~100 kDa proteins from cells on PBS- or FN-adsporbed TCPS without AG18 PBS FN

—

N/Db DNA topoisomerase II beta

182,578

DNA dependent protein kinase catalytic subunit

465,266



Table IV. (Continued). The effect of Fn-adsorbed TCPS upon protein expression in adherent U937 cells* Surface ligand


Protein

Comparison of ~52 kDa proteins from cells on PBS- or FN-adsorbed TCPS without AG18


PBS

FNb

TPO autoantibody immunoglobulin heavy chain, V-region (TR1.41)

13,367

Anti-colorectal carcinoma heavy chain

50,570

HLA-B-associated transcript 1 (BAT1 gene product)

33,121

Growth regulated nuclear 68 protein

66,881

TPO autoantibody immunoglobulin heavy chain, V-region (TR1.41)

13,367

Anti-colorectal carcinoma heavy chain

50,570

Vimentin

53,653

Mitochondrial ATP synthase beta chain

34,026

Growth regulated nuclear 68 protein

66,881

Comparison of ~42 kDa proteins from cells on PBS- or FN-adsorbed TCPS without AG18

PBS

CTCL tumor antigen se2-2

88,383

Mutant beta-actin (beta’-actin)

41,786

Desmoglein type 1

113,644

Glyceraldehyde-3-phosphate dehydrogenase

36,031

Alpha enolase

47,079

Hqp0256 protein

31,162

Apolipoprotein B precursor

187,126

Sulfide:quinone oxidoreductase, Mitochondrial

49,917

Vimentin

53,653

Ribosomal protein L3

45,440

NCL protein

50,920

Eukaryotic translation elongation factor 1 gamma

50,115



Table IV. (Continued). The effect of Fn-adsorbed TCPS upon protein expression in adherent U937 cells* Surface ligand


FN


Protein Beta actin variant

41,738

Lamin A/C

53,219

Vimentin

53,653

40S ribosomal protein SA (laminin-binding protein)

31,774

NCL protein

50,920

Muscle specific enolase

46,957

Eukaryotic translation initiation factor 2, subunit 3 gamma, 52 kDa

51,077

Eukaryotic translation elongation factor 1 gamma

50,115

Plasminogen activator inhibitor 2

46,615

Comparison of ~23 kDa proteins from cells on PBS- or FN-adsorbed TCPS without AG18 PBS

FN

—

N/Db Peroxiredoxin 1

22,096

Histone H1.4 (histone H1b)

21,721

Testicular H1 histone

22,020

a Common proteins are in bold text. b None detected. from reference (13). Copyright 2006 Elsevier.

*

Reproduced with permission

An in-depth study was conducted to identify intracellular cytoskeletal and inflammatory proteins from adherent U937 cells on surface with pre-adsorbed Fn-derived peptides (91). The tripeptide arginine-glycine-aspartic acid (RGD) is a cell adhesion sequence in Fn and the synergistic sequence proline-histadine-serine-arginine-asparagine (PHSRN) is known to increase cell adhesion to RGD (93). Thus, the study utilized oligopeptides G3RGDG and G3PHSRNG to investigate the effect of these pre-adsorbed peptides on the intracellular signaling of adherent monocytes. Nanospray LC/MS was used to survey and identify proteins from adherent monocytes mediated by surface-adsorbed peptide ligands. Twelve adhesion and inflammatory-related proteins were identified including moesin, heat shock protein 90-β, α- and β-tubulin, elongation factor 1α, β-actin, vimentin, PAI-2, hnRNP A2, HMGB1, CARD5, gp96, and hnRNP D0. The functions of these proteins are summarized in Table V. 827 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Table V. Twelve identified proteins and the related cellular functions*

*

Proteins

Functions

moesin

Couple the actin cytoskeleton to the plasma membrane

heat shock protein 90-β

Bind to tubulin and retard polymerization

α- and β-tubulin

Cytoskeleton proteins

α- and β-tubulin

Localize mRNA to cell protrusions

β-actin and vimentin

Cytoskeleton proteins

PAI-2

Inhibit inflammatory cell migration in ECM remodeling

hnRNP A2

Aid ECM remodeling through collagen folding

HMGB1

Stimulate release of inflammatory cytokines

CARD5

Increase cellular metabolism of pro-IL-1β

gp96

Antigen presentation and CD8+ T-cell activation

hnRNP D0

Initiate complement receptor 2 (CR2) transcription

Adapted from reference (91).

Above studies utilized TCPS as the model system to identify proteins expressed by adherent U937 monocytes. However, protein expression from adherent cells on TCPS may vary significantly from that of adherent cells on surfaces such as hydrogels or other tissue-engineering constructs (92). Therefore, Zuckerman S et al further explored the study in soluble proteins from adherent monocytes on PEG containing hydrogel matrices using the aforementioned proteomic approach. As shown in Figure 5B, cell lysates from adherent U937 cells on TCPS was subjected to LC-MALDI analysis and 43 proteins of interest relevant to monocyte-mediated host inflammatory response were identified and refined. The Src family hematopoietic cell kinase (Hck) and plasminogen activator inhibitor-2 (PAI-2) were selected for an additional study using a small molecule inhibitor and exogenous protein addition, respectively. The study investigated the effect of Hck and PAI-2 on inflammatory cytokine secretion, matrix metalloproteinase (MMP) expression, and the plasminogen system in monocytes adherent to TCPS, RGD-modified semi-interpenetrating networks (sIPNs) containing gelatin and PEG, and PEG-only hydrogels. Interestingly, monoctye chemotactic protein-1 (MCP-1) secretion showed Src-dependence in monocytes on TCPS but not on PEG-only hydrogels. Secretion of the gelatinase matrix metalloproteinase 9 (MMP-9) from monocytes on PEG-only hydrogels was similar to that observed from monocytes on TCPS. Low levels of MMP-9, PAI-2, and MCP-1 were observed from monocytes on sIPNs. These results showed significant surface-dependent secretion of proteins from adherent monocytes. 828 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

In sum, the combination of high-resolution separation techniques and powerful mass spectrometric analysis were developed to efficiently study the proteome of adherent cells on biomaterials without a priori knowledge. However, the techniques discussed above are not quantitative thus cannot provide direct comparisons between proteins. Thus, complementary analyses such as western blot, ELISA, and polymerase chain reaction (PCR) should be performed to obtain more quantitative information.


Limitations and Challenges in Biomaterials Research The essence of proteomics is performing sensitive analysis on specific proteins/peptides in a complex sample. Traditional protein analysis techniques focus only on a few target proteins per analysis, whereas proteomics conducts a global proteome analysis in a high throughput manner (94). For proteomic studies, protein identification is the primary goal and quantitative proteome profiling is another goal. Regarding proteins at the material interface, quantitative protein information is important for comparative analysis of proteins adsorbed or expressed by adherent cells. However, quantification is one of the major challenges for both protein microarrays and MS-based technologies thus requires additional complementary tools for quantification. Labeling technologies have been developed to conduct relative quantitative proteomics, e.g., isotope-coded affinity tags (ICAT) (95), tandem mass tags (TMT) (96, 97), isobaric tags for relative and absolute quantitation (iTRAQ) (98), and SILAC (99, 100). Using LC-MS/MS with spiked internal standards, e.g., a known concentration of isotope-labeled peptides, provides a possible approach to conduct an absolute proteomic quantitation (101, 102). As discussed previously, the competing binding from high abundance proteins and the dynamic range of protein concentrations present a major challenge on both protein microarray and MS-based proteomics. The use of nanocapillary LC/MS to identify phosphotyrosine enriched proteins from cells adherent on peptide- and protein-adsorbed substrates illustrated the difficulty of identifying proteins with very low expression profiles (13, 91). In addition, a limited sample quantity presents another challenge to biomaterial studies. For example, cell lysates obtained from adherent cells on TCPS was around 500 μg and the proteins of interest were on the nanogram scale, e.g., phosphotyrosine protein (~275 ng) (68). Sample pretreatment is thus critical in developing analytical methods of high sensitivity and consistency.

Conclusion Proteomics provides a viable approach to survey global proteome of surfaceadsorbed proteins and soluble proteins from adherent cells. MS-based proteomics provides a powerful tool to identify proteins that are involved in extensive cellmaterial interactions without a priori knowledge. However, biomaterials present unique challenges to proteomic study, namely scarcity of the amount of proteome samples. 829 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

References 1. 2.

3.


4. 5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

Castner, D. G.; Ratner, B. D. Biomedical Surf. Sci.: Foundations to frontiers. Surf. Sci. 2002, 500 (1-3), 28–60. Vroman, L.; Adams, A. L. Findings with recording ellipsometer suggesting rapid exchange of specific plasma proteins at liquid/solid interfaces. Surf. Sci. 1969, 16, 438. Vroman, L.; Adams, A. L. Possible involvement of fibrinogen and proteolysis in surface activation - a study with recording ellipsometer. Thromb. Diath. Haemorrh. 1967, 18 (3-4), 510&. Vroman, L. Effects of hydrophobic surfaces upon blood coagulation. Thrombosis et diathesis haemorrhagica 1964, 10, 455–93. Vroman, L.; Adams, A. L.; Fischer, G. C.; Munoz, P. C. Interaction of high molecular-weight kininogen, factor-xii, and fibrinogen in plasma at interfaces. Blood 1980, 55 (1), 156–159. Sivaraman, B.; Latour, R. A. Time-dependent conformational changes in adsorbed albumin and its effect on platelet adhesion. Langmuir 2012, 28 (5), 2745–2752. Hylton, D. M.; Shalaby, S. W.; Latour, R. A. Direct correlation between adsorption-induced changes in protein structure and platelet adhesion. J. Biomed. Mater. Res. Part A 2005, 73A (3), 349–358. Lehnert, M.; Gorbahn, M.; Rosin, C.; Klein, M.; Koeper, I.; Al-Nawas, B.; Knoll, W.; Veith, M. Adsorption and conformation behavior of biotinylated fibronectin on streptavidin-modified TiOX surfaces studied by SPR and AFM. Langmuir 2011, 27 (12), 7743–7751. Tanaka, M.; Motomura, T.; Kawada, M.; Anzai, T.; Kasori, Y.; Shiroya, T.; Shimura, K.; Onishi, M.; Mochizuki, A. Blood compatible aspects of poly(2-methoxyethylacrylate) (PMEA) - relationship between protein adsorption and platelet adhesion on PMEA surface. Biomaterials 2000, 21 (14), 1471–1481. Katsikogianni, M.; Missirlis, Y. F. Concise review of mechanisms of bacterial adhesion to biomaterials and of techniques used in estimating bacteria-material interactions. Eur. Cells Mater. 2004, 8, 37–57. Francolini, I.; Crisante, F.; Martinelli, A.; D’Ilario, L.; Piozzi, A. Synthesis of biomimetic segmented polyurethanes as antifouling biomaterials. Acta Biomater. 2012, 8 (2), 549–558. Almeida, C. R.; Vasconcelos, D. P.; Goncalves, R. M.; Barbosa, M. A. Enhanced mesenchymal stromal cell recruitment via natural killer cells by incorporation of inflammatory signals in biomaterials. J. R. Soc. Interface 2012, 9 (67), 261–271. Zuckerman, S. T.; Kao, W. J. Effect of surface-adsorbed proteins and phosphorylation inhibitor AG18 on intracellular protein expression in adherent macrophages. Biomaterials 2006, 27 (20), 3745–57. Wang, X.; Schmidt, D. R.; Joyce, E. J.; Kao, W. J. Application of MS-based proteomics to study serum protein adsorption/absorption and complement C3 activation on poly(ethylene glycol) hydrogels. J. Biomater. Sci., Polym. Ed. 2011, 22 (10), 1343–1362. 830 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


15. Wilkins, M. Proteomics data mining. Expert Rev. Proteomics 2009, 6, 599–603. 16. Gygi, S. P.; Aebersold, R. Mass spectrometry and proteomics. Curr. Opin. Chem. Biol. 2000, 4 (5), 489–494. 17. MacBeath, G.; Schreiber, S. L. Printing proteins as microarrays for highthroughput function determination. Science 2000, 289 (5485), 1760–1763. 18. Hale, J. E.; Gelfanova, V.; Ludwig, J. R.; Knierman, M. D. Application of proteomics for discovery of protein biomarkers. Briefings Funct. Genomics Proteomics 2003, 2 (3), 185–93. 19. MacBeath, G. Protein microarrays and proteomics. Nat. Genet. 2002, 32, 526–532. 20. Gonzalez-Gonzalez, M.; Jara-Acevedo, R.; Matarraz, S.; Jara-Acevedo, M.; Paradinas, S.; Sayagues, J. M.; Orfao, A.; Fuentes, M. Nanotechniques in proteomics: Protein microarrays and novel detection platforms. European Journal of Pharm. Sci. 2012, 45 (4), 499–506. 21. Zarate, X.; Henderson, D. C.; Phillips, K. C.; Lake, A. D.; Galbraith, D. W. Development of high-yield autofluorescent protein microarrays using hybrid cell-free expression with combined Escherichia coli S30 and wheat germ extracts. Proteome Sci. 2010, 8. 22. Nand, A.; Gautam, A.; Perez, J. B.; Merino, A.; Zhu, J. Emerging technology of in situ cell free expression protein microarrays. Protein Cell 2012, 3 (2), 84–8. 23. Tang, C. K.; Vaze, A.; Rusling, J. F. Fabrication of immunosensor microwell arrays from gold compact discs for detection of cancer biomarker proteins. Lab Chip 2012, 12 (2), 281–286. 24. Stoevesandt, O.; Taussig, M. J.; He, M. Y. Protein microarrays: high-throughput tools for proteomics. Exp. Rev. Proteomics 2009, 6 (2), 145–157. 25. Liotta, L. A.; Espina, V.; Mehta, A. I.; Calvert, V.; Rosenblatt, K.; Geho, D.; Munson, P. J.; Young, L.; Wulfkuhle, J.; Petricoin, E. F. Protein microarrays: meeting analytical challenges for clinical applications. Cancer Cell 2003, 3 (4), 317–325. 26. Talapatra, A.; Rouse, R.; Hardiman, G. Protein microarrays: challenges and promises. Pharmacogenomics 2002, 3 (4), 527–536. 27. Bally, M.; Syed, S.; Binkert, A.; Kauffmann, E.; Ehrat, M.; Voros, J. Fluorescent vesicles for signal amplification in reverse phase protein microarray assays. Anal. Biochem. 2011, 416 (2), 145–151. 28. Alivisatos, P. The use of nanocrystals in biological detection. Nat. Biotechnol. 2004, 22 (1), 47–52. 29. Aebersold, R.; Mann, M. Mass spectrometry-based proteomics. Nature 2003, 422 (6928), 198–207. 30. Strupat, K.; Karas, M.; Hillenkamp, F. 2,5-dihydroxybenzoic acid - a new matrix for laser desorption ionization mass-spectrometry. Int. J. Mass Spectrom. Ion Processes 1991, 111, 89–102. 31. Liu, H. B.; Sadygov, R. G.; Yates, J. R. A model for random sampling and estimation of relative protein abundance in shotgun proteomics. Anal. Chem. 2004, 76 (14), 4193–4201. 831 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


32. Wu, S. L.; Huehmer, A. F. R.; Hao, Z. Q.; Karger, B. L. On-line LC-MS approach combining collision-induced dissociation (CID), electron-transfer dissociation (ETD), and CID of an isolated charge-reduced species for the trace-level characterization of proteins with post-translational modifications. J. Proteome Res. 2007, 6 (11), 4230–4244. 33. Samgina, T. Y.; Vorontsov, E. A.; Gorshkov, V. A.; Artemenko, K. A.; Nifant’ev, I. E.; Kanawati, B.; Schmitt-Kopplin, P.; Zubarev, R. A.; Lebedev, A. T. Novel cysteine tags for the sequencing of non-tryptic disulfide peptides of anurans: ESI-MS study of fragmentation efficiency. J. Am. Soc. Mass Spectrom. 2011, 22 (12), 2246–2255. 34. Schirmer, E. C.; Florens, L.; Guan, T. L.; Yates, J. R.; Gerace, L. Nuclear membrane proteins with potential disease links found by subtractive proteomics. Science 2003, 301 (5638), 1380–1382. 35. Cheeseman, I. M.; Anderson, S.; Jwa, M.; Green, E. M.; Kang, J.-s.; Yates, J. R., III; Chan, C. S. M.; Drubin, D. G.; Barnes, G. Phospho-regulation of kinetochore-microtubule attachments by the Aurora kinase IpI1p. Cell 2002, 111 (2), 163–172. 36. Leng, J.; Wang, H.; Zhang, L.; Zhang, J.; Wang, H.; Cai, T.; Yao, J.; Guo, Y. Integration of high accuracy n-terminus identification in peptide sequencing and comparative protein analysis via isothiocyanate-based isotope labeling reagent with ESI Ion-trap TOF MS. J. Am. Soc. Mass Spectrom. 2011, 22 (7), 1204–1213. 37. Domon, B.; Aebersold, R. Options and considerations when selecting a quantitative proteomics strategy. Nat. Biotechnol. 2010, 28 (7), 710–721. 38. Sze, S. K.; Ge, Y.; Oh, H.; McLafferty, F. W. Top-down mass spectrometry of a 29-kDa protein for characterization of any posttranslational modification to within one residue. Proc. Natl. Acad. Sci. U.S.A. 2002, 99 (4), 1774–1779. 39. Kelleher, N. L. Top-down proteomics. Anal. Chem. 2004, 76 (11), 197A–203A. 40. Valaskovic, G. A.; Kelleher, N. L.; McLafferty, F. W. Attomole protein characterization by capillary electrophoresis mass spectrometry. Science 1996, 273 (5279), 1199–1202. 41. Jiang, X. G.; Ye, M. L.; Zou, H. F. Technologies and methods for sample pretreatment in efficient proteome and peptidome analysis. Proteomics 2008, 8 (4), 686–705. 42. Paulo, J. A.; Kadiyala, V.; Banks, P. A.; Steen, H.; Conwell, D. L. Mass spectrometry-based proteomics for translational research: a technical overview. Yale J. Biol. Med. 2012, 85 (1), 59–73. 43. Ward, W. W.; Swiatek, G. Protein Purification. Curr. Anal. Chem. 2009, 5 (2), 85–105. 44. Jiang, L.; He, L.; Fountoulakis, M. Comparison of protein precipitation methods for sample preparation prior to proteomic analysis. J. Chromatogr., A 2004, 1023 (2), 317–320. 45. Azarkan, M.; Huet, J.; Baeyens-Volant, D.; Looze, Y.; Vandenbussche, G. Affinity chromatography: A useful tool in proteomics studies. J. Chromatogr., B 2007, 849 (1-2), 81–90. 832 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


46. Lescuyer, P.; Hochstrasser, D. F.; Sanchez, J. C. Comprehensive proteome analysis by chromatographic protein prefractionation. Electrophoresis 2004, 25 (7-8), 1125–1135. 47. Leitner, A.; Lindner, W. Current chemical tagging strategies for proteome analysis by mass spectrometry. J. Chromatogr., B 2004, 813 (1-2), 1–26. 48. Weinberger, S. R.; Viner, R. I.; Ho, P. Tagless extraction-retentate chromatography: a new global protein digestion strategy for monitoring differential protein expression. Electrophoresis 2002, 23 (18), 3182–3192. 49. Kuyama, H.; Watanabe, M.; Toda, C.; Matsuo, E.-i.; Ando, E.; Tanaka, K.; Nishimura, O. An approach to quantitative proteome analysis by labeling tryptophan residues. Mol. Cell. Proteomics 2004, 3 (10), S289–S289. 50. Ji, J. Y.; Chakraborty, A.; Geng, M.; Zhang, X.; Amini, A.; Bina, M.; Regnier, F. Strategy for qualitative and quantitative analysis in proteomics based on signature peptides. J. Chromatogr., B 2000, 745 (1), 197–210. 51. Limber, G. K.; Mason, R. G. Studies of proteins elutable from cuprophane exposed to human plasma. Thrombosis Res, 1975, 6 (5), 421–430. 52. Weathersby, P. K.; Horbett, T. A.; Hoffman, A. S. New method for analysis of adsorbed plasma-protein layer on biomaterial surfaces. Trans. - Am. Soc. Artif. Intern. Organs 1976, 22, 242–252. 53. Mulzer, S. R.; Brash, J. L. Identification of plasma-proteins adsorbed to hemodialyzers during clinical use. J. Biomed. Mater. Res. 1989, 23 (12), 1483–1504. 54. Elbert, D. L. Proteomic and advanced biochemical techniques to study protein adsorption. In Comprehensive Biomaterials, 1st ed.; Elsevier: New York, 2011; Vol. 3. 55. Power, K. A.; Fitzgerald, K. T.; Gallagher, W. M. Examination of cell-hostbiomaterial interactions via high-throughput technologies: A re-appraisal. Biomaterials 2010, 31 (26), 6667–6674. 56. Griesser, H. J.; Kingshott, P.; McArthur, S. L.; McLean, K. M.; Kinsel, G. R.; Timmons, R. B. Surface-MALDI mass spectrometry in biomaterials research. Biomaterials 2004, 25 (20), 4861–4875. 57. Hu, W. J.; Eaton, J. W.; Tang, L. P. Molecular basis of biomaterial-mediated foreign body reactions. Blood 2001, 98 (4), 1231–1238. 58. Nakanishi, K.; Sakiyama, T.; Imamura, K. On the adsorption of proteins on solid surfaces, a common but very complicated phenomenon. J. Biosci. Bioeng. 2001, 91 (3), 233–244. 59. Higuchi, A.; Sugiyama, K.; Yoon, B. O.; Sakurai, M.; Hara, M.; Sumita, M.; Sugawara, S.; Shirai, T. Serum protein adsorption and platelet adhesion on pluronic (TM)-adsorbed polysulfone membranes. Biomaterials 2003, 24 (19), 3235–3245. 60. Chen, H.; Yuan, L.; Song, W.; Wu, Z. K.; Li, D. Biocompatible polymer materials: Role of protein-surface interactions. Progr. Polym. Sci. 2008, 33 (11), 1059–1087. 61. Welle, A.; Grunze, M.; Tur, D. Plasma protein adsorption and platelet adhesion on poly bis(trifluoroethoxy)phosphazene and reference material surfaces. J. Colloid Interface Sci. 1998, 197 (2), 263–274. 833 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


62. Schmidt, D.; Joyce, E. J.; Kao, W. J. Fetal bovine serum xenoproteins modulate human monocyte adhesion and protein release on biomaterials in vitro. Acta Biomater. 2011, 7 (2), 515–25. 63. Hamada, I.; Hunter, A. C.; Szebeni, J.; Moghimi, S. M. Poly(ethylene glycol)s generate complement activation products in human serum through increased alternative pathway turnover and a MASP-2-dependent process. Mol. Immunol. 2008, 46 (2), 225–232. 64. Ying, S. C.; Gewurz, A. T.; Jiang, H. X.; Gewurz, H. Human serum amyloid-p component oligomers bind and activate the classical complement pathway via residue-14-26 and residue-76-92 of the a-chain collagen-like region of C1Q. J. Immunol. 1993, 150 (1), 169–176. 65. Oughlis, S.; Lessim, S.; Changotade, S.; Bollotte, F.; Poirier, F.; Helary, G.; Lataillade, J. J.; Migonney, V.; Lutomski, D. Development of proteomic tools to study protein adsorption on a biomaterial, titanium grafted with poly(sodium styrene sulfonate). J. Chromatogr., B 2011, 879 (31), 3681–3687. 66. Tong, W. Y.; Liang, Y. M.; Tam, V.; Yip, H. K.; Kao, Y. T.; Cheung, K. M.; Yeung, K. W.; Lam, Y. W. Biochemical characterization of the cellbiomaterial interface by quantitative proteomics. Mol. Cell. Proteomics 2010, 9 (10), 2089–98. 67. Feltkamp, C. A.; Pijnenburg, M. A. P.; Roos, E. Organization of talin and vinculin in adhesion plaques of wet-cleaved chicken-embryo fibroblasts. J. Cell Sci. 1991, 100, 579–587. 68. Drees, F.; Reilein, A.; Nelson, W. J. Cell-adhesion assays: fabrication of an E-cadherin substratum and isolation of lateral and Basal membrane patches. Methods Mol. Biol. 2005, 294, 303–20. 69. Cattelino, A.; Albertinazzi, C.; Bossi, M.; Critchley, D. R.; de Curtis, I. A cell-free system to study regulation of focal adhesions and of the connected actin cytoskeleton. Mol. Biol. Cell 1999, 10 (2), 373–391. 70. Cohen, C. M.; Kalish, D. I.; Jacobson, B. S.; Branton, D. Membrane isolation on polylysine-coated beads - plasma-membrane from hela-cells. J. Cell Biol. 1977, 75 (1), 119–134. 71. Aggeler, J.; Werb, Z. Initial events during phagocytosis by macrophages viewed from outside and inside the cell - membrane-particle interactions and clathrin. J. Cell Biol. 1982, 94 (3), 613–623. 72. Jacobson, B. S.; Branton, D. Plasma-membrane - rapid isolation and exposure of cytoplasmic surface by use of positively charged beads. Science 1977, 195 (4275), 302–304. 73. Derhami, K.; Wolfaardt, J. F.; Wennerberg, A.; Scott, P. G. Quantifying the adherence of fibroblasts to titanium and its enhancement by substrate-attached material. J. Biomed. Mater. Res. 2000, 52 (2), 315–322. 74. Derhami, K.; Zheng, J.; Li, L.; Wolfaardt, J. F.; Scott, P. G. Proteomic analysis of human skin fibroblasts grown on titanium: novel approach to study molecular biocompatibility. J. Biomed. Mater. Res. 2001, 56 (2), 234–244. 75. Ong, S.-E.; Mann, M. A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC). Nat. Protoc. 2006, 1 (6), 2650–2660. 834 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


76. Backovic, A.; Huang, H. L.; Del Frari, B.; Piza, H.; Huber, L. A.; Wick, G. Identification and dynamics of proteins adhering to the surface of medical silicones in vivo and in vitro. J. Proteome Res. 2007, 6 (1), 376–381. 77. Kingshott, P.; St John, H. A. W.; Griesser, H. J. Direct detection of proteins adsorbed on synthetic materials by matrix-assisted laser desorption ionization-mass spectrometry. Anal. Biochem. 1999, 273 (2), 156–162. 78. McArthur, S. L.; McLean, K. M.; St John, H. A. W.; Griesser, H. J. XPS and surface-MALDI-MS characterisation of worn HEMA-based contact lenses. Biomaterials 2001, 22 (24), 3295–3304. 79. Neto, A. I.; Custodio, C. A.; Song, W. L.; Mano, J. F. High-throughput evaluation of interactions between biomaterials, proteins and cells using patterned superhydrophobic substrates. Soft Matter 2011, 7 (9), 4147–4151. 80. Taylor, M.; Urquhart, A. J.; Anderson, D. G.; Williams, P. M.; Langer, R.; Alexander, M. R.; Davies, M. C. A methodology for investigating protein adhesion and adsorption to microarrayed combinatorial polymers. Macromol. Rapid Commun. 2008, 29 (15), 1298–1302. 81. Jones, J. A.; Chang, D. T.; Meyerson, H.; Colton, E.; Kwon, I. K.; Matsuda, T.; Anderson, J. M. Proteomic analysis and quantification of cytokines and chemokines from biomaterial surface-adherent macrophages and foreign body giant cells. J. Biomed. Mater. Res.. Part A 2007, 83A (3), 585–596. 82. Juliano, R. L. Signal transduction by cell adhesion receptors and the cytoskeleton: functions of integrins, cadherins, selectins, and immunoglobulin-superfamily members. Annu. Rev. Pharmacol. Toxicol. 2002, 42, 283–323. 83. MacEwan, M. R.; Brodbeck, W. G.; Matsuda, T.; Anderson, J. M. Monocyte/ lymphocyte interactions and the foreign body response: in vitro effects of biomaterial surface chemistry. J. Biomed. Mater. Res., Part A 2005, 74A (3), 285–293. 84. Mograbi, B.; Rochet, N.; Emiliozzi, C.; Rossi, B. Adhesion of human monocytic THP-1 cells to endothelial cell adhesion molecules or extracellular matrix proteins via beta(1) integrins regulates heparin binding epidermal growth factor-like growth factor (HB-EGF) expression. Eur. Cytokine Network 1999, 10 (1), 79–86. 85. Collier, T. O.; Anderson, J. M. Protein and surface effects on monocyte and macrophage adhesion, maturation, and survival. J. Biomed. Mater. Res. 2002, 60 (3), 487–496. 86. Anderson, J. M.; Rodriguez, A.; Chang, D. T. Foreign body reaction to biomaterials. Semin. Immunol. 2008, 20 (2), 86–100. 87. Maxeiner, H.; Husemann, J.; Thomas, C. A.; Loike, J. D.; El Khoury, J.; Silverstein, S. C. Complementary roles for scavenger receptor A and CD36 of human monocyte-derived macro-phages in adhesion to surfaces coated with oxidized low-density lipoproteins and in secretion of H2O2. J. Exp. Med. 1998, 188 (12), 2257–2265. 88. Hamilton, J. A. Nondisposable materials, chronic inflammation, and adjuvant action. J. Leukocyte Biol. 2003, 73 (6), 702–712. 835 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


89. Schmidt, D. R.; Kao, W. J. Monocyte activation in response to polyethylene glycol hydrogels grafted with RGD and PHSRN separated by interpositional spacers of various lengths. J. Biomed. Mater. Res., Part A 2007, 83A (3), 617–625. 90. Schmidt, D. R.; Kao, W. J. The interrelated role of fibronectin and interleukin1 in biomaterial-modulated macrophage function. Biomaterials 2007, 28 (3), 371–82. 91. Zuckerman, S. T.; Kao, W. J. LC/MS identification of 12 intracellular cytoskeletal and inflammatory proteins from monocytes adherent on surface-adsorbed fibronectin-derived peptides. J. Biomed. Mater. Res., Part A 2008, 85 (2), 513–29. 92. Zuckerman, S. T.; Brown, J. F.; Kao, W. J. Identification of regulatory Hck and PAI-2 proteins in the monocyte response to PEG-containing matrices. Biomaterials 2009, 30 (23-24), 3825–33. 93. Ruoslahti, E. RGD and other recognition sequences for integrins. Annu. Rev. Cell Develop. Biol. 1996, 12, 697–715. 94. Din, S.; Lennon, A. M.; Arnott, I. D. R.; Hupp, T.; Satsangi, J. Technology insight: the application of proteomics in gastrointestinal disease. Nat. Clin. Pract. Gastroenterol. Hepatol. 2007, 4 (7), 372–385. 95. Sohn, C. H.; Lee, J. E.; Sweredoski, M. J.; Graham, R. L. J.; Smith, G. T.; Hess, S.; Czerwieniec, G.; Loo, J. A.; Deshaies, R. J.; Beauchamp, J. L. Click Chemistry Facilitates Formation of Reporter Ions and Simplified Synthesis of Amine-Reactive Multiplexed Isobaric Tags for Protein Quantification. J. Am. Chem. Soc. 2012, 134 (5), 2672–2680. 96. Guo, J.; Prokai, L. To tag or not to tag: A comparative evaluation of immunoaffinity-labeling and tandem mass spectrometry for the identification and localization of posttranslational protein carbonylation by 4-hydroxy-2-nonenal, an end-product of lipid peroxidation. J. Proteomics 2011, 74 (11), 2360–2369. 97. Coombs, K. M. Quantitative proteomics of complex mixtures. Exp. Rev. Proteomics 2011, 8 (5), 659–677. 98. Chang, K.-P.; Yu, J.-S.; Chien, K.-Y.; Lee, C.-W.; Liang, Y.; Liao, C.-T.; Yen, T.-C.; Lee, L.-Y.; Huang, L.-L.; Liu, S.-C.; Chang, Y.-S.; Chi, L.-M. Identification of PRDX4 and P4HA2 as Metastasis-Associated Proteins in Oral Cavity Squamous Cell Carcinoma by Comparative Tissue Proteomics of Microdissected Specimens Using iTRAQ Technology. J. Proteome Res. 2011, 10 (11), 4935–4947. 99. Austin, R. J.; Kuestner, R. E.; Chang, D. K.; Madden, K. R.; Martin, D. B. SILAC Compatible Strain of Pichia pastoris for Expression of Isotopically Labeled Protein Standards and Quantitative Proteomics. J. Proteome Res. 2011, 10 (11), 5251–5259. 100. Datta, A.; Qian, J.; Khor, T. H.; Teo, M. T.; Heese, K.; Sze, S. K. quantitative neuroproteomics of an in vivo rodent model of focal cerebral ischemia/reperfusion injury reveals a temporal regulation of novel pathophysiological molecular markers. J. Proteome Res. 2011, 10 (11), 5199–5213. 836 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


101. Huang, Z. L.; Wang, H. L.; Huang, H. L.; Xia, L. H.; Chen, C. S.; Qiu, X. X.; Chen, J. B.; Chen, S. S.; Liang, W. H.; Huang, M.; Lang, L.; Zheng, Q. L.; Wu, B. H.; Lai, G. C. iTRAQ-based proteomic profiling of human serum reveals down-regulation of platelet basic protein and apolipoprotein B100 in patients with hematotoxicity induced by chronic occupational benzene exposure. Toxicology 2012, 291 (1-3), 56–64. 102. Xiong, Q.; Zhong, Q.; Zhang, J.; Yang, M.; Li, C.; Zheng, P.; Bi, L.-J.; Ge, F. Identification of novel mir-21 target proteins in multiple myeloma cells by quantitative proteomics. J. Proteome Res. 2012, 11 (4), 2078–90.


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