Protein Patterns Fabricated by Affinity-Based ... - ACS Publications

Chapter 36

Downloaded by UNIV OF ARIZONA on December 13, 2012 | http://pubs.acs.org Publication Date (Web): December 12, 2012 | doi: 10.1021/bk-2012-1120.ch036

Protein Patterns Fabricated by Affinity-Based Surface Ligand Selection from Protein Solution Mixtures on a Polymer Hydrogel Substrate Hironobu Takahashi,1 David G. Castner,2 and David W. Grainger*,3 1Institute

of Advanced Biomedical Engineering and Science Tokyo Women’s Medical University (TWIns), 8-1 Kawadacho Shinjuku, Tokyo 162-8666, Japan 2National ESCA and Surface Analysis Center for Biomedical Problems, Departments of Chemical Engineering and Bioengineering, Box 351750, University of Washington, Seattle, Washington 98195-1750 U.S.A. 3Departments of Pharmaceutics and Pharmaceutical Chemistry, and Bioengineering Health Sciences, University of Utah, Salt Lake City, Utah 84112-5820 U.S.A. *E-mail: [email protected]. Phone: +1 801-585-7824. Fax: +1 801-5813674

We review a recent surface patterning, modification and protein-surface affinity selection strategy that yields high-fidelity protein patterns by protein-ligand selection from solutions at surfaces – so-called affinity-based surface “protein sorting”. The approach exploits pre-patterned high affinity ligands immobilized on polymer surface chemistry known to effectively inhibit non-specific protein adsorption and cell adhesion, while providing a reliable capacity for specific, dense, uniform immobilization of desired molecules to pre-designed patterns of reactive chemistry. Soluble proteins select ligands at these surfaces from solution by affinity-matched surface engagement, producing two distinct types of protein monolayer organization on surfaces: spatial (e.g., two different proteins selecting their respective ligands in spatial patterns on surfaces) and orientational (e.g., antibody binding to ligands specific to their Fab versus Fc domains). These ligand patterns and surface-protein interactions are analyzed, and spatially and

© 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.


orientationally verified using time-of-flight secondary ion mass spectrometry (TOF-SIMS). Photolithographic patterning of reactive ester groups on a non-fouling PEG-coated surface facilitate ligand coupling with high fidelity or patterns of peptides, proteins, and mammalian cells. Furthermore, two different surface-patterned affinity ligands, facilitate binding of two different proteins (e.g., streptavidin and HaloTag®), co-patterned self-selectively from their mixed solution on the non-fouling surface. As a unique label-free chemically selective surface imaging technique, TOF-SIMS analysis can distinguish differences in amino acid composition between bound streptavidin and HaloTag® proteins, and also between Fab and Fc domains on surface-immobilized antibodies. Since antibody orientation and spatial patterning remains important to antibody-based surface capture assays, TOF-SIMS imaging is useful to correlate immobilized biomolecule bioactivity. Patterned RGD peptides can also be imaged, and maintain high-fidelity cell patterns in long-term serum-containing cultures. Keywords: TOF-SIMS imaging; protein sorting; affinity ligands; Surface Analysis; antibody orientation; protein mixtures; protein patterning; multivariate analysis; principal component analysis

1. Introduction Surface patterning techniques are often used to spatially regulate local chemical reactions with immobilized biomolecules such as oligonucleotides, proteins, and peptides for bioassays and to create microenvironments for organizing surface cell and bacterial activities (1–5). DNA microarray technology in particular has asserted its value in genomic research in diverse forms (6, 7). However, genomic message and transcriptional information is several steps away from direct information regarding target proteins. With validated performance and validation, protein microarrays provide new potential for exploitation in a variety of biomedical and biotechnological applications including biosensors, drug screening, and fundamental studies involving proteomics in pathogenesis and aspects of cell biology (4, 8–13). Unlike oligonucleotides, however, proteins are highly diverse in terms of charge, hydrophobic character, structure and other biochemical factors that affect their stability and behavior at interfaces. Protein microarrays therefore require well-defined immobilization methods that preserve protein structure-property relationships, with surface chemistry and fabrication techniques that accommodate wide varieties of different proteins. 782 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Routine surface patterning technologies and microcontact printing methods are frequently used to produce nano- or micro-patterns of biomolecules on surfaces (14, 15). A number of such techniques (e.g., photolithography) have demonstrated spatio-selective bio-immobilization on a variety of substrates (16–19). These are then commonly used to pursue cell patterning methods (20–22) for applications biochips (23–25), co-cultures (26–28), tissue engineering (29, 30), cell-based biosensors (9). Successful performance in these applications requires that protein-immobilized platforms exhibit reliable specific immobilization together with general background resistance to non-specific protein adsorption (fouling) to these surfaces. Few surfaces reliably yield these properties. One convenient protein immobilization commercial method coats glass substrates with nitrocellulose or poly-L-lysine such that proteins passively adsorb through non-specific binding interactions (31, 32). While high densities of proteins can be physisorbed on these surfaces, these platforms are limited in their ability to obtain high capture sensitivity and selectivity in bioassay systems due to high surface population fractions of randomly oriented and partially denatured adsorbed proteins (10). Retention of immobilized bioactivity of surface-resident proteins requires careful surface chemistry designs that maximize immobilization density, retain protein function and eliminate non-specific capture, often from complex mixtures containing thousands of components (e.g., serum or cell lysate).

2. Nonfouling Protein-Capture Polymer Surfaces Inhibiting non-specific biomolecular binding and cellular adhesion to solid surfaces is critical to in vitro bioassay performance whose metric is specific analyte capture. Microarray formats often print proteins at high densities in micron-sized areas, often with no regard for printed area thickness. These pre-printed, surface-bound and dried spots are probed for various binding and biochemical activities. Traditional materials used for immunoassay and DNA microarraying (e.g., polystyrene, poly(vinylidene fluoride) (PVDF) and nitrocellulose) are often not compatible for protein microarrays (10, 32). These surfaces often yield insufficient immobilized protein density and retained bioactivity, and can have unacceptable wetting or spotting properties limiting assay reproducibility, reliability and sensitivity. In contrast, thin hydrophilic coatings are commonly exploited to provide biologically “non-fouling” surface chemistries for biomedical and biotechnology applications (13, 33, 34). Among the many chemistries reported, poly(ethylene glycol) (PEG) polymers and PEG-like materials have an extensive history (35–37). Numerous surface treatment methods to produce PEG interfaces have been reported, including PEG grafting (38, 39), adsorptive chemistries (40, 41), and oligo-PEG-terminated self-assembled monolayers (42, 43). Despite intensive work in this area, many surface chemistries suffer from limitations, hindering widespread adoption. Many coating methods require multiple, difficult-to-control processing steps to achieve a high-quality final films. Furthermore, these surface chemistries, when scaled beyond research production, often do not exhibit non-fouling performance required for biomedical utility in sensors, assays, and medical devices. 783 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Additionally, many coating formulations contain reactive chemistries necessary for immobilization (e.g., N-hydroxysuccinimide (NHS), sulfhydryl, maleimide, vinylsulfones, nitrophenylesters), often reactive with amine-based nucleophiles commonly found in a range of biomolecules including proteins, enzymes, chromophore dyes, and commercially derivatized oligonucleotides. Specifically, NHS is widely used as an activating reagent for carboxylic acid-based coupling in biochemistry (44), specifically in bioconjugation and bio-immobilization, as well as in a number of commercial chemistry kits and assay, including biodiagnostic arrays, biochips and biosensors (9, 12, 23, 24, 45). With these intrinsic, broad chemical reactivity, careful step-wise methods are necessary to immobilize desired molecules then remove residual reactivity across the surface and retain high resistance to non-specific background adsorption. Many coatings suffer performance reductions in these surface chemical sequences used for spatially controlled surface immobilization. 2.1. Patterning of Bioimmobilization Reactivity in Low-Background Polymer Coatings Surface patterning methods extensively used to immobilize proteins and other bioactive molecules for biomedical applications (1, 25, 46) must spatially localize and control their immobilized targets, then remain passive against other species not targeted for immobilization. This is despite the chemical reactivity similarities between immobilization targets (e.g., antibodies or streptavidin) and non-targets (e.g., over 20,000 different proteins in human plasma samples or cell lysates). This is often discriminated using masking steps that cover unreacted surface chemistry with a sacrificial species (e.g., albumin), or by consuming the residual reactivity by a small molecule substitution that retains low non-specific binding (e.g., eliminating NHS with methoxyethylamine providing methoxy (MeO)-capping of NHS groups) (47). In microarraying methods, immobilized molecules are spatially printed using contact or non-contact printing methods into designated surface locations and chemical immobilization ensues spontaneously within seconds as the aqueous solution droplet evaporates rapidly. Subsequent stringency rinsing and processing steps over the entire surface allow masking or capping of residual surface reactive chemistry in unprinted spatial areas (48). Additionally, routine photolithography techniques can also be used to micropattern NHS surface chemistry directly, allowing spatial deactivation of chemistry prior to desired spatial bio-immobilization, or sequential protection/deprotection of NHS groups in different spatial areas for different pattern exposures (49–51). Using this process, NHS (reactive) and MeO-terminated (deactivated) surface patterns are obtained and a variety of biomolecule patterns can be produced in different designs for different purposes. For protein immobilization purposes, we and many others have used a commercial multi-component PEG-based coating formulation supplied on low-fluorescence glass slides (Optichem®, Accelr8 Technologies, USA, marketed as Slide H™, Schott-Nexterion, Germany, see http://www.us.schott.com/ nexterion/english/products/coated_slides/thin_film.html for application notes and updated technical publication bibliography for this chemistry use). The 784 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


polymer chemistry and coating is unique in that it: (1) is applied in a single, reproducible, solution-based coating step; (2) can be applied to diverse substrate materials without the use of special primers; and (3) is readily functionalized to provide several known specific immobilization chemistries. The polymer base coating formulation comprises a single mixture of three components: (1) the active immobilization component, (2) matrix-forming component, and (3) cross-linking component (52). Figure 1 shows the active component as a heterobifunctional PEG polymer (NHS-PEG-aminosilane) bearing NHS end groups that serve as the reactive PEG-tethered functional groups in the final coating. The other PEG terminal group (aminosilane) provides covalent crosslinking capabilities and both attachment within the coating matrix and to certain substrates. Added polyoxyethylene sorbitan tetraoleate serves as the matrix-forming film component, and in some formulations, an azidosilane is used as a thermally or photochemically reactive cross-linker for the matrix and surface anchoring. The azide converts to a reactive nitrene that rapidly and non-specifically inserts into aliphatic or aromatic bonds within the coating matrix and into organic surfaces such as polystyrene, polycarbonates, or polypropylene. The multiple reaction pathways convert the soluble three-component mixture to a stable, resilient functional coating through diverse cross-linking, adhesion, and covalent attachment mechanisms upon curing. Importantly, both film uniformity and swelling properties as well as intrinsic NHS activity in the final film can be adjusted by changing component ratios and concentrations. 2.2. Polymer Background Nonspecific Adsorption Properties After fabrication, NHS groups are easily converted to MeO-terminated groups by slide immersion into a 2-methoxyethylamine solution (50 mM in 50 mM borate buffer at pH 9 for 1 hour (47). The deactivated polymer film provides significant inhibition of non-specific serum protein adsorption and also PCR reagent uptake under rigorous in vitro testing conditions. Exposed to 10% goat serum as a model for in vitro bioassay formats, the polymer provides 97% reduction in non-specifically adsorbed serum components over controls. Single proteins such as fibrinogen and lysozyme are also inhibited significantly in binding non-specifically to the surface. As a functional assay, serum protein adsorption is low enough that no adhesion-dependent mammalian cell lines tested in 10% fetal bovine serum (e.g., macrophage, fibroblast, endothelial phenotypes) will attach to the surface (unpublished data) (49, 52). Bacteria adhesion - a critical first step in the cascade of processes from surface colonization to biofilm formation – is also severely inhibited. OptiChem® is shown effective in vitro in reducing the adhesion of different clinical bacterial isolates by several orders of magnitude in several different flowing actual biological media such as saliva, urine, and plasma, and delaying ultimate biofilm formation in flow-cell extended cultures (53). Additionally, two model bacterial strains (clinical strains of Staphylococcus aureus as model Gram-positive cocci and Klebsiella pneumoniae as model Gram-negative rods were easily removed at the lowest shear rate (4.6 sec-1) in a microfluidic flow cell, reflecting their poor adhesion in biological fluids. For these representative strains, surface performance is qualitatively comparable to that 785 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


seen on ethylene oxide-terminated SAMs (43) and long chain-length PEG brushes (54). Lastly, the OptiChem® coating effectively inhibited biofilm formation in vitro during 960 min of growth in a well-characterized flow chamber, while the adsorption of plasma proteins produced a small loss of the anti-adhesive coating activity. Biofilms produced in vitro were slightly less viable on the coating than on glass. In a mouse in vivo pocket implant infection model, OptiChem®-coated silicone rubber discs were not colonized by staphylococci, while bare silicone rubber discs were consistently colonized (55). This is a collective, consistent functional and in vitro/in vivo correlating testament to the low non-specific binding properties of this polymer coating – a critical pre-requisite for patterned applications (Figure 2).

3. Time-of-Flight Secondary Ion Mass Spectrometry (TOF-SIMS) Chemical State Imaging Techniques for Surface Analysis of Immobilized Proteins TOF-SIMS is a widely used surface analysis technique for characterization of biomaterial surfaces (56, 57). Specifically, TOF-SIMS chemical state imaging is a powerful tool for visualizing the distribution of surface chemical compositions at micron resolution (24, 58). Although X-ray photoelectron spectroscopy (XPS) is also extremely useful for surface chemistry analysis, it does not have sufficient molecular specificity (59). Particularly for this PEG-based polymer coating, the atomic percentage of XPS-detected nitrogen signals cannot be used to uniquely quantify the NHS chemistry on the polymer surface due to the presence of more than one nitrogen-containing species in the composition (see Figure 1) (45). With its high detection sensitivity and specificity to selected chemical groups, TOFSIMS has been shown to provide semi-quantitative analysis of NHS-conjugated PEG surfaces in combination with multivariate analysis statistical methods such as principal component analysis (PCA) (59). In fact, TOF-SIMS methods have been shown to enable a method for understanding relative NHS density on surfaces as an important quality control feature to assess the known hydrolytic instability of this chemistry upon storage (60) and impact of this degradation on surface immobilization efficiencies (49, 59). TOF-SIMS data here were acquired using previously published methods (49, 59, 61): using an ION-TOF 5-100 instrument (ION-TOF GmbH, Münster, Germany) using a Bi3+ primary ion source with a pulsed 25 keV, 1.3 pA primary ion beam in high current bunched mode (i.e., high mass resolution mode) from 500 µm x 500 µm areas on the sample surfaces. All images contain 128 x 128 pixels. These analysis conditions result in spatial resolution of approximately 4 microns. All data were collected using an ion dose below the static SIMS limit of 1 x 1012 ions/cm2. A low-energy electron beam was used for charge compensation on the polymer-coated glass slides. The mass resolutions (m/Δm) for the negative secondary ion spectra are typically between 6000 and 7500 for the (m/z) 25 peak. The mass resolutions (m/Δm) for the positive secondary ion spectra are typically between 7000 and 8500 for the (m/z) 27 peak. PCA was performed on this dataset as described previously using a series of scripts written 786 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


by NESAC/BIO for MATLAB (MathWorks, Inc., Natick, USA) to build PCA scores images of the surfaces from chemical fragment data (62, 63). TOF-SIMS image line resolution can be calculated to be 6.0 ± 0.4 µm as derived from multiple line scans, approximately the same resolution as the photomask used for surface patterning.

Figure 1. Schematic illustration of NHS-containing PEG-based crosslinked polymer coating process. Reproduced with permission from Ref. (52). Copyright 2007 American Chemical Society. 787 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Figure 2. Relative non-specific protein adsorption on bare glass, bovine serum albumin (BSA)-blocked substrates, and the PEG-based polymer-coated substrate. Fluorescently-labeled proteins (a: goat serum, b: human fibrinogen, c: human lysozyme). Fluorescence intensity was detected by a commercial array laser scanner and calculated as relative fluorescence unit (RFU) under identical conditions. Reproduced with permission from Ref. (52). Copyright 2007 American Chemical Society.

788 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. Chemically specific NHS surface mapping using TOF-SIMS. Negative TOF-SIMS ion images for patterned NHS-co-methoxy capped patterned PEG polymer surfaces showing areas from TOF-SIMS analysis selected for fragments m/z 42, 98, and 114 from fresh NHS patterned (top, raw ion images) and hydrolyzed PEG-NHS surfaces (bottom, raw ion images). Scale bar: 100 µm. Reproduced with permission from Ref. (64). Copyright 2009 John Wiley & Sons, Ltd.

3.1. TOF-SIMS Imaging of Chemical and Protein Patterns on Polymer Surfaces NHS groups undergo well-known hydrolysis both under ambient atmospheric humidity and rapidly in bulk water with both temperature and pH dependence (44, 49, 59). While NHS coupling chemistry is utilized in thousands of publications and many commercial kits and technologies, quality control methods to assess NHS presence, activity and hydrolysis on surfaces for controlling surface immobilization reaction efficiency are not readily available. TOF-SIMS analysis of chemical fragments derived from NHS-polymer surfaces after various treatments exploited PCA methods to distinguish resident NHS presence and activity between fresh NHS-containing, NHS-aged and hydrolyzed surfaces (59, 64). Principal component (PC1) scores and loadings plot for negative ion surface data shows that these polymer samples are clearly differentiated (64). Peaks from fragments at m/z 98 (C4H4NO2-) and 114 (C4H4NO3-) among others are characteristic of the NHS five-member ring. TOF-SIMS analysis clearly shows remarkable decreases in these ion peaks from NHS-hydrolyzed surfaces. Subsequently, NHS hydrolysis results in increasing intensity of peaks at m/z 58 (C2H2O2-) and 43 (C2H3O-) from the hydrolyzed NHS ring-opened fragment and resulting surface carboxylate group. TOF-SIMS analysis is therefore capable of producing a quality control metric for NHS surface states, and produce surface images for this chemistry and hydrolytic changes on surfaces (Figure 3) (59, 64). This method of “chemical mapping” of surface reactivity can then be used 789 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


further to follow sequential reactions at surfaces by following the changes in TOF-SIMS fragment profiles and resulting surface chemical maps, especially valuable for validating approaches that involve surface patterns for spatial control of immobilization. TOF-SIMS can be exploited to provide chemical fragment images for immobilized proteins by mapping specific ion fragments originating from constituent surface-derived amino acids (65–67). The use of fluorescently-labeled proteins on surface patterns confirms the validity of this approach. Figure 4 shows that the fluorescence image for streptavidin forms micropatterns only on NHS-bearing surface regions through solution phase protein immobilization (Figure 4a). The corresponding chemical state TOF-SIMS confirms these protein patterns by detecting and mapping the mass fragments from amino acids in the immobilized protein (m/z 110, 120, 130, 136, 159, and 170) (Figure 4b) (49).

Figure 4. (a) Fluorescence image of a NHS-patterned surface treated with solution phase streptavidin and then exposed to biotinylated BSA labeled with Alexa555. Scale bar left: 500 µm. (b) TOF-SIMS image generated from PC-1 score map of TOF-SIMS positive ion analysis of the streptavidin-immobilized surface pattern (image: 500 µm x 500 µm, streptavidin ion fragments mapped to lighter PCA score regions). Reproduced with permission from Ref. (49). Copyright 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

4. Affinity-Based Protein Immobilization: Self-Selecting Ligand Patterns Traditional affinity chromatography exploits highly specific, unique binding interactions between a desired target, typically a protein, and its paired ligand bound at sufficient surface density to a separation matrix (i.e., a solid phase filter, suspended particles, or a stationary phase chromatography support). This method is used to separate proteins from mixed solutions using protein-ligand affinities (Kd ~nM) that provide reliable selectivity and specificity for target removal from complex samples (68). We have adapted these affinity selection methods to planar surfaces by tethering high affinity ligands in patterns to polymer surface chemistry that exhibits very low background non-specific capture. The patterning process can be followed step-wise using ToF-SIMS to validate each derivatization, and can reliably bind target proteins to patterns from mixed aqueous solutions. 790 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


4.1. Dual Protein Patterning by Ligand Self-Selection at Interfaces A variety of patterning techniques now allow multiple different proteins to be co-patterned on the same surface by soft lithography (69, 70), masked stencils (71, 72), and other methods (73, 74). However, many studies on protein patterning are still based on sequential strategies immobilizing different proteins stepwise in series. These strategies typically utilize serial processing methods to immobilize one protein at a time from pure, single component solutions onto surfaces by physical adsorption, covalent attachment, or affinity ligand capture (1). Capture using affinity ligands is promising to facilitate protein selection and immobilization from mixed solution phases (10, 75). Self-selection of ligands as a co-patterning technique is intuitive but characterizing this pattern for properties beyond confocal imaging is challenging. As affinity ligand models, biotin and chloroalkane were co-patterned using lithography-generated NHS patterned chemistry on PEG hydrogel surfaces (61). As shown in Figure 3, NHS groups can be patterned site-selectively. Photoresist can be selectively retained in regions to mask and protect NHS chemistry while exposed groups are reacted with a ligand (49). NHS groups in the exposed regions are coupled with a first ligand (biotin) by incubation with hydrazine-derivatized biotin. The photoresist in the second pattern is then removed and the second ligand, amino-chloroalkane, can be further immobilized onto the biotin/NHS-patterned surface, yielding biotin/chloroalkane co-patterned slides. The chloroalkane ligand is specific to HaloTag® protein (Promega, USA) a 34kDa modified hydrolase enzyme that rapidly forms specific, covalent bonds with chloroalkane ligands (76). Each region of this dual ligand-immobilized surface has high binding affinity in principle for one of two proteins, allowing self-selecting co-patterning solely by exposure of protein solutions comprising streptavidin and HaloTag® proteins. 4.2. Fluorescence Imaging of Protein Co-Patterned Surfaces Fluorescence detection of pattern recognition by labeled proteins is a simple, direct confirmation of site-specific binding. Detection of fluorescently labeled proteins on substrates using common microarray scanners is standard protocol (8, 31, 45, 71). After exposure to mixed protein solutions where both proteins bear different fluorophores, resulting fluorescence patterns exhibit images corresponding to the lithographed dual-ligand co-patterning. The approach is schematically shown in Figure 5. High fidelity of the protein-ligand surface interactions in respective side-by-side spatial zones using paired ligand-protein interactions on PEG-based hydrogel surface with its intrinsically low non-specific protein adsorption is expected (52). Patterned NHS groups are converted to spatially controlled areas of ligand-immobilized chemistry and facilitate reliable immobilization of streptavidin and HaloTag® from aqueous mixed solutions (Figure 5). Fluorescence images reveal that two different proteins, streptavidin and HaloTag®, bind specifically and are exclusively captured on the surface through specific interactions with their respective partner molecules, biotin and chloroalkane (61). These data are then conveniently correlated with TOF-SIMS chemical state images for the same samples. 791 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. Schematic illustration for self-sorting of two different proteins, streptavidin (green) and HaloTag® (red), onto biotin and chloroalkane ligand-patterned low-background polymer surfaces. Fluorescence imaging of co-patterned surfaces after exposure to solutions of mixed streptavidin-Alexa555 and HaloTag®-Alexa647 demonstrates high fidelity of each protein to their respective surface ligand patterns. Reproduced with permission from Ref. (61). Copyright 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

4.3. TOF-SIMS Chemical State Imaging of Protein Co-Patterned Surfaces TOF-SIMS chemical imaging with PCA provides a “label-free” surface mapping technique to corroborate fluorescence surface patterns and confirm successful co-patterning of streptavidin and HaloTag® using the affinity-ligand self-sorting solution approach (61). TOF-SIMS has been widely used to characterize proteins and peptides on various substrates by exploiting specific ion fragments originating from constituent amino acids (65, 66, 77). The overall amino acid composition for proteins is generally restricted to the canonical natural amino acid population, where most proteins exhibit relatively small differences in their amino acid composition that manifest much more substantial and diverse distinctions in size, folded shapes, domains and therefore respective functions. The ability of TOF-SIMS to readily discriminate and then image 2 different unlabeled proteins in adjacent surface-patterned areas was the idea pursued in this study. Moreover, as minute amounts of albumin were mixed into the protein mixtures to limit non-specific protein adsorption to the surface, this represented an additional confounding protein signal source for TOF-SIMS to overcome. Compositional differences in amino acids between these three proteins are listed in Table 1. Cysteine and methionine are two amino acids not present in streptavidin, so the characteristic sulfur-containing fragments from these amino acids (i.e., CHS, 45 m/z, and C2H5S, 61 m/z) provide specific indications for where streptavidin is absent. By contrast, amino acids threonine (16%), tryptophan (9%) and tyrosine (8%) are present in higher concentrations in streptavidin compared to either HaloTag® or BSA, so TOF-SIMS images corresponding to the characteristic fragments from these three amino acids (e.g., C3H8NO, 74 m/z; C9H8N, 130 m/z; C7H7O, 107 m/z; and C8H10NO,136 m/z) should indicate streptavidin presence. 792 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

Table 1. Protein amino acid composition comparisons for streptavidin, HaloTag® and bovine serum albumin (BSA) (61) % composition in protein Amino acid


Streptavidin

HaloTag®

BSA

Lys

3.96

5.74

11.35

His

2.20

3.15

3.26

Arg

4.85

5.37

5.74

Asp

3.53

8.15

6.09

Asn

5.95

2.59

2.96

Thr

16.08

2.96

4.26

Ser

5.67

3.52

3.13

Pro

0.96

7.96

3.65

Gly

6.72

7.04

0.96

Glu

4.32

7.41

12.13

Gln

3.08

1.67

3.91

Ala

8.79

6.48

6.63

Cys

0

1.30

4.57

Val

5.01

5.74

6.24

Met

0

2.96

1.04

Ile

2.63

6.30

1.39

Leu

6.61

10.74

10.26

Tyr

7.93

3.89

4.69

Phe

2.42

4.63

7.41

Trp

9.25

2.41

0.30

Total

100

100

100

Despite theoretical challenges for discriminating different proteins patterned on the same surface using subtle amino acid compositional differences, TOF-SIMS imaging clearly indicates its capabilities to discriminate streptavidin from HaloTag® proteins on the ligand-patterned surface. TOF-SIMS chemical fragment images generated by selecting specific ion fragments clearly distinguishes co-patterning of streptavidin and HaloTag® on a PEG-based hydrogel film, consistent with both the NHS patterns and fluorescence images from labeled protein patterns (see Figure 6). The sensitive and selective protein chemical discrimination of surface patterns shown here by these methods is unprecedented. Furthermore, the co-patterning study also exhibit a potential of



TOF-SIMS analysis for distinguishing different proteins immobilized onto the same surface.

Figure 6. TOF-SIMS images of identical sample areas for an affinity ligand-selected protein co-patterned surface using biotin/chloroalkane, generated by selecting protein-specific ion fragments identified in the PCA loadings plot for both streptavidin and HaloTag®. Bright patterned regions in each image are generated from chemical state maps derived from (a) Cys+Met ion-specific fragments characteristic of HaloTag® protein, and (b) Tyr+Thr+Trp ion-specific fragments characteristic of streptavidin. Reproduced with permission from Ref. (61). Copyright 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

5. Using TOF-SIMS Chemical Imaging To Demonstrate Orientational Control of Immobilized Proteins at Interfaces (78) Surface capture-based technologies and proteomics tools in high-throughput formats have been an on-going interest for biosensing, clinical chemistry, and fundamental work analyzing protein expression patterns, protein-protein interactions, and processes underlying cellular functions. As a central component, immobilized antibody surface capture is central to more traditional enzyme-linked immunosorbent assays (ELISAs) (79, 80), affinity chromatography separations 794 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


(81, 82), lateral flow assays (83), antibody-based diagnostics (84), antibody microarray assay formats (85, 86), and biosensors (87). Improvements in antibody surface-immobilized stability, sensitivity, density, and shelf-life, reduced cross-reactivity remain as a long-standing issue limiting performance in numerous applications. Surface-immobilized antibody orientation is frequently a focus since mis-oriented antibodies conceivably are compromised in their antigen binding capacity (85, 88, 89). Random antibody surface orientation results in limited access to bind analytes if the antigen-binding domains of the antibody (i.e., Fv variable domains within the antigen-binding Fab domains) are immobilized against the surface (10). In additional to surface immobilization methods that might reliably improve antibody immobilized orientations, methods to actually analyze this as a quality control measure in situ on surfaces are challenging (90). The affinity-based protein self-selecting strategy, using surfaces patterned with ligands with preference for specific antibody sites, offers an opportunity for TOF-SIMS discrimination (78). 5.1. Fluorescent Protein Imaging for Visualizing Antibody Patterning Specificities To validate TOF-SIMS as a new method to analyze protein orientation, we exploited our previous surface co-patterning strategy, using lithography of commercial NHS-bearing PEG polymer surfaces to attach two different ligands into adjacent regions with spatial selectively. Unlike the previous example where two different proteins selected two different surface affinity ligands by self-selection from mixed aqueous solutions (61), the antibody orientation approach involved a dual ligand co-patterning method to facilitate antibody orientation selection on adjacent surface patterns. To achieve this, a bacterial membrane protein, Protein A, well-known to specifically bind the antibody Fc domain (91, 92) and extensively used as a surface affinity ligand to bind and orient antibodies for solid-phase affinity use (93) was patterned. The antibody Fc-Protein A interaction pairing at the solid surface allows a preference for orientation of the antigen-binding domain Fab fragment to be exposure to reaction solution. While this is not absolute certain orientation, given finite possibilities for surface mis-orientation and non-specific surface adsorption, the method does improve antigen capture, reflecting surface orientation with more antibody Fab domain exposure/accessibility away from the surface (93). Second, fluorescein, a known high affinity antigen for several anti-fluorescein monoclonal antibodies (e.g., MAb 4-4-20) (94), was surface-immobilized using amino-fluorescein, producing specific antigen ligands to orient anti-fluorescein antibodies with Fab domains down against the surface by antigen binding. Co-patterning of fluorescein haptens in adjacent regions co-planar with protein A using the NHS patterning strategy defined here (vida supra) provides an approximate 2-state surface selection model. This was intended to produce patterned regions on surfaces where antibodies select an antibody Fab upwards surface orientation using protein A capture (i.e., “heads-up”), and an antibody Fab downwards surface orientation using fluorescein hapten binding (i.e., “tails-up”) (78). Figure 7a depicts this desired result. This strategy provides a basis for analyzing antibody surface selection and 795 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


orientational control. Both convenient capabilities for dual ligand-patterning (in this case, dual protein A and fluorescein adjacent patterns) combined with low non-specific background binding already shown for this surface (52), provide a suitable model system to assess the abilities of fluorescence mapping and TOF-SIMS chemical state imaging to validate this approach.

Figure 7. Antibody self-selection of 2-state ligand patterns on surfaces from solution. (a) Schematic illustration showing the intended 2-state immobilized antibody orientations using co-patterned protein A- and fluorescein- immobilized regions to selectively bind antibodies in “heads-up” (Fab domain exposed) and “tails-up” (Fc domain exposed) orientations on ligand-patterned surfaces known to select these states; (b) Fluorescence images of Alexa647-labeled anti-fluorescein antibody, non-specific murine Fab fragments, and Fc polyclonal fragments captured on protein A- and fluorescein-patterned surfaces, respectively, showing surface specificities for each species and the designed patterned surface ligand. Reproduced with permission from Ref. (78). Copyright 2010 American Chemical Society.

First, domain-specific antibody reactions were confirmed indirectly using fluorescence imaging (see Figure 7b). AlexaFluor-labeled MAb 4-4-20 exhibits the anticipated selection of either protein A or fluorescein on single-ligand patterned surface controls (i.e., either protein A/MeO-capped or fluorescein hapten/MeO-capped patterns). No antibody signal from exposure of fluorescently-labeled Fab fragment to the protein A-patterned surface supports specific reaction of the full antibody on regions where protein A is immobilized (Figure 7b). In contrast, Alexa-labeled Fc fragments bind selectively to the protein A-patterned surfaces, similar to the full antibody. These images indicate that 796 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


anti-fluorescein 4-4-20 antibody specifically interacts with surface-immobilized protein A through Fc recognition. Thus, when this antibody binds to protein A-immobilized regions, a predominantly “heads-up” orientation is expected in these regions. By contrast, when the fluorescein-patterned surface is exposed to non-specific murine Fab and Fc polyclonal fragments lacking specificity for the immobilized fluorescein, neither of these two antibody fragments bind to this surface (Figure 7b). This supports specific anti-fluorescein antibody binding with patterned fluorescein ligands through specific antigen-Fab domain interactions, providing the desired “tails-up” orientation (78).

5.2. TOF-SIMS Imaging for Visualizing Antibody Orientation

TOF-SIMS has proven to be an effective surface analytical method for providing information on the orientation and other aspects of surface-bound proteins (59, 95–98). While fluorescence imaging shows site-specific high-fidelity antibody selection of ligand patterns on surfaces, protein-surface orientation cannot be distinguished from data in Figure 7b. Even commonly employed analytical methods (e.g., SPR, TIRF, AFM) have difficulties asserting conformational or orientational differences on antibody-immobilized surfaces (99). Importantly, TOF-SIMS methods provide new chemical information capable of discerning protein orientations on surfaces. Since the TOF-SIMS sampling depth is generally ~2 nm, the ion yields reflect only the outermost amino acids of the exposed protein regions on these surfaces (100). Antibody orientation therefore is selectively detectable if: (1) these amino acids in the surfaces of these different antibody domains are sufficiently compositionally distinct in different orientations (i.e., Fab domain oriented toward ambient interface versus Fc domain oriented toward ambient interface), (2) antibody orientation is relatively consistent across the sampling area of the TOF-SIMS analysis, and (3) the method is capable of sorting the complex surface mass spectra to provide these distinguishing features. Table 2 shows specific amino acids for antibody domains, showing the relative enrichment between Fab versus Fc domains, and the basis for predicting whether amino acid TOF-SIMS fragments originating from antibodies selecting protein A versus fluorescein patterns could show pattern-specific signals. With such analytical performance, the co-patterning strategy using TOF-SIMS analysis distinguishes “heads-up” from “tails-up” antibody orientations shown in Figure 7(a) (78). Fab/Fc amino acid ratios less than unity in Table 2 have these amino acids enriched in the Fc region and therefore would be predicted to have lower TOF-SIMS intensities from these amino acids if the antibody is bound “tails-up” in fluorescein hapten regions. Correspondingly, Fab/Fc amino acid ratios greater than unity in Table 2 have these amino acids enriched in their Fab domains and therefore would be predicted to have higher TOF-SIMS intensities from these amino acids if the antibody is bound “heads-up” on protein A patterns. This experimental design is conceptually captured in Figure 8 (78). 797 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

Table 2. Comparisons of relative amino acid enrichment in Fab versus Fc antibody domains and predicted TOF-SIMS PCA loadings based on affinity immobilization to protein A versus fluorescein surface patterns (78)


Amino Acid

Compositional ratio (Fab/Fc)

Predicted PCA loading region

Cys

0.70

Fluorescein

His

0.42

Fluorescein

Pro

0.53

Fluorescein

Leu

1.57

Protein-A

Arg

1.21

Protein-A

Gln

1.18

Protein-A

Figure 8. Schematic for the orientation-dependence of TOF-SIMS amino acid signals from antibodies oriented in a theoretical 2-state surface model (i.e., “heads-up” versus “tails-up” orientations) on antibody regio-specific affinity-capture ligand co-patterned surfaces (78). Based on this predicted amino acid signal enrichment and the opportunity for TOF-SIMS to detect this enrichment, TOF-SIMS images generated from peptide fragments specific to either the antibody Fab or Fc regions were used to validate this method. Surface images generated from summing all amino acid fragment m/z signals for antibody patterns on surfaces show clear surface patterns consistent with the lithographic patterning and its characterization. This contrast must arise from differences in total immobilized antibody densities between both surface regions. This reflects possible intrinsic differences between protein A-Fc 798 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


recognition and fluorescein antigen-antibody surface interactions, as well from the presence of photoresist residue in the UV exposed regions. Figure 9(a) shows the total amino acid ion intensities, with the pattern contrast consistent with more antibody residing on the protein A region than on the fluorescein region. However, compositional “mapping” of the selected amino acid fragments known for Fab (i.e., “heads-up” orientation) versus Fc (i.e., “tails-up” orientation) across the surface (Figure 9(b)) clearly indicates greater ion intensity for fragments associated with Fc domains originate from the fluorescein-patterned region. Complete analysis of surface patterned antibody capture for each affinity ligand is consistent with different pattern specificity for antibody Fab versus Fc domain binding as depicted in Figure 7(a). This prompted our conclusion that antibody orientation could be produced on each pattern by ligand-based orientational influences on immobilization (78).

Figure 9. TOF-SIMS-generated images of antibody-patterned surfaces produced from solution phase binding with co-patterned protein A/fluorescein. Contrast in identical images is generated from TOF-SIMS surface analysis data from (a) summing all amino acid ion fragments detected, and (b) amino acid enrichment ratio characteristic of Fab versus Fc domain amino acid compositions as defined in Table 2. Reproduced with permission from Ref. (78). Copyright 2010 American Chemical Society.

Direct evidence of surface-immobilized orientation is seldom directly shown in similar antibody studies: the complexity of the problem at surfaces with immobilized proteins is not easily interrogated and few methods exist to assert orientation of protein monolayers. TOF-SIMS chemical state imaging reveals antibody orientation regulated by site-specific protein A-Fc and antigen-antibody Fab interactions, respectively. The dual ligand co-patterning technique elicits antibody sorting at surfaces into “heads-up” and “tails-up” oriented antibodies validated by TOF-SIMS imaging based on differences in oriented antibody amino acid compositions. Importantly, this approach could lead to both understanding of and control over surface antibody orientations required for improved bioassay performance (i.e., assay precision, sensitivity and accuracy) with impact to protein microarrays, biosensors, affinity chromatography and immunoassays. 799 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


6. Cell Culture Patterning through Cell Adhesion Peptide Patterns Cell patterning techniques facilitate local control over adherent cellular shapes, footprint or adhered size, cell density, cell-cell interactions and cell communication, influencing cell function, phenotype, and metabolism at surfaces (29, 71, 101). Additionally, micropatterned viable cells on a chip represent a promising micro-sensor in the field of medical diagnostics (23–25). The PEG-based crosslinked polymer coating described in Figures 1-3 and previous work exhibits sufficiently reliable non-fouling properties in cell culture serum-containing media to both mammalian cell and bacterial adhesion to these surfaces (vida supra) (49, 52). This low background protein binding is critical for cell patterning. With its pattern-capable amine-reactive NHS groups, the surface is conveniently patterned with proteins and peptides known to promote cell adhesion even on non-adhesive surfaces. Because peptides are much shorter, less expensive and more stable than longer proteins, high-density peptide microarrays can be fabricated by peptide conjugation to surfaces (102, 103). Short RGD-containing peptides are most commonly used to promote specific cell-surface immobilization (104, 105). These can be immobilized on NHS patterns on the PEG hydrogel surface coating through bulk aqueous immobilization (49). Figure 10 shows the RGD peptide and its ion fragments detected by TOF-SIMS in analysis. Chemical fragment images from solution-immobilized RGD to NHS patterned surfaces show the anticipated pattern for NHS-specific peptide immobilization (compare Figure 3). This is consistent with previous data (vida supra) showing the chemical specificity of this surface chemistry for bulk peptide solution chemical immobilization to NHS patterns (49, 52).

Figure 10. (a) Cell adhesion peptide RGD with characteristic TOF-SIMS fragments (boxes). (b) TOF-SIMS chemical fragment image generated from characteristic RGD fragments m/z 45 + 58 + 59, showing the ability to co-pattern RGD from solution to patterned NHS chemistry on the PEG crosslinked coating. Reproduced with permission from Ref. (49). Copyright 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. 800 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Figure 11(a) shows that mammalian fibroblast cultures in 10% serum cannot adhere or grow on the PEG coating without adhesion peptides. Figure 11(b) shows that uniform RGD peptide immobilization to the unpatterned PEG-NHS surface endows this non-adhesive PEG chemistry with the uniform ability to adhere fibroblasts in serum-based culture. Figure 11(c) demonstrates that line patterns of various widths using photolithographically patterned NHS and bulk solution RGD modification readily adhere fibroblasts from serum-based cultures with high fidelity to these same patterns. This is consistent with the TOF-SIMS chemical image mapping also clearly showing the same RGD peptide patterning (see Figure 10) (49).

Figure 11. Phase contrast microscopic images of cultured fibroblast adhesion on RGD-patterned PEG-based surfaces in serum-containing culture at 48 h after cell seeding: unpatterned NHS-PEG coating surface without (a) and with (b) RGD peptide solution phase modification; Variable-width line RGD-immobilized peptide patterns on PEG surfaces cultured with fibroblasts (c) after 3 days of continuous serum-based cell seeding and culture; and (d) a single narrow patterned line after 15 days in serum-containing culture showing single cell-width patterns. Scale bars: (a, b, c) 200 microns, (d) 50 microns. Reproduced with permission from Ref. (49). Copyright 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fibroblasts remain confined with high fidelity to these RGD patterns on the PEG hydrogel surface in continuous 10% serum-containing media to 15 days (Figure 11(d)). This performance reflects the high on-pattern peptide adhesion signal/low off-pattern background protein deposition, despite continuous competition from serum proteins (49). Typically, endogenous cell extracellular 801 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

matrix production, proliferation and migration contribute ultimately to cell pattern failure in cultures over time within a few days (20, 106, 107). That all RGD patterns on this chemistry show no cell exit from these patterns and invasion of adjacent inert surface areas for at least 15 days after cell seeding in serum-containing media is a testament to the selective surface patterned chemical reactivity that produces cell-specific adhesion domains and non-specific binding in off-pattern areas.


7. Conclusions Given PEG’s current popularity as a chemistry of choice in diverse biotechnology and biomaterials applications, this study validates some of the practical value for a commercial chemically reactive PEG surface coating and accompanying analytical value of TOF-SIMS methods in asserting this value. TOF-SIMS methods were enabled by 1) the versatile patterning capability for reactive chemistry on this surface, and 2) the resulting on-pattern high signal, off-pattern low noise for desired modification using solution phase reagents. This signal:noise contrast for patterned surface immobilization facilitated high-fidelity co-patterning of high affinity ligands for specific proteins that demonstrated the ability to 1) producing self-sorting surfaces capable of selecting proteins immobilized to specific surface regions from mixed protein solutions by ligand selection, and 2) immobilized antibody orientational control on surfaces. TOF-SIMS chemical state imaging clearly demonstrated its utility to discriminate these patterns and validate both the approach and the operating hypothesis for controlling and monitoring surface-protein interfacial behaviors. Highly specific surface patterning and surface analysis tools for both site- and orientation selective protein immobilization is one impact. Extension of the surface patterning approach to validate surface control of subsequent interfacial events including cell and bacterial adhesion in complex physiological fluids is a second demonstrated impact. As described, these features are particularly relevant for improving in vitro bioassay applications in microarrays and biosensors. In addition, chemical imaging-based TOF-SIMS analysis combined with PCA can be a very useful tool to understand surface chemical reactivity including patterning and orientation of immobilized biomolecules when high signal-to-noise ratio can be specifically maintained by design.

Acknowledgments This research was supported by the National ESCA and Surface Analysis Center for Biomedical Problems (NIH Grant EB-002027) and NIH Grant EB-001473. Note: Author DWG discloses financial interests in Accelr8 Technologies, Inc (USA), commercial vendor for one polymer coating described in this manuscript, representing a possible conflict of interest (either real or perceived). 802 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. 15. 16. 17.

18. 19. 20.

21. 22. 23. 24. 25.

Blawas, A. S.; Reichert, W. M. Biomaterials 1998, 19, 595–609. Demers, L. M.; Ginger, D. S.; Park, S. J.; Li, Z.; Chung, S. W.; Mirkin, C. A. Science 2002, 296, 1836–1838. West, J. L. Nat. Mater. 2011, 10, 727–729. Christman, K. L.; Enriquez-Rios, V. D.; Maynard, H. D. Soft Matter 2006, 2, 928–939. Weibel, D. B.; Diluzio, W. R.; Whitesides, G. M. Nat. Rev. Microbiol. 2007, 5, 209–218. Schena, M.; Shalon, D.; Davis, R. W.; Brown, P. O. Science 1995, 270, 467–470. Brown, P. O.; Botstein, D. Nat. Genet. 1999, 21, 33–37. Zhu, H.; Bilgin, M.; Bangham, R.; Hall, D.; Casamayor, A.; Bertone, P.; Lan, N.; Jansen, R.; Bidlingmaier, S.; Houfek, T.; Mitchell, T.; Miller, P.; Dean, R. A.; Gerstein, M.; Snyder, M. Science 2001, 293, 2101–2105. Falconnet, D.; Csucs, G.; Grandin, H. M.; Textor, M. Biomaterials 2006, 27, 3044–3063. Zhu, H.; Snyder, M. Curr. Opin. Chem. Biol. 2003, 7, 55–63. MacBeath, G.; Schreiber, S. L. Science 2000, 289, 1760–1763. Lahiri, J.; Isaacs, L.; Tien, J.; Whitesides, G. M. Anal. Chem. 1999, 71, 777–790. Wu, P.; Castner, D. G.; Grainger, D. W. J. Biomater. Sci., Polym. Ed. 2008, 19, 725–753. Barbulovic-Nad, I.; Lucente, M.; Sun, Y.; Zhang, M.; Wheeler, A. R.; Bussmann, M. Crit. Rev. Biotechnol. 2006, 26, 237–259. Renault, J. P.; Bernard, A.; Juncker, D.; Michel, B.; Bosshard, H. R.; Delamarche, E. Angew. Chem., Int. Ed. 2002, 114, 2426–2429. Sorribas, H.; Padeste, C.; Tiefenauer, L. Biomaterials 2002, 23, 893–900. Carrico, I. S.; Maskarinec, S. A.; Heilshorn, S. C.; Mock, M. L.; Liu, J. C.; Nowatzki, P. J.; Franck, C.; Ravichandran, G.; Tirrell, D. A. J. Am. Chem. Soc. 2007, 129, 4874–4875. Martin, T. A.; Herman, C. T.; Limpoco, F. T.; Michael, M. C.; Potts, G. K.; Bailey, R. C. ACS Appl. Mater. Interfaces 2011, 3, 3762–3771. Kane, R. S.; Takayama, S.; Ostuni, E.; Ingber, D. E.; Whitesides, G. M. Biomaterials 1999, 20, 2363–2376. Rozkiewicz, D. I.; Kraan, Y.; Werten, M. W. T.; de Wolf, F. A.; Subramaniam, V.; Ravoo, B. J.; Reinhoudt, D. N. Chem.−Eur. J. 2006, 12, 6290–6297. Yang, Z. P.; Chilkoti, A. Adv. Mater. 2000, 12, 413–417. Tan, W.; Desai, T. A. Tissue Eng. 2003, 9, 255–267. Houseman, B. T.; Gawalt, E. S.; Mrksich, M. Langmuir 2003, 19, 1522–1531. Lee, C. Y.; Harbers, G. M.; Grainger, D. W.; Gamble, L. J.; Castner, D. G. J. Am. Chem. Soc. 2007, 129, 9429–9438. Xu, G.; Goldberg, M. U.S. Patent 20040023367, 2004. 803 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


26. Bhatia, S. N.; Balis, U. J.; Yarmush, M. L.; Toner, M. FASEB J. 1999, 13, 1883–900. 27. Khademhosseini, A.; Suh, K. Y.; Yang, J. M.; Eng, G.; Yeh, J.; Levenberg, S.; Langer, R. Biomaterials 2004, 25, 3583–3592. 28. Hui, E. E.; Bhatia, S. N. Langmuir 2007, 23, 4103–4107. 29. Tsuda, Y.; Kikuchi, A.; Yamato, M.; Chen, G.; Okano, T. Biochem. Biophys. Res. Commun. 2006, 348, 937–944. 30. Tsuda, Y.; Shimizu, T.; Yamato, M.; Kikuchi, A.; Sasagawa, T.; Sekiya, S.; Kobayashi, J.; Chen, G.; Okano, T. Biomaterials 2007, 28, 4939–4946. 31. Haab, B. B.; Dunham, M. J.; Brown, P. O. Genome Biol. 2001, 2, 0004.1–0004.13. 32. Balboni, I.; Limb, C.; Tenenbaum, J. D.; Utz, P. J. Proteomics 2008, 8, 3443–3449. 33. Gong, P.; Grainger, D. W. Methods Mol. Biol. 2007, 381, 59–92. 34. Grainger, D. W.; Greef, C. H.; Gong, P.; Lochhead, M. J. Methods Mol. Biol. 2007, 381, 37–57. 35. Harris, J. M. Poly(ethylene glycol) chemistry : biotechnical and biomedical applications; Plenum: New York, 1992. 36. Hoffman, A. S. J. Biomater. Sci., Polym. Ed. 1999, 10, 1011–1014. 37. Ostuni, E.; Chapman, R. G.; Holmlin, R. E.; Takayama, S.; Whitesides, G. M. Langmuir 2001, 17, 5605–5620. 38. Gombotz, W. R.; Wang, G. H.; Horbett, T. A.; Hoffman, A. S. J. Biomed. Mater. Res. 1991, 25, 1547–1562. 39. Emoto, K.; Van Alstine, J. M.; Harris, J. M. Langmuir 1998, 14, 2722–2729. 40. Lee, J. H.; Kopecek, J.; Andrade, J. D. J. Biomed. Mater. Res. 1989, 23, 351–368. 41. Huang, N. P.; Michel, R.; Voros, J.; Textor, M.; Hofer, R.; Rossi, A.; Elbert, D. L.; Hubbell, J. A.; Spencer, N. D. Langmuir 2001, 17, 489–498. 42. Mrksich, M.; Whitesides, G. M. ACS Symp. Ser. 1997, 680, 361–373. 43. Ostuni, E.; Chapman, R. G.; Liang, M. N.; Meluleni, G.; Pier, G.; Ingber, D. E.; Whitesides, G. M. Langmuir 2001, 17, 6336–6343. 44. Hermanson, G. T. Bioconjugate Techniques; Academic Press: London, U.K., 1996. 45. Gong, P.; Harbers, G. M.; Grainger, D. W. Anal. Chem. 2006, 78, 2342–2351. 46. Revzin, A.; Tompkins, R. G.; Toner, M. Langmuir 2003, 19, 9855–9862. 47. Metzger, S. W.; Lochhead, M. J.; Grainger, D. W. In Vitro Diagn. Technol. 2002, 8, 39–45. 48. Taylor, S.; Smith, S.; Windle, B.; Guiseppi-Elie, A. Nucleic Acids Res. 2003, 31, e87. 49. Takahashi, H.; Emoto, K.; Dubey, M.; Castner, D. G.; Grainger, D. W. Adv. Funct. Mater. 2008, 18, 2079–2088. 50. Pathak, S.; Dentinger, P. M. Langmuir 2003, 19, 1948–1950. 51. Petrou, P. S.; Chatzichristidi, M.; Douvas, A. A.; Argitis, P.; Misiakos, K.; Kakabakos, S. E. Biosens. Bioelectron. 2007, 22, 1994–2002.



52. Harbers, G. M.; Emoto, K.; Greef, C.; Metzger, S. W.; Woodward, H. N.; Mascali, J. J.; Grainger, D. W.; Lochhead, M. J. Chem. Mater. 2007, 19, 4405–4414. 53. Saldarriaga Fernandez, I. C.; van der Mei, H. C.; Lochhead, M. J.; Grainger, D. W.; Busscher, H. J. Biomaterials 2007, 28, 4105–4112. 54. Roosjen, A.; Boks, N. P.; van der Mei, H. C.; Busscher, H. J.; Norde, W. Colloids Surf., B 2005, 46, 1–6. 55. Saldarriaga Fernandez, I. C.; Mei, H. C.; Metzger, S.; Grainger, D. W.; Engelsman, A. F.; Nejadnik, M. R.; Busscher, H. J. Acta Biomater. 2010, 6, 1119–1124. 56. Castner, D. G.; Ratner, B. D. Surf. Sci. 2002, 500, 28–60. 57. Belu, A. M.; Graham, D. J.; Castner, D. G. Biomaterials 2003, 24, 3635–3653. 58. Barnes, T. J.; Kempson, I. M.; Prestidge, C. A. Int. J. Pharm. 2011, 417, 61–69. 59. Cheng, F.; Gamble, L. J.; Grainger, D. W.; Castner, D. G. Anal. Chem. 2007, 79, 8781–8788. 60. Gong, P.; Grainger, D. W. Surf. Sci. 2004, 570, 67–77. 61. Dubey, M.; Emoto, K.; Takahashi, H.; Castner, D. G.; Grainger, D. W. Adv. Funct. Mater. 2009, 19, 3046–3055. 62. Graham, D. J.; Wagner, M. S.; Castner, D. G. Appl. Surf. Sci. 2006, 252, 6860–6868. 63. Wickes, B. T.; Kim, Y.; Castner, D. G. Surf. Interf. Anal. 2003, 35, 640–648. 64. Dubey, M.; Emoto, K.; Cheng, F.; Gamble, L. J.; Takahashi, H.; Grainger, D. W.; Castner, D. G. Surf. Interf. Anal. 2009, 41, 645–652. 65. Aoyagi, S.; Kudo, M. Biosens. Bioelectron. 2005, 20 (8), 1626–30. 66. Bernsmann, F.; Lawrence, N.; Hannig, M.; Ziegler, C.; Gnaser, H. Anal. Bioanal. Chem. 2008, 391, 545–554. 67. Mantus, D. S.; Ratner, B. D.; Carlson, B. A.; Moulder, J. F. Anal. Chem. 1993, 65, 1431–8. 68. Cutler, P. Methods Mol. Biol. 2004, 244, 139–49. 69. Yap, F. L.; Zhang, Y. Biosens. Bioelectron. 2007, 22, 775–88. 70. Coyer, S. R.; Garcia, A. J.; Delamarche, E. Angew. Chem., Int. Ed. 2007, 46, 6837–6840. 71. Wright, D.; Rajalingam, B.; Karp, J. M.; Selvarasah, S.; Ling, Y.; Yeh, J.; Langer, R.; Dokmeci, M. R.; Khademhosseini, A. J. Biomed. Mater., Res. A 2008, 85, 530–538. 72. Atsuta, K.; Noji, H.; Takeuchi, S. Lab Chip 2004, 4, 333–336. 73. Lee, L. M.; Heimark, R. L.; Guzman, R.; Baygents, J. C.; Zohar, Y. Lab Chip 2006, 6, 1080–1085. 74. Jang, C. H.; Stevens, B. D.; Phillips, R.; Calter, M. A.; Ducker, W. A. Nano Lett. 2003, 3, 691–694. 75. Hodneland, C. D.; Lee, Y.-S.; Min, D.-H.; Mrksich, M. Proc. Natl. Acad. Sci. U.S.A. 2002, 99, 5048–5052. 76. Urh, M.; Hartzell, D.; Mendez, J.; Klaubert, D. H.; Wood, K. Methods Mol. Biol. 2008, 421, 191–209. 77. Wagner, M. S.; Castner, D. G. Langmuir 2001, 17, 4649–4660. 805 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


78. Liu, F.; Dubey, M.; Takahashi, H.; Castner, D. G.; Grainger, D. W. Anal. Chem. 2010, 82, 2947–58. 79. de Wildt, R. M. T.; Mundy, C. R.; Gorick, B. D.; Tomlinson, I. M. Nat. Biotechnol. 2000, 18, 989–994. 80. Orosz, F.; Ovadi, J. J. Immunol. Methods 2002, 270, 155–162. 81. Berry, M. J.; Davies, J.; Smith, C. G.; Smith, I. J. Chromatogr. 1991, 587, 161–169. 82. Muronetz, V. I.; Korpela, T. J. Chromatogr., B: Anal. Technol. Biomed. Life Sci. 2003, 790, 53–66. 83. Chan, C. P.; Sum, K. W.; Cheung, K. Y.; Glatz, J. F.; Sanderson, J. E.; Hempel, A.; Lehmann, M.; Renneberg, I.; Renneberg, R. J. Immunol. Methods 2003, 279, 91–100. 84. Saengjaruk, P.; Chaicumpa, W.; Watt, G.; Bunyaraksyotin, G.; Wuthiekanun, V.; Tapchaisri, P.; Sittinont, C.; Panaphut, T.; Tomanakan, K.; Sakolvaree, Y.; Chongsa-Nguan, M.; Mahakunkijcharoen, Y.; Kalambaheti, T.; Naigowit, P.; Wambangco, M. A.; Kurazono, H.; Hayashi, H. J. Clin. Microbiol. 2002, 40, 480–489. 85. Peluso, P.; Wilson, D. S.; Do, D.; Tran, H.; Venkatasubbaiah, M.; Quincy, D.; Heidecker, B.; Poindexter, K.; Tolani, N.; Phelan, M.; Witte, K.; Jung, L. S.; Wagner, P.; Nock, S. Anal. Biochem. 2003, 312, 113–124. 86. Kato, K.; Toda, M.; Iwata, H. Biomaterials 2007, 28, 1289–1297. 87. D’Orazio, P. Clin. Chim. Acta 2003, 334, 41–69. 88. Spitznagel, T. M.; Clark, D. S. Biotechnology (N.Y.) 1993, 11, 825–829. 89. Ahmed, S. R.; Kelly, A. B.; Barbari, T. A. J. Membr. Sci. 2006, 280, 553–559. 90. Hurst, R.; Hook, B.; Slater, M. R.; Hartnett, J.; Storts, D. R.; Nath, N. Anal. Biochem. 2009, 392, 45–53. 91. Ogi, H.; Motohisa, K.; Hatanaka, K.; Ohmori, T.; Hirao, M.; Nishiyama, M. Biosens. Bioelectron. 2007, 22, 3238–3242. 92. Lee, W.; Oh, B. K.; Bae, Y. M.; Paek, S. H.; Lee, W. H.; Choi, J. W. Biosens. Bioelectron. 2003, 19, 185–192. 93. Jung, Y.; Lee, J. M.; Jung, H.; Chung, B. H. Anal. Chem. 2007, 79, 6534–6541. 94. Ahlers, M.; Grainger, D. W.; Herron, J. N.; Lim, K.; Ringsdorf, H.; Salesse, C. Biophys. J. 1992, 63, 823–838. 95. Tyler, B. J.; Rayal, G.; Castner, D. G. Biomaterials 2007, 28, 2412–2423. 96. Wagner, M. S.; Castner, D. G. Appl. Surf. Sci. 2004, 231-2, 366–376. 97. Xia, N.; May, C. J.; McArthur, S. L.; Castner, D. G. Langmuir 2002, 18, 4090–4097. 98. Wang, H.; Castner, D. G.; Ratner, B. D.; Jiang, S. Y. Langmuir 2004, 20, 1877–1887. 99. Bilitewski, U. Anal. Chim. Acta 2006, 568, 232–247. 100. Tidwell, C. D.; Castner, D. G.; Golledge, S. L.; Ratner, B. D.; Meyer, K.; Hagenhoff, B.; Benninghoven, A. Surf. Interface Anal. 2001, 31, 724–733. 101. Mei, Y.; Cannizzaro, C.; Park, H.; Xu, Q.; Bogatyrev, S. R.; Yi, K.; Goldman, N.; Langer, R.; Anderson, D. G. Small 2008, 4, 1600–1604. 806 In Proteins at Interfaces III State of the Art 2012; Horbett, T., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


102. Usui, K.; Tomizaki, K.-y.; Ohyama, T.; Nokihara, K.; Mihara, H. Mol. BioSyst. 2006, 2, 113–121. 103. Antohe, B. V.; Cooley, P. W. Methods Mol. Biol. 2007, 381, 299–312. 104. Mrksich, M. Chem. Soc. Rev. 2000, 29, 267–273. 105. Houseman, B. T.; Mrksich, M. Biomaterials 2001, 22, 943–955. 106. Sharma, S.; Tan, W.; Desai, T. A. Bioconjugate Chem. 2005, 16, 18–22. 107. Luk, Y. Y.; Kato, M.; Mrksich, M. Langmuir 2000, 16, 9604–9608.


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