Impact of the Nanoparticle–Protein Corona on Colloidal Stability and

Apr 23, 2012 - Institute for Molecular Biology, Centre for Medical Biotechnology (ZMB), University of Duisburg-Essen, Universitätsstrasse, 45117. Ess...
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Impact of the Nanoparticle−Protein Corona on Colloidal Stability and Protein Structure Julia S. Gebauer,† Marcelina Malissek,† Sonja Simon,‡ Shirley K. Knauer,§ Michael Maskos,∥ Roland H. Stauber,⊥ Wolfgang Peukert,‡ and Lennart Treuel*,†,# †

Institute for Physical Chemistry, University of Duisburg-Essen, Universitätsstrasse 5-7, 45117 Essen, Germany Institute of Particle Technology (LFG), University of Erlangen-Nuernberg, Erlangen, Germany § Institute for Molecular Biology, Centre for Medical Biotechnology (ZMB), University of Duisburg-Essen, Universitätsstrasse, 45117 Essen, Germany ∥ Institut für Mikrotechnik Mainz (IMM), Carl-Zeiss-Strasse 18-20, 55129 Mainz, Germany ⊥ Molecular and Cellular Oncology/Mainz Screening Center (MSC), University Hospital of Mainz, Langenbeckstrasse 1, 55101 Mainz, Germany # Institute of Applied Physics and Center for Functional Nanostructures (CFN), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany ‡

S Supporting Information *

ABSTRACT: In biological fluids, proteins may associate with nanoparticles (NPs), leading to the formation of a so-called “protein corona” largely defining the biological identity of the particle. Here, we present a novel approach to assess apparent binding affinities for the adsorption/desorption of proteins to silver NPs based on the impact of the corona formation on the agglomeration kinetics of the colloid. Affinities derived from circular dichroism measurements complement these results, simultaneously elucidating structural changes in the adsorbed protein. Employing human serum albumin as a model, apparent affinities in the nanomolar regime resulted from both approaches. Collectively, our findings now allow discrimination between the formation of protein mono- and multilayers on NP surfaces.

1. INTRODUCTION When nanoparticles (NPs) enter a biological fluid, proteins and other biomolecules rapidly compete for binding to the nanoparticle surface, leading to the formation of a dynamic protein corona that critically defines the biological identity of the particle.1−3 The biophysical properties of such a particle− protein complex often differ significantly from those of the formulated particle. Hence, the further biological responses as well as the particle biodistribution are significantly affected by the nanoparticle−protein complex, potentially contributing also to unwanted biological side effects.4−6 A key aspect of the adsorption of proteins onto NP surfaces is that it can affect the protein conformation,7 which may ultimately culminate in the loss of the protein biological activity.8−10 Structural changes in the protein upon adsorption onto the NP surface may also lead to the exposure of novel “cryptic” peptide epitopes11,12 and altered function and/or avidity effects.13−15 When a protein containing cryptic epitopes is denatured on a particle surface, the exposure of new antigenic sites may initiate an immune response which, if launched against a self-protein, could promote autoimmune disease.16 However, the exact causes and mechanistic details of protein unfolding at NP surfaces are not yet fully understood.16−19 © 2012 American Chemical Society

The ability of NPs to adsorb proteins has been shown to depend on their surface coating7,20 but also on the protein identity and function. Physicochemical characteristics of NPs determine interactions with the surrounding medium by promoting adsorption of ions, proteins, natural organic materials, and detergents or by allowing the free surface energy to be minimized.16,21,22 The same properties also control the type and kinetics of biomolecule binding as well as the efficiency of this interaction4,5,16,23−25 and are therefore critical for nanotoxicology and nanomedicine as they determine the (patho)biological effects at the nano−bio interface.2 The notion of “hard” and “soft” protein coronae has been introduced,26 and it is believed that the soft corona forms on short time scales (seconds to minutes) and evolves to a hard corona over incubation times on the order of hours.5 First correlations between protein corona formation and biological behavior have been shown; e.g., it has been demonstrated that immunoglobulin binding leads to particle opsonization and hence promotes receptor-mediated phagocytosis.27 Decreased protein absorption on injected polyReceived: March 14, 2012 Revised: April 16, 2012 Published: April 23, 2012 9673

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rate constant for irreversible agglomeration processes.44 Assuming that every collision leads to a successful aggregation (i.e., the collision efficiency is 1) and further assuming that only monodisperse spheres are colliding, Smoluchowski44 derived the following expression for the perikinetic collision rate coefficient:

ethylene glycol (PEG) coated particles has led to longer circulation times and altered biodistribution.27 It has also been suggested that the corona-constituting proteins may be subjected to NP-influenced transport across membranes, bringing them into biological entities which they would not normally reach.11 The toxicological and immunological implications of such proposed effects remain unclear largely due to an incomplete comprehension of the underlying molecular mechanisms. While highly abundant proteins are assumed to dominate the protein corona for short time periods, the picture might change at longer time scales where proteins with low abundance but high affinities might prevail.13,16 An improved understanding of the biological effects of NPs requires a more profound knowledge of the binding properties of proteins and other molecules that associate with the NPs.11 It is now recognized how important a profound understanding of this protein corona is for shaping the surface properties, charges, resistance to aggregation, and hydrodynamic size of NPs.16,25 As discussed above, information about the mechanistic aspects of the NP/protein interaction and hence the importance of this interaction for cellular uptake and intracellular transport remains very scarce.17−19,28,29 Advancing our current physicochemical understanding of the bio−nano interface, we here provide a highly controlled analysis of the interactions between model NPs and proteins under standardized conditions. 1.1. Agglomeration of NPs in Biological Media. It was shown that many nanoparticles aggregate in media with a high electrolyte content.30−32 NPs are usually stabilized in solution by a repulsive barrier preventing particles from agglomeration upon collision with one another. Stabilization can be achieved by electrostatic or steric repulsion.33,34 The former depends on the surface charge of the particles and is destroyed to a large extent by the presence of electrolytes. The presence of proteins in the colloidal suspension can stabilize nanoparticles against agglomeration even in the presence of physiological electrolyte concentrations by steric or electrosteric effects. This relation between colloidal stability and protein corona formation was suggested before4,5,13,15,24,35,36 and attributed to a steric stabilization.7 1.2. Colloidal Stability and Collision Efficiencies. Agglomeration of nanoparticles in the presence of molecular species is far from being completely understood.37,38 However, the successful scientific assessment of biological effects of NPs is significantly impaired by agglomeration effects.39 Characterizing NP suspensions in protein-containing environments and assessing the consequences of corona formation remains an important issue. Colloidal NPs in liquid suspension always undergo Brownian motion, depending on their hydrodynamic radius and mass and the overall temperature. This thermal motion leads to collisions between the individual NPs. Depending on the overall stabilization of these particles, it can be avoided that these collisions lead to agglomeration. From the Derjaguin−Landau−Verwey−Overbeek (DLVO) theory,40,41 it follows that the repulsive barrier of chargestabilized NPs decreases with increasing electrolyte concentration, thus promoting formation of agglomerates. In principle, the agglomeration process depends mainly on binary collisions of particles, which leads to a second-order rate process that has been described in detail.37,42,43 Smoluchowski described this second-order rate process by the so-called perikinetic collision

ka,max =

4kBT 3η

(1)

In this equation, kB describes the Boltzmann constant, T the absolute temperature, and η the viscosity of the surrounding medium. For stabilized colloids with collision efficiencies smaller than 1, this rate decreases and can then be described by the following equation: ka =

1 taN0

(2)

Here N0 describes the initial concentration of primary particles and ta the agglomeration time, in which the number of particles is reduced to half of the initial value.37 The ratio ka/ka,max then represents the collision efficiency and hence contains information about the agglomeration rate. It can be expressed as a function of the interaction potential between the two spheres and is then denoted as the stability factor W.40,41 If ka < ka,max, not every collision leads to the formation of an agglomerate. However, if the repulsive barrier is completely destroyed, every collision leads to a successful agglomeration and hence the particles act as hard spheres and ka = ka,max holds. In this work, we study the influence of the protein corona formation on the colloidal stability and agglomeration efficiencies of charge-stabilized silver NPs. We have used these data and data acquired from circular dichroism (CD) spectroscopy to derive apparent binding affinities for the adsorption/desorption process of serum albumin onto silver NP surfaces.

2. EXPERIMENTAL SECTION Throughout all experiments described here, HSA solutions were handled in special low-binding microvials (Eppendorf, protein LoBind tubes). 2.1. Brownian Motion Nanoparticle Sizer (BMNS). Determining NP size distributions from tracking Brownian motion pathways of individual NPs is an extremely valuable approach for size determination of nanoparticulate colloids in liquid suspensions avoiding many of the common drawbacks of conventional methods.32 All BMNS measurements were carried out with a laboratory-built setup which has been previously described.7,32 It essentially comprises two different lasers (He−Ne laser, 632 nm, Uniphase, model 1135P, and Ar ion laser, 488 nm, Coherent, Innova 90 Plus), both allowing sufficient amounts of light to be coupled into the measuring cell to visualize individual NPs as scattering centers. The Brownian pathways of individual NPs can then be monitored and recorded using a commercial dark-field microscope (Askania, KMA1, objective 50×) equipped with a standard charge-coupled device (CCD) camera (The imaging Source, resolution 640 × 480 pixels) with a time resolution of 30 frames/s. From the pathways of single NPs, size distribution histograms can be derived using the Stokes−Einstein equation.45 The influence of shear forces within the measuring cell is eliminated with an iteration derived by Nordlund.46 The resulting diameter is then determined by a log-normal fit to the histogram data. 2.2. CD Measurements. CD spectroscopy has been used to elucidate structural changes within proteins during their interaction with NPs. All CD measurements were carried out using an AVIV 62 A DS CD spectrometer. The slit width was 1 μm, and the scanning step size was 0.1 nm. Measurements were performed in a 1 mm path length 9674

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Suprasil quarz cuvette. The protein concentration in solution was constant throughout the measurements at 0.052 mg mL−1. The total volume of the combined protein/NP solution was also kept constant by addition of deionized water. After mixing, all solutions were left to equilibrate at room temperature for 4 h. 2.3. Dialysis Experiments. Complementing the CD spectroscopy results, dialysis experiments were carried out. We used a cellulose ester tube membrane (Spectrum Spectra/Por Biotech) with an MWCO (molecular weight cutoff) of 100 000. This membrane can be penetrated by the HSA molecules but not by the NPs and hence not by NP−protein conjugates. NP suspensions were mixed with protein solution, and 5 mL of the mixed solution was placed inside the membrane tube after the usual incubation time. The tube ends were then sealed, and the filled tubes were situated in a beaker filled with 45 mL of deionized water (18.2 MΩ cm). The beaker was then sealed with Parafilm and the system left to equilibrate under stirring for 16 h at 21 °C. Thereafter, the protein content in the beaker outside of the membrane-enclosed volume was

being used as the particle size. For each particle size distribution, typically 200 individual particles were measured. Dynamic light scattering was performed by using a Malvern NanoZS Instrument (Worcestershire, U.K.) with a 633 nm “red” laser. For each sample, 3 measurements with 10 runs were performed, and the average value per sample was calculated. The resulting NP sizes are summarized in Table 1.

Table 1. Results of NP Characterization diameter (nm)

BMNS

DLS

TEM

36 ± 3

42 ± 3

32 ± 3

Figure 2. Nanoparticle size distribution determined by the BMNS. Figure 1. Comparison of the dialysis results with CD spectroscopic results, with the error bars indicating the standard deviation.

NP surface areas were determined using the BMNS histogram (Figure 2). This was done by calculating the surface area of all individual NPs contributing to the size distribution shown in Figure 2 (assuming a spherical shape) and dividing the result by the total number of NPs comprising the histogram. This leads to an average surface area of 8765 nm2 per NP (corresponding to a diameter of 53 nm).

determined using a Bradford assay. Figure 1 compares the protein concentrations determined by this procedure to the amount of free protein obtained from CD spectroscopic measurements. Slight differences between both methods all lie within the respective margins of error, and both approaches produce essentially the same results. It has to be pointed out that smaller protein concentrations can be measured using CD spectroscopy but are below a reliable detection limit of the Bradford assay. 2.4. NP Synthesis and Characterization. The colloidal silver NPs used in this study were prepared by a previously described procedure.7,32 Briefly, 17 mg of silver nitrate (Roth, ≥99.9%) was dissolved in 100 mL of deionized water (18.2 MΩ cm) and the solution boiled for 2 min. Thereafter, 10 mL of a 1% (w/w) trisodium citrate dihydrate (AppliChem, ≥99%) was added, and the solution was continuously boiled until it had a golden yellow color. At this point the solution was cooled to room temperature. All glassware was cleaned with boiling aqua regia followed by deionized water. After synthesis, the NPs were characterized by high-resolution transition electron microscopy (HRTEM), dynamic light scattering (DLS) and the BMNS (described above). HRTEM images were obtained with a CM300 UT transmission electron microscope from Philips (Amsterdam, The Netherlands). The samples were prepared by dropping 10 μL of silver dispersion onto hollow amorphous carbon films supported by a Cu grid purchased from Plano GmbH (Wetzlar, Germany). Images (∼50 particles) were analyzed using the software ImageJ (National Institutes of Health, Bethesda, MD), with the diameter of a circle of area equivalent to that of the measured particle

3. RESULTS AND DISCUSSION 3.1. Influence of the Protein Corona on Colloidal Stability. The influence of the protein corona on the colloidal stability was studied using a novel approach based on the stabilizing effect of the HSA protein corona. The destabilization of the repulsive barrier by addition of K2SO4 (this salt does not induce the precipitation of insoluble silver salts) was measured using the BMNS setup. Reduction of the agglomeration rate due to formation of a protein corona upon addition of different amounts of HSA was then observed. Throughout these measurements, equal amounts of citratestabilized silver NPs at a concentration of 2.86 × 1011 NPs·mL−1 were incubated with different amounts of HSA. HSA concentrations were chosen to correspond to concentrations needed for a monolayer formation around the NPs present and were then lowered for further experiments. After mixing, all NP/protein mixtures were left to equilibrate at room temperature for 4 h. Thereafter, a defined quantity of potassium sulfate (0.01538 mol·L−1) was added to these NP/protein solutions to induce agglomeration. The concentration was determined by agglomeration studies using this colloid and 9675

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represents the concentration where ka = ka,max and hence the repulsive barrier is fully destroyed. HSA is well-known to bind ionic compounds,47 but it should be noted that the salt concentrations used here exceed the binding capacity of the HSA molecules present in the mixture by several orders of magnitude. The time-dependent evolution of the hydrodynamic diameters of the agglomerating colloid was measured in time intervals of 2 min over a total time scale of 1−2 h. From these measurements, collision efficiencies were determined as described previously.32 The amount of HSA that can be accommodated on the NP surface was determined from the division of the surface area of an individual NP (as discussed above) by the well-known contact area of one HSA molecule. This approach has been widely adopted and was supported by size measurements,35,36,48 but it has also been suggested that it could underestimate the number of adsorbed proteins.49,50 The HSA molecule can be viewed as a triangular prism as previously described35,36,51 and is assumed to bind in a face-on configuration to the NP surface with a contact surface of ∼32 nm2.36 From these considerations, it follows that approximately 274 HSA molecules fit onto the surface of an average NP. The dependence of the collision efficiency on the HSA concentration was determined, and the results are shown in Figure 3. These data clearly reveal a decrease in the collision

efficiency with increasing protein concentration until the collision efficiency reaches zero and hence the colloid is stable even in the presence of the electrolyte. Complete stabilization occurs around a point where sufficient amounts of HSA are present in solution to form a monolayer on the NPs, illustrating well how the formation of the protein corona leads to an electrosteric or steric stabilization of the NPs which were previously charge stabilized. This is in line with previous findings showing that HSA exists as a monomer under these conditions,52 thus indicating a limited relevance of protein− protein interactions under these conditions. No formation of multilayers should therefore be expected, and it has been previously claimed that protein coronae exist as monolayers under similar conditions. 35,36 The same applies under physiological conditions with HSA concentrations of 35−50 g·L−1.52 Another aspect allowing formation of multilayers to be ruled out in these experiments is the zero collision efficiency for protein-coated NPs, which could not be observed in the case of relevant binding protein−protein interactions. However, to some extent there will possibly be interactions between the proteins constituting the corona around the same NP. To quantify the NP−protein interaction and to allow comparisons between information derived by different experimental approaches, apparent binding affinities can be determined as previously described using CD spectroscopy,7 fluorescence spectroscopy,53 and fluorescence correlation spectroscopy (FCS).36,48 It should be noted that CD measurements will generally refer to the so-called “hard” corona. From these results an apparent equilibrium constant KD could be derived for the protein adsorption/desorption equilibrium on the NP surface. It should be noted that these parameters are not proper equilibrium coefficients or affinities since the adsorption layer, or at least a significant fraction of it, is persistent and thus not appropriately described by a binding equilibrium. The fact that the protein concentration dependence of corona formation resembles an equilibrium binding curve35,36 when, in fact, it is not an equilibrium process is presently still a conundrum.1 Here, we derive this information using a new model based on statistical considerations of the collision geometries. For this model we assume that agglomeration between two colliding particles can only occur when two metal sites collide without having an HSA molecule bound to their surface. This is in line with our finding that a complete protein corona around the NP surfaces leads to a complete stabilization of the colloid. Collisions between two protein-covered sites and between protein-covered and uncovered metal sites do not lead to a successful agglomeration. This last assumption is in line with the fitted exponential curve in Figure 3 showing that a halfcoverage of the surface leads to a reduction of the collision efficiency to about 25% of ka,max (i.e., the probability for the collision of two uncovered surface sites under these conditions). These considerations can be rationalized by the following equation (see the Supporting Information for derivation):

Figure 3. Resulting collision efficiencies showing the inhibition of the salt-induced agglomeration by HSA−protein coronae.

ka ka,max

= (1 − Θ)2 (3)

Here, ka/ka,max again describes the collision efficiency and Θ the surface coverage of proteins binding to the silver NPs. This method can now be used for the evaluation of the agglomeration data acquired as described above. This approach

Figure 4. Hill fit to the experimental data of surface coverage versus the logarithmic HSA concentration (KD = 71 ± 17 nM nmol·L−1, n = 2.71). 9676

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has the advantage of avoiding the assumption of full surface coverage under equilibrium conditions. Rather, it allows the determination of the equilibrium position as described by the equilibrium constant. A plot of the surface coverage against the logarithmic protein concentration allows the evaluation of the data via a fitting routine using the Hill equation:36,54−56 1

Θ = Θmax 1+

(

KD [HSA]

n

)

(4)

This equation describes the dependence of the surface coverage Θ on the protein concentration [HSA], where Θmax is the maximum surface coverage, n is the Hill coefficient, and KD is the dissociation equilibrium constant, describing the position of the adsorption/desorption equilibrium. We obtain an apparent KD = 71 ± 17 nM (nmol·L−1) from our data using the Hill fit (Figure 4). Previous studies found values in the low nanomolar concentration range for metallic NPs7 and between 400 nM and 200 μM for polymer-coated NPs depending on the type of protein investigated.35,48 The Hill coefficient can usually be used to interpret the degree of cooperativity in binding during the surface adsorption process.35,55,57 The Hill fit to our data yields a Hill coefficient of n = 2.71, indicating a cooperative binding behavior.35 While generally an anticooperative behavior could have been expected for this adsorption situation, cooperative adsorption of proteins to NPs has been reported before35 and was attributed to stabilizing interactions between adjacent protein molecules. However, these interpretations should generally be treated with great caution due to the potential nonequilibrium character of the observed system. 3.2. Structural Integrity of HSA in the Protein Corona. Interactions of HSA with the same silver NPs were also quantitatively investigated using CD spectroscopy. CD signals of proteins arise from electronic transitions in specific secondary structural elements (e.g., α-helix, random coil, etc.). Monitoring them in dependence on the NP surface area present in solution at a constant protein concentration allows the α-helix content of the protein to be determined according to the method developed by Lu et al.58 This method has found a broad application in the interpretation of CD spectra.59−62 As serum albumin contains predominantly α-helices as secondary structural elements, the quantitative analysis of these data gives a good indication of the overall extent to which the original protein structure as a whole is destroyed in the interaction. This information can also be used to determine the amount of free protein remaining in solution.7,63 Typical spectra acquired from measurements with an HSA/Ag nanoparticle system are displayed in Figure 5. These spectra allow the determination of the amount of free protein present in the solution, [P]. For pure HSA a value of 70% for the α-helix content is determined by this method, which is well in line with literature values.51,64 This value is then set to be 100% of intact protein as determined by the CD signal, [P0]. Any loss in the α-helix content is attributed to loss of free protein and hence adsorption of proteins on NP surface sites, [S]. Subsequently, the α-helix content of the protein is determined from the CD signal at various NP concentrations as described, and [P] is determined in relation to [P0] by the rule of proportion. Assuming a simple adsorption/desorption equilibrium of proteins bound to NP surface sites being in equilibrium with

Figure 5. CD spectra of HSA with citrate-stabilized silver nanoparticles (diameter 36 nm with NP surface site concentrations ranging from 1.1 × 1014 to 4.8 × 1014 nm2·mL−1 and a protein concentration of 0.052 mg·mL−1).

free proteins and free surface sites, an apparent equilibrium constant KD can be derived from a plot of [P0]/[P] − 1 versus [S](1/KD) according to eq 5 (see the Supporting Information [P0] 1 − 1 = [S] [P] KD

(5)

for details of the derivation). The KD values resulting from this approach will also suffer from the consequences of nonequilibrium behavior as discussed above. Using this procedure for the evaluation of the CD results, a KD value of 33 ± 11 nM was derived for the adsorption/ desorption of HSA to the Lee−Meisel-type silver NPs. This compares reasonably well to the 71 ± 17 nM derived from the agglomeration experiments described above considering the margin of error of both values. The remaining differences are small compared to differences reported for different individual proteins on the same NPs35,48 and also compared to the differences of several orders of magnitude in KD introduced by different NP surface coatings.7

4. CONCLUSIONS In this study we have convincingly demonstrated that the protein corona formed by HSA around citrate-functionalized silver NPs stabilizes the particles against agglomeration. Additionally, we showed how this stabilizing effect on the NP agglomeration kinetics can be employed as a novel approach to determine apparent affinities describing the protein adsorption/ desorption equilibrium. Moreover, we used circular dichroism spectroscopy as a complementing method to also determine affinities for the same process. While the agglomeration experiments utilize changes in the behavior of the colloid (i.e., the influence of the protein on the NP stability), the CD approach is based on structural information about the protein only. Notably, both methods are largely independent of the NP properties and thus present ideal tools for studying protein adsorption even in complex environments, such as human body fluids. The apparent KD values that were determined using both approaches are in line with each other but should generally be interpreted with caution as discussed above. The protein 9677

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(10) Deng, Z. J.; Liang, M.; Monteiro, M.; Toth, I.; Minchin, R. F. Nanoparticle-induced unfolding of fibrinogen promotes Mac-1 receptor activation and inflammation. Nat. Nanotechnol. 2011, 6, 39−44. (11) Klein, J. Probing the interactions of proteins and nanoparticles. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 2029−2030. (12) Lynch, I.; Dawson, K. A.; Linse, S. Detecting cryptic epitopes created by nanoparticles. Sci. STKE 2006, 2006, 14. (13) Cedervall, T.; Lynch, I.; Lindman, S.; Berggård, T.; Thulin, E.; Nilsson, H.; Dawson, K. A.; Linse, S. Understanding the nanoparticle− protein corona using methods to quantify exchange rates and affinities of proteins for nanoparticles. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 2050−2055. (14) Linse, S.; Cabaleiro-Lago, C.; Xue, W.-F.; Lynch, I.; Lindman, S.; Thulin, E.; Radford, S. E.; Dawson, K. A. Nucleation of protein fibrillation by nanoparticles. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 8691−8696. (15) Lundqvist, M.; Stigler, J.; Elia, G.; Lynch, I.; Cedervall, T.; Dawson, K. A. Nanoparticle size and surface properties determine the protein corona with possible implications for biological impacts. Proc. Natl. Acad. Sci. U.S.A. 2008, 105, 14265−14270. (16) Nel, A. E.; Mädler, L.; Velegol, D.; Xia, T.; Hoek, E. M. V.; Somasundaran, P.; Klaessig, F.; Castranova, V.; Thompson, M. Understanding biophysicochemical interactions at the nano−bio interface. Nat. Mater. 2009, 8, 543−557. (17) des Rieux, A.; Fievez, V.; Garinot, M.; Schneider, Y.-J.; Préat, V. Nanoparticles as potential oral delivery systems of proteins and vaccines: a mechanistic approach. J. Controlled Release 2006, 116, 1− 27. (18) Yan, M.; Du, J.; Gu, Z.; Liang, M.; Hu, Y.; Zhang, W.; Priceman, S.; Wu, L.; Hong Zhou, Z.; Liu, H.; Segura, T.; Tang, Y.; Lu, Y. A novel intracellular protein delivery platform based on single-protein nanocapsules. Nat. Nanotchnol. 2009, 5, 48−53. (19) Liu, L.; Xu, K.; Wang, H.; Tan, P. K., J.; Fan, W.; Venkatraman, S. S.; Li, L.; Yang, Y.-Y. Self-assembled cationic peptide nanoparticles as an efficient antimicrobial agent. Nat. Nanotechnol. 2009, 4, 457− 463. (20) Müller, R. H.; Keck, C. M. Drug delivery to the brain realization by novel drug carriers. J. Nanosci. Nanotechnol. 2004, 4, 471−483. (21) Gilbert, B.; Huang, F.; Zhang, H.; Waychunas, G. A.; Banfield, J. F. Nanoparticles: strained and stiff. Science 2004, 305, 651−654. (22) Min, Y.; Akbulut, M.; Kristiansen, K.; Golan, Y.; Israelachvili, J. The role of interparticle and external forces in nanoparticle assembly. Nat. Mater. 2008, 7, 527−538. (23) Schneider, L.; Peukert, W. Review: second harmonic generation spectroscopy as a method for in situ and online characterization of particle properties. Part. Part. Syst. Charact. 2006, 23, 351−359. (24) Cedervall, T.; Lynch, I.; Foy, M.; Berggård, T.; Donnelly, S. C.; Cagney, G.; Linse, S.; Dawson, K. A. Detailed identification of plasma proteins adsorbed on copolymer nanoparticles. Angew. Chem., Int. Ed. 2007, 46, 5754−5756. (25) Tenzer, S.; Docter, D.; Rosfa, S.; Wlodarski, A.; Kuharev, J.; Rekik, A.; Knauer, S. K.; Bantz, C.; Nawroth, T.; Bier, C.; Sirirattanapan, J.; Mann, W.; Treuel, L.; Zellner, R.; Maskos, M.; Schild, H.; Stauber, R. H. Nanoparticle size is a critical physicochemical determinant of the human blood plasma corona: a comprehensive quantitative proteomic analysis. ACS Nano 2011, 5, 7155−7167. (26) Cedervall, T.; Lynch, I.; Lindman, S.; Berggård, T.; Thulin, E.; Nilsson, H.; Dawson, K. A.; Linse, S. Understanding the nanoparticle− protein corona using methods to quantify exchange rates and affinities of proteins for nanoparticles. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 2050−2055. (27) Owens, D. E.; Peppas, N. A. Opsonization, biodistribution, and pharmacokinetics of polymeric nanoparticles. Int. J. Pharm. 2006, 307, 93−102. (28) Borm, P. J.; Robbins, D.; Haubold, S.; Kuhlbusch, T.; Fissan, H.; Donaldson, K.; Schins, R.; Stone, V.; Kreyling, W.; Lademann, J.;

corona that is formed in our experiments around silver NPs consists of a protein monolayer on the NP surfaces, supporting previous findings of HSA adsorption to polymer-coated NPs.36 Our results underline the potential of both methods to determine quantitative information about the adsorption of proteins to NP surfaces. Our current knowledge about the protein adsorption to NP surfaces does not allow a more detailed assessment of the physiological implications of these findings. However, the techniques described in this work set the stage for future studies examining the biologically most relevant corona constituents and integrating additional NPs with defined surface functionalization.



ASSOCIATED CONTENT

S Supporting Information *

Details about the determination of KD values and about the derivation of surface coverage from the collision efficiency. This material is available free of charge via the Internet at http:// pubs.acs.org/.



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]; [email protected]. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS L.T., R.H.S., J.S.G., Ma.M., and Mi.M. acknowledge the support of this work by the Deutsche Forschungsgemeinschaft within the priority program Bio-Nano-Responses, SPP1313. J.S.G. acknowledges support via a Ph.D. scholarship from the Deutsche Bundesstiftung Umwelt. L.T. acknowledges support via a Young Scientists Grant from the University of DuisburgEssen and by the Bruno-Werdelmann Foundation.



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