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Structure and Interaction in pH-Dependent Phase Behavior of Nanoparticle-Protein Systems Indresh Yadav, Sugam Kumar, Vinod K. Aswal, and Joachim Kohlbrecher Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.6b04127 • Publication Date (Web): 12 Jan 2017 Downloaded from http://pubs.acs.org on January 14, 2017
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Structure and Interaction in pH-Dependent Phase Behavior of Nanoparticle-Protein Systems
Indresh Yadav†,#, Sugam Kumar†, Vinod K. Aswal†,#,* and Joachim Kohlbrecher‡
†
Solid State Physics Division, Bhabha Atomic Research Centre, Mumbai 400 085, India #
‡
Homi Bhabha National Institute, Mumbai 400 094, India
Laboratory for Neutron Scattering, Paul Scherrer Institut, CH-5232 PSI Villigen, Switzerland
*Corresponding author. E-mail:
[email protected], Phone: +91 22 25594642, Fax: +91 22 25505151 1 ACS Paragon Plus Environment
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ABSTRACT The pH-dependent structure and interaction of anionic silica nanoparticles (diameter 18 nm) with two globular model proteins-lysozyme and bovine serum albumin (BSA) have been studied. Cationic lysozyme adsorbs strongly on the nanoparticles and the adsorption follows an exponential growth as a function of lysozyme concentration, where the saturation value increases with pH approaching towards the isoelectric point (IEP) of lysozyme. In contrast, irrespective of the pH, anionic BSA does not show any adsorption. Despite having different nature of interactions both proteins render the similar phase behavior where nanoparticleprotein systems transform from one-phase (clear) to two-phase (turbid) above a critical protein concentration (CPC). The measurements have been carried out for fixed concentration of silica nanoparticles (1 wt %) with varying proteins concentration (0-5 wt %). The CPC is found to be much higher for BSA than lysozyme and increases for lysozyme but decreases for BSA with pH approaching towards their respective IEPs. The structure and interaction in these systems have been examined by dynamic light scattering (DLS) and small-angle neutron scattering (SANS). The effective hydrodynamic size of the nanoparticles measured by DLS increases with protein concentrations and is related to the aggregation of the nanoparticles above CPC. The propensity of the nanoparticles aggregation is suppressed for lysozyme and enhanced for BSA with varying pH towards their respective IEPs. This behavior is understood by SANS data through interaction potential determined by interplay of electrostatic repulsion with the short-range attraction for lysozyme and the long-range attraction for BSA. The nanoparticle aggregation is caused by the charge neutralization by oppositely charged lysozyme, whereas through depletion for similarly charged BSA. Lysozyme mediated attractive interaction decreases with pH approaching IEP due to decrease in charge on the protein. In the case of BSA, decrease in BSA-BSA repulsion enhances the depletion attraction between the nanoparticles as pH is shifted towards IEP. The morphology of the nanoparticle aggregates is found to be mass fractal.
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INTRODUCTION Recently, the nanoparticle-protein systems have gained much attention as they show rich phase behavior which has myriad applications in biology and material science.1-3 The interactions of the nanoparticles with proteins can control the protein-protein interactions, enzymatic activity, protein delivery and applied to diagnostics and sensors.4-6 For their part, proteins may induce the phase transformations of the nanoparticles for instance glass transition, gelation, crystallization and flocculation which could be used to prepare multifunctional materials.7-10 The important interactions those govern the phase behavior of the nanoparticle-protein systems are van der Waals, hydrogen bonding, steric repulsion, electrostatic and depletion.7 The dominance of a particular interaction depends on the intrinsic characteristics (e.g. size, shape, charge, hydrophobicity or hydrophilicity) of the nanoparticles and proteins.7,9 Furthermore the strength and range of these interactions ascertain the macroscopic properties of the resultant systems, and easily tuned by varying solution parameters such as ionic strength, pH, temperature and concentration.10-14 The well known Derjaguin-Landau-Verwey-Overbeek (DLVO) theory combining attractive van der Waals and repulsive electrostatic double-layer interactions has been widely used to describe the equilibrium phase behavior of the charged colloidal systems.15 However, in the case of nanoparticle-protein complexes, non-DLVO interactions such as depletion, steric and solvation forces need to be taken into account.7,16 For example, the selective adsorption of protein can enhance the colloidal stability by steric repulsion whereas depletion induced aggregation of the nanoparticles occur for non-adsorbing protein.13,17 In addition to this the asymmetric distribution of charges and presence of hydrophobic patches on protein molecules is also known to influence their interaction with the nanoparticles.18 In many cases, the interaction of proteins to hydrophilic surfaces has been attributed to electrostatic interaction, where proteins strongly adsorb on the oppositely charged surfaces.19-22 On the 3 ACS Paragon Plus Environment
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other hand, even under electrostatically unfavourable conditions, protein adsorb onto hydrophobic surfaces where entropy driven hydrophobic attraction dominates over electrostatic repulsion.20 The understanding of these interactions plays important role in controlling the nanoparticle-protein interactions and ensuing phase behavior. Scattering techniques (dynamic light scattering (DLS), small-angle neutron/X-ray scattering (SANS/SAXS)) along with complementary techniques (zeta potential, cryo-TEM, UV-vis and circular dichroism (CD) spectroscopy) have been extensively employed to study the nanoparticle-protein interactions.19-24 Zeta potential has been widely used to determine the stability of the nanoparticle-protein complexes and results are interpreted in terms of protein binding to the nanoparticles.19,20 UV-vis spectroscopy provides information on protein adsorption by the red-shift of the spectra for metal nanoparticles.24,25 On the other hand, the possibility to separate adsorbed and non-adsorbed protein by centrifugation and subsequently measured absorbance spectra of proteins are utilized to quantify the adsorbed protein for both the metallic and non-metallic nanoparticles.21-23 Any conformation changes in protein on their interaction with the nanoparticles are mostly probed by CD spectroscopy.11,23 Cryo-TEM can give the direct imaging of the nanoparticle-protein conjugates.22,23 However, the sample preparations are tricky and the structures measured are not under native conditions, moreover much less sensitive to the details of microscopic interactions in the system. Scattering techniques measure the samples in-situ and under native conditions also highly sensitive to interactions in the system. The structural information of the system is obtained by DLS through the diffusion of particles.26 In SANS and SAXS, both the structure and interaction can be determined via form factor and structure factor of the scattering intensity, respectively.27,28 The nanoparticle-protein interactions have been mostly studied for charged nanoparticles with globular proteins.20-25 The important issues have been looked into are 4 ACS Paragon Plus Environment
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adsorption isotherms of protein on the nanoparticles, conformational changes of adsorbed proteins, and structures and resultant phase behavior of the complexes. The results are found to be strongly depending on the characteristic of the nanoparticles and proteins as well as solution conditions such as ionic strength and pH.11,29-32 We have been interested to study the interaction of anionic silica nanoparticles with two globular proteins-lysozyme and bovine serum albumin (BSA).33-36 In these systems, the electrostatic interactions dictate the nanoparticle-protein interactions and their resultant phases. SANS was employed to probe the interactions and structures governing the phase behavior. The interactions between the nanoparticles in presence of proteins are successfully modelled by combining electrostatic repulsion with short-range attraction for lysozyme and long-range attraction in the case of BSA protein.33 In the systems dominated by attractive interaction leads to the nanoparticle aggregation, which are characterised as fractal.33,36 The differences in phase behavior of the nanoparticles with lysozyme and BSA proteins are interpreted in terms of different adsorption isotherms of these proteins on the nanoparticles.35 In varying ionic strength, the modifications in nanoparticle-nanoparticle, nanoparticle-protein and protein-protein interactions results in significant changes in the phases of the nanoparticle-protein systems.34 The interplay of number density effect and surface area effect by varying the size of the nanoparticles on their interaction with proteins has also been examined.35 The pH of the solution is another important parameter, which can be used to tune the nanoparticle-protein interactions and resultant phase behavior.11,22,36 In this paper, we have studied the pH effect on nanoparticleprotein interactions as the pH of solution is varied from physiological to IEP of the proteins. The pH variation allows systematic changes in the electrostatic interactions of the components in the system. The pH-dependent interaction of anionic silica nanoparticles with lysozyme and BSA proteins has been examined by zeta potential, UV-vis spectroscopy, DLS and SANS. The effect of the pH on protein adsorption, phase behavior (one-phase to twophase transformation), structures and interactions in these systems are reported.
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EXPERIMENTS The electrostatically stabilized colloidal suspensions of spherical silica nanoparticles (Ludox HS40, catalog no. 420816) and lyophilized powder proteins (lysozyme, catalog no. 62970 and BSA, catalog no. A2153) were purchased from Sigma-Aldrich. Samples were prepared in 20 mM phosphate buffer at pH7 in D2O by keeping concentration of silica nanoparticles fixed (1 wt %) and varying the concentration (0-5 wt %) of proteins. The pH was raised or lowered by adding small amount of 1 M NaOH or 1 M HCl, respectively. The adsorption isotherms of proteins on the nanoparticles were obtained using a nanodrop spectrophotometer ND 1000. The instrument has a pulsed Xenon flash lamp as a source (2200-7500 Å) and the sample absorbance spectra were measured using CCD arrays. The zeta potential and DLS measurements were performed on nanoparticle size analyzer SZ-100 (HORIBA, Japan). This instrument is equipped with a green (5320 Å) laser and photomultiplier tube detectors. A detection angle of 173° was chosen for the DLS measurements. SANS experiments were carried out at the SANS-I facility at the Swiss spallation neutron source, SINQ, Paul Scherrer Institut, Switzerland.37 A combination of two sample-to-detector distances (2 and 8 m) at mean wavelength (λ) 6 Å with wavelength resolution (∆λ/λ) ~ 10 % were used to cover a scattering vector (Q = 4πsin(θ/2)/λ, where θ is scattering angle) range of 0.006-0.25 Å-1. The scattered neutrons are detected using a large (96 × 96 cm2) He3 area detector. The data were corrected and normalized to absolute scale using standard procedure. All the measurements were performed at constant temperature of 30oC. DATA ANALYSIS Dynamic light scattering. DLS has been used to measure the collective diffusion of the nanoparticle-protein systems. This technique relies on the detection and analysis of fluctuations in the intensity of scattered light by particles in a medium subject to Brownian motion. Experimentally, one measures the fluctuations in terms of normalized autocorrelation 6 ACS Paragon Plus Environment
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function (ACF) [g(2)(τ)] of scattered light intensity. For an ergodic system, it is related to the electric field autocorrelation function [g(1)(τ)] by the Siegert relation as26,38
g (2) (τ ) = β [ g (1) (τ )]2 + 1
(1)
where τ is the delay time in the ACF and β (0 < β < 1) is an experimental constant called spatial coherence factor whose magnitude depends on the optical geometry. For monodisperse spherical scatterers g(1)(τ) decay exponentially, whereas for polydisperse system it can be written as the Laplace transform of the distribution of decay constants G(Γ) as26 ∞
g (1) (τ ) = ∫ G(Γ )exp(−Γτ )d Γ
(2)
0
where Γ (=DQ2) is the decay constant for a given size with the translational diffusion coefficients D of the particles and the magnitude of scattering vector Q. The cumulant analysis can be used to calculate the average decay constant and the polydispersity. In this analysis, Equation (2) can be written as26
g (τ ) = exp[−Γτ + (1)
µ2τ 2 2
]
(3)
where Γ is the average decay constant and µ2 is the variance. The ratio of variance to the square of the average decay constant is called the polydispersity index (PI). From average diffusion coefficient, the effective hydrodynamic size can be calculated using Stokes-Einstein relation. However, the application of the method of cumulants is limited to monomodal distribution with small polydispersity where the criteria µ2τ2
