Simultaneous Surface Plasmon Resonance and Quartz Crystal

Nov 6, 2004 - The UV/ozone exposure used to clean all surfaces before a measurement is started also completes the SiO2 films (oxygen saturation), whic...
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Anal. Chem. 2004, 76, 7211-7220

Simultaneous Surface Plasmon Resonance and Quartz Crystal Microbalance with Dissipation Monitoring Measurements of Biomolecular Adsorption Events Involving Structural Transformations and Variations in Coupled Water Erik Reimhult,*,† Charlotte Larsson, Bengt Kasemo, and Fredrik Ho 1o 1 k*

Department of Applied Physics, Chalmers University of Technology, Go¨teborg, S-412 96, Sweden

Simultaneous quartz crystal microbalance with dissipation monitoring (QCM-D) and surface plasmon resonance (SPR) measurements are used to analyze the surface kinetics of two biomacromolecular systems, one lipid and one protein based, undergoing surface-induced conformational changes. First we establish a theoretical platform, which allows quantitative analysis of the combined SPR and QCM-D data. With this theoretical base, new information can be extracted, not obtainable with either technique alone. As an example we demonstrate how time-resolved measurements with these two techniques in combinationsyielding three independent measured quantitiessadd new information about (i) kinetics, i.e. number of adsorbed molecules per unit area versus time, and (ii) temporal variation in the mass fraction of coupled water versus coverage. In particular, it is demonstrated for the first time, how the kinetics of the process during which adsorbed vesicles are spontaneously transformed into a supported phospholipid bilayer (SPB) on SiO2 can be quantitatively separated into its two dominating states: adsorbed vesicles and supported planar bilayer patches. In addition, the relevance of dynamically coupled water for interpretation and modeling of the QCM-D response during bilayer formation is discussed and further illustrated with a second model system: streptavidin adsorption on a biotin-modified SPB. A very strong coverage dependence in the number of water molecules per protein sensed by the QCM is demonstrated, with strong implications for the use of QCM as a tool for quantitative determination of protein mass uptake kinetics. Scientific studies and applications of biomolecular interactions, e.g., binding kinetics, affinity constants, and abundance in unknown samples, rely increasingly on surface-based analytical techniques. For this purpose, a variety of physical principles, e.g. * To whom correspondence should be addressed. Telephone: +65-6874-8378. Fax: +65-6872-0785. E-mail: [email protected]. Telephone: +4646-2227740 Fax: +46-46-2223637. E-mail: [email protected]. † Current address: Institute of Materials Research and Engineering, 3 Research Link, Singapore 117602, Singapore. 10.1021/ac0492970 CCC: $27.50 Published on Web 11/06/2004

© 2004 American Chemical Society

optical, electrical, electroacoustic, and micromechanical, are employed to this end.1 In particular, detection of changes in the interfacial (optical) refractive index, upon, for example, binding events, is a central detection principle utilized in, for example, surface plasmon resonsance (SPR),2,3 optical waveguide lightmode spectroscopy, ellipsometry,4 reflectometric interference spectroscopy,5 and coupled plasmon waveguide resonance,6 The measured signal originates in these cases from the influence caused by the polarizability of the (bio)macromolecules (refractive indices) on an incident electric field that is often locally amplified in the sensing region. Under appropriate conditions, a detection sensitivity of down to 10-5 is achieved. Due to the close to linear relation that exists between changes in (bio)macromolecule concentration and effective refractive index, dc/dn,7 this measurement principle has become extremely valuable for measurements of adsorbed mass of biomolecules. This in particular so, because the measured variable can be obtained with high sampling rate facilitating detailed analysis of binding kinetics.8 Despite the success of the optical refractive index-based techniques, there are inherent limitations in measurements based on a single measured quantity (refractive index in this case). As increasingly more detailed information is required or the complexity of the systems under investigation is increased, there is a growing need to measure independent quantities in order to arrive at correct and unambiguous interpretations. With such multiobservable measurements, generally requiring a multitechnique approach, there is a potential to access information hidden in different binding pathways, transition states, phase transitions, and structural changes associated with the measured interactions. One must also be aware that severe misinterpretation of binding (1) Cunningham, A. J. Introduction to bioanalytical sensors; John Wiley & Sons: New York, 1998. (2) Homola, J.; Yee, S. S.; Gauglitz, G. Sens. Actuators, B 1999, 54, 3-15. (3) Lo¨fa˚s, S.; Malmqvist, M.; Ro¨nnberg, I.; Stenberg, E.; Liedberg, B.; Lundstro¨m, I. Sens. Actuators, B 1991, 5, 79-84. (4) Azzam, R. M.; Bashara, N. M. Ellisometry and polarized light; North-Holland Physics Publishing: Amsterdam, 1987. (5) Ha¨nel, C.; Gauglitz, G. Anal. Bioanal. Chem. 2002, 372, 91-100. (6) Salamon, Z.; Tollin, G. Spectroscopy 2001, 15, 161-175. (7) Jung, L. S.; Campbell, C. T.; Chinowsky, T. M.; Mar, M. N.; Yee, S. S. Langmuir 1998, 14, 5636-5648. (8) Liedberg, B.; Lundstro¨m, I.; Stenberg, E. Sens. Actuators, B 1993, 11, 6372.

Analytical Chemistry, Vol. 76, No. 24, December 15, 2004 7211

kinetics can result if, for example, structural changes or macromolecular rearrangements affect the measured observable, such as temporal variations in thickness, dc/dn, or both. While most previous combinations of different surface-analytical tools have not allowed for simultaneous recording of binding kinetics, but comparison of saturated response only, we show in this paper how simultaneous measurements using the SPR and quartz crystal microbalance with dissipation monitoring (QCMD) technique under identical conditions enables information from independent quantities to be obtained also during adsorption/ binding kinetics. In contrast to SPR, the QCM-D technique9-11 is based on an entirely different transducer principle, namely, on the variation in the electromechanical response of a shear-oscillating piezoelectric sensor, caused by, doe example, biomolecule binding or structural transformations in biomolecular adlayers. As a consequence, the mass obtained by QCM-D measurements corresponds to the total mass coupled to the motion of the sensor crystal, including both the mass of the biomolecules, measured by, for example, SPR and the water bound to or dynamically coupled to the film. The difference between the mass obtained from QCM measurements, mQCM, and the mass obtained via measurements of the refractive index, m∆n, when operated in aqueous solution, thus originates from water dynamically coupled by the biomolecules in the film (see refs 12-14 and references therein). As illustrated in this work, simultaneous measurements of the biomolecule mass, proportional to the density of molecules (SPR) and the dynamically coupled mass (QCM), including bound and trapped water. In addition, by measuring the temporal variation in the D factor (relating to the viscoelastic properties of the adsorbate), new information and much improved interpretation schemes, not obtainable by either technique or quantity alone, is obtained. In particular, the introduction of simultaneous D measurements at multiple harmonics adds a 3-fold advantage compared to classical QCM measurements, as done in previous studies combining SPR and QCM:15-18 First, a proper base for appropriate theoretical modeling of the temporal variations in both the optical, m∆n(t), and acoustical mass, mQCM(t), is obtained. It is shown how this makes possible reliable analysis of binding kinetics (the number of adsorbed molecules versus time) also for systems of (bio)macromolecules that undergo significant structural transformations. Second, the variation in the amount of dynamically coupled water, mwater(t) () mQCM(t) - m∆n(t)), is determined not only on the surface saturated with biomolecules

as in previous studies,12,13,19 but also during the sequence of adsorption/binding events or structure transformations leading up to saturation. Third, quantification of the amount of dynamically coupled water makes it possible to estimate the temporal variation in the effective density of the adlayer. By then using the timeresolved effective density as input, a more accurate Voigt-Kelvinbased viscoelastic analysis of combined f and D QCM-D measurements is arrived at (the effective density could previously only be assumed based on similar systems.)13,20 Two model systems are used to demonstrate the advantage of the combined, simultaneous SPR and QCM-D measurements. The first one, for which condensed combination data have been presented separately and been further analyzed with respect to that particular process,21 but without the detailed theoretical platform described here, is the adsorption kinetics of vesicles and subsequent, spontaneous formation of supported phospholipid bilayer (SPB) on SiO2.22 This system is known to undergo large conformational changes. We demonstrate how neither technique alone captures the true kinetics (number of lipids adsorbed versus time) because of the occurrence of the transition from intact vesicles to bilayer, while the kinetics are reliably reproduced when the QCM-D and SPR data are properly combined. The second model system uses a SPB template, containing a small fraction (5%) of biotin-lipids to investigate streptavidin binding. Streptavidin is known to undergo a two-dimensional rearrangement, and even crystallization, on planar supported bilayers.23 In this case, focus is put on how the variation in dynamically coupled water influences the binding kinetics as measured with the QCM-D technique and how knowledge about the water content improves a viscoelastic analysis of structural changes in this type of system.

(9) Rodahl, M.; Ho¨o ¨k, F.; Krozer, A.; Brzezinski, P.; Kasemo, B. Rev. Sci. Instrum. 1995, 66, 3924-3930. (10) Rodahl, M.; Ho ¨o ¨k, F.; Kasemo, B. Anal. Chem. 1996, 68, 2219-2227. (11) Janshoff, A.; Galla, H. J.; Steinem, C. Angew. Chem., Int. Ed. 2000, 39, 40044032. (12) Ho ¨o ¨k, F.; Vo ¨ro ¨s, J.; Rodahl, M.; Kurrat, R.; Boni, P.; Ramsden, J. J.; Textor, M.; Spencer, N. D.; Tengvall, P.; Gold, J.; Kasemo, B. Colloids Surf., B 2002, 24, 155-170. (13) Larsson, C.; Rodahl, M.; Ho ¨o ¨k, F. Anal. Chem. 2003, 75, 5080-5087. (14) Ho¨o ¨k, F.; Kasemo, B.; Nylander, T.; Fant, C.; Sott, K.; Elwing, H. Anal. Chem. 2001, 73, 5796-5804. (15) Bailey, L. E.; Kambhampati, D.; Kanazawa, K. K.; Knoll, W.; Frank, C. W. Langmuir 2002, 18, 479-489. (16) Bund, A.; Baba, A.; Berg, S.; Johannsmann, D.; Lu ¨ bben, J.; Wang, Z.; Knoll, W. J. Phys. Chem. B 2003, 107, 6743-6747. (17) Plunkett, M. A.; Wang, Z.; Rutland, M. W.; Johannsmann, D. Langmuir 2003, 19, 6837-6844. (18) Laschitsch, A.; Menges, B.; Johannsmann, D. Appl. Phys. Lett. 2000, 77, 2252-2254.

where deffective is obtained as an output from a weighted leastsquares fit (Q-tools software 2.0.2, Q-Sense AB) between the experimental data and the Voigt model (using at least two harmonics, as described in detail elsewhere13). In the elastic limit, i.e., when D f 0, mVoigt f mSauerbrey, where the latter is given by25

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THEORY AND DATA ANALYSIS Combined measurements of f and D with the QCM-D technique were analyzed using a Voigt-Kelvin-based viscoelastic model.20,24 In this viscoelastic representation, the film is defined by an effective thickness (deffective), density (Feffective), and complex shear modulus (µ+iωη), where η is the effective shear viscosity, µ the effective shear elasticity, and ω ) 2πf the oscillation frequency. As described previously,13 the use of an effective film density, Feffective, makes it possible to estimate the mass uptake, mVoigt, via

mVoigt ) deffectiveFeffective

mSauerbrey ) (C/ν)∆f

(1)

(2)

where C ()17.7 ng/(cm2‚Hz) at f ) 5 MHz) is the mass sensitivity (19) Vo ¨ro ¨s, J. Biophys. J. 2004, 87, 553-561. (20) Voinova, M. V.; Rodahl, M.; Jonson, M.; Kasemo, B. Phys. Scr. 1999, 59, 391-396. (21) Reimhult, E.; Za¨ch, M.; Ho ¨o ¨k, F.; Kasemo, B. Submitted to Biophys. J. (22) Keller, C. A.; Kasemo, B. Biophys. J. 1998, 75, 1397-1402. (23) Reviakine, I.; Brisson, A. Langmuir 2001, 17, 8293-8299.

constant and ν ()1, 3, ...) is the overtone number. In the nonelastic regime, i.e., when ∆D * 0, mVoigt is generally higher than mSauerbrey for acoustically thin films probed in aqueous environment. The different systems investigated in this paper are of both types (see below). It should be pointed out too, that even if the viscoelastic components (η and µ) can be separated through this theoretical treatment, the density and thickness cannot.13 Accordingly, the density, which is known to be somewhere between that of water (∼1.0 g/cm3) and (bio)macromolecules (typically being between 1.1 and 1.7 g/cm3 depending on the system) must be guessed and used as a constant input in the modeling. While this uncertainty has a negligible influence on the determination of mVoigt, i.e., the obtained mass is essentially conserved independent of the choice of density in this interval, the estimation of the effective film thickness is inversely proportional to the assumed effective density Feffective (cf. eq 1 and below). Accordingly, a proper quantification of film thickness requires that the density is known, which in turn requires that the amount of entrapped water is known. Fortunately, this number can be obtained by comparing the mass uptake obtained from QCM-D measurements with those obtained from SPR measurements, if properly analyzed. In the framework proposed by Jung et al.,7 developed in order to translate changes in plasmon angle, ∆Θ, into changes in refractive index of an adsorbed film, account is taken of the decaying sensitivity of the evanescent field. Thus, the change in refractive index, ∆n, within an adsorbed (bio)film of thickness, d, is

∆Θ ∆n ) κ 1 - e-2d/ldecay

(3)

where κ is the sensitivity factor of the system relating a change in ∆Θ to the change in refractive index within the evanescent field and ldecay is the decay length of the evanescent field given by

ldecay )

( {( 2π Re λ

-

nm4 2

) }) x 1/2

2

nAu + nm

-1

=

λ 2π

-

r,Au + r,m r,m2

(4)

where λ ) 632.8 nm is the excitation wavelength, r,m ) n2m, the dielectric constant of the medium in the evanescent field,26 and nAu the complex refractive index of gold (r,Au ) Re{n2Au} ≈ -13.5 at 633 nm).8,27 Commonly the adsorbed mass also in an aqueous environment is approximated as linearly related to the change in refractive index (eq 3), i.e.,

m∆n ) d(dc/dn)∆n

(5)

where dc/dn is the inverse of the refractive index increment with (24) Domack, A.; Prucker, O.; Ru ¨ he, J.; Johannsmann, D. Phys. Rev. E 1997, 56, 680-689. (25) Sauerbrey, G. Z. Phys. 1959, 155, 206-222. (26) Simplifying to use the refractive index of the buffer produces a negligible error, but in this work the measured effective refractive index was used calculated as the sensitivity factor times the angle shift for each measurement point.

bulk concentration.28 By combining eqs 3 and 5, we obtain

m∆n ) d

∆Θ dc κ dn 1 - e-2d/ldecay

(6)

which can be used as an easy, but fairly accurate, formula for determining the adsorbed mass (see Supporting Information for a comparison with a treatment employing the Fresnel equations for a multilayer system including interference effects). However, in the thin-film limit d , ldecay/2 (ldecay/2 being the sensitivity depth of the SPR, ∼95 nm in the present case) eq 6 can be rewritten as

m∆n )

ldecay dc κ∆Θ ) CSPR∆Θ 2 dn

(7)

By calibrating the change in SPR angle with solutions (glycerol) mixed in Milli-Q water of known refractive index, κ was estimated to be 9.4926 × 10-3 deg-1. Furthermore, using known and calculated values for dc/dn, CSPR is 345.24 and 504.15 ng/ (cm2‚deg) for SPB and proteins, respectively.29-31 However, for films with thicknesses that correspond to a significant part of the evanescent field, eq 6 instead of eq 7 must be used. Furthermore, in aqueous solution, where the adsorbed film consists of a mixture of buffer and adsorbed molecules, a significant error in the mass uptake estimation can be introduced by using a simple linear relation like eqs 6 and 7.32 Instead, the more general two-component Lorenz-Lorentz formula

m∆n )

3d(n2 - nb2) (n2 + 2)(r(nb2 + 2) - v(nb2 - 1))

(8)

should be used, where r is the specific refractivity of the (bio)molecule, v is the partial specific volume, and the refractive index of the biofilm n can be calculated by eq 3 and n(bio)molecule ) nbuffer + ∆n.32 The specific refractivity, i.e., the ratio between molar refractivity and molecular weight, was calculated for lipids (r ) 0.003 30 mL/g) and streptavidin (r ) 0.248 81 mL/g) using the refractivity of their chemical bonds and amino acids. The partial specific volume is the inverse of density, and v ) 0.98 mL/g was used for the POPC lipids and v ) 0.719 mL/g for streptavidin.32 It is notable that, for macromolecular assemblies undergoing significant conformational changes, dc/dn is not necessarily constant throughout the reaction with respect to the p-polarized electric field used to excite SPR. To a first approximation, the film thickness can then be a useful parameter in order to estimate the conformational state of an adsorbed (bio)macromolecular complex. The order and orientation of adsorbed molecules can (27) Lide, D. R., Ed. CRC Handbook of Chemistry and Physics, 84th ed.; CRC Press: Boca Raton, FL, 2004. (28) de Feijter, J. A.; Benjamins, J.; Veer, F. A. Biopolymers 1978, 17, 17591772. (29) dc/dn for streptavidin was 5.556 g/cm3,30 while dc/dn values for lipids in an SPB could be calculated from known values for density and refractive index in ref 31. (30) Stenberg, E.; Persson, B.; Roos, H.; Urbaniczky, C. J. Colloid Interface Sci. 1991, 143, 513-526. (31) Salamon, Z.; Tollin, G. Biophys. J. 2001, 80, 1557-1567. (32) Cuypers, P. A.; Corsel, J. W.; Janssen, M. P.; Kop, J. M. M.; Hermens, W. T.; Hemker, H. J. Biol. Chem. 1983, 258, 2426-2431.

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indeed have a large influence on nbiomolecule. According to Salamon and Tollin, the anisotropy of lipid membranes implies that the refractive index may vary as much as from 1.47 to 1.525 depending on molecular orientation.31 For our rather rough sensor surfaces (rms ∼2-3 nm) and deformed vesicles, the anisotropy effect is probably not that significant but should be taken into account on, for example, perfectly smooth surfaces and a larger difference in molecular ordering. Furthermore, the film thickness is a parameter in determining the measured refractive index of the adsorbed film, and the thickness, and thus implicitly the water content, of the adsorbed film also plays a role in determining the mass using eq 8. Herein, we reduce these uncertainties by making use of the information about thickness and conformation obtained from eq 1 and the D parameter, respectively, in QCM-D measurements. With a reliable estimate of the optical anisotropy of, for example, two different adsorbed states, this could also have been taken into account using the same information. With respect to the saturated response, we have previously proposed the use of combined QCM-D and SPR measurements for an improved estimate of the effective thickness according to eq 1:13

deffective ) mVoigt/Feffective

(9)

where

Feffective ) mVoigt m∆n/F(bio)macromolecule + (mVoigt - m∆n)/Fwater

(10)

where (i) mVoigt is obtained from eq 1 (being independent of Feffective in the density range 1-2 g/cm3) and (ii) m∆n is obtained from eqs 3 and 8 and thus depends on the film thickness. Therefore, an iterative process was employed, in which mVoigt and the deffective were first determined for a reasonable value of Feffective at full surface coverage. m∆n was then estimated using deffective as d in eqs 3 and 8. The obtained m∆n was then used to calculate a new value for Feffective using eq 10 and the process reiterated to reach convergence in Feffective, deffective, m∆n and mVoigt (eqs 3 and 8-10) at all times. The values were typically converging after only a few iterations. MATERIALS AND METHODS Lipids, Buffers, and Other Chemicals. 1-Palmitoyl-2-oleoylsn-glycero-3-phospocholine lipids (POPC; lyophilized, Avanti Polar Lipids), biotin-PE (Avanti Polar Lipids), and streptavidin (SigmaAldrich) were stored at -20 °C. The biotin-PE was stored in chloroform and the POPC under nitrogen atmosphere. Tris(hydroxymethyl)aminomethane (Tris) and sodium chloride for making buffers were purchased from Sigma-Aldrich. All buffers were made from Milli-Q water, 10 mM Tris, and 100 mM NaCl. The pH was set to pH 8.0 with hydrogen chloride (VWR International). Other chemicals used in the experiments were chloroform (VWR International), ethanol (95.5%, Kemetyl), acetone (VWR International), sodium dodecyl sulfate (SDS) (Aldrich), and nitrogen gas (N48, Air Liquide). All water used in the experiments 7214 Analytical Chemistry, Vol. 76, No. 24, December 15, 2004

Figure 1. Schematic illustration of the layout of the measurement configuration. The sensing surfaces are deployed in a parallel, symmetrical configuration, with a rapid ( 12 s1/2) slopes correspond to the same amount of adsorbed vesicles. (a) displays ∆D and ∆Θ versus t1/2. Since the responses in ∆D and ∆Θ up to the critical coverage are due to vesicles only, a calibration curve for ∆Θ versus ∆D can be created, which is valid for the changes in ∆D on both the positive and negative slope. This calibration curve is shown in (b). (Note that the exact point for the critical coverage, i.e., the state when vesicles start to rupture, is not known. This means, in turn, that this calibration is somewhat uncertain close to the maximum in ∆D.) In (c), the part of ∆Θ originating from vesicles, ∆Θvesicle, for the entire adsorption process is calculated using (a) and (b). In (d), the contribution originating from SPB islands only, ∆ΘSPB, is shown by subtracting ∆Θvesicle from the total change in ∆Θtotal. (e) displays the changes in vesicle, mvesicle, and SPB, mSPB, lipid mass versus t1/2, respectively, obtained as described in the Theory and Data Analysis section. (f) Comparison of the final result for the total mass, mtotal ) mvesicle + mSPB, together with the expected result for mass transport limited adsorption for ∼60-nm vesicles (solid line).

of the bulk concentration42 or a transition to reaction-limited adsorption as the coverage increases, at an earlier stage, is not an explanation for the latter observation, since both would yield a reduction in the mass uptake rate. The elimination of this feature through the data analysis described above suggests that this feature should be attributed to a failure of the assumptions, in particular the ones of constant thickness and dc/dn values, used (42) Depletion was always controlled to be well below 5% of the original concentration.

to estimate m∆n via eq 7. When the data are corrected accordingly, there is an excellent agreement between the observed uptake and the calculated expected uptake up to 90% coverage (cf. Figure 3f). It is clear that we, in this particular case, have been treating a situation where the commonly used means of estimating mass uptake from SPR results is in error by as much as 25% for the final uptake (SPB) and as much as 60% when vesicles are present on the surface. The latter has the effect of producing a mass curve Analytical Chemistry, Vol. 76, No. 24, December 15, 2004

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Figure 4. Mass measured by QCM (mVoigt) and SPR (m∆n) vs t1/2 for (a) vesicle to bilayer formation and (b) streptavidin binding and 2D crystallization on top of a biotinylated lipid bilayer. The initial part of the streptavidin adsorption is obscured due to a pressure/temperature peak in the QCM-D data upon addition of the protein and is not shown in the figure. Shown is also the difference between the two measured masses, attributed to trapped water (mwater). As for the lipid vesicle case, m∆n and mQCM were determined using the iterative process described in the Theory and Data Analysis section. Also shown in both plots is the expected adsorption rate for mass transport limited adsorption (mdiff.lim.) using (C0 ) 125 µg/mL, D ≈ 3.5 × 10-8 cm2/s) and (C0 ) 3.33 µg/mL, D ≈ 5.9 × 10-7 cm2/s) for 60-nm vesicles and streptavidin, respectively.

that even qualitatively displays misleading kinetics. With the information contained in combined f and D QCM-D measurements it was, in the present case, possible to correct for the major errors, but not until a proper optical model was used that could take the additional information of the QCM-D into account to calculate the mass of a film with high buffer content. Calculating the refractive index change of the films using the simplified Jung model (eq 3) instead of using the multilayer Fresnel equations, which also take into account, for example, interference effects, yields an error of 5-12% for the SPB (decreasing with increasing coverage) and 10% for the vesicle film (see Supporting Information). Thus, for this system, the largest error would be due to neglecting to take into account the difference in thickness and optical density between vesicles and SPB in the optical model. Estimation of the Temporal Variation in Coupled Water. By combining the above determined temporal variation in the total lipid mass, with the information about total mass (including dynamically coupled water) obtained from the QCM-D data, it becomes possible to estimate the amount of coupled water, not only at saturated coverage but also during an entire adsorption/ transformation process. In this analysis, we also investigate the variation in coupled water for a second model system with lower water content: streptavidin (65 kDa) binding to a small fraction of biotin-modified lipids incorporated in the SPB. Through these experiments and analysis we arrive at the result that there is, for both the lipid films and proteins, a significantly higher amount of coupled water at low compared to high coverage. The latter finding is very important, since it has general implications for the evaluation of QCM results in order to extract correct kinetics data. Panels a and b of Figure 4 display mVoigt, m∆n, and mwater ()mVoigt - m∆n) versus t1/2 for the lipid bilayer formation process 7218

Analytical Chemistry, Vol. 76, No. 24, December 15, 2004

and streptavidin binding, respectively. Figure 5 displays the temporal variation in the coupled water mass per adsorbed biomolecule mass

φ)

mwater mVoigt ) -1 m∆n m∆n

(11)

Also shown in Figure 5 is the temporal variation in effective shear viscosity, η, obtained via the Voigt-based modeling of the QCM-D data (not shown) for the two systems. From an inspection of the vesicle-to-bilayer transformation (Figures 4a and 5a), it is clear that the absolute amount of coupled water, as expected, changes most dramatically during the rupture process (Figure 4a). Using a molecular mass of 768 g/mol for the lipids,43 the lipid mass of the SPB (∼400 ng/cm2) corresponds to an area per lipid of 64 Å2, which is in good agreement with most of the literature on vesicles and planar membranes.31,44 By further comparing this value to mwater for the SPB (60 ng/cm2), we find that ∼13 water molecules are associated with each lipid molecule. This is in the range of values on the hydration of the lipid headgroups previously reported, i.e., 11-16 water molecules per phosphocholine lipid (12 water molecules/lipid in a recent study45).46 The agreement with the hydration shell is a bit unexpected since it is believed that there is a water layer ∼1 nm thick between the SPB and the surface, which would almost double the expected number of water molecules per lipid. (43) www.avantilipids.com, 2004. (44) Hauser, H.; Pascher, I.; Pearson, R. H.; Sundell, S. Biochim. Biophys. Acta 1981, 650, 21-51. (45) Binder, H.; Kohlstrunk, B.; Heerklotz, H. H. Chem. Phys. Lett. 1999, 304, 329-335.

Figure 5. Coupled water mass per adsorbed biomolecule mass, φ, and shear viscosity versus t1/2 for (a) the vesicle to SPB formation process and (b) streptavidin binding on top of a biotin-modified lipid bilayer.

However, the water in this layer might at least partly be taken into account in the QCM-D baseline, since the SPB is known to smoothen rough surfaces and the roughness of the current substrate has an rms of ∼2 nm. Thus, the water in these cavities will not contribute to the difference between mVoigt and m∆n. The close to zero ∆D value is also an indication that the amount of extra, loosely entrapped water for the SPB should be low and close to the hydration shell. These estimations apply, however, only for the final SPB formed at saturation. This is obvious from the fact that the amount of coupled water per lipid mass is significantly higher at low coverage, where φ is ∼4, compared to saturated coverage, where φ has decreased to ∼0.15 (Figure 5a). Taking into account that the QCM measures all mass that is (dynamically) coupled to the shear oscillation of the sensor crystal, it is interesting to note the maximum amount of water that can be entrapped within a ∼60nm spherical vesicle corresponds to φ ∼1.7. In reality, the deformation of the adsorbed vesicles makes φ with respect to water trapped only in the interior closer to 1. Since this value is significantly lower than that observed at low coverage, water in between adsorbed vesicles must also be dynamically coupled to the shear oscillation of the sensor crystal. As the vesicle coverage increases, part of this water is then being replaced by lipid mass, thus leading to the observed gradual reduction in the total amount of coupled water (Figure 5a). At the critical coverage, the amount of water trapped within and between vesicles, respectively, are comparable, and both are strongly reduced during the rupture process, eventually only consisting of the hydration shells of the lipid headgroups and water trapped between the bilayer and the solid support (see above). It should be pointed out that the reduction in coupled water per lipid mass as the critical coverage is approached may also have a contribution from a slow structural change of the vesicles. However, if some kind of structural change were the dominating origin of the reduction in φ, a similar change would be expected in the shear viscosity. From Figure 5a it is clear that the initial variation in the shear viscosity is minor and varies linearly with t1/2 until the stage is reached at which the rupture process starts. There is also a drastic increase in shear viscosity by almost 1 order of magnitude at this stage, as one might expect. Thus, we (46) Gennis, R. B. Biomembranes: Molecular structure and function; SpringerVerlag: New York, 1989.

conclude that the initial reduction in φ (water content) is caused by adsorbed vesicles replacing trapped water and not by structural changes. We now turn to the second model system, streptavidin binding on top of a biotinylated SPB. The data for streptavidin binding to a biotin-lipid containing SPB are shown in Figures 4b and 5b. In this case, we are dealing with a protein whose structure is not expected to undergo extensive structural changes during binding, yet the variation in the amount of coupled water per protein molecule varies from ∼7.5 at low coverage to ∼1.3 at high coverage. The streptavidin coverage at the end of the measurement is somewhat above 30%, which means that ∼60% of the water between the proteins is trapped in the acoustic oscillations. Although the initial high water content increases the detection sensitivity of the QCM, the somewhat surprisingly large variation versus protein coverage is a critical observation, with a number of important implications: First, we note that the SPR data obtained for streptavidin is also in this case in perfect agreement with mass transport limited adsorption (C0 ) 3.33 µg/mL, D ) 5.9 × 10-7 cm/s2), which strongly supports that eqs 3 and 8 for translating ∆Θ into protein mass are adequate. In strong contrast, the QCM mass uptake data do not follow this dependence, which puts strong doubts on the numerous studies in which the QCM technique has been used alone for estimations of adsorption/ binding kinetics or, for that matter, when measured changes in f have been used to evaluate differences in the adsorbed amount of biomolecules, without taking the water content into account. This ambiguity arises because a film composed of few molecules entrapping a large amount of water may give a QCM response very similar to that of a dense film entrapping a small amount of water. Adding D measurements to the classical f measurements, and at several overtones, changes this situation and makes the QCM-D technique a very valuable tool for evaluating binding kinetics. This is obvious not only from the analysis of the vesicleto-bilayer formation process performed above but also from the temporal variation in the shear viscosity obtained for the streptavidin adsorption. Interestingly, the shear viscosity increases in this case, with the same rate as the mass uptake obtained from SPR. This unusual behavior opens up for a possible generalization; it points to the possibility that the variation in viscosity with the variation in water content might be used as a signal of 2D crystallization. Analytical Chemistry, Vol. 76, No. 24, December 15, 2004

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Second, we note that appropriate theoretical modeling of the data20 is required to quantify the structural information contained in QCM-D data. As described in the Theory and Data Analysis section, a large variation in the amount of coupled water will have a significant influence on the effective density. Since this parameter must be used as a “known” input in the existing models, significant variations in the water content may lead to misinterpretations of the output from the modeling. In the present work, this was taken into account by iterating eqs 3 and 8-10, as described in the Theory and Data Analysis section. It turned out from this treatment of the data that a time-resolved measure of the density had, for these systems, only a negligible effect on the shear viscosity and shear modulus (not shown). However, the effective thickness varied as the inverse of the density (∝ mVoigt/Feffective). Since the analyzed systems varied quite significantly in water content, we conclude that “a constant density assumption” in a narrow density range (1-2 g/cm3) is a sufficiently good approximation in order to analyze the kinetics of the variation in the viscoelastic components but that the thickness estimation gains significantly from an independent estimation of the amount of dynamically coupled water. This should not be taken as a general rule, however, and should be carefully evaluated for each investigated system, especially if the induced change in D is high and if the film cannot be treated as acoustically thin. From the present, as well as previous studies,13 we note that the shear viscosity obtained from a Voigt-Kelvin-based treatment of the QCM-D data qualitatively follows the ratio between ∆D and ∆f and that a higher water content generally results in a lower viscosity (higher ∆D/∆f values), which for strongly hydrated films, such as DNA, approaches that of water (∼1 × 10-3 kg/ms).13 This overall trend is observed also in the present data, signaling a higher viscosity as the coverage increasessand as the amount of coupled water decreases. Thus, water is indeed likely to be an important dissipative channel. The two most likely mechanisms are (i) exchange of molecules with higher kinetic energy from within the adsorbed film, with molecules of lower kinetic energy in the bulk, and (ii) transformation of the kinetic energy to internal degrees of freedom (rotation), which is eventually being transmitted to water molecules in the bulk. It is clear, however, that the total amount of coupled water does not scale linearly with the shear viscosity or D, indicating that internal dissipative mechanisms within the adsorbed (bio)macromolecules also contribute to the viscous losses. Furthermore, it is theoretically and experimentally established that roughness on the same length and height scale as adsorbed vesicles yields a significant contribution to the dissipation (and viscosity) through nonlaminar motion (in the plane perpendicular to the surface) of dynamically coupled water.47,48 This points toward the need for further refined theoretical and analytical concepts, treating the heterogeneity of adsorbed films. (47) Daikhin, L.; Gileadi, E.; Katz, G.; Tsionsky, V.; Urbakh, M.; Zagidulin, D. Anal. Chem. 2002, 74, 554-561. (48) Bund, A.; Schneider, M. J. Electrochem. Soc. 2002, 149, E331-E339. (49) Wojciechowski, P. W. In Interfacial phenomena and bioproducts; Brash, J. L., Wojciechowski, P. W., Eds.: New York, 1996; p 209.

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SUMMARY AND CONCLUDING REMARKS We have presented how the mass adsorption kinetics for systems undergoing complicated conformational changes can be resolved by combining SPR and QCM-D measurements. The three independent, measured quantities, variations in the SPR angle, frequency shift of the QCM and the damping (dissipation factor) of QCM-D, provide complementary information. Omitting either of them weakens the analysis and interpretation of the studied kinetics. Specifically, this approach allowed the kinetics of planar bilayer formation on SiO2 to be separated into the two parallel processes; vesicle adsorption and SPB formation from the adsorbed vesicles. It was in this context shown that the commonly used conversion between a change in SPR angle and mass (eq 5) must be used with care in situations when (i) the thickness of film is on the order of the decay length of the sensing regime of the SPR technique or (ii) when structural transformations cause changes in (bio)macromolecular ordering and biofilm water content. It was also shown that the water mass sensed by the QCM originates not only from water entrapped within supramolecular assemblies, such as lipid vesicles, or from the water shells surrounding adsorbed molecules but also from water dynamically entrapped in between adsorbed biomacromolecules. The latter observation suggests revision of interpretations of earlier QCM data to resolve binding kinetics data. Yet another result of this work is that the obtained information about the variation in water content, i.e., the difference between mVoigt (mQCM) and m∆n, allows determination of the temporal variation in the effective density of the absorbed biofilms. The effective density was estimated via an iteration of the equations used to interpret both the QCM-D and the SPR data. In particular, it was shown that the density is not a crucial factor in determining the viscosity (and the shear modulus), while the effective thickness varies as the inverse of the density. Finally, a correlation is demonstrated between the water content in the biofilm and its shear viscosity. For binding of streptavidin to a biotin-lipid containing SPB, it was shown that the viscosity versus water content possibly contains information of protein aggregation, and a more detailed study of the origin of the viscosity (and dissipation) of water rich films is warranted. ACKNOWLEDGMENT The Swedish Research Council (Grants 621-2001-2649 and 2003-3959) is acknowledged for its financial support of this project. Part of the combined QCM-D and SPR equipment was funded by the Vinnova+SSF (Grant 16254080) within the VINST program. SUPPORTING INFORMATION AVAILABLE Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org.

Received for review May 13, 2004. Accepted September 9, 2004. AC0492970