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Measuring antibody affinity and performing immunoassay at the single molecule level
ANALYTICAL BIOCHEMISTRY Analytical Biochemistry 307 (2002) 84–91 www.academicpress.com
Measuring antibody affinity and performing immunoassay at the single molecule level Sergey Y. Tetin,a,* Kerry M. Swift,b and Edmund D. Matayoshib b
a Drug Monitoring, Abbott Diagnostics Division, 100 Abbott Park Road, Abbott Park, IL 60064-6016, USA Department of Structural Biology, Global Pharmaceutical Research and Development, Abbott Laboratories, 100 Abbott Park Road, Abbott Park, IL 60064-6114, USA
Received 27 November 2001
Abstract Fluorescence correlation spectroscopy (FCS) enables direct observation of the translational diffusion of single fluorescent molecules in solution. When fluorescent hapten binds to antibody, analysis of FCS data yields the fractional amounts of free and bound hapten, allowing determination of the equilibrium binding constant. Equilibrium dissociation constants of anti-digoxin antibodies and corresponding fluorescein-labeled digoxigenin obtained by FCS and fluorescence polarization measurements are identical. It is also possible to follow a competitive displacement of the tracer from the antibody by unlabeled hapten using FCS in an immunoassay format. The fluorescence polarization immunoassay for vancomycin detection was used to test the FCS approach. Fitting of the FCS data for the molar fractions of free and bound fluorescein-labeled vancomycin yielded a calibration curve which could serve for determination of the vancomycin concentration in biological samples. Ó 2002 Elsevier Science (USA). All rights reserved. Keywords: Fluorescence correlation spectroscopy; Antibody affinity; Immunoassay
Fluorescence correlation spectroscopy (FCS)1 is a method to observe diffusion at the single molecule level. Diffusion times and the corresponding diffusion coefficients of fluorescent molecules can be determined in the solution phase enabling FCS applications in biophysical studies of intermolecular interactions [1]. Elson, Magde, and Webb created the groundwork for FCS more then 20 years ago [2–4], but development of the method progressed only gradually until the 1990s due to technical hurdles. The work of Eigen, Rigler, and co-workers [5–7] led to the development of the first commercial FCS instrument in 1995 by Carl Zeiss Jena GmbH (Jena, Germany) in collaboration with Evotec BioSys-
*
Corresponding author. Fax: 847-935-6498. E-mail address: [email protected] (S.Y. Tetin). 1 Abbreviations used: FCS, fluorescence correlation spectroscopy; ACF, autocorrelation function; PCH, photon-counting histogram; FIDA, fluorescence intensity distribution analysis; FPIA, fluorescence polarization immunoassays; FP, fluorescence polarization; MEA, mercaptoethylamine; mP, TDx analyzer millipolarization units.
tems AG (Hamburg, Germany). Since then, FCS has been applied to a variety of biological systems [1]. Briefly, FCS is based on the detection of concentration fluctuations occurring at equilibrium within small sampling volumes. Spikes of fluorescence intensity corresponding to single molecules undergoing Brownian translational diffusion can be resolved in sufficiently diluted solutions [8–10]. Concentrations of the fluorescent component should be in the nanomolar range for subfemtoliter observation volumes. Such volumes can be readily achieved in a microscope using one-photon excitation and pinhole optics [11–16], or alternatively by multiphoton excitation techniques [17–19]. An autocorrelation analysis of the temporal intensity fluctuations identifies diffusion rates and the average number of fluorescent molecules in the observation volume. Meseth et al. [20] have demonstrated that resolution of two fluorescent species in the intensity autocorrelation function (ACF) analysis is possible if they exhibit at least twofold difference in their diffusion rates and the experimental conditions are thoroughly optimized. Using a different approach, photon-counting histogram
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(PCH) analysis or fluorescence intensity distribution analysis (FIDA), Chen et al. [21,22] and Kask et al. [23] were able to resolve two fluorescent species if their relative intensities differ by twofold. In general, ligand binding may result in either or both effects: the diffusion rate and the fluorescence intensity may be affected, dictating the method of the data analysis. In a recent study of the anti-digoxin mouse monoclonal antibody the binding constant was evaluated using PCH analysis [24]. This antibody quenches fluorescence of the fluorescein-labeled digoxin by 52% and probably represents an ideal system for the analysis of the FCS data on the basis of PCH or FIDA. For many other antibody–hapten pairs or for binding experiments in general, association of molecules may result in little or no change in fluorescence intensity. In such situations the ability of the ACF analysis to resolve free and bound components on the basis of their diffusion rates in a homogeneous format is clearly invaluable. Indeed, binding of relatively small fluorescent haptens by antibodies leads to a tremendous decrease in the hapten diffusion rate. Also, binding affinities of many antibodies typically fall in the 109 –107 M range, permitting easy optimization of the FCS-based binding experiment. Thus, the FCS method appears to be an attractive choice for characterizing antibody–hapten interactions. The FCS approach to study binding interaction can be enhanced by various experimental modifications. One of these strategies includes the use of nanoparticles to amplify the difference in antibody and hapten diffusion rates [25]. It is also feasible to combine total internal reflection and FCS for detection of antibody binding to immobilized ligand [26,40]. However, the latter experimental approach requires a planar surface where antibody interacts with the ligand. In this way, it is similar to techniques based on the surface plasmon resonance [27]. Depending on the molecular size of each species in the sample solution and their affinities, and measurement requirements such as acquisition speed, sample throughput, and precision, each approach has its respective advantages. There is an experimental advantage to the study of interaction between freely diffusing antibody and hapten in solution at equilibrium, unmodified except for the presence of the covalently linked fluorescent label. Since the molecular weights of antibody and probe-derivatized hapten in our systems differ by 150-fold, the translational diffusion times corresponding to bound and free species in the mixture are easily resolved without tethering either component to a surface or large particle. Indeed, the elimination of surfaces has the benefit of avoiding potential interfering effects due to nonspecific surface-binding phenomena. The latter plays a significant role at low concentrations of antibody or hapten, where high-binding affinity necessitates large dilutions of the reagents. Other advantages of using the freely diffusing bivalent antibody include its precisely defined
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binding stoichiometry and the unperturbed access of the hapten to each binding site. It is also important to underline that concentrations of fluorescent molecules are directly measured in FCS experiments. Digoxin is one of many therapeutically or diagnostically important analytes measured in blood and urine samples by commercial homogeneous fluorescence polarization immunoassays (FPIA). In this paper we compare the performance capabilities of FCS with fluorescence polarization (FP) techniques in the determination of the equilibrium dissociation constant of fluorescein-labeled digoxigenin and anti-digoxin antibody. A general comparison of FP with FCS for studying protein– ligand interactions can be found elsewhere [28]. In the current study, FP results serve as a reference and are performed by traditional macroscopic (cuvette) measurements with a spectrofluorometer. In addition to direct binding experiments, we also compare the performance of FCS and FPIA by measuring the competitive displacement of fluorescein-labeled vancomycin from anti-vancomycin antibody with the unlabeled drug using commercial Vancomycin II TDx =TDx FLx immunoassay reagents (Abbott Laboratories, Abbott Park, IL).
Materials and methods Antibodies and tracers. Anti-digoxin antibody was purified from rabbit hyper immune serum on a rProtein A–Sepharose 4 Fast Flow column (AmershamPharmaciaBiothech, Piscataway, NJ) using standard procedures. The IgG fraction was eluted with 0.1 M citrate buffer, pH 3.0, immediately neutralized, and dialyzed against 0.1 M phosphate buffer, pH 8.0. Purity of the protein was confirmed by SDS-gel electrophoresis in SepraGel precast 12.5% polyacrylamide gel (Owl Separation Systems, Portsmouth, NH). Fluorescein-labeled digoxigenin synthesized at Abbott Laboratories (a component of Digoxin II TDx =TDx FLx fluorescence polarization immunoassay kit) was greater than 97% pure by HPLC analysis. A commercial Abbott Laboratories kit for Vancomycin TDx =TDx FLx assay was used for comparative studies of the immunoassay performed by FCS and fluorescence polarization methods. Fluorescence correlation spectroscopy. FCS measurements were performed on a first generation Zeiss/Evotec ConfoCor (Carl Zeiss Jena GmbH, and Evotec BioSystems AG). This instrument is based on a Carl Zeiss Axiovert microscope chassis and relies on a pinhole to eliminate out-of-focus emission at the detector and to define a subfemtoliter detection volume. A 10-mW aircooled argon ion laser (488/514 nm) is used for excitation, and emission is acquired with a single photon-counting APD and single channel hardware correlator (ALV, Langen, Germany). We used the standard Zeiss fluores-
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cein filter set and a 40 N.A.1.4 water immersion microscope objective lens (Carl Zeiss C-Apochromat). Data acquisition times typically were 30–60 s, with three or more replicates routinely taken to check reproducibility. Sample droplets (10–30 lL) were placed on the glass bottom of a single well of a Nunc 8-chamber coverslip. Fluorescein derivatives exhibit high quantum efficiency, are relatively inexpensive, and, therefore, are widely utilized in FPIA. However, fluorescein probes (tracers) are susceptible to photobleaching even at moderate excitation power levels and must be used in FCS experiments with precautions. The photobleaching of fluorescein results in a monotonic loss of average emission intensity with irradiation time or, in other words, in a reduction of photon counts per molecule upon observation. It appears in the fluorescence autocorrelation function as a fast decay component at times shorter than 5 ls due to the kinetics of the triplet state. In the work presented here, the diffusion times of small tracers are typically significantly longer, in the range of 60 ls under the conditions defined by the geometry of the microscope. However, when high yields of the triplet state are generated, the correlation times revealed by the ACF analysis will no longer reflect only the molecular diffusion time, but will be substantially shortened regardless of whether the fast triplet component is resolved. Reduction of the diffusion time is more noticeable for slower diffusing antibody–hapten complexes, where loss of fluorescence due to intersystem crossing to the triplet state is increased. For these reasons, we routinely attenuated the input excitation power with neutral density filters until the triplet fraction is reduced below 20%, or as low as practical. In addition, we always require that power levels should satisfy linearity of the emission intensity as a function of excitation power and accepted results only if the observed diffusion times do not change at several power levels used in the experiment. Typically, in our experiments the laser power at 488 nm (Coherent LM-2 silicon diode power meter) measured after the objective was significantly below 10 lW. We considerably improved FCS performance by the addition of 10–25 mM mercaptoethylamine (MEA), which acts as a selective triplet-state quencher. In the presence of MEA, photon counts per fluorescein molecule are greatly increased due to a minimized fraction of molecules in the triplet state and decreased photo bleaching [29]. It becomes possible to conduct FCS experiments at higher excitation power levels and the results of these measurements are indistinguishable from the data obtained in the absence of MEA at decreased laser power. We also established that antibody–antigen affinities are not altered by the presence of 10–25 mM MEA during the data-collection time. FCS autocorrelation data were fit for fractions of the bound and free tracer with the Evotec Biosystems AG software FCS Access v.1.0.12. This fit is based on
fT GðtÞ ¼ 1 þ et=ss N ð1 fT Þ 2 3 3 X fi 6 7 4 1=2 5; i¼1 1 þ sti 1 þ S 2tsi
ð1Þ
where N is the number of fluorescent particles (molecules); fi the fraction of ith diffusion component; fT the triplet fraction; S the axis ratio of the confocal element (structure parameter); si the ith correlation time; sT the triplet decay time; and t the time. A single diffusion component model (after correction for the triplet state component) sufficiently fits the limiting cases of the titration when no antibody is present or at saturating antibody, as judged by inspection of the residuals. It was also verified that the diffusion times of the free and bound tracer are consistently maintained throughout the titration range. Then, the evaluation of the FCS data across a titration curve was performed by linking all ACF analyses, i.e., using the diffusion times for the completely free and bound tracer as fixed parameters. Binding data analysis. Binding data were analyzed with the simple binding model based on a stoichiometry of one hapten (tracer) molecule per each antibodybinding site, Fb ¼
m ½ABS free þc Kd þ ½ABS free
ð2Þ
where Fb is fraction of the tracer bound, m and c are the scaling factors, ½ABS free the concentration of free antibody-binding sites, and Kd the dissociation constant. Binding sites in the bivalent antibody molecule behave independently [30]. Binding data analysis and curve fitting were performed with the program DeltaGraph (SPSS, Chicago, IL). Other methods. Steady-state fluorescence measurements were performed on an SLM 8100 photon-counting spectrofluorometer equipped with prism polarizers. IgG concentration was determined by absorption at 1 mg=mL 278 nm (A278 ¼ 1:4) on a Cary 4 spectrophotometer (Varian, Sugarland, TX), with corrections included for scattered light.
Results Initially, binding of digoxin tracer to anti-digoxin antibody was measured at equilibrium by changes in fluorescence anisotropy. The hapten concentration was kept at 1.2 nM, while the antibody concentration incrementally increased from picomoles to micromoles in the series of 18 samples shown as the titration points in Fig. 1. The fluorescence intensity of the tracer did not change upon binding, hence no corrections were
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Fig. 1. Binding of digoxin tracer with anti-digoxin antibody measured by fluorescence polarization. Points correspond to tracer fraction bound as a function of free antibody-binding sites (Eqs. [3] and [4]). Solid line is the fit to the data according to Eq. [2]. Concentration of the tracer is 1:2 nM. Excitation at 470 nm. Slits in the excitation channel are 4-nm bandwidth. Emission light is collected through a 530-nm (25nm bandwidth) optical filter (Schott Glass Technologies, Duryea, PA).
necessary when calculating the fraction of bound tracer from the anisotropy data, r rfree Fb ¼ ; ð3Þ rbound rfree
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Fig. 2. Binding of digoxin tracer with anti-digoxin antibody measured by FCS. Autocorrelation data points and fits for samples (from bottom to top) with free tracer (no antibody), partially bound tracer, and fully bound tracer (saturating antibody). Fits were performed with structure factor determined separately using a fluorescent dye standard, R6G. The diffusion time measured for R6G was 55 ls. Less than approximately 10 lW at 488 nm was applied at the sample in order to reduce contribution of triplet state.
where r is the anisotropy measured in the sample; rfree and rbound are anisotropy values of tracer in the absence of antibody and at saturation. The concentration of the free antibody-binding sites can be calculated from ½ABS free ¼ ½ABS total ½T total Fb ;
ð4Þ
where ½ABS total and ½T total are the antibody-binding sites and total concentrations of the tracer, respectively. The fluorescence anisotropy data shown in Fig. 1 fit well to the simple binding model with Kd ¼ 11 nM. All samples measured by FP were also analyzed in the FCS microscope. Fig. 2 shows three autocorrelation function plots corresponding to the samples without antibody, with 50% ligand bound, and in the presence of saturating antibody. A two-component analysis of the ACF at each point in the titration was performed by holding constant the diffusion times for free (sd ¼ 73 ls) and bound tracer (sd ¼ 330 ls) in the nonlinear leastsquares fit. These two parameters were measured directly in samples without antibody and with saturating antibody, respectively. The fit yielded fractions of the free (MW ¼ 732) and bound tracer (MW 151; 000) as a function of antibody-binding site concentration, and fitted well to the simple binding model with Kd ¼ 12 nM (Fig. 3). Thus, the results demonstrate good agreement between FCS- and fluorescence polarization-based measurements for quantitative determination of antibody affinity. We also evaluated the application of FCS to a competition format immunoassay. In this assay the analyte,
Fig. 3. Determination of the dissociation constant for anti-digoxin antibody from the FCS experiment (same samples as in Fig. 1). Points correspond to tracer fraction bound as a function of free antibodybinding sites (Eq. [1]). Solid line is the fit to the data according Eq. [2].
vancomycin, competitively displaces tracer, fluoresceinlabeled vancomycin, bound to the antibody. Vancomycin was assayed using the TDx analyzer, an FPIA-based instrument (Fig. 4). Concentration of the tracer in the assay is 2 nM. The FCS measurements (Figs. 5 and 6) were taken on the same samples and analyzed for free and bound tracer species as described above. The diffusion time of free vancomycin tracer (MW ¼ 1907) was measured as sd ¼ 268 ls and increased to sd ¼ 665 ls when bound to the antibody (MW 152,000). It is important to recognize that fluorescence intensity of the vancomycin tracer is notably weaker compared to the above-mentioned digoxin tracer. To obtain a sufficient
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Fig. 4. Calibration curve for the TDx n TDx FLx vancomycin immunoassay. Each point on the plot shows TDx response in mP units in the presence of a calibrator (analytically prepared vancomycin solution in normal human serum). Curve is generated by a 4-parameter logistic curve fit (4PLC) equation [39].
Fig. 5. Autocorrelation data for vancomycin competition series (same samples as in Fig. 4). Curves from top to bottom correspond to data and fits (Eq. [1]) for 0, 5, 10, 25, and 50 lg/mL of vancomycin. The curves for 50 and 100 lg/mL were identical. In these experiments 0.5% Pluronic F68 was added prior to FCS measurements to minimize nonspecific adsorptive losses on the coverslip at the low component concentrations. In addition, 10 mM mercaptoethylamine (MEA) was added as a triplet-state quencher to all samples.
signal in the experiment the pinhole was increased, leading to increased observation volume and the diffusion times. Also, 10 mM MEA was added as a tripletstate quencher to all samples. The latter dramatically improves quantum efficiency of the tracer, allowing increase of the excitation power to the level required for reliable FCS measurements. As a result, the diffusion times of vancomycin tracer observed under these experimental conditions are significantly longer than in the experiment with digoxin tracer for both the free and the antibody-bound forms. Traditionally, the TDx analyzer results are expressed in the millipolarization (mP) units proportional to the
Fig. 6. Vancomycin immunoassay calibrators (same samples as in Fig. 5) measured with FCS and expressed as a function of the long diffusion time component fraction and concentration of vancomycin. Data points (Table 1) are fitted in the same manner as in Fig. 4.
polarization values measured on a spectrofluorometer. The TDx response changes from 234 mP for the bound tracer to 119 mP when all of the tracer molecules were displaced from the antibody-binding sites by vancomycin. When identical samples were measured by FCS, we observed a strong decline of the fraction of the long diffusion time component from 100% to practically 0%, and therefore, an agreement between the two methods (Fig. 6). The ACF analysis of FCS data also provides information on the number of molecules (N) diffusing through the observation volume. In beginning of the competition experiment with the vancomycin antibody, the average number of fluorescent molecules was 1.2 (Table 1). This number increased monotonically through the titration up to 2.2, when all tracer molecules became essentially free. Such a trend is consistent with the bivalent nature of antibody which initially had two bound tracer molecules, followed by their release in the presence of competitor.
Discussion Nicoli and co-authors [31,32] were first to demonstrate application of FCS to immunoassays in a set of elegant experiments carried out before the advent of modern instrumentation. In this work, the slow diffusion and high fluorescence intensity of micron-sized microparticles coated with antibody were keys in resolving bound vs free fractions of hapten in the fluctuation analysis. Fluorescence fluctuations from nanoliter volumes were generated spatially by scanning the solution. As pointed out by the authors, a drawback to the format they employed was the aggregation of microparticles. In contrast, the antibody–hapten characteristics described in the present study are based on observations
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Table 1 Vancomycin TDx =TDx FLx assay performed on ConfoCor and TDx Vancomycin concentration (lg/mL)
FCS Fraction of long diffusion time component
Number of molecules
Polarization (mP)
FPIA Fraction of tracer bound
0 5 10 25 50 100
1.0 0.87 0.69 0.32 0.11 0
1.2 1.2 1.4 1.7 2.1 2.2
234 223 207 167 139 119
1.0 0.91 0.76 0.41 0.16 0
of binding equilibrium at the single molecule level: the average number of molecules in the observation volume in the experiments presented here was less than 3. A major advantage of modern FCS is the ability to study high-affinity binding reactions in a homogeneous solution without perturbing the equilibrium between free and bound molecules. Thus, FCS becomes one of few techniques which are truly thermodynamically sound. Neither antibody described here changes fluorescence intensity of the bound tracers. Hence, we used ACF analysis to resolve free and bound molecules in solution. As previously indicated, analytical separation of two components in the ACF analysis typically requires at least a twofold ratio in their respective diffusion coefficients, which corresponds to an eightfold ratio in molecular weights for an idealized compact hydrodynamic sphere [20]. For this reason most antibody–hapten systems, including the two described in the current study, are good candidates for the FCS-ACF approach, especially when differences in the fluorescence quantum yields between free and bound states are too small to utilize. Furthermore, with current FCS instrumentation, detection of single molecule events for bright fluorescent labels is optimal in the range of 0.1–100 nM, allowing the measurement of nanomolar affinities. Altogether, these characteristics make the application of FCS and ACF analysis to antibody–hapten-binding equilibria promising. The same experimental setup can be combined with other data-collecting modes and analyses based on changes in fluorescence intensity occurring upon binding. Moment analysis [33], high-order autocorrelation [34,35], and analysis of the single particle photon-count distribution [21,23] have all been successfully applied to extract the fractions of fluorescent species as defined by their molecular brightness. These methods require significant binding-induced changes in fluorescence intensity. For example, the affinity of a mouse monoclonal anti-digoxin antibody was determined by analysis of the photon-count distribution [24] since in this instance, hapten binding is accompanied by a twofold quenching.
Large binding-induced changes in fluorescence intensity occur in antibody–hapten systems typically by circumstance and not by design. On the other hand, it is possible to engineer such an intensity change by introducing a second proximal group that can quench via resonance energy transfer. However, caution is necessary in implementing chemical modifications of antibodies or haptens because new functional groups might introduce a significant perturbation to the relevant binding event and, therefore, might not be tolerable for purposes of the assay. Steady-state fluorescence polarization has long been established as a valuable method for homogeneous immunoassay [36]. FP and FCS share the same advantages with regard to the capability of measuring binding in the homogeneous format with good sensitivity at the nanomolar concentration range typically needed for assaying antibody–hapten reactions. A general comparison of the application of these two techniques to protein–ligand interactions was recently presented [28]. For immunoassay applications, a preference for either FP (steady state) or FCS will depend on the nature of the information sought, as well as experimental parameters and requirements which must be satisfied including measurement speed, numbers of samples, assay design restrictions, choice of fluorophores, and interfering background factors. FP has the advantages of far cheaper and simpler instrumentation, faster sample throughput (e.g., commercial highthroughput FP plate readers now are available), and generally greater precision and reproducibility. However, while FP and FCS are both susceptible to background interferences caused by autofluorescence, quenching, light scattering, and possible aggregation of the assay components, FCS has intrinsically higher information content since both bound and free molecules are directly detected as time-resolved species. In contrast, steady-state FP reveals only the net polarization of the populations, and it must be assumed that the free and bound polarization values (determined in separate measurements) are being maintained under real assay conditions. Hence, FCS has better potential in ligand-binding studies, especially for troubleshoot-
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ing, although both methods are complementary in this regard. Immunoassay probe design is easier with FCS because the choice of both fluorescence probe and chemical linker can be optimized for biological compatibility usually without adverse effects on assay performance. In contrast, probe optimization for FP presents much more of a compromise between biological and assay performance considerations [28]. This study sought to demonstrate the capabilities of FCS in the determination of an antibody–hapten equilibrium dissociation constant and use of FCS in an immunoassay format. It is clear that the single molecule approach of FCS is well suited for immunoassay studies whether one wishes to exploit differences in diffusion between an antibody and hapten as demonstrated in the present work, or binding-induced differences in fluorescence intensity [24]. Implementation of dual fluorophore labeling and cross-correlation FCS strategies [37,38] promises additional advantages by making assays more robust and resistant to background interferences, and allowing greater flexibility in assay design.
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Measuring antibody affinity and performing immunoassay at the single molecule level Sergey Y. Tetin,a,* Kerry M. Swift,b and Edmund D. Matayoshib b
a Drug Monitoring, Abbott Diagnostics Division, 100 Abbott Park Road, Abbott Park, IL 60064-6016, USA Department of Structural Biology, Global Pharmaceutical Research and Development, Abbott Laboratories, 100 Abbott Park Road, Abbott Park, IL 60064-6114, USA
Received 27 November 2001
Abstract Fluorescence correlation spectroscopy (FCS) enables direct observation of the translational diffusion of single fluorescent molecules in solution. When fluorescent hapten binds to antibody, analysis of FCS data yields the fractional amounts of free and bound hapten, allowing determination of the equilibrium binding constant. Equilibrium dissociation constants of anti-digoxin antibodies and corresponding fluorescein-labeled digoxigenin obtained by FCS and fluorescence polarization measurements are identical. It is also possible to follow a competitive displacement of the tracer from the antibody by unlabeled hapten using FCS in an immunoassay format. The fluorescence polarization immunoassay for vancomycin detection was used to test the FCS approach. Fitting of the FCS data for the molar fractions of free and bound fluorescein-labeled vancomycin yielded a calibration curve which could serve for determination of the vancomycin concentration in biological samples. Ó 2002 Elsevier Science (USA). All rights reserved. Keywords: Fluorescence correlation spectroscopy; Antibody affinity; Immunoassay
Fluorescence correlation spectroscopy (FCS)1 is a method to observe diffusion at the single molecule level. Diffusion times and the corresponding diffusion coefficients of fluorescent molecules can be determined in the solution phase enabling FCS applications in biophysical studies of intermolecular interactions [1]. Elson, Magde, and Webb created the groundwork for FCS more then 20 years ago [2–4], but development of the method progressed only gradually until the 1990s due to technical hurdles. The work of Eigen, Rigler, and co-workers [5–7] led to the development of the first commercial FCS instrument in 1995 by Carl Zeiss Jena GmbH (Jena, Germany) in collaboration with Evotec BioSys-
*
Corresponding author. Fax: 847-935-6498. E-mail address: [email protected] (S.Y. Tetin). 1 Abbreviations used: FCS, fluorescence correlation spectroscopy; ACF, autocorrelation function; PCH, photon-counting histogram; FIDA, fluorescence intensity distribution analysis; FPIA, fluorescence polarization immunoassays; FP, fluorescence polarization; MEA, mercaptoethylamine; mP, TDx analyzer millipolarization units.
tems AG (Hamburg, Germany). Since then, FCS has been applied to a variety of biological systems [1]. Briefly, FCS is based on the detection of concentration fluctuations occurring at equilibrium within small sampling volumes. Spikes of fluorescence intensity corresponding to single molecules undergoing Brownian translational diffusion can be resolved in sufficiently diluted solutions [8–10]. Concentrations of the fluorescent component should be in the nanomolar range for subfemtoliter observation volumes. Such volumes can be readily achieved in a microscope using one-photon excitation and pinhole optics [11–16], or alternatively by multiphoton excitation techniques [17–19]. An autocorrelation analysis of the temporal intensity fluctuations identifies diffusion rates and the average number of fluorescent molecules in the observation volume. Meseth et al. [20] have demonstrated that resolution of two fluorescent species in the intensity autocorrelation function (ACF) analysis is possible if they exhibit at least twofold difference in their diffusion rates and the experimental conditions are thoroughly optimized. Using a different approach, photon-counting histogram
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(PCH) analysis or fluorescence intensity distribution analysis (FIDA), Chen et al. [21,22] and Kask et al. [23] were able to resolve two fluorescent species if their relative intensities differ by twofold. In general, ligand binding may result in either or both effects: the diffusion rate and the fluorescence intensity may be affected, dictating the method of the data analysis. In a recent study of the anti-digoxin mouse monoclonal antibody the binding constant was evaluated using PCH analysis [24]. This antibody quenches fluorescence of the fluorescein-labeled digoxin by 52% and probably represents an ideal system for the analysis of the FCS data on the basis of PCH or FIDA. For many other antibody–hapten pairs or for binding experiments in general, association of molecules may result in little or no change in fluorescence intensity. In such situations the ability of the ACF analysis to resolve free and bound components on the basis of their diffusion rates in a homogeneous format is clearly invaluable. Indeed, binding of relatively small fluorescent haptens by antibodies leads to a tremendous decrease in the hapten diffusion rate. Also, binding affinities of many antibodies typically fall in the 109 –107 M range, permitting easy optimization of the FCS-based binding experiment. Thus, the FCS method appears to be an attractive choice for characterizing antibody–hapten interactions. The FCS approach to study binding interaction can be enhanced by various experimental modifications. One of these strategies includes the use of nanoparticles to amplify the difference in antibody and hapten diffusion rates [25]. It is also feasible to combine total internal reflection and FCS for detection of antibody binding to immobilized ligand [26,40]. However, the latter experimental approach requires a planar surface where antibody interacts with the ligand. In this way, it is similar to techniques based on the surface plasmon resonance [27]. Depending on the molecular size of each species in the sample solution and their affinities, and measurement requirements such as acquisition speed, sample throughput, and precision, each approach has its respective advantages. There is an experimental advantage to the study of interaction between freely diffusing antibody and hapten in solution at equilibrium, unmodified except for the presence of the covalently linked fluorescent label. Since the molecular weights of antibody and probe-derivatized hapten in our systems differ by 150-fold, the translational diffusion times corresponding to bound and free species in the mixture are easily resolved without tethering either component to a surface or large particle. Indeed, the elimination of surfaces has the benefit of avoiding potential interfering effects due to nonspecific surface-binding phenomena. The latter plays a significant role at low concentrations of antibody or hapten, where high-binding affinity necessitates large dilutions of the reagents. Other advantages of using the freely diffusing bivalent antibody include its precisely defined
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binding stoichiometry and the unperturbed access of the hapten to each binding site. It is also important to underline that concentrations of fluorescent molecules are directly measured in FCS experiments. Digoxin is one of many therapeutically or diagnostically important analytes measured in blood and urine samples by commercial homogeneous fluorescence polarization immunoassays (FPIA). In this paper we compare the performance capabilities of FCS with fluorescence polarization (FP) techniques in the determination of the equilibrium dissociation constant of fluorescein-labeled digoxigenin and anti-digoxin antibody. A general comparison of FP with FCS for studying protein– ligand interactions can be found elsewhere [28]. In the current study, FP results serve as a reference and are performed by traditional macroscopic (cuvette) measurements with a spectrofluorometer. In addition to direct binding experiments, we also compare the performance of FCS and FPIA by measuring the competitive displacement of fluorescein-labeled vancomycin from anti-vancomycin antibody with the unlabeled drug using commercial Vancomycin II TDx =TDx FLx immunoassay reagents (Abbott Laboratories, Abbott Park, IL).
Materials and methods Antibodies and tracers. Anti-digoxin antibody was purified from rabbit hyper immune serum on a rProtein A–Sepharose 4 Fast Flow column (AmershamPharmaciaBiothech, Piscataway, NJ) using standard procedures. The IgG fraction was eluted with 0.1 M citrate buffer, pH 3.0, immediately neutralized, and dialyzed against 0.1 M phosphate buffer, pH 8.0. Purity of the protein was confirmed by SDS-gel electrophoresis in SepraGel precast 12.5% polyacrylamide gel (Owl Separation Systems, Portsmouth, NH). Fluorescein-labeled digoxigenin synthesized at Abbott Laboratories (a component of Digoxin II TDx =TDx FLx fluorescence polarization immunoassay kit) was greater than 97% pure by HPLC analysis. A commercial Abbott Laboratories kit for Vancomycin TDx =TDx FLx assay was used for comparative studies of the immunoassay performed by FCS and fluorescence polarization methods. Fluorescence correlation spectroscopy. FCS measurements were performed on a first generation Zeiss/Evotec ConfoCor (Carl Zeiss Jena GmbH, and Evotec BioSystems AG). This instrument is based on a Carl Zeiss Axiovert microscope chassis and relies on a pinhole to eliminate out-of-focus emission at the detector and to define a subfemtoliter detection volume. A 10-mW aircooled argon ion laser (488/514 nm) is used for excitation, and emission is acquired with a single photon-counting APD and single channel hardware correlator (ALV, Langen, Germany). We used the standard Zeiss fluores-
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cein filter set and a 40 N.A.1.4 water immersion microscope objective lens (Carl Zeiss C-Apochromat). Data acquisition times typically were 30–60 s, with three or more replicates routinely taken to check reproducibility. Sample droplets (10–30 lL) were placed on the glass bottom of a single well of a Nunc 8-chamber coverslip. Fluorescein derivatives exhibit high quantum efficiency, are relatively inexpensive, and, therefore, are widely utilized in FPIA. However, fluorescein probes (tracers) are susceptible to photobleaching even at moderate excitation power levels and must be used in FCS experiments with precautions. The photobleaching of fluorescein results in a monotonic loss of average emission intensity with irradiation time or, in other words, in a reduction of photon counts per molecule upon observation. It appears in the fluorescence autocorrelation function as a fast decay component at times shorter than 5 ls due to the kinetics of the triplet state. In the work presented here, the diffusion times of small tracers are typically significantly longer, in the range of 60 ls under the conditions defined by the geometry of the microscope. However, when high yields of the triplet state are generated, the correlation times revealed by the ACF analysis will no longer reflect only the molecular diffusion time, but will be substantially shortened regardless of whether the fast triplet component is resolved. Reduction of the diffusion time is more noticeable for slower diffusing antibody–hapten complexes, where loss of fluorescence due to intersystem crossing to the triplet state is increased. For these reasons, we routinely attenuated the input excitation power with neutral density filters until the triplet fraction is reduced below 20%, or as low as practical. In addition, we always require that power levels should satisfy linearity of the emission intensity as a function of excitation power and accepted results only if the observed diffusion times do not change at several power levels used in the experiment. Typically, in our experiments the laser power at 488 nm (Coherent LM-2 silicon diode power meter) measured after the objective was significantly below 10 lW. We considerably improved FCS performance by the addition of 10–25 mM mercaptoethylamine (MEA), which acts as a selective triplet-state quencher. In the presence of MEA, photon counts per fluorescein molecule are greatly increased due to a minimized fraction of molecules in the triplet state and decreased photo bleaching [29]. It becomes possible to conduct FCS experiments at higher excitation power levels and the results of these measurements are indistinguishable from the data obtained in the absence of MEA at decreased laser power. We also established that antibody–antigen affinities are not altered by the presence of 10–25 mM MEA during the data-collection time. FCS autocorrelation data were fit for fractions of the bound and free tracer with the Evotec Biosystems AG software FCS Access v.1.0.12. This fit is based on
fT GðtÞ ¼ 1 þ et=ss N ð1 fT Þ 2 3 3 X fi 6 7 4 1=2 5; i¼1 1 þ sti 1 þ S 2tsi
ð1Þ
where N is the number of fluorescent particles (molecules); fi the fraction of ith diffusion component; fT the triplet fraction; S the axis ratio of the confocal element (structure parameter); si the ith correlation time; sT the triplet decay time; and t the time. A single diffusion component model (after correction for the triplet state component) sufficiently fits the limiting cases of the titration when no antibody is present or at saturating antibody, as judged by inspection of the residuals. It was also verified that the diffusion times of the free and bound tracer are consistently maintained throughout the titration range. Then, the evaluation of the FCS data across a titration curve was performed by linking all ACF analyses, i.e., using the diffusion times for the completely free and bound tracer as fixed parameters. Binding data analysis. Binding data were analyzed with the simple binding model based on a stoichiometry of one hapten (tracer) molecule per each antibodybinding site, Fb ¼
m ½ABS free þc Kd þ ½ABS free
ð2Þ
where Fb is fraction of the tracer bound, m and c are the scaling factors, ½ABS free the concentration of free antibody-binding sites, and Kd the dissociation constant. Binding sites in the bivalent antibody molecule behave independently [30]. Binding data analysis and curve fitting were performed with the program DeltaGraph (SPSS, Chicago, IL). Other methods. Steady-state fluorescence measurements were performed on an SLM 8100 photon-counting spectrofluorometer equipped with prism polarizers. IgG concentration was determined by absorption at 1 mg=mL 278 nm (A278 ¼ 1:4) on a Cary 4 spectrophotometer (Varian, Sugarland, TX), with corrections included for scattered light.
Results Initially, binding of digoxin tracer to anti-digoxin antibody was measured at equilibrium by changes in fluorescence anisotropy. The hapten concentration was kept at 1.2 nM, while the antibody concentration incrementally increased from picomoles to micromoles in the series of 18 samples shown as the titration points in Fig. 1. The fluorescence intensity of the tracer did not change upon binding, hence no corrections were
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Fig. 1. Binding of digoxin tracer with anti-digoxin antibody measured by fluorescence polarization. Points correspond to tracer fraction bound as a function of free antibody-binding sites (Eqs. [3] and [4]). Solid line is the fit to the data according to Eq. [2]. Concentration of the tracer is 1:2 nM. Excitation at 470 nm. Slits in the excitation channel are 4-nm bandwidth. Emission light is collected through a 530-nm (25nm bandwidth) optical filter (Schott Glass Technologies, Duryea, PA).
necessary when calculating the fraction of bound tracer from the anisotropy data, r rfree Fb ¼ ; ð3Þ rbound rfree
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Fig. 2. Binding of digoxin tracer with anti-digoxin antibody measured by FCS. Autocorrelation data points and fits for samples (from bottom to top) with free tracer (no antibody), partially bound tracer, and fully bound tracer (saturating antibody). Fits were performed with structure factor determined separately using a fluorescent dye standard, R6G. The diffusion time measured for R6G was 55 ls. Less than approximately 10 lW at 488 nm was applied at the sample in order to reduce contribution of triplet state.
where r is the anisotropy measured in the sample; rfree and rbound are anisotropy values of tracer in the absence of antibody and at saturation. The concentration of the free antibody-binding sites can be calculated from ½ABS free ¼ ½ABS total ½T total Fb ;
ð4Þ
where ½ABS total and ½T total are the antibody-binding sites and total concentrations of the tracer, respectively. The fluorescence anisotropy data shown in Fig. 1 fit well to the simple binding model with Kd ¼ 11 nM. All samples measured by FP were also analyzed in the FCS microscope. Fig. 2 shows three autocorrelation function plots corresponding to the samples without antibody, with 50% ligand bound, and in the presence of saturating antibody. A two-component analysis of the ACF at each point in the titration was performed by holding constant the diffusion times for free (sd ¼ 73 ls) and bound tracer (sd ¼ 330 ls) in the nonlinear leastsquares fit. These two parameters were measured directly in samples without antibody and with saturating antibody, respectively. The fit yielded fractions of the free (MW ¼ 732) and bound tracer (MW 151; 000) as a function of antibody-binding site concentration, and fitted well to the simple binding model with Kd ¼ 12 nM (Fig. 3). Thus, the results demonstrate good agreement between FCS- and fluorescence polarization-based measurements for quantitative determination of antibody affinity. We also evaluated the application of FCS to a competition format immunoassay. In this assay the analyte,
Fig. 3. Determination of the dissociation constant for anti-digoxin antibody from the FCS experiment (same samples as in Fig. 1). Points correspond to tracer fraction bound as a function of free antibodybinding sites (Eq. [1]). Solid line is the fit to the data according Eq. [2].
vancomycin, competitively displaces tracer, fluoresceinlabeled vancomycin, bound to the antibody. Vancomycin was assayed using the TDx analyzer, an FPIA-based instrument (Fig. 4). Concentration of the tracer in the assay is 2 nM. The FCS measurements (Figs. 5 and 6) were taken on the same samples and analyzed for free and bound tracer species as described above. The diffusion time of free vancomycin tracer (MW ¼ 1907) was measured as sd ¼ 268 ls and increased to sd ¼ 665 ls when bound to the antibody (MW 152,000). It is important to recognize that fluorescence intensity of the vancomycin tracer is notably weaker compared to the above-mentioned digoxin tracer. To obtain a sufficient
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Fig. 4. Calibration curve for the TDx n TDx FLx vancomycin immunoassay. Each point on the plot shows TDx response in mP units in the presence of a calibrator (analytically prepared vancomycin solution in normal human serum). Curve is generated by a 4-parameter logistic curve fit (4PLC) equation [39].
Fig. 5. Autocorrelation data for vancomycin competition series (same samples as in Fig. 4). Curves from top to bottom correspond to data and fits (Eq. [1]) for 0, 5, 10, 25, and 50 lg/mL of vancomycin. The curves for 50 and 100 lg/mL were identical. In these experiments 0.5% Pluronic F68 was added prior to FCS measurements to minimize nonspecific adsorptive losses on the coverslip at the low component concentrations. In addition, 10 mM mercaptoethylamine (MEA) was added as a triplet-state quencher to all samples.
signal in the experiment the pinhole was increased, leading to increased observation volume and the diffusion times. Also, 10 mM MEA was added as a tripletstate quencher to all samples. The latter dramatically improves quantum efficiency of the tracer, allowing increase of the excitation power to the level required for reliable FCS measurements. As a result, the diffusion times of vancomycin tracer observed under these experimental conditions are significantly longer than in the experiment with digoxin tracer for both the free and the antibody-bound forms. Traditionally, the TDx analyzer results are expressed in the millipolarization (mP) units proportional to the
Fig. 6. Vancomycin immunoassay calibrators (same samples as in Fig. 5) measured with FCS and expressed as a function of the long diffusion time component fraction and concentration of vancomycin. Data points (Table 1) are fitted in the same manner as in Fig. 4.
polarization values measured on a spectrofluorometer. The TDx response changes from 234 mP for the bound tracer to 119 mP when all of the tracer molecules were displaced from the antibody-binding sites by vancomycin. When identical samples were measured by FCS, we observed a strong decline of the fraction of the long diffusion time component from 100% to practically 0%, and therefore, an agreement between the two methods (Fig. 6). The ACF analysis of FCS data also provides information on the number of molecules (N) diffusing through the observation volume. In beginning of the competition experiment with the vancomycin antibody, the average number of fluorescent molecules was 1.2 (Table 1). This number increased monotonically through the titration up to 2.2, when all tracer molecules became essentially free. Such a trend is consistent with the bivalent nature of antibody which initially had two bound tracer molecules, followed by their release in the presence of competitor.
Discussion Nicoli and co-authors [31,32] were first to demonstrate application of FCS to immunoassays in a set of elegant experiments carried out before the advent of modern instrumentation. In this work, the slow diffusion and high fluorescence intensity of micron-sized microparticles coated with antibody were keys in resolving bound vs free fractions of hapten in the fluctuation analysis. Fluorescence fluctuations from nanoliter volumes were generated spatially by scanning the solution. As pointed out by the authors, a drawback to the format they employed was the aggregation of microparticles. In contrast, the antibody–hapten characteristics described in the present study are based on observations
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Table 1 Vancomycin TDx =TDx FLx assay performed on ConfoCor and TDx Vancomycin concentration (lg/mL)
FCS Fraction of long diffusion time component
Number of molecules
Polarization (mP)
FPIA Fraction of tracer bound
0 5 10 25 50 100
1.0 0.87 0.69 0.32 0.11 0
1.2 1.2 1.4 1.7 2.1 2.2
234 223 207 167 139 119
1.0 0.91 0.76 0.41 0.16 0
of binding equilibrium at the single molecule level: the average number of molecules in the observation volume in the experiments presented here was less than 3. A major advantage of modern FCS is the ability to study high-affinity binding reactions in a homogeneous solution without perturbing the equilibrium between free and bound molecules. Thus, FCS becomes one of few techniques which are truly thermodynamically sound. Neither antibody described here changes fluorescence intensity of the bound tracers. Hence, we used ACF analysis to resolve free and bound molecules in solution. As previously indicated, analytical separation of two components in the ACF analysis typically requires at least a twofold ratio in their respective diffusion coefficients, which corresponds to an eightfold ratio in molecular weights for an idealized compact hydrodynamic sphere [20]. For this reason most antibody–hapten systems, including the two described in the current study, are good candidates for the FCS-ACF approach, especially when differences in the fluorescence quantum yields between free and bound states are too small to utilize. Furthermore, with current FCS instrumentation, detection of single molecule events for bright fluorescent labels is optimal in the range of 0.1–100 nM, allowing the measurement of nanomolar affinities. Altogether, these characteristics make the application of FCS and ACF analysis to antibody–hapten-binding equilibria promising. The same experimental setup can be combined with other data-collecting modes and analyses based on changes in fluorescence intensity occurring upon binding. Moment analysis [33], high-order autocorrelation [34,35], and analysis of the single particle photon-count distribution [21,23] have all been successfully applied to extract the fractions of fluorescent species as defined by their molecular brightness. These methods require significant binding-induced changes in fluorescence intensity. For example, the affinity of a mouse monoclonal anti-digoxin antibody was determined by analysis of the photon-count distribution [24] since in this instance, hapten binding is accompanied by a twofold quenching.
Large binding-induced changes in fluorescence intensity occur in antibody–hapten systems typically by circumstance and not by design. On the other hand, it is possible to engineer such an intensity change by introducing a second proximal group that can quench via resonance energy transfer. However, caution is necessary in implementing chemical modifications of antibodies or haptens because new functional groups might introduce a significant perturbation to the relevant binding event and, therefore, might not be tolerable for purposes of the assay. Steady-state fluorescence polarization has long been established as a valuable method for homogeneous immunoassay [36]. FP and FCS share the same advantages with regard to the capability of measuring binding in the homogeneous format with good sensitivity at the nanomolar concentration range typically needed for assaying antibody–hapten reactions. A general comparison of the application of these two techniques to protein–ligand interactions was recently presented [28]. For immunoassay applications, a preference for either FP (steady state) or FCS will depend on the nature of the information sought, as well as experimental parameters and requirements which must be satisfied including measurement speed, numbers of samples, assay design restrictions, choice of fluorophores, and interfering background factors. FP has the advantages of far cheaper and simpler instrumentation, faster sample throughput (e.g., commercial highthroughput FP plate readers now are available), and generally greater precision and reproducibility. However, while FP and FCS are both susceptible to background interferences caused by autofluorescence, quenching, light scattering, and possible aggregation of the assay components, FCS has intrinsically higher information content since both bound and free molecules are directly detected as time-resolved species. In contrast, steady-state FP reveals only the net polarization of the populations, and it must be assumed that the free and bound polarization values (determined in separate measurements) are being maintained under real assay conditions. Hence, FCS has better potential in ligand-binding studies, especially for troubleshoot-
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ing, although both methods are complementary in this regard. Immunoassay probe design is easier with FCS because the choice of both fluorescence probe and chemical linker can be optimized for biological compatibility usually without adverse effects on assay performance. In contrast, probe optimization for FP presents much more of a compromise between biological and assay performance considerations [28]. This study sought to demonstrate the capabilities of FCS in the determination of an antibody–hapten equilibrium dissociation constant and use of FCS in an immunoassay format. It is clear that the single molecule approach of FCS is well suited for immunoassay studies whether one wishes to exploit differences in diffusion between an antibody and hapten as demonstrated in the present work, or binding-induced differences in fluorescence intensity [24]. Implementation of dual fluorophore labeling and cross-correlation FCS strategies [37,38] promises additional advantages by making assays more robust and resistant to background interferences, and allowing greater flexibility in assay design.
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