Open Access
1 November 2009 Confocal detection of planar homogeneous and heterogeneous immunosorbent assays
Homanaz Ghafari, Yanzhou Zhou, Selman Ali, Quentin S. Hanley
Author Affiliations +
Abstract
Optically sectioned detection of fluorescence immunoassays using a confocal microscope enables the creation of both homo- and heterogeneous planar format assays. We report a set assays requiring optically sectioned detection using a model system and analysis procedures for separating signals of a surface layer from an overlying solution. A model sandwich assay with human immunoglobulin G as the target antigen is created on a glass substrate. The prepared surfaces are exposed to antigen and a FITC-labeled secondary antibody. The resulting preparations are either read directly to provide a homogeneous assay or after wash steps, giving a heterogeneous assay. The simplicity of the object shapes arising from the planar format makes the decomposition of analyte signals from the thin film bound to the surface and overlayer straightforward. Measured response functions of the thin film and overlayer fit well to the Cauchy-Lorentz and cumulative Cauchy-Lorentz functions, respectively, enabling the film and overlayer to be separated. Under the conditions used, the detection limits for the homogeneous and heterogeneous forms of the assay are 2.2 and 5.5 ng/ml, respectively. Planar format, confocally read fluorescence assays enable wash-free detection of antigens and should be applicable to a wide range of assays involving surface-bound species.

1.

Introduction

Immunoassay is an analytical technology that has been widely used for diagnosis, chemical analysis, and screening.1 It is a quantitative assay that depends on the reaction between an antigen and an antibody.2 Since its origin around 1960 with the introduction of the first generation of radioimmunoassay until the present, research efforts have been directed toward increasing the sensitivity, decreasing the processing time, and reducing the amount of reagents and sample required.3 A sandwich immunoassay is based on two antibodies that bind to different sites on an antigen. Typically, an enzyme or a fluorophore is attached to the secondary antibody followed by absorbance or fluorescence detection. These techniques are enzyme-linked immunosorbent assay (ELISA) and fluorescence-linked immunosorbent assay (FLISA), respectively.2

Immunochemical assay methods can be grouped to heterogeneous and homogeneous formats. Heterogeneous formats require separation of bound and free labels before measuring the results. Homogeneous assays do not require this separation step and therefore tend to be faster, simpler, and more amenable to automation. There is a wide range of homogeneous format assays in the literature. These vary from assays within a single liquid phase followed by turbidimetric,4 colorimetric, 5, 6, 7 fluorometric,8, 9 and luminescent10 detection schemes to biphasic assays in which reagents partition between a liquid and a solid phase. Examples of the latter include beads,11, 12, 13, 14 colloidal gold and latex particles,15, 16 membranes,17, 18 and cells.19, 20, 21 Some authors have argued that the term homogeneous be restricted to assays where the solid phase remains suspended in solution,22 however, there is no general agreement on this point. Here we use the term homogeneous to refer to a biphasic assay that does not require separation of free reagents via wash steps.

Confocal laser scanning microscopy (CLSM) is an imaging technique producing optical sections of a 3-D specimen from a single focal plane by introducing illumination and detection pinholes. The optical sections have a shallow depth of field, enabling collection of data from a single plane rather than the entire thickness of the specimen. The elimination of out-of-focus light results in an increase in contrast, clarity, and detection sensitivity.23 By moving the focal plane along the z axis, a series of optical sections can be recorded. The important advantage of confocal microscopy is the improvement in z axis (axial) resolution due to elimination of out-of-focus photons. Axial resolution depends on the pinhole size, the numerical aperture (NA) of the objective, and the excitation and emission wavelengths. The scan speed of CLSM is limited by its low duty cycle, however, a variety of alternative optical sectioning methods exist, including multipoint24 (Nipkow-type spinning-disk microscopy) and line scanning laser microscopy25 (L2M), programmable array microscopy (PAM),26, 27 and spinning disks equipped with a microlens arrays.28 These and a variety of other structured light approaches29, 30 could provide optical sectioning for fast detection of planar format assays.

Detection of a FLISA by CLSM has been described previously for bead-based assays11, 13, 31, 32, 33 and spot microarray formats.34 Although confocal readout has been described in these papers, they were not carried out in a homogeneous planar format nor have the characteristics of the confocal response from these systems been published. A planar format has two main advantages over beads in this context. First, beads are susceptible to motion during readout unless immobilized. Second, the shape of the bead requires that more complex procedures be used to remove the fluorescent background and determine the intensity arising over the entire volume of the bead.

Fluorometric microvolume assay technology (FMAT) was used as a detection method in FLISA bead-based homogenous assays for high-throughput screening. The optical system of FMAT has been described in detail11, 35 and a commercial FMAT scanner was released11 in 1999. The FMAT system consisted of a confocal scanner with a 20×NA 0.45 objective for detecting the FLISA with 6-μm -diam polystyrene beads in a homogenous immunoassay format.

Confocal readout of microarray format immunoassays was accomplished previously and there are commercially available scanners for this purpose.36, 37 The requirement when using such a confocal microscope system for microarray scanning is a very flat surface for the microarray substrate and sufficient scanning speed to avoid photobleaching of the fluorophores.38 There is, however, no consensus on the benefits of confocal readout in the literature. For example, confocal readout has been presented as a sensitive method for determination of fluorescent signals emitted from the spots while rejecting out-of-focus background.3 Conversely, it has been argued that most of the background signal on microarrays comes from nonspecific binding to the slide surface, which is in the same plane of focus as the sample and, thus, confocal read out provides little benefit as a microarray scanning method.38

Two-photon excitation has been described as another optical sectioning method for measuring the degree of binding of a fluorescent tracer attached to 3-μm polystyrene microparticles in a homogeneous immunoassay.39 An instrument for two-photon excitation microparticle fluorometry (TPX) was built to detect the fluorescence from individual microparticles (1to10μm) in suspension and measure C-reactive protein,40 antiadenovirus antibodies,41 and influenza A and B virus antigens.42 The authors reported good sensitivity and dynamic range with no washing steps along with the ability to multiplex the assay. Real-time monitoring of the bioreaction and testing of the plasma samples demonstrated the potential of the TPX method for development of clinical immunoassays.40

Here we demonstrate a set of planar FLISA assays requiring optical sectioning to read out. The assays are based on a model sandwich immunoassay consisting of a goat antihuman immunoglobulin G (IgG) immobilized on a glass surface and a goat FITC-labeled antihuman IgG, which are used to detect human IgG. The model system was used to explore the confocal readout process while carrying it out in a spectrum of assays ranging from completely heterogeneous (two wash steps) to completely homogeneous (no wash steps). In these model systems, confocal readout enables fewer wash and incubation steps compared to conventional planar assays. By eliminating wash steps, the confocal assay is simpler and potentially more rapid.

1.1.

Theory

1.1.1.

Optically sectioned detection of planar format immunoassays

The key part of the confocal sandwich immunoassay (Fig. 1 ) is a fluorescent layer consisting of three stacked IgG molecules, which is <50nm in thickness.43, 44, 45 Depending on the orientation of the IgGs within the film, the thickness may range from 12to45nm . This dimension varies depending on whether it is estimated based on x-ray crystallographic data, scanning probe micrsocpy, or electron microscopy.42, 43, 44, 45 The value of 50nm used here is meant to be a conservative estimate indicating that the film thickness is arbitrarily thin under the measurement conditions. In contrast to beads, the axial position of a planar thin fluorescent film oriented along the bottom of a plate can not be detected with a conventional microscope. Hence, there is no way to determine the location and relative intensities of the thin film and overlayer with such a system. In addition, the thickness of this thin fluorescent layer is below the resolution limit of all but the most advanced far-field fluorescence microscopes.46 Although the thickness of IgGs stacked in a film can not be measured with a confocal microscope due to the diffraction limit, both the position on the maximum in the axial response curve and the intensity of light from the film can be measured with considerable precision.

Fig. 1

Schematic diagram of a confocal sandwich immunoassay. The response curve has three zones: (I) the negative z position represents locations inside the 170-μm -thick glass slide; (II) the location of the thin sandwich immunoassay film ( 50nm thick); and (III) the positive z position shows the fluorescent overlayer of unbound secondary antibody. The assay structure consisting of overlayer, thin film, and glass substrate is located above the objective and inverted microscope. To clarify the geometry of the assay with respect to the microscope the graph is oriented relative to the laboratory axes. Subsequent figures plot axial position horizontally.

064022_1_024906jbo1.jpg

In the confocal microscope, the planar assay format can be thought of as the sum of a thin film and an overlayer. An optical model of this system consists of a 50-nm thin film and a uniformly fluorescent overlayer beginning 50nm above the glass surface and extending away from the film (Fig. 1). The thin film and overlayer differ only in the concentration-dependent intensity, designated C1 and C2 , respectively. More rigorously, the two fluorescent objects (O) in the microscope can be given as a function of position along the z axis: O1(z)=C1 for 0<z<50nm and is 0 everywhere else, and O2(z)=C2 for 50nmz< and is 0 elsewhere. The overall object function is the sum of the two:

Eq. 1

O(z)=O1(z)+O2(z).
For the purpose of the assay, the key to making accurate measurements of surface-bound fluorescence is the ability to selectively determine the concentration-dependent intensities C1 and C2 .

In the microscope, the object function is not observed directly. Instead, the measured object (M) depends on the object function convolved with h , the confocal point spread function (PSF):

Eq. 2

M(z)=hO(z).
Since the diffraction-limited resolution along the z axis in a confocal microscope observed at a high NA is of the order of 500nm , the surface-bound film is thin relative to the resolution of the microscope. This has the consequence that although the object as modeled consists of exclusive zones associated with either C1 or C2 , the measured z axis “image” contains signals arising from both the overlayer and the thin film at every position along the z axis. For large z , the contribution of the film can be made arbitrarily small. A similar condition does not hold for the overlayer; the overlayer will contribute significantly to the signal at all locations along z due to blurring by the confocal PSF. Note that M can be broken down into the parts corresponding to the two composing objects:

Eq. 3

M(z)=hO1(z)+hO2(z).
This equation suggests two ways to obtain information selectively from the thin film. The first approach is to convolve ideal objects [Eqs. 1, 2] with a computed PSF. For this study, the PSF, as described by van der Woort and Brakenhoff,47 was applied to idealized objects, as in Eq. 1. The relative intensities associated with C1 and C2 are then adjusted until a best fit to the measured data is obtained using least-squares minimization. Alternately, a semiempirical approach can be used in which the axial response of the microscope is measured for a thin film in the absence of an overlayer and for the overlayer in the absence of the thin film. The measured data are then synthesized by making linear combinations of the two measured objects. The best results are obtained by fitting the observed data to simplified functions that mimic much of the behavior of planar objects modified by PSFs. The Cauchy-Lorentz function and the cumulative Cauchy-Lorentz function are comparatively simple functions that fit the shape of real axial response functions affected by aberrations reasonably well. The semiempirical fit used the following form:

Eq. 4

M(z)=C11πγ{1+[(zz0)γ]2}+C2[1πarctan(zz0γ)+12]+B,
where z is the axial position, z0 is the center of the thin film, γ is the width of the response, and B is a constant that corrects for electronic offsets and photomultiplier tube background in the confocal microscope.

1.1.2.

Adsorption of proteins to a solid phase

The Langmuir equation is widely used to describe equilibrium adsorption phenomena.3, 48 The Langmuir isotherm was originally developed to model the adsorption of gas molecules to solid phases but it has been further applied to the adsorption of proteins to a solid phase49 as follows:

Eq. 5

F=Fmax[C]KD+[C].
In this equation, F is the observed fluorescence, Fmax is the maximal fluorescence, [C] the concentration of protein in the solution, and KD is the thermodynamic dissociation constant.

1.1.3.

Estimating errors in parameters

Numerical differentiation can be used to estimate errors in parameters found by least-squares minimization50 [e.g., least squares fits to Eq. 4]. The standard deviations si of the i ’th parameter ai is

Eq. 6

si=[Pi,i1(ssresidnk)]12.
The treatment here is substantially based on Billo.50 This reference should be consulted for further details of the method. In Eq. 6 Pi,i1 is the i ’th diagonal element of the inverse of the matrix P , ssresid is the residual sum of squares for the model, n is the number of data points, and k is the number of parameters; P has elements given by

Eq. 7

Pi,j=n=1NδMδaiδMδaj,
where δMδai and δMδaj are partial derivatives of the model function [e.g., Eq. 4] with respect to the i ’th and j ’th parameters. The derivatives can be approximated as ΔMΔai by making small changes in a coefficient and computing the change in M . In this fashion, the elements of P are computed. We compute P1 to estimate the errors in the estimated parameters.

2.

Materials and Methods

2.1.

Reagents

Human IgG (Product No. I4506), goat antihuman IgG ( γ -chain specific) (Product No. I3382), goat antihuman IgG ( γ -chain specific), FITC conjugate (Product No. F-0132), bovine serum albumin (BSA) minimum 98% (Product No. A7030), Dulbecco’s phosphate-buffered saline (PBS) pH 7.4 (Product No. D8537), and NaN3 (Product No. S8032) were purchased from Sigma-Aldrich Company Ltd. (Dorset, United Kingdom). The step size optimization study employed quantum dot labeled goat F(ab)2 anti-human IgG (Product No. Q11231MP; Invitrogen Ltd.; Paisley, United Kingdom). Chambered cover glass slides (Lab-Tek chambered #1.0 borosilicate, Product No. 155411, Nalgene Nunc International, United States) and glass bottom 96-well plates (Product No. 164588, Nalgene Nunc International, United States) were used as solid supports for the immunoassay.

2.2.

Instrumentation

A confocal scanner head (TCS NT; Leica Microsystems, Heidelberg GmbH, Germany) installed on an inverted microscope (DMIRBE, Leica Microsystems Wetzlar GmbH, Germany) was used for the optical sectioning of the immunoassay. The 488-nm line of an argon ion laser was used for excitation and the emission fluorescent intensity was detected using a 53030-nm bandpass filter. The objectives used were HC PL FLUOTAR 10×0.3 DRY, PL FLUOTAR 16×0.5 IMM, HCX PL FL L 40×0.6 CORR, HCX PL FLUOTAR L 40×0.75 DRY, and HCX PL FLUOTAR L 63×0.7 CORR.

2.3.

Preparation of Confocal Sandwich Immunoassay

The IgG immunoassays were conducted by immobilizing antihuman IgG as the capture antibody on chamber slides or 96-well plates overnight at 4°C . The remaining sites for protein binding were blocked with a solution of 1% BSA (1% BSA in PBS with 0.02% NaN3 ) for 2h . After washing with PBS, for heterogeneous immunoassay, human IgG was added as an antigen and incubated for 2h with shaking. The chambers/wells were washed with buffer. Goat anti-human IgG-FITC was added to the chambers/wells as the secondary labeled antibody and incubated for 1h . For the homogenous format assays, human IgG and goat antihuman IgG-FITC were added simultaneously to the chambers/wells and incubated for 3h . All steps from blocking to final incubation were performed at room temperature under continuous shaking. The chambers/plates were scanned with the confocal microscope without washing the second labeled antibody. The chambers/wells were then washed after scanning to investigate the effect of washing the secondary antibody on the response of the immunoassays.

2.4.

Analysis

The sum of the intensity of each image in the stack of confocal images was computed and plotted against z axis position. These data were fit to Eqs. 2, 4 using least-squares minimization. Detection limits were determined in two steps. First, the dose response curve was determined over a range of antigen concentration from 0to500ngml with three replicates at each concentration. This was used to determine the slope of the linear portion of the response curve. Second, a further 10 replicates at the lowest detectable concentration from the dose response curve and the blank were measured and used to calculate the detection limit (DL):

Eq. 8

DL=tsm,
where m is the slope of the linear portion of a dose response curve, t=2.821, and s is the standard deviation of a set of 10 sample measurements. Reported “lowest detected concentrations” represent the lowest concentration of the sample generating a significant (p<0.05) difference from a set of blank measurements based on a t test.

3.

Results

3.1.

Quality Assessment of Parameters Affecting the Confocal Axial Response

Image quality is important when evaluating the performance of a confocal microscope.51, 52, 53 We investigated parameters affecting the quality of the response from the confocal microscope relevant to our assays: NA, pinhole size, and step size. Step size is discussed in Sec. 3.2.3.

3.1.1.

NA

The intensity of a thin fluorescent film resulting from the human IgG model system after removal of the overlayer was measured in the confocal microscope with five different objectives varying in NA from 0.3 to 0.7 in a 512×512 region. The axial response was measured with a 74-μm pinhole every 0.4μm along the z axis for a total of 50 images. While remaining constant in this set of experiments, the pinhole was below one Airy disk diameter and has little or no effect on the resolution for this set of magnifications and NAs. The full width at half maximum (FWHM) was measured for each objective (Table 1 ). As expected, the FWHM decreased with increasing NA with all the objectives showing an axial response to the thin film even at low NA. The improved resolution at a high NA is advantageous as it will result in less blurring between film and overlayer and thus improve both sensitivity and limits of detection. Based on these results, the 40×NA 0.75 objective was selected for subsequent use.

Table 1

Variation of the FWHM of the axial response to a thin film when observed in the microscope as a function of NA for a variety of objectives.

ObjectiveFWHM (μm)
10×NA 0.3010.5
16×NA 0.57.0
40×NA 0.603.4
63×NA 0.702.8
40×NA 0.751.8

3.1.2.

Pinhole size

The effect of the pinhole size on the intensity and resolution of the axial response was studied using the 40×NA 0.75 objective using 50 steps of 0.4μm along the z axis. The intensity of the signal increased nearly linearly with the pinhole size, but the FWHM of the axial response increased rapidly when the pinhole exceeded 150μm (Fig. 2 ). The Airy disk diameter in the focal plane for the 40×NA 0.75 objective is approximately 140μm and the optimal pinhole size is considered to be about 50 to 60% of this value,53 in good agreement with the measured data. In addition, since the axial resolution does not improve significantly below this optimum, there is no benefit to further reduction in pinhole size. The only effect would be to reduce the signal strength from the film. Based on these experiments the pinhole size was set to 74μm in subsequent experiments.

Fig. 2

Variation of the FWHM of the axial response of a confocal microscope as a function of pinhole size for the 40×NA 0.75 objective. The axial response begins to degrade when the pinhole is near the diameter of the Airy disk (140μm) . The line is only to guide the eye.

064022_1_024906jbo2.jpg

3.2.

Heterogenous Confocal Sandwich Assay

3.2.1.

Response of film and overlayer

Human IgG as the antigen (1μgml) was added to coated chamber slides with the primary antibody (20μgml) followed by the secondary antibody (40μgml) . The chamber was scanned in the confocal microscope using the 40×NA 0.75 objective using 50 steps of 0.2μm along the z axis and a 74-μm pinhole without removing the fluorescent solution. The axial response exhibited three distinct features (Fig. 1): (I) a region of gradually decreasing signal trending to zero corresponding to the glass surface below the assay (0to5μm) , (II) a prominent peak arising from the thin film of concentrated fluorescence on the glass surface (0μm) , and (III) a region of decreasing fluorescence trending to a constant value resulting from the fluorescence of the overlayer of unbound secondary antibody (0to5μm) . The FWHM of the peak was 1.75μm and the measured axial response indicated that the peak height contains signals from both the thin film and the fluorescent overlayer. The presence of overlayer fluorescence indicates that an excess of secondary antibody is present and must be separated from the film signal.

3.2.2.

Decomposition of the signals of the thin film from an overlying fluorescent solution

The first approach to separating the signals used full numerical simulation of the response from an object consisting of a thin film and overlayer convolved with a confocal PSF. The PSF was generated according to van der Voort and Brakenhoff;47 however, the correspondence between experimental results and simulation was poor (data not shown), particularly in the wings of the thin film response. We ascribe this to aberrations resulting from refractive index mismatches (air, glass, and water) and the imperfect behavior of the lenses in our system.

The second method used for separation was based on distribution functions. Axial responses of the thin film in the absence of overlayer (a sample after washing the overlayer) and the overlayer in the absence of the thin film (a blank with same concentrations of first and secondary antibodies) were scanned [Fig 3a ]. After testing the Gaussian and the Cauchy-Lorentz functions, the Cauchy-Lorentz functions were found to fit the measured data well. The sum of the Cauchy-Lorentz and cumulative Cauchy-Lorentz functions [Eq. 4] fit well to the experimental data from the confocal immunoassay. This enabled the decomposition of the axial response of the assay into two objects: the thin film and the overlayer [Fig. 3b]. Excellent reproducibility (±0.04μm) was seen in localizing the position of the thin film across the bottom of a chambered glass slide, indicating good slide flatness and microscope stability.

Fig. 3

Decomposition the signal of confocal immunoassay to the thin film and overlayer based on Cauchy-Lorentz function: (a) the axial responses of thin film (●) and overlayer (◼) measured separately, and (b) the axial response of a sandwich immunoassay where the experimental data (●) is decomposed to thin film (- - -) and overlayer (—) after fitting the experimental data to the sum of thin film and overlayer. The line connecting the data points is the best fit to Eq. 4 for this set of measurements.

064022_1_024906jbo3.jpg

3.2.3.

Step size optimization

The effect of step size on the separation of signals from the thin film and the fluorescent overlayer was studied by changing the step size in 0.1-μm intervals between 1.6 and 0.1μm over an approximately 10-μm scan range with a 40×NA 0.75 objective. Where 10μm was not evenly divisible by the step size the closest scan range to 10μm was selected. This experiment was performed using quantum dots as the reporter fluorophore to mitigate photobleaching problems in repeated scans of the same location encountered with FITC-labeled materials. The results showed that the signal-to-noise ratio (SNR) of the thin film intensity parameter [ C1 in Eq. 4] decreases in a logarithmic fashion as the step size increased (Fig. 4 ) with a tendency to overestimate the intensity of the thin film at step sizes 1μm . Experiments described in subsequent portions of this report were performed using a 0.2-μm step size, which corresponded to an SNR of 168 in the optimization study.

Fig. 4

Variation in SNR as step size increases over a fixed z axis scan range. Scans were done using a quantum dot reporter in this experiment to enable repeated scans of the same location to be comparable. All other data reported in this paper used FITC-labeled materials. The line shown corresponds to a logarithmic fit to the measured data. SNR improves as the step size decreases for a fixed scan range. This arises from better sampling of the axial response and an increase in the number of data points in the fit.

064022_1_024906jbo4.jpg

3.2.4.

Heterogenous confocal sandwich assay optimization

We optimized the different steps of the immunoassay procedure for the widest dynamic range. The concentration of coating antibody (goat antihuman IgG) was tested from 2.5to320μgml at a constant saturating level of antigen and secondary antibody (100μgml) [Fig. 5a ]. Using our protocol, the observed behavior appeared to follow a Langmuir adsorption process. A concentration of 160μgml was chosen as optimal for the first antibody. This is a relatively high loading of the first antibody, but was found to work well for the chamber slides, reagents, and conditions in these experiments. The influence of the FITC-conjugated secondary antibody was investigated between 10 and 100μgml [Fig. 5b] at a constant coating of antibody and the antigen yielding an optimal concentration of secondary antibody (50μgml) .

Fig. 5

Optimization of the model assay system for wide dynamic range: (a) response curve of the primary antibody with Langmuir fit and (b) response curve of the secondary antibody.

064022_1_024906jbo5.jpg

3.2.5.

Heterogeneous confocal planar immunoassay detection limit

A glass 96-well plate was coated with a saturating concentration of primary antibody overnight. After blocking and washing the wells, serial dilutions of human IgG over the range from 0.5μgmlto0.5ngml , and the same volume of buffer with no human IgG as blank were added to the wells and detected with a low concentration of secondary antibody (0.5μgml) . Figure 6a shows the calibration curve plotted as the difference between intensity of sample and the average of blank signal (n=3) versus antigen concentration. The wells were washed with PBS and scanned again to see the effect of washing on responses. The dose response curve before washing the overlayer has a good linear range over the studied range of human IgG concentrations (r2=0.9984) . A comparison of average intensities of the low concentrations of antigen and blanks (n=10) showed that 5ngml (before washing) and 10ngml (after washing) of human IgG could be detected with > 98% confidence. The confidence level reported is from a two-tailed test. Strictly speaking, a one-tailed test can be used as the only relevant result is when the average blank is less than the sample. We chose to report the confidence level of the more conservative test. The calculated detection limits were 5.5 (before washing) and 10.4ngml (after washing). The protocol with fewer wash and incubation steps was more sensitive, an effect we ascribe to some second antibody being rinsed from the surface.

Fig. 6

Calibration curves of low concentrations of antigen before (◼) and after (●) washing the fluorescent overlayer in (a) heterogeneous and (b) homogeneous format assays. The intensity was obtained after subtraction of the mean blank signal (n=10) . Error bars correspond to ±s (n=3) .

064022_1_024906jbo6.jpg

3.3.

Homogeneous Confocally Detected Planar Immunoassay

To demonstrate the adaptability of the confocally detected immunoassay to a homogenous format, the same model system was adopted to remove all sample and detection wash steps. A serial dilution of antigen over a range from 0.5μgmlto0.5ngml was compared to blanks consisting of PBS buffer with no human IgG. A low concentration of second antibody (0.5μgml) was added simultaneously with the prepared antigen solution to the wells of a 96-well plate coated with a saturating amount of primary antibody. The dynamic range of the calibration curve is shown in Fig. 6b. The homogeneous format approached saturation around 0.5μgml , a result consistent with the amount of second antibody (0.5μgml) and the ratio of antigen and antibody molecular weights (1:1) . The dynamic range of the calibration curve was limited because the concentration of second antibody was intentionally kept low as this was found to improve sensitivity. The assays were subsequently washed for comparison purposes to evaluate the effect of washing on the thin film. The homogeneous assay detection limit was 2.2ngml in the absence of all wash steps. As observed in the heterogenous assay results, the detection limit increased to 6.0ngml after washing the overlayer. This reinforces the conclusion that wash steps remove analytically important material from the surface and the confocally detected homogeneous planer assay showed better detection limits than the heterogeneous one.

4.

Discussion

We demonstrated a confocal readout method for detection of sandwich immunoassays using a human IgG model system. The response of the confocal system showed an antigen-dependent intensity variation originating from a thin film on a glass surface in the presence of an overlayer. We studied the axial response of the thin films generated by our assay to changes of NA and pinhole size and the results showed general agreement with published data on thin films.27 These results are general to a wide range of planar format assay systems,54, 55 which could be readily adapted to become homogenous assays. These include planar arrays for the detection of genetic material and infectious diseases and many assays currently used in high-throughput screening. Further, other optical sectioning methods, such as two- and three-photon excitation and stimulated emission depletion (STED) could be used to similar or better effect to the standard confocal methods used here. Also, using high-speed confocal microscopy systems24, 25, 26, 27, 28, 29, 30 will improve the slow frame rate of currently available confocal systems.

The consistent trend for improved detection limits observed as the number of wash steps decreased across all of the assay formats implies that weak antigen-dependent interactions were removed by washing. A related trend was seen when comparing the heterogeneous and homogeneous formats. Perhaps uniquely, the homogeneous format reported here exhibited better sensitivity than any of the others. This is due to a combination of preserving interactions between the first antibody and the antigen, between the antigen and the second antibody, and possibly some formation of aggregates in solution between the antigen and the second antibodies prior to binding to the plate. By deleting all washing steps, it is possible to keep and detect even weak interactions between antigen and antibodies and improving the detection limits. Our 2.3-ngml detection limit for the human IgG immunoassay is competitive with others reported for this model system. For example, such a model system detected using quantum dots after removing the overlayer was37 sensitive to 2μgml . Note that the conditions producing the greatest sensitivity differ greatly from those producing a quantitative response over the widest dynamic range. Sensitivity is expected to be fundamentally limited by the Poisson statistics of photons generated by the overlayer. Therefore, sensitivity is enhanced at lower concentrations of secondary antibody because it lowers the noise generated by the overlayer. The widest dynamic range is produced by levels of secondary antibody sufficient to detect saturating levels of antigen. We anticipate future improvements in the method by optimized instrumentation, the introduction of quantum dots for better photostability,56 higher NA optics, and additional optimization of the reagent and support surfaces.

A wide range of reports of confocal scanners for readout of fluorescent spots in planar arrays and bead assay systems have appeared in the literature. Despite numerous reports, we are not aware of a paper in which instrumental details are provided for the confocal scanner sufficient to reproduce the experiment together with a measured axial response from an immunoassay. Miriglia 11 are exceptional in providing the NA and other optical details of their experiment. More common are reports of “proprietary” systems with few other details.57, 58 It is also of interest that, to our knowledge, none of these previous studies required a confocal or optically sectioned readout and the confocal readout was of arguable benefit. This work is an attempt to provide a clear example where the confocal readout is required and provides benefit (e.g., no wash steps and preservation of weak interactions) together with sufficient optical detail to determine how to best take advantage of optical sectioning in assays.

Our approach to planar assays shares advantages with other related homogenous and fluorescence-based assays and presents several attractive features. First, compared to conventional ELISAs, the planar homogenous assay could potentially save time due to the reduction of wash steps and the fluorescence readout does not require time for an enzyme reaction to develop. Second, assays can be stored for several days before readout.59 Third, the planar homogeneous assay does not require beads or specialized reagents beyond those commonly available in many laboratories and will not suffer from bead motion during readout. Fourth, Due to the ability to eliminate wash steps, the approach is quite attractive for assays based on weaker interactions; such interactions are of very wide interest in high-throughput screening. High-throughput screening instrumentation already exists for confocally detected cellular assays and could be adapted for other types of screening and use in clinical labs. Fifth, since no washing is required, antigen-antibody reactions can be monitored in real time by measuring the intensity of the thin layer on the well bottom in the presence of free labeled antibody in the overlayer at any time. Evaluation of the rate constants of antigen–antibody pairs is possible under true assay conditions. Similar studies have been done on microparticles,60 but not in planar formats. Studies on the kinetics of surface interactions by our method are underway. Sixth, it enables assays to be stacked in 3-D arrays followed optically sectioned readout. Finally, although we implemented the planar format using antibody-antigen interactions, the approach is general to a wide range of assays that can be presented as a reaction between a surface-bound species and free ligands.

The optical system is designed to work in chamber slides or multiwell plates presenting an optical glass surface with standard refractive index (n=1.515) and thickness (0.17mm) . This matches the design criteria for many microscope objectives and minimizes the spherical aberration due to refractive index mismatch. The use of different optical media could result in poor resolution and decreased intensity. For example, when working with polystyrene (n=1.5917) or polycarbonate (n=1.5849) plates, objectives with a correction collar for variable glass thickness (e.g., 0to2mm ) can be used to correct the lack of correct refractive index matching. The use of air objectives, as described here, simplifies sample-changing automation in an inverted geometry by eliminating immersion fluids.

The best separation between film and overlayer was achieved with the highest NA. Further improvement is expected at a higher NA due to better resolution and consequential improvements in detection limits, and better sensitivity are expected under these conditions. Practically, air lenses with longer working distances may be preferable; however, this choice is an engineering related compromise not a fundamental issue. Immersion objectives are somewhat awkward to use in inverted geometries. Finally, for a given a fixed scan range, SNR is improved by decreasing the step size.

Acknowledgments

This work was funded by the European Union Sixth Framework Programme as part of the FLUOROMAG consortium under Contract No. 037465. Dr. Yanzhou Zhou was funded by the Engineering and Physical Sciences Research Council (EPSRC) under a Life Sciences Interface Grant No. EP/E013422/1.

References

1. 

A. H. Wu, “A selected history and future of immunoassay development and applications in clinical chemistry,” Clin. Chim. Acta, 369 (2), 119 –124 (2006). https://doi.org/10.1016/j.cca.2006.02.045 0009-8981 Google Scholar

2. 

C. P. Price and D. J. Newman, Principles and Practice of Immunoassay, Macmillan Reference Ltd., London (1997). Google Scholar

3. 

R. P. Ekins, “Ligand assays: from electrophoresis to miniaturized microarrays,” Clin. Chem., 44 (9), 2015 –2030 (1998). 0009-9147 Google Scholar

4. 

G. Burns, A. Kurrle-Weittenhiller, J. Karl, W. D. Engel, A. Gromping, K. S. Boos, and D. Seidel, “A simple turbidimetric assay designed for the routine screening well as therapeutic monitoring of native LDL particles,” Clin. Chim. Acta, 303 (1–2), 155 –165 (2001). https://doi.org/10.1016/S0009-8981(00)00395-8 0009-8981 Google Scholar

5. 

L. J. Lewellen and H. H. McCurdy, “A novel procedure for the analysis of drugs in whole-blood by homogeneous enzyme-immunoassay (emit),” J. Anal. Toxicol., 12 (5), 260 –264 (1988). 0146-4760 Google Scholar

6. 

D. A. Armbruster, E. C. Hubster, M. S. Kaufman, and M. K. Ramon, “Cloned enzyme donor immunoassay (cedia) for drugs-of-abuse screening,” Clin. Chem., 41 (1), 92 –98 (1995). 0009-9147 Google Scholar

7. 

Z. S. Wu, S. B. Zhang, M. M. Guo, C. R. Chen, G. L. Shen, and R. Q. Yu, “Homogeneous, unmodified gold nanoparticle-based colorimetric assay of hydrogen peroxide,” Anal. Chim. Acta, 584 (1), 122 –128 (2007). https://doi.org/10.1016/j.aca.2006.11.003 0003-2670 Google Scholar

8. 

T. Kokko, L. Kokko, T. Soukka, and T. Lovgren, “Homogeneous noncompetitive bioaffinity assay based on fluorescence resonance energy transfer,” Anal. Chim. Acta, 585 (1), 120 –125 (2007). https://doi.org/10.1016/j.aca.2006.12.021 0003-2670 Google Scholar

9. 

E. Loomans, A. M. van Doommalen, J. W. Y. Wat, and G. J. R. Zaman, “High-throughput screening with immobilized metal ion affinity-based fluorescence polarization detection, a homogeneous assay for protein kinases,” Assay Drug Develop. Technol., 1 (3), 445 –453 (2003). https://doi.org/10.1089/154065803322163759 Google Scholar

10. 

E. F. Ullman, H. Kirakossian, A. C. Switchenko, J. Ishkanian, M. Ericson, C. A. Wartchow, M. Pirio, J. Pease, B. R. Irvin, S. Singh, R. Singh, R. Patel, A. Dafforn, D. Davalian, C. Skold, N. Kurn, and D. B. Wagner, “Luminescent oxygen channeling assay (LOCI(TM)): sensitive, broadly applicable homogeneous immunoassay method,” Clin. Chem., 42 (9), 1518 –1526 (1996). 0009-9147 Google Scholar

11. 

S. Miraglia, E. E. Swartzman, J. Mellentin-Michelotti, L. Evangelista, C. Smith, I. Gunawan, K. Lohman, E. M. Goldberg, B. Manian, and P. M. Yuan, “Homogeneous cell- and bead-based assays for high throughput screening using fluorometric microvolume assay technology,” J. Biomol. Screening, 4 (4), 193 –204 (1999). https://doi.org/10.1177/108705719900400407 1087-0571 Google Scholar

12. 

J. H. Toney, A. Ogawa, M. Blair, and Y. W. Park, “A ‘Mix and read’ assay for insulin using fluorometric microvolume assay technology,” Assay Drug Develop. Technol., 1 (4), 521 –525 (2003). https://doi.org/10.1089/154065803322302772 Google Scholar

13. 

E. E. Swartzman, S. J. Miraglia, J. Mellentin-Michelotti, L. Evangelista, and P. M. Yuan, “A homogeneous and multiplexed immunoassay for high-throughput screening using fluorometric microvolume assay technology,” Anal. Biochem., 271 (2), 143 –151 (1999). https://doi.org/10.1006/abio.1999.4128 0003-2697 Google Scholar

14. 

D. K. Miller, J. D. Menke, N. S. Hayes, A. Uzieblo, D. Tew, Y. Hayashi, Y. F. Guan, A. Zhao, R. T. Cummings, Y. W. Park, and T. T. D. Yamin, “Development of a high-capacity homogeneous fluorescent assay for the measurement of leukotriene B-4,” Anal. Biochem., 349 (1), 129 –135 (2006). https://doi.org/10.1016/j.ab.2005.10.043 0003-2697 Google Scholar

15. 

M. Tanaka, K. Matsuo, M. Enomoto, and K. Mizuno, “A sol particle homogeneous immunoassay for measuring serum cystatin C,” Clin. Biochem., 37 (1), 27 –35 (2004). https://doi.org/10.1016/j.clinbiochem.2003.08.001 0009-9120 Google Scholar

16. 

J. H. W. Leuvering, B. C. Goverde, P. Thal, and A. Schuurs, “A homogeneous sol particle immunoassay for human chorionic-gonadotropin using monoclonal-antibodies,” J. Immunol. Methods, 60 (1–2), 9 –23 (1983). https://doi.org/10.1016/0022-1759(83)90330-7 0022-1759 Google Scholar

17. 

T. Aoki, S. Tsuchida, T. Yahara, and N. Hamaue, “Novel assays for proteases using green fluorescent protein-tagged substrate immobilized on a membrane disk,” Anal. Biochem., 378 (2), 132 –137 (2008). https://doi.org/10.1016/j.ab.2008.04.022 0003-2697 Google Scholar

18. 

T. Aoki, H. Kazama, M. Satoh, K. Mizuki, and H. Watabe, “A homogeneous assay for relative affinity of binding proteins using a green fluorescent protein tag and membrane disk,” Anal. Biochem., 344 (1), 25 –32 (2005). https://doi.org/10.1016/j.ab.2005.06.019 0003-2697 Google Scholar

19. 

A. Datti, R. S. Donovan, B. Korczak, and J. W. Dennis, “A homogeneous cell-based assay to identify N-linked carbohydrate processing inhibitors,” Anal. Biochem., 280 (1), 137 –142 (2000). https://doi.org/10.1006/abio.2000.4506 0003-2697 Google Scholar

20. 

A. L. Niles, R. A. Moravec, P. E. Hesselberth, M. A. Scurria, W. J. Daily, and T. L. Riss, “A homogeneous assay to measure live and dead cells in the same sample by detecting different protease markers,” Anal. Biochem., 366 (2), 197 –206 (2007). https://doi.org/10.1016/j.ab.2007.04.007 0003-2697 Google Scholar

21. 

R. Lee, M. Tran, M. Nocerini, and M. Liang, “A high-throughput hybridoma selection method using fluorometric microvolume assay technology,” J. Biomol. Screening, 13 (3), 210 –217 (2008). https://doi.org/10.1177/1087057108314148 1087-0571 Google Scholar

22. 

X. Y. Xu, D. G. Georganopoulou, H. D. Hill, and C. A. Mirkin, “Homogeneous detection of nucleic acids based upon the light scattering properties of silver-coated nanoparticle probes,” Anal. Chem., 79 (17), 6650 –6654 (2007). https://doi.org/10.1021/ac070867g 0003-2700 Google Scholar

23. 

S. J. Wright and D. J. Wright, “Introduction to confocal microscopy,” Method in Cell Biology, 2 –81 Academic Press, San Diego (2002). Google Scholar

24. 

T. Wilson, R. Juskaitis, M. A. A. Neil, and M. Kozubek, “Confocal microscopy by aperture correlation,” Opt. Lett., 21 (23), 1879 –1881 (1996). https://doi.org/10.1364/OL.21.001879 0146-9592 Google Scholar

25. 

R. Wolleschensky, B. Zimmermann, and M. Kempe, “High-speed confocal fluorescence imaging with a novel line scanning microscope,” J. Biomed. Opt., 11 (6), 064011 (2006). https://doi.org/10.1117/1.2402110 1083-3668 Google Scholar

26. 

P. J. Verveer, Q. S. Hanley, P. W. Verbeek, L. J. Van Vliet, and T. M. Jovin, “Theory of confocal fluorescence imaging in the programmable array microscope (PAM),” J. Microsc., 189 192 –198 (1998). https://doi.org/10.1046/j.1365-2818.1998.00336.x 0022-2720 Google Scholar

27. 

Q. S. Hanley, P. J. Verveer, M. J. Gemkow, D. Arndt-Jovin, and T. M. Jovin, “An optical sectioning programmable array microscope implemented with a digital micromirror device,” J. Microsc., 196 317 –331 (1999). https://doi.org/10.1046/j.1365-2818.1999.00602.x 0022-2720 Google Scholar

28. 

T. Tanaami, S. Otsuki, N. Tomosada, Y. Kosugi, M. Shimizu, and H. Ishida, “High-speed 1-framems scanning confocal microscope with a microlens and Nipkow disks,” Appl. Opt., 41 (22), 4704 –4708 (2002). https://doi.org/10.1364/AO.41.004704 0003-6935 Google Scholar

29. 

M. A. A. Neil, R. Juskaitis, and T. Wilson, “Method of obtaining optical sectioning by using structured light in a conventional microscope,” Opt. Lett., 22 (24), 1905 –1907 (1997). https://doi.org/10.1364/OL.22.001905 0146-9592 Google Scholar

30. 

D. Karadaglic and T. Wilson, “Image formation in structured illumination wide-field fluorescence microscopy,” Micron, 39 (7), 808 –818 (2008). https://doi.org/10.1016/j.micron.2008.01.017 0968-4328 Google Scholar

31. 

J. Mellentin-Michelotti, L. T. Evangelista, E. E. Swartzman, S. J. Miraglia, W. E. Werner, and P. M. Yuan, “Determination of ligand binding affinities for endogenous seven-transmembrane receptors using fluorometric microvolume assay technology,” Anal. Biochem., 272 (2), 182 –190 (1999). https://doi.org/10.1006/abio.1999.4175 0003-2697 Google Scholar

32. 

N. Komatsu, S. Shichijo, Y. Maeda, and K. Itoh, “Measurement of interferon-gamma by high-throughput fluorometric microvolume assay technology system,” J. Immunol. Methods, 263 (1–2), 169 –176 (2002). https://doi.org/10.1016/S0022-1759(02)00037-6 0022-1759 Google Scholar

33. 

P. Zuck, Z. G. Lao, S. Skwish, J. F. Glickman, K. Yang, J. Burbaum, and J. Inglese, “Ligand-receptor binding measured by laser-scanning imaging,” Proc. Natl. Acad. Sci. U.S.A., 96 (20), 11122 –11127 (1999). https://doi.org/10.1073/pnas.96.20.11122 0027-8424 Google Scholar

34. 

R. P. Ekins and F. W. Chu, “Multianalyte microspot immunoassay—microanalytical compact-disk of the future,” Clin. Chem., 37 (11), 1955 –1967 (1991). 0009-9147 Google Scholar

35. 

L. J. Dietz, R. S. Dubrow, B. S. Manian, and N. L. Sizto, “Volumetric capillary cytometry: a new method for absolute cell enumeration,” Cytometry, 23 (3), 177 –186 (1996). https://doi.org/10.1002/(SICI)1097-0320(19960301)23:3<177::AID-CYTO1>3.0.CO;2-G 0196-4763 Google Scholar

36. 

T. Bacarese-Hamilton, L. Mezzasoma, A. Ardizzoni, F. Bistoni, and A. Crisanti, “Serodiagnosis of infectious diseases with antigen microarrays,” J. Appl. Microbiol., 96 (1), 10 –17 (2004). https://doi.org/10.1046/j.1365-2672.2003.02111.x 1364-5072 Google Scholar

37. 

B. Q. Sun, W. Z. Xie, G. S. Yi, D. P. Chen, Y. X. Zhou, and J. Cheng, “Microminiaturized immunoassays using quantum dots as fluorescent label by laser confocal scanning fluorescence detection,” J. Immunol. Methods, 249 (1–2), 85 –89 (2001). https://doi.org/10.1016/S0022-1759(00)00331-8 0022-1759 Google Scholar

38. 

M. Schaferling and S. Nagl, “Optical technologies for the read out and quality control of DNA and protein microarrays,” Anal. Bioanal. Chem., 385 (3), 500 –517 (2006). https://doi.org/10.1007/s00216-006-0317-5 1618-2642 Google Scholar

39. 

P. Hanninen, A. Soini, N. Meltola, J. Soini, J. Soukka, and E. Soini, “A new microvolume technique for bioaffinity assays using two-photon excitation,” Nat. Biotechnol., 18 (5), 548 –550 (2000). https://doi.org/10.1038/75421 1087-0156 Google Scholar

40. 

M. E. Waris, N. J. Meltola, J. T. Soini, E. Soini, O. J. Peltola, and P. E. Hanninen, “Two-photon excitation fluorometric measurement of homogeneous microparticle immunoassay for C-reactive protein,” Anal. Biochem., 309 (1), 67 –74 (2002). https://doi.org/10.1016/S0003-2697(02)00256-7 0003-2697 Google Scholar

41. 

J. O. Koskinen, J. Vaarnor, R. Vainionpaa, and A. E. Soini, “A novel separation-free assay technique for serum antibodies using antibody bridging assay principle and two-photon excitation fluorometry,” Clin. Chim. Acta, 355 S142 –S142 (2005). 0009-8981 Google Scholar

42. 

J. O. Koskinen, R. Vainionpää, N. J. Meltola, J. Soukka, P. E. Hänninen, and A. E. Soini, “Rapid method for the detection of influenza A and B virus antigens using TPX assay technique and dry-chemistry reagents,” J. Clin. Microbiol., 45 3581 –3588 (2007). https://doi.org/10.1128/JCM.00128-07 0095-1137 Google Scholar

43. 

E. Cunningham and C. J. Campbell, “A novel self-assembled nanoparticulate film for covalent attachment of antibodies to plastic,” Langmuir, 19 (10), 4509 –4511 (2003). https://doi.org/10.1021/la026826r 0743-7463 Google Scholar

44. 

K. Wadu-Mesthrige, N. A. Amro, J. C. Garno, S. Xu, and G. Y. Liu, “Fabrication of nanometer-sized protein patterns using atomic force microscopy and selective immobilization,” Biophys. J., 80 (4), 1891 –1899 (2001). https://doi.org/10.1016/S0006-3495(01)76158-9 0006-3495 Google Scholar

45. 

F. R. F. Fan and A. J. Bard, “Imaging of biological macromolecules on mica in humid air by scanning electrochemical microscopy,” Proc. Natl. Acad. Sci. U.S.A., 96 (25), 14222 –14227 (1999). https://doi.org/10.1073/pnas.96.25.14222 0027-8424 Google Scholar

46. 

G. Donnert, J. Keller, R. Medda, M. A. Andrei, S. O. Rizzoli, R. Lurmann, R. Jahn, C. Eggeling, and S. W. Hell, “Macromolecular-scale resolution in biological fluorescence microscopy,” Proc. Natl. Acad. Sci. U.S.A., 103 (31), 11440 –11445 (2006). https://doi.org/10.1073/pnas.0604965103 0027-8424 Google Scholar

47. 

H. T. M. Vandervoort and G. J. Brakenhoff, “3-D image-formation in high-aperture fluorescence confocal microscopy—a numerical-analysis,” J. Microsc., 158 43 –54 (1990). 0022-2720 Google Scholar

48. 

C. S. Lee, S. H. Lee, Y. G. Kim, J. H. Lee, Y. K. Kim, and B. G. Kim, “A method of binding kinetics of a ligand to micropatterned proteins on a microfluidic chip,” Biosens. Bioelectron., 22 (6), 891 –898 (2007). https://doi.org/10.1016/j.bios.2006.03.020 0956-5663 Google Scholar

49. 

A. P. G. A. W. Adamson, Physical Chemistry of Surfaces, Wiley, New York (1997). Google Scholar

50. 

E. J. Billo, Excel for Chemists a Comprehensive Guide, Wiley-VCY, New York (2001). Google Scholar

51. 

R. M. Zucker, “Evaluation of confocal microscopy system performance,” Methods Mol. Biol., 319 77 –135 (2006). https://doi.org/10.1007/978-1-59259-993-6_5 1064-3745 Google Scholar

52. 

R. M. Zucker, “Quality assessment of confocal microscopy slide based systems: performance,” Cytometry, 69A (7), 659 –676 (2006). https://doi.org/10.1002/cyto.a.20314 0196-4763 Google Scholar

53. 

J. B. E. Pawley, Handbook of Biological Confocal Microscopy, Springer, New York (2006). Google Scholar

54. 

J. S. Martinez, W. K. Grace, K. M. Grace, N. Hartman, and B. I. Swanson, “Pathogen detection using single mode planar optical waveguides,” J. Mater. Chem., 15 (43), 4639 –4647 (2005). https://doi.org/10.1039/b502329g 0959-9428 Google Scholar

55. 

M. Pawlak, E. Schick, M. A. Bopp, M. J. Schneider, P. Oroszlan, and M. Ehrat, “Zeptosens’ protein microarrays: a novel high performance microarray platform for low abundance protein analysis,” Proteomics, 2 (4), 383 –393 (2002). https://doi.org/10.1002/1615-9861(200204)2:4<383::AID-PROT383>3.0.CO;2-E 1615-9853 Google Scholar

56. 

M. Seydack, “Nanoparticle labels in immunosensing using optical detection methods,” Biosens. Bioelectron., 20 (12), 2454 –2469 (2005). https://doi.org/10.1016/j.bios.2004.11.003 0956-5663 Google Scholar

57. 

L. Prix, P. Uciechowski, B. Bockmann, M. Giesing, and A. J. Schuetz, “Diagnostic biochip array for fast and sensitive detection of K-ras mutations in stool,” Clin. Chem., 48 (3), 428 –435 (2002). 0009-9147 Google Scholar

58. 

V. Souplet, R. Desmet, and O. Melnyk, “Imaging of protein layers with an optical microscope for the characterization of peptide microarrays,” J. Pept. Sci., 13 (7), 451 –457 (2007). https://doi.org/10.1002/psc.866 1075-2617 Google Scholar

59. 

Q. Gu, T. M. Sivanandam, and C. A. Kim, “Signal stability of Cy3 and Cy5 on antibody microarrays,” Proteome. Sci., 4 21 (2006). https://doi.org/10.1186/1477-5956-4-21 Google Scholar

60. 

P. Hanninen, M. Waris, M. Kettunen, and E. Soini, “Reaction kinetics of a two-photon excitation microparticle based immunoassay-from modelling to practice,” Biophys. Chem., 105 (1), 23 –28 (2003). https://doi.org/10.1016/S0301-4622(03)00042-5 0301-4622 Google Scholar
©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)
Homanaz Ghafari, Yanzhou Zhou, Selman Ali, and Quentin S. Hanley "Confocal detection of planar homogeneous and heterogeneous immunosorbent assays," Journal of Biomedical Optics 14(6), 064022 (1 November 2009). https://doi.org/10.1117/1.3268772
Published: 1 November 2009
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KEYWORDS
Confocal microscopy

Thin films

Microscopes

Glasses

Luminescence

Systems modeling

Point spread functions

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