Anal. Chem. 2003, 75, 1147-1154
Imaging and Analysis of Immobilized Particle Arrays Priscilla Wilkins Stevens and David M. Kelso*
Department of Biomedical Engineering, Robert R. McCormick School of Engineering and Applied Science, Northwestern University, 2145 Sheridan Road, Evanston, Illinois 60208-3107
An automated imaging system was developed to quantify fluorescence signals from particles immobilized on hydrogel-coated slides. Arrays of submicrometer-diameter particles were printed with up to 600 particles/spot. The slides were read under 20× magnification without cover slips. Software was written to image individual spots and measure the median particle fluorescence in each spot. To locate array spots, an alignment program made use of two fiducial grids of fluorescent reference particles at either end of the slide. Focusing was adjusted locally using spots of reference particles located at the centers of focusing neighborhoods. The response was linear across a two-decade range, and the precision of readings was better than 5% down to ∼1000 fluors/particle. Exposure times varied with signal intensity, reaching 1 s at the lowest levels of fluorescence. Data demonstrate feasibility for measuring fluorescence from immobilized particle arrays on an automated microscope with accuracy and precision similar to fluorescence measurements of microparticles with a flow cytometer. This work provides automation of imaging and analysis procedures necessary for development of immobilized particle arrays as an analytical platform that combines advantageous features of both planar and suspension arrays. The preceding paper introduced immobilized particle array (IPA) technology, an innovative array platform that combines aspects of planar-array and suspension-array formats.1 With this new hybrid technology, reagent-coated microparticles serve as capture zones in spots arrayed on a thin film applied to a planar surface. A single array spot thus contains a large number of particles, each of which provides replicate assay data concerning binding of the capture reagent’s specific target. To actualize the potential benefits of IPAs, specialized focusing, imaging, and measuring protocols are required. Whereas standard array readers consider each spot a single assay, IPAs conduct assays at the level of microparticles. Reading these arrays requires automated procedures for high-quality imaging of each arrayed spot, the ability to locate particles within the spot, accurate measurement of each particle’s signal, and an appropriate means for recording and analyzing the data. * To whom correspondence should be addressed. Phone: 847-467-2167. Fax: 847-491-4928. E-mail:
[email protected]. (1) Wilkins Stevens, P.; Wang, C. H. J.; Kelso, D. M. Anal. Chem. 2003, 75, 1141-1146. 10.1021/ac0205816 CCC: $25.00 Published on Web 01/30/2003
© 2003 American Chemical Society
Imaging microparticles in the spots of an IPA is a task in some respects similar to analysis of fluorescently labeled cells by laser scanning cytometry (LSC)2 or analysis of cell- or bead-based assays by fluorometric microvolume assay technology (FMAT).3,4 In each case, fluorescence is measured for individual cells or beads on a planar surface. LSC is specialized for applications involving whole cells and utilizes a scatter sensor to define the locations of cells on the slide. FMAT images either cells or 6-8-µm-diameter particles in microwell assay plates. With each of these technologies, the objects imaged are much larger than the submicrometer particles employed in an IPA. Thus, higher resolution and more sensitive imaging and analysis procedures were required to automate data collection for this new type of array. This paper describes automated instrumentation, software routines, and data analysis protocols developed especially for IPAs. These procedures were designed particularly for analysis of IPAs where all microparticles within an array spot are coated with the same capture probe. Protein-coated microparticles comprised the IPAs described herein, but the imaging and data handling methodologies specified are appropriate for analysis of IPAs incorporating other types of reagent-coated microparticles. EXPERIMENTAL SECTION Materials and Methods. A Lovins Micro-Slide Field Finder from Teledyne Gurley (Troy, NY) was used in the stage calibration routines. Alexa-546-labeled biocytin was purchased from Molecular Probes (Eugene, OR). Slides, particles, buffers, and other reagents were previously described, as were procedures for preparing reference particles.1 In the current paper, however, the spotting buffer was CTEG buffer, prepared with 4 parts CT buffer and 1 part ethylene glycol. Methods for printing IPAs with a TeleChem SMP4 microspotting pin on a SpotBot arrayer are also specified in the previous paper.1 For studies in the current paper, however, arrays were not printed with assay particles but with either fluorescently labeled reference particles or fluorescence intensity particle standards. Analyses of variance and significance were conducted with standard statistical techniques.5 Fluorescence Intensity Particle Standards. Two series of sequential 1:2 dilutions of Alexa-546-labeled biocytin were prepared (2) Kamentsky, L. A. Methods Cell Biol. 2001, 63, 51-87. (3) Swartzman, E. E.; Miraglia, S. J.; Mellentin-Michelotti, J.; Evangelista, L.; Yuan, P.-M. Anal. Biochem. 1999, 271, 143-151. (4) Mellentin-Michelotti, J.; Evangelista, L. T.; Swartzman, E. E.; Miraglia, S. J.; Werner, W. E.; Yuan, P.-M. Anal. Biochem. 1999, 272, 182-190. (5) Box, G. E. P.; Hunter, W. G.; Hunter, J. S. Statistics for Experimenters; John Wiley & Sons: New York, 1978.
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in TBST buffer, one series containing six dilutions from 1.5 × 10-7 to 4.8 × 10-9 M and the other series containing seven dilutions from 2.4 × 10-9 to 3.8 × 10-11 M. For each of these 13 dilutions, particle standards of different fluorescence intensities were prepared by incubating 0.4 mL of diluted Alexa-546-labeled biocytin with a 0.5-mL suspension of 3 × 107 0.8-µm-diameter streptavidin-coated particles in TBST. With the most concentrated dilution, the incubation mix contained 1.2 × 106 molecules of Alexa-546-labeled biocytin for each particle, i.e., ∼9-fold more than the particle’s capacity. In the least concentrated mix, however, there were only ∼300 molecules/particle, i.e., enough to cover ∼0.25% of the particle’s available sites. After a 10-h incubation with continual rotation at room temperature, particles were pelleted, washed once with TBST and once with CTEG buffer, and then resuspended in CTEG at a final concentration of 1.0 × 106 particles/µL. Prior to array printing, the final suspension was sonicated 1 min at 18 W in a Misonix cup horn sonicator (Misonix, Inc., Farmingdale, NY). To compare IPA technology with flow cytometry, another series of particle standards was prepared in a similar manner except that there were 6 × 107 particles/tube and 20 concentrations of Alexa-546-labeled biocytin ranging from 1.0 × 10-6 to 1.9 × 10-12 M. Imaging System. A computer-controlled imaging system was assembled from a motorized epifluorescence microscope, cooled charge-coupled device (CCD) camera, and personal computer workstation. The microscope, a Zeiss Axiovert 135M, was equipped with an AttoArc 100-W mercury arc lamp (Carl Zeiss Microimaging, Inc., Thornwood, NY), Chroma Technology (Brattleboro, VT) high-Q interference filters, a Ludl Electronic Products (Hawthorne, NY) MAC 2000 motor controller and joystick, and a stepper motor-driven filter wheel/shutter, XY stage, and Z focusing, all also from Ludl Electronic Products. Connected though a prism slid between the objective turret and the binocular eyepiece, the QImaging (Burnaby, BC, Canada) Retiga 1350 EX cooled CCD digital camera was equipped with a 1392 × 1040 chip with a 6.45µm pixel size and on-chip binning up to 4 × 4. It had a 12-bit A/D converter, low dark current, and over 50% quantum efficiency in the visible range. All images were acquired with a Zeiss Fluar 20×/0.75 NA objective and Cy3 filter set. The motor controller and QImaging camera were interfaced to a Dell Pentium 4 workstation running Microsoft Windows 2000 Professional. Custom software was written in Microsoft Visual Basic version 6.0, and Image-Pro Plus version 4.5 (Media Cybernetics, Silver Spring, MD) was used for image acquisition and analysis. Imaging Software. Device control software modules were written to interface with the motors and camera. Device handlers for the motors communicated with the MAC 2000 controller using an RS-232 serial communications protocol. The camera device handler called Dynamic Link Library (DLL) routines included in the Image-Pro Plus software, which used a FireWire communication protocol to set binning, exposure time, region of interest, and other operational parameters. Higher-level routines were written for stage calibration, autofocusing, autoalignment, and array scanning.6 Forms were created (6) Russ, J. C. Imaging Processing Handbook, 3rd ed.; CRC Press: Boca Raton, FL, 1999.
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to input setup parameters, control processing, and display run time information. Input parameters included magnification and numerical aperture of the objective, emission filter center wavelength, camera binning and exposure time, alignment and locations of focusing neighborhoods, number and spacing of spots, and diameters of reference and assay particles. These settings, along with status, timing, and positional information from each run, were recorded in an Excel workbook, which served as a scan record for the slide. Autofocusing and autoalignment programs, written to correct for variations in slide geometry and spot locations, imaged spots containing the reference particles described above. For alignment, a 5 × 5 grid of fiducial spots of reference particles was printed at each end of the slide. For focusing, a single focusing spot of reference particles was printed in the center of each focusing neighborhood. Stage Calibration. A stage calibration program was written to convert the array printer’s program-specified locations, defined in millimeters from the slide’s reference corner, into microscope stepper motor coordinates, defined as 5 steps/µm for the X and Y axes and as 10 steps/µm for the Z axis. A field finder slide was used to determine the slide corner and to focus the objective on the surface of the slide. Setup included viewing a live video image of the field finder slide shown through the preview function of the camera driver and utilizing a joystick to focus and move to a predefined grid in the field finder. Clicking a control button on the calibration form captured the setup coordinates. Autofocusing. Focusing routines did not attempt to find objects, but instead relied entirely on analyses of the distribution of pixel intensities. With a Fibonacci search,7 the autofocusing program found the Z position that maximized the normalized contrast, defined as the standard deviation (SD) of pixel intensities divided by the mean of these intensities. As the algorithm approached the maximum response, it called upon a quadratic interpolating function to produce a more precise estimate of the focal plane position. Autoalignment. The purpose of alignment routines was to accurately locate spot centers so there would be only one image acquired per spot. The calibration program’s initial setup with the field finder slide, described above, provided an initial estimate that was close enough to move inside the first fiducial group. The autoalignment program then adjusted coordinate translation parameters by finding the corners of the two fiducial groups. After the autofocusing program brought the fiducial spots into sharp focus, the autoalignment program found the center of one of the spots. A center-of-mass location routine estimated the spot center by dilating particles to essentially cover the entire spot, creating a solid disk whose edges were utilized to identify the spot center. The amount of dilation was determined by the average distance between objects in the spot. Only a fraction of the disk had to be in the field of view to obtain a good estimate of the spot center. After locating the center of a spot in the fiducial group, the program then moved in the X and Y directions until it located the corner spot of the fiducial group’s 5 × 5 grid. With the first fiducial group, the program was able to adjust the offset to the origin, while the second fiducial group allowed the program to estimate the angle between the axes of the slide and the stage. (7) Krotkov, E. Int. J. Comput. Vision 1987, 1, 223-237.
After determining slide coordinates, the autoalignment program moved to the central spot of each focusing neighborhood, located its center with the center-of-mass location routine, and determined the local focal plane using the autofocus program to bring the reference particles in this focusing spot into precise focus. The optimal Z value determined for the focusing spot was then utilized to focus every spot in that focusing neighborhood. Most focusing neighborhoods were 3 × 3 grids of spots, but 5 × 5 and 9 × 9 grids were utilized occasionally. Imaging Spots in the Focusing Neighborhoods. The spot scanning program moved to the coordinates of each spot in the focusing neighborhood, opened the shutter, and captured an image of that spot. This procedure enabled accurate localized focusing while protecting assay spots from undue exposure to the excitation light prior to image capture. Image files for each array spot were saved in a software folder created for the slide. Names of the image files, along with spot location, camera settings, and microscope settings utilized for image acquisition, were recorded in the scan record workbook, which was stored in the same folder as the image files. Image Analysis. An analysis program written to postprocess the image data and determine intensities of the particles imaged within each spot called Image-Pro DLL routines to enable measurements, set ranges, and count objects. To identify objects within an imaged spot, the program first located all pixels in the image whose intensity was greater than a preset threshold value. Adjacent pixels exceeding the threshold value were grouped together and considered a single object. For each spot image, the threshold value was set empirically by a search algorithm that tested as potential threshold values 19 intensities evenly spaced between the intensity value of the spot background8 and the intensity value of the brightest pixel in the image. For each potential threshold value, the algorithm determined the number of objects in the image where the object had size and shape parameters within the ranges defined below. The intensity value selected as the threshold was the value that resulted in identification of the maximum number of objects. Particle diameter and roundness were the parameters by which potential objects were filtered for appropriate size and shape. The particle diameter in pixels was calculated from particle diameter in micrometers, magnification, pixel size in micrometers, and binning. The mean diameter, i.e., the average length of diameters measured at 2° intervals passing through the centroid, was measured for each potential object. For an object to be considered appropriately sized, its mean diameter had to fall within the range from one particle diameter up to 3 times the particle diameter. Objects whose mean diameters fell outside this range were excluded. An object’s roundness quotient (R) was based on its perimeter (p) and area (a) according to the following equation: R ) p2/(4πa). For a perfect circle, R ) 1. An object with 0.9 < R < 1.1 was considered acceptable; objects whose roundness quotients fell outside this range were excluded. RESULTS AND DISCUSSION Alignment Precision. To minimize the time to read an array, images are acquired only when there is a spot centered in the (8) The background intensity is defined as the mode of the pixel intensity distribution plus twice the full width at half-maximum.
field of view. To determine spot locations, two fiducial groups of reference particles are printed at either end of the slide. After the corner of each fiducial group is located by a search algorithm, plane geometry is used to calculate the locations of all other spots in the array. To test these procedures, an IPA was prepared with 48 3 × 3 grids of spots printed in CTEG buffer on an aldehyde hydrogel slide. Each grid was a focusing neighborhood where the central spot was a focusing spot containing ∼600 reference particles. Differences between the expected locations of focusing spot centers calculated from fiducial group data and the locations of these spot centers estimated based on the center-of-mass location routine were calculated for the 48 focusing spots. Along the X axis, the mean difference was 46 µm, and the mean difference along the Y axis was 10 µm. Both values represent only a small fraction of the spot diameter. The larger error in the X axis is probably due to the precision of the SpotBot printer, where X axis movement involves the entire gantry assembly, while along the Y axis, only the print head moves.9 Spot Diameters. In the array described above, spot diameters for each of the 48 focusing spots were estimated by calculating the smallest circle that contained all the reference particles identified in that spot. A calibration factor of 0.322 µm/pixel was determined by imaging a micrometer reticle and counting pixels between bars with the Image-Pro measurement tool. Mean spot diameter was 225 ( 10 µm. Reported spot diameters for the SMP4 spotting pin are 120-130 µm for spots printed on standard aldehyde slides with commercially prepared DNA spotting buffers.10 Since spot size generally increases with substrate wettability and viscosity of the spotting solution,11 the larger spot diameters measured for IPA spots are most likely due to both the hydrogel substrate and the physical properties of the CTEG printing solution. Although we have not conducted an extensive evaluation of spot size on various slide surfaces, we have observed that spots printed on epoxy-activated hydrogel slides with CTEG buffer are ∼20% smaller than when printed on aldehyde-activated hydrogel slides. Autofocusing. The high magnification and numerical aperture of our optics makes the response very sensitive to focusing. To minimize errors due to variations in distance between the objective and the immobilized particles, a focusing spot containing fluorescent reference particles is placed in the center of a neighborhood of assay spots. The intense points of luminescence, which ideally are less than three pixels in diameter, facilitate the search for an optimum distance that is then used for all surrounding assay spots in the neighborhood. Figure 1A shows a typical autofocused, false-color image of reference particles. The distribution of pixel intensities is shown in Figure 1B. Pixels in the regions outside the spot, colored blue, are the most frequent and are represented in the first peak on the histogram. The second highest peak is from the interior of the spot, which appears light blue and green in the image. The higher intensity of the background inside the spot is most likely due to the point spread function of (9) Following this study, the manufacturer recommended changing SpotBot acceleration speed and parameters, which significantly reduced positioning errors. (10) http://arrayit.com/Products/Printing/Stealth/stealth.html. (11) Smith, J. T.; Viglianti, B. L.; Reichert, W. M. Langmuir 2002, 18, 62896293.
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Figure 2. Focusing of reference particles in the central spot of a focusing neighborhood by maximizing the normalized contrast. Negative objective distance is within the glass of the slide; positive distance is above the surface of the slide.
Figure 1. (A) Autofocused, false-color image of reference particles in a fiducial spot. The highest intensity objects, shown in red, are microparticles. In the background outside the spot, the lowest intensity pixels are blue. (B) Histogram plotting the number of pixels in the image in (A) registering each intensity.
the optical system, where, because of imperfections in the lenses and focusing, photons emitted from a point on the slide are spread over several pixels on the camera. The photons collected by the camera have a Gaussian distribution, which results in pixels just outside the particle boundary appearing brighter than background outside the spot. Since the entire slide is blocked after spotting, there is nothing to suggest nonspecific binding would be different in these two regions. The pixels in the right tail of the histogram represent the fluorescent particles, which appear red in the image. As the image comes into focus, both the number of pixels in the tail and the variance of the distribution increase. Typically, less than 0.5% of the pixels in the image are associated with fluorescent particles. The outside background accounts for 70-75% of the pixels and the interior background for 25-30%. 1150 Analytical Chemistry, Vol. 75, No. 5, March 1, 2003
As shown in Figure 2, the focusing function peaks sharply. A Fibonacci algorithm7 searches an interval of 40 µm on either side of the initial focal plane, and if the maximum occurs near the edge of the region, the algorithm repeats the search using an interval of 40 µm on either side of the new estimate. The response curve is asymmetric, decreasing much more rapidly as the objective moves away from the slide. The algorithm calculates the final estimate from a quadratic fit of points nearest the maximum response. Several alternative focusing functions were tested, but none gave better performance than this simple variance calculation.12,13 Binning. Tradeoffs between resolution and sensitivity can be made by changing the binning, which electronically combines pixels. For images of reference particles in fiducial spots or focusing spots, 1 × 1 binning was applied to maximize resolution. With 1 × 1 binning, a 1280 × 1024 image contains 1 310 720 pixels, and a 0.8-µm-diameter particle has an average area of ∼4.8 pixels. A spot, typically ∼225 µm in diameter, contains ∼382 000 pixels, or ∼29% of the total pixels in the image. From 200 particles in a spot, 1200 bright pixels would be expected with 1 × 1 binning, but spreading of the fluorescence intensity due to imperfections in the optics generally resulted in a ∼4-fold higher number of bright pixels being registered. To enhance sensitivity, 2 × 2 binning was applied for images of spots containing assay particles. With 2 × 2 binning, an image contains 327 680 pixels, with each 0.8-µm-diameter particle having an average area of ∼1.2 pixels. Figure 3 shows two images of the same four particles. In one image (A), 1 × 1 binning was applied, while 2 × 2 binning was applied in the other image (B). Particle Identification. To identify particles, each pixel must first be classified as either signal or background. A threshold level is used to divide intensities into these two classes. A sequence of trial thresholds, spanning the range of observed intensities, is applied to the image, and contiguous signal pixels are identified as candidate particles. By using a priori criteria about particle size and shape, the nonconforming objects are filtered out. The spot’s threshold is set at the value that maximizes the number of objects conforming to the shape and size criteria. Figure 4 shows an example of the analysis program searching the interval between the intensity of the spot background and the (12) Firestone, L.; Cook, K.; Culp, K.; Talsania, N.; Preston, K., Jr. Cytometry 1991, 12, 195-206. (13) Groen, F. C.; Young, I. T.; Ligthart, G. Cytometry 1985, 6, 81-91.
Figure 3. Autofocused, false-color image of four immobilized particles. The highest intensity pixels are red, while pixels registering the lowest intensity are blue. (A) Particles imaged with 1 × 1 binning. (B) Same particles imaged with 2 × 2 binning. Table 1. Effect of Number of Particles per Spot on Readings of MPF (Counts)a dilution of stock
Nb
MPFc
% CV
1:64 1:32 1:16 1:8 1:4 1:2
19 ( 4 35 ( 6 82 ( 12 156 ( 17 289 ( 32 610 ( 61
887 ( 90 918 ( 88 984 ( 48 1033 ( 39 1105 ( 32 1139 ( 45
10.1 9.6 4.9 3.8 2.9 4.0
a For each dilution, a total of 64 spots were read, i.e., all but the center spots from eight 3×3 grids of spots. b N, number of particles/ spot, reported as mean ( SE. c MPF, median particle fluorescence, i.e., median fluorescence intensity of particles in spot, reported as mean ( SE of the median.
Figure 4. Setting the object intensity threshold. The object intensity threshold is based on object analysis at 19 different test thresholds between the background intensity and the maximal pixel intensity. In this example, the spot contained reference particles in a fiducial spot. For this image, analyzed with 1 × 1 binning, the threshold was set at ∼700 counts, the intensity where the maximum number of objects was defined.
intensity of the maximum pixel in the spot to set an appropriate threshold for object intensity. Adjacent pixels whose intensities were greater than the threshold value were considered an object. At the higher thresholds, only the centermost pixels are included, so some potential objects are not counted because they are smaller than the minimum diameter. As the threshold is lowered, the count increases because more of the pixels in each object are above the limit, and thus, the mean diameter of the object increases. At the lower thresholds, however, particles bleed together and the number of objects decreases because mean diameters exceed the upper limit. Once the threshold value for a spot was determined, particle diameter and particle roundness criteria were applied to eliminate objects that represented clumps of more than ∼3-4 particles. For each object that passed the size and shape criteria, the program recorded the object’s maximal pixel intensity. This set of maximal intensities was considered the intensities of the particles within the imaged spot, even though in some cases the intensity recorded
was the maximal pixel intensity not of a single particle but of a cluster containing a small number of particles. Particle Number Effects. To investigate how the number of particles per spot affects the imaging process, six 2-fold dilutions, from 1:2 to 1:64, were prepared by sequential dilution of the reference particle stock solution in CTEG buffer, and an IPA was printed with these particle dilutions. The array contained six rows, each printed from a different dilution of reference particles, with eight replicate 3 × 3 grids in each row. The slide was blocked, rinsed, dried, and then analyzed by the automated focusing, imaging, and analysis routines described in the Experimental Section. For each spot, the median particle fluorescence (MPF) characterized the distribution of particle intensities within that spot. Coefficients of variation (CVs) for distributions of withinspot particle intensities were fairly consistent, regardless of the number of particles printed per spot. For the six dilutions, from least to most concentrated, these CVs were 18, 17, 15, 15, 16, and 16%, respectively. As shown in the within-group data in Table 1, the number of particles per spot did affect both the mean and variance of the distribution of MPF values measured for the 64 spots printed with the same dilution. The increase in mean fluorescence with particle number is most likely due to the point spread function of the Analytical Chemistry, Vol. 75, No. 5, March 1, 2003
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Table 2. Analysis of Multiple Reads of a Single 3 × 3 Grid of Replicate Spots of Reference Particlesa binning exposure (ms) particle fluorescence MPFb (counts) % CV photobleaching counts/s %/s
1×1
2×2
40
10
1267 ( 22 1.76
899 ( 17 1.85
-7.5 -0.59
-8.45 -0.94
a The eight spots on the exterior of a 3 × 3 grid were read 16 times with 2 × 2 binning and then 16 times with 1 × 1 binning, with the same focus setting used for all reads. b MPF, median particle fluorescence for a spot, reported as mean of the medians of 128 reads (8 spots × 16 reads/spot) ( SE of the median adjusted for difference between spots and between reads.
Figure 5. MPF values for spots containing particle standards coated with Alexa-546-labeled biocytin at various fluor/particle ratios. For each dilution, 32 spots were imaged. For each of the imaged spots, the median of that spot’s distribution of particle intensities is plotted with a plus sign.
optical system, which causes photons from one particle to be added to those of nearby particles. Since when there are more particles per spot, the particles are closer together, this effect increases with particle number. For most IPA applications, this effect will not be problematic, since similar numbers of assay particles will be printed in each assay spot. For the most sparsely populated spots, with average particle counts of 19 and 35, CVs were ∼10%. As the number of particles per spot increased, however, CVs fell to 3% for spots with an average of 289 particles/spot. The slightly higher CVs for the most densely populated spots, with an average of 610 particles/spot, are most likely attributable to the combined effect of the point spread function and the analysis algorithm’s method of locating objects. Printing ∼80-600 particles/spot, therefore, results in optimal readings of particle fluorescence intensity. Dynamic Range. To investigate how particle intensity affects the imaging process, an IPA was printed with four replicate 3 × 3 grids for each of 13 fluorescence intensity particle standards. After printing, blocking, washing, and drying, the slide was then imaged and analyzed according to the automated routines specified in the Experimental Section. Exposure times were 20 ms for the three most intensely fluorescent standards and 1 s for the three dimmest standards, with progressively longer exposure times for the seven standards between: 50 ms for two standards; 100 ms for two standards; and 200, 250, and 500 ms for one standard each. Spots contained an average of 130 particles/spot, and 32 spots were measured for each standard. For all spots of the fluorescence intensity particle standards, Figure 5 plots the MPF values, reported as counts per millisecond. CVs ranged from 2.5% for the highest intensity particle standards down to 5% for the least intense particle standards. As configured for this experiment, the dynamic range of the IPA imaging system is two decades, from 1000 to 100 000 fluors/ particle. The detection limit is ∼1000 fluors/particle. However, the lower limit could potentially be extended by increasing exposure times beyond 1 s or by binning more than 2 × 2 pixels. The upper limit could be extended by employing larger particles with greater capacities. An immobilized 0.8-µm-diameter strepta1152 Analytical Chemistry, Vol. 75, No. 5, March 1, 2003
vidin-coated particle can bind 105 labeled biocytins before the response plateaus. A 3.2-µm-diameter particle would have 16 times the surface area, which should increase the dynamic range to more than three decades. Imaging Error Analysis. Imaging errors can be partitioned into three general categories: (1) between images/within spot; (2) between spots/within group; and (3) between groups/within slide. The first category, within-spot errors, could be due to real differences between particles, nonuniformity of lamp illumination, lamp flicker, noise in the CCD detector, or errors in the analysis algorithm. The cumulative effect of these errors would be reflected in the standard error (SE) of the median intensities of multiple images of a single spot. The second category, between-spot errors, also includes effects due to position of the spot in the field of view and variability in the surface of the slide. In the third category, between-group errors, focusing errors are also included. Within- and Between-Spot Imaging Errors. As discussed in the experiment addressing optimal particle number above (see Table 1), CVs for the distribution of particle intensities within a single spot were typically 15-20%. For each spot, results are reported as the MPF. Increasing the number of particles per spot thus tends to reduce the variability of the medians (see Table 1). The SD of the distribution of particle intensities within a spot is also affected by binning and exposure time. Low-intensity spots require larger binning and longer exposure times to achieve similar precision. Binning was the same for all readings on a slide, but exposure times were adjusted depending on the intensity of the signal. SEs of the median for replicate reads of a single spot (withinspot errors) and for reads of replicate spots in the same grid (between-spot errors) are also of interest. With a uniform focus setting, a 3 × 3 grid of spots printed with a 1:4 dilution of reference particles was read 16 times with 2 × 2 binning and then 16 times with 1 × 1 binning. Images were collected one per spot from each of the eight spots in an ordered sequence, and this process was repeated for each of the 16 reads with each binning. Exposure times, 10 and 40 ms, respectively, were adjusted to obtain fluorescence intensities of ∼1000 counts with 2 × 2 and 1 × 1 binning. Table 2 presents results of the analysis of variance, which demonstrates that there were significant differences (p < 10-6) in fluorescence intensities measured read to read for the same spot as well as spot to spot for a given focusing neighborhood.
Table 3. Effect of Localized Focusing on Readings of Particle Fluorescence Intensitya dilution of stock
SEb
Fc
pd
1:16 1:8 1:4
48 39 32
0.77 0.42 2.73
0.61 0.85 0.16
a For each dilution, a total of 64 spots was read. Each 3 × 3 grid was independently focused based on the grid’s central focusing spot. b SE, standard error of the median. c F, ratio of between-group to withingroup variance in particle fluorescence. d p, significance level.
These differences probably result from differences in the position of the particles relative to the illumination intensity. Particles will appear slightly more intense if the spot is precisely in the center of the field of view. Binning, however, did not affect the distribution of medians. CVs were less than 2% for both types of binning. Over the course of the experiment, photobleaching of the Cy3 fluor was measurable but limited to less than 1% per second of exposure. Due to delays in shutter opening and closing, the total exposure of a spot for each image is ∼1 s. Photobleaching has a minimal effect on the focusing function, since the contrast maximized by this function is normalized to mean pixel intensity. The SEs and CVs reported in Table 2 have been corrected for photobleaching effects. Within-Slide Imaging Errors. Autofocusing of the central spot in each 3 × 3 grid determined the position of the objective for reading all spots in the neighborhood. Within-slide imaging errors would arise from any differences among the replicate grids due to the localized focusing. Table 3 presents between-group analyses of the replicate 3 × 3 grids spotted with three dilutions of reference particles (see Table 1 for within-group analyses of these same grids). The analyses in Table 3 demonstrate that focusing did not significantly add to the variability of the readings. CVs from multiple 3 × 3 grids that were focused independently were no greater than CVs from within a single 3 × 3 grid, where the same focusing was applied to all spots in the grid. The data indicate that, at the 0.05 significance level, no significant variations in particle intensity were attributable to focusing. Correlation with Flow Cytometer. A series of 20 fluorescence intensity particle standards were prepared by incubating streptavidin-coated microparticles with dilutions of Alexa 546-biocytin. An IPA was prepared with one 3 × 3 grid printed for each particle standard. After the slide was blocked, rinsed, and dried, it was then analyzed with 2 × 2 binning and exposure times varying from 40 to 1000 ms, adjusted to keep measured intensities above ∼1000 counts. Aliquots of the same particle standards were diluted 1:100 in sheath fluid and read on a Luminex 100 flow cytometer with the PMT gain set at its maximum value of 1000. Figure 6 illustrates the excellent correlation (r ) 0.998) between readings (counts) of the standards by flow cytometry and readings (counts/ ms) of the standards printed on an IPA and analyzed by the automated focusing, imaging, and analysis routines developed for measurement of IPA particle fluorescence. The IPA readings were far more precise than the flow cytometer, whose population CVs ranged from 40 to 50% for the (14) Fulton, R. J.; McDade, R. L.; Smith, P. L.; Kienker, L. J.; Kettman, J. R., Jr. Clin. Chem. 1997, 43, 1749-1756.
Figure 6. Comparison of flow cytometry and IPA measurements. Plotted along the X axis for each dilution is the MPF (counts; N ) 10 000) measured by flow cytometry. The mean of MPF values (counts/ms) measured for eight IPA spots (N ) 90-250 particles/ spot) of that dilution is plotted according to the Y axis. Results are plotted only for the 16 lowest concentrations. Particles were saturated by the four most concentrated standards.
high-intensity standard and 80 to 100% for the low-intensity standards. For the correlation analysis, comparable precision was achieved by counting 10 000 particles in the flow cytometer. In that experiment, the SEs of the mean intensities were thus a factor of 100 smaller than the SDs of the population distributions. Since the flow cytometer optics were optimized for 6-µm-diameter particles, our submicrometer-diameter particles were well outside its design envelope.14 CONCLUSIONS These results demonstrate feasibility for reading slide-immobilized particles with precision comparable to flow cytometry, thus positioning the IPA as a viable array technology. With capture particles immobilized on hydrogel-coated slides, IPAs provide a hybrid analytical platform that combines advantageous features of both slide and suspension arrays. IPA technology should provide the potential for achieving the favorable capture rates and detection limits of suspension arrays while exhibiting the low nonspecific binding and high degree of multiplexing characteristic of planar arrays. With IPAs, it may even be possible to increase the level of multiplexing by printing mixtures of fluorescently coded particles in each array spot. The IPA imaging system is equivalent to conventional planar arrray scanners in terms of ease of operation. Fiducial groups of reference particles make possible automatic slide alignment, and partitioning the array into neighborhoods centered around a focusing spot of reference particles facilitates automatic focusing. Additionally, automated data analysis provides easily usable measurements similar to those obtained from slide scanners and flow cytometers. Although the time to read a slide is considerably longer at present, it may be shortened by using higher intensity sources and faster focusing mechanisms. It is likely that many fluorescence microscopes currently available in research laboratories can be upgraded in a similar manner. Analytical Chemistry, Vol. 75, No. 5, March 1, 2003
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ACKNOWLEDGMENT Dr. Steven Stroupe at Abbott Laboratories graciously permitted use of the Luminex 100 flow cytometer in his laboratory, and Dr. Jeff Wang of Spherotech, Inc. generously provided microparticles for these studies.
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Analytical Chemistry, Vol. 75, No. 5, March 1, 2003
Received for review September 17, 2002. Accepted December 17, 2002.
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