High-throughput microarray analyses require digitized images in order to convert the signal intensity to numerical values. To acquire the images, laser scanners are usually used for fluorescent signal detection. However, such microarray scanners have a limited number of excitation wavelengths, take minutes to scan a slide, and are expensive. In standard transcriptional array configurations, most study designs use relatively few samples against many probes, so only a small number of scans are necessary to complete the digital image acquisition for an experimental set. However, other microarray-based procedures may be more impacted by the limitations of dedicated microarray scanners. For instance, scanning is a major rate-limiting step when using high-density reverse-phase protein lysate microarrays (RPA) (Reference 1 and (Figure 1)A), which we have previously described as a method to perform proteomic profiling of many protein species across many samples. Because RPA signal detection employs a specific primary antibody followed by the catalyzed signal amplification colorimetric detection system (CSA; DakoCytomation, Carpinteria, CA, USA), whose final product is the dark-colored stain diaminobenzodine (DAB), signals can be obtained using the reflective mode of an ordinary optical flatbed scanner. Hence, we have been using optical flatbed scanners because of their fast scanning, relatively compact file size, and wide availability. However, there are several issues to be considered when using these scanners for quantitative applications.

Figure 1.

Ordinary optical flatbed scanners are generally designed for capturing photographs in digitized format. Specifications of each scanner model are often not clear enough for quantitative analyses based on the manufacturer's information. For the use in quantitative analyses, several scanning factors should be clarified. For instance, resolution, dynamic range, bit depth, light source, and the software A driver's characteristics can be important factors as any of them could influence the downstream analyses. It must be noted that digital data acquired from images are the product of all processes listed above, which are also characteristic of each scanner.

Since a scanner's specification information may be limited or unavailable, a calibrated material may be useful in estimating its performance (2,3). To examine dynamic range, bit depth, and most importantly, linearity in response to protein concentration, we used a wedge density strip (WDS; Danes-Picta, Praha, Czech Republic) including 20 calibrated reflective surfaces in each of 6×10 mm area, which can be mounted on a glass slide ((Figure 1)B). Raw pixel values of scanned images are converted into numerical values using the P-SCAN program (abs.cit.nih.gov/pscan) (1,4). Theoretically, the range of numerical values should be from 0 to 255 or 0 to 65,535 for 8- and 16-bit grayscale, respectively.

The WDS and RPAs were scanned with two ordinary flatbed scanners (Perfection 1250 and Perfection 4870; both from Epson, Long Beach, CA, USA). The scanning parameters were set as black and white photo, 600 dpi, and 8- and 16-bit grayscale for the Perfection 1250 and 4870, respectively. Numerical values corresponding to each sector of the density wedge strip were obtained using P-SCAN and were plotted against the optical densities measured by the manufacturer ((Figure 2), A and B). Both the Perfection 1250 and 4870 demonstrated that they were able to utilize almost the full range of 256 and 65,536 levels of grayscale. As expected, the plots level off at high optical density as a consequence of the theoretical limitation of the absor-bance detection principle. Sequential mechanical adjustments (scanner hardware, scanning software, and graphical applications) may also limit the linear range. As a result, density-readout association could be slightly skewed or compressed.