Abstract
An automatic spot identification method is developed for high throughput surface plasmon resonance imaging (SPRi) analysis. As a combination of video accessing, image enhancement, image processing and parallel processing techniques, the method can identify the spots in SPRi images of the microarray from SPRi video data. In demonstrations of the method, SPRi video data of different protein microarrays were processed by the method. Results show that our method can locate spots in the microarray accurately regardless of the microarray pattern, spot-background contrast, light nonuniformity and spotting defects, but also can provide address information of the spots.
Highlights
In the past few decades, the biomolecule microarray has emerged as a high-throughput parallel screening tool for the identification of biomolecular interaction and been widely applied in several fields, including functional protein screening [1,2], drug discovery [3,4], biomarker discovery [5] and antibody profiling [6,7]
Due to the obvious superiority of label-free, real-time monitoring and kinetic analysis, the surface plasmon resonance imaging (SPRi) biosensor has become an important technique for biomolecular interaction analysis (BIA) [8], and several methodologies have been carried out to enhance the sensitivities [9]
In most SPRi instruments, an expanded and collimated light beam reflects from a metal slide supporting a microarray of biomolecules, and the reflection is collected as real-time images in video data by a charge-coupled device (CCD) detector array [21,22]
Summary
In the past few decades, the biomolecule microarray has emerged as a high-throughput parallel screening tool for the identification of biomolecular interaction and been widely applied in several fields, including functional protein screening [1,2], drug discovery [3,4], biomarker discovery [5] and antibody profiling [6,7]. In most SPRi instruments, an expanded and collimated light beam reflects from a metal slide supporting a microarray of biomolecules, and the reflection is collected as real-time images in video data by a charge-coupled device (CCD) detector array [21,22]. The microarray is surveyed for interactions with a probe molecule in a high-throughput and parallel manner, and different reagents injected in the interactions can produce varied refractive index changes in spots of the microarray and their background [5]. Variations of the interaction strength and refractive index among the spots, as well as interruption factors, such as air bubbles, make it impossible to mark a report point of the image with
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