Bioinformatics Advance Access originally published online on October 27, 2004
Bioinformatics 2005 21(5):689-690; doi:10.1093/bioinformatics/bti088
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LabArray: real-time imaging and analytical tool for microarrays
1 Division of Bioengineering 10 Kent Ridge Crescent, Singapore 119260, Singapore
2 Department of Civil Engineering 10 Kent Ridge Crescent, Singapore 119260, Singapore
*To whom correspondence should be addressed at Department of Civil Engineering, National University of Singapore, Blk E1A, #07–03, Engineering Drive 2, Singapore 117576, Singapore.
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Abstract |
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Summary: Microarrays have been used to perform high-throughput genetic analyses such as single-nucleotide polymorphisms detection and microbial genome analysis. Some of these analyses require real-time monitoring of the hybridization signals with respect to a varying experimental condition, such as temperature. However, current microarray imaging and analysis packages typically do not possess such real-time capabilities. Therefore, microarray image analyses are often time-consuming and labour-intensive. LabArray was developed to expedite such processes by enabling real-time monitoring of microarray signals.
Availability: LabArray is available at http://www.eng.nus.edu.sg/civil/Labarray/labarray.htm
Contact: cveliuwt{at}nus.edu.sg
Supplementary information: Screenshots and instructions for use are available at the above website.
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INTRODUCTION |
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DNA microarrays consisting thousands of cDNA probes up to few kilobases immobilized onto solid substrates have been widely used in gene expression analyses (Schena et al., 1995). Hybridization of labelled DNA/RNA targets with their complementary probes results in the concentration of labelled signals on designated spots, and provides information related to the patterns of gene expression of interest. The signal intensities of all probe-target duplexes mostly expressed as fluorescence light are measured through a laser scanner using suitable software available commercially or free-of-charge.
In recent years, oligonucleotide microarrays (
15–25 bases long) have been developed for the analysis of single nucleotide mismatches in microbial detection or single nucleotide polymorphisms (SNPs) in genomic DNA. Such analyses, for example, enable bacterial identification in environmental microbiology (Bavykin et al., 2000; Liu et al., 2001) and reveal information regarding an individual's response to a certain drug or susceptibility to a particular disease (McCarthy and Hilfiker, 2000; Wang et al., 1998). The success of these studies ultimately relies on the efficacy of oligonucleotide microarrays to discriminate perfect match (PM) duplexes from duplexes containing one or more mismatched (MM) nucleotides occurring at any positions (Liu et al., 2001). However, the discrimination between PM and MM duplexes in the microarray studies is a daunting task when a single washing condition (formamide concentration, salt concentration, and temperature) is used (Tijssen, 1993). This task can be solved by using a non-equilibrium dissociation approach that simultaneously determines the dissociation processes (melting) of all duplexes from low to high temperature, and then examining the difference in signal intensities between a PM duplex and an MM duplex at the corresponding dissociation temperature (T d ) of the PM probes (Liu et al., 2001; Urakawa et al., 2002).
Profiling the non-equilibrium dissociation curves of all probe-target duplexes requires real-time analysis of the oligonucleotide microarray signals throughout the melting process, but this cannot be easily achieved using existing software. Here, LabArray that allows automated image acquisition and real-time signal quantification was developed to facilitate the process of microarray image analysis in non-equilibrium dissociation studies. The main advantage of LabArray is its ability to perform real-time monitoring. Most existing packages do not have such capability, which makes it very time-consuming and labour-intensive to conduct these real-time microarray experiments.
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PROGRAM OVERVIEW |
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LabArray was developed using LabVIEW (Version 5.1, National Instruments, Austin, TX, USA) for the creation of a graphical user interface (GUI). It integrated the controls of a heating stage and a cooled-CCD camera (Photometrics Coolsnap; Roper Scientific, Tuscon, AZ, USA) for the time-lapsed acquisition and analysis of microarray images corresponding to different individual temperatures. After capturing the first image in an experiment, LabArray employed a morphological erosion algorithm (Soille, 1999) to determine the pitch and size of the probe spots. This algorithm made use of the covariance of an image containing periodic objects to calculate the distance between any two given objects or probe spots. By using spot size and pitch as the parameters, the size of the grids required to quantify the array of spots was determined. A grid was subsequently formed to define a region of interest (ROI) for all spots in the array, and can be manually fine-tuned by the user if necessary. Once the user manually shifted the grid over the approximate region of the array of spots, an automatic spot-finding process was activated to allow each spot to be located by the grids with greater precision. This process also could identify spots that were misaligned during the printing process. The gridding and spot-finding steps were only necessary for the first image in the experiment.
To measure the pixel intensities of individual probe spots, LabArray used a morphological opening algorithm (Soille, 1999) to initially remove noise found within an ROI that might affect the quantification results. For a given ROI, the distinction between a spot intensity and its local background was then differentiated based on a segmentation algorithm (Otsu, 1979). The final intensities of individual probe spots were calculated by subtracting mean background intensity from that of each segmented spot, and the values were exported to a spreadsheet file. The quantification step was automatically repeated for all subsequent captured images based on the grid from the first image. During the experiment, dissociation profiles for any given probe spot could be instantly accessed via a pop-up window. When the final image was quantified, LabArray determined the T d for each spot based on their respective dissociation profiles. The robustness of the imaging quantification in the LabArray was evaluated by comparing a set of microarray images manually quantified using commercial image analysis software, Metamorph (Universal Imaging, Downingtown, PA, USA). The two sets of result were closely matched (Fig. 1).
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LabArray also provided an additional advantage over commercial software. It can easily be modified to control multiple cameras as long as a LabVIEW driver is available for the camera, and incorporate the controls of other instruments, such as a motorized stage, into a common GUI. Such flexibility can greatly enhance its capability to cope with even more challenging applications.
Received on June 17, 2004; revised on September 21, 2004; accepted on October 7, 2004
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REFERENCES |
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Bavykin, S.G., Akowski, J.P., Zakhariev, V.M., Barsky, V.E., Perov, A.N., Mirzabekov, A.D. (2000) Portable system for microbial sample preparation and oligonucleotide microarray analysis. Appl. Environ. Microbiol., 67, 922–928.
Liu, W.T., Mirzabekov, A.D., Stahl, D.A. (2001) Optimization of an oligonucleotide microchip for microbial identification studies: a non-equilibrium dissociation approach. Environ. Microbiol., 3, 619–629[CrossRef][Medline].
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