Development of a Common Oligonucleotide Reference Standard for Microarray Data Normalization and Comparison across Different Microbial Communities

High-density functional gene arrays have become a powerful tool for environmental microbial detection and characterization. However, microarray data normalization and comparison for this type of microarray remain a challenge in environmental microbiology studies because some commonly used normalization methods (e.g., genomic DNA) for the study of pure cultures are not applicable. In this study, we developed a common oligonucleotide reference standard (CORS) method to address this problem. A unique 50-mer reference oligonucleotide probe was selected to co-spot with gene probes for each array feature. The complementary sequence was synthesized and labeled for use as the reference target, which was then spiked and cohybridized with each sample. The signal intensity of this reference target was used for microarray data normalization and comparison. The optimal amount or concentration were determined to be ca. 0.5 to 2.5% of a gene probe for the reference probe and ca. 0.25 to 1.25 fmol/μl for the reference target based on our evaluation with a pilot array. The CORS method was then compared to dye swap and genomic DNA normalization methods using the Desulfovibrio vulgaris whole-genome microarray, and significant linear correlations were observed. This method was then applied to a functional gene array to analyze soil microbial communities, and the results demonstrated that the variation of signal intensities among replicates based on the CORS method was significantly lower than the total intensity normalization method. The developed CORS provides a useful approach for microarray data normalization and comparison for studies of complex microbial communities.Microarray-based technology has become a robust genomic tool to detect, track, and profile hundreds to thousands of different microbial populations simultaneously in complex environments such as soils and sediments. For example, GeoChip, a comprehensive functional gene array, has been developed for investigating biogeochemical, ecological, and environmental processes (12, 18, 23, 27, 29, 32). Although a massive amount of microarray data can be generated rapidly, one of the bottlenecks in using microarrays for environmental microbial community studies is the lack of an appropriate standard for data comparison and normalization (6). Currently, it is difficult to compare microarray data across different sites, experiments, laboratories, and/or time periods (10). This limits the power of the technology to address ecological and environmental questions.In pure culture-based functional genomics studies, genomic DNAs (gDNAs) have been used as a common reference for hybridizations in which the same amount of gDNAs are used to cohybridize with each target cDNA sample and then to normalize different target cDNAs based on the gDNA standard (4, 5, 8, 9, 19, 21, 23). Several normalization methods such as scale normalization, quantile normalization, and Lowess normalization have been used for gene expression studies (2). Using the gDNA standard method can minimize or eliminate differences in target cDNA quantity, spot morphology, uneven hybridization, labeling, and sequence-specific hybridization behaviors (5), and this allows the comparison of microarray data across different sites, laboratories, experiments, and/or times. The main rationale for gDNA as a common reference is that it provides complete coverage for all genes represented on the array because the DNA composition from a particular organism should be identical across different treatment samples even though RNA expression is different (8). However, this approach is not applicable to microbial community studies because not all communities have identical DNA compositions. Pooling of equal amounts of gDNA or RNA from every target sample to make a common sample could be used as an alternative reference for cohybridization (1, 22). However, the disadvantage of the sample pooling approach is that samples do not provide large amounts of DNA or RNA in a reliable and reproducible way. For example, groundwater samples usually have a very low biomass and thus would not provide enough DNA for pooling. In addition, the sample pool itself is uncharacterized, and gene abundance may be diluted out so that insufficient DNA is present to result in a positive signal some array features, especially for those genes in low abundance. Moreover, a new sample pool would be required for every new experiment, making comparison across experiments difficult. Thus, other approaches need to be developed for microbial community studies.Dudley et al. (7) used a 25-mer oligonucleotide that matched a small portion of the parental EST clone vector contained in every PCR product printed on the array for normalization of pure culture RNA expression. Although the oligonucleotide generated a stable hybridization signal on every array feature, this method requires a universal sequence tag as a “capture” sequence, limiting its general use in microbial community studies. Thus, in the present study, we developed a common oligonucleotide reference standard (CORS) approach by co-spotting a common oligonucleotide with each array feature to improve the accuracy and comparability of microarray data for microbial community studies. This method was evaluated by using a pilot array, a whole-genome array, and a functional gene array, and all results demonstrate that the developed CORS is a reliable and reproducible method for microarray data normalization and comparison for microbial community studies.