The Human Genome Project, or HGP, is a multinational scientific effort to determine the 3.2 billion DNA bases that make up the human genome. These sequences are the instructional material for the mechanisms governing the behavior of each cell, including why some cells become part of a disease process and others do not. The small variations in the DNA sequence that lead to different characteristics (such as skin color, facial features or height) are known as polymorphisms, which also can cause or contribute to the development of many syndromes and diseases.¹ Therefore, the completion of the draft version of the human genome sequence in 2001 was an important first step for a more comprehensive understanding of the fundamental determinants of health and disease.² In addition, the HGP provides the basis for many other scientific questions. For example, the genomes of many other organisms are being sequenced; this will allow the examination of cross-species similarity and differences as represented in their genomic sequences and provide us with insights on human evolution.

The great challenge now is to understand how the enormous amount of information contained in the genome is translated into molecular action. By examining the sequences, for example, researchers hope to implicate regions of DNA (genes) that control normal and disease processes. An early application of this effort has involved the development of microarrays: small devices, about the size of a thumbnail, that contain pieces of DNA sequences that can measure the gene expression levels of thousands of genes simultaneously.^3–5 In traditional biological research, genes were studied one at a time through a series of laborious and time-consuming experimental techniques. This is one reason that only a small fraction of all the genes have been characterized so far. By allowing simultaneous genome-wide measurements, microarrays can greatly expedite the research process, as well as enable new avenues of research. Currently, microarrays are used primarily in research, but their enormous clinical potential is beginning to be explored.

Several recent reports have discussed how the HGP can play an integrative role in the oral health care profession in terms of future directions and challenges.^6–8 In this review, we will discuss microarrays, emphasizing the biology behind the technology, the types of arrays available and some future applications to clinical dentistry. (Author’s note: the box provides a glossary of some of the key terms used in this article.)

	THE BIOLOGY BEHIND MICROARRAYS

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While proteins carry out the activities in a cell, they ultimately are controlled by the instructions contained in the DNA sequences, through an intermediate step involving messenger RNA, or mRNA. mRNA is an intermediary molecule that carries the genetic information from the cell nucleus to the cytoplasm, where proteins are made. When certain genes become active, or "expressed," many copies of mRNAs corresponding to those genes are produced (a process called "transcription"), and they in turn generate the necessary proteins (a process called "translation") (Figure 1). Therefore, by knowing which mRNAs are present in a cell, we can identify which genes are being expressed, and we can begin to understand some of the basic elements controlling the structure and function of the cell.

View larger version (40K): [in this window] [in a new window]   Figure 1. Transcription of DNA to RNA to protein.

An estimated 30,000 to 40,000 genes are present in the human genome. While every cell contains every gene within that cell’s DNA, only 10 to 20 percent of the genes are expressed in a given cell at a particular time. By measuring how these genes are differentially expressed differently among various conditions, it is possible to implicate certain genes as being relevant in the underlying process. For example, by comparing the different patterns of gene expression levels between a group of cancer patients and a group of normal patients, we can find the genes that may be associated with cancer. Without microarrays, one would have to study thousands of genes one at a time; with them, one can examine all of those thousands of genes simultaneously.

	MICROARRAY TECHNOLOGY

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A microarray is composed of a series of pieces of DNA, usually corresponding to segments of genes, that are placed in a prespecified arrangement, typically on a glass slide or a silicon chip.⁹ In addition to the array designed for the human genome, different arrays are available for the genomes of a variety of model organisms such as yeast and mouse.^10–13

The principle behind microarrays is the fact that complementary sequences will bind to each other under the right conditions. That is, if the DNA is 10 base pairs long and the sequence is ATGGCTTGAC, for example, the mRNA containing segment TACCGAACTG will "hybridize" to the probe. (The base pair A is complementary to T and C is complementary to G; the actual DNAs on the array are at least 25 base pairs long to maximize the chance of there being a unique sequence for each gene.) On a microarray, many thousands of spots are placed on a rectangular grid, each spot containing a large number of pieces of DNA from a particular gene. When the sample of interest contains many copies of mRNA, many bindings will occur, indicating that the gene from which the mRNA is transcribed is highly expressed. The quantity of hybridization can be determined because each copy of mRNA is labeled in the experiment with a fluorescent or radioactive tag and a brighter signal is detected when more copies bind.

There are presently two types of microarray technology in common usage: cDNA microarrays and oligonucleotide microarrays. They differ in their method, design and image. cDNA arrays contain long fragments of DNA (from 100 to thousands of base pairs) and oligonucleotide arrays contain short fragments of DNA (25 base pairs) (Figure 2). cDNA microarrays are created by robotically spotting individual samples of purified cDNA clones onto a glass slide, whereas oligonucleotide microarrays are made by constructing exact probe sequences using a photolithography masking technique similar to the one used for fabricating computer chips. cDNA arrays often are made by individual laboratories based on their particular resources and needs; oligonucleotide arrays are built base by base on the array surface by repeated cycles of photodeprotection and nucleotide addition until the desired length is reached. These arrays generally are more costly to make and are purchased through the manufacturer.

View larger version (58K): [in this window] [in a new window]   Figure 2. Oligonucleotide and complementary DNA, or cDNA, microarray. A. Affymetrix GeneChip (Santa Clara, Calif.) microarray cartridge, consisting of oligonucleotide probes (25 base pairs long). Within the microarray, up to 1 million unique oligonucleotide probes can be affixed to a silicon chip. The plastic cartridge protects the microarray and serves as a chamber for hybridization. After hybridization, the array is scanned. B. Spotted cDNA microarray robot. A light source causes the spots that contain cDNA probes (from 100 to thousands of base pairs long) hybridizing to the Cy3 labeled target strands to fluoresce red. Spots that hybridize to Cy5 labeled strands fluoresce green, and spots that hybridize both Cy3 and Cy5 fluoresce yellow. The intensity of the fluorescence correlates with the amount of hybridization. After hybridization, the array is scanned. Image of GeneChip probe array reproduced with permission of Affymetrix.

	THE CHALLENGES OF USING MICROARRAYS

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While these arrays are designed to give a genome-wide view of the cell on an unprecedented scale, there are some problems and obstacles. A major drawback is their high cost, although prices have dropped significantly in the past few years. Each oligonucleotide array typically costs hundreds of dollars; chemicals and labor needed for the experiment also can cost a substantial amount. This is in addition to the hundreds of thousands of dollars necessary for the initial setup.

Another challenge is the efficient management and accurate analysis of the large volume of data generated by microarrays. As with other high-throughput technologies, microarrays collect massive amounts of raw data. These data then need to be stored in a database in such a way that relevant information can be retrieved efficiently and be linked to various databases on the Internet containing biological annotations. Analysis of the data requires considerable expertise in statistics and data-mining techniques, especially given the low quality of data at present. In addition to the usual biological variations, microarray data can be very noisy owing to many technical shortcomings that are yet to be overcome. Recently, poor reproducibility between different technologies for the same samples has been observed.¹⁷ Standard methods of analysis include cluster analysis for grouping similar patient samples or similar genes, as well as classification techniques for finding genes differentially expressed between conditions and predicting the class of a new sample. Many software packages are available for standard analysis, but the validity of the statistical methods in these packages needs to be examined for particular data sets, and more sophisticated analysis than is available in these software packages is necessary for extracting the maximum amount of information from the data. Microarray data present many unresolved statistical issues, and therefore new methodology to remediate this is being developed by many researchers in the field of bioinformatics.

The molecular and biochemical activity associated with oral health and disease has the potential to be understood and classified by the ‘signature’ of the DNA or the proteins characterized using microarray technologies.

Quality of the laboratory work also is important to minimize the noise level in the data that are generated, which can substantially decrease the number of false positive gene expression changes. "Noise" is an informal term widely used in microarray data analyses and experiments to refer to parameters extraneous to the aspect of a system one is investigating, which eventually can interfere with data analysis. Performing a microarray experiment and the follow-up validations for genes with statistically significant result requires expertise in the experimental procedures, including the preservation of biological specimens in a manner that protects the integrity of mRNA.¹⁸

While DNA microarrays have become mainstream, the development of protein microarrays is still in its infancy. The microarray format is similar to that of oligonucleotide and cDNA arrays for gene expression profiling, but instead of DNA sequences, proteins are deposited in specified spots on the chip. There are many formidable technical hurdles at this point, but this technology has considerable potential, as it would allow us to measure the protein abundance directly rather than measuring the abundance of the intermediary mRNA molecules. It is well-known that mRNA levels do not always accurately reflect the level or activity of proteins, the molecules that directly govern cell function.¹⁹ Protein arrays can reveal information about post-translational modifications or protein-protein interactions,²⁰ and the information obtained from them in the future will complement transcriptional data.²¹ Among the many applications will be a rapid approach to identifying small molecules with desirable drug-protein interactions. This would lead to a more direct and efficient method of finding drug candidates.

	APPLICATIONS OF MICROARRAYS TO DENTISTRY

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The molecular and biochemical activity associated with oral health and disease has the potential to be understood and classified by the "signature" or "fingerprint" of the DNA or the proteins characterized using these technologies. Areas that can be coupled with microarray technologies include classification of diseases, or molecular phenotyping²²; the study of gene function in relation to gene regulatory networks, or functional genomics²³; drug development and prediction of efficacy and toxicity, or pharmacogenomics²⁴; and developmental biology.²⁵

Antibiotic treatment. Antibiotic treatment and prevention of infection have become increasingly complex with the rise of antibiotic-resistant bacterial strains. While certain local and systemic factors increase the likelihood of postoperative infections, little is known about virulent strains that may increase a patient’s potential susceptibility to orofacial infections. Many anaerobic bacteria might be the infective agent, but they often are not easily culturable; organisms such as actinomyces require long incubation periods and so must be treated empirically. DNA microarray analysis may offer a more sensitive and accurate endpoint for several reasons. First, bacterial genomic DNA often outlasts the viability of the bacteria. Second, a diagnosis can be made using a small amount of DNA, as opposed to the large numbers of bacteria needed for culture. One day, an abscess specimen might be sent not for culture and sensitivity testing but rather for DNA microarray analysis.

Oral lesions. Leukoplakia or white lesions of the oral cavity may result from a myriad of reversible conditions. Currently, microscopic examination fails to identify the small subset of these lesions that progress to oral cancer. Identification of gene expression profiles or "genomic fingerprints" will allow clinicians to differentiate harmless white lesions (leukoplakias) from pre-cancerous lesions or from very early cancer. Recent studies have illustrated the effectiveness of microarrays in oral cancer.^26,27 In the future, samples taken from an incisional biopsy or brush biopsy may be sent to a laboratory for gene expression analysis. Early diagnosis and management of oral cancer is correlated with increased survival. Identification and treatment of premalignant and early cancerous oral lesions may become one of the most valuable services dentistry performs.

TMD. TMD is a pervasive and challenging problem across the disciplines of dentistry. Today, diagnosis of and treatment planning for patients with TMD are based largely on anatomical changes associated with pain, functional complaints or both. Treatment of TMD can be controversial and unsuccessful, even if the right "diagnosis" is obtained. However, because TMD is a complex, multifactorial problem, researchers are studying the mediators and byproducts of the disease process within the joint fluid to develop new, biologically based diagnostic and therapeutic approaches.

Ultimately, protein arrays may prove to be important tools used in identifying biomarkers associated with TMD. In the future, clinicians may be able to better classify and treat TMD by microarray analysis of joint aspirates.

	CONCLUSION

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Microarrays hold much promise for the analysis of diseases in the oral cavity. Classification of oral disease by DNA, RNA or protein profiles will greatly enhance our ability to diagnose, prevent, monitor and treat our patients. Currently, microarrays are primarily a research tool. However, in the future, these highly sophisticated screening tools or their derivatives may provide an accurate, simple, rapid and inexpensive means for better managing the care of dental patients. Microarrays promise a more biologically based, individualized and vastly improved standard for oral care that will have great clinical impact on the way dentistry will be practiced in the future.