Before the introduction of live attenuated vaccines, measles was endemic in all countries and was a leading cause of childhood morbidity and mortality. High vaccination coverage through routine and supplemental vaccination programs has significantly reduced the circulation of measles virus (MV) in many industrialized nations (14
); however, the virus remains endemic in many developing countries, leading to 30 million cases and approximately 454,000 deaths annually (36
). The goal of the Global Measles Strategic Plan, sponsored by the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF), is to significantly reduce measles mortality in countries where the virus is endemic and to maintain measles-free status in countries that have already interrupted measles transmission (38
). Laboratory confirmation of suspected cases is an essential component of measles surveillance. To this end, WHO has developed a global network of measles laboratories. These laboratories perform serologic assays to detect MV-specific immunoglobulin M antibodies and conduct genetic characterization of wild-type MVs isolated from outbreaks and sporadic cases (2
). Molecular epidemiological studies, along with standard case investigation and reporting, provide the necessary tools to monitor MV circulation and gauge the success of vaccination programs (23
The classification system for wild-type MV is based on the sequences of the 450 nucleotides coding for the 150 amino acids at the C terminus of the N protein (24
). The intergenotype diversity within this region of the N gene is greater than 2.5%, and the most divergent MV genotypes differ by as much as 12%. Measles viruses are classified into eight clades (A to H) that are currently subdivided into 23 recognized genotypes (A, B1 to B3, C1, C2, D1 to D10, E, F, G1 to G3, H1, and H2) (24
). Sequence analysis of PCR products is currently the most practical, cost-effective, and accurate method for MV genotyping. Other genotyping methods, such as restriction fragment length polymorphism (RFLP) (22
), the heteroduplex mobility assay (HMA) (18
), refractory mutation analysis (27
), genotyping by nucleotide-specific multiplex PCR (19
), and real-time PCR (31
), have been proposed. Most of these methods have inherent shortcomings and can differentiate only a limited number of MV genotypes. RFLP-based methods depend on the availability of restriction sites suitable for analysis, and the results of HMA are often difficult to interpret and reproducibility is low. Some of these techniques are technically challenging, expensive, and difficult to standardize. Furthermore, these methods are not amenable to high-throughput screening and lack the sensitivity of sequence analysis. Data from these various alternative approaches cannot be easily reported to a central database, so results obtained in different laboratories cannot be easily compared.
As the WHO measles laboratory network expands, additional methods for the genetic characterization of MV will be desirable. For example, high-throughput screening techniques may be necessary if the number of specimens increases significantly. Characterization of larger regions of the genome or complete genomes may be required in order to increase the sensitivity of the molecular epidemiologic analysis and to efficiently monitor multiple genetic characteristics of the virus.
DNA microarray technology is an efficient tool for rapid genetic analysis of microorganisms including transcription profiling, resequencing, single-nucleotide polymorphism (SNP) analysis, and genotyping of bacterial and viral pathogens (4
). Short oligonucleotide probes (oligoprobes) enable discrimination of samples with minor genetic differences. MV genotypes may differ by only a few nucleotides, and these differences are not always conserved even within a specific genotype. Unique signature nucleotide patterns capable of distinguishing all genotypes may not be readily identifiable, and accurate microarray discrimination of closely related genotypes presents a challenge. We propose a novel approach for microarray design and analysis that relies on the recognition of patterns of hybridization signals from a large number of genotype-specific and control oligoprobes. This method has allowed us to correctly identify the genotypes of most tested samples, including a previously unidentified genotype that was not included in the initial microarray design.