alexa Utilization of microsatellite polymorphism for differentiating herpes simplex virus type 1 strains.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Data Mining in Genomics & Proteomics

Author(s): Deback C, Boutolleau D, Depienne C, Luyt CE, Bonnafous P,

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Abstract The herpes simplex virus type 1 (HSV-1) genome is a linear double-stranded DNA of 152 kpb. It is divided into long and short regions of unique sequences termed U(L) and U(S), respectively, and these are flanked by regions of inverted internal and terminal repeats. Microsatellites are short tandem repeats of 1- to 6-nucleotide motifs; they are often highly variable and polymorphic within the genome, which raises the question of whether they may be used as molecular markers for the precise differentiation of HSV-1 strains. In this study, 79 different microsatellites (mono-, di-, and trinucleotide repeats) in the HSV-1 complete genome were identified by in silico analysis. Among those microsatellites, 45 were found to be distributed in intergenic or noncoding inverted repeat regions, while 34 were in open reading frames. Length polymorphism analysis of the PCR products was used to investigate a set of 12 distinct HSV-1 strains and allowed the identification of 23 polymorphic and 6 monomorphic microsatellites, including two polymorphic trinucleotide repeats (CGT and GGA) within the UL46 and US4 genes, respectively. A multiplex PCR method that amplified 10 polymorphic microsatellites was then developed for the rapid and accurate genetic characterization of HSV-1 strains. Each HSV-1 strain was characterized by its own microsatellite haplotype, which proved to be stable over time in cell culture. This relevant innovative tool was successfully applied both to confirm the close relationship between sequential HSV-1 isolates collected from patients with multiple recurrent infections and to investigate putative nosocomial infections.
This article was published in J Clin Microbiol and referenced in Journal of Data Mining in Genomics & Proteomics

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