An array-based melt curve analysis method for the identification and classification of closely related pathogen strains

基于阵列的熔解曲线分析方法,用于密切相关的病原体菌株的鉴定和分类

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作者:Arjang Hassibi, Jessica Ebert, Sara Bolouki, Alexander Anemogiannis, Gelareh Mazarei, Yuan Li, Kirsten A Johnson, Tran Van, Pallavi Mantina, Taraneh Gharooni, Kshama Jirage, Lei Pei, Ruma Sinha, Arun Manickam, Amin Zia, Pejman Naraghi-Arani, Gary Schoolnik, Robert G Kuimelis

Abstract

PCR-based techniques are widely used to identify disease causing bacterial and viral pathogens, especially in point-of-care or near-patient clinical settings that require rapid results and sample-to-answer workflows. However, such techniques often fail to differentiate between closely related species that have highly variable genomes. Here, a homogenous (closed-tube) pathogen identification and classification method is described that combines PCR amplification, array-based amplicon sequence verification, and real-time detection using an inverse fluorescence fluorescence-resonance energy transfer technique. The amplification is designed to satisfy the inclusivity criteria and create ssDNA amplicons, bearing a nonradiating quencher moiety at the 5'-terminus, for all the related species. The array includes fluorescent-labeled probes which preferentially capture the variants of the amplicons and classify them through solid-phase thermal denaturing (melt curve) analysis. Systematic primer and probe design algorithms and empirical validation methods are presented and successfully applied to the challenging example of identification of, and differentiation between, closely related human rhinovirus and human enterovirus strains.

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