Enhancement of Coronaviridae Pathotyping Using Length Polymorphism

Abstract

Coronaviridae is a class of enveloped, single stranded, and positive-sense RNA viruses including genera Coronavirus and Torovirus. During the severe acute respiratory syndrome (SARS-CoV) outbreak in Asia, virus identification becomes a leading issue in recent years. Studies of SARS-CoV were diagnosed by various molecular techniques. Only a few tools are included to help the identification process. One of the detections is PCR-based approach, for the detection and identification of DNA strains – length polymorphism. Length polymorphism indicates variations in the length of sequence fragment, resulting from various genetic mutation, and used as a DNA marker to detect genetic diversity. In this paper, we formalize the problem of cleaved amplified polymorphic sequences (CAPS) subtyping issue. We propose a simple heuristic algorithm to solve the problem of CAPS subtyping. Besides, the necessary condition for optimality CAPS subtyping problem is also refined. First, fragment lengths after digestion on genome are improved from boolean vectors to integer vectors (CI-Vectors). This helps a comprehensive quantification in length polymorphism for pathotyping. Second, a simulated histogram is proposed to demonstrate the variation in DNA length polymorphism, describing a simplified view in CI-Vectors. Results showed that when genomic DNA of Coronaviridae strains were digested with enzymes AatII, BbeI, and SplI, most of the SARS-CoV strains can be isolated from other CoV, including bovine torovirus, equine torovirus, and human torovirus. In addition, the proposed method is applied to major structural protein of SARS-CoV in spike protein and envelope protein. Comparing to general subtyping approach, our CAPS patterns provide a promotive advantage on its capability. Each generated enzyme set is also evaluated to ensure their validation. This PCR-based approach offers a practical direction for DNA subtyping.