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Abstract
Phylogenetic analysis is commonly used in epidemiology, evolutionary biology, and even forensic investigations. Before conducting such analysis, one of the questions frequently asked is whether the gene/genomic region chosen is appropriate for the purpose of the intended studies? This questions is especially crucial for the epidemiological studies on bluetongue virus (Orbivirus, Reoviridae), since its 11 genes carried by 10 double-stranded RNA segments can evolve independently and may reflect different characteristics of the virus under natural selection pressures.
Traditionally, evaluating the suitability of genes used in phylogenetic analysis is mainly based on the topologies of constructed phylogenetic trees, which at times, appear to be arbitrary. In the present study, we attempted to help judge the appropriateness of BTV genes for phylogenetic analysis using a quantitative approach in order to establish more objective criteria. The nucleotide sequences of BTV VP3, VP5, VP6, VP7, NS2, and NS3 genes, obtained from the GenBank database, were divided into six groups based on their geographical origins: Asia, Australia, Africa, the Mediterranean Basin, Europe, and the Americas. Percent identities between the sequences and the corresponding sequences of two reference BTV strains were calculated and the percent identities of different geographic regions were compared statistically. The results indicated that, by the differences in nucleotide percent identities of VP3 and NS3 genes, the Asian and Australian BTV strains can be distinguished from the African and American strains, generally in accordance with the findings of the corresponding phylogenetic trees. Moreover, NS2 presented its distinguishing ability to discriminate Asian strains from African, Mediterranean, and American strains.
This attempt demonstrates that the reliability of phylogenetic analysis can be assessed not only topologically by phylogenetic tree construction but also quantitatively by the percent identities of the strains employed. However, the latter method might be biased by the reference strain selected and the field strains sampled.
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Abstract
H1N1 novel influenza virus contains 8 genes which commonly rearrange among swine, poultry and human origin and become new mutant viruses. Until now, swine infected by the H1N1 novel influenza virus has been reported in over 10 countries. In Taiwan, the first case of H1N1 novel influenza virus infection in swine was identified in November 2009. Genetic analyses on H1N1 novel influenza virus isolated from a pig showed that it was identical to that of human beings. It revealed that H1N1 novel influenza virus could circulate between humans and swine. In Taiwan, the surveillance of H1N1 novel influenza virus follows the protocol of real-time RT-PCR developed by the CDC for detection and characterization of swine influenza A (H1N1). However, the method itself cannot differentiate novel H1N1 influenza virus from swine influenza, and further identification must be performed by DNA sequencing, a rather time-consuming step. Therefore, there is an immediate and critical need for a rapid differential diagnostic method for novel H1N1 influenza virus detection in swine. In the current study, specific primers and LNA probes were designed based on the HA and NA sequences of H1N1 novel influenza virus. They were then applied using real-time RT-PCR for detecting the varying host origins of influenza viruses. Our results showed that the sensitivity of the primer was higher than that of the CDC. Arguably, the real-time RT-PCR method, when combined with the LNA probe could be usedfor the rapid identification of novel H1N1 influenza viruses. Furthermore, a DNA chip method was also developed to identify novel H1N1 influenza viruses. Specific oligonucleotide primers and probes were designed from the influenza virus genome. One-step multiplex RT-PCR amplification was performed with biotin-labeled primers, followed by hybridization to the DNA probe immobilized on a plastic chip. The results showed that the DNA chip was also able to differentiate between H1N1 novel influenza virus and swine influenza virus.
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