The ongoing evolution of microbial pathogens represents a significant issue in diagnostic PCR/qPCR. Many assays are burdened with false negativity due to mispriming and/or probe-binding failures. Therefore, PCR/qPCR assays used in the laboratory should be periodically re-assessed in silico on public sequences to evaluate the ability to detect actually circulating strains and to infer potentially escaping variants. In the work presented we re-assessed a RT-qPCR assay for the universal detection of influenza A (IA) viruses currently recommended by the European Union Reference Laboratory for Avian Influenza. To this end, the primers and probe sequences were challenged against more than 99,000 M-segment sequences in five data pools. To streamline this process, we developed a simple algorithm called the SequenceTracer designed for alignment stratification, compression, and personal sequence subset selection and also demonstrated its utility. The re-assessment confirmed the high inclusivity of the assay for the detection of avian, swine and human pandemic H1N1 IA viruses. On the other hand, the analysis identified human H3N2 strains with a critical probe-interfering mutation circulating since 2010, albeit with a significantly fluctuating proportion. Minor variations located in the forward and reverse primers identified in the avian and swine data were also considered.
The development of a diagnostic polymerase chain reaction (PCR) or quantitative PCR (qPCR) assay for universal detection of highly variable viral genomes is always a difficult task. The purpose of this chapter is to provide a guideline on how to align, process, and evaluate a huge set of homologous nucleotide sequences in order to reveal the evolutionarily most conserved positions suitable for universal qPCR primer and hybridization probe design. Attention is paid to the quantification and clear graphical visualization of the sequence variability at each position of the alignment. In addition, specific problems related to the processing of the extremely large sequence pool are highlighted. All of these steps are performed using an ordinary desktop computer without the need for extensive mathematical or computational skills.
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