PCR assays for detection of human astroviruses: In silico evaluation and design, and in vitro application to samples collected from patients in the Netherlands

Abstract

Background: Human astroviruses (HAstV) comprise three phylogenetically compact and non-adjacent groups of species including classical HAstV (HAstV-C) and the novel ones (HAstV-VA/HMO and HAstV-MLB). Of these, HAstV-C is known to be responsible for gastroenteritis while the novel HAstV are associated with cases of neurological disorders. Accurate detection of all known variants by (real-time) PCR is challenging because of the high intra- and intergroup genetic divergence of HAstV.

Objectives: To evaluate published HAstV PCR assays in silico, design de novo real-time PCR assays that can detect and discriminate three groups of HAstV, and apply those to patient samples to analyse the prevalence of HAstV in stool and cerebrospinal fluid (CSF) specimens.

Study design: In silico evaluation of published PCR assays and design of real-time PCR assays for detection of different subsets of HAstV was conducted within a common computational framework that used all astrovirus full genome sequences from GenBank. The newly designed real-time PCR assays were evaluated in vitro and applied to faecal samples (collected in January-May 2016) and cerebrospinal fluid specimens (2010-2016) from patients in the Netherlands.

Results: Quantitative in silico evaluation of published PCRs is provided. The newly designed real-time PCR assays can reliably assign all available HAstV genome sequences to one of the three phylogenetic groups in silico, and differentiate among HAstV-specific controls in vitro. A total of 556 samples were tested using these PCR assays. Fourteen fecal samples (2.5%) tested positive for HAstV, 3 of which could be identified as the novel HAstV-MLB variants. No novel HAstV were found in CSF specimens.

Conclusion: Newly designed real-time PCR assays with improved detection of all known HAstV allowed the first-time identification of novel astroviruses from stool samples in the Netherlands.

Keywords: Bioinformatics; Diarrhoea; Encephalitis; In silico PCR evaluation and design; Mamastrovirus; Meningitis.