Defining the Enterovirus Diversity Landscape of a Fecal Sample: A Methodological Challenge?

Abstract

Enteroviruses are a group of over 250 naked icosahedral virus serotypes that have been associated with clinical conditions that range from intrauterine enterovirus transmission withfataloutcome through encephalitis and meningitis, to paralysis. Classically, enterovirus detection was done by assaying for the development of the classic enterovirus-specific cytopathic effect in cell culture. Subsequently, the isolates were historically identified by a neutralization assay. More recently, identification has been done by reverse transcriptase-polymerase chain reaction (RT-PCR). However, in recent times, there is a move towards direct detection and identification of enteroviruses from clinical samples using the cell culture-independent RT semi-nested PCR (RT-snPCR) assay. This RT-snPCR procedure amplifies the VP1 gene, which is then sequenced and used for identification. However, while cell culture-based strategies tend to show a preponderance of certain enterovirus species depending on the cell lines included in the isolation protocol, the RT-snPCR strategies tilt in a different direction. Consequently, it is becoming apparent that the diversity observed in certain enterovirus species, e.g., enterovirus species B(EV-B), might not be because they are the most evolutionarily successful. Rather, it might stem from cell line-specific bias accumulated over several years of use of the cell culture-dependent isolation protocols. Furthermore, it might also be a reflection of the impact of the relative genome concentration on the result of pan-enterovirus VP1 RT-snPCR screens used during the identification of cell culture isolates. This review highlights the impact of these two processes on the current diversity landscape of enteroviruses and the need to re-assess enterovirus detection and identification algorithms in a bid to better balance our understanding of the enterovirus diversity landscape.

Keywords: cell culture; enterovirus diversity landscape; enteroviruses; species bias.

Figure 1

Poliovirus (PV) isolation algorithm as recommended by the World Health Organization (2003, 2004).

Figure 2

Recently recommended algorithm for direct detection of enteroviruses from clinical specimens (WHO, 2015).

Figure 3

Modified WHO algorithm used in our laboratory for direct detection of enteroviruses from clinical specimens.