Impact of RNA Degradation on Viral Diagnosis: An Understated but Essential Step for the Successful Establishment of a Diagnosis Network

Abstract

The current global conditions, which include intensive globalization, climate changes, and viral evolution among other factors, have led to an increased emergence of viruses and new viral diseases; RNA viruses are key drivers of this evolution. Laboratory networks that are linked to central reference laboratories are required to conduct both active and passive environmental surveillance of this complicated global viral environment. These tasks require a continuous exchange of strains or field samples between different diagnostic laboratories. The shipment of these samples on dry ice represents both a biological hazard and a general health risk. Moreover, the requirement to ship on dry ice could be hampered by high costs, particularly in underdeveloped countries or regions located far from each other. To solve these issues, the shipment of RNA isolated from viral suspensions or directly from field samples could be a useful way to share viral genetic material. However, extracted RNA stored in aqueous solutions, even at -70 °C, is highly prone to degradation. The current study evaluated different RNA storage conditions for safety and feasibility for future use in molecular diagnostics. The in vitro RNA-transcripts obtained from an inactivated highly pathogenic avian influenza (HPAI) H5N1 virus was used as a model. The role of secondary structures in the protection of the RNA was also explored. Of the conditions evaluated, the dry pellet matrix was best able to protect viral RNA under extreme storage conditions. This method is safe, cost-effective and assures the integrity of RNA samples for reliable molecular diagnosis. This study aligns with the globally significant "Global One Health" paradigm, especially with respect to the diagnosis of emerging diseases that require confirmation by reference laboratories.

Keywords: RNA storage; laboratory networks; real time RT-PCR; sample exchange; secondary structures; viral diagnosis.

Figure 1

Comparison of RNA load values detected from M gene diagnostic target region under different storage conditions for 57 days post incubation (dpi). Dynamics of degradation at (A) low RNA load, (B) medium RNA load and (C) high RNA load. Each matrix of storage is denoted (S: swab matrix, RSB: RNA safe buffer described by Hoffmann et al. (2006) modified in this study, DP: dry pellet matrix), each temperature of storage is also denoted. Data is mean of qRT-PCR from triplicate samples. Based on the limit of detection of the assay, samples with ct > 35 were considered negative (see Supplementary Material Figure S1A).

Figure 2

Comparison of RNA load values detected from the HA gene diagnostic target region under different storage conditions for 57 days post incubation (dpi). Dynamic of degradation at (A) low RNA load, (B) medium RNA load and (C) high RNA load. Each matrix of storage is denoted (S: swab matrix, RSB: RNA safe buffer described by Hoffmann et al. (2006) modified in this study, DP: dry pellet matrix), each temperature of storage is also denoted. Data is mean of qRT-PCR from triplicate samples. Based on the limit of detection of the assay, samples with ct > 35 were considered negative (see Supplementary Materials Figure S1B).

Figure 3

Comparison of the probability of folding for secondary structures. (A) Secondary structure folding and conservation pattern of pairing for M gene. The target region framed by M+25 and M-124 primers is denoted by a rectangle, and the hybridization region for each primer is highlighted. (B) Secondary structure folding and conservation pattern of pairing for HA gene. The target region framed by H155f and H699r is denoted by a rectangle and the hybridization region for each primer is highlighted. In the upper panels, the color scale indicates level of conservation and in the lower panels the bar indicates the scale of probability for folding.

Figure 4

Comparison of the RNA load values under RNase A treatment for HA and M genes. The dynamics of degradation of RNA by the action of RNase A for each gene (HA gene and M gene) is shown. Data is mean of triplicate samples.