An Innovative Binding-Protein-Based dsRNA Extraction Method: Comparison of Cost-Effectiveness of Virus Detection Methods Using High-Throughput Sequencing

Abstract

Viral diseases represent a threat to global food production. Managing the impact of viruses on crop production requires the ability to monitor viruses, study their ecology and anticipate outbreaks. Double-stranded RNA (dsRNA) sequencing is a well-established and reliable method of detecting viruses and studying virome-host interactions and ecology. Compared to total RNA extraction, dsRNA extraction eliminates the majority of host RNAs, improving the recovery of viral RNAs. In this study, we developed and evaluated a novel dsRNA extraction method for high-throughput sequencing (HTS) applications based on the Flock House virus (FHV) B2 protein (B2-based method), and compared its performance with that of established cellulose-based and DRB4-based methods (commercial kit), as well as total RNA extraction techniques. The electrostatic properties of B2 have been instrumental in developing a bead-free and resin-free dsRNA extraction method. The B2-based method demonstrated high viral read recovery, achieving proportions exceeding 20% in most samples, and provided better dsRNA purity with less low weight molecule co-extracted RNA than the DRB4-based method and cellulose-based methods. Despite producing overall fewer total reads than the DRB4-based method, the B2-based enrichment for viral-derived dsRNA was better, with a higher percentage of viral reads, making it effective in virome profiling. Furthermore, it had an excellent detection specificity (0.97) and a good detection sensitivity (0.71), minimising false positives and false negatives. In addition, the B2-based method proved to be highly cost-effective, with a per-reaction cost of $4.47, compared to $35.34 for the DRB4-based method. This method offers a practical solution for laboratories with limited resources or for large-scale sampling for viral ecology studies. Future improvements to the B2-based method should focus on optimising sensitivity to Vitivirus species and developing scalable, automated workflows for high-throughput viral detection.

Keywords: HTS; Viromics; capture sequencing; dsRNA; grapevine virome; viral ecology.

FIGURE 1

Graphical representation of the method using a double‐stranded RNA (dsRNA) binding protein (B) to extract dsRNA from total RNA. The process involves three different buffer solutions: Binding buffer (BB), treatment buffer (TB) and washing buffer (WB) and one dissociation solution (LiCL, ETHOH).

FIGURE 2

Graphical representation of the workflow, from nucleic acid extraction to bioinformatic processing and data analysis, used to handle the results from each of the five nucleic acid extraction methods. Two pipelines, SOVAP and Virtool, were employed, each using different approaches to process raw data from the MiSeq sequencer.

FIGURE 3

dsRNA profiles obtained with different extraction methods. Panel A shows dsRNA extracted using the cellulose method; Panel B, dsRNA extracted using the Plant Viral dsRNA Enrichment Kit (DRB4‐based); and Panel C, dsRNA extracted with the B2‐based method. The gel includes the following samples: (M) XLarge DNA Ladder RTU (GeneDireX Inc.); (1) CO3_36; (2) TM6_75; (3) BacPN4_2; (4) DSJ3_2; (5) Bac9_2; (6) FN_1; (7) P_GPgV; (8) Chaudo_PN9; (9) CA15_6; (10) Comb_9 extract from an equal weight mixture of samples 1–9; and (11) PN_M3_1349 (virus‐free control). The dsRNA samples were run on a 1% agarose gel with 1× SB buffer at 100 V for 30 min and stained with GelRed (EMD Millipore).

FIGURE 4

Comparison of total and viral reads from different samples using five nucleic acid extraction methods (B2, CELL, DRB4, SPEC and CTAB): The bar charts represent the total number of reads (red) and viral reads (green) for each sample, with the viral read percentages indicated by a dashed line. The box plots (red boxes edged in aqua blue for total reads and green boxes edged in red for viral reads) illustrate the distribution of total and viral reads from all extraction methods, emphasising the differences in viral read recovery between techniques. The lower boundary of each box represents the 25th percentile, the line inside the box indicates the median, and the upper boundary represents the 75th percentile. Whiskers (aqua blue for total reads and yellow for viral reads) extend above and below the box, marking the 90th and 10th percentiles. The yellow dashed line indicates the mean for viral reads, while outliers are shown as yellow circles for viral reads and grey squares for total reads.

FIGURE 5

Virome composition of the 11 samples used to assess the efficiency of the five nucleic acid extraction methods compared in this study. The graph represents a total of 10 distinct viral species that were detected: Grapevine rupestris stem pitting‐associated virus (GRSPV), Grapevine leafroll‐associated virus 2 (GLRaV‐2), Grapevine leafroll‐associated virus 3 (GLRaV‐3), Grapevine virus H (GVH), Grapevine virus B (GVB), Grapevine virus E (GVE), Grapevine Pinot Gris virus (GPGV), Grapevine red blotch virus (GRBV), Grapevine Red Globe virus (GRGV) and Nepovirus lycopersici (Tomato ringspot virus, ToRSV). Note that the virus icons in the figure are symbolic and do not reflect the actual morphology of the virions.

FIGURE 6

Heatmap showing the abundance of each virus in five extraction methods (B2‐based, CELL, DRB4, CTAB and SPEC). In this figure, “Expected” refers to the true detection of a virus, based on the criteria outlined in the main text and Figure 2; B2 represents the B2‐based dsRNA extraction method; CELL, the cellulose‐based dsRNA extraction method; DRB4 method, the DRB4‐based extraction method (commercial kit, MBL); CTAB, the cetyltrimethylammonium bromide‐based RNA extraction method; and SPEC, the total RNA extraction method using the Spectrum Kit. Viral abundance is expressed as a percentage of transcripts per kilobase million (TPM).

FIGURE 7

Graphical representation of the results of the receiver operating characteristic (ROC) analysis. Specificity refers to the proportion of healthy plants correctly identified as virus‐free, while sensitivity reflects the proportion of virus‐infected plants correctly identified. The area under the ROC curve (AUC) represents overall accuracy. To, TN, FP and FN denote true positive, true negative, false positive and false negative events, respectively. Each detection event was assigned a random unique value for plotting in the coordinate system. B2 refers to the B2‐based dsRNA extraction method; CELL, the cellulose‐based method; DRB4 method, the DRB4‐based commercial kit; CTAB, the cetyltrimethylammonium bromide‐based RNA extraction method; and SPEC, total RNA extraction using the Spectrum Kit.

FIGURE 8

Breakdown of the costs associated with each of the five extraction methodologies. The total cost per reaction was calculated by compiling the ingredients and quantities of materials consumed in each method. B2 refers to the B2‐based dsRNA extraction method; CELL, the cellulose‐based method; DRB4 method, the DRB4‐based commercial kit; CTAB, the cetyltrimethylammonium bromide‐based RNA extraction method; and SPEC, total RNA extraction using the Spectrum Kit. Rtn stands for reaction.