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INTRODUCTION
Severe fever with thrombocytopenia syndrome virus (SFTSV), a tick-borne virus, induces a clinical disease known as severe fever with thrombocytopenia syndrome (SFTS), characterized by fever, thrombocytopenia, and gastrointestinal symptoms.1 Since its emergence in China in 2009, SFTSV infection has been reported in the Republic of Korea (ROK), Japan, and Taiwan.2345 The increasing risk of SFTSV infection in Asia and the United States are attributed to the expanding distribution of natural hosts, specifically Haemaphysalis longicornis ticks.678 In humans, SFTS poses a critical threat to public health owing to the lack of effective preventive and therapeutic measures. SFTS is a serious infectious disease with a mortality rate of approximately 20%.910
SFTSV has been classified into six distinct clades, referred to as genotypes A–F.11 Among these genotypes, the prevalent strains of SFTSV primarily belong to genotypes A, B, D, and F. Genotype B, especially the B-2 sub-genotype, is the most prevalent in the ROK and Japan, with a higher mortality rate. In China, genotype F is most common, followed by genotypes A and D.1011 Notably, SFTSV genotypes A exhibits relatively low case-fatality rates in the ROK.12 The differences in case fatality rates may be related to the geographical distribution of SFTSV genotypes among nations.12 Previous studies have demonstrated the occurrence of SFTSV reassortment in East Asia. In the ROK, at least nine distinct reassortant genotypes have been identified, whereas seven have been reported in China.1112
Early diagnosis of SFTSV infection is crucial in facilitating clinical care, infection control, and epidemiological investigations.1013 SFTS diagnosis requires the fulfillment of specific criteria, including the isolation of SFTSV from patient samples, detection of SFTSV RNA in the blood or serum, and the presence of SFTSV-specific antibodies in the serum.14 To date, various techniques including reverse transcription-quantitative polymerase chain reaction (RT-qPCR), reverse transcription loop-mediated isothermal amplification, and metagenomic next-generation sequencing (mNGS) have been applied to diagnose SFTSV infection.2151617181920 RT-qPCR provides a sensitive and specific assay for the early clinical diagnosis of SFTS in the acute phase (1–7 days after symptom onset).2122 However, detection declines within 8–14 days, indicating that the sensitivity of RT-qPCR decreases as the viral load decreases.2223 Recently, mNGS has enabled the diagnosis of SFTS in patients presenting with complicated symptoms in China.16 This methodology allows for the rapid and unbiased identification of pathogens in cases where the etiological agent remains unclear.
Inadequate molecular diagnosis of SFTS cases may lead to an underestimation of laboratory-confirmed infections, thereby affecting accurate risk assessment of SFTSV infections.1224 To address this concern, we conducted a comparative analysis of two different RT-qPCR methods and validated the results using multiplex PCR-based NGS to resolve the discrepancies. This study provides insights into the direct improvement of the current molecular diagnostics and genomic surveillance of SFTSV in clinical patients.
METHODS
Study subjects and sample collection
Seventeen patients with suspected SFTS were prospectively enrolled at Chuncheon Sacred Heart Hospital in the ROK between September and December 2022. Clinical data and blood samples were collected, and medical records were reviewed to obtain the clinical data of the study subjects. Serum samples from 17 patients with suspected SFTS were transferred to the Gangwon Institute of Health and Environment (GIHE) for laboratory diagnosis of SFTSV. Whole blood samples were collected and transferred to the Infectious Diseases Laboratory at the Asan Medical Center (AMC) on the day of collection.
Laboratory diagnosis by RT-qPCR/GIHE and RT-qPCR/AMC
For the RT-qPCR/GIHE method, total RNA was extracted using the QIAamp Viral RNA Mini kit (Qiagen, Hilden, Germany), and the detection of SFTSV was conducted using the PowerChek™ SFTSV (S/M segment) Real-time PCR kit (Kogene Biotech, Seoul, Korea). The primer and probe sequences were listed at Supplementary Table 1. The RT-qPCR was performed using 20 μL of the mixture, including 5 μL RNA sample, 2 μL Primer (590 nM)/Probe (140 nM), 0.8 μL 25 × Agpath ID (Ambion, Austin, TX, USA) enzyme Mix, 10 μL 2 × buffer, 2.2 μL nuclease-free distilled water (DW). If the cycle threshold (Ct) values for both SFTSV M and S segments were < 35, the sample was positive for SFTSV. If the Ct value of either the M or S segments was > 35, it was considered SFTSV negative.
RT-qPCR/AMC was performed using LightCycler Multiplex RNA Virus Master Mix (Roche, Indianapolis, IN, USA). The RT-qPCR was performed in a 20 μL of the mixture, containing 5 μL RNA sample, 4 μL 5 × RT-qPCR Mix, 1 μL of each 10 pmol primer, 0.5 μL of each 10 pmol probe, 1 μL 20 × RT enzyme, and 2.5 μL DW.25 The primer and probe sequences were described at Supplementary Table 2. The viral load was determined by the mean log10 of the M and S segments. If the mean log10 of M or S segments was > 1, it was considered SFTSV positive. If the value of both M and S segments were < 1, they were negative for SFTSV. The cycling conditions of RT-qPCR/GIHE and RT-qPCR/AMC are shown in Table 1.
Table 1
Comparison of two real-time RT-qPCR methods used in this study
RT-qPCR = reverse transcription-quantitative polymerase chain reaction, GIHE = Gangwon Institute of Health and Environment, AMC = Asan Medical Center, SFTSV = severe fever with thrombocytopenia syndrome virus, Ct = cycle threshold.
aThe value of the viral load is the mean in log10 of the M and S segments. The copy numbers of the viruses were determined using a standard curve.
Amplicon-based next-generation sequencing (NGS)
Amplicons were generated using SFTSV-specific primer mixtures and Solg 2 × Uh-Taq PCR Smart mix (Solgent, Seoul, Korea). The primers were pooled into three different pools and the PCR reactions were separated according to the segments. The reaction mixture consisted of 12.5 μL 2 × Uh pre-mix, 10.0 μL of primer mixtures, 1.0 μL cDNA template, and 1.5 μL DW in 25 μL and the multiplex PCR was done one time. The multiplex PCR products were pooled and purified using AMPure XP beads (Beckman Coulter, Brea, CA, USA). The SFTSV-specific primer mixtures and PCR cycling conditions were previously described.26 The amplicons were prepared using a Ligation Sequencing Kit (SQK-LSK109) and a Native Barcoding Kit (EXP-NBD104) according to the manufacturer’s instructions (Oxford Nanopore Technologies, Oxford, UK). The libraries were purified using AMPure XP beads (Beckman Coulter). Barcoded libraries were pooled, ligated to sequencing adapters, and sequenced using a MinION device by loading onto a FLO-MIN106 (R9.4; Oxford Nanopore Technologies) flow cell for minimum 14 hours. Porechop (v.0.2.4) was used for trimming the adapter and demultiplexing the barcode. Demultiplexing option was single barcoding with filter threshold over 85 and trimming mid threshold at 50. The reads were mapped to the reference genome sequence (SFTSV SPL114A), and consensus sequences were extracted using CLC Genomics Workbench (v7.5.2; Qiagen). Samples containing the ratio of viral reads to total reads < 1% was designated as a SFTSV negativity. Accession numbers of the SFTSV genomes, deposited in GenBank, are listed in Supplementary Table 3.
Phylogenetic analysis
Genomic sequences of SFTSV were aligned using the ClustalW method in Lasergene version 5 (DNASTAR, Madison, WI, USA). Phylogenetic analysis was performed using the best-fit General Time Reversible (GTR) + Gamma (G) + Invariable (I) (for L and M segments) and Kimura 2-parameter (K2) + G (for S segment) substitution models of evolution using the maximum-likelihood (ML) method in MEGA X. Topologies were evaluated using bootstrap analysis of 1,000 iterations.
Genetic reassortment analysis
To estimate genetic reassortment events, a graph incompatibility-based reassortment finder (GiRaF) analysis was performed.27 Nucleotide alignments of SFTSV tripartite genome were used as an input source for Bayesian analysis. In total 1,000 unrooted candidate trees were estimated using the GTR + G + I substitution model sampled every 200 iterations with a 25% burn-in. The analysis was repeated 10 times with 10 independent MrBayes-based tree data per segment. The default value for the confidence threshold was 0.7 for the data set.
A tanglegram algorithm was applied for evaluating the genetic reassortment event and comparing different evolutionary patterns of SFTSV genomes. The method was implemented using the R package “dendextend.”28
Ethics statement
The study protocol was approved by the Institutional Review Board (IRB) of Hallym University Chuncheon Sacred Heart Hospital (IRB No. 2022-06-005-002). Written informed consent for participation in the study and blood sample collection was obtained from all patients. The study complied with the principles of the Declaration of Helsinki.
RESULTS
Clinical characteristics of patients with suspected SFTS in this study
The clinical characteristics of patients enrolled in this study are shown in Table 2 and Supplementary Table 4. A total of 17 patients hospitalized for fever, 88.2% (15/17) had an epidemiological association and 35.3% (6/17) had gastrointestinal symptoms. Thrombocytopenia occurred in 76.5% (13/17) of patients, leukopenia in 47.1% (8/17), and aminotransferase elevation in 82.4% (14/17). Approximately, 29.4% (5/17) required admission to the intensive care unit, and gram-negative bacteremia was concomitant in 23.5% (4/17) including N39, N41, N70, and N82. All of patients were negative for both influenza and coronavirus disease 2019 (COVID-19). Except for one patient (N49) diagnosed with scrub typhus, 16 patients with suspected SFTS tested negative in serological tests for scrub typhus, leptospirosis, and hemorrhagic fever with renal syndrome.
Table 2
Characteristics of patients with suspected severe fever with thrombocytopenia syndrome enrolled at Chuncheon Sacred Heart Hospital from September to December in 2022 (N = 17)
Comparison of laboratory diagnostics of patients with suspected SFTS using RT-qPCR
Among 17 samples, RT-qPCR/GIHE exhibited Ct values < 35 for both M and S segments in samples N39 and N50, classifying them as positive for SFTSV. The remaining samples yielded undetectable results for SFTSV when subjected to RT-qPCR/GIHE (Table 3). Meanwhile, RT-qPCR/AMC identified only 4 SFTSV-negative samples (N20, N21, N25, and N49) with mean log10 values < 1 for both M and S segments. Additionally, two samples (N38 and N51) tested positive for either M or S segments, with the other 11 samples testing positive for both segments. RT-qPCR/AMC categorized 13 samples as positive and four samples as negative. Consequently, two samples (N39 and N50) were considered positive, and four samples (N20, N21, N25, and N49) were identified as negative by both assays, while the remaining 11 samples exhibited discordant results between the two assays.
Table 3
Comparison of real-time RT-qPCR results of 17 patients with suspected severe fever with thrombocytopenia syndrome
Gray indicates the clinical samples that were significantly observed for SFTSV genomes by Amplicon-based NGS. Green indicates the result of RT-qPCR/AMC for SFTSV.
RT-qPCR = reverse transcription-quantitative polymerase chain reaction, GIHE = Gangwon Institute of Health and Environment, AMC = Asan Medical Center, Neg = negative, Pos = positive, ND = not determined, Ct = cycle threshold, SFTSV = severe fever with thrombocytopenia syndrome virus, NGS = next-generation sequencing.
Whole-genome sequencing of SFTSV using amplicon-based NGS
Nearly whole-genome sequences of SFTSV were recovered from samples N39 and N50, in which SFTSV had already been detected for SFTSV by both RT-qPCR assays (Table 4, Supplementary Fig. 1). Among the 11 samples previously diagnosed as positive by RT-qPCR/AMC, five samples (N41, N55, N56, N60, and N64) contained reads of SFTSV tripartite genomes ranging from 1.8 to 4.6% of the total reads. However, the remaining six samples (N38, N51, N70, N78, N82, and N83) showed an insignificant number of SFTSV reads, which were designated as negative. Samples N20, N21, N25, and N49 were negative for SFTSV by the NGS as well as RT-qPCR assays.
Table 4
Summary of total reads and read mapping to SFTSV strain SPL114A reference genome using multiplex PCR-based NGS
The comparative analysis of multiplex PCR-based NGS with two RT-qPCR methods are shown in Table 5. Among the 17 samples, the RT-qPCR/GIHE method showed discrepancies in five samples that were determined as positive via NGS. However, the RT-qPCR/AMC method yielded different results for six samples that were identified as negative via NGS. The concordance rates with NGS for RT-qPCR/GIHE and RT-qPCR/AMC were 70.6% and 64.7%, respectively. The difference in the concordance rate was statistically insignificant.
Phylogenetic analysis of SFTSV obtained from samples of SFTS patients
Nearly full-length genome sequences of SFTSV obtained from patients N39 and N50 were inferred to phylogenetic analysis. The patient sample N39 was clustered with genotype A in all segments of SFTSV. The SFTSV L, M, and S segments of N50 showed various levels of phylogenetic incongruence: The L segment shared common ancestors with sub-genotype B-1, whereas M and S segments belonged to the B-2 sub-genotype (Fig. 1).
Fig. 1
Phylogenetic analysis of severe fever with thrombocytopenia syndrome virus from patients with SFTS in Chuncheon, 2022. The phylogenetic trees were generated using maximum likelihood methods in MEGAX with bootstrap 1,000 iterations based on the ORF regions of the SFTSV (A) L (60–6,271 nt), (B) M (19–3,240 nt), and (C) S (70–1,703 nt) segments. The scale bars indicate the number of nucleotide substitutions per site. The numbers at each node are bootstrap probabilities determined for 1,000 replicates. The SFTSV obtained in this study is shown in red. The genetic clades indicate six genotypes (A–F) and three sub-genotypes (B1 to B-3) in the right panel.
SFTS = severe fever with thrombocytopenia syndrome, ORF = open reading frame, SFTSV = severe fever with thrombocytopenia syndrome virus.
Genetic reassortment of SFTSV
The GiRaF analysis demonstrated a reassortment event between the L and S segments of the SFTSV in N50 sample. However, the genetic exchange was undetectable between M and the other two segments. Based on tanglegram analyses (Fig. 2), N39 showed no reassortment events in any of the segments, indicated by parallel auxiliary lines in the center that connect phylogenetic trees. Notably, reassortment events were observed in the L–M and L–S segments of N50. This data may show a genomic configuration with the exchange of L segment in SFTSV N50.
Fig. 2
Tanglegram comparing the phylogenies between each segment of severe fever with thrombocytopenia syndrome virus in South Korea. Tanglegram comparing phylogenies between each segment of SFTSVs tripartite genomes (A) L–M segments, (B) L–S segments, and (C) M–S segments. The tanglegram was generated using the R package, using consensus maximum likelihood topologies based on the nucleotide sequences of each SFTSV genome. Letters for taxa are indicated in red for the SFTSV genome found in this study. The tanglegrams illustrate putative reassortment events by highlighting when two segments from the same viral isolate appear in different configurations between their respective ML trees.
SFTSV = severe fever with thrombocytopenia syndrome virus, ML = maximum-likelihood.
DISCUSSION
Rapid and accurate laboratory diagnosis of SFTS is crucial for effectively treating severe infectious diseases with non-specific clinical symptoms.29 In this study, discrepancies in the molecular diagnostics of SFTSV were observed in two molecular assays, RT-qPCR/GIHE and RT-qPCR/AMC. Amplicon-based NGS was implemented to complement and validate the RT-qPCR analysis in clinical patients. The high-throughput sequencing showed robust sensitivity for the direct detection of SFTSV in clinical samples containing ultra-low copies of viral genomes. Nearly whole-genome sequences of SFTSV were obtained from Patients N39 and N50, previously positive by both RT-qPCR/GIHE and RT-qPCR/AMC. Out of 11 discordant samples from two RT-qPCR assays, the reads of SFTSV were significantly detected in only five that were positive by RT-qPCR/AMC, whereas the six samples yielded insufficient viral reads in accordance with the negative results obtained from RT-qPCR/GIHE. In addition, N39 formed a genetic lineage with genotype A in all segments. In contrast, N50 grouped with B-1 sub-genotype for the L segment and B-2 sub-genotype for M and S segments, indicating a very likely reassortant between sub-genotypes.
In a previous study, RT-qPCR was used to detect SFTSV infection in China and Japan.18 However, RT-qPCR has limitations in detecting ultra-low copy numbers of SFTSV. This study was conducted to investigate whether amplicon-based NGS enables to overcome the limitations of RT-qPCR assays. Multiplex PCR-based NGS recovered nearly whole-genome sequences of SFTSV directly from tick samples.26 Here, nearly full-length genomes of SFTSV were obtained from Patients N39 and N50, with genome coverages of 99.4%, 98.8%, and 97.7% for the L, M, and S segments, respectively. Notably, the viral genome was acquired from five of the 11 discordant samples containing ultra-low viral copies. However, the number of reads was insignificantly detected in six out of the 11 discordant samples, falling below the threshold for sample barcode bleeding (0–2%).30 Sample-barcode bleeding may occur when free barcodes from samples containing low amounts of DNA molecules are ligated to non-barcoded DNA from samples with high molecule overloads.31 Here, the NGS outcomes validated the molecular diagnosis of SFTSV using the RT-qPCR assays, wherein five samples were classified as positive and six as negative. The concordance rates of amplicon-based NGS with RT-qPCR/GIHE and RT-qPCR/AMC were 70.6% and 64.7%, respectively. Amplicon-based NGS provides validation and criteria for determining SFTSV positivity via laboratory molecular diagnoses, aiding physicians in diagnosing patients with SFTS.
Genetic diversity and molecular evolution in viral genomes result from genetic reassortment when segmented RNA viruses shuffle their genetic materials. In nature, genome exchanges occur between intra- and inter-lineage SFTSV, leading to the formation of novel genotypes.26 Most Korean SFTSVs (69.2%) belong to genotype B, consisting of three sub-genotypes: B-2 (36.1%), B-3 (21.1%), and B-1 (12%).12 In total, 17 of 116 strains from South Korea showed reassortants with the genomic configuration of nine forms.12 In this study, the L segment of SFTSV revealed a divergent evolutionary pattern compared to the M and S segments. These findings implied that SFTSV N50 carries the B-1 subtype for the L segment and B-2 subtype for the M and S segments in the genomic organization. A comprehensive understanding of the genetic diversity and evolutionary dynamics of SFTSV markedly enhances surveillance, diagnosis, and control strategies against SFTS. Further investigations into the pathogenicity of reassortant strains are required to address potential risks associated with severe clinical outcomes.
This study has limitations owing to the small number of patient samples and systemic sample collection. Continuous large-scale studies should be beneficial for enhancing the accuracy and reliability of SFTS prevalence and molecular diagnosis. In this study, the delayed delivery of samples to the amplicon sequencing might account for our inability to detect SFTSV, potentially leading to the negativity of NGS results. It is crucial to establish an optimized procedure for the clinical sample collection and transport, facilitating rapid and accurate molecular diagnostics of SFTSV. The serological test of SFTSV patients is necessary to accurately assess the sensitivity and specificity of RT-qPCR and NGS in confirming infectious status.
In conclusion, this study demonstrated that amplicon-based NGS resolves the discrepancies in the molecular diagnosis of SFTSV using different RT-qPCR methods. These observations provide a comprehensive understanding of the prevalence and genomic characterization for the tick-borne disease. Thus, this report raises awareness and caution for physicians about the molecular diagnosis and epidemiology of SFTS using NGS technologies.
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