
==== Front
Poult Sci
Poult Sci
Poultry Science
0032-5791
1525-3171
Elsevier

S0032-5791(24)00720-X
10.1016/j.psj.2024.104141
104141
ANIMAL WELL-BEING AND BEHAVIOR
Development and application of a novel recombinase polymerase amplification-Pyrococcus furiosus argonaute system for rapid detection of goose parvovirus
Liu Yaqun *‡§1
Chen Lianghui †1
Zhang Zhenxia *
Zhang Rong *
Xu Jinyu *
Yang Peikui *
Sun Yanjie *
Chen Yicun ‡
Xie Chengsong §
Lin Min *†
Zheng Yuzhong zhengyuzhong@gmail.com
*†2
⁎ Guangdong Key Laboratory of Functional Substances in Medicinal Edible Resources and Healthcare Products, Hanshan Normal University, Chaozhou 521041, China
† Industrial College of Biomedicine and Health Industry, Youjiang Medical University for Nationalities, Baise 533000, China
‡ Shantou University Medical College, Shantou 515000, China
§ Guangdong Taiantang Pharmaceutical Co., Ltd. Shantou 515000, China
2 Correspondence author: zhengyuzhong@gmail.com
1 These authors contributed equally to this work.

03 8 2024
10 2024
03 8 2024
103 10 1041417 4 2024
25 7 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Rapid and accurate detection of goose parvovirus (GPV) is crucial for controlling outbreaks and mitigating their economic impact on the poultry industry. This study introduces recombinase polymerase amplification combined with the Pyrococcus furiosus argonaute (RPA-PfAgo) system, a novel diagnostic platform designed to address the limitations of traditional GPV detection methods. Capitalizing on the rapid DNA amplification of RPA and stringent nucleic acid cleavage by the PfAgo protein, the RPA-PfAgo system offers high specificity and sensitivity in detecting GPV. Our optimization efforts included primer and probe configurations, reaction parameters, and guided DNA selection, culminating in a detection threshold of 102 GPV DNA copies per microlitre. The specificity of the proposed method was rigorously validated against a spectrum of avian pathogens. Clinical application to lung tissues from GPV-infected geese yielded a detection concordance of 100%, surpassing that of qPCR and PCR in both rapidity and operational simplicity. The RPA-PfAgo system has emerged as a revolutionary diagnostic modality for managing this disease, as it is a promising rapid, economical, and onsite GPV detection method amenable to integration into broad-scale disease surveillance frameworks. Future explorations will extend the applicability of this method to diverse avian diseases and assess its field utility across various epidemiological landscapes.

Key words

goose parvovirus
recombinase polymerase amplification (RPA)
Pyrococcus furiosus argonaute (PfAgo)
rapid detection
==== Body
pmcINTRODUCTION

Goose parvovirus (GPV) is the aetiological agent of Derzsy's disease (also known as goose hepatitis), goose plague, and viral enteritis (Brown et al., 1995, Niu et al., 2018). GPV predominantly infects geese (Anser anser domestica) and Muscovy ducks (Cairina moschata), leading to an acute disease course, high mortality, and rapid transmission, thus posing significant threats to the waterfowl farming industry and resulting in substantial economic losses (Glavits et al., 2005). In recent years, the age of GPV-susceptible populations has shown an increasing trend, with the disease manifesting in sporadic epidemics, complicating epidemiological control efforts. GPV belongs to the genus Parvovirus within the family Parvoviridae and is a nonenveloped, single-stranded linear DNA virus with a genome of approximately 5.1 kb encoding 3 structural proteins: VP1, VP2, and VP3 (Tu et al., 2018). VP3, the main structural protein of the virus, is highly conserved and capable of inducing the production of neutralizing antibodies in the host, making it the primary immunogenic protein of GPV (Tarasiuk et al., 2019).

Traditional GPV detection methods, such as virus isolation and identification (Tarasiuk et al., 2019), polymerase chain reaction (PCR) detection (Ma et al., 2022), TaqMan real-time PCR (Wan et al., 2019), high-resolution melting curve analysis (HRM) (Dong et al., 2019), and enzyme-linked immunosorbent assay (ELISA) (Tarasiuk et al., 2019) are time-consuming and costly and require stringent equipment specifications, rendering them unsuitable for large-scale rapid field testing. Therefore, rapid, simple, and low-cost detection methods are needed. The applications of loop-mediated isothermal amplification (LAMP) (Liu et al., 2023), recombinase polymerase amplification (RPA) (Liu et al., 2019), and their derivative technologies for GPV detection have been reported (Yang et al., 2017). Given the high efficiency, specificity, and low equipment requirements of RPA across a broad temperature range, this study adopted this method. To further improve the detection specificity and sensitivity, the cleavage capability of PfAgo, an Argonaute protein derived from the archaeon Pyrococcus furiosus, was integrated into the assay. PfAgo can precisely cleave specific nucleic acid sequences, and by designing small DNA molecules that target specific sequences within GPV, it can accurately identify and cleave GPV genomic DNA, eliminating nonspecific amplification products and potential contaminants (Swarts et al., 2015). The introduction of PfAgo technology has significantly improved the specificity of the detection process and enhanced the ability to detect low-copy-number viruses, increasing the accuracy and sensitivity of GPV detection. RPA combined with PfAgo technology has been used for the detection of pathogens such as rice viruses (Liu et al., 2023), shrimp white spot syndrome virus (Wang et al., 2023), Enterocytozoon hepatopenaei (Yang et al., 2023), and Mycoplasma synoviae (Zhao et al., 2023), demonstrating its effectiveness as a novel strategy for pathogen detection.

The establishment of the RPA-PfAgo detection system provides a vital tool for the rapid and accurate diagnosis of GPV and is expected to transform the current state of avian disease management. This technology not only offers direct benefits for disease control but also paves new pathways for pathogen detection in the poultry industry worldwide and in the broader field of animal health. Future research will aim to refine this technique, explore its application in a wider array of avian diseases, incorporate it into comprehensive disease surveillance programs, and provide poultry farmers and veterinarians with the necessary tools to swiftly identify and respond to infectious threats, thereby safeguarding flock health and ensuring the sustainability of poultry production worldwide.

MATERIALS AND METHODS

RPA Primer, gDNA, and Probe Design for GPV RPA-RPA-PfAgo

The conserved sequence of the VP3 gene of GPV (Gene ID: 1403425) was downloaded from the NCBI database. Using Primer Premier 5 software, 3 sets of RPA primers were designed on the basis of the conserved sequence. The specificity of the designed primers was verified using the primer-BLAST tool of the NCBI. Additionally, on the enzymatic cleavage characteristics of the PfAgo protein, guide DNAs (gDNAs) were designed to include the RPA primer sequences (He et al., 2019). Four gDNA sequences and their corresponding probes were designed; the probes were modified with either FAM or ROX, and the 5′ ends of the gDNAs were phosphorylated (Table 1). The designed primers, gDNAs, and probes were subsequently synthesized by the GENEWIZ laboratory (Jiangsu, China).Table 1 RPA primers, gDNA, and probe design for GPV RPA-PfAgo.

Table 1Primer/gDNA/Probe name	Label	Sequence (5′-3′)	
RPA Primers	F1	TCACAACGCAGGATCAGACAAAGACCATTG	
F2	CAATCTCACCTCAACAATTCAAGTCTTTACG	
F3	TGAGCATCAACTCCCGTATGTCCTGGGCTCG	
R1	TCAAAGTCAAATGTGAACTCAAAGTTGTTG	
R2	GAATGAGCGAACATGCTATGGAAAGGAACT	
R3	GGTTCATCAGCCTGTCTAAGTCCTGTGAAT	
PfAgo-gDNA	gDNA1-1	TCCGACGGGAACGGCG	
gDNA1-2	TGGCAGGGCATAGACA	
gDNA6-1	TCATAGACATCCGACG	
gDNA6-2	TCCGTACTGCGGCAGG	
gDNA25-1	TTGAACCGTGCTCCAT	
gDNA25-2	TAATGCACTACGGTCA	
gDNA31-1	TCAGTAGAATGCACTA	
gDNA31-2	TGGTCATTGAACCGTG	
qPCR Primers	F	AGTCACAACGCAGGATCAGA	
R	TCTGGTTGGTGTGCATTGTG	
Probes	Probe1	FAM-TGCGGCAGGGCATAGACATCCGACGGGAA-BHQ1	
ROX-TGCGGCAGGGCATAGACATCCGACGGGAA-BHQ2	
Probe2	FAM-AGAATGCACTACGGTCATTGAACCGTGCT-BHQ1	
ROX-AGAATGCACTACGGTCATTGAACCGTGCT-BHQ2	

Construction of Recombinant Plasmid

The complete genome sequence of GPV was retrieved from the NCBI database (accession number: NC_001701.1). A specific fragment of the GPV genome was synthesized, cloned, and inserted into the pUC57 vector, resulting in the recombinant plasmid pUC57-GPV. The initial concentration of the plasmid was 287 ng/μL, and the target fragment was 687 bp in length. The copy number concentration (copies/μL) was calculated using the following formula: Copy number concentration (copies/μL) = 6.02 × 1023 (copies/mol) ×DNA concentration (g/μL)/molecular weight of full transcript (g/mol) (Zhao et al., 2020). On the basis of these calculations, the initial concentration of the plasmid was 3.89 × 1011 copies/μL. Serial tenfold dilutions were performed to obtain plasmid copy number concentrations ranging from 3.89 × 108 to 3.89 × 10° copies/μL for subsequent experimental studies.

Establishment and Optimization of the RPA System

RPA was carried out using a TwistDx basic RPA kit (TwistDx, UK). The reaction mixture consisted of 29.5 μL of A buffer, 2.4 μL each of the forward and reverse primers at 10 μM, 2 μL of template DNA, and varying volumes of magnesium acetate (MgAc, 280 mM), with the final volume increased to 50 μL with ddH2O. After mixing and centrifuging, the reaction mixture was incubated at 39°C for 30 min in a PCR thermocycler or an isothermal heating device. The RPA amplification products were subsequently assessed via agarose gel electrophoresis. The intensity of the bands was quantified using ImageJ software (v1.8.0, National Institutes of Health, USA; http://www.imagej.softonic.de) (Schroeder et al., 2021). The optimization process involved systematic variations in the MgAc concentration, reaction temperature, and reaction time. MgAc (280 mM) concentrations of 2.0, 2.2, 2.5, 2.8, and 3.0 μL were tested, and the reaction temperatures were evaluated at 35°C, 37°C, 39°C, 42°C and 45°C. Reaction times of 10, 15, 20, 25, and 30 min were also explored. During the comprehensive optimization of the RPA system, only the optimized conditions were varied, while all of the other conditions were held constant. A negative control using ddH2O as the template was included. Each experiment was performed in triplicate.

RPA-PfAgo Cleavage Assay

The RPA reaction was conducted following the protocol provided by TwistDx, Inc., UK. The lyophilized reagents were reconstituted by adding 29.5 μL of Buffer A, 2 μL of DNA template, 2 μL of each RPA primer (10 μM), 12.5 μL of deionized water, and 2.5 μL of MgAc (280 mM) to the reaction mixture. After thorough mixing by inversion and centrifugation, the reaction mixtures were incubated at 36°C for 25 min. Subsequently, 4 μL of the amplified product was mixed with 25 μL of PfAgo reaction mixture containing the following: gDNA1-1 (20 μM, 4 μL), gDNA1-2 (20 μM, 4 μL), molecular beacon (MB, 20 μM, 1 μL), PfAgo enzyme (JY0316-L, Tiosbio, 200 U/μL, 2 μL), MnCl2 (250 nM, 4 μL), 10 × buffer (2 μL), ddH2O (4 μL), and the RPA product (4 μL). The PfAgo cleavage experiment was performed with a SLAN® 965 instrument (Hongshi, Shanghai, China) at 95°C for 30 min, and the FAM fluorescence was recorded at 30-second intervals. Upon completion of the reaction, the tubes were imaged using a GelView 6000Plus Intelligent Image Workstation (Boluteng, Guangzhou, China) under blue light (470 nm) and green light (525 nm).

Optimization of the RPA-PfAgo System

The optimization of the RPA-PfAgo system for the precise detection of GPV involved fine-tuning key parameters, including the concentrations of gDNA, MnCl2, fluorescent probes, the PfAgo enzyme, and the amount of RPA product incorporated into the reaction mixture. The gDNA concentrations were adjusted to 10 μM, 20 μM, 40 μM, 60 μM, 80 μM, or 100 μM. Similarly, the concentrations of the fluorescent probes were optimized to the same micromolar range. The volumes of MnCl2 (250 mM), the PfAgo enzyme (200 U/μL), and the RPA product were adjusted to 1, 2, 3, 4, 5, and 6 μL, respectively. During the optimization process of the RPA-PfAgo detection method, all of the other parameters remained constant except for the parameter being optimized. A negative control with ddH2O as the template was included in the analysis. To ensure the reliability and consistency of the results, each concentration of each parameter was independently replicated in triplicate.

Sensitivity, Repeatability, and Specificity Assays

Sensitivity Evaluation: The sensitivity of the RPA-PfAgo detection method was evaluated by using a serial dilution of positive plasmid DNA, ranging from 3.89 × 108 to 3.89 × 10° copies/μL, to serve as a template for the amplification reaction according to the optimized RPA-PfAgo protocol. A negative control was included to validate the lower limit of detection.

Repeatability Assessment: To assess repeatability, the assay was performed with fixed concentrations of 3.89 × 108 copies/μL and 3.89 × 102 copies/μL of the positive control plasmid. The amplification was executed under optimal conditions that were previously established, maintaining uniformity in the reaction mixture, temperature, and timing. The procedure was repeated 3 times, and the coefficient of variation (CV) was calculated using the following formula: CV = (standard deviation/mean) × 100% (Memon et al., 2024).

Specificity analysis: Specificity was tested by conducting RPA-PfAgo amplification with DNA from six different pathogens: GPV, Muscovy duck parvovirus (MDPV), duck plague virus (DPV), duck circovirus (DuCV), Klebsiella pneumoniae (K. pneumoniae), and Escherichia coli (E. coli). The samples were provided by the Guangdong Provincial Key Laboratory of Functional Substances and Healthy Products for Medicinal Food Resources. These pathogens were isolated from different clinical samples and were cultured and characterized by Prof. Yuzhong Zheng using standard methods. A negative control was also used to ensure that the amplification was specific to the target DNA, confirming the specificity of the detection method.

Quantitative Polymerase Chain Reaction Protocol

qPCR primers for the detection of GPV were designed using Primer Premier 5 software (Table 1). qPCR was performed using 2× SGExcel FastSYBR Mixture (Sangon, Shanghai, China). The reaction mixture consisted of 12.5 µL of SYBR Green premix, 0.5 µL of forward and reverse primers at a final concentration of 500 nM each, 2 µL of DNA template, and nuclease-free water to a final volume of 25 µL. The thermal cycling protocol was initiated by denaturation at 95°C for 3 min, followed by 40 cycles of 95°C for 5 seconds and 60°C for 20 seconds for annealing and extension, respectively, with fluorescence detection at the end of each cycle. A threshold cycle (Ct) value of less than 30.0 was considered indicative of a positive result in accordance with established qPCR interpretive standards.

PCR Amplification Procedure

PCR amplification was carried out with extracted DNA serving as the template. The reaction mixture had a total volume of 25 µL and contained 12.5 µL of 2× Taq PCR MasterMix (TIANGEN, Beijing, China), 1 µL of each forward and reverse primer at a concentration of 10 µM, 2 µL of the viral DNA template, and 8.5 µL of water. The thermal cycling procedure commenced with initial denaturation at 95°C for 5 min; 35 cycles of 95°C for 45 s, 54°C for 45 s, and 72°C for 30 s; and a final extension at 72°C for 10 min and a holding temperature of 4°C. The PCR products were analysed by 1.0% agarose gel electrophoresis to verify the amplification of the target bands.

Clinical Validation

In this study, 46 lung tissue samples were collected from geese confirmed to have succumbed to goose parvovirus infection through standard veterinary autopsy procedures, and the collection took place between January and March 2023 at breeding farms in Jiangsu Province, China. After collection, the lung tissues were sectioned into approximately 50 mg fragments and placed into sterile centrifuge tubes containing 1 mL of phosphate-buffered saline (PBS). The samples underwent 3 freeze‒thaw cycles between -80°C and room temperature. Then, the tissue samples were pulverized into a fine powder with liquid nitrogen in a mortar, and nucleic acids were subsequently extracted from the powdered tissues using a DNA extraction kit (Sangon, Shanghai, China). The extracted nucleic acid samples were then tested via the established RPA-PfAgo detection method, qPCR, and PCR electrophoresis analysis.

RESULTS

Design and Construction of the RPA-PfAgo Detection Platform for GPV

The construction of the RPA-PfAgo detection platform for GPV involved a series of optimizations grounded in the following design principles. Given the dependency of the nuclease activity of the PfAgo protein on its interaction with a specific gDNA sequence, the length of the gDNA was initially carefully tailored. Guide sequences shorter than 15 nucleotides (nt) may lack the necessary binding stability for effective target strand cleavage, whereas overly long gDNA sequences might impede cleavage efficiency owing to steric hindrance (He et al., 2019). Consequently, 16 nt gDNA was chosen to balance the binding affinity and cleavage efficiency. To increase the detection sensitivity, RPA technology was utilized, as this method enables rapid DNA amplification at ambient temperature and eliminates the need for thermal cycling intrinsic to traditional PCR methods. RPA, with its specific primers and enzyme cocktail, facilitates significant DNA amplification within a brief timeframe, providing sufficient substrate for PfAgo-mediated cleavage. Additionally, the selection of target sequences for the PfAgo protein took into consideration the necessity for complementarity between gDNA and the target DNA region. The target sequences were meticulously selected and validated to ensure that the PfAgo protein could effectively identify and cleave GPV-specific DNA sequences, thus increasing the specificity of the detection. In the context of primer design, the conserved VP3 sequence of the GPV genome was chosen to guarantee the system's efficacy in identifying all GPV variants, even in the face of viral mutations. For real-time amplification monitoring, fluorescent markers were integrated into the primers. The intensification of the fluorescent signal concurrent with the RPA-PfAgo reaction permits real-time tracking via specialized detection equipment, enabling swift diagnostic processes. The collective enhancements in gDNA length, RPA amplification efficiency, PfAgo cleavage specificity, and real-time monitoring have led to the development of an advanced and highly specific GPV RPA-PfAgo detection platform, representing an innovative technological advance for the prompt diagnosis and management of GPV (Figure 1A).Figure 1 Design principles of the GPV RPA-PfAgo platform and RPA optimization strategies. (A) Conceptual design of the GPV RPA-PfAgo detection platform. (B) Assessment of the selection and repeatability of the RPA primers. (C) Optimization of the reaction conditions for RPA, including MgAc (280 mM): 2.0, 2.2, 2.5, 2.8, and 3.0 μL. Reaction temperatures: 35, 37, 39, 42, 45°C. Reaction times: 10, 15, 20, 25, and 30 min. Band intensities were quantified using ImageJ software. NC: negative control (ddH2O); M: DNA molecular weight marker.

Figure 1

Optimization of RPA Conditions for the RPA-PfAgo Detection Platform

Increasing the efficiency and sensitivity of the GPV RPA-PfAgo detection platform necessitated the systematic selection and optimization of RPA primers. Initially, 3 primer sets were designed and evaluated in combination, which led to the identification of a highly luminous downstream R2 primer. This primer was subsequently paired with various upstream primers to identify the combination with the highest amplification efficiency, resulting in the selection of the F1R2 pair. Agarose gel electrophoresis revealed that the amplification products of the F1R2 primer pair were both distinct and intensely bright, indicating that this primer pair was the optimal primer pair (Figure 1B). Moreover, the MgAc concentration in the RPA reaction was fine-tuned. Studies with different MgAc concentrations revealed that adding 2.8 μL of MgAc at 39°C produced the brightest and most distinct specific fragment. An increase in the MgAc concentration led to reduced brightness and diffusion of the product bands, thus establishing 2.8 μL as the optimal volume. Temperature optimization for the RPA reaction involved setting various reaction temperatures. At 39°C, clear and specific amplification bands were observed. However, increasing the temperature to 42°C caused a decrease in band brightness and an onset of dispersion. Consequently, 39°C was determined to be the optimal reaction temperature for RPA. Optimization of the reaction time for RPA was also conducted. At the established optimal temperature of 39°C, different durations were tested, revealing that the product bands were most distinct at 25 min. As the reaction time increased, the clarity of the bands decreased. Hence, for expedient detection, a reaction time of 25 min was deemed optimal (Figure 1C).

Selection of Guide DNA for the RPA-PfAgo Detection Platform

For gDNA screening within the GPV RPA-PfAgo detection platform, 4 gDNAs (gDNA1, gDNA6, gDNA25, and gDNA31) were synthesized, each labelled with either fluorescein amidite (FAM) or rhodamine X (ROX). All gDNAs produced fluorescent signals upon assay activation. Quantitative fluorescence analysis revealed that the ROX-labelled primers yielded significantly stronger signals and faster activation kinetics than did their FAM counterparts. Specifically, the gDNA31 set presented the highest fluorescence intensity in the FAM channel, a finding that was mirrored in the ROX channel. These results were corroborated by imaging with a fluorescence detection system. Accordingly, gDNA31 was selected as the prime candidate for further experimentation (Figure 2A).Figure 2 Multiparametric optimization of the GPV RPA-PfAgo detection platform. (A) Selection of gDNA candidates. (B) gDNA concentration tuning. (C) MnCl2 concentration adjustment. (D) Probe concentration refinement. (E) PfAgo concentration calibration. (F) RPA product concentration fine-tuning. The fluorescence intensity (× 104) was plotted against time (min). NC, negative control; Con, concentration; FAM, fluorescein amidite; ROX, rhodamine X.

Figure 2

Multiparametric Optimization for the RPA-PfAgo Detection Platform

In the optimization study of the GPV RPA-PfAgo detection platform, the concentrations of key reaction components were precisely adjusted. The optimization of the gDNA concentration revealed that the fluorescence signal initially increased with increasing gDNA concentration but subsequently decreased, indicating that 20 μM was the optimal concentration (Figure 2B). The optimization of MnCl2 addition revealed that the fluorescence intensity increased with increasing MnCl2 volume, with an optimal volume of 6 μL identified (Figure 2C). Probe concentration optimization indicated that the efficacy of the system was optimal at a concentration of 10 μM; at concentrations above this concentration, the fluorescence signal decreased (Figure 2D). The optimal volume for PfAgo enzyme addition was 4 μL, following the observation that the fluorescence signal peaked before it decreased (Figure 2E). Similarly, after the volume of the RPA product was optimized, 6 μL was determined to be the optimal volume for eliciting the strongest fluorescence signal (Figure 2F). The use of 2 fluorescently labelled probes, namely, FAM and ROX, increased the precision of the measurements. Consistent expression trends and optimal concentration selections were observed across different systems, with ROX demonstrating a more pronounced gradient response than that of FAM.

Evaluation of the Sensitivity, Specificity, and Repeatability of the RPA-PfAgo Detection Platform

Evaluations of sensitivity, specificity, and repeatability were performed using the optimized GPV RPA-PfAgo protocol. Sensitivity assessments demonstrated a marked and progressive decrease in signal density across a tenfold dilution gradient. No signal was detected at 3.89 × 101 and 3.89 × 100 copies/μL, indicating that the lower detection limit was 3.89 × 102 copies/μL plasmid DNA (Figure 3A). Specificity was confirmed by testing DNA from a panel of six pathogens, namely, GPV, MDPV, DPV, DuCV, K. pneumoniae, and E. coli, with only GPV being detectable, thus indicating no cross-reactivity (Figure 3B). Repeatability was demonstrated by a CV that was consistently less than 10.0% across both high-concentration plasmid DNA (3.89 × 108 copies/μL) and low-concentration plasmid DNA (3.89 × 102 copies/μL), reflecting the robustness of the assay (Figure 3C and Figure S1). Principal component analysis (PCA) and cluster heatmaps of repeatability revealed distinct and consistent clustering of the FAM and ROX probe signals, with the ROX probe system exhibiting greater repeatability than the FAM probe system (Figure 3C).Figure 3 Assessment of the sensitivity, specificity, and repeatability of the optimized GPV RPA-PfAgo platform. (A) Sensitivity tested across a range of plasmid DNA concentrations (3.89 × 108 to 3.89 × 10° copies/μL). (B) Specificity confirmed by testing against various pathogens. (C) Repeatability was established through multiple independent experiments and visualized using principal component analysis (PCA) and a clustering heatmap. The repeatability of 3.89 × 108 copies/μL plasmid DNA is presented here, whereas the repeatability of 3.89 × 102 copies/μL plasmid DNA is shown in Supplementary Figure 1.

Figure 3

Clinical Validation of the GPV RPA-PfAgo Detection Platform and Comparative Analysis With qPCR and PCR Methods

Forty-six clinical samples infected with GPV were subjected to analysis using the RPA-PfAgo method with both FAM and ROX probes, which detected significant fluorescence signals indicative of infection. qPCR and conventional PCR also yielded positive results, with all methods achieving 100% detection and accuracy. The operation time for each method varied significantly, with RPA-PfAgo requiring approximately 1 h, qPCR requiring 3 h, and PCR requiring 4 h. The equipment requirements also differ: RPA-PfAgo utilizes a basic heating and fluorescence detection apparatus, whereas qPCR requires a sophisticated fluorescence quantitative PCR instrument, and PCR requires a thermocycler, electrophoresis, and imaging equipment. While all of the methods detected GPV effectively, RPA-PfAgo showed greater result stability and a more consistent trend alignment with the PCR results (Figure 4).Figure 4 Clinical validation of the GPV RPA-PfAgo detection platform and comparison with qPCR and PCR methods. (A) GPV RPA-PfAgo assay results for 46 clinical samples. (B) qPCR results for the same set of samples. (C) PCR amplification outcomes for these samples. (D) Comparative analysis of GPV detection efficiency with RPA-PfAgo (FAM, ROX), qPCR, and PCR. RPA-PfAgo and qPCR data reflect end-point fluorescence intensities, while PCR band intensities were quantified via ImageJ software (Schroeder et al., 2021).

Figure 4

DISCUSSION

In this study, we present a novel detection system for GPV that integrates RPA technology with PfAgo. The development of this system is predicated on an understanding of the limitations associated with existing GPV detection methods, including time consumption, high costs, and strict equipment requirements. By combining the rapid amplification capabilities of RPA with the specific nucleic acid cleavage ability of the PfAgo protein, we designed a detection platform that is both fast and precise and is particularly well suited for rapid field testing and resource-limited settings. This study also included performance optimization of the RPA-PfAgo system, assessment of its sensitivity and specificity, and investigation of its potential advantages over traditional GPV detection methods. This study aimed to assess the potential of this system for widespread application in the poultry industry and for global animal health management and to consider its possible impact on disease surveillance and control strategies in the future.

During the development of the RPA-PfAgo system, we meticulously designed primers and probes, adjusted the reaction conditions, and increased the sensitivity and specificity of the detection process. Known for its immunogenicity and conservation across different strains, the VP3 gene of GPV was selected as the target sequence to ensure broad-spectrum detection capabilities (Tarasiuk et al., 2019). A set of primers was designed to bind to conserved regions, maximizing the probability of successful amplification across various GPV variants. The RPA reaction conditions were systematically optimized, including adjustments to the MgAc concentration, reaction temperature, and reaction time, to obtain the strongest amplification signal (Liu et al., 2023). This approach is crucial for developing a robust detection scheme that can reliably operate under diverse field conditions. Integrating the PfAgo protein, renowned for its precise nucleic acid sequence cutting, into the detection system represents a significant innovation. This feature allowed our system to eliminate nonspecific amplification products, greatly enhancing the specificity of GPV detection, which is vital in veterinary clinical settings to avoid unnecessary culling and economic loss. Notably, we opted to utilize 2 short gDNA segments (16 nt), diverging from the commonly used longer or single-stranded gDNA sequences used in other studies (Wang et al., 2021; Wang et al., 2023; Yang et al., 2023). The use of shorter gDNA reduces spatial hindrance between molecules and enhances the kinetics of the cleavage reaction. Additionally, employing 2 gDNA segments improves the specificity and signal strength, significantly reducing the likelihood of false-positive results and generating more marked fragments in a single reaction, thereby increasing the detection signal intensity. Although this approach may increase raw material costs, the expenditure is justified by improved diagnostic accuracy and efficiency. Accurate diagnostics can decrease economic losses caused by misdiagnoses, thereby increasing the cost-effectiveness of disease management and control. Future investigations will investigate the specific impacts of different gDNA configurations on the performance of the RPA-PfAgo system, aiming to further optimize our detection methods. In terms of sensitivity, the RPA-PfAgo system was capable of detecting low copy numbers of GPV DNA, which is beneficial for the early detection and control of this disease. The repeatability of the detection was demonstrated by a low coefficient of variation, reflecting consistent and reliable results across multiple tests. Specificity testing further confirmed that the RPA-PfAgo system did not cross-react with DNA from other pathogens, highlighting its practicality as a highly specific diagnostic tool for GPV. Clinical validation of the RPA-PfAgo system using goose lung tissue samples infected with GPV proved its practical application value. For the test samples, the system demonstrated a 100% detection rate comparable to that of qPCR and traditional PCR methods but with faster processing times and simpler equipment requirements. This rapid turnaround time for results is crucial for epidemic management, enabling swift implementation of intervention and control measures.

In addition to the optimization steps and conditions mentioned above, during the development of the RPA-PfAgo system, we also considered the use of multiple probes and pathogens to further refine and enhance the precision of our detection system. The use of FAM and ROX fluorescent probes in the RPA-PfAgo system for detecting GPV improves the sensitivity and enables quantitative real-time monitoring of the reaction. These probes were chosen for their unique emission spectra, allowing for concurrent dual detection, which minimizes false-positive results and enhances assay reliability. In optimization experiments, ROX-labelled probes demonstrated greater signal stability and a more pronounced increase in fluorescence over time than did FAM probes, which is consistent with the well-known properties of stability and high quantum efficiency of ROX (Mao et al., 2018). The contrasting behaviours of the FAM and ROX probes provide insight into the dynamic range and sensitivity of the assay. Although both probes effectively identify GPV DNA, the stronger signal from ROX probes indicates their potential for detecting lower target DNA concentrations. This feature is especially beneficial for early infection stages characterized by lower viral loads, where prompt detection is essential for effective disease control. To ascertain the specificity of the RPA-PfAgo system for the detection of GPV, we conducted a series of tests against a panel of pathogens that are commonly found in the avian environment or are known to cause diseases in geese. This panel included MDPV, DPV, DuCV, K. pneumoniae and E. coli. The identification of MDPVs, which share a close genetic relationship with GPVs, was critical for confirming that our system can discriminate between closely related parvoviruses (Wang et al., 2017). DPV and DuCV, both of which are significant viral pathogens in poultry, were selected to establish that our system's detection capabilities are exclusive to GPV and not confounded by other viral DNA (Zhou et al., 2016; Liu et al., 2020). The bacterial pathogens K. pneumoniae and E. coli represent common bacterial flora and potential contaminants during sample collection (Afolabi et al., 2022; Bai et al., 2022). The inclusion of these strains ensured that the RPA-PfAgo system was not susceptible to false-positive results from bacterial DNA, which is essential for maintaining high diagnostic confidence. The specificity tests conclusively demonstrated that the RPA-PfAgo system did not yield positive results for any of these nontarget pathogens, confirming its high specificity for GPV.

RPA combined with the PfAgo system is gaining recognition as a potent diagnostic tool for pathogen detection, with particular implications for avian pathogens such as GPV. Established methods such as PCR and ELISA have long served as the foundation for viral diagnostics because of their exceptional specificity and sensitivity. Nevertheless, the reliance on conventional thermocyclers, protracted amplification cycles, and intricate sample preparation procedures often restricts the applicability of these methods, especially in settings with limited resources or during critical periods of epidemic control. In stark contrast, the RPA-PfAgo system operates under isothermal conditions, negating the need for thermal cycling and thus enabling the use of simplified, portable equipment. This characteristic is particularly beneficial for field diagnostics in remote locations or areas where laboratory capabilities are constrained. The integration of the PfAgo protein into the RPA assay markedly increases the specificity of the diagnostic process. The distinct nucleic acid cleavage activity of PfAgo ensures the targeted elimination of nonspecific amplification products, substantially diminishing the likelihood of false-positive results from complex biological samples (Wu et al., 2023). This precise cleavage, in combination with the swift amplification kinetics of RPA, facilitates the detection of minimal viral genomic copies. The success of the RPA-PfAgo system is underscored by its ability to deliver diagnostic outcomes within an hour, significantly accelerating the process compared with the several-hour timeframe typically associated with traditional PCR techniques. This accelerated diagnostic capability is not only pivotal for prompt clinical decision-making but also indispensable for the rapid enactment of biosecurity interventions during outbreaks of GPV. Compared with other rapid detection systems, such as RPA and RPA-CRISPR/Cas, standalone RPA can rapidly amplify nucleic acids but has limited specificity for complex targets. The RPA-PfAgo system, however, enhances specificity through the targeted cleavage capability of PfAgo, expanding the range of potential targets. Although the RPA-CRISPR/Cas system is highly sensitive and can detect a variety of pathogens, including Neospora caninum (Wang et al., 2024), Erwinia amylovora (Ivanov et al., 2022), and Opisthorchis viverrini (Phuphisut et al., 2024), it requires precise temperature control and typically involves complex and costly guide RNA structures that are unstable. Therefore, the RPA-PfAgo system, which is not limited by PAM sequences and utilizes PfAgo-based gDNA editing, offers increased specificity and ease of use.

Despite the rapid detection and specificity of the RPA-PfAgo system for identifying GPV, certain limitations must be acknowledged. The efficacy of this system depends on the precise design of primers and guide DNA molecules, which requires an in-depth understanding of the virus genome. Given the propensity for genetic shifts in viruses such as GPV, these molecular tools may need regular updates to align with emerging strains (Huo et al., 2023). The specificity of the detection system is currently limited to a few pathogens, limiting its utility in scenarios involving coinfections. Future research must broaden the detection spectrum to differentiate and accurately identify coinfecting viruses. Moreover, investigating cross-reactivity among different viruses is crucial for preventing false-positive results, ensuring the precision of diagnostic outcomes. Although the RPA-PfAgo system has increased the detection sensitivity for GPV at low copy numbers, its ability to detect samples with extremely low viral loads remains limited. For example, compared with the RT-RPA-PfAgo system, which can detect rice ragged stunt virus (RRSV), rice grassy stunt virus (RGSV), and rice black streaked dwarf virus (RBSDV) within a range of 3.13 to 5.13 copies/µL (Liu et al., 2023), the sensitivity of the RPA-PfAgo system for Mycoplasma synoviae is reported to be 2 copies/µL (Zhao et al., 2024). However, in this study, the sensitivity of the RPA-PfAgo system was significantly lower, at 3.89 × 102 copies/µL. Therefore, to reliably detect early infections or samples with very low viral quantities, it may be necessary to employ more sensitive detection methods or to include preprocessing steps to concentrate the viral DNA. The affordability of the RPA-PfAgo system is a notable advantage since it eliminates the need for costly laboratory apparatuses. However, in settings with limited resources, the expense of the necessary equipment and reagents, including the acquisition and storage of the PfAgo protein, could be prohibitive. The assay may also require specific storage conditions to preserve the protein's stability and activity, potentially increasing operational costs (Feller, 2010). Despite the favorable laboratory performance of the RPA-PfAgo method, real-world applications could be influenced by the quality and treatment of the samples. Complex samples may contain inhibitors of the RPA reaction, and suboptimal DNA extraction could generate false-negative results (Kinloch et al., 2020). Although the RPA-PfAgo system is a valuable tool for swift point-of-care testing, its utility in extensive surveillance and epidemiological research remains to be thoroughly examined (Liu et al., 2023). Future studies should evaluate the system's performance in diverse environmental and epidemiological settings and consider its effectiveness in detecting a wider array of pathogens.

The RPA-PfAgo system has demonstrated promising efficacy in detecting GPV, which paves the way for extensive future research endeavors. These efforts are directed not only toward refining the current system but also toward enhancing its utility and evaluating its potential for application in actual epidemiological surveillance contexts. Future improvements to the RPA-PfAgo system may include the exploration of innovative guide DNA constructs and amendments that increase the stability and efficiency of the PfAgo-mediated cleavage process. The system's applicability needs to be tested across a spectrum of disease models, requiring validation of its effectiveness in identifying a variety of avian pathogens, thus widening its implementation in the poultry sector. Ideal studies could involve a suite of viruses characterized by diverse genomic configurations and conformations to verify the system's adaptability to assorted viral targets. The practical deployment of the RPA-PfAgo in epidemiological monitoring is also a subject worthy of investigation. Comprehensive field evaluations in disparate geographical and environmental settings will yield invaluable insights into the system's robustness and dependability. Integrating the RPA-PfAgo system with current disease surveillance frameworks could significantly improve the speed and precision of infectious disease tracking and management. The development of compact, user-friendly devices, including the RPA-PfAgo system, has the potential to lead to the transformation of field-testing protocols. These devices are especially beneficial for swift diagnostic assessments in areas with limited access to laboratory infrastructure. Subsequent research should also address the fiscal and logistical aspects of deploying the RPA-PfAgo system on an expanded scale. Detailed cost‒benefit analyses, supply chain evaluations, and comprehensive training programs for users are essential elements that influence the viability and sustainability of broad-scale adoption. The use of the RPA-PfAgo system signifies a substantial advancement in the swift molecular detection of GPV. The projected research trajectories aim not only to refine this system but also to promote its assimilation into international disease control strategies, ultimately contributing to the protection of avian health and the stabilization of poultry production worldwide.

In conclusion, the RPA-PfAgo system heralds a significant transformation in diagnostic methodology for GPV, shifting away from traditional techniques towards more advanced molecular diagnostics. This innovative system meets the critical demand for swift, precise, and onsite diagnostic capabilities and is crucial for combating emergent viral diseases that pose a risk to poultry production worldwide. Owing to its streamlined operation, robust specificity, and elevated sensitivity, the RPA-PfAgo system is an invaluable resource for the poultry sector and animal health management at large. Prospective research endeavors will concentrate on enhancing this technology, broadening its diagnostic scope to encompass an extensive array of avian pathogens and incorporating it into an all-encompassing disease surveillance framework. These developments are poised to equip poultry farmers and veterinarians with indispensable tools for the expedited detection and management of infectious diseases, thereby enhancing avian health and fortifying the sustainability of worldwide poultry production.

CRediT authorship contribution statement

Yaqun Liu: Conceptualization, Methodology, Investigation, Writing – original draft. Lianghui Chen: Data curation, Formal analysis, Visualization, Writing – review & editing. Zhenxia Zhang: Software, Validation. Rong Zhang: Resources, Data curation. Jinyu Xu: Investigation, Resources. Peikui Yang: Software, Validation. Yanjie Sun: Data curation, Writing – review & editing. Yicun Chen: Supervision, Project administration. Chengsong Xie: Funding acquisition, Project administration. Min Lin: Conceptualization, Supervision, Writing – review & editing. Yuzhong Zheng: Conceptualization, Methodology, Supervision, Writing – review & editing, Funding acquisition.

DISCLOSURES

The authors declare no conflicts of interest.

Appendix Supplementary materials

Image, image 1

ACKNOWLEDGMENTS

This work was supported by the Guangdong Key Laboratory of Functional Substances in Medicinal Edible Resources and Healthcare Products (grant number 2021B1212040015 ), the Special Research Projects of Hybribio (grant number KP202304 ) and the Scientific Projects of Key Disciplines in Guangdong Province (grant numbers 2021ZDJS042 and 2022ZDJS070 ), Chaozhou Science and Technology Bureau Science and Technology Project (grant number 2023ZC24 ), Hanshan Normal University Scientific Research Mentor Support Program (grant number XBF202302 )

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.psj.2024.104141.
==== Refs
REFERENCES

Afolabi E.O. Quilliam R.S. Oliver D.M. Time since faecal deposition influences mobilisation of culturable E. coli and intestinal enterococci from deer, goose and dairy cow faeces PLoS One 17 2022 e274138
Bai S. Yu Y. Kuang X. Li X. Wang M. Sun R. Sun J. Liu Y. Liao X. Molecular characteristics of antimicrobial resistance and virulence in klebsiella pneumoniae strains isolated from goose farms in Hainan, China Appl Environ Microbiol 88 2022 e245721
Brown K.E. Green S.W. Young N.S. Goose parvovirus–an autonomous member of the dependovirus genus? Virology 210 1995 283 291 7618268
Dong J. Bingga G. Sun M. Li L. Liu Z. Zhang C. Guo P. Huang Y. Zhang J. Application of high-resolution melting curve analysis for identification of Muscovy duck parvovirus and goose parvovirus J Virol Methods 266 2019 121 125 30638587
Feller G. Protein stability and enzyme activity at extreme biological temperatures J Phys Condens Matter 22 2010 323101
Glavits R. Zolnai A. Szabo E. Ivanics E. Zarka P. Mató T. Palya V. Comparative pathological studies on domestic geese (Anser anser domestica) and Muscovy ducks (Cairina moschata) experimentally infected with parvovirus strains of goose and Muscovy duck origin Acta Vet Hung 53 2005 73 89 15782661
He R. Wang L. Wang F. Li W. Liu Y. Li A. Wang Y. Mao W. Zhai C. Ma L. Pyrococcus furiosus Argonaute-mediated nucleic acid detection Chem Commun (Camb) 55 2019 13219 13222 31589231
Huo X. Chen Y. Zhu J. Wang Y. Evolution, genetic recombination, and phylogeography of goose parvovirus Comp Immunol Microbiol Infect Dis 102 2023 102079
Ivanov A.V. Safenkova I.V. Drenova N.V. Zherdev A.V. Dzantiev B.B. Comparison of biosensing methods based on different isothermal amplification strategies: a case study with erwinia amylovora Biosensors (Basel) 12 2022 1174
Kinloch N.N. Ritchie G. Brumme C.J. Dong W. Dong W. Lawson T. Jones R.B. Montaner J.S.G. Leung V. Romney M.G. Stefanovic A. Matic N. Lowe C.F. Brumme Z.L. Suboptimal biological sampling as a probable cause of false-negative COVID-19 diagnostic test results J Infect Dis 222 2020 899 902 32594170
Liu J.T. Chen Y.H. Pei Y.F. Yu Q. Afumba R. Dong H. Rapid and visual detection of an isolated and identified goose parvovirus (GPV) strain by a loop-mediated isothermal amplification assay Vet Res Forum 14 2023 7 12 36816861
Liu Y. Xia W. Zhao W. Hao P. Wang Z. Yu X. Shentu X. Sun K. RT-RPA-PfAgo system: a rapid, sensitive, and specific multiplex detection method for rice-infecting viruses Biosensors (Basel) 13 2023 941 37887134
Liu W.J. Yang Y.T. Du S.M. Yi H.D. Xu D.N. Cao N. Jiang D.L. Huang Y.M. Tian Y.B. Rapid and sensitive detection of goose parvovirus and duck-origin novel goose parvovirus by recombinase polymerase amplification combined with a vertical flow visualization strip J Virol Methods 266 2019 34 40 30677463
Liu Y. Huang H. Zheng Y. Wang C. Chen W. Huang W. Lin L. Wei H. Wang J. Lin M. Development of a POCT detection platform based on a locked nucleic acid-enhanced ARMS-RPA-GoldMag lateral flow assay J Pharm Biomed Anal 235 2023 115632 37573622
Liu Y. Lin L. Wei H. Luo Q. Yang P. Liu M. Wang Z. Zou X. Zhu H. Zha G. Sun J. Zheng Y. Lin M. Design and development of a rapid meat detection system based on RPA-CRISPR/Cas12a-LFD Curr Res Food Sci 7 2023 100609 37860145
Liu J. Yang X. Hao X. Feng Y. Zhang Y. Cheng Z. Effect of goose parvovirus and duck circovirus coinfection in ducks J Vet Res 64 2020 355 361 32984623
Ma H. Gao X. Fu J. Xue H. Song Y. Zhu K. Development and evaluation of NanoPCR for the detection of goose parvovirus Vet Sci 9 2022 460 36136676
Mao H. Luo G. Zhang J. Xue H. Song Y. Zhu K. Detection of simultaneous multi-mutations using base-quenched probe Anal Biochem 543 2018 79 81 29233678
Memon S.S. Srivastava P. Karlekar M. Thakkar H. Bandgar T. KEM Pheochromocytoma Investigators Ambulatory blood pressure monitoring in pheochromocytoma - paraganglioma: a single center experience J Postgrad Med 70 2024 84 90 37555422
Niu Y. Zhao L. Liu B. Liu J. Yang F. Yin H. Huo H. Chen H. Comparative genetic analysis and pathological characteristics of goose parvovirus isolated in Heilongjiang, China Virol J 15 2018 27 29391035
Phuphisut O. Poodeepiyasawat A. Yoonuan T. Watthanakulpanich D. Thawornkuno C. Reamtong O. Sato M. Adisakwattana P. Ov-RPA-CRISPR/Cas12a assay for the detection of Opisthorchis viverrini infection in field-collected human feces Parasit Vectors 17 2024 80 38383404
Schroeder A.B. Dobson E. Rueden C.T. Tomancak P. Jug F. Eliceiri K.W. The ImageJ ecosystem: open-source software for image visualization, processing, and analysis Protein Sci 30 2021 234 249 33166005
Swarts D.C. Hegge J.W. Hinojo I. Shiimori M. Ellis M.A. Dumrongkulraksa J. Terns R.M. Terns M.P. van der Oost J. Argonaute of the archaeon Pyrococcus furiosus is a DNA-guided nuclease that targets cognate DNA Nucleic Acids Res 43 2015 5120 5129 25925567
Tarasiuk K. Holec-Gasior L. Ferra B. Rapak A. The development of an indirect ELISA for the detection of goose parvovirus antibodies using specific VP3 subunits as the coating antigen BMC Vet Res 15 2019 274 31370852
Tu M. Liu P. Liu F. Wang M. Jia R. Zhu D. Liu M. Sun K. Yang Q. Wu Y. Chen X. Cheng A. Chen S. Construction of expression vectors of capsid proteins from goose parvovirus and investigation of the immunogenicity Acta Virol 62 2018 415 423 30472872
Wan C. Chen C. Cheng L. Liu R. Shi S. Fu G. Chen H. Fu Q. Huang Y. Specific detection and differentiation of classic goose parvovirus and novel goose parvovirus by TaqMan real-time PCR assay, coupled with host specificity BMC Vet Res 15 2019 389 31676004
Wang L. Li X. Li L. Cao L. Zhao Z. Huang T. Li J. Zhang X. Cao S. Zhang N. Wang X. Gong P. Establishment of an ultrasensitive and visual detection platform for Neospora caninum based-on the RPA-CRISPR/Cas12a system Talanta 269 2024 125413 38042139
Wang J. Ling J. Wang Z. Huang Y. Zhu J. Zhu G. Molecular characterization of a novel Muscovy duck parvovirus isolate: evidence of recombination between classical MDPV and goose parvovirus strains BMC Vet Res 13 2017 327 29121936
Wang Y. Chen Y. Tang Y. Wang Y. Gao S. Yang L. Wang P. A recombinase polymerase amplification and Pyrococcus furiosus Argonaute combined method for ultra-sensitive detection of white spot syndrome virus in shrimp J Fish Dis 46 2023 1357 1365 37635423
Wang F. Yang J. He R. PfAgo-based detection of SARS-CoV-2 Biosens Bioelectron 177 2021 112932
Wu Z. Yu L. Shi W. Ma J. Argonaute protein-based nucleic acid detection technology Front Microbiol 14 2023 1255716
Yang J. Chen H. Wang Z. Yu X. Niu X. Tang Y. Diao Y. Development of a quantitative loop-mediated isothermal amplification assay for the rapid detection of novel goose parvovirus Front Microbiol 8 2017 2472 29312182
Yang L. Guo B. Wang Y. Zhao C. Zhang X. Wang Y. Tang Y. Shen H. Wang P. Gao S. Pyrococcus furiosus argonaute combined with recombinase polymerase amplification for rapid and sensitive detection of enterocytozoon hepatopenaei J Agric Food Chem 71 2023 944 951 36548210
Zhao B. Xiong C. Li J. Zhang D. Shi Y. Sun W. Duan X. Species quantification in complex herbal formulas-vector control quantitative analysis as a new method Front Pharmacol 11 2020 488193 33324200
Zhao Y. Zhang Y. Wu W. Kang T. Sun J. Jiang H. Rapid and sensitive detection of Mycoplasma synoviae using RPA combined with Pyrococcus furiosus Argonaute Poult Sci 103 2023 103244 38194834
Zhao Y. Zhang Y. Wu W. Kang T. Sun J. Jiang H. Rapid and sensitive detection of Mycoplasma synoviae using RPA combined with Pyrococcus furiosus Argonaute Poult Sci 103 2024 103244 38194834
Zhou H. Chen S. Zhou Q. Wei Y. Wang M. Jia R. Zhu D. Liu M. Liu F. Yang Q. Wu Y. Sun K. Chen X. Cheng A. Cross-species antiviral activity of goose interferons against duck plague virus is related to its positive self-feedback regulation and subsequent interferon stimulated genes induction Viruses 8 2016 195
