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Rapid and specific detection of Pentastiridius leporinus by recombinase polymerase amplification assay

Published online by Cambridge University Press:  06 May 2024

Omid Eini*
Affiliation:
Institute of Sugar Beet Research, Holtenser Landstraße 77, 37079 Göttingen, Germany
René Pfitzer
Affiliation:
Institute of Sugar Beet Research, Holtenser Landstraße 77, 37079 Göttingen, Germany Agricultural Entomology, Department of Crop Sciences, Faculty of Agricultural Sciences, University of Göttingen, Grisebachstrasse 6, 37077 Göttingen, Germany
Mark Varrelmann
Affiliation:
Institute of Sugar Beet Research, Holtenser Landstraße 77, 37079 Göttingen, Germany
*
Corresponding author: Omid Eini; Email: [email protected]
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Abstract

Pentastiridius leporinus (Hemiptera: Cixiidae) is the main vector of an emerging and fast spreading sugar beet disease, the syndrome ‘basses richesses’ (SBR), in different European countries. The disease is caused by the γ-3-proteobacterium ‘Candidatus Arsenophonus phytopathogenicus’ and the phytoplasma ‘Candidatus Phytoplasma solani’ which are exclusively transmitted by planthoppers and can lead to a significant loss of sugar content and yield. Monitoring of this insect vector is important for disease management. However, the morphological identification is time consuming and challenging as two additional cixiid species Reptalus quinquecostatus and Hyalesthes obsoletus with a very close morphology have been reported in sugar beet fields. Further, identification of females and nymphs of P. leporinus at species level based on taxonomic key is not possible. In this study, an isothermal nucleic acid amplification based on recombinase polymerase amplification (RPA) was developed to specifically detect P. leporinus. In addition, real-time RPA was developed to detect both adults (male and female) and nymph stages using pure or crude nucleic acid extracts. The sensitivity of the real-time RPA for detection of P. leporinus was comparable to real-time PCR, but a shorter time (< 7 min) was required. This is a first report for real-time RPA application for P. leporinus detection using crude nucleic acid templates which can be applied for fast and specific detection of this vector in the field.

Type
Research Paper
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

Introduction

Pentastiridius leporinus (Hemiptera: Auchenorrhyncha: Cixiidae) is the main vector for syndrome ‘basses richesses’ (SBR) disease in sugar beet (Beta vulgaris) which is a fast-spreading disease in Central Europe and causing up to 5% absolute sugar content loss and severe yield reduction of the taproot (Gatineau et al., Reference Gatineau, Jacob, Vautrin, Larrue, Lherminier, Richard-Molard and Boudon-Padieu2002; Sémétey et al., Reference Sémétey, Bressan, Richard-Molard and Boudon-Padieu2007c; Bressan et al., Reference Bressan, Sémétey, Nusillard, Clair and Boudon-Padieu2008). The disease was initially reported in eastern France in 1991 (Gatineau et al., Reference Gatineau, Jacob, Vautrin, Larrue, Lherminier, Richard-Molard and Boudon-Padieu2002) and then further spreaded into sugar beet fields in Germany (Pfitzer et al., Reference Pfitzer, Schrameyer, Voegele, Maier, Lang and Varrelmann2020; Behrmann et al., Reference Behrmann, Schwind, Schieler, Vilcinskas, Martinez, Lee and Lang2021) and Switzerland (Mahillon et al., Reference Mahillon, Groux, Bussereau, Brodard, Debonneville, Demal, Kellenberger, Peter, Steinger and Schumpp2022). The causal agents of SBR are the γ-3-proteobacterium ‘Candidatus Arsenophonus phytopathogenicus’ (here called: ‘SBR proteobacterium’) and a phytoplasma from the stolbur group (16SrXII group) ‘Candidatus Phytoplasma solani’ which are exclusively transmitted by planthoppers (Sémétey et al., Reference Sémétey, Gatineau, Bressan and Boudon-Padieu2007a; Bressan et al., Reference Bressan, Sémétey, Nusillard, Clair and Boudon-Padieu2008). Among them, P. leporinus is the key factor in spreading the SBR disease. This is due to the high population densities, infection rates, the ability to transmit both pathogens and vertical transmission of the SBR proteobacterium to their offspring (Sémétey et al., Reference Sémétey, Bressan, Richard-Molard and Boudon-Padieu2007c; Bressan et al., Reference Bressan, Sémétey, Nusillard, Clair and Boudon-Padieu2008; Pfitzer et al., Reference Pfitzer, Schrameyer, Voegele, Maier, Lang and Varrelmann2020; Mahillon et al., Reference Mahillon, Groux, Bussereau, Brodard, Debonneville, Demal, Kellenberger, Peter, Steinger and Schumpp2022). Additionally, this insect vector has been host-shifted from natural host plant, reed (Phragmites australis) to sugar beet and other crops including barley (Hordeum vulgare) and winter wheat (Triticum aestivum) during crop rotations (Holzinger et al., Reference Holzinger, Kammerlander and Nickel2003; Bressan et al., Reference Bressan, Holzinger, Nusillard, Sémétéy, Gatineau, Simonato and Boudon-Padieu2009b). This phenomenon together with increasing P. leporinus populations led to a significant SBR spread in sugar beet (Bressan, Reference Bressan2009; Bressan et al., Reference Bressan, Holzinger, Nusillard, Sémétéy, Gatineau, Simonato and Boudon-Padieu2009b; Bressan et al., Reference Bressan, Moral García and Boudon-Padieu2011).

In addition to P. leporinus, several Auchenorrhyncha species including two closely related cixiid planthoppers, Reptalus quinquecostatus and Hyalesthes obsoletus, have been collected in sugar beet fields in France (Sémétey et al., Reference Sémétey, Bressan, Gatineau and Boudon-Padieu2007b) and Germany (Pfitzer, Reference Pfitzer2019). R. quinquecostatus has recently undergone a taxonomic revision with a new name, R. artemisiae (Emeljanov, Reference Emeljanov2020). To provide easier connection to the published data regarding this species, we referred to it as R. quinquecostatus. P. leporinus can be hardly distinguished from R. quinquecostatus and H. obsoletus by morphological traits. Based on the morphological traits, these species are also closely related (Ceotto and Bourgoin, Reference Ceotto and Bourgoin2008). They have hyaline or transparent wings and their mesonotum has five keels and the absence of a post-tibial calcar at the hind legs and their fore wings are characterised by a roof-shaped resting position (Holzinger et al., Reference Holzinger, Kammerlander and Nickel2003). Identification of P. leporinus based on morphological characters is challenging and time consuming (Bertin et al., Reference Bertin, Picciau, Ács, Alma and Bosco2010a). This requires highly skilled and experienced personnel which limits the throughput in practical monitoring. Further, the morphological keys for P. leporinus identification at the species level are exclusively described for male adults and thus lacking for female adults and nymphal instars (Holzinger et al., Reference Holzinger, Kammerlander and Nickel2003; Biedermann and Niedringhaus, Reference Biedermann and Niedringhaus2004). Further, identification of sticky trap collected insects which is a common method of monitoring the vector spread could be more difficult and error prone for identification based on morphological characters (Bertin et al., Reference Bertin, Picciau, Ács, Alma and Bosco2010b).

Supporting the morphological identification or even as an alternative identification method, molecular methods such as DNA barcoding (Virgilio et al., Reference Virgilio, Backeljau, Nevado and De Meyer2010) have been used for insects. Among these methods, polymerase chain reaction (PCR) is the most widely used (Mullis et al., Reference Mullis, Faloona, Scharf, Saiki, Horn and Erlich1986) to specifically amplify a part of insect genome that can be sequenced and used for identification. However, due to the requirements of a PCR machine, time, and professional operation, it is difficult to apply PCR for on-site detection. In recent years, the advancement and application of isothermal amplification methods have been emerged rapidly. These isothermal amplification methods including loop-mediated isothermal amplification (LAMP) (Notomi et al., Reference Notomi, Okayama, Masubuchi, Yonekawa, Watanabe, Amino and Hase2000), helicase-dependent isothermal DNA amplification (HAD) (Jeong et al., Reference Jeong, Park and Kim2009), rolling-circle amplification (RCA) (Ali et al., Reference Ali, Li, Zhang, Zhang, Kang, Ankrum, Le and Zhao2014) and recombinase polymerase amplification (RPA) (Piepenburg et al., Reference Piepenburg, Williams, Stemple and Armes2006, Lobato and O'Sullivan, Reference Lobato and O'Sullivan2018), which use different enzyme mechanisms and settings. The RPA assay uses three core enzymes including recombinase, single-stranded DNA binding protein, and strand-displacing polymerase (Piepenburg et al., Reference Piepenburg, Williams, Stemple and Armes2006). Due to a simple operation, reaction at 37–42°C and fast amplification speed (5–20 min), RPA is widely used in various fields like the detection of bacteria, fungi, parasites, viruses or drug resistance genes in recent years (Mota et al., Reference Mota, Guimarães, Gandarilla, Filho, Brito and Mariúba2022; Tan et al., Reference Tan, Liao, Liang, Yi, Zhou and Wei2022). Additionally, compared to other common isothermal amplification methods (RCA, LAMP, HAD), RPA requires only simple primer design, tolerates certain mismatches in primers and allows multiplex amplification (Tan et al., Reference Tan, Liao, Liang, Yi, Zhou and Wei2022). However, there are only few examples for application of RPA for the identification of insects. For examples, RPA has been used to identify Thrips palmi (Thysanoptera: Thripidae), a vector of tospoviruses. They targeted a conserved region of ITS2 to identify all known intra-specific variants of this insect species (Priti et al., Reference Priti, Jangra, Baranwal, Dietzgen and Ghosh2021).

The use of mitochondrial gene cytochrome c oxidase I (COI) was established as the core of a global bioidentification system for animals including insects (Hebert et al., Reference Hebert, Cywinska, Ball and deWaard2003). It was demonstrated that species–level assignments can be obtained by creating comprehensive COI profiles (Hebert et al., Reference Hebert, Cywinska, Ball and deWaard2003). This gene also was used for identification and phylogenetic analysis of planthoppers in the genera Hyalesthes and Reptalus by using species-specific primers (Bressan et al., Reference Bressan, Arneodo, Simonato, Haines and Boudon-Padieu2009a; Bertin et al., Reference Bertin, Picciau, Ács, Alma and Bosco2010b). Recently, we have designed specific primers based on COI gene to identify and differentiate all life stages of P. leporinus from two closely related cixiid species, R. quinquecostatus and H. obsoletus, in sugar beet using PCR (Pfitzer et al., Reference Pfitzer, Varrelmann, Hesse and Eini2022a). In this study, a rapid and real-time detection of P. leporinus was developed based on the RPA assay. The sensitivity and specificity of the RPA assays for detection of both adults and nymphal stages were compared to real-time PCR assay using a simple and quick method for template DNA preparation.

Materials and methods

Planthopper collection from sugar beet fields and morphological identification

The main SBR vector, P. leporinus, and two morphologically close planthopper species (R. quinquecostatus, and H. obsoletus) were field collected with sweep nets during summer 2020 from several locations (Baden-Württemberg, Rhineland-Palatinate, and Saxony) in Germany (Pfitzer et al., Reference Pfitzer, Varrelmann, Schrameyer and Rostás2022b). Morphological identification of the sweep net collected insects was carried out using a stereomicroscope according to the taxonomic key (Biedermann and Niedringhaus, Reference Biedermann and Niedringhaus2004). The family and genus of individual female adult specimens were identified by observation of pronotum, wings, postnotum, mesonotum, and tarsus. Furthermore, the genital structures of male adults were evaluated to allow morphological identification at the species level. Additionally, species identification for both female and male insects was confirmed by sequencing COI gene (Pfitzer et al., Reference Pfitzer, Varrelmann, Hesse and Eini2022a). Additionally, nymphal instars of P. leporinus were obtained from our local P. leporinus rearing on sugar beet (Pfitzer et al., Reference Pfitzer, Varrelmann, Schrameyer and Rostás2022b). Developmental stages of nymphs were determined under a stereomicroscope according to the described key (Pfitzer et al., Reference Pfitzer, Varrelmann, Schrameyer and Rostás2022b) and the third, fourth and fifth nymphal instars were used in this study. We had no access to the nymphal stages of R. quinquecostatus, and H. obsoletus, therefore, only adults (male and female) were included.

Template DNA preparation

Two methods were used for preparation of template DNA from the insect specimens. Pure DNA from insects (adults or nymphs; fig. S1) was prepared using ‘DNeasy Blood & Tissue Kit’ (QIAGEN GmbH, Hilden, Germany) according to the manufacturer's instructions and dissolved in 60 μl of Tris acetate buffer (pH = 7). For crude extracts a slightly modified method described by Priti et al. (Reference Priti, Jangra, Baranwal, Dietzgen and Ghosh2021) was used. The insects (one adult or one nymph) were individually transferred into 1.5 ml tubes containing 60 μl phosphate-buffered saline (PBS; pH = 7.4) and then crushed with a sterile micropestle. After 10 min incubation at 95°C, samples were centrifuged for 10 min with 13,500 × g at room temperature. The supernatants were used as a PCR or RPA template. DNA quality and quantity were analysed with a spectrophotometer (‘DeNovix DS-110’, DeNovix Inc., Wilmington, USA) and via gel electrophoresis (fig. S2).

Primer design and RPA assay

For efficient RPA assay, primers (31 and 32 bp in size) were designed based on the COI gene sequence from P. leporinus (GenBank accession number ONO94072) following the instruction by TwistAmp® kit (TwistDx Ltd. Cambridge, UK). For this purpose, primer sequences that produced secondary structure, hairpin and primer-primer binding were avoided (Wan Rasni et al., Reference Wan Rasni, Yahaya and Mohamed Rehan2022). For the specificity of primers, COI sequences of P. leporinus, R. quinquecostatus, and H. obsoletus were obtained from our recent study (Pfitzer et al., Reference Pfitzer, Varrelmann, Hesse and Eini2022a) and NCBI database (National Center for Biotechnology Information, U.S. National Library of Medicine, Rockville Pike, MD, USA). These sequences were aligned using BioEdit software (version 7.2; https://bioedit.software.informer.com/7.2/), then primers with no mismatch to the COI gene of P. leporinus but with mismatches to the COI gene of the closely related species were selected and tested in silico on close cixiid species (fig. 1) and species which were reported from sugar beet fields, P. leporinus, R. quinquecostatus and H. obsoletus (Sémétey et al., Reference Sémétey, Bressan, Gatineau and Boudon-Padieu2007b; Pfitzer, Reference Pfitzer2019). Table 1 shows the sequence, GC content and melting temperature of the designed primers.

Figure 1. Alignment of the specific primers to the COI gene of Pentastiridius leporinus and different members of Hyalesthes spp. and Reptalus spp. The identical nucleotides with the specific primers (black arrows) are shown with dots. The positions of the primers are shown based on the COI gene with GenBank accession number ON094072. Number of mismatches between primers and the analysed sequences are shown on the right side of each alignment.

Table 1. Primers used for the detection of Pentastiridius leporinus.

The specificity of the designed primers was initially tested by PCR and compared to RPA assay. For PCR reactions, 10 μM of each primers (Penta-F and Penta-R) were used in a final volume of 20 μl containing 10 μl ‘DreamTaq PCR Master Mix (2X)’ (Thermo Fisher Scientific, Waltham, MA, USA), and about 100 ng of DNA templates from P. leporinus and two close species, respectively. The PCR conditions were 95°C for 3 min, 30 cycles at 95°C for 30 s, 56°C for 25 s and 72°C for 25 s and a final step at 72°C for 2 min according to the protocol by ThemoFisher Scientific (https://assets.thermofisher.com/TFS-Assets/BID/Reference-Materials/dreamtaq-dna-polymerases-labaid.pdf).

RPA reactions were performed according to the instruction of the TwistAmp® Basic kit (TwistDx Ltd. Cambridge, UK). For each reaction, 10.7 μl of sterile water, 2.4 μl of forward and reverse primers (10 μM; Penta-F and Penta-R), 29.5 μl of rehydration buffer and 2.5 μl of template were mixed. This mixture was added to an enzyme pellet from the kit. All samples were kept on ice during the preparation. To start the reactions, 2.5 μl of magnesium acetate solution (280 mM) was added to each tube. The tubes were briefly vortexed, then centrifuged and incubated in a water bath at 39°C for 5, 10 or 15 min. After the RPA reaction, the products were heated at 80°C for 5 min to inactivate the polymerase. The RPA and PCR products (2 μl) were analysed by gel electrophoresis. The amplified DNA in PCR or RPA assays was sequenced (Microsynth Seqlab GmbH, Göttingen, Germany) and aligned with published sequence data for COI gene of P. leporinus (Pfitzer et al., Reference Pfitzer, Varrelmann, Hesse and Eini2022a) to confirm the specificity of each assay.

The sensitivity of RPA and PCR was tested using ten-fold serial dilutions of crude nucleic acid from P. leporinus adults and nymphs. One microliter of each template DNA dilution was amplified in each assay. The RPA and PCR products were analysed by gel electrophoresis.

Real-time PCR and real-time RPA assay

For real-time PCR, each reaction was set up in a 15 μl volume containing 1x iTaq Universal SYBR Green Supermix (BioRad, Hercules, USA), 0.330 μM of each primer (Penta-F and Penta-R) and 1 μl DNA (about 100 ng). The qPCR was carried out in the CFX96 Real Time System C1000 Touch Thermal Cycler (Bio-Rad, Feldkirchen, Germany). The reaction was set with initial denaturation of 95°C for 3 min followed by 40 cycles of 95°C for 10 s and 60°C for 20 s. Three biological samples were tested for each insect group and each biological sample was analysed with three technical replicates. The threshold cycle (CT) data was analysed based on Livak and Schmittgen (Reference Livak and Schmittgen2001) with some modification. As the aim of this assay was specific detection of P. leporinus rather than quantification of COI gene, normalisation of data against a house keeping gene was not included. The CT value is the cycle at which the fluorescence signal reaches a threshold value, so a low number of CT represents a higher concentration of target gene in each sample. Therefore, an average of 2−Ct was calculated for each sample. Data were statistically analysed with R software (Tukey test, P < 0.05).

Real-time RPA assay was performed using the TwistAmp® Basic kit with some modifications. For each reaction, 10.2 μl of iTaq Universal SYBR Green Supermix, 2.4 μl of forward and reverse primers (10 μM, Penta-F and Penta-R), 29.5 μl of rehydration buffer and 3 μl of template (about 200 ng) were mixed. This mixture was added to an enzyme pellet from the kit. Then, 2.5 μl magnesium acetate (280 mM) was added to reach 50 μl volume. This mixture was mixed and divided into two tubes each containing a final 25 μl reaction. This was to have more technical replicates and to scale down the costs for each reaction. The real-time RPA reactions were carried out in the CFX96 Real Time System C1000 Touch Thermal Cycler. The reaction was set at 39°C for 20 min and fluorescence signals were measured after each 40 s. Then, enzyme reaction was stopped at 80°C for 10 s. The melting curve was created by ramping the temperature from 65°C to 95°C by 0.5°C. The fluorescence cycle threshold for SYBR Green was set just above the water control for each platform, so that samples with equal or less fluorescence than the water control were identified as negative (Teoh et al., Reference Teoh, Sam, Tan, Danlami, Shu, Johari, Hooi, Brooks, Piepenburg, Nentwich, Wilder-Smith, Franco, Tenorio and AbuBakar2015). Three replicates of each variant in at least three independent runs were performed for sensitivity and specificity experiments. In addition, the amplified products were directly run on 1% agarose gel without any additional purification step (Babujee et al., Reference Babujee, Witherell, Mikami, Aiuchi, Charkowski and Rakotondrafara2019) and the amplicons were visualised under UV light (312 nm).

The sensitivity of real-time RPA and real-time PCR was tested using a ten-fold serial dilution of crude nucleic acid extracts from individual P. leporinus adults and fourth-instar nymphs. To reduce time and cost and also to optimising this assay for the future field application only the crude nucleic acid extracts from individual insects were tested and therefore, the precise measurement of nucleic templates was not possible. Thus, this assay was repeated at least three times to obtain more robust data based on a single insect per sample. One microliter of each template DNA dilution was amplified in both assays using the explained reaction conditions for Real-time RPA assay. The threshold time was plotted against the detected DNA templates.

Results

Specific P. leporinus detection by RPA

The specific primers for P. leporinus (fig. 1) based on the sequence of the COI gene, produced a specific PCR product of the expected size (269 bp) from adults (female and male) samples using kit purified nucleic acids as a template. No amplicon was detected for the closely related planthoppers, R. quinquecostatus and H. obsoletus (fig. 2a). The same results were obtained in the RPA assay at 39°C for 15 min (fig. 2b). In addition, shorter reaction times showed clear RPA products to appear as well after 10 minutes. However, COI amplification and planthopper detection was not possible as early as 5 min (fig. 2c and S3). The sensitivity of the RPA assay for P. leporinus monitoring in crude samples was tested on a 10-fold dilution series. The COI gene from P. leporinus adults was detectable in dilution range from 1 × 10−1 to 1 × 10−3 for the adults and 1 × 10−1 to 1 × 10−2 for nymphs. Therefore, these specific primers can be used for specific detection of P. leporinus by RPA in a short reaction time (10 min).

Figure 2. PCR and RPA for specific detection of Pentastiridius leporinus. A representative electrophoretic pattern of PCR (a) and RPA (b) products show specific amplification of the COI gene of P. leporinus (lanes 7 to 9). Lanes 1 to 3 represent R. quinquecostatus, and lanes 4 to 6 represent H. obsoletus samples. (c) RPA was performed for 5, 10, and 15 min at 39°C using DNA samples of R. quinquecostatus (lanes 1 to 3) and P. leporinus (lanes 4 to 6) adult samples. (d) RPA assay using 10-fold serial dilutions of crude nucleic acid of adults (top panel) or nymphs (lower panel) shows the sensitivity of this assay for amplification of COI gene of P. leporinus. RPA products were gel-separated without an additional purification step. The size of amplicons was compared with 100 bp ladder (M).

Real-time PCR for specific P. leporinus detection

The real-time PCR assay was used to test specific detection of P. leporinus from pure and crude nucleic acids from nymph and adult samples. The COI gene was specifically detected in both P. leporinus adults and nymphs using specific primers and pure nucleic acid template (fig. 3a). The fluorescence signal intensity for adults (male and female) and nymphal stages (L3, L4, and L5) reflected their body size. Variations of the size of nymphal stages and adults have been described (Pfitzer et al., Reference Pfitzer, Varrelmann, Schrameyer and Rostás2022b). The strongest signals appeared for adults that have the largest size and contain more COI templates. For the nymphal stage, L5 has the largest size and showed the strongest fluorescence signals (fig. 3a). This was reflecting the higher DNA concentration in adult samples (250 to 340 ng μl−1) compared with nymphs (65 to 80 ng μl−1) as we intentionally did not optimise the DNA concentration to directly detect and compare all life stages of the insect from individual DNA samples.

Figure 3. Real-time amplification of the COI gene for the specific detection of Pentastiridius leporinus. Real-time PCR (a) and real-time RPA (b) show specific amplification of the COI gene using pure (kit) or crude nucleic acid of both adults (female and male) and nymphs (L3, L4, and L5) of P. leporinus compared with samples of adult R. quinquecostatus and H. obsoletus. For each treatment three biological replicates were tested, and the average threshold cycle (Ct) is presented. The same letter on the bars means not statistically different (P < 0.05%).

In addition, using crude template DNA, a comparable and specific P. leporinus detection was possible for adults (female and male) and nymphal stages (L3–L5). For the close cixiid species, R. quinquecostatus and H. obsoletus, no clear fluorescence signals (CT > 32) were detected (fig. 3a). Therefore, real-time PCR can be used for specific detection of P. leporinus adults and nymphs using crude DNA templates.

Optimising the real-time RPA conditions for specific P. leporinus detection

Application of real-time RPA based on a SYBR green assay was tested using P. leporinus specific primers and the TwistAmp Basic kit. This allows application of real-time RPA for detection of target genes without probe design and extra costs. This assay was initially tested on pure nucleic acids from P. leporinus and the two closely related species. Using a constant temperature of 39°C produced fluorescence signals for both P. leporinus adults and nymphs after a short incubation time (less than 10 min). However, background fluorescence signals also appeared for the nonspecific targets in both R. quinquecostatus and H. obsoletus samples after a longer time (more than 10 min) (fig. 4). Testing the real-time RPA products on agarose gel showed a clear amplification of COI gene only in P. leporinus samples, while no clear amplicons were detected in R. quinquecostatus and H. obsoletus samples even after 20 min. Thus, real-time RPA specifically amplifies the target COI gene exclusively in P. leporinus extracts. Based on the fluorescence plot data which included 14 runs and also agarose gel results, the detection threshold of the real-time RPA was established as equal to 10 cycles ( = 400 s) and the baseline to 200 relative fluorescence units (RFU) (fig. 4). Samples that produced exponential amplification curves above the threshold were considered as positive for P. leporinus and below the threshold were considered as negative. Detection of both adults and nymphal stages was confirmed in this assay (fig. 3b and 4). In addition, this detection threshold was applied to compare real-time RPA for detection of P. leporinus using crude nucleic acids from both adults and nymphs. Higher fluorescence signals were observed in pure nucleic acids from adults compare to crude nucleic acid, while fluorescence signals were comparable in both pure and crude nucleic acids of nymphs (fig. 3). Therefore, real-time RPA specifically detects P. leporinus in both pure and crude nucleic acids of adults and nymphs.

Figure 4. Real-time RPA assay for the specific detection of Pentastiridius leporinus. (a) Real-time RPA plot shows strong fluorescence signals for P. leporinus (5–8) and weak signals with a delay for R. quinquecostatus (1 and 2) and H. obsoletus (3 and 4). Time unit of each cycle represents 40 s. The threshold level for reliable P. leporinus detection was established as equal to 10 units of time (6.6 min) and baseline of fluorescent signals at 200 relative fluorescence units (RFU) indicated with the horizontal green line. (b) Electrophoretic patterns of real-time RPA products show clear amplification of the COI gene in P. leporinus samples. There were no amplicons for R. quinquecostatus adults and H. obsoletus adults. Lane numbers coordinate with panels A. RPA products were gel-separated without additional purification step. The size of amplicons was compared with 100 bp ladder (M).

Comparison of sensitivity between real-time PCR and real-time RPA for P. leporinus detection

The sensitivity of real-time PCR was compared to real-time RPA using a ten-fold serial dilution of crude nucleic acid of individual P. leporinus adults and nymphs. In real-time PCR, COI gene from adults was detectable in dilution range from 1 × 10−1 to 1 × 10−4. However, this range was from 1 × 10−1 to 1 × 10−3 for nymphs (fig. 5a). This indicated that fluorescence signals after 30 cycles are not reliable and adult DNA contains more COI templates compared to nymphs. Similarly, in real-time RPA, COI gene from adults was detectable in dilution range from 1 × 10−1 to 1 × 10−4 and a lower level of COI gene (1 × 10−3 dilution) was detected in nymphs (fig. 5b). The signals after 10 units of time and below 200 RFU were not reliable and considered as no detection.

Figure 5. Amplification plots of real-time measurements for 10-fold serial dilutions of template DNA from P. leporinus. (a) Real-time PCR and (b) Real-time RPA fluorescence plots for adults (top panel) and nymphs (lower panel) using crude nucleic acid extracts. The threshold level for reliable P. leporinus detection was established as equal to 10 units (each unit equal to 40 s) and baseline of fluorescent signals to 200 RFU indicated with a green line. The amplified COI gene fragment in each assay was additionally separated on 1% agarose gels. The 100 bp ladder was used as DNA marker (M).

Discussion

Recently, a PCR method based on COI gene was developed to specifically identify and distinguish all life stages of P. leporinus from the two closely related planthopper species (Pfitzer et al., Reference Pfitzer, Varrelmann, Hesse and Eini2022a). In this study, we further developed a more rapid assay based on real-time RPA to identify and monitor P. leporinus in a short time and without the need for pure DNA extraction and gel electrophoresis.

Isothermal DNA amplification methods such as RPA (Piepenburg et al., Reference Piepenburg, Williams, Stemple and Armes2006) that works under ambient temperature (37–42°C) with short reaction time (5–20 min), considerable sensitivity and specificity, resistance to inhibitors and tolerance for more primer mismatches (Tan et al., Reference Tan, Liao, Liang, Yi, Zhou and Wei2022), increasingly was used for the detection and monitoring of pathogens (Li et al., Reference Li, Li, Fan, Zou, Zhang, Wang, Sun, Pan, Wu and Wang2018; Zhou et al., Reference Zhou, Zheng, Jiang, Liu, Zhang and Yan2022) and insects (Priti et al., Reference Priti, Jangra, Baranwal, Dietzgen and Ghosh2021). To detect the RPA products in end-point assays, agarose gel electrophoresis (Tran et al., Reference Tran, Tran, Pham and Phung2022) and lateral flow (Zhou et al., Reference Zhou, Zheng, Jiang, Liu, Zhang and Yan2022) have been used. For real-time detection, in most cases an exo-probe which is specific for TwistAmp exo kit has been applied (Li et al., Reference Li, Li, Fan, Zou, Zhang, Wang, Sun, Pan, Wu and Wang2018; Babujee et al., Reference Babujee, Witherell, Mikami, Aiuchi, Charkowski and Rakotondrafara2019). For example, real-time RPA assay was used for the rapid, simple, reliable, and sensitive detection of Campylobacter jejuni in food samples (Geng et al., Reference Geng, Liu, Liu, Deng, Zhao, Sun, Wang, Zhao and Wang2019). In addition, RPA reaction can be detected using DNA intercalating fluorophores such as SYBR Green I (Azinheiro et al., Reference Azinheiro, Roumani, Rodríguez-Lorenzo, Carvalho, Prado and Garrido-Maestu2022). However, due to non-specific interaction with double stranded DNA, this method produces false-positive results (Zou et al., Reference Zou, Mason and Botella2020). To avoid such errors, we developed a real-time based RPA which specifically detects the amplified target gene of P. leporinus in a short time (about 7 min) and does not require probe design or agarose gel electrophoresis, which can save time and costs.

RPA assays were shown to amplify DNA targets from impure DNA templates and crude extracts from plants (Londoño et al., Reference Londoño, Harmon and Polston2016; Qian et al., Reference Qian, Lu, Meng, Ye, Wang, Wang, Zheng, Wu and Wu2018; McCoy et al., Reference McCoy, Miles, Bilodeau, Woods, Blomquist, Martin and Chilvers2020) and insects (Priti et al., Reference Priti, Jangra, Baranwal, Dietzgen and Ghosh2021). Most reports have used general extraction buffer (McCoy et al., Reference McCoy, Miles, Bilodeau, Woods, Blomquist, Martin and Chilvers2020), Tris-EDTA, CTAB-Tris buffer or Tris-HCl as extraction buffer for template DNA preparation from plant tissue (Kalischuk et al., Reference Kalischuk, Roberts and Paret2020). In addition, PBS was also used for plant template DNA preparation (Kalischuk et al., Reference Kalischuk, Roberts and Paret2020). We have recently shown that PBS extracts from P. leporinus are suitable for the specific PCR-based detection of this insect vector (Pfitzer et al., Reference Pfitzer, Varrelmann, Hesse and Eini2022a). In this study, the PBS extracted samples were used for specific detection of both adults and nymphal stages of P. leporinus using real-time PCR and real-time RPA. In both assays, PBS extracts showed a comparable sensitivity of detection for both adults and nymphal stages. A ten-fold dilution of nucleic acids up to 10−6 for adult samples and up to 10−5 for nymph samples was still detectable in real-time PCR and real-time RPA assays, respectively. This confirms the sensitivity of real-time RPA for detection of P. leporinus even from a low concentration of nucleic acid samples which can be applied for detection of this insect vector from a mixture of cixiid planthoppers. An excellent correlation between real-time PCR and real-time RPA assays for detection of Human mastadenoviruses (HAdVs) (Wu et al., Reference Wu, Wu, Zhao, Hu, Ge, Zhu, Zhang, Zhou, Zhu and Cui2019), small ruminant morbillivirus (SRMV) (Li et al., Reference Li, Li, Fan, Zou, Zhang, Wang, Sun, Pan, Wu and Wang2018) and C. jejuni in food samples (Geng et al., Reference Geng, Liu, Liu, Deng, Zhao, Sun, Wang, Zhao and Wang2019) supports our results. Figure 3 shows that in the real-time PCR assay, the fluorescence intensity for both pure and crude nucleic acid were comparable in adult samples. However, a lower level of fluorescence signals was observed in nymphal crude samples. In the real-time RPA assay, the fluorescence intensity for both pure and crude nucleic acid were comparable in both adult and nymph samples. This may reflect the resistance to inhibitors by RPA assays compared to real-time PCR.

Rapid detection (ca 7 min) of P. leporinus using real-time RPA is the main advantage over real-time PCR. Similarly, the analysis time for monitoring food samples for C. jejuni by real-time RPA was reduced from 60 to approximately 13 min and the results were as reliable as those of the real-time PCR assay (Geng et al., Reference Geng, Liu, Liu, Deng, Zhao, Sun, Wang, Zhao and Wang2019). According to the kit instruction and published reports the optimised temperature is between 37 and 42°C for 15–20 min reaction time (Londoño et al., Reference Londoño, Harmon and Polston2016; McCoy et al., Reference McCoy, Miles, Bilodeau, Woods, Blomquist, Martin and Chilvers2020; Londono et al., Reference Londono, Ghasemi, Lawand and Dashti2021). However, at lower temperature as low as 25°C, RPA produced amplicons only at a longer incubation time (Wang et al., Reference Wang, Chen, Nie, Zhong, Li, Li, Huang, Fu, Liu and Nie2020). In contrast, the incubation time could be shortened to 5 min when the reaction temperature was 42°C (Lee et al., Reference Lee, Kim, Lee and Jeong2020; Kim et al., Reference Kim, Lee, Kim and Jeong2022). In this study, non-target insects produced weak fluorescence signals and non-specific curves with a clear delay. In both assays, the amplicon products were tested on agarose gel and showed no detectable products, which confirm the specificity of both assays. Such non-specific curves were also observed in non-target nematode samples (Subbotin, Reference Subbotin2019) and Fusarium oxysporum detection using real-time RPA assays (Zou et al., Reference Zou, Mason and Botella2020). Therefore, a defined threshold for the reaction period and RFU for real-time RPA assays need to be optimised during assay development to avoid false positive results. In conclusion, the developed real-time RPA allows a rapid and sensitive assay for specific detection of adults and nymphal stages of P. leporinus. This method can be further developed for field application and monitoring the main SBR vector in a short time (under 7 min). Such real-time RPA approach was successfully applied in the field for the rapid (under 15 min) and specific detection of Phytophthora sp. in various crops using lyophilised reagents (McCoy et al., Reference McCoy, Miles, Bilodeau, Woods, Blomquist, Martin and Chilvers2020) and for rapid and real-time detection of Xanthomonas gardneri and X. euvesicatoria the causal agents of bacterial spots in tomato plants in fields (Strayer-Scherer, Reference Strayer-Scherer2019).

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0007485324000099

Acknowledgements

We thank Z. Shoaei, J. Nienstedt and G. Hesse for their technical supports. This research was funded by Board of Trustees for sugar beet trials and advice (Kuratorium für Versuchswesen und Beratung im Zuckerrübenanbau; Mannheim, Germany) and the Institute of Sugar Beet Research, Goettingen.

Competing interests

None.

References

Ali, MM, Li, F, Zhang, Z, Zhang, K, Kang, DK, Ankrum, JA, Le, XC and Zhao, W (2014) Rolling circle amplification: a versatile tool for chemical biology, materials science and medicine. Chemical Society Reviews 43, 33243341.10.1039/c3cs60439jCrossRefGoogle ScholarPubMed
Azinheiro, S, Roumani, F, Rodríguez-Lorenzo, L, Carvalho, J, Prado, M and Garrido-Maestu, A (2022) Combination of recombinase polymerase amplification with SYBR Green I for naked-eye, same-day detection of Escherichia coli O157:H7 in ground meat. Food Control 132, 108494.10.1016/j.foodcont.2021.108494CrossRefGoogle Scholar
Babujee, L, Witherell, RA, Mikami, K, Aiuchi, D, Charkowski, AO and Rakotondrafara, AM (2019) Optimization of an isothermal recombinase polymerase amplification method for real-time detection of Potato virus Y O and N types in potato. Journal of Virological Methods 267, 1621.10.1016/j.jviromet.2019.02.006CrossRefGoogle Scholar
Behrmann, S, Schwind, M, Schieler, M, Vilcinskas, A, Martinez, O, Lee, K-Z and Lang, C (2021) Spread of bacterial and virus yellowing diseases of sugar beet in South and Central Germany from 2017–2020. Sugar Industry 146, 476485.10.36961/si27343CrossRefGoogle Scholar
Bertin, S, Picciau, L, Ács, Z, Alma, A and Bosco, D (2010a) Molecular identification of the Hyalesthes species (Hemiptera: Cixiidae) occurring in vineyard agroecosystems. Annals of Applied Biology 157, 435445.10.1111/j.1744-7348.2010.00434.xCrossRefGoogle Scholar
Bertin, S, Picciau, L, Ács, Z, Alma, A and Bosco, D (2010b) Molecular differentiation of four Reptalus species (Hemiptera: Cixiidae). Bulletin of Entomological Research 100, 551558.10.1017/S0007485309990605CrossRefGoogle ScholarPubMed
Biedermann, R and Niedringhaus, R (2004) Die Zikaden Deutschlands: Bestimmungstafeln für alle Arten Scheeßel, Wissenschaftlicher Akademischer Buchvertrieb. Fründ, Scheeßel, Germany.Google Scholar
Bressan, A (2009) Agronomic practices as potential sustainable options for the management of Pentastiridius leporinus (Hemiptera: Cixiidae) in sugar beet crops. Journal of Applied Entomology 133, 760766.10.1111/j.1439-0418.2009.01407.xCrossRefGoogle Scholar
Bressan, A, Sémétey, O, Nusillard, B, Clair, D and Boudon-Padieu, E (2008) Insect vectors (Hemiptera: Cixiidae) and pathogens associated with the disease Syndrome “Basses Richesses” of Sugar beet in France. Plant Disease 92, 113119.10.1094/PDIS-92-1-0113CrossRefGoogle Scholar
Bressan, A, Arneodo, J, Simonato, M, Haines, WP and Boudon-Padieu, E (2009a) Characterization and evolution of two bacteriome-inhabiting symbionts in cixiid planthoppers (Hemiptera: Fulgoromorpha: Pentastirini). Environmental Microbiology 11, 32653279.10.1111/j.1462-2920.2009.02055.xCrossRefGoogle ScholarPubMed
Bressan, A, Holzinger, WE, Nusillard, B, Sémétéy, O, Gatineau, F, Simonato, M and Boudon-Padieu, E (2009b) Identification and biological traits of a planthopper from the genus Pentastiridius (Hemiptera: Cixiidae) adapted to an annual cropping rotation. European Journal of Entomology 106, 405413.10.14411/eje.2009.052CrossRefGoogle Scholar
Bressan, A, Moral García, FJ and Boudon-Padieu, E (2011) The prevalence of ‘Candidatus Arsenophonus phytopathogenicus’ infecting the planthopper Pentastiridius leporinus (Hemiptera: Cixiidae) increase nonlinearly with the population abundance in sugar beet fields. Environmental Entomology 40, 13451352.10.1603/EN10257CrossRefGoogle ScholarPubMed
Ceotto, P and Bourgoin, T (2008) Insights into the phylogenetic relationships within Cixiidae (Hemiptera: Fulgoromorpha): cladistic analysis of a morphological dataset. Systematic Entomology 33, 484500.10.1111/j.1365-3113.2008.00426.xCrossRefGoogle Scholar
Emeljanov, AF (2020) Nomenclatorial changes in the family Cixiidae (Homoptera, Auchenorrhyncha, Fulgoroidea), with fixation of type species of the genus Reptalus Emeljanov, 1971 and description of a new subgenus. Zootaxa 4780, 197200.10.11646/zootaxa.4780.1.11CrossRefGoogle ScholarPubMed
Gatineau, F, Jacob, N, Vautrin, S, Larrue, J, Lherminier, J, Richard-Molard, M and Boudon-Padieu, E (2002) Association with the syndrome “Basses Richesses” of sugar beet of a Phytoplasma and a bacterium-like organism transmitted by a Pentastiridius sp. Phytopathology 92, 384392.10.1094/PHYTO.2002.92.4.384CrossRefGoogle Scholar
Geng, Y, Liu, G, Liu, L, Deng, Q, Zhao, L, Sun, XX, Wang, J, Zhao, B and Wang, J (2019) Real-time recombinase polymerase amplification assay for the rapid and sensitive detection of Campylobacter jejuni in food samples. Journal of Microbiological Methods 157, 3136.10.1016/j.mimet.2018.12.017CrossRefGoogle ScholarPubMed
Hebert, PD, Cywinska, A, Ball, SL and deWaard, JR (2003) Biological identifications through DNA barcodes. Proceedings: Biological Sciences 270, 313321.Google ScholarPubMed
Holzinger, WE, Kammerlander, I and Nickel, H (2003) The Auchenorrhyncha of Central Europe = Die Zikaden Mitteleuropas Leiden, The Netherlands, Brill. Leiden, The Netherlands.Google Scholar
Jeong, YJ, Park, K and Kim, DE (2009) Isothermal DNA amplification in vitro: the helicase-dependent amplification system. Cellular and Molecular Life Sciences 66, 33253336.10.1007/s00018-009-0094-3CrossRefGoogle ScholarPubMed
Kalischuk, ML, Roberts, PD and Paret, ML (2020) A rapid fluorescence-based real-time isothermal assay for the detection of Cucurbit yellow stunting disorder virus in squash and watermelon plants. Molecular and Cellular Probes 53, 101613.10.1016/j.mcp.2020.101613CrossRefGoogle ScholarPubMed
Kim, NK, Lee, HJ, Kim, SM and Jeong, RD (2022) Rapid and visual detection of barley yellow dwarf virus by reverse transcription recombinase polymerase amplification with lateral flow strips. Plant Pathology Journal 38, 159166.10.5423/PPJ.NT.01.2022.0009CrossRefGoogle ScholarPubMed
Lee, HJ, Kim, HJ, Lee, K and Jeong, RD (2020) Rapid detection of peach latent mosaic viroid by reverse transcription recombinase polymerase amplification. Molecular and Cellular Probes 53, 101627.10.1016/j.mcp.2020.101627CrossRefGoogle ScholarPubMed
Li, Y, Li, L, Fan, X, Zou, Y, Zhang, Y, Wang, Q, Sun, C, Pan, S, Wu, X and Wang, Z (2018) Development of real-time reverse transcription recombinase polymerase amplification (RPA) for rapid detection of peste des petits ruminants virus in clinical samples and its comparison with real-time PCR test. Scientific Reports 8, 17760.10.1038/s41598-018-35636-5CrossRefGoogle ScholarPubMed
Livak, KJ and Schmittgen, TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(t)) method. Methods (San Diego, Calif.) 25, 402408.10.1006/meth.2001.1262CrossRefGoogle ScholarPubMed
Lobato, IM and O'Sullivan, CK (2018) Recombinase polymerase amplification: basics, applications and recent advances. Trends in Analytical Chemistry 98, 1935.10.1016/j.trac.2017.10.015CrossRefGoogle ScholarPubMed
Londoño, MA, Harmon, CL and Polston, JE (2016) Evaluation of recombinase polymerase amplification for detection of begomoviruses by plant diagnostic clinics. Virology Journal 13, 48.10.1186/s12985-016-0504-8CrossRefGoogle ScholarPubMed
Londono, J, Ghasemi, S, Lawand, G and Dashti, M (2021) Evaluation of the golden proportion in the natural dentition: a systematic review and meta-analysis. Journal of Prosthetic Dentistry 129, 696702.10.1016/j.prosdent.2021.07.020CrossRefGoogle ScholarPubMed
Mahillon, M, Groux, R, Bussereau, F, Brodard, J, Debonneville, C, Demal, S, Kellenberger, I, Peter, M, Steinger, T and Schumpp, O (2022) Virus yellows and syndrome “Basses Richesses” in western Switzerland: a dramatic 2020 season calls for urgent control measures. Pathogens (Basel, Switzerland) 11, 885.Google Scholar
McCoy, AG, Miles, TD, Bilodeau, GJ, Woods, P, Blomquist, C, Martin, FN and Chilvers, MI (2020) Validation of a preformulated, field deployable, recombinase polymerase amplification assay for phytophthora species. Plants (Basel) 9, 446.Google ScholarPubMed
Mota, DS, Guimarães, JM, Gandarilla, AMD, Filho, J, Brito, WR and Mariúba, LAM (2022) Recombinase polymerase amplification in the molecular diagnosis of microbiological targets and its applications. Canadian Journal of Microbiology 68, 383402.10.1139/cjm-2021-0329CrossRefGoogle ScholarPubMed
Mullis, K, Faloona, F, Scharf, S, Saiki, R, Horn, G and Erlich, H (1986) Specific enzymatic amplification of DNA in vitro: the polymerase chain reaction. Cold Spring Harbor Symposia on Quantitative Biology 51, 263273.10.1101/SQB.1986.051.01.032CrossRefGoogle ScholarPubMed
Notomi, T, Okayama, H, Masubuchi, H, Yonekawa, T, Watanabe, K, Amino, N and Hase, T (2000) Loop-mediated isothermal amplification of DNA. Nucleic Acids Research 28, E63.10.1093/nar/28.12.e63CrossRefGoogle ScholarPubMed
Pfitzer, R (2019) Investigation of the spread and control of SBR in sugar beet (In Germany) (MSc Thesis). University of Hohenheim, Germany.Google Scholar
Pfitzer, R, Schrameyer, K, Voegele, RT, Maier, J, Lang, C and Varrelmann, M (2020) Ursachen und Auswirkungen des Auftretens von „Syndrome des basses richesses” in deutschen Zuckerrübenanbaugebieten. Sugar Industry 145, 234244.Google Scholar
Pfitzer, R, Varrelmann, M, Hesse, G and Eini, O (2022a) Molecular detection of Pentastiridius leporinus, the main vector of the syndrome ‘Basses richesses’ in sugar beet. Insects 13, 992.10.3390/insects13110992CrossRefGoogle ScholarPubMed
Pfitzer, R, Varrelmann, M, Schrameyer, K and Rostás, M (2022b) Life history traits and a method for continuous mass rearing of the planthopper Pentastiridius leporinus, a vector of the causal agent of syndrome “basses richesses” in sugar beet. Pest Management Science 78, 47004708.10.1002/ps.7090CrossRefGoogle Scholar
Piepenburg, O, Williams, CH, Stemple, DL and Armes, NA (2006) DNA detection using recombination proteins. PLoS Biology 4, e204.10.1371/journal.pbio.0040204CrossRefGoogle ScholarPubMed
Priti, , Jangra, S, Baranwal, VK, Dietzgen, RG and Ghosh, A (2021) A rapid field-based assay using recombinase polymerase amplification for identification of Thrips palmi, a vector of tospoviruses. Journal of Pest Science 94, 219229.10.1007/s10340-020-01284-wCrossRefGoogle ScholarPubMed
Qian, W, Lu, Y, Meng, Y, Ye, Z, Wang, L, Wang, R, Zheng, Q, Wu, H and Wu, J (2018) Field detection of citrus huanglongbing associated with ‘ Candidatus Liberibacter asiaticus’ by recombinese polymerase amplification within 15 min. Journal of Agricultural and Food Chemistry 66, 54735480.10.1021/acs.jafc.8b01015CrossRefGoogle ScholarPubMed
Sémétey, O, Gatineau, F, Bressan, A and Boudon-Padieu, E (2007a) Characterization of a gamma-3 Proteobacteria responsible for the syndrome “Basses Richesses” of sugar beet transmitted by pentastiridius sp. (Hemiptera, Cixiidae). Phytopathology 97, 7278.10.1094/PHYTO-97-0072CrossRefGoogle Scholar
Sémétey, O, Bressan, A, Gatineau, F and Boudon-Padieu, E (2007b) Development of a specific assay using RISA for detection of the bacterial agent of ‘basses richesses’ syndrome of sugar beet and confirmation of a Pentastiridius sp. (Fulgoromopha, Cixiidae) as the economic vector. Plant Pathology 56, 797804.10.1111/j.1365-3059.2007.01693.xCrossRefGoogle Scholar
Sémétey, O, Bressan, A, Richard-Molard, M and Boudon-Padieu, E (2007c) Monitoring of proteobacteria and phytoplasma in sugar beets naturally or experimentally affected by the disease syndrome ‘Basses richesses’. European Journal of Plant Pathology 117, 187196.10.1007/s10658-006-9087-3CrossRefGoogle Scholar
Strayer-Scherer, A (2019) Recombinase polymerase amplification assay for field detection of tomato bacterial spot pathogens. Phytopathology 109, 690700.10.1094/PHYTO-03-18-0101-RCrossRefGoogle ScholarPubMed
Subbotin, SA (2019) Recombinase polymerase amplification assay for rapid detection of the root-knot nematode Meloidogyne enterolobii. Nematology 21, 243251.10.1163/15685411-00003210CrossRefGoogle Scholar
Tan, M, Liao, C, Liang, L, Yi, X, Zhou, Z and Wei, G (2022) Recent advances in recombinase polymerase amplification: principle, advantages, disadvantages and applications. Frontiers Cellular Infection Microbiology 12, 1019071.10.3389/fcimb.2022.1019071CrossRefGoogle ScholarPubMed
Teoh, BT, Sam, SS, Tan, KK, Danlami, MB, Shu, MH, Johari, J, Hooi, PS, Brooks, D, Piepenburg, O, Nentwich, O, Wilder-Smith, A, Franco, L, Tenorio, A and AbuBakar, S (2015) Early detection of dengue virus by use of reverse transcription-recombinase polymerase amplification. Journal of Clinical Microbiology 53, 830837.10.1128/JCM.02648-14CrossRefGoogle ScholarPubMed
Tran, DH, Tran, HT, Pham, TNM and Phung, HTT (2022) Direct multiplex recombinase polymerase amplification for rapid detection of S taphylococcus aureus and P seudomonas aeruginosa in food. Molecular Biology Research and Communication 11, 110.Google ScholarPubMed
Virgilio, M, Backeljau, T, Nevado, B and De Meyer, M (2010) Comparative performances of DNA barcoding across insect orders. BMC Bioinformatics 11, 206.10.1186/1471-2105-11-206CrossRefGoogle ScholarPubMed
Wan Rasni, WHN, Yahaya, N and Mohamed Rehan, M (2022) Recombinase polymerase amplification and their application in phytopathogen detection. Malaysian Journal of Science Health & Technology 8, 1424.10.33102/mjosht.v8i2.254CrossRefGoogle Scholar
Wang, Y, Chen, R, Nie, X, Zhong, Z, Li, C, Li, K, Huang, W, Fu, X, Liu, J and Nie, B (2020) Rapid and sensitive detection of potato virus Y by isothermal reverse transcription-recombinase polymerase amplification assay in potato. Molecular and Cellular Probes 50, 101505.10.1016/j.mcp.2019.101505CrossRefGoogle ScholarPubMed
Wu, T, Wu, H, Zhao, K, Hu, C, Ge, Y, Zhu, X, Zhang, X, Zhou, M, Zhu, F and Cui, L (2019) Rapid detection of human mastadenovirus species B by recombinase polymerase amplification assay. BMC Microbiology 19, 17.10.1186/s12866-018-1365-7CrossRefGoogle ScholarPubMed
Zhou, Y, Zheng, HY, Jiang, DM, Liu, M, Zhang, W and Yan, JY (2022) A rapid detection of tomato yellow leaf curl virus using recombinase polymerase amplification-lateral flow dipstick assay. Letters in Applied Microbiology 74, 640646.10.1111/lam.13611CrossRefGoogle ScholarPubMed
Zou, Y, Mason, MG and Botella, JR (2020) Evaluation and improvement of isothermal amplification methods for point-of-need plant disease diagnostics. PloS One 15, e0235216.10.1371/journal.pone.0235216CrossRefGoogle ScholarPubMed
Figure 0

Figure 1. Alignment of the specific primers to the COI gene of Pentastiridius leporinus and different members of Hyalesthes spp. and Reptalus spp. The identical nucleotides with the specific primers (black arrows) are shown with dots. The positions of the primers are shown based on the COI gene with GenBank accession number ON094072. Number of mismatches between primers and the analysed sequences are shown on the right side of each alignment.

Figure 1

Table 1. Primers used for the detection of Pentastiridius leporinus.

Figure 2

Figure 2. PCR and RPA for specific detection of Pentastiridius leporinus. A representative electrophoretic pattern of PCR (a) and RPA (b) products show specific amplification of the COI gene of P. leporinus (lanes 7 to 9). Lanes 1 to 3 represent R. quinquecostatus, and lanes 4 to 6 represent H. obsoletus samples. (c) RPA was performed for 5, 10, and 15 min at 39°C using DNA samples of R. quinquecostatus (lanes 1 to 3) and P. leporinus (lanes 4 to 6) adult samples. (d) RPA assay using 10-fold serial dilutions of crude nucleic acid of adults (top panel) or nymphs (lower panel) shows the sensitivity of this assay for amplification of COI gene of P. leporinus. RPA products were gel-separated without an additional purification step. The size of amplicons was compared with 100 bp ladder (M).

Figure 3

Figure 3. Real-time amplification of the COI gene for the specific detection of Pentastiridius leporinus. Real-time PCR (a) and real-time RPA (b) show specific amplification of the COI gene using pure (kit) or crude nucleic acid of both adults (female and male) and nymphs (L3, L4, and L5) of P. leporinus compared with samples of adult R. quinquecostatus and H. obsoletus. For each treatment three biological replicates were tested, and the average threshold cycle (Ct) is presented. The same letter on the bars means not statistically different (P < 0.05%).

Figure 4

Figure 4. Real-time RPA assay for the specific detection of Pentastiridius leporinus. (a) Real-time RPA plot shows strong fluorescence signals for P. leporinus (5–8) and weak signals with a delay for R. quinquecostatus (1 and 2) and H. obsoletus (3 and 4). Time unit of each cycle represents 40 s. The threshold level for reliable P. leporinus detection was established as equal to 10 units of time (6.6 min) and baseline of fluorescent signals at 200 relative fluorescence units (RFU) indicated with the horizontal green line. (b) Electrophoretic patterns of real-time RPA products show clear amplification of the COI gene in P. leporinus samples. There were no amplicons for R. quinquecostatus adults and H. obsoletus adults. Lane numbers coordinate with panels A. RPA products were gel-separated without additional purification step. The size of amplicons was compared with 100 bp ladder (M).

Figure 5

Figure 5. Amplification plots of real-time measurements for 10-fold serial dilutions of template DNA from P. leporinus. (a) Real-time PCR and (b) Real-time RPA fluorescence plots for adults (top panel) and nymphs (lower panel) using crude nucleic acid extracts. The threshold level for reliable P. leporinus detection was established as equal to 10 units (each unit equal to 40 s) and baseline of fluorescent signals to 200 RFU indicated with a green line. The amplified COI gene fragment in each assay was additionally separated on 1% agarose gels. The 100 bp ladder was used as DNA marker (M).

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