Introduction
Lobesia botrana (Denis and Shiffermüller, 1776), commonly known as the European grapevine moth is an economically important pest of the vine-growing areas of North Africa, several countries of Asia and Europe as well as North and South America (Lucchi and Scaramozzino, Reference Lucchi and Scaramozzino2022). L. botrana feeds predominantly on grapes but it also has a host range across almost 27 plant families, a characteristic that contributes to the establishment of the pest in a wide range of ecological zones (Altimira et al., Reference Altimira, Vitta, Tapia, Morata, Loira and González2021). The larvae feed on flower clusters and berries which can subsequently facilitate the development of harmful fungi such as Botrytis cinerea and Aspergillus (Cozzi et al., Reference Cozzi, Somma, Haidukowski and Logrieco2013; Delbac and Thiéry, Reference Delbac and Thiéry2016).
Mating disruption using synthetic sex pheromones, natural enemies, biopesticides, and sterile insect techniques have been applied against L. botrana (reviewed in Benelli et al., Reference Benelli, Lucchi, Anfora, Bagnoli, Botton, Campos-Herrera, Carlos, Daugherty, Gemeno, Harari, Hoffmann, Ioriatti, López Plantey, Reineke, Ricciardi, Roditakis, Simmons, Tay, Torres-Vila, Vontas and Thiéry2023). However, chemical control, using insecticides has been the most common practice in many geographical regions, such as the Mediterranean Basin, including Greece and Turkey. Several insecticides have been used for L. botrana in these countries, including neonicotinoids (acetamiprid) avermectins (abamectin and emamectin benzoate), pyrethroids (acrinathrin, cypermethrin, deltamethrin, etofenprox, lambda-cyhalothrin and tau-fluvalinate), spinosyns (spinosad and spinetoram), diamides (chlorantraniliprole), oxidiazines (indoxacarb) and Bacillus thuringiensis (subsp. Aizawai and Kurstaki).
Despite a number of control failure reports, there are only a few confirmed resistance cases in L. botrana. For example, indoxacarb resistance has been identified through field trials and laboratory bioassays in Emilia-Romagna (Italy) and Manisa (Turkey) (Civolani et al., Reference Civolani, Boselli, Butturini, Chicca, Fano and Cassanelli2014; Durmuşoğlu et al., Reference Durmuşoğlu, Hatipoğlu, Gürkan and Moores2015; Hati̇poğlu et al., Reference Hati̇poğlu, Durmuşoğlu and Gürkan2015).
Insecticide resistance mechanisms primarily include modification of target sites and/or enhancement of detoxification (ffrench-Constant, Reference ffrench-Constant2013). Cytochrome P450s (P450s), glutathione S-transferases, and carboxylesterase are the key metabolic detoxification gene families (Li et al., Reference Li, Schuler and Berenbaum2007; Pavlidi et al., Reference Pavlidi, Kampouraki, Tseliou, Wybouw, Dermauw, Roditakis, Nauen, Van Leeuwen and Vontas2018; Nauen et al., Reference Nauen, Bass, Feyereisen and Vontas2022). Target site resistance, conferred by alterations (typically point mutations) on the molecular target of the insecticide, has been reported in several gene/subunit targets, including: nicotinic acetylcholine receptors against neonicotinoids and spinosyns (Silva et al., Reference Silva, Berger, Bass, Williamson, Moura, Ribeiro and Siqueira2016); acetylcholinesterases against organophosphates (Feyereisen et al., Reference Feyereisen, Dermauw and Van Leeuwen2015); voltage gated sodium channels (knock-down resistance) against pyrethroids; glutamate gated chloride channels against avermectins (Casida and Durkin, Reference Casida and Durkin2013; ffrench-Constant, Reference ffrench-Constant2013) and ryanodine receptor against diamides (Douris et al., Reference Douris, Papapostolou, Ilias, Roditakis, Kounadi, Riga, Nauen and Vontas2017).
Monitoring insecticide resistance, using bioassays and/or molecular diagnostic tools (Van Leeuwen et al., Reference Van Leeuwen, Dermauw, Mavridis and Vontas2020) is important to design and apply evidence-based insecticide resistance management (IRM) strategies. However, the analysis of insecticide resistance mechanisms at the molecular level and the identification of specific molecular markers for resistance have been hampered by the lack of genomic information in L. botrana.
The aim of this study was to monitor the susceptibility of L. botrana populations from Greece and Turkey, against different insecticides registered and used for their control. Molecular analysis of the insecticide target site was also performed, aiming to identify known conserved resistance mutations. Finally, the L. botrana CYPome was identified and phylogenetically characterised.
Materials and methods
Insect collection and rearing
Seven L. botrana populations from Crete, Greece were collected from the following locations: Vagiona, Episkopi, Archanes, Alagni, and Ano Archanes (table S1). The laboratory susceptible reference strain (LB-S), which originated from Bordeaux France, and maintained under laboratory conditions for more than 20 years was used as a reference strain, for the analysis of resistance ratio factors in this subgroup (L. botrana populations from Greece).
Five populations of L. botrana were collected from different locations in Turkey, respectively: Manisa-Merkez, Manisa-Alaşehir, Manisa-Ahmetli, Manisa-Saruhanlı, Denizli. One population (namely S strain), was collected for Kahramanmaraş area, more than 700 km away from Manisa and Denizli areas (fig. 1) where viticulture is less intense and pest control is practically absent. This field population (Kahramanmaraş) was used as a control, to calculate resistance levels, for the populations collected in Turkey.
The collection sites for the L. botrana populations tested, were in Greece and Turkey. S: Kahramanmaraş strain (susceptible reference strain), R; Manisa-Merkez strain, MA: Manisa-Alaşehir strain, MAh: Manisa-Ahmetli strain, MS: Manisa-Saruhanlı strain, D: Denizli strain.
The exact location of all the collection sites is shown in fig. 1, while a detailed record for each population from both Greece and Turkey is provided in table S1. For each population, an assigned code name was used. Insects were collected as larvae of different stages from infested grape berries. The collected larvae were transferred into trays with artificial diet, where they started feeding and completed their life cycle. Emerging adults were used to establish respective strains from each population under laboratory conditions. The insect-rearing protocol for the Greek and the Turkish populations was according to Mironidis and Savopoulou-Soultani, Reference Mironidis and Savopoulou-Soultani2008 and Durmuşoğlu et al., Reference Durmuşoğlu, Hatipoğlu, Gürkan and Moores2015, respectively. All populations were maintained at 25 ± 2 °C and 60–65% relative humidity in the laboratory with a fixed 16:8 (L:D) photoperiod. The Greek strains were maintained on an artificial diet for two to three generations.
Insecticides
The insecticides tested in bioassays L. botrana populations from Greece were the following: the pyrethroids (group 3A-IRAC classification) etofenprox (Therbonal 28.75 EC, Mitsui Chemicals, Tokyo) and alpha-cypermethrin (Fastac 10 EC, BASF S.E., Germany); the neonicotinoid (group 4A) acetamiprid (Carnadine 20 SL, Nufarm, Australia); the spinosyns (group 5) spinetoram (Radiant 120 SC, Corteva, Switzerland) and spinosad (Laser 480 SC, Dow, USA); the avermectin (group 6) emamectin benzoate (Affirm 095 SG, Syngenta, UK); the oxadiazine indoxacarb (Stewart 30 WG, DuPont, France) and; the diamide (group 28) chlorantraniliprole (Coragen 20 SG, DuPont, Switzerland).
The insecticides tested in bioassays with L. botrana populations from Turkey were the following: the pyrethroid (group 3A) deltamethrin (Decis 25 EC, Bayer, Germany); the oxadiazine (group 22A) indoxacarb (Avaunt® 150 EC, DuPont, France); the spinosyn (group 5) spinosad (Laser 480 SC, Dow, USA).
Bioassays
The methodology used for analysing the susceptibility to insecticides of L. botrana populations from Greece was a slightly modified version of IRAC method 017. The modified method IRAC017 was initially validated against the standard IRAC017, by conducting dose response bioassays, on the susceptible reference strain LB-S.
Briefly, for the standard IRAC017 method, insecticide dilutions were mixed with ready to use stone fly diet mix (growth substrate previously tested for supporting L. botrana development (data not shown) (38–0600 Stonefly Heliothis Diet) at a ratio of 1 solution:40 diet, based on producers instructions. Small aliquots of the insecticide/diet mix were placed into individual cells of a 16-well polystyrene bioassay tray (BioServe, USA). A single neonate (1st instar larvae <24 h old) was placed into each well and the tray was covered and left for 96 h in the same conditions described previously for insect rearing (25 ± 2 °C, 60–65% RH and 16:8 h L:D). For the preparation of the modified IRAC017 method, while the final diet mixture was still in liquid form (at 40 °C), insecticide dilutions were added at a ratio of 1: 40. The mixture was allowed to cool down for 30 min. Once the diet became solid it was divided in bioassay trays. In each tray, 10 neonates were placed and left for 96 h as previously described. For both bioassay protocols (standard and modified IRAC017) all insecticide concentrations were calculated at the final diet volume. The mortality was assessed after 96 h (4 days) by counting dead and moribund larvae which were unable to make coordinated movement when they were gently poked with a fine brush.
A two-step approach was implemented in the resistance studies for Greek populations, using the modified IRAC017 protocol. First, there was implemented a single-dose bioassays approach, for putative resistance detection, followed by dose–response experiments for accurate resistance levels estimation. Briefly, full-dose experiments on the susceptible reference strain allowed the determination of the LC95 for each insecticide tested. This value was used as a diagnostic dose for putative insecticide resistance detection on the wild strains. The % mortality was assessed, using the aforementioned bioassay protocol. If the observed mortality at the diagnostic dose did not exceed 80%, the tested strains were considered as candidates for resistance development and full dose–response experiments were designed to estimate the extract LC values and the potential resistance levels. For each dose–response experiment 5–6 sequential insecticide concentrations were used resulting in mortality levels ranging between 0 and 100%. For each dose, three replicates were performed, with a total of 20 insects per dose. Insecticide concentrations were calculated as mg per L of diet and ranged between 0.01 and 1.0 for chlorantraniliprole, 30–300 for acetamiprid, 0.15–30.0 for alpha-cypermethrin, 43–1438 for etofenprox, 0.03–0.30 for spinetoram, 0.16–0.48 for spinosad, 0.01–0.48 for emamectin benzoate, and 1.5–4.5 for indoxacarb. All insecticide concentrations were predefined by preliminary range finder tests. In some cases, the total number of insects per bioassay was marginally lower than the minimum of 120, but some biological limitations posed by L. botrana (i.e. number of neonates available in a single day) made it very difficult to achieve.
Here it should be mentioned that the Greek and Turkish L. botrana populations were handled separately, using different methodologies. The bioassays for the L. botrana populations collected from Turkey were conducted using the diet incorporation method described by Durmuşoğlu et al., Reference Durmuşoğlu, Hatipoğlu, Gürkan and Moores2015. The insecticides were mixed with the artificial diet (mixture at 40 °C) while for control treatment, sterile distilled water was used at a ratio of 1: 9. The mixture was homogenised, left for 24 h at room temperature and then separated in 1 cm3 cubes. The cubes were placed into individual cells of the 16-well polystyrene bioassay tray to conduct the bioassays.
A single 3rd stage larva was placed into each well and the tray was covered and maintained at 25 ± 2 °C, 60–65% RH and a 16:8 h light:dark photoperiod. For the bioassay, six insecticide concentrations and a control were used. Each concentration included twenty 3rd stage larvae. Insecticide concentrations ranged between 0.02 and 200 mg l−1 for deltamethrin and spinosad, while for Indoxacarb the concentration ranged between 0.05 and 20 mg l−1. The mortality was assessed after 72 h, and larvae were considered dead if they were unresponsive to gentle prodding with a fine brush. If a larva failed to grow further to the pupal stage, it was recorded as dead. Each bioassay was repeated twice.
Statistical analysis
Mortality data from dose–response bioassays were subjected to probit analysis based on Finney (Reference Finney1964) using PriProbit 3.4 (Sakuma, Reference Sakuma1998) or Polo Plus (LeOra Software Inc., Berkeley, CA, USA). Both types of software test the linearity of dose–mortality response and provide the slope, the lethal concentrations (LC), and the 95% confidence limits (CL) of the lethal concentration for each mortality line. Using the appropriate function, the relative potency ratio among responses was calculated. Responses were considered significantly different when the 95% confidence interval of relative potency ratio did not include the value 1. Percentage mortality values generated in bioassays were corrected using Abbott's formula (Abbott, Reference Abbott1925). Resistance ratios (RR) were calculated by dividing the LC50 value of the resistant strains by that of the susceptible strain.
RNA extraction and cDNA synthesis
For the transcriptome analysis, L. botrana larvae of the Kahramanmaraş population (S) and the Manisa-Merkez (R) populations from Turkey were placed in microcentrifuge tubes and rapidly frozen in liquid nitrogen before storage at −80 °C. Total RNA was extracted from of mixed-age insects using a total RNA purification kit (GeneMark, Taiwan) according to the manufacturer's instructions. DNase treatment followed, to eliminate the presence of gDNA in the RNA samples. Agarose gel electrophoresis and spectrophotometry (NanoDrop 2000, Thermo Fisher Scientific, USA) were used to assess the integrity and the concentration of each RNA sample respectively. RNA concentration was measured using Qubit® RNA Assay Kit in Qubit® 2.0 Fluorometer (Life Technologies, CA, USA). RNA integrity was assessed using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA, USA).
For the target sequencing analysis, total RNA was extracted from all seven populations from Crete (table S1), originating from pools of 20 L2 instar larvae/population using Trizol reagent (MRC, Cincinnati, OH, USA), according to the manufacturer's instructions (1 ml of TRIzol per prep). RNA samples were treated with Turbo DΝase (Ambion, Foster City, CA, USA) to remove genomic DNA. Then, 3 μg of the treated RNA was used to generate first-strand cDNA using oligo-dT20 primers with Superscript III reverse transcriptase (Invitrogen, Carlsbad, CA, USA).
Library preparation and transcriptome sequencing
A total amount of 3 μg RNA per sample was used as input material for RNA library preparations. Sequencing libraries were generated using NEB Next® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer's recommendations and index codes were added to attribute sequences to each sample. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads. Fragmentation was carried out using divalent cations under elevated temperature in NEB Next First Strand Synthesis Reaction Buffer (5x). First-strand cDNA was synthesised using random hexamer primer and M-MuLV Reverse Transcriptase (Rnase H-). Second-strand cDNA synthesis was subsequently conducted using DNA polymerase I and RNase H. Remaining overhangs were converted into blunt ends via exonuclease/polymerase activities. After adenylation of 3′ ends of DNA fragments, NEB Next Adaptor with a hairpin loop of 150–200 bp in length, the library fragments were purified with AMPure XP system (Beckman Coulter, Beverly, USA). Then 3 μl USER Enzyme (NEB, USA) was used with size-selected, adaptor-ligated cDNA at 37 °C for 15 min followed by 5 min at 95 °C before PCR. Then PCR was performed with Phusion High-Fidelity DNA polymerase, Universal PCR primers, and Index Primer. At last, PCR products were purified (AMPure XP system) and the library quality was assessed on the Agilent Bioanalyzer 2100 system. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using HiSeq PE Cluster Kit cBot-HS (Illumina) according to the manufacturer's instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 150 bp paired-end reads were generated. The sequencing reads are available from the Sequence Read Archive (SRA) under the BioProject accession PRJNA827155.
De novo transcriptome assembly
Reads from both the resistant and the susceptible population were first quality-trimmed with Trimmomatic v0.39 (Bolger et al., Reference Bolger, Lohse and Usadel2014) with default parameters. The trimmed reads were then assembled de novo using Trinity v2.5.1 (Grabherr et al., Reference Grabherr, Haas, Yassour, Levin, Thompson, Amit, Adiconis, Fan, Raychowdhury, Zeng, Chen, Mauceli, Hacohen, Gnirke, Rhind, di Palma, Birren, Nusbaum, Lindblad-Toh, Friedman and Regev2011), with parameters ‘-seqType fq –max_memory 50G’. The assembled transcriptome is available from the Transcriptome Shotgun Assembly (TSA) under the BioProject accession PRJNA827155.
Analysis of loci containing conserved target site insecticide resistance mutations
The raw reads were then mapped onto the unfiltered Trinity contigs using Hisat2 (Kim et al., Reference Kim, Paggi, Park, Bennett and Salzberg2019) and the generated SAM files were converted to sorted BAM files using SAMtools (Li et al., Reference Li, Handsaker, Wysoker, Fennell, Ruan, Homer, Marth, Abecasis and Durbin2009). VarScan v2.4.4 (Koboldt et al., Reference Koboldt, Zhang and Larson2012) was used to detect statistically significant SNPs in genes that are known targets of specific insecticides (table S3). The Lobesia target genes were searched in the de novo assembled transcriptome using BLAST. More specifically, the amino acid sequence of the genes that are known to be involved in insecticide resistance in other species was BLASTed against the Lobesia transcriptome. Finally, the SNPs were manually inspected in the Integrative Genomics Viewer v2.6.3 (Robinson et al., Reference Robinson, Thorvaldsdottir, Winckler, Guttman and Lander2011).
Analysis of loci containing conserved target site insecticide resistance mutations by PCR and sequencing
cDNA was used as a template for PCR amplification of target-site gene fragments encompassing insecticide resistance mutations, identified in various arthropod species and highly linked with insecticide resistance (table S3). For the ace gene of L. botrana specific primers were designed based on the available mRNA on NCBI (accession number: JQ771363.1). For the rest of the genes of interest, primers were designed in conserved gene regions (table S3) based on available mRNA sequences of ten Lepidopteran species in NCBI. PCR reactions (50 μl) contained 1ul cDNA, 0.4 mM primers, 0.2 mM dNTPs, 5 μl of 10 × buffer, and 1U Kapa Taq DNA polymerase (KAPABIOSYSTEMS). The thermal conditions were: 95 °C for 2 min, followed by 35 cycles of 95 °C for 30 s, 54–60 °C for 30 s (depending on the primer set for the gene of interest in table S3), 72 °C for 60 s, and final extension at 72 °C for 2 min. PCR products were purified using NucleoSpin Extract II (Macherey-Nagel) and sequenced directly on PCR products with the original PCR primers (table S3). Sequencing reactions were performed at GENEWIZ (Germany). Sequencing data were analyzed with BioEdit v7.2 (Hall, Reference Hall1999). The presence/absence of target-site mutations was also based on visual examination of sequence chromatographs.
Identification of cytochrome P450 (CYP) genes
To identify the coding sequences of genes in the predicted Trinity transcripts and obtain the encoded proteins, TransDecoder programme (included in the Trinity suite) was used with the default parameters. From the resulting set of predicted protein contaminants, originating from ingested plant material were removed. To achieve this filtering step, a Diamond (Buchfink et al., Reference Buchfink, Xie and Huson2015) search of all the Trinity proteins against the Uniref50 (Suzek et al., Reference Suzek, Wang, Huang, McGarvey, Wu and Consortium2015) database was used. Using a set of custom Perl scripts we filtered out proteins whose first hit was bacterial, plant, or viral. Also using custom Perl scripts, we kept only the longest isoform per gene, by using the Trinity naming scheme and finally removed any identical sequences using CD-HIT (Fu et al., Reference Fu, Niu, Zhu, Wu and Li2012), with parameters ‘-n 5 -c 1.00 -M 64000’. Completeness was assessed using BUSCO v3.0.2 (Waterhouse et al., Reference Waterhouse, Seppey, Simão, Manni, Ioannidis, Klioutchnikov, Kriventseva and Zdobnov2018). This set of unigenes is available as a fasta file in the Supplementary Material (Supplementary File S1). InterProScan v5.28–67 (Jones et al., Reference Jones, Binns, Chang, Fraser, Li, McAnulla, McWilliam, Maslen, Mitchell, Nuka, Pesseat, Quinn, Sangrador-Vegas, Scheremetjew, Yong, Lopez and Hunter2014) was subsequently run on the final set of unigenes and the ones containing the IPR001128 InterPro domain were considered to be CYPs. In addition, we searched the entire set of unigenes using BLAST (Camacho et al., Reference Camacho, Coulouris, Avagyan, Ma, Papadopoulos, Bealer and Madden2009), against a curated collection of 2942 CYPs from a wide variety of arthropods (Dermauw et al., Reference Dermauw, Van Leeuwen and Feyereisen2020). L. botrana unigenes with significant similarity (e-value <1e-05), to any of the curated CYPs were also considered to be candidate CYPs. Unigenes identified by either method (InterProScan or BLAST hit against the curated CYPs) constituted our final set of L. botrana CYPs. The set of all L. botrana P450s is also available as a fasta file in the Supplementary Material (Supplementary File S2).
A phylogenetic analysis was conducted using the herein identified L. botrana CYPs, using the curated CYPome of the related cotton bollworm Helicoverpa armigera (Dermauw et al., Reference Dermauw, Van Leeuwen and Feyereisen2020) as a reference. More specifically, the amino acid sequence of the CYPomes of the two species were aligned using MAFFT (Katoh and Standley, Reference Katoh and Standley2013) with the ‘auto’ parameter. Next, the alignment was trimmed using Trimal (Capella-Gutierrez et al., Reference Capella-Gutierrez, Silla-Martinez and Gabaldon2009), with the ‘automated1’ parameter. RaxML (Stamatakis, Reference Stamatakis2014) was used for reconstructing a maximum likelihood phylogeny with 100 bootstrap replicates. Moreover, the human CYP51A1 was used as an outgroup and the automatic selection of the amino acid model (‘PROTGAMMAAUTO’). Finally, Evolview v2 (He et al., Reference He, Zhang, Gao, Lercher, Chen and Hu2016) was used for drawing and decorating the phylogenetic tree.
Results
Bioassay data – Lobesia botrana populations from Greece
The LC50 provided by the modified IRAC017 bioassay protocol were compared to the LC50 of the standard IRAC017 protocol for the insecticides chlorantraniliprole, alpha- cypermethrin, spinetoram, spinosad, etofenprox and acetamiprid (table S2). No statistically significant differences were detected in the response of the strain when using either bioassay approach (table S2). In addition, the chi-square values were either identical or lower in the modified IRAC017 bioassay protocol suggesting higher accuracy and reliability of the results, associated with the proposed method modification. This protocol was implemented in the toxicological studies hereafter.
Single-dose bioassays were conducted on wild strains using the LC95 of the susceptible strain (LB-S) as diagnostic dose. As shown in table S2, the diagnostic dose was 151 mg l−1 for etofenprox, 1.02 mg l−1 for alpha-cypermethrin, 36.1 mg l−1 for acetamiprid, 0.12 mg l−1 for spinetoram, 0.47 mg l−1 for spinosad, 0.2 mg l−1 for emamectin benzoate, 3.37 mg l−1 for indoxacarb and 0.39 mg l−1 for chlorantraniliprole. The percentage mortality rates for the insecticides emamectin benzoate, spinosad, and indoxacarb exceeded 80% at the diagnostic dose, (94.4–100% mortality in all wild strains), therefore full dose-response bioassays were not conducted for these chemicals. Chlorantraniliprole, acetamiprid, alpha-cypermethrin, etofenprox and spinetoram exhibited mortality levels below 80% at the diagnostic dose. To accurately evaluate the suspected resistance levels, full dose-response experiments were implemented. The responses of the wild populations were compared against the susceptible reference strain and the results are shown in table 1. In all cases, control mortality was found below 5% and the responses of the populations to the insecticides were homogenous and fitted the log-dose probit-mortality model. The LC50 for the insecticide chlorantraniliprole was estimated between 0.13 and 0.18, for alpha-cypermethrin between 0.92 and 1.58, for spinetoram between 0.06 and 0.12, for etofenprox between 90 and 102 and for acetamiprid at 43 (all values in mg l−1). The resistance levels (RR) of the wild populations from Greece to all insecticides were below 2-fold with the exception of alpha-cypermethrin where resistance scaled up to 3- and 5-fold (table 1).
Log dose probit mortality data for L. botrana populations from Greece
LB-S, laboratory susceptible reference strain; BAG 21-1, Bagiona strain; EPIS 21-4, Episkopi strain; N, number of larvae tested; CL, confidence limits; RR, resistance ratio; LC50 in mg l−1, χ 2 testing linearity of dose–mortality response: resistance ratio (RR) is based on strain LB-S.
*Different letters indicate significant differences in the responses (P < 0.05).
Bioassay data – Lobesia botrana populations from Turkey
In all the L. botrana populations from Turkey (mentioned in table 2), full dose–response bioassays for the insecticides deltamethrin, spinosad, and indoxacarb were performed (table 2). The population Kahramanmaras LC50 numbers for deltamethrin, spinosad, and indoxacarb were 1.22, 0.27, and 0.35 mg l−1, respectively.
Log dose probit mortality data for L. botrana populations from Turkey
S, Kahramanmaraş strain (susceptible reference strain); R, Manisa-Merkez strain; MA, Manisa-Alaşehir strain; MAh, Manisa-Ahmetli strain; MS, Manisa-Saruhanlı strain; D, Denizli strain; N, number of larvae; LC50, lethal concentration, expressed in ppm (95% confidence intervals); H, heterogeneity; RR, resistance ratio.
*Different letters indicate significant differences in the responses (P < 0.05).
The LC50 values of the tested populations varied from 21.66–36.57, 1.44–15.64, and 1.37–10.34 mg l−1 for deltamethrin, spinosad, and indoxacarb, respectively. The respected resistance ratio was up to 30-fold for deltamethrin and indoxacarb and up to 59-fold for spinosad. The Manisa-Merkez (R strain) exhibited the highest LC50 values in all three tested insecticides in all three tested insecticides (table 2).
Transcriptome assembly
A de novo transcriptome was assembled for L. botrana using the Trinity programme with the two Illumina libraries that were sequenced in the frame of this study. A total of 169,945 transcripts were assembled that are grouped into 98,064 unigenes (table S4). This transcriptome contains the complete sequence of 84% of the Insecta BUSCO, thus being fairly complete. A total of 43,857 proteins were predicted from the assembled transcripts. This set of proteins was first filtered in order to exclude contaminants, such as sequences with similarity to plant proteins (n = 43,322 proteins survived). Subsequently, only one protein per unigene was kept (n = 22,847 proteins survived) and as a last filtering step proteins identical with other proteins in the unigene set were excluded (n = 22,803 proteins survived). The BUSCO pipeline found the complete sequence for 79.5% of the Insecta data set. Such a considerable decrease (by 4.5%) compared to the unfiltered protein set is most probably due to the draft nature of gene prediction that is implemented here.
Analysis of insecticide targets for the presence of resistance mutations
Based on the de novo assembled L. botrana transcriptome (for resistant and susceptible populations from Turkey), as well as subsequent PCR and sequence investigations (populations from Greece), the presence of known resistance mutations or putative novel polymorphism in the insecticide binding sites associated with insecticide resistance was investigated (table S3 and fig. 2). The conditions and primer sets described above and in table S3 respectively, were used for this analysis, which included the insecticide targets VGSC (pyrethroids and oxadiazines); nAChR_α6; spinosad; RyR (diamides); GluCl (avermectins) and; AChE (organophosphates). The analysis revealed the absence of resistance mutation in all resistant or suspected resistance populations included in this analysis (nine in total: seven from Greece and two from Turkey, as mentioned in subsection RNA extraction and cDNA synthesis.).
Target site mutations linked to insecticide resistance in arthropod species, with the corresponding alignment in L. botrana populations. Five different target genes were checked for mutations implicated in resistance against six insecticides. No mutations were detected in any of the 23 positions (amino acids highlighted in red). The structure of the transmembrane domains (except for acetylcholinesterase) is shown for each gene and red stars mark the position in which each mutation occurs. Finally, the actual alignment of the relevant gene area is shown beneath each gene. The alignment contains three sequences; the consensus L. botrana sequence (i.e. the Trinity transcript), followed by the sequence of the susceptible (S) and resistant (R) strain, which were collected from different locations in Turkey.
The CYPome of lobesia botrana: annotation and phylogenetic characterisation
We identified 161 CYPs in the L. botrana transcriptome assembly (table S5). Only 49 of these CYPs appear to be full-length (>450 amino acids) with the remaining 112 unigenes being apparently fragmented. This fragmentation is probably due to the low RNA sequencing depth. Despite the occurrence of many fragmented CYPs, three of the four insect P450 clans (2, 3, and Mito) are well-supported with bootstrap values >65% (fig. 3). Additionally, many conserved families and subfamilies within each clan are also well-supported. The CYP4 clan, however, has a bootstrap support of 39%, which is considered to be relatively low.
Cytochrome P450 phylogeny. Maximum likelihood phylogeny of the grapevine moth CYPs (names shown in red) compared to those of the cotton bollworm, H. armigera (names shown in blue). All four insect CYP clans are well-supported with bootstrap values >65%. Branches from each of the four clans are coloured differently; Clan M – gold, Clan 2 – turquoise, Clan 3 – green, Clan 4 – orange. Full-length genes (>450 amino acids) are marked with a star, whereas those with a length between 250 and 450 amino acids are marked with a triangle. CYP clades that have bloomed in L. botrana, compared to H. armigera are annotated with a ‘+’ inside a light blue circle, whereas contractions are annotated with a ‘−’ inside a light red circle.
Discussion
Low to moderate insecticide resistance levels indoxacarb (4–30 fold), spinosad (5–59 fold), and deltamethrin (18–30 fold) were detected in L. botrana populations from Turkey, compared to a susceptible population from the same geographical region. However, resistance against chlorantraniliprole, alpha-cypermethrin, spinetoram, etofenprox, and acetamiprid was not detected (below 2.5 fold in all cases) in L. botrana populations from Greece, indicating that the phenomenon is not responsible for control failures often reported in the region. Other parameters, than insecticide efficacy, could be associated with these failures, such as the accurate estimation of application time (based on pest flight density), which is critical for the efficiency of the application (Benelli et al., Reference Benelli, Lucchi, Anfora, Bagnoli, Botton, Campos-Herrera, Carlos, Daugherty, Gemeno, Harari, Hoffmann, Ioriatti, López Plantey, Reineke, Ricciardi, Roditakis, Simmons, Tay, Torres-Vila, Vontas and Thiéry2023). Cultural practices and appropriate spray coverage of the grape bunches may also affect the efficacy of an application at a technical level.
The absence of high-level resistance to insecticides (i.e. compared to other lepidopteran species) in L. botrana populations from Turkey and Greece, despite the history of intensive insecticide application in both countries for many years might be partially attributed to the few generations of L. botrana (3 generations) per year (Siddiqui et al., Reference Siddiqui, Fan, Naz, Bamisile, Hafeez, Ghani, Wei, Xu and Chen2023). The ability of L. botrana to develop some generations on alternative host plants (more than 40 wild and cultivated plants i.e. Olea europea, Drimia maritima) (Ioriatti et al., Reference Ioriatti, Anfora, Tasin, De Cristofaro, Witzgall and Lucchi2011) that do not receive insecticide application in combination with potential fitness cost of insecticide resistance might also contribute to the maintenance of susceptible alleles into the population.
Additionally, our results revealed no known or putative novel mutations in any of the gene targets of pyrethroids and oxadiazines (VGSC), spinosad (nAChR_α6), diamides (RyR), avermectins (GluCl), and organophosphates (ace), in all populations tested. These indicated a low risk for the future selection of target site resistance in this region.
Despite the absence of resistance mutations, the bioassays indicated resistance against indoxacarb and deltamethrin for some populations from Turkey, possibly indicating alternative resistance mechanisms. This is in contrast to other lepidopteran species, such as Tuta absoluta, Plutella xylostella, and H. armigera, where target site mutations constitute the major resistance mechanism responsible for high resistance levels (reviewed by Guedes et al., Reference Guedes, Roditakis, Campos, Haddi, Bielza, Siqueira, Tsagkarakou, Vontas and Nauen2019; Banazeer et al., Reference Banazeer, Afzal, Hassan, Ijaz, Shad and Serrão2022).
P450s have been found to play major roles in the insecticide resistance of lepidopteran species (Katsavou et al., Reference Katsavou, Riga, Ioannidis, King, Zimmer and Vontas2022), more specifically, 56 P450s have been validated for their contribution to resistance in ten economically important lepidopteran pest species. Here, through transcriptome assembly we identified 161 L. botrana CYPs, enzymes that are involved in key physiological processes. It is known that CYPs that are involved in ecdysteroid metabolism, a key physiological process in the moulting insects (Feyereisen, Reference Feyereisen2012), belong to Clan 2 and M and include the CYP302A, CYP306A, CYP307A, CYP314A, CYP315A, and CYP18A/B subfamilies. It is worth noting that we could detect orthologs of all these CYPs (fig. 3). Importantly, the lepidoptera-specific duplication of CYP18 is present as full-length transcripts. Also, CYP306A1 and CYP307A2 were both detected. In Clan M, there are two CYP302A1 fragments that most probably are different parts of the same transcript. In the same clan, there are also two CYP314A1-like fragments, whereas no CYP315A1 homologue was found. However, given the critical role of CYP315A1 it is possible that the reason we could not detect it is due to a low level of transcription, rather than it being indeed absent from L. botrana.
Another key physiological process is the biosynthesis of cuticular hydrocarbons. CYPs from the CYP4G subfamily (Clan 4) play an important role in this process. H. armigera contains five CYP4G genes and L. botrana contains four (fig. 3), only one of which, however, appears to be full-length. It is not easy to determine whether any of the three remaining CYP fragments originate from the same transcript. As a result, it is not easy to estimate the total number of CYP4G genes in the grapevine moth.
Our phylogenetic analysis showed that there are some notable expansions (blooms) in certain CYP subfamilies in L. botrana, such as in CYP333B, CYP341B, CYP6B, CYP6AB, and CYP338A (fig. 3 – annotated with a ‘ + ’ inside a blue circle). More specifically, CYP333B3 (Clan M) is the only bloom in Clan M and it appears that the grapevine moth has at least three copies, compared to only one in H. armigera. This gene has also been extensively duplicated in another lepidopteran species, the tobacco hornworm Manduca sexta (Dermauw et al., Reference Dermauw, Van Leeuwen and Feyereisen2020). However, the function of the extra CYP333B copies has not been elucidated yet. CYP341B genes in Clan 4 are involved in the biosynthesis of sex pheromones and are frequently duplicated in Lepidoptera (Dermauw et al., Reference Dermauw, Van Leeuwen and Feyereisen2020). In the grapevine moth, there are as many as 23 L. botrana CYP341B genes that cluster with the five CYP341B genes of H. armigera. Two of these sequences are full-length genes and an additional eight are of intermediate length (between 250 and 450 amino acids, marked with a triangle in fig. 3), indicating that most probably there are more CYP341B copies in L. botrana than in H. armigera. Lepidopteran CYP341B genes are involved in the biosynthesis of sex pheromones (Dermauw et al., Reference Dermauw, Van Leeuwen and Feyereisen2020). As a result, an expansion CYP341B in L. botrana could possibly underlie behavioural differences between L. botrana and H. armigera.
The remaining three blooms are in Clan 3 subfamilies. The CYP6B clade appears to be greatly expanded in L. botrana with at least seven full-length genes and another 12 fragments, compared to only five genes in H. armigera. Additionally, the grapevine moth appears to have a great number of genes in the CYP6AB/6AN clade. More specifically, while there are only four 6AB and one 6AN genes in H. armigera, there are 27 CYP6AB (nine of which are full-length) and four CYP6AN genes in L. botrana. The L. botrana CYP6AB genes are grouped into three well-supported clades. All four L. botrana CYP6AN genes are sister to the CYP6AN1 of H. armigera, thus suggesting a possible duplication in the L. botrana lineage. Quite a number of CYP6B and CYP6AB genes have been associated with insecticide resistance (Katsavou et al., Reference Katsavou, Riga, Ioannidis, King, Zimmer and Vontas2022), and as a result the observed expansions could be responsible for insecticide resistance in L. botrana.
Finally, there is a striking contraction in the CYP340 family (fig. 3 – noted with a ‘−’ inside a red circle), whereby L. botrana appears to have only three genes, only one of which is nearly full-length. In sharp contrast, H. armigera has as many as 25 CYP340 genes grouped in seven different subfamilies (340Q, K, H, G, AD, AG, and J). This finding is in agreement with the previously reported recent expansion of the CYP340 family in H. armigera and H. zea (Pearce et al., Reference Pearce, Clarke, East, Elfekih, Gordon, Jermiin, McGaughran, Oakeshott, Papanicolaou, Perera, Rane, Richards, Tay, Walsh, Anderson, Anderson, Asgari, Board, Bretschneider, Campbell, Chertemps, Christeller, Coppin, Downes, Duan, Farnsworth, Good, Han, Han, Hatje, Horne, Huang, Hughes, Jacquin-Joly, James, Jhangiani, Kollmar, Kuwar, Li, Liu, Maibeche, Miller, Montagne, Perry, Qu, Song, Sutton, Vogel, Walenz, Xu, Zhang, Zou, Batterham, Edwards, Feyereisen, Gibbs, Heckel, McGrath, Robin, Scherer, Worley and Wu2017). However, since the L. botrana genes could not be classified into a specific CYP340 subfamily (fig. 3) their role is not clear.
The assembled transcriptome, the set of unigenes and the annotation of cytochrome P450s generated in this study are publicly available in the NCBI TSA database and the Supplement of this manuscript, and they will facilitate molecular studies on L. botrana.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0007485323000640.
Acknowledgements
The authors would like to thank Nikos Mpagkis (Ministry of Agriculture) for his valuable assistance in the collection of the grapevine moth populations. The authors would also like to thank anonymous reviewers for their extremely pertinent comments, which helped us substantially improve the manuscript. This research was financially supported in part by the Project ‘Graperoutes’ (Project Code:2018ΣΕ01300000, General Secretariat of Research and Technology, GSRT, Greece). The study was also financially supported by the Republic of Turkey, Ministry of Agriculture and Forestry, General Directorate of Agricultural Research and Policies with a Project no: 521. N.S.Ç., was supported by 100/2000 YÖK PhD Scholarship and TUBITAK (The Scientific and Technological Research Council of Turkey, Project number: 1649B031801960) 2211-A PhD Scholarship Programmes. E.K. was supported by the Hellenic Foundation for Research and Innovation (HFRI) under the HFRI PhD Fellowship grant (Fellowship Number: 1021). The project was also partially funded by the European Union- Next Generation EU, Greece 2.0 National Recovery and Resilience plan.
Competing interests
None.
