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Article

Identification and Characterization of Glutathione S-transferase Genes in Spodoptera frugiperda (Lepidoptera: Noctuidae) under Insecticides Stress

by
Ahmed A. A. Aioub
1,*,
Ahmed S. Hashem
2,
Ahmed H. El-Sappah
3,4,
Amged El-Harairy
5,6,
Amira A. A. Abdel-Hady
7,
Laila A. Al-Shuraym
8,*,
Samy Sayed
9,10,
Qiulan Huang
4 and
Sarah I. Z. Abdel-Wahab
1
1
Plant Protection Department, Faculty of Agriculture, Zagazig University, Zagazig 44511, Egypt
2
Stored Product Pests Research Department, Plant Protection Research Institute, Agricultural Research Center, Sakha, Kafr El-Sheikh 33717, Egypt
3
Department of Genetics, Faculty of Agriculture, Zagazig University, Zagazig 44511, Egypt
4
School of Agriculture, Forestry and Food Engineering, Yibin University, Yibin 644000, China
5
Unit of Entomology, Plant Protection Department, Desert Research Center, Mathaf El-Matariya St. 1, El-Matariya, Cairo 11753, Egypt
6
Department of Integrated Pest Management, Plant Protection Institute, Hungarian University of Agriculture and Life Sciences, Páter Károly utca 1, 2103 Gödöllő, Hungary
7
Economic Entomology Department, Faculty of Agriculture, Mansoura University, Mansoura 35516, Egypt
8
Department of Biology, College of Science, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
9
Department of Economic Entomology and Pesticides, Faculty of Agriculture, Cairo University, Giza 12613, Egypt
10
Department of Science and Technology, University College-Ranyah, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
*
Authors to whom correspondence should be addressed.
Toxics 2023, 11(6), 542; https://doi.org/10.3390/toxics11060542
Submission received: 23 May 2023 / Revised: 14 June 2023 / Accepted: 15 June 2023 / Published: 19 June 2023
(This article belongs to the Special Issue Detoxification Mechanisms in Insects)
Browse Figures
Versions Notes

Abstract

:
Insect glutathione S-transferases (GSTs) serve critical roles in insecticides and other forms of xenobiotic chemical detoxification. The fall armyworm, Spodoptera frugiperda (J. E. Smith), is a major agricultural pest in several countries, especially Egypt. This is the first study to identify and characterize GST genes in S. frugiperda under insecticidal stress. The present work evaluated the toxicity of emamectin benzoate (EBZ) and chlorantraniliprole (CHP) against the third-instar larvae of S. frugiperda using the leaf disk method. The LC50 values of EBZ and CHP were 0.029 and 1.250 mg/L after 24 h of exposure. Moreover, we identified 31 GST genes, including 28 cytosolic and 3 microsomal SfGSTs from a transcriptome analysis and the genome data of S. frugiperda. Depending on the phylogenetic analysis, sfGSTs were divided into six classes (delta, epsilon, omega, sigma, theta, and microsomal). Furthermore, we investigated the mRNA levels of 28 GST genes using qRT-PCR under EBZ and CHP stress in the third-instar larvae of S. frugiperda. Interestingly, SfGSTe10 and SfGSTe13 stood out with the highest expression after the EBZ and CHP treatments. Finally, a molecular docking model was constructed between EBZ and CHP using the most upregulated genes (SfGSTe10 and SfGSTe13) and the least upregulated genes (SfGSTs1 and SfGSTe2) of S. frugiperda larvae. The molecular docking study showed EBZ and CHP have a high binding affinity with SfGSTe10, with docking energy values of −24.41 and −26.72 kcal/mol, respectively, and sfGSTe13, with docking energy values of −26.85 and −26.78 kcal/mol, respectively. Our findings are important for understanding the role of GSTs in S. frugiperda regarding detoxification processes for EBZ and CHP.

1. Introduction

The activity of detoxifying enzymes is necessary for an insect to survive toxic surroundings such as insecticides [1]. The process of cellular detoxification in insects can be separated into three phases: phase I, phase II (involving metabolizing enzymes), and phase III (involving transporters) [2]. Cytochrome P450 monooxygenase, glutathione S-transferase (GST), and carboxylesterase (CarE) are the primary enzymes involved in phase I and phase II detoxification processes [3], whereas phase III is dominated by ATP-binding cassette (ABC) transporters [4,5,6,7].
In insects, one of the most important detoxification enzymes in phase II is the GST family of multifunctional enzymes. GSTs are known to catalyze the nucleophilic attack of the sulfhydryl group of reduced glutathione (GSH) on electrophilic centers of xenobiotic compounds, including insecticides [8,9]. GSTs are categorized into four major protein types based on cellular locations, including cytosol, microsomes, mitochondria, and bacterial Fosfomycin-resistant proteins [8,10,11,12]. Only the first two groups have been found in insects thus far [13]. More genes are present in cytosolic GSTs than in microsomal GSTs [14]. GSTs in cytosols can either function as homodimers or heterodimers and typically include 200–250 amino acids. The six primary classes of insect cytosolic GSTs are delta, epsilon, omega, sigma, theta, zeta, and unclassified genes [15]. Microsomal GSTs are membrane-bound proteins that function as trimmers, and they typically have 150 amino acid residues [16]. Microsomal GSTs are membrane-associated proteins in eicosanoid and glutathione metabolism (MAPEG family), which are crucial for reducing lipid peroxidation and xenobiotic detoxification [17]. Reports correlating high levels of GST with high resistance to insecticides do exist for many insects [13,18]. GSTs confer insecticide resistance directly through metabolism or sequestration or indirectly by protecting against oxidative stress induced by synthetic insecticides [19]. For example, upregulated GSTu1 in several CHP-resistant Plutella xylostella strains contributed to CHP resistance [20]. Several GSTs have been implicated in resistance to organophosphates (OPs) in Musca domestica [21]. A biochemical study of Anopheles gambiae indicated that DDT resistance is associated with both quantitative and qualitative changes in multiple GST enzymes [22].
Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), a natural species of tropical and subtropical origin in the Western Hemisphere, is a damaging pest in maize. Its wide host range includes corn, wheat, cotton, soybean, cabbage, and potatoes [23,24,25]. The early 21st century saw the introduction of this insect, which is indigenous to the Western Hemisphere, Africa, Asia, and Oceania [26]. The high reproduction rate, extensive migration, great dispersal ability, and vigorous flight (up to 500 km before oviposition) of S. frugiperda are factors contributing to its economic significance [27]. Since the fall armyworm was introduced to the Eastern Hemisphere and quickly spread from western Africa to southeastern Asia, these traits have become a global concern [23]. The first significant S. frugiperda infestations in Africa were discovered in southwestern Nigeria in 2016 [28]. In 2018, the Food and Agriculture Organization in Egypt declared it a global pest that requires quarantine. The first occurrence was in maize fields in the Upper Egypt Governorates in 2019 [29]. S. frugiperda can swiftly damage a maize crop because of its intense feeding, and if it is not promptly controlled, it may also destroy other crops. Following an S. frugiperda invasion, Brazil’s corn yield decreased by 34%, and the annual loss brought on by S. frugiperda is USD 400 million [30]. S. frugiperda control relies intensively on chemical insecticides, prompting resistance to many classes of insecticides [31,32]. Currently, S. frugiperda is among the top 15 most resistant insect pest species worldwide [33]. The resistance mechanism of insects toward insecticides comprises two main aspects, including detoxification enzyme activity upregulation and target-induced decreased sensitivity [34]. In S. frugiperda, enhanced glutathione transferase activity is associated with the degradation of Fluxametamide [35]. Another study showed that the overexpression of GSTs was involved in S. frugiperda developing resistance to pyrethroids, organophosphorus, and carbamate pesticides [34]. Consequently, S. frugiperda is considered one of the most dangerous insects and can cause heavy losses in the economic crops of Egypt.
Given the seriousness of S. frugiperda and the speed of its spread, it is necessary to intervene quickly with chemical pesticides. CHP and EBZ, which target ryanodine receptors and glutamate-gated chloride channel receptors, respectively, were found to be effective against S. frugiperda. In 2022–2023, the Egyptian Ministry of Agriculture suggested that CHP and EBZ be used to control S. frugiperda. Here, we hypothesize that GSTs play a role in S. frugiperda larva detoxification, suggesting a potential focus for further investigation into integrated pest management techniques. Thus, we aimed to evaluate the LC50 values of CHP and EBZ against 3rd instar S. frugiperda larvae. Moreover, we identified and characterized 31 GST genes (SfGSTs) in S. frugiperda using previously released transcriptome datasets [36] and genome data (InsectBase http://www.insect-genome.com (accessed on 30 April 2023). Furthermore, we determined the expressions of 28 out of 31 GST genes in S. frugiperda under insecticide stress using qRT-PCR. Finally, molecular docking was performed to clarify putative interactions between the proteins and tested insecticides.

2. Materials and Methods

2.1. S. frugiperda Rearing

S. frugiperda were collected from infested maize fields in the Assuit Governorate, Upper Egypt (27.2134° N, 31.4456° E) and then reared at the Plant Protection Research Institute, Agricultural Research Centre, Giza, Egypt, at 25 ± 3 °C and 70 ± 10% relative humidity and a photoperiod of 16:8 (L:D) h, without being exposed to insecticides. The larvae were put in 20 mL plastic cups and fed fresh corn leaves. The grown-up pupae were collected and kept in a plastic container inside a 30 cm × 30 cm × 30 cm rearing cage. Water was added to fresh plant leaves before they were placed in an egg-laying chamber. The larvae were moved for study once they reached the third larval age.

2.2. Bioassay of Tested Insecticides against Third-Instar S. frugiperda Larvae

Technical-grade EBZ (99.4%; catalog number: P-996S) and CHP (95%; catalog number: P-952S) were obtained from Sigma-Aldrich, China. The effectiveness of EBZ and CHP against S. frugiperda third larval instars in varied doses was assessed using the leaf disk method [37]. Briefly, active-ingredient insecticides were first dissolved in acetone. Fresh maize leaves were chopped into leaf discs that measured 0.5 cm × 0.5 cm and submerged in different concentrations of EBZ (0.005, 0.01, 0.02, 0.04, 0.08 mg/L) and CHP (0.25, 0.50, 1, 2, and 4 mg/L) for 10 s. Leaves coated with an equal amount of acetone were provided as a control. Then, the leaf strips were placed in a tray and allowed to air dry. A 24-well plate was filled with dried corn leaves. The third-instar larvae were transplanted to a 24-well plate after fasting for 12 h. A total of 30 larvae were used for each concentration. Each treatment had 3 replicates under carefully controlled settings (25 ± 3 °C) for 24 h. After 24 h, mortality was recorded. Dead larvae were those that did not move when touched by a brush. Mortality was calculated, and the LC50 value of each insecticide was calculated, as well as a 95% confidence interval.

2.3. Quantitative Real-Time (PCR qRT-PCR) Analysis

Following a 24-h feeding period on corn leaves with control and insecticide-treated larvae, the LC50 values were recorded for the live larvae and control, and they were collected for RNA extraction. Fifteen treated and control S. frugiperda larvae with three replicates were used to measure gene expression. Total RNA was isolated using RNAiso Plus reagent (Takara, Dalian, China) and treated with RNase-free DNase I (Takara, Dalian, China) to remove potential contaminants from genomic DNA. The quality and concentration of RNA were determined via agarose gel electrophoresis and a NanoDrop 2000 spectrophotometer (Thermo Scientific, Wilmington, CA, USA). First-strand cDNA was reverse-transcribed using the TransScript First-Strand cDNA Synthesis SuperMix (Transgen, Beijing, China). qRT-PCR primers were designed with Primer 3 Plus for 28 GST genes per previously published transcriptome datasets [36], and Table S1 contains a list of all the primer sequences utilized in this investigation. The internal reference genes chosen for this study were elongation factor 1-alpha (EF1) and ribosomal protein S18 (RPS18) [38], and the qRT-PCR was performed using an SYBR Green qPCR Master Mix kit (Catalog number: 4309155, Takara, Japan) with a 240 Light Cycler 480 II system (Roche Diagnostics, Mannheim, Germany) under the following parameters: 95 °C for 30 s, 40 cycles at 95 °C for 5 s, and 60 °C for 20 s. The 2−ΔΔCt technique was used to calculate the relative quantification of gene expression (Livak and Schmittgen 2001).

2.4. Bioinformatics Analyses

cDNA sequences for GSTs were obtained from S. frugiperda transcriptome databases that were previously made available [36], as well as from a genome (InsectBase http://www.insect-genome.com (accessed on 30 April 2023). GST sequences from typical insect species were downloaded, including Drosophila melanogaster, Spodoptera litura, Pieris rapae, Nilaparvata lugens, Sogatella furcifera, Leptinotarsa decemlineata, Bombyx mori, and Tribolium castaneum from the National Centre for Biotechnology Information (NCBI) (https://www.ncbi.nlm.nih.gov/ (accessed on 30 April 2023) as queries using the TBLASTN algorithm in the Basic Local Alignment Search Tool (BLAST) program (http://blast.ncbi.nlm.nih.gov/blast.cgi (accessed on 30 April 2023) with a cut-off E-value of 1 × 10−5 [39]. After manually deleting duplicated sequences, we combined the GST genes found in the two datasets. The neighbor-joining approach with the pair-wise deletion option was used with the MEGA6.0 software to generate a phylogenetic tree [40].

2.5. In Silico Molecular Docking Assay

All modeled protein structures (SfGSTe10, SfGSTe13, SfGSTs1, and SfGSTe2) were downloaded from the National Center for Biotechnology Information (NCBI) server to construct 3D models. To create a more acceptable structural template for trustworthy theoretical 3D models, Swiss-model tools supplied the sequences of all proteins. Ramachandran’s plot (PROCHECK analysis) was then used to analyze and validate these models. Structure models of all proteins and their active sites (pockets) were downloaded in PDB format and imported into the Molecular Operating Environment (MOE) 2014.13 software (Chemical Computing Group Inc., Montreal, QC, Canada) [41]. The heteroatoms and crystallographic water molecules were eliminated from the protein after the protein’s missing hydrogen chemistry was restored [42].
Ligand selection, CHP, and EBZ were created using the Chem Draw Professional 15 Builder module. Before starting the docking process, the ligands were reduced using the CHARM m 99 force field. Three-dimensional (3D) structures were then constructed, duplicates were removed, and bonds were added. The ligands were made flexible and manually placed inside the catalytic site cavity of the enzyme model after all the default parameters were established and the minimal energy structures were obtained. A full-force field was used to investigate the binding energy, and scoring functions that generated free-binding interaction energies based on molecular force field terms were used to assess the ligand and protein’s affinity. At the conclusion of the docking, the best ligand interaction was investigated and evaluated using scoring functions and root-mean-square deviation (RMSD) computations [43].

2.6. Statistical Analysis

Probit analyses were used to determine LC50 values and 95% confidence intervals with the aid of the SPSS software (version 19.0, SPSS Inc., Chicago, IL, USA, 2003). The expression patterns based on qRT-PCR were examined using the 2−∆∆Ct technique. The significance of differences between patterns was assessed using a one-way ANOVA with PASW Statistics and Duncan’s multiple range test. The outcomes were displayed using the relative mRNA expressions’ mean and standard deviations.

3. Results

3.1. Insecticidal Activity of Tested Insecticides against the Third Larval Instars of S. frugiperda

Table 1 shows the bioassay results of the leaf disk method for the two studied insecticides (CHP and EBZ) against third-instar S. frugiperda after one day of treatment. The LC50 values were 0.029 mg/L for EBZ and 1.250 mg/L for CHP after 24 h of treatment for the third-instar S. frugiperda.

3.2. Identification and Classification of S. frugiperda GSTs

A total of 31 SfGST genes were discovered in the S. frugiperda genome and transcriptome, involving 27 cytosolic and 3 microsomal SfGSTs, designated SfGSTd1–SfGSTt1 (Table 2). Based on phylogenetic analyses and protein sequence comparisons with other insect GSTs, such as Spodoptera litura, Pieris rapae, Nilaparvata lugens, Sogatella furcifera, Leptinotarsa decemlineata, Acyrthosiphon pisum, Anopheles gambiae, and Bombyx mori, 28 cytosolic CsGSTs were further classified into 5 classes depending on NCBI blast and phylogenetic analysis, including 2 deltas (SfGSTd1 and SfGSTd2); 17 epsilons (SfGSTe1 to SfGSTe17); 2 omegas (SfGSTo1 and SfGSTo2); 5 sigmas (SfGSTs1 to SfGSTs6); 1 theta (SfGSTt1); and 3 microsomal genes (SfGSTm1, SfGSTm2, and SfGSTm3) (Table 3). A phylogenetic examination of GSTs from other insect orders revealed that SfGSTs have a high degree of similarity with the GSTs of S. litura and B. mori, and the homologous genes of various insects are grouped together in the same clade (Figure 1). According to a sequencing study of the SfGSTs genes, the 31 SfGSTs had full open reading frames (ORF) that encoded 63-282 amino acids with protein molecular masses ranging from 7.05 to 94.38 kDa.

3.3. Expression Profiling of sfGSTs in S. frugiperda Larvae Exposed to Tested Insecticides

SfGST transcript levels were measured in larvae exposed to LC50 concentrations of these insecticides to evaluate whether SfGST expression responds to CHP and EBZ (Figure 2). The expression of the 28 SfGSTs showed that 11 SfGSTs (SfGSTe2, SfGSTe7, SfGSTe8, SfGSTe9, SfGSTe10, SfGSTe13, SfGSTe15, SfGSTs1, SfGSTs4, SfGSTs6, and SfGSTm2) were significantly upregulated under LC50 of CHP and EBZ compared with the control. Conversely, five genes (SfGSTe3, SfGSTe6, SfGSTe11, SfGSTe14, and SfGSTo2) were significantly downregulated after exposure to LC50 of CHP and EBZ. The mRNA levels of sfGSTo1 and sfGSTm3 decreased with EBZ by 0.81 and 3.83 fold but increased with CHP by 3.81 and 4.46 fold compared with the control. Meanwhile, the mRNA level of sfGSTe16 increased by 4.18 fold with EBZ and decreased by 2.32 fold with CHP. Remarkably, sfGSTe10 and sfGSTe13 showed the highest relative expression with 13.21- and 16.27-fold increases for CHP and 12.89- and 17.66-fold increases for EBZ, respectively.

3.4. Molecular Docking Analysis

Based on relative expression experiments, a molecular docking analysis using SfGSTe10 and SfGSTe13 as the most upregulated genes and SfGSTs1 and SfGSTe2 as the least upregulated genes of S. frugiperda larvae was built using homology modeling. The docking analysis showed that EBZ had a higher binding affinity for SfGSTe13 (−26.85 kcal/mol), followed by SfGSTe10 (−24.41 kcal/mol), SfGSTs1 (−23.16 kcal/mol), and SfGSTe2 (−19.01 kcal/mol), whilst CHP had a higher binding affinity with SfGSTe13 (−26.78 kcal/mol), followed by SfGSTe10 (−26.72 kcal/mol), SfGSTe2 (−19.52 kcal/mol), and SfGSTs1 (−18.45 kcal/mol) (Table 4).
As a ligand, EBZ penetrates deep into the hydrophobic pocket in SfGSTe10 (4.47 Å) through two bonds (H-bonds), with Arg 111 and an H-pi bond with Tyr 116, surrounded by residual Lys 120, Tyr 115, Glu 115, Arg 41, His 40, Leu 25, Ser 11, and His 52. EBZ links to the active site of SfGSTe13 via an H-pi bond with Val 15, surrounded by more residues of Ser 140, Ser 49, Met 99, Val 90, Phe 10, Met 1, Pro 97, Val 90, Lau 100, Thr 99, and Lau 17. EBZ connects to the active sites of SfGSTs1 (1.49 Å) via H– bonds with Asn 9 and two bonds with Asp 34, as well as van der Waals interactions with a large number of amino acids: Asn 45, His22, Arg 22, Ala 197, Arg 198, and Asp 22. In SfGSTe2, EBZ is linked by two bonds with Lys 112 and via van der Waals interactions with the following amino acids: Leu 36, Tyr 120, His 53, His 41, Arg 127, Thr 113, Pro 112, Val 116, and Ala 158 (Figure 3).
An amino acid (Arg 111) binds to CHP through three bonds (two H-pi bonds and one H- bond as a hydrophobic interaction) in the SfGSTe10 receptor with a distance of 2.94 Å and is in a pocket formed by residual Phe 107, Phe 10, Pro 12, Thr 114, Ser 11, Lle 61, Ser 53, His 52, Arg 41, Glu 119, and His 40. CHP connects to the active sites of SfGSTe13 via H– bonds with Val 13 (2.36 Å) and van der Waals interactions with many amino acids, including Glu 40, Met 39, Val 38, and Glu 11. Meanwhile, CHP connects to the active sites of SfGSTs1 via an H-pi bond with Lys 108 (4.61 Å) and eight amino acids (Arg 35, Tyr 97, Lle 13, Phe 52, Gin 51, Gly 104, Ser 101, and Ala 105) in the active site through van der Waals interactions. Likewise, in SfGSTe2, this insecticide connects via an H-pi bond with His 53 (4.42 Å) and is surrounded by residual Thr 54, Lys 112, His 41, Tyr 120, Leu 35, and Phe 42 (Figure 4).

4. Discussion

Spodoptera frugiperda is an insect that causes huge agricultural losses all over the world [50]. It has remarkable long-distance flight ability, a high dispersal ability, and a high potential for intensive migratory behavior. Consequently, it is necessary to intervene with chemical controls to limit the spread of this insect. In this study, EBZ and CHP were proved to be toxic to S. frugiperda larvae with LC50 values of 0.029 and 1.250 mg/L at 24 h. EBZ is a significant Avermectin family macrocyclic lactone pesticide with outstanding effectiveness against lepidopteran pests [51]. EBZ causes DNA damage and apoptosis in S. frugiperda’s sf-9 cell line [52]. Furthermore, EBZ produces a hyperpolarized cell by attaching to glutamate-gated chloride channels and causing an inflow of chloride ions [53]. CHP is highly effective against lepidopteran insects and was the first ryanodine receptor insecticide to be developed from a novel chemical class [54]. This outcome was in line with Zhao, et al. [55], who showed that the LC50 values of CHP against S. frugiperda ranged from 0.849 mg/L in Xuzhou to 3.446 mg/L in Dongtai. The LC50 values of EBZ against S. frugiperda ranged from 0.019 mg/L in Yichang to 0.041 mg/L in Dehong. Moreover, the LC50 value of CHP was 0.068 µg/mL against third-instar S. frugiperda larvae [56]. Interestingly, EBZ achieved toxicity with an LC50 value of 0.383 against the third-instar larvae of S. frugiperda [57]. Furthermore, the LD50 values of CHP and EBZ were 0.410 and 0.355 µg/g against S. frugiperda larvae [58].
GSTs are involved in detoxifying endogenous and external chemical compounds and are linked to the development of pesticide resistance [59]. Based on genomic data, GSTs have been identified from a range of insects; however, the number and classification of GST genes vary between insect species. For example, 17 GSTs genes were discovered in Pieris rapae [45], 22 GSTs were discovered in Plutella xylostella [14], 32 GSTs were discovered in Acyrthosiphon pisum [47], 35 GSTs were discovered in Anopheles gambiae [48], and 25 GSTs were discovered in Cnaphalocrocis medinalis [60]. In the present study, 31 sfGST genes were identified in the S. frugiperda genome and transcriptome, which had similar number and classification distributions to those of 37 lepidopteran GSTs in Spodoptera litura [44] and 24 GSTs in Bombyx mori [49]. Therefore, GST levels differ widely between insect species.
We used phylogenic tree analysis to determine GST classifications. As a result, 31 sfGSTs were discovered and classified as delta, epsilon, omega, sigma, theta, and microsomal. The two largest categories identified in this insect are sigma and epsilon. GSTs from these two classes frequently play detoxifying roles and have been linked to insecticide resistance [18]. For example, SfGSTe7 was discovered in the same lineage as SlGSTe2, an enzyme implicated in carbaryl, DDT, and deltamethrin detoxification [44]. Likewise, In the epsilon clade, SfGSTe8 was found to be closely related to SlGSTe3, and it was marginally upregulated in S. litura by carbaryl and DDT [61]. Moreover, SfGSTs1 and SfGSTs4 appeared in the same clade as BmGSTs2, and the expression of the BmGSTs2 gene increased in the midgut after exposure to the herbicide glyphosate and the insecticide permethrin, reaching a peak at 6 to 12 h in B. mori [62].
Our finding suggests that 11 out of 28 genes showed the highest relative expression in S. frugiperda against CHP and EBZ. This could be because GSTs share a set of detoxifying enzyme systems for different kinds of pesticides [2,59]. This result is in agreement with Hu, et al. [63], who showed that GSTe6 was upregulated against CHP in Spodoptera exigua. Moreover, abamectin and CHP significantly upregulated PrGSTs1 in P. rapae [45]. Furthermore, 9 GSTs out of 16 identified were upregulated after different periods and doses of malathion exposure, while 3 GSTs were upregulated by β-cypermethrin exposure in Bactrocera dorsalis [64]. In addition, the mRNA levels of GSTe1, 3, 10, and 15 increased in S. litura under chlorpyrifos compared with the control [44]. Additionally, EBZ significantly upregulated GmGSTs1 in Grapholita molesta [65].
In contrast, our data showed that the transcript levels of five genes (SfGSTe3, SfGSTe6, SfGSTe11, SfGSTe14, and SfGSTo2) were significantly downregulated under CHP and EBZ stress. An adaptive mechanism in insects that lowers the overall activity of GST enzymes to avoid excessive GST activity from a depleted supply of GSH may involve downregulating a subset of GSTs [1]. The expression levels of PxGSTd1, PxGSTd2, and PxGSTd4 were significantly decreased in P. xylostella under acephate stress [66]. Moreover, SfGSTo1 and SfGSTt1 were slightly downregulated in Sogatella furcifera under chlorpyrifos stress [46].
Molecular docking was applied to predict the binding sites for proteins. Structural modeling aids in understanding the binding mechanisms between any protein and any ligand [67]. Protein–ligand docking was carried out using the MOE and an induced fit technique with a fixed receptor and a flexible ligand [68]. A protein–ligand complex’s binding interaction can be identified using the docking process, as well as binding geometry and other interactions [69]. Small compounds have frequently been docked to target enzymes using this technique [70]. Our findings showed that four receptors (SfGSTe10, SfGSTe13, SfGSTs1, and SfGSTe2) were targets of CHP and EBZ. Our data showed the binding affinity between CHP and EBZ to be high with SfGSTe10 and SfGSTe13 and low with SfGSTs1 and SfGSTe2, indicating the potential of SfGSTe10 and SfGSTe13 to metabolize CHP and EBZ more than SfGSTs1 and SfGSTe2. This is evident in the compatibility of the gene expression data with molecular docking analysis (the lowest binding energy with ligands), which showed that the binding affinity between CHP and EBZ is high with SfGSTe10 and SfGSTe13, and low with SfGSTs1 and SfGSTe2. This result may be because the amino acids in the receptor are linked by double or triple bonds, and the docking binding affinity is high with lower binding energy [71,72]. Additionally, the type and position of amino acids in the active site of GSTs (the G-site and H-site) play important roles in insecticide binding affinity and catalytic functions [73]. The enzyme catalyzes the nucleophilic attack by the glutathione and its conjugation with the substrate, making the substrate less reactive and more soluble, and, therefore, it is easier for it to excrete GSTs, detoxifying insecticides by catalyzing nucleophilic attacks from the thiol group in reduced glutathione (GSH) in a wide range of electrophilic substrates [8,19]. In addition, GSTs may participate in the passive non-catalytic binding of substrates and sequestration, which prevents insecticides from binding to their target proteins [20]. Consequently, evidence was provided that SfGSTe10, SfGSTe13, SfGSTs1, and SfGSTe2 catalyzed to conjugate with CHP and EBZ and identified the possible site of binding amino acids with insecticides. A study showed that the activity of recombinant TcGSTm02 in Tetranychus cinnabarinus could be inhibited by cyflumetofen, and the enzyme catalyzed the conjugation of GSH into cyflumetofen [74]. In another study, the mechanism of detoxification by GSTD2 in D. melanogaster was revealed by its strong affinity toward isothiocyanate and catalyzing the conjugation between GSH and isothiocyanate [75]. Likewise, Bombyx mori, the antenna-specific BmGSTD4, had high GSH-conjugating activity toward 1-chloro-2 and 4-dinitrobenzene (CDNB), indicating its potential role in the metabolism of xenobiotics [76]. Moreover, higher binding affinities between pesticides and enzymes were observed with lower binding energies [77,78]. Finally, the molecular docking is considered complementary to the aforementioned results at the applied level, not just the research level, because this part shows the effect of insecticides and their contents on insect proteins and enzymes, which are necessary to know the extent of the insect’s ability to show the resistance to these pesticides in the long term [79]. On the environmental level, knowing which of the chemical bonds within the insecticides is more closely related to the amino acids within the target protein of the target insect helps us design more targeted pesticides for specific organisms without any side effects on other organisms in the surroundings, or in other words, designing more specialized chemical pesticides at the genetic level for target organisms.

5. Conclusions

In this study, bioassay results showed that EBZ and CHP have a toxic effect on the third-instar larvae of S. frugiperda. In addition, 31 SfGST genes were identified from S. frugiperda by analyzing previously published transcriptome data, and the phylogenetic relationships of SfGSTs were investigated. SfGST genes showed different expression profiles following exposure to CHP and EBZ. The obtained data showed that SfGST genes are related to EBZ and CHP detoxification in S. frugiperda. Molecular docking revealed that EBZ and CHP have a high binding affinity with SfGSTe13 compared with other genes. Our findings focused on the roles of GSTs in EBZ and CHP detoxification in S. frugiperda.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/toxics11060542/s1: Table S1: primer sequences of qRT-PCR.

Author Contributions

Conceptualization, A.A.A.A. and S.I.Z.A.-W.; methodology, A.A.A.A., A.H.E.-S. and S.I.Z.A.-W.; software, A.A.A.A.; validation, A.A.A.A. and A.S.H.; formal analysis, A.H.E.-S. and A.E.-H.; investigation, A.H.E.-S. and A.A.A.A.-H.; resources, A.S.H.; data curation, S.I.Z.A.-W. and Q.H.; writing—original draft preparation, A.A.A.A.; writing—review and editing, A.A.A.A.; visualization, S.I.Z.A.-W.; supervision, A.A.A.A.; project administration, L.A.A.-S.; funding acquisition, S.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Princess Nourah bint Abdulrahman University Researchers Support Project Number (PNURSP2023R365), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data and materials are included in the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Han, J.-B.; Li, G.-Q.; Wan, P.-J.; Zhu, T.-T.; Meng, Q.-W. Identification of glutathione S-transferase genes in Leptinotarsa decemlineata and their expression patterns under stress of three insecticides. Pestic. Biochem. Physiol. 2016, 133, 26–34. [Google Scholar] [CrossRef] [PubMed]
  2. Qie, X.; Lu, W.; Aioub, A.A.; Li, Y.; Wu, W.; Hu, Z. Insight into the detoxification of haedoxan A and the synergistic effects of phrymarolin I against Mythimna separata. Ind. Crops Prod. 2020, 158, 112967. [Google Scholar] [CrossRef]
  3. Xiao, L.-F.; Zhang, W.; Jing, T.-X.; Zhang, M.-Y.; Miao, Z.-Q.; Wei, D.-D.; Yuan, G.-R.; Wang, J.-J. Genome-wide identification, phylogenetic analysis, and expression profiles of ATP-binding cassette transporter genes in the oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae). Comp. Biochem. Physiol. Part D Genom. Proteom. 2018, 25, 1–8. [Google Scholar] [CrossRef] [PubMed]
  4. Zhou, C.; Yang, H.; Wang, Z.; Long, G.-Y.; Jin, D.-C. Protective and detoxifying enzyme activity and ABCG subfamily gene expression in Sogatella furcifera under insecticide stress. Front. Physiol. 2019, 9, 1890. [Google Scholar] [CrossRef] [Green Version]
  5. Wu, C.; Chakrabarty, S.; Jin, M.; Liu, K.; Xiao, Y. Insect ATP-binding cassette (ABC) transporters: Roles in xenobiotic detoxification and Bt insecticidal activity. Int. J. Mol. Sci. 2019, 20, 2829. [Google Scholar] [CrossRef] [Green Version]
  6. Jin, M.; Cheng, Y.; Guo, X.; Li, M.; Chakrabarty, S.; Liu, K.; Wu, K.; Xiao, Y. Down-regulation of lysosomal protein ABCB6 increases gossypol susceptibility in Helicoverpa armigera. Insect Biochem. Mol. Biol. 2020, 122, 103387. [Google Scholar] [CrossRef]
  7. Jin, M.; Liao, C.; Chakrabarty, S.; Zheng, W.; Wu, K.; Xiao, Y. Transcriptional response of ATP-binding cassette (ABC) transporters to insecticides in the cotton bollworm, Helicoverpa armigera. Pestic. Biochem. Physiol. 2019, 154, 46–59. [Google Scholar] [CrossRef]
  8. Hayes, J.D.; Flanagan, J.U.; Jowsey, I.R. Glutathione transferases. Annu. Rev. Pharmacol. Toxicol. 2005, 45, 51–88. [Google Scholar] [CrossRef]
  9. Berenbaum, M.R.; Johnson, R.M. Xenobiotic detoxification pathways in honey bees. Curr. Opin. Insect Sci. 2015, 10, 51–58. [Google Scholar] [CrossRef] [Green Version]
  10. Liu, Y.; Moural, T.; Koirala BK, S.; Hernandez, J.; Shen, Z.; Alyokhin, A.; Zhu, F. Structural and functional characterization of one unclassified glutathione S-transferase in xenobiotic adaptation of Leptinotarsa decemlineata. Int. J. Mol. Sci. 2021, 22, 11921. [Google Scholar] [CrossRef]
  11. Allocati, N.; Federici, L.; Masulli, M.; Di Ilio, C. Glutathione transferases in bacteria. FEBS J. 2009, 276, 58–75. [Google Scholar] [CrossRef]
  12. Enayati, A.A.; Ranson, H.; Hemingway, J. Insect glutathione transferases and insecticide resistance. Insect Mol. Biol. 2005, 14, 3–8. [Google Scholar] [CrossRef] [Green Version]
  13. Koirala BK, S.; Moural, T.; Zhu, F. Functional and structural diversity of insect Glutathione S-transferases in xenobiotic adaptation. Int. J. Biol. Sci. 2022, 18, 5713–5723. [Google Scholar] [CrossRef]
  14. You, Y.; Xie, M.; Ren, N.; Cheng, X.; Li, J.; Ma, X.; Zou, M.; Vasseur, L.; Gurr, G.M.; You, M. Characterization and expression profiling of glutathione S-transferases in the diamondback moth, Plutella xylostella (L.). Bmc Genom. 2015, 16, 1–13. [Google Scholar] [CrossRef] [Green Version]
  15. Low, W.Y.; Ng, H.L.; Morton, C.J.; Parker, M.W.; Batterham, P.; Robin, C. Molecular evolution of glutathione S-transferases in the genus Drosophila. Genetics 2007, 177, 1363–1375. [Google Scholar] [CrossRef] [Green Version]
  16. Shi, H.; Pei, L.; Gu, S.; Zhu, S.; Wang, Y.; Zhang, Y.; Li, B. Glutathione S-transferase (GST) genes in the red flour beetle, Tribolium castaneum, and comparative analysis with five additional insects. Genomics 2012, 100, 327–335. [Google Scholar] [CrossRef] [Green Version]
  17. Kim, J.-H.; Raisuddin, S.; Rhee, J.-S.; Lee, Y.-M.; Han, K.-N.; Lee, J.-S. Molecular cloning, phylogenetic analysis and expression of a MAPEG superfamily gene from the pufferfish Takifugu obscurus. Comp. Biochem. Physiol. Part C Toxicol. Pharmacol. 2009, 149, 358–362. [Google Scholar] [CrossRef]
  18. Kostaropoulos, I.; Papadopoulos, A.I.; Metaxakis, A.; Boukouvala, E.; Papadopoulou-Mourkidou, E. Glutathione S–transferase in the defence against pyrethroids in insects. Insect Biochem. Mol. Biol. 2001, 31, 313–319. [Google Scholar] [CrossRef]
  19. Pavlidi, N.; Vontas, J.; Van Leeuwen, T. The role of glutathione S-transferases (GSTs) in insecticide resistance in crop pests and disease vectors. Curr. Opin. Insect Sci. 2018, 27, 97–102. [Google Scholar] [CrossRef]
  20. Zhu, B.; Li, L.; Wei, R.; Liang, P.; Gao, X. Regulation of GSTu1-mediated insecticide resistance in Plutella xylostella by miRNA and lncRNA. PLoS Genet. 2021, 17, e1009888. [Google Scholar] [CrossRef]
  21. Wei, S.; Clark, A.; Syvanen, M. Identification and cloning of a key insecticide-metabolizing glutathione S-transferase (MdGST-6A) from a hyper insecticide-resistant strain of the housefly Musca domestica. Insect Biochem. Mol. Biol. 2001, 31, 1145–1153. [Google Scholar] [CrossRef] [PubMed]
  22. Prapanthadara, L.-a.; Hemingway, J.; Ketterman, A.J. DDT-resistance in Anopheles gambiae (Diptera: Culicidae) from Zanzibar, Tanzania, based on increased DDT-dehydrochlorinase activity of glutathione S-transferases. Bull. Entomol. Res. 1995, 85, 267–274. [Google Scholar] [CrossRef]
  23. Nagoshi, R.N.; Htain, N.N.; Boughton, D.; Zhang, L.; Xiao, Y.; Nagoshi, B.Y.; Mota-Sanchez, D. Southeastern Asia fall armyworms are closely related to populations in Africa and India, consistent with common origin and recent migration. Sci. Rep. 2020, 10, 1421. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Jin, M.; Yang, Y.; Shan, Y.; Chakrabarty, S.; Cheng, Y.; Soberón, M.; Bravo, A.; Liu, K.; Wu, K.; Xiao, Y. Two ABC transporters are differentially involved in the toxicity of two Bacillus thuringiensis Cry1 toxins to the invasive crop-pest Spodoptera frugiperda (JE Smith). Pest Manag. Sci. 2021, 77, 1492–1501. [Google Scholar] [CrossRef] [PubMed]
  25. Zhang, L.; Liu, B.; Zheng, W.; Liu, C.; Zhang, D.; Zhao, S.; Li, Z.; Xu, P.; Wilson, K.; Withers, A. Genetic structure and insecticide resistance characteristics of fall armyworm populations invading China. Mol. Ecol. Resour. 2020, 20, 1682–1696. [Google Scholar] [CrossRef]
  26. Jamil, S.Z.; Saranum, M.M.; Saleh Hudin, L.J.; Anuar Wan Ali, W.K. First incidence of the invasive fall armyworm, Spodoptera frugiperda (JE Smith, 1797) attacking maize in Malaysia. BioInvasions Rec. 2021, 10, 81–90. [Google Scholar]
  27. Padhee, A.; Prasanna, B. The emerging threat of Fall Armyworm in India. Indian Farming 2019, 69, 51–54. [Google Scholar]
  28. Goergen, G.; Kumar, P.L.; Sankung, S.B.; Togola, A.; Tamò, M. First report of outbreaks of the fall armyworm Spodoptera frugiperda (JE Smith) (Lepidoptera, Noctuidae), a new alien invasive pest in West and Central Africa. PLoS ONE 2016, 11, e0165632. [Google Scholar] [CrossRef] [Green Version]
  29. Dahi, H.F.; Salem, S.A.; Gamil, W.E.; Mohamed, H.O. Heat requirements for the fall armyworm Spodoptera frugiperda (JE Smith) (Lepidoptera: Noctuidae) as a new invasive pest in Egypt. Egypt. Acad. J. Biol. Sci. A Entomol. 2020, 13, 73–85. [Google Scholar]
  30. Lima, M.; Silva, P.; Oliveira, O.; Silva, K.; Freitas, F. Corn yield response to weed and fall armyworm controls. Planta Daninha 2010, 28, 103–111. [Google Scholar] [CrossRef] [Green Version]
  31. Whalon, M.; Mota-Sanchez, D.; Hollingworth, R.; Duynslager, L. Arthropod Pesticide Resistance Database; Michigan State University: East Lansing, MI, USA, 2012; p. 38. [Google Scholar]
  32. Yu, S.; Nguyen, S.; Abo-Elghar, G. Biochemical characteristics of insecticide resistance in the fall armyworm, Spodoptera frugiperda (JE Smith). Pestic. Biochem. Physiol. 2003, 77, 1–11. [Google Scholar] [CrossRef]
  33. Sparks, T.C.; Crossthwaite, A.J.; Nauen, R.; Banba, S.; Cordova, D.; Earley, F.; Ebbinghaus-Kintscher, U.; Fujioka, S.; Hirao, A.; Karmon, D. Insecticides, biologics and nematicides: Updates to IRAC’s mode of action classification-a tool for resistance management. Pestic. Biochem. Physiol. 2020, 167, 104587. [Google Scholar] [CrossRef]
  34. Liu, J.; Hao, Z.; Yang, S.; Lin, Y.; Zhong, H.; Jin, T. Insecticide resistance and its underlying synergism in field populations of Spodoptera frugiperda (JE Smith) from Hainan Island, China. Phytoparasitica 2022, 50, 933–945. [Google Scholar] [CrossRef]
  35. Roy, D.; Biswas, S.; Sarkar, S.; Adhikary, S.; Chakraborty, G.; Sarkar, P.K.; Al-Shuraym, L.A.; Sayed, S.; Gaber, A.; Hossain, A. Risk Assessment of Fluxametamide Resistance and Fitness Costs in Fall Armyworm (Spodoptera frugiperda). Toxics 2023, 11, 307. [Google Scholar] [CrossRef]
  36. Chen, H.; Xie, M.; Lin, L.; Zhong, Y.; Zhang, F.; Su, W. Transcriptome analysis of detoxification-related genes in Spodoptera frugiperda (Lepidoptera: Noctuidae). J. Insect Sci. 2022, 22, 11. [Google Scholar] [CrossRef]
  37. Wu, W.; Tu, Y.; Liu, H.; Zhu, J. Celangulins II, III, and IV: New insecticidal sesquiterpenoids from Celastrus angulatus. J. Nat. Prod. 1992, 55, 1294–1298. [Google Scholar] [CrossRef]
  38. Zhou, L.; Meng, J.Y.; Ruan, H.Y.; Yang, C.L.; Zhang, C.Y. Expression stability of candidate RT-qPCR housekeeping genes in Spodoptera frugiperda (Lepidoptera: Noctuidae). Arch. Insect Biochem. Physiol. 2021, 108, e21831. [Google Scholar] [CrossRef]
  39. Tamura, K.; Stecher, G.; Peterson, D.; Filipski, A.; Kumar, S. MEGA6: Molecular evolutionary genetics analysis version 6.0. Mol. Biol. Evol. 2013, 30, 2725–2729. [Google Scholar] [CrossRef] [Green Version]
  40. Labute, P. Molecular Operating Environment; Chemical Computing Group. Inc.: Montreal, QC, Canada, 2008. [Google Scholar]
  41. Damayanthi Devi, I. Comparative binding mode of organophosphates, pyrethroids against modelled structures of acetylcholinesterase and alpha amylase in Blattella germanica. J. Entomol. Zool. Stud. 2015, 3, 233–238. [Google Scholar]
  42. Elkanzi, N.A.; Hrichi, H.; Bakr, R.B. Antioxidant, Antimicrobial, and Molecular Docking Studies of Novel Chalcones and Schiff Bases Bearing 1, 4-naphthoquinone Moiety. Lett. Drug Des. Discov. 2022, 19, 654–673. [Google Scholar] [CrossRef]
  43. Zhang, N.; Liu, J.; Chen, S.N.; Huang, L.H.; Feng, Q.L.; Zheng, S.C. Expression profiles of glutathione S-transferase superfamily in Spodoptera litura tolerated to sublethal doses of chlorpyrifos. Insect Sci. 2016, 23, 675–687. [Google Scholar] [CrossRef] [PubMed]
  44. Liu, S.; Zhang, Y.-X.; Wang, W.-L.; Zhang, B.-X.; Li, S.-G. Identification and characterisation of seventeen glutathione S-transferase genes from the cabbage white butterfly Pieris rapae. Pestic. Biochem. Physiol. 2017, 143, 102–110. [Google Scholar] [CrossRef] [PubMed]
  45. Zhou, W.-W.; Liang, Q.-M.; Xu, Y.; Gurr, G.M.; Bao, Y.-Y.; Zhou, X.-P.; Zhang, C.-X.; Cheng, J.; Zhu, Z.-R. Genomic insights into the glutathione S-transferase gene family of two rice planthoppers, Nilaparvata lugens (Stål) and Sogatella furcifera (Horváth) (Hemiptera: Delphacidae). PLoS ONE 2013, 8, e56604. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Francis, F.; Haubruge, E.; Gaspar, C.; Dierickx, P.J. Glutathione S-transferases of Aulacorthum solani and Acyrthosiphon pisum: Partial purification and characterization. Comp. Biochem. Physiol. Part B Biochem. Mol. Biol. 2001, 129, 165–171. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Ding, Y.; Ortelli, F.; Rossiter, L.C.; Hemingway, J.; Ranson, H. The Anopheles gambiae glutathione transferase supergene family: Annotation, phylogeny and expression profiles. BMC Genom. 2003, 4, 1–16. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Yu, Q.; Lu, C.; Li, B.; Fang, S.; Zuo, W.; Dai, F.; Zhang, Z.; Xiang, Z. Identification, genomic organization and expression pattern of glutathione S-transferase in the silkworm, Bombyx mori. Insect Biochem. Mol. Biol. 2008, 38, 1158–1164. [Google Scholar] [CrossRef]
  49. Prasanna, B.; Huesing, J.; Eddy, R.; Peschke, V. Fall Armyworm in Africa: A Guide for Integrated Pest Management; USAID: Washington, DC, USA; CIMMYT: Texcoco, Mexico, 2018.
  50. Sparks, T.C.; Nauen, R. IRAC: Mode of action classification and insecticide resistance management. Pestic. Biochem. Physiol. 2015, 121, 122–128. [Google Scholar] [CrossRef] [Green Version]
  51. Wu, X.; Zhang, L.; Yang, C.; Zong, M.; Huang, Q.; Tao, L. Detection on emamectin benzoate-induced apoptosis and DNA damage in Spodoptera frugiperda Sf-9 cell line. Pestic. Biochem. Physiol. 2016, 126, 6–12. [Google Scholar] [CrossRef]
  52. Fanigliulo, A.; Sacchetti, M. Emamectin benzoate: New insecticide against Helicoverpa armigera. Commun. Agric. Appl. Biol. Sci. 2008, 73, 651–653. [Google Scholar]
  53. Lahm, G.P.; Stevenson, T.M.; Selby, T.P.; Freudenberger, J.H.; Cordova, D.; Flexner, L.; Bellin, C.A.; Dubas, C.M.; Smith, B.K.; Hughes, K.A. Rynaxypyr™: A new insecticidal anthranilic diamide that acts as a potent and selective ryanodine receptor activator. Bioorganic Med. Chem. Lett. 2007, 17, 6274–6279. [Google Scholar] [CrossRef]
  54. Zhao, Y.-X.; Huang, J.-M.; Ni, H.; Guo, D.; Yang, F.-X.; Wang, X.; Wu, S.-F.; Gao, C.-F. Susceptibility of fall armyworm, Spodoptera frugiperda (JE Smith), to eight insecticides in China, with special reference to lambda-cyhalothrin. Pestic. Biochem. Physiol. 2020, 168, 104623. [Google Scholar] [CrossRef]
  55. Hardke, J.T.; Temple, J.H.; Leonard, B.R.; Jackson, R.E. Laboratory toxicity and field efficacy of selected insecticides against fall armyworm (Lepidoptera: Noctuidae). Fla. Entomol. 2011, 94, 272–278. [Google Scholar] [CrossRef]
  56. Zhang, J.; Jiang, J.; Wang, K.; Zhang, Y.; Liu, Z.; Yu, N. A Binary Mixture of Emamectin Benzoate and Chlorantraniliprole Supplemented with an Adjuvant Effectively Controls Spodoptera frugiperda. Insects 2022, 13, 1157. [Google Scholar] [CrossRef]
  57. Chen, H.-L.; Hasnain, A.; Cheng, Q.-H.; Xia, L.-J.; Cai, Y.-H.; Hu, R.; Gong, C.-W.; Liu, X.-M.; Pu, J.; Zhang, L. Resistance monitoring and mechanism in the fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae) for chlorantraniliprole from Sichuan Province, China. Front. Physiol. 2023, 14, 694. [Google Scholar] [CrossRef]
  58. El-Sayed, M.H.; Ibrahim, M.M.; Elsobki, A.E.; Aioub, A.A. Enhancing the Toxicity of Cypermethrin and Spinosad against Spodoptera littoralis (Lepidoptera: Noctuidae) by Inhibition of Detoxification Enzymes. Toxics 2023, 11, 215. [Google Scholar] [CrossRef]
  59. Liu, S.; Rao, X.J.; Li, M.Y.; Feng, M.F.; He, M.Z.; Li, S.G. Glutathione S-transferase genes in the rice leaffolder, Cnaphalocrocis medinalis (Lepidoptera: Pyralidae): Identification and expression profiles. Arch. Insect Biochem. Physiol. 2015, 90, 1–13. [Google Scholar] [CrossRef]
  60. Deng, H.; Huang, Y.; Feng, Q.; Zheng, S. Two epsilon glutathione S-transferase cDNAs from the common cutworm, Spodoptera litura: Characterization and developmental and induced expression by insecticides. J. Insect Physiol. 2009, 55, 1174–1183. [Google Scholar] [CrossRef]
  61. Gui, Z.; Hou, C.; Liu, T.; Qin, G.; Li, M.; Jin, B. Effects of insect viruses and pesticides on glutathione S-transferase activity and gene expression in Bombyx mori. J. Econ. Entomol. 2009, 102, 1591–1598. [Google Scholar] [CrossRef]
  62. Hu, B.; Hu, S.; Huang, H.; Wei, Q.; Ren, M.; Huang, S.; Tian, X.; Su, J. Insecticides induce the co-expression of glutathione S-transferases through ROS/CncC pathway in Spodoptera exigua. Pestic. Biochem. Physiol. 2019, 155, 58–71. [Google Scholar] [CrossRef]
  63. Hu, F.; Dou, W.; Wang, J.J.; Jia, F.X.; Wang, J.J. Multiple glutathione S-transferase genes: Identification and expression in oriental fruit fly, Bactrocera dorsalis. Pest Manag. Sci. 2014, 70, 295–303. [Google Scholar] [CrossRef]
  64. Zhang, S.; Zhang, D.; Jia, Y.; Li, J.; Li, Z.; Liu, X. Molecular identification of glutathione S-transferase genes and their potential roles in insecticides susceptibility of Grapholita molesta. J. Appl. Entomol. 2023, 147, 249–260. [Google Scholar] [CrossRef]
  65. Chen, X.e.; Zhang, Y.l. Identification and characterisation of multiple glutathione S-transferase genes from the diamondback moth, Plutella xylostella. Pest Manag. Sci. 2015, 71, 592–600. [Google Scholar] [CrossRef] [PubMed]
  66. Zhang, Y.; Dong, X.; Liu, J.; Hu, M.; Zhong, G.; Geng, P.; Yi, X. Molecular cloning, expression and molecular modeling of chemosensory protein from Spodoptera litura and its binding properties with Rhodojaponin III. PLoS ONE 2012, 7, e47611. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Venkatachalam, C.M.; Jiang, X.; Oldfield, T.; Waldman, M. LigandFit: A novel method for the shape-directed rapid docking of ligands to protein active sites. J. Mol. Graph. Model. 2003, 21, 289–307. [Google Scholar] [CrossRef]
  68. Chu, Y.-H.; Li, Y.; Wang, Y.-T.; Li, B.; Zhang, Y.-H. Investigation of interaction modes involved in alkaline phosphatase and organophosphorus pesticides via molecular simulations. Food Chem. 2018, 254, 80–86. [Google Scholar] [CrossRef]
  69. Jiang, L.; Li, Y.; Shi, W.; Chen, W.; Ma, Z.; Feng, J.; Hashem, A.S.; Wu, H. Cloning and expression of the mitochondrial cytochrome c oxidase subunit II gene in Sitophilus zeamais and interaction mechanism with allyl isothiocyanate. Pestic. Biochem. Physiol. 2023, 192, 105392. [Google Scholar] [CrossRef]
  70. Alanazi, M.A.; Arafa, W.A.; Althobaiti, I.O.; Altaleb, H.A.; Bakr, R.B.; Elkanzi, N.A. Green Design, Synthesis, and Molecular Docking Study of Novel Quinoxaline Derivatives with Insecticidal Potential against Aphis craccivora. ACS Omega 2022, 7, 27674–27689. [Google Scholar] [CrossRef]
  71. Yang, S.; Peng, H.; Zhu, J.; Zhao, C.; Xu, H. Design, synthesis, insecticidal activities, and molecular docking of novel pyridylpyrazolo carboxylate derivatives. J. Heterocycl. Chem. 2022, 59, 1366–1375. [Google Scholar] [CrossRef]
  72. Wiktelius, E.; Stenberg, G. Novel class of glutathione transferases from cyanobacteria exhibit high catalytic activities towards naturally occurring isothiocyanates. Biochem. J. 2007, 406, 115–123. [Google Scholar] [CrossRef] [Green Version]
  73. Feng, K.; Yang, Y.; Wen, X.; Ou, S.; Zhang, P.; Yu, Q.; Zhang, Y.; Shen, G.; Xu, Z.; Li, J. Stability of cyflumetofen resistance in Tetranychus cinnabarinus and its correlation with glutathione-S-transferase gene expression. Pest Manag. Sci. 2019, 75, 2802–2809. [Google Scholar] [CrossRef]
  74. Gonzalez, D.; Fraichard, S.; Grassein, P.; Delarue, P.; Senet, P.; Nicolaï, A.; Chavanne, E.; Mucher, E.; Artur, Y.; Ferveur, J.-F. Characterization of a Drosophila glutathione transferase involved in isothiocyanate detoxification. Insect Biochem. Mol. Biol. 2018, 95, 33–43. [Google Scholar] [CrossRef]
  75. Tan, X.; Hu, X.-M.; Zhong, X.-W.; Chen, Q.-M.; Xia, Q.-Y.; Zhao, P. Antenna-specific glutathione S-transferase in male silkmoth Bombyx mori. Int. J. Mol. Sci. 2014, 15, 7429–7443. [Google Scholar] [CrossRef] [Green Version]
  76. Naine, S.J.; Devi, C.S.; Mohanasrinivasan, V.; Doss, C.G.P.; Kumar, D.T. Binding and molecular dynamic studies of sesquiterpenes (2R-acetoxymethyl-1, 3, 3-trimethyl-4t-(3-methyl-2-buten-1-yl)-1t-cyclohexanol) derived from marine Streptomyces sp. VITJS8 as potential anticancer agent. Appl. Microbiol. Biotechnol. 2016, 100, 2869–2882. [Google Scholar] [CrossRef]
  77. Hashem, A.S.; Ramadan, M.M.; Abdel-Hady, A.A.; Sut, S.; Maggi, F.; Dall’Acqua, S. Pimpinella anisum essential oil nanoemulsion toxicity against Tribolium castaneum? Shedding light on its interactions with aspartate aminotransferase and alanine aminotransferase by molecular docking. Molecules 2020, 25, 4841. [Google Scholar] [CrossRef]
  78. Da Silva Mesquita, R.; Kyrylchuk, A.; Grafova, I.; Kliukovskyi, D.; Bezdudnyy, A.; Rozhenko, A.; Tadei, W.P.; Leskelä, M.; Grafov, A. Synthesis, molecular docking studies, and larvicidal activity evaluation of new fluorinated neonicotinoids against Anopheles darlingi larvae. PLoS ONE 2020, 15, e0227811. [Google Scholar] [CrossRef]
  79. Tiwari, N.; Mishra, A. Computational perspectives on Chlorpyrifos and its degradants as human glutathione S-transferases inhibitors: DFT calculations, molecular docking study and MD simulations. Comput. Toxicol. 2023, 26, 100264. [Google Scholar] [CrossRef]
Toxics 11 00542 g001 550
Figure 1. Phylogenetic analysis of SfGSTs in S. frugiperda. The phylogenetic tree was constructed using a neighbor-joining method to analyze the amino acid sequences of insect GSTs. Sl, Spodoptera litura; Pr, Pieris rapae; Bm, Bombyx mori; Nl, Nilaparvata lugens; Sf, Sogatella furcifera; Dm, Drosophila melanogaster; Ld, Leptinotarsa decemlineata; Ap, Acyrthosiphon pisum.
Figure 1. Phylogenetic analysis of SfGSTs in S. frugiperda. The phylogenetic tree was constructed using a neighbor-joining method to analyze the amino acid sequences of insect GSTs. Sl, Spodoptera litura; Pr, Pieris rapae; Bm, Bombyx mori; Nl, Nilaparvata lugens; Sf, Sogatella furcifera; Dm, Drosophila melanogaster; Ld, Leptinotarsa decemlineata; Ap, Acyrthosiphon pisum.
Toxics 11 00542 g001
Toxics 11 00542 g002a 550Toxics 11 00542 g002b 550
Figure 2. Relative expression levels of SfGSTs in larvae exposed to an LC50 of emamectin benzoate (EBZ) and chlorantraniliprole (CHP). Dunnett’s tests were performed to compare the gene expression of the tested insecticides with the corresponding control group (* p < 0.05, ** p < 0.01, *** p < 0.001).
Figure 2. Relative expression levels of SfGSTs in larvae exposed to an LC50 of emamectin benzoate (EBZ) and chlorantraniliprole (CHP). Dunnett’s tests were performed to compare the gene expression of the tested insecticides with the corresponding control group (* p < 0.05, ** p < 0.01, *** p < 0.001).
Toxics 11 00542 g002aToxics 11 00542 g002b
Toxics 11 00542 g003 550
Figure 3. Docking view of the binding interactions of emamectin benzoate (EBZ) within four receptors, (A) SfGSTe10, (B) SfGSTe13, (C) SfGSTs1, (D) SfGSTe2), in S. frugiperda. Left: two-dimensional interaction diagram of insecticide–receptor complexes. Right: the 3D complex structure and ligand bonds are depicted by yellow lines.
Figure 3. Docking view of the binding interactions of emamectin benzoate (EBZ) within four receptors, (A) SfGSTe10, (B) SfGSTe13, (C) SfGSTs1, (D) SfGSTe2), in S. frugiperda. Left: two-dimensional interaction diagram of insecticide–receptor complexes. Right: the 3D complex structure and ligand bonds are depicted by yellow lines.
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Figure 4. Docking view of the binding interactions of chlorantraniliprole (CHP) within four receptors, (A) SfGSTe10, (B) SfGSTe13, (C) SfGSTs1, (D) SfGSTe2), in S. frugiperda. Left: two-dimensional interaction diagram of insecticide–receptor complexes. Right: the 3D complex structure and ligand bonds are depicted by yellow lines.
Figure 4. Docking view of the binding interactions of chlorantraniliprole (CHP) within four receptors, (A) SfGSTe10, (B) SfGSTe13, (C) SfGSTs1, (D) SfGSTe2), in S. frugiperda. Left: two-dimensional interaction diagram of insecticide–receptor complexes. Right: the 3D complex structure and ligand bonds are depicted by yellow lines.
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Table
Table 1. Bioassay of EBZ and CHP against the third-instar of Spodoptera frugiperda after 24 h of treatment.
Table 1. Bioassay of EBZ and CHP against the third-instar of Spodoptera frugiperda after 24 h of treatment.
CompoundsToxicity Regression EquationLC50 (mg/L)95% Fiducial Limits (mg/L)rdf
EBZy = 0.059x + 3.23550.0290.019–0.0450.974
CHPy = 0.058x + 2.63881.2500.973–1.4550.964
Table
Table 2. Details of the 31 GSTs identified in Spodoptera frugiperda.
Table 2. Details of the 31 GSTs identified in Spodoptera frugiperda.
GroupGene NameORF (bp)Protein (aa)Molecular Weight (kDa)Theoretical pINCBI ID
DeltaSfGSTd172324027.235.64MZ673611
SfGSTd265121624.226.90MZ673619
EpsilonSfGSTe159419723.015.75MZ673615
SfGSTe265421725.176.23MZ673616
SfGSTe365421725.146.53MZ673617
SfGSTe434811594.385.71MZ673620
SfGSTe52919611.166.26MZ673621
SfGSTe666922225.117.81MZ673622
SfGSTe769323025.758.42MZ673623
SfGSTe842914215.956.90MZ673625
SfGSTe943214323.836.72MZ673626
SfGSTe1065721824.986.97MZ673629
SfGSTe1165721825.067.10MZ673630
SfGSTe1242013915.736.90MZ673632
SfGSTe1347415718.055.19MZ673633
SfGSTe1454017920.595.86MZ673635
SfGSTe1565721824.906.96MZ673636
SfGSTe1642013915.766.90MZ673637
SfGSTe17192637.055.44MZ673638
OmegaSfGSTo172324028.777.01MZ673610
SfGSTo284928232.487.01MZ673624
SigmaSfGSTs161820523.986.98MZ673614
SfGSTs261520423.094.92MZ673618
SfGSTs363921224.196.11MZ673628
SfGSTs463921220.075.44MZ673631
SfGSTs51083510.094.82MZ673634
SfGSTs663321023.875.61MZ673639
MicrosomalSfGSTm151617116.599.62MZ673612
SfGSTm245615116.649.79MN480699
SfGSTm345315016.649.65MZ673627
ThetaSfGSTt168722826.427.66MN480695
ORF: Open reading frame.
Table
Table 3. Comparison of GST genes in various insect species. Data are collated from [10,15,44,45,46,47,48,49].
Table 3. Comparison of GST genes in various insect species. Data are collated from [10,15,44,45,46,47,48,49].
SpeciesDeltaEpsilonOmegaSigmaThetaZetaUnclassifiedMicrosomalTotal
Spodoptera frugiperda21726100331
Spodoptera litura31536121536
Pieris rapae3344120017
Nilaparvata lugens2113101211
Sogatella furcifera211111029
Leptinotarsa decemlineata31054412130
Drosophila melanogaster111441421340
Acyrthosiphon pisum16126202332
Anopheles gambiae17811212335
Bombyx mori5742120122
Table
Table 4. Docking results for chlorantraniliprole (CHP) and emamectin benzoate (EBZ) within four modeled active sites of S. frugiperda.
Table 4. Docking results for chlorantraniliprole (CHP) and emamectin benzoate (EBZ) within four modeled active sites of S. frugiperda.
GenesEBZCHP
Binding Energy (kcal/M)RMSD
(A ◦)		Binding Energy (kcal/M)RMSD
(A ◦)
SfGSTe10−24.414.47−26.722.94
SfGSTe13−26.852.96−26.782.36
SfGSTs1−23.161.49−18.454.61
SfGSTe2−21.192.36−19.524.42
RMSD: root-mean-square deviation.
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Aioub, A.A.A.; Hashem, A.S.; El-Sappah, A.H.; El-Harairy, A.; Abdel-Hady, A.A.A.; Al-Shuraym, L.A.; Sayed, S.; Huang, Q.; Abdel-Wahab, S.I.Z. Identification and Characterization of Glutathione S-transferase Genes in Spodoptera frugiperda (Lepidoptera: Noctuidae) under Insecticides Stress. Toxics 2023, 11, 542. https://doi.org/10.3390/toxics11060542

AMA Style

Aioub AAA, Hashem AS, El-Sappah AH, El-Harairy A, Abdel-Hady AAA, Al-Shuraym LA, Sayed S, Huang Q, Abdel-Wahab SIZ. Identification and Characterization of Glutathione S-transferase Genes in Spodoptera frugiperda (Lepidoptera: Noctuidae) under Insecticides Stress. Toxics. 2023; 11(6):542. https://doi.org/10.3390/toxics11060542

Chicago/Turabian Style

Aioub, Ahmed A. A., Ahmed S. Hashem, Ahmed H. El-Sappah, Amged El-Harairy, Amira A. A. Abdel-Hady, Laila A. Al-Shuraym, Samy Sayed, Qiulan Huang, and Sarah I. Z. Abdel-Wahab. 2023. "Identification and Characterization of Glutathione S-transferase Genes in Spodoptera frugiperda (Lepidoptera: Noctuidae) under Insecticides Stress" Toxics 11, no. 6: 542. https://doi.org/10.3390/toxics11060542

APA Style

Aioub, A. A. A., Hashem, A. S., El-Sappah, A. H., El-Harairy, A., Abdel-Hady, A. A. A., Al-Shuraym, L. A., Sayed, S., Huang, Q., & Abdel-Wahab, S. I. Z. (2023). Identification and Characterization of Glutathione S-transferase Genes in Spodoptera frugiperda (Lepidoptera: Noctuidae) under Insecticides Stress. Toxics, 11(6), 542. https://doi.org/10.3390/toxics11060542

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