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Article

Detect Cytochrome C Oxidase- and Glutathione-S-Transferase-Mediated Detoxification in a Permethrin-Resistant Population of Lygus lineolaris

1
United States Department of Agriculture, Agricultural Research Service, Jamie Whitten Delta States Research Center (USDA-ARS-JWDSRC), Stoneville, MS 38776, USA
2
Department of Entomology, Kansas State University, Manhattan, KS 66506, USA
3
Zhejiang Academy of Agricultural Sciences, Hangzhou 310004, China
*
Author to whom correspondence should be addressed.
Submission received: 24 February 2023 / Revised: 26 March 2023 / Accepted: 2 April 2023 / Published: 4 April 2023
(This article belongs to the Special Issue Effect of Pesticides on Insects and Other Arthropods)

Abstract

:
Frequent sprays on cotton prompted resistance development in the tarnished plant bug (TPB). Knowledge of global gene regulation is highly desirable to better understand resistance mechanisms and develop molecular tools for monitoring and managing resistance. Novel microarray expressions of 6688 genes showed 3080 significantly up- or down-regulated genes in permethrin-treated TPBs. Among the 1543 up-regulated genes, 255 code for 39 different enzymes, and 15 of these participate in important pathways and metabolic detoxification. Oxidase is the most abundant and over-expressed enzyme. Others included dehydrogenases, synthases, reductases, and transferases. Pathway analysis revealed several oxidative phosphorylations associated with 37 oxidases and 23 reductases. One glutathione-S-transferase (GST LL_2285) participated in three pathways, including drug and xenobiotics metabolisms and pesticide detoxification. Therefore, a novel resistance mechanism of over-expressions of oxidases, along with a GST gene, was revealed in permethrin-treated TPB. Reductases, dehydrogenases, and others may also indirectly contribute to permethrin detoxification, while two common detoxification enzymes, P450 and esterase, played less role in the degradation of permethrin since none was associated with the detoxification pathway. Another potential novel finding from this study and our previous studies confirmed multiple/cross resistances in the same TPB population with a particular set of genes for different insecticide classes.

1. Introduction

The tarnished plant bug (TPB), Lygus lineolaris, is a polyphagous insect and can easily be found year-round on a variety of crops in Mid-south US. Although transgenic Bt crops are effective against many insect pests, the TPB is still the most economically important pest in Mid-south cotton growing areas [1]. Damage caused by feeding TPBs leads to malformed cotton bolls with dark lesions, resulting in the shedding of squares, small bolls, stunted plants, aborted terminals, boll deformation, lint staining, and yield loss [2]. Currently, chemical control with synthetic insecticides is the primary control method for this pest. More than forty insecticides are currently recommended by extension specialists in the United States for the chemical control of row crop insects [3,4,5]. Many insecticides have been used on cotton for controlling TPB, bollworm, and a range of other pests, including pyrethroids, organophosphates, carbamates, neonicotinoids, and novel insect growth regulators [3].
Permethrin is a neurotoxic synthetic pyrethroid insecticide. It acts on the nervous system of insects, interfering with sodium channels to disrupt neuron function, causing muscles to spasm, culminating in paralysis and death [6,7]. Long-term use of chemical insecticides for TPB control gradually decreases the efficacy of insecticides, and resistance to pyrethroids has been found in many TPB populations in the mid-south [8,9,10]. Since the first report of pyrethroid resistance in a tarnished plant bug field population high enough to cause a control failure in cotton [11], very little research has been conducted to determine biochemical and molecular mechanisms for resistance development in the natural ecosystem before the 2000s. Research has concentrated on knockdown resistance and has provided evidence that mutations in sodium channels are the primary resistance mechanism [12]. However, many researchers have linked mechanisms of pyrethroid resistance with metabolic detoxification enzymes, such as P450 monooxygenases, esterases, and glutathione S-transferases [13,14,15]. Zhu et al. [16] and Zhu and Luttrell [17] found that TPB populations were able to develop multiple and cross resistance to different insecticides (classes). If resistance is left unchecked, the cost due to yield loss, control cost increase, and environmental contamination could be enormous.
Quantitative real-time PCR (qrt-PCR) is a common method for studying gene regulation and insecticide resistance mechanisms by measuring whether relevant gene expressions are altered [18]. However, the method is inefficient, and no more than 96 genes can be examined at a time. As an alternative, microarray technology is a powerful tool for examining the expression of thousands or even millions of genes at once [19]. To understand how gene regulation and biochemical processes influence insecticide susceptibility, we took advantage of robust microarray technology in this study to analyze 6688 gene expressions simultaneously in a TPB population collected from a cotton field and subsequently selected with permethrin. A laboratory colony unexposed to any pesticide was used as a side-by-side control. To identify genes participating in detoxification pathways, Blast2go annotation, and enzyme KEGG pathway analyses were also applied to reveal the functions of major significantly up- and down-regulated genes. By using these novel microarrays and powerful analytical tools, we were able to identify a set of metabolic genes relevant to the detoxification of insecticides, thus expanding our ability to effectively monitor and manage permethrin resistance in TPB, a great step forward in our understanding of resistance in pest insect populations.

2. Materials and Methods

2.1. Insect Laboratory Colony and Field Population

A laboratory colony (LLMCK) was originally provided by Kathy Knighten and Fred Musser at Mississippi State University. The colony, established in 2005 from a collection of tarnished plant bug from the Mississippi Delta area, has been maintained on an artificial diet [20] without exposure to insecticide. Wild adults (collected from fleabane [Erigeron spp.] and ryegrass [Lolium spp.]) are introduced into this colony in the spring of each year to enhance genetic diversity and colony vigor. This colony was used as a standard susceptible strain.
During 2011, many field populations were collected and subjected to discriminating dose assays using permethrin (Arctic 3.2 EC, 36.8% a.i., Winfield Solution, LLC, St. Paul, MN, USA) at 145 mg/L Arctic formulation. Bugs were treated with a modified spray tower, and mortality was recorded after 48 h. To prepare samples for microarray analysis, a field population was collected in July 2011 from a cotton field north of Stoneville, Mississippi. Permethrin-selected bugs (Arct2175FF) were from a permethrin treatment of the field population. Approximately 300 bugs were collected and selected with Arctic 3.2 EC at 2175 mg/L (or 800.44 mg a.i./L permethrin), which was 15-fold (resistance ratio = 15-fold) higher than the LC50 of LLMCK. Adults were held in a 2.5-ga bucket covered with fine (10 grids/cm) net cloth at the top and bottom. Two mL of permethrin solution (4× higher volume than that used for the LC50 test) was used to treat the cage thoroughly from the top by using a modified Potter Spray Tower. The sprayer was set at 7.5 psi with a spray distance of 30.5 cm to ensure uniform deposition of insecticide mist on the inner surface of the container, green beans (supplied as food for TPBs), and bugs. Treated bugs stayed on permethrin-treated green beans for 48 h, and survivors (showing normal viability) were collected and stored at −80 °C for microarray analysis.

2.2. Preparation of cDNA Sequences for Microarray Expression Chips

Total RNA was prepared using TriZol reagent (Invitrogen, Carlsbad, CA, USA). mRNA was purified from total RNA using the NucleoTrap mRNA purification kit (BD Bioscience Clontech, Palo Alto, CA, USA). The Creator Smart cDNA Library Construction Kit (BD Bioscience Clontech) was used for cDNA library construction by following the manufacturer’s instructions and modified protocols described by Zhu et al. [21]. Approximately 30,000 clones were obtained and sequenced with an M13 forward primer on an ABI 3730XL sequencer. cDNA sequences were assembled using Lasergene software (DNAStar, Madison, WI, USA) and subjected to a similarity search for putative identity against GenBank protein and nucleotide databases (http://blast.ncbi.nlm.nih.gov/Blast.cgi (accessed on 1 April 2023)). cDNA sequences were submitted to Roche NimbleGen (Roche NimbleGen, Inc., Madison, WI, USA) for the production of 72K gene expression chips in 4-plex format. A 60-bp specific oligonucleotide was designed and synthesized as a probe. Approximately 35,000 probes (an average of 5 probes per cDNA) were synthesized and printed on each gene expression chip.

2.3. Acquiring Microarray Data

Roche NimbleGen gene expression chips were used to compare global gene expression between permethrin-selected (Arct2175FF) and susceptible (LLMCK) strains of TPB. Microarray analysis was processed using standard NimbleGen array protocols. Total RNA was extracted from adults using TriZol reagent (Invitrogen). Double-strand cDNAs were synthesized by using the SuperScript Double-Stranded cDNA Synthesis Kit (Invitrogen) according to the manufacturer’s protocols. Double strand cDNA samples were labeled with the One-color DNA Labeling Kit and hybridized to the microarray chips. Microarray data were acquired according to NimbleScan v.25 User’s Guide through Florida State University’s Microarray processing facility. Three arrays (3 replicates) of 72K NimbleGen expression chips were processed for each sample.

2.4. Analysis of Microarray Data

After gene expression data were obtained from 4 × 72 K array processing, ArrayStar® software (DNAStar, Inc., Madison, WI, USA) was used to analyze and compare microarray data between LLMCK and Arct2175FF. Expression data were log2-transformed and normalized through quantile normalization [22]. The data were analyzed using classical parametric statistics. p-values were calculated using a Modified t-test. A fold-change cutoff of 2 and p-value threshold of 0.05 were used to determine significantly differential gene expression.
After microarray data were processed, up-regulated and down-regulated genes (cDNAs) were separately subjected to sequence annotation and pathway analysis using step-by-step processing of Blastx, mapping, annotation, enzyme code, and KEGG analysis protocols provided by Blast2go (https://www.blast2go.com (accessed on 1 April 2023)).

3. Results

3.1. Scatter-Plot Comparison of Gene Expression Levels between LLMCK and Arct2175FF

A total of 7446 unique contigs and singletons were obtained from cDNA library sequencing, with 6688 genes showing valid expression values from hybridization to labeled probes (Double-Stranded cDNAs of permethrin-resistant Arct2175FF and susceptible LLMCK bug samples). Figure 1 was from scanned signals of hybridized gene chips of Arct2175FF that were log2 converted, normalized, and plotted against the corresponding signals of the susceptible (LLMCK) strain. The plot (Figure 1) shows distributions of 6688 gene expression levels. Each tiny square represents a unique gene expression ratio between Arct2175FF and LLMCK strains. Gene expression levels of the two strains showed a linear correlation (R2 = 0.721). Statistics show the expression levels of 3080 genes in permethrin-selected (Arct2175FF) bugs were up- or down-regulated by >2-fold. Among those 3080 genes, 1364 were up/down-regulated by >4-fold, and 539 were up/down-regulated by >8-fold. Another 2622 genes were up/down-regulated by less than 2-fold (1205 up and 1417 down) (Figure 1). The expression levels of the remaining 986 genes studied were not significantly different between Arct2175 and LLMCK.

3.2. Identity of Up- and Down-Regulated Genes

Among 1543 up-regulated (>2 fold) genes, 255 code for 39 enzymes. Based on function and participation in important pathways involving metabolic detoxification and resistance development, Table 1 lists contig names, sequence length, up-regulation levels (fold), coded enzymes, and other parameters of 187 enzyme-coding cDNAs. Fifteen different metabolic enzymes are encoded by these 187 cDNAs; several of these enzymes are encoded by multiple cDNA sequences, including 64 cDNAs for oxidases, 49 cDNAs for dehydrogenases, 28 cDNAs for synthases, 11 cDNAs for reductases, 11 cDNAs for transferases, 7 cDNAs for esterases, 5 cDNAs for glutathione S-transferases, and four or fewer cDNAs for ATPase, cytochrome P450 monooxygenases, phosphatases, phosphodiesterase, thioesterases, ATP sythetases, and transcriptases. Some synthases may include ATP synthases, ATPases, and synthetases (Table 1). Another 24 enzymes coded by 68 cDNAs were not included in Table 1; they are amidase, amylase, carboxypeptidase, cathepsin, cysteine protease, dioxygenase, dismutase, exonuclease, glucosidase, helicase, hydrolase, integrase, isomerase, kinase, ligase, lipase, lyase, myrosinase, nuclease, peptidase, peptidase, polygalacturonase, polymerase, and protease.
There were 386 enzyme-coding genes showing significantly reduced (>2-fold) expression levels, coding for 53 enzymes. By considering the importance of their functions and involvements in metabolic detoxification pathways, contig names, sequence length, down-regulation levels (fold), coded enzymes, and other parameters of 114 enzyme-coding cDNAs are listed in Table 2. These genes encode 13 important metabolic enzymes. Several of the enzymes are encoded by multiple cDNA sequences, including 26 cDNAs for dehydrogenases, 19 cDNAs for ATP synthases or ATPases, 18 for transferases, 11 for P450 monooxygenases, 9 for reductases, 8 for hydrolases, 7 for oxidases, 6 for esterases, 5 for GSTs, 3 for reductases/peptidases, one for peroxidase, and one for phosphate synthase (Table 2). In addition, another 40 encoded enzymes may be indirectly involved in some metabolic processes (not included in Table 2). They are aldolase, amylase, anhydrase, carboxypeptidase, cathepsin, chitinase, cysteine peptidase, cysteine protease, decarboxylase, deoxyribonuclease, desaturase, dioxygenase, dismutase, enolase, epimerase, fucosidase, glucosidase, glyoxalase, helicase, hexosaminidase, hydroxylase, isomerase, kinase, ligase, lipase, lyase, nucleotidase, ovochymase, peptidase, phosphatase, phosphodiesterase, polygalacturonase, polymerase, protease, RNase H, synthetase, thioesterase, transaminase, translocase, and trypsin. Several digestive-related enzymes are encoded by a large number of cDNA sequences, and their gene expression levels were significantly down-regulated in permethrin-treated bugs. These enzymes included 41 cDNAs for cathepsins, 41 cDNAs for proteases, 14 cDNAs for polygalacturonases, and 6 cDNAs for trypsins.

3.3. Annotation and Functional Analysis of Up-Regulated Genes in Arct2175FF

Reruns of Blast2go mapping, annotation, and KEGG analyses of 1543 up-regulated (≥2-fold) cDNAs revealed a large number of genes involved in biological processes (Figure 2) and molecular functions (Figure 3).

3.3.1. Gene Regulation in Biological Processes

Annotation with Blast2go showed that 759 up-regulated genes were involved in 40 biological processes in Arct2175FF at GO level 3 (Figure 2). These are cumulative numbers of the genes for each biological process and are higher than the actual number of genes, indicating some genes had multiple functions. Among the 40 biological processes at GO level 3, cellular metabolic, primary metabolic, biosynthetic, macromolecule metabolic, and oxidation-reduction processes seemed to be particularly important, as indicated by the participation of higher numbers (164, 115, 93, 78, and 67, respectively) of genes in these processes than in other biological processes and the fact that metabolic detoxification is a major mechanism in insecticide resistance development. Other affected metabolic processes are nitrogen compound metabolism (44 genes) and small-molecule metabolism (30 genes); 24 of these 40 biological processes involved less than 4 up-regulated genes (Figure 2).

3.3.2. Gene Regulation in Molecular Function

Annotation with Blast2go showed that at level 3, 433 up-regulated genes were influenced by permethrin treatment. These up-regulated genes were involved in 30 molecular functions in Arct2175FF (Figure 3). The most enhanced five molecular functions, oxidoreductase activity, substrate-specific transporter activity, transmembrane transporter activity, structural constituent of ribosome, and hydrolase activity, were associated with 77, 74, 68, 53, and 43 up-regulated genes, respectively.

3.4. Gene Regulation Influencing Metabolic Pathways in Arct2175FF

KEGG analyses of 1543 up-regulated genes (>2-fold) identified 165 up-regulated specific genes and their involvements in 27 specific pathways. In Table 3, 71 contig names of the cDNAs are listed for 9 important pathways potentially associated with metabolic detoxification and resistance development to permethrin in TPB. Genes involved in another 18 pathways, such as nitrogen, starch, and sucrose metabolisms, etc., are not included in Table 3. Oxidase and reductase (H+-translocating) (ec:1.6.5.3) genes are the primary up-regulated genes for the oxidative phosphorylation pathway (37 and 23 genes, respectively). A few dehydrogenase, reductase (ec:1.10.2.2), ATPase, and diphosphatase genes were also found to be associated with this pathway. The gene LL_2258 (GST) participates in three pathways, i.e., glutathione metabolism, drug metabolism—cytochrome P450, and metabolism of xenobiotics by cytochrome P450 (Table 3).
Analyses of 1537 down-regulated genes (>2-fold) identified 256 specific genes involving 147 pathways. In Table 4, 32 contigs containing cDNAs are listed to represent 12 pathways potentially associated with metabolic detoxification and resistance to permethrin in TPB. Another 135 pathways, such as nitrogen metabolism (oxidases and reductases), pyruvate metabolism (dehydrogenases, reductases, kinases), the citrate cycle (dehydrogenase, hydratase, ligases), etc., were affected but were not included in Table 4. Down-regulation of 12 ATPase genes made the phosphorylation pathway the most heavily influenced pathway by permethrin. LL_6284, coding for a GST, is associated with three detoxification pathways: glutathione metabolism, drug metabolism, and metabolism of xenobiotics (Table 4); however, LL_6284 was significantly down-regulated in Arct2175FF. LL_2553, a down-regulated phosphoribosyltransferase gene, also participates in drug metabolism. Large numbers of cathepsin (41), lipase (9), polygalacturonase (14), protease (41), and trypsin (6) genes were among the 1537 significantly down-regulated genes. In contrast, 11 of the 12 P450 but only 7 of the 71 oxidase genes were significantly down-regulated in Arct2175FF. In addition, 24 vitellogenin and 9 RP45 eggshell genes were significantly down-regulated in Arct2175FF.

4. Discussion

In this study, microarray analysis was applied to quantify expressions of 6688 gene transcripts (simply called genes) simultaneously. Most of the 6688 cDNAs obtained using an ABI 3730XL sequencer were probably single reads (singletons). Five 60-bp oligonucleotides were designed as five probes (replicates) from different regions of each cDNA and printed on a gene chip. For microarray processing, we used three gene chips as three replications for each permethrin-treated sample and control sample. Therefore, each expression signal was averaged from 15 separate probe signals. Increased replicates and replications ensured data reliability which was higher than that of previously published data obtained from only one or two chips per sample. Microarrays were commonly used between 2002 and 2013 for the analysis of gene expression. Some hybridization data collected from nylon membranes dotted with less than 100 known cDNAs were also called microarray analysis. Next-generation sequencers facilitated the capacity of microarrays to analyze twenty thousand or more gene expressions at once [23,24,25]. Surprisingly, our microarray analysis detected greater numbers and diversity of detoxification genes than those microarrays using higher capacity chips (20,000 genes). Similarly, the popular and more recent (2015-present) RNA-Seq technology has been used to quantify pyrethroid resistance-related transcript expression against a larger gene pool [26,27,28]. However, RNA-Seq has not significantly increased knowledge of transcriptional expression patterns in either variety or number of pyrethroid resistance genes detected compared to microarrays. Furthermore, a novel mechanism of (large number) cytochrome c oxidase-mediated, along with a GST-mediated, detoxification as the major mechanism in permethrin-resistant TPB was detected in this study using microarray, which has not been detected using RNA-Seq or microarray even with higher capacity gene chips [26,27,28].
Functional analyses indicated that large numbers of up-regulated genes participated in 40 biological processes and 30 molecular functions. Of these, two biological processes, cellular metabolism and primary metabolism, are carried out by more than 100 up-regulated genes in permethrin-selected TPB. Molecular function analyses showed this trend in five molecular functions as well. Oxidoreductase activity, substrate-specific transporter activity, transmembrane transporter activity, structural constituent of ribosome, and hydrolase activity were the five most enhanced molecular functions in permethrin-treated TPBs. Oxidoreductase activity (pumps protons across the inner membrane of mitochondria or the plasma membrane [29]) is the most enhanced molecular function (Figure 3), which is catalysis of an oxidation-reduction reaction (oxidative phosphorylation [30] in Table 3) by oxidases, dehydrogenases, hydroperoxidases, and oxygenases. Therefore, both functional and pathway analyses (see below) indicated that oxidases reductases, dehydrogenases, ATPases, and diphosphatases were consistently associated with and facilitated pyrethroid detoxification [31] and resistance development in TPB.
By using blast2go and other molecular tools, we identified 256 significantly up-regulated genes that code for a variety of enzymes. In total, 187 genes code several functionally important enzymes that regulate 17 physiologically essential pathways. Nine of these pathways are associated with oxidative phosphorylation and metabolism of drugs and xenobiotics (i.e., detoxification), comprised of oxidases, reductases, dehydrogenases, ATPases, transferases, and cytochrome P450 monooxygenases. After frequent exposures to insecticides, some insect populations may evolve resistance to those insecticides via gene mutation [32,33] and [34]/or enhanced gene expressions [35].
By using microarray analysis, we found that cytochrome c oxidase genes are the most over-expressed enzyme genes in permethrin-treated TPB (Arct2175FF). Sixty-four oxidase genes were identified that code for at least 8 different oxidases from subunits 1 to 10 except subunits 4 and 5. Cytochrome c oxidase subunit 3 is the most abundant oxidase in permethrin-treated TPB, followed by subunits 7 and 2. Over-expression of oxidase subunits 3 and 1 was reportedly responsible for resistance development in many insects [36,37,38]. However, not all oxidase genes were up-regulated. Seven oxidase genes were found to be significantly down-regulated in permethrin-resistant TPB, including glutathione peroxidase-like, cytochrome c oxidase subunits 5a and 5b, cytochrome c oxidase assembly protein cox15, fad-linked sulfhydryl oxidase alr-like, and spermine oxidase. None of these down-regulated oxidase genes belong to the subunits (1–3 and 6–10) of up-regulated oxidase genes, indicating some oxidase genes are functionally diverged and are differentially regulated in permethrin-resistant TPB. In addition, oxidase subunit 4, coded by LL_1380, showed 1.195-fold down-regulation (<2-fold and therefore not significant). Molecular phylogeny analysis showed that TPB oxidase genes are relatively diverse: six subgroups have four or more members, and three have two members. Another 7–11 members’ positions have not been clearly resolved (phylogeny tree not included). Hence, this study profiles the gene expression of 11 subunits (1–10 and 15) of cytochrome c oxidase, significantly extending our knowledge of the involvement of these oxidase genes, particularly the overexpressed subunits 1–3 and 6–10 in permethrin-treated TPBs. These data will greatly facilitate the development of specific biomarkers and molecular control strategies for future studies.
Previously we used the same gene chips to analyze differences in gene expression between the susceptible colony LLMCK (also used in this study) and an imidacloprid-resistant population Im1500FF [17]. The Im1500FF TPBs were collected from the same location as Arct2175FF (Feather Farm) and treated with 1500 mg/L imidacloprid formulation (Advise 2FL). Only one oxidase (LL 547, subunit 1) gene was up-regulated in Im1500FF compared with 64 in Arct2175FF. Incidentally, LL 547, subunit 1 was significantly down-regulated in Arct2175FF. A total of 3 oxidase genes were significantly down-regulated in Im1500FF. Of these, LL_963 (subunit 7a), down-regulated in Im1500FF, was up-regulated in Arct2175FF. The other two, LL_791 (subunit 5a) and LL_5776 (spermine oxidase), were down-regulated in both Im1500FF and Arct2175FF. The data from comparison of the same population treated with different insecticides, imidacloprid (a neonicotinoid) for Im1500FF and permethrin (a pyrethroid) for Arct2175FF, indicated that cytochrome oxidase genes are predominantly associated with permethrin metabolic detoxification/resistance development, while P450 monooxygenase and esterases are the major genes for imidacloprid resistance. Therefore, it is clear that the same population had developed resistance to multiple insecticides and cross resistance to different insecticide classes (have different modes of action [17]) with different/unique sets of genes for different insecticides (classes) (see below).
Most resistance development is associated with over-expression of genes encoding metabolic detoxification enzymes, such as esterase, glutathione S-transferases (GST), and cytochrome P450 monooxygenase (P450) genes [39]. Cytochrome P450 monooxygenases (P450) catalyze the oxidation of organic substances to fulfill many important tasks, from the synthesis, degradation, and metabolic intermediation of lipids, ecdysteroids, and juvenile hormones to the metabolism of xenobiotics [40]. P450 genes play a central role in the adaptation to plant chemicals and the development of resistance to pesticides. It is well established that many cases of metabolic resistance to insecticides are the result of elevated levels of P450 [41]. Only one P450 gene (LL_3359) was significantly up-regulated, but it did not participate in any important pathway (Table 3); 11 P450 genes were significantly down-regulated, but again none of the 11 P450s was involved in an important pathway in Arct2175FF, with the exception of the P450 encoded by significantly down-regulated LL_3822. Unlike Arct2175FF, imidacloprid-selected Im1500FF showed 5 significantly up-regulated and zero significantly down-regulated P450s. The putative enzyme EC:1.14.14.1 (P450), coded by LL_3822, participates in 11 different metabolic pathways, including potential insecticide-resistance-related drug metabolism and xenobiotics metabolism pathways in Im1500FF [17], while this functionally important gene was significantly down-regulated by >2-fold in the Arct2175FF. All these phenomena indicate that P450s are not closely associated with detoxification and survival in permethrin-treated TPBs.
Esterases (EC 3.1) are a group of hydrolase enzymes capable of hydrolyzing compounds containing ester bonds, thereafter splitting esters into an acid and an alcohol in a chemical reaction with water [42]. Esterases are frequently implicated in the resistance of insects to organophosphates, carbamates, and pyrethroids through gene amplification, upregulation, coding sequence mutations, or a combination of these mechanisms [39]. Seven esterase genes were significantly up-regulated, and six esterase genes were significantly down-regulated in Arct2175FF. However, imidacloprid-selected Im1500FF showed nine significantly up-regulated and only one significantly down-regulated esterase gene. Of the nine up-regulated esterase genes, five (LL_699, LL_2508, LL_2600, LL_2639, and LL_L223) code for esterase ec:3.1.1.1, associated with drug metabolism and potentially resistance development in Im1500FF [17]. Only one ec:3.1.1.1-coding gene (LL-223) was found to be up-regulated in Arct2175FF, indicating that this TPB population relied less on esterases for detoxifying permethrin than for detoxifying imidacloprid.
Glutathione S-transferase (GST) utilizes glutathione to catalyze the conjugation of reduced (sulfur-substituted) glutathione, via a sulfhydryl group, to electrophilic centers on a wide variety of substrates [43]. The catalysis reactions transform a wide range of endogenous and xenobiotic compounds, including therapeutic drugs, products of oxidative stress, and pesticides, by neutralizing their electrophilic sites and rendering the products more water-soluble for further metabolization and excretion [44,45,46,47]. Several studies have indicated that GSTs play an important role in the acquisition of resistance to insecticides [46,47,48]. Results from this study showed that 5 GST genes were significantly up-regulated, while another 5 GST genes were significantly down-regulated in permethrin-treated TPBs. Pathway analysis revealed that the GST gene LL_2258, up-regulated >4.29-fold (the highest), participates in glutathione metabolism, drug metabolism, and metabolism of xenobiotics, indicating its versatilities in detoxification and importance for surviving permethrin treatment. In imidacloprid-treated TPBs, 4 GST genes were significantly down-regulated, and none was up-regulated, indicating the TPB relies less on GSTs for detoxifying imidacloprid [17].
Besides the four enzyme genes mentioned above, there are 15 other metabolic enzyme genes that were upregulated or downregulated by >2-fold in Arct2175FF. Seventeen polygalacturonase genes were up-regulated, while fourteen other polygalacturonase genes were down-regulated. Equal numbers of genes for cysteine protease and polymerase were up- and down-regulated. Five and three ligase genes were down- and up-regulated, respectively. Three- to five-fold more down-regulated genes than up-regulated genes were found in genes for amylase, lipase, hydrolase, kinase, peptidase, glucosidase, protease, and helicase. Eight-, 10.25-, and 12-fold more down-regulated than up-regulated genes were found in the genes for isomerase, cathepsin, and carboxypeptidase, respectively. Many of these genes, such as cathepsin, carboxypeptidase, and protease, are involved in the digestion of food nutrients. A significant increase in the numbers of these down-regulated enzyme-coding genes, including many genes for eggshell and vitellogenins, may be associated with the fitness cost of insecticide resistance development, resulting in a substantial decrease in colony vitality and reproduction [17]. Further investigations are needed to reveal any direct and/or indirect associations of some up-and down-regulated genes with metabolic detoxification and development of multiple and cross resistance in TPB.

5. Conclusions

Severe damage to crops, increased control cost, and environmental insecticide contamination would be the grievous consequences if insecticide resistance in one of the most damaging pests is left unchecked. In this study, novel microarray and extensive functional and pathway analyses of 6688 genes identified a unique set of up-regulated genes that participated in many metabolic processes and catalytic functions, confirming that metabolic resistance has evolved in TPBs from a cotton field. Oxidase and GST are the most potent detoxification enzymes, and over-expressions of these genes enable permethrin-treated TPBs to survive. Besides these commonly known detoxification enzymes, pathway analysis in this study revealed several oxidative phosphorylations associated with large number of oxidases and reductases, as well as some dehydrogenases, reductases, ATPases, and diphosphatases. These oxidative phosphorylations may directly or indirectly influence the chance of surviving TPBs after permethrin treatment. Based on all our microarray data from this study and previous studies, we found that TPB has evolved resistance to multiple insecticides, including organophosphates, neonicotinoids, and pyrethroids. Our findings indicated that the TPB population has developed a particular set of resistance genes for different insecticides. The findings of this current analysis, combined with previous data and our ongoing study on gene regulation in carbamate-treated TPB, will shed light on the resistance mechanisms of four commonly used insecticide classes and facilitate the future development of integrated strategies for monitoring and minimizing resistance risk.

Author Contributions

Conceptualization, Y.-C.Z.; methodology, Y.-C.Z. and X.F.L.; software, Y.-C.Z.; validation, Y.-C.Z.; formal analysis, Y.-C.Z.; investigation, Y.-C.Z.; resources, Y.-C.Z.; data curation, Y.-C.Z. and X.F.L.; writing—original draft preparation, Y.-C.Z.; writing—review and editing, Y.-C.Z., Y.D., J.Y. and Y.W.; visualization, Y.-C.Z.; supervision, Y.-C.Z.; project administration, Y.-C.Z.; funding acquisition, Y.Z All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived because the animal used in this study is an insect pest. Publishing the research data (Log # 387926) was approved by agency Research Leader, Area Director, and National Program Leader.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data were provided in the publication.

Acknowledgments

The authors appreciate Sandy West, Lily Luo, and Brian Scheffler for their assistance in this study. The authors are deeply thankful to Joel Caren for his thorough editing of the manuscript and to anonymous journal reviewers for their comments and suggestions in improving the manuscript. Any mention of a proprietary product does not constitute a recommendation or endorsement by the USDA.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Analysis of microarray data and comparison of 6688 gene expression levels between susceptible (LLMCK) and permethrin-selected (Arct2175FF) tarnished plant bugs using ArrayStar software. Scatter-plot comparison of 6688 gene expression levels between LLMCK and Arct2175FF. The mini squares of the scatter plot in the upper left corner represented up-regulated genes, and the squares in low right corner represented down-regulated genes. Squares above line 2 × Up and below line 2 × Dn represent up- and down-regulated genes by 2-fold; Squares above line 4 × Up and below line 4 × Dn represent up- and down-regulated genes by 4-fold; Squares above line 8 × Up and below line 8 × Dn represent up- and down-regulated genes by 8-fold.
Figure 1. Analysis of microarray data and comparison of 6688 gene expression levels between susceptible (LLMCK) and permethrin-selected (Arct2175FF) tarnished plant bugs using ArrayStar software. Scatter-plot comparison of 6688 gene expression levels between LLMCK and Arct2175FF. The mini squares of the scatter plot in the upper left corner represented up-regulated genes, and the squares in low right corner represented down-regulated genes. Squares above line 2 × Up and below line 2 × Dn represent up- and down-regulated genes by 2-fold; Squares above line 4 × Up and below line 4 × Dn represent up- and down-regulated genes by 4-fold; Squares above line 8 × Up and below line 8 × Dn represent up- and down-regulated genes by 8-fold.
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Figure 2. Variable number of up-regulated genes associated with each biological process in permethrin-selected tarnished plant bug.
Figure 2. Variable number of up-regulated genes associated with each biological process in permethrin-selected tarnished plant bug.
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Figure 3. Variable number of up-regulated genes associated with each molecular function in permethrin-selected tarnished plant bug.
Figure 3. Variable number of up-regulated genes associated with each molecular function in permethrin-selected tarnished plant bug.
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Table 1. Identification of 187 metabolic-enzyme-coding genes showing significantly up-regulated (≥2-fold) gene expressions in Arct2175FF resistant population using microarrays and analyzed with ArrayStar and Blat2go protocols (https://www.blast2go.com (accessed on 1 April 2023)).
Table 1. Identification of 187 metabolic-enzyme-coding genes showing significantly up-regulated (≥2-fold) gene expressions in Arct2175FF resistant population using microarrays and analyzed with ArrayStar and Blat2go protocols (https://www.blast2go.com (accessed on 1 April 2023)).
Sequence IDLength bpFold IncreaseFold p ValueEnzyme Up-RegulatedSimilarity e ValueSequence IDLength bpFold IncreaseFold p ValueEnzyme Up-RegulatedSimilarity e Value
LL_3387102.3481.18 × 10−6ATPase1.48 × 10−113LL_9534352.1971.16 × 10−5Oxidase8.30 × 10−80
LL_716562.1434.57 × 10−3Dehydrogenase1.19 × 10−16LL_9544082.3699.09 × 10−5Oxidase4.67 × 10−62
LL_65493554.8952.35 × 10−7Dehydrogenase1.46 × 10−29LL_9634055.5882.37 × 10−6Oxidase2.95 × 10−11
LL_56314615.122.47 × 10−7Dehydrogenase9.61 × 10−28LL_9877022.251.45 × 10−6Oxidase4.50 × 10−117
LL_23704888.1852.02 × 10−7Dehydrogenase1.34 × 10−20LL_10212802.2853.95 × 10−5Oxidase2.82 × 10−35
LL_17554818.1821.85 × 10−7Dehydrogenase1.75 × 10−30LL_10224095.4184.87 × 10−7Oxidase4.72 × 10−19
LL_46703737.5051.94 × 10−7Dehydrogenase9.76 × 10−30LL_15984972.1561.91 × 10−6Oxidase1.52 × 10−100
LL_1875195.7994.71 × 10−7Dehydrogenase1.71 × 10−57LL_16174672.2113.13 × 10−5Oxidase8.67 × 10−89
LL_7195005.7561.93 × 10−7Dehydrogenase1.38 × 10−57LL_16934962.3421.54 × 10−5Oxidase6.26 × 10−13
LL_48983595.5143.75 × 10−7Dehydrogenase7.74 × 10−36LL_17354902.9741.07 × 10−6Oxidase2.09 × 10−20
LL_29434283.831.16 × 10−6Dehydrogenase4.45 × 10−40LL_17712453.2239.50 × 10−7Oxidase2.54 × 10−11
LL_40425783.5764.76 × 10−7Dehydrogenase3.96 × 10−43LL_18192952.72.68 × 10−6Oxidase1.13 × 10−27
LL_3355753.0824.74 × 10−7Dehydrogenase2.85 × 10−21LL_18903432.687.02 × 10−6Oxidase2.14 × 10−14
LL_24784922.9796.94 × 10−7Dehydrogenase1.19 × 10−23LL_18982612.0661.92 × 10−6Oxidase8.39 × 10−25
LL_23895382.9581.59 × 10−6Dehydrogenase2.95 × 10−30LL_1918864.047.38 × 10−7Oxidase2.00 × 10−6
LL_25034022.4221.02 × 10−6Dehydrogenase2.00 × 10−16LL_19292922.0958.86 × 10−6Oxidase5.33 × 10−9
LL_503992.3451.95 × 10−5Dehydrogenase2.92 × 10−24LL_20582622.6651.17 × 10−6Oxidase3.50 × 10−8
LL_18815252.1484.29 × 10−5Dehydrogenase1.86 × 10−16LL_22034077.43.36 × 10−7Oxidase4.99 × 10−19
LL_36783752.1242.36 × 10−5Dehydrogenase3.60 × 10−20LL_23133939.7522.11 × 10−7Oxidase1.08 × 10−13
LL_36763493.9261.20 × 10−6Dehydrogenase9.11 × 10−5LL_23634092.6022.94 × 10−6Oxidase8.88 × 10−11
LL_8902497.2892.36 × 10−5Dehydrogenase6.32 × 10−12LL_37341054.8041.74 × 10−6Oxidase1.30 × 10−2
LL_24174145.0582.58 × 10−7Dehydrogenase3.62 × 10−11LL_44485542.9524.06 × 10−6Oxidase1.51 × 10−33
LL_2588503.6354.24 × 10−5Dehydrogenase1.31 × 10−35LL_45015132.4874.79 × 10−6Oxidase1.58 × 10−10
LL_23074492.8691.75 × 10−6Dehydrogenase4.63 × 10−11LL_49953982.7431.29 × 10−6Oxidase3.25 × 10−29
LL_2606072.1812.27 × 10−6Dehydrogenase9.19 × 10−21LL_50185652.431.46 × 10−5Oxidase5.18 × 10−103
LL_23195392.1223.50 × 10−6Dehydrogenase9.17 × 10−22LL_54392533.0973.68 × 10−6Oxidase1.00 × 10−6
LL_16454807.0341.81 × 10−7Dehydrogenase4.69 × 10−19LL_55484924.2894.86 × 10−7Oxidase3.00 × 10−20
LL_16763086.3199.62 × 10−7Dehydrogenase6.00 × 10−18LL_57103742.9933.52 × 10−6Oxidase6.58 × 10−14
LL_363726.0512.63 × 10−7Dehydrogenase1.68 × 10−19LL_60544222.2152.33 × 10−6Oxidase5.45 × 10−85
LL_7273445.9712.34 × 10−7Dehydrogenase1.47 × 10−15LL_61225334.1153.18 × 10−7Oxidase4.26 × 10−20
LL_11543025.382.63 × 10−7Dehydrogenase2.05 × 10−18LL_61574572.3973.52 × 10−6Oxidase3.41 × 10−13
LL_16083167.1078.33 × 10−6Dehydrogenase7.11 × 10−14LL_61884212.2663.79 × 10−6Oxidase5.96 × 10−33
LL_30084357.7211.88 × 10−7Dehydrogenase1.26 × 10−33LL_33596407.7112.58 × 10−7P4506.38 × 10−45
LL_23814237.7113.07 × 10−7Dehydrogenase5.22 × 10−44LL_66498152.5581.75 × 10−6Phosphatase2.65 × 10−10
LL_9676217.6522.18 × 10−7Dehydrogenase2.18 × 10−42LL_30275502.2213.14 × 10−6Phosphatase2.15 × 10−31
LL_10972547.5622.71 × 10−7Dehydrogenase1.74 × 10−11LL_27635272.2671.39 × 10−5Phosphatase1.44 × 10−19
LL_619359.2396.79 × 10−7Dehydrogenase5.15 × 10−59LL_44884952.1214.24 × 10−5phosphodi-Est2.25 × 10−83
LL_9815252.1823.05 × 10−5Dehydrogenase3.82 × 10−26LL_4274652.0613.38 × 10−4Reductase1.18 × 10−15
LL_54464966.8141.85 × 10−7Dehydrogenase2.47 × 10−16LL_3045812.0611.13 × 10−4Reductase4.82 × 10−25
LL_49564816.7893.11 × 10−7Dehydrogenase3.44 × 10−16LL_57114352.6342.36 × 10−6Reductase3.16 × 10−21
LL_3065622.7424.62 × 10−5Dehydrogenase3.11 × 10−33LL_56585203.262.94 × 10−6Reductase2.62 × 10−19
LL_45114412.5871.65 × 10−6Dehydrogenase6.26 × 10−32LL_569140411.4871.97 × 10−7Reductase3.76 × 10−22
LL_5064462.2011.60 × 10−6Dehydrogenase4.44 × 10−32LL_4318275.1815.38 × 10−7Reductase8.17 × 10−21
LL_27734992.0468.38 × 10−6Dehydrogenase1.51 × 10−33LL_15182863.2351.92 × 10−6Reductase5.50 × 10−6
LL_46903777.1512.79 × 10−7Dehydrogenase3.48 × 10−23LL_43172763.5771.33 × 10−6Reductase5.70 × 10−23
LL_16802186.5741.75 × 10−7Dehydrogenase2.87 × 10−7LL_17143712.2191.80 × 10−6Reductase6.14 × 10−4
LL_19213256.9533.06 × 10−7Dehydrogenase2.06 × 10−33LL_17195765.2519.41 × 10−7Reductase1.26 × 10−22
LL_6906233.5114.40 × 10−7Dehydrogenase4.43 × 10−95LL_28545845.2281.18 × 10−6Reductase3.79 × 10−22
LL_6593272.0252.51 × 10−6Dehydrogenase4.66 × 10−40LL_2262704.3661.05 × 10−6Synthase8.24 × 10−17
LL_36357162.3417.77 × 10−7Dehydrogenase5.90 × 10−43LL_14033083.7334.11 × 10−7Synthase1.89 × 10−14
LL_22444716.4484.15 × 10−7Esterase3.05 × 10−14LL_12132403.1194.80 × 10−6Synthase2.52 × 10−19
LL_25205576.4441.99 × 10−7Esterase7.53 × 10−31LL_58106613.055.47 × 10−7Synthase7.02 × 10−80
LL_12333174.6691.73 × 10−6Esterase1.52 × 10−51LL_4078362.9941.46 × 10−6Synthase1.49 × 10−80
LL_27703684.6282.68 × 10−7Esterase5.28 × 10−72LL_16206772.7131.35 × 10−6Synthase3.32 × 10−76
LL_2236684.4684.99 × 10−7Esterase7.12 × 10−45LL_20333502.6772.95 × 10−6Synthase8.22 × 10−26
LL_39796123.7116.19 × 10−7Esterase2.48 × 10−52LL_61737862.4848.39 × 10−7Synthase2.66 × 10−79
LL_51046102.027.61 × 10−6Esterase1.06 × 10−139LL_2066482.4483.48 × 10−6Synthase6.41 × 10−59
LL_46695492.291.73 × 10−5GST1.60 × 10−30LL_54962342.3843.67 × 10−6Synthase3.11 × 10−24
LL_44344552.0742.00 × 10−3GST2.75 × 10−24LL_16355742.3512.10 × 10−6Synthase1.32 × 10−60
LL_8924124.922.25 × 10−7GST1.06 × 10−13LL_16386102.3462.63 × 10−6Synthase8.66 × 10−68
LL_2944422.362.75 × 10−6GST1.14 × 10−23LL_16554162.2749.01 × 10−7Synthase2.37 × 10−50
LL_22583694.4297.33 × 10−7GST2.49 × 10−37LL_2272742.2661.45 × 10−6Synthase2.51 × 10−29
LL_617292.2245.51 × 10−6Oxidase3.14 × 10−124LL_2253672.2651.40 × 10−6Synthase1.94 × 10−46
LL_952442.0041.01 × 10−5Oxidase1.98 × 10−32LL_9713262.2253.03 × 10−6Synthase3.48 × 10−40
LL_968132.1551.09 × 10−5Oxidase5.78 × 10−130LL_16395272.2094.76 × 10−6Synthase2.20 × 10−51
LL_985462.2984.25 × 10−6Oxidase8.49 × 10−91LL_23494246.7532.12 × 10−7Synthase2.37 × 10−21
LL_993502.1461.20 × 10−5Oxidase2.53 × 10−55LL_49894156.551.96 × 10−7Synthase1.87 × 10−21
LL_1002132.6288.97 × 10−6Oxidase1.02 × 10−14LL_65894326.4831.90 × 10−7Synthase2.52 × 10−21
LL_1013222.0491.72 × 10−5Oxidase4.20 × 10−34LL_24553002.1082.71 × 10−6Synthase4.31 × 10−36
LL_1024072.4869.91 × 10−6Oxidase5.24 × 10−73LL_60284422.0941.91 × 10−6Synthase2.11 × 10−40
LL_1033702.4698.70 × 10−7Oxidase2.11 × 10−64LL_45525782.1223.22 × 10−6Synthase1.41 × 10−63
LL_1036492.3134.32 × 10−5Oxidase8.99 × 10−107LL_31714782.8014.90 × 10−5Synthase2.13 × 10−5
LL_1042182.6342.34 × 10−6Oxidase1.54 × 10−28LL_22915322.1279.48 × 10−6Synthase2.30 × 10−33
LL_1053282.4781.78 × 10−6Oxidase1.92 × 10−55LL_39284982.0753.37 × 10−6Synthase2.55 × 10−30
LL_1055282.411.23 × 10−5Oxidase6.10 × 10−91LL_234972.0734.67 × 10−6Synthase1.28 × 10−36
LL_1066682.4591.08 × 10−4Oxidase3.15 × 10−98LL_34063062.0687.08 × 10−6Synthase1.27 × 10−17
LL_1072482.8581.16 × 10−5Oxidase1.55 × 10−14LL_19974033.31.23 × 10−6ATPsynthase8.75 × 10−14
LL_1134632.1352.42 × 10−5Oxidase2.07 × 10−86LL_23475303.189.49 × 10−7Synthetase4.96 × 10−14
LL_1171922.246.59 × 10−6Oxidase6.00 × 10−8LL_7653252.6158.66 × 10−6Synthetase2.45 × 10−32
LL_2186972.2563.80 × 10−6Oxidase3.38 × 10−118LL_4332922.5051.11 × 10−5thio-Est1.25 × 10−9
LL_2195762.4611.60 × 10−5Oxidase6.78 × 10−92LL_21046777.3934.80 × 10−7thio-Est7.36 × 10−31
LL_2205572.4381.54 × 10−5Oxidase8.13 × 10−115LL_573242112.363.07 × 10−7transcriptase3.17 × 10−32
LL_2502752.0969.44 × 10−6Oxidase5.51 × 10−37LL_17535824.2564.15 × 10−6Transferase1.04 × 10−41
LL_3763282.5112.48 × 10−5Oxidase1.90 × 10−10LL_4715584.8184.37 × 10−7Transferase1.17 × 10−20
LL_3774862.5512.97 × 10−5Oxidase5.88 × 10−13LL_64793872.4697.50 × 10−6Transferase5.14 × 10−20
LL_4355622.9043.95 × 10−6Oxidase1.63 × 10−33LL_35453645.5852.56 × 10−7Transferase7.38 × 10−9
LL_6546412.7113.35 × 10−5Oxidase1.60 × 10−112LL_60903935.3772.64 × 10−7Transferase8.82 × 10−9
LL_6574315.2413.69 × 10−7Oxidase5.75 × 10−19LL_3943322.8037.51 × 10−7Transferase5.19 × 10−19
LL_7003836.3221.84 × 10−7Oxidase1.69 × 10−11LL_59886387.097.10 × 10−7Transferase1.77 × 10−13
LL_9463112.2483.56 × 10−6Oxidase1.98 × 10−46LL_55623912.4419.49 × 10−7Transferase5.31 × 10−12
LL_9476992.314.61 × 10−5Oxidase5.95 × 10−114LL_5797742.4151.14 × 10−5Transferase3.81 × 10−36
LL_9496852.43.75 × 10−5Oxidase1.90 × 10−113LL_3185802.0423.11 × 10−6Transferase1.83 × 10−34
LL_9505972.2681.17 × 10−6Oxidase8.80 × 10−109LL_38642872.3331.01 × 10−6Translocase2.40 × 10−38
LL_9515202.4514.96 × 10−6Oxidase5.72 × 10−91
Table 2. Identification of 114 metabolic-enzyme-coding genes showing significantly down-regulated (≥2-fold) gene expressions in Arct2175FF resistant population using microarrays and analyzed with ArrayStar and Blat2go protocol (https://www.blast2go.com (accessed on 1 April 2023)).
Table 2. Identification of 114 metabolic-enzyme-coding genes showing significantly down-regulated (≥2-fold) gene expressions in Arct2175FF resistant population using microarrays and analyzed with ArrayStar and Blat2go protocol (https://www.blast2go.com (accessed on 1 April 2023)).
Seq IDLength bpFold DecreaseFold p ValueEnzyme Down-RegulatedSimilarity e ValueSeq IDLength bpFold DecreaseFold p ValueEnzyme Down-RegulatedSimilarity e Value
LL_8206302.2611.16 × 10−5ATPsynthase5.8232 × 10−36LL_52554266.9921.83 × 10−7Hydrolase1.13622 × 10−36
LL_1317582.2132.32 × 10−5ATPsynthase1.427 × 10−34LL_39627636.7374.45 × 10−7Hydrolase3.50134 × 10−73
LL_3626342.2092.30 × 10−5ATPsynthase5.1568 × 10−36LL_30856313.0742.82 × 10−4Hydrolase1.07472 × 10−63
LL_530883816.1891.15 × 10−4ATPsynthase0LL_48016622.6757.52 × 10−5Hydrolase1.09695 × 10−81
LL_16575992.41.31 × 10−5ATPsynthase2.0737 × 10−35LL_816552.1898.69 × 10−5Hydrolase1.20116 × 10−80
LL_51094132.4037.15 × 10−6ATPsynthase7.7674 × 10−39LL_21735843.0733.68 × 10−6Hydrolase6.88239 × 10−60
LL_551543315.491.87 × 10−6ATPsynthase7.9528 × 10−52LL_63885115.8475.86 × 10−4Hydrolase4.00172 × 10−45
LL_212564516.0451.50 × 10−4ATPsynthase1.037 × 10−149LL_52243599.6984.73 × 10−6Oxidase4.18565 × 10−50
LL_26716514.2311.73 × 10−5ATPsynthase8.547 × 10−62LL_7594482.8041.72 × 10−6Oxidase1.89888 × 10−52
LL_6655303.6443.39 × 10−6ATPsynthase4.9619 × 10−47LL_7915622.9318.69 × 10−7Oxidase2.55893 × 10−55
LL_33155533.4328.29 × 10−7ATPsynthase1.7271 × 10−36LL_36053684.2753.64 × 10−6Oxidase4.26515 × 10−50
LL_171044624.7325.39 × 10−7ATPsynthase8.6728 × 10−82LL_5476842.0916.76 × 10−5Oxidase1.95781 × 10−33
LL−7206994.475.35 × 10−7ATPase1.7367 × 10−62LL_5675493.9175.84 × 10−4Oxidase2.22528 × 10−19
LL_255454514.5864.02 × 10−7ATPase5.3234 × 10−20LL_57766155.3381.17 × 10−6Oxidase3.81699 × 10−34
LL_24185412.4383.03 × 10−6ATPase4.487 × 10−101LL_74644517.8191.87 × 10−7P4505.43569 × 10−29
LL_23377112.0337.42 × 10−5ATPase3.203 × 10−106LL_471128913.22.24 × 10−7P4505.23118 × 10−15
LL_38967414.8733.29 × 10−5ATPase2.145 × 10−132LL_302483412.9331.42 × 10−6P4501.55029 × 10−65
LL_52075952.2596.53 × 10−6ATPase6.9486 × 10−15LL_51338486.9251.83 × 10−7P4503.53153 × 10−68
LL_464758013.512.29 × 10−6ATPase6.6458 × 10−23LL_55262426.4631.96 × 10−7P4503.28538 × 10−5
LL_566560816.923.05 × 10−6Dehydrogenase3.6376 × 10−79LL_46075612.2711.06 × 10−5P4501.24796 × 10−42
LL−75648915.6371.14 × 10−4Dehydrogenase5.933 × 10−99LL_38228522.0925.86 × 10−5P4507.78634 × 10−54
LL_48894143.677.38 × 10−7Dehydrogenase9.9234 × 10−30LL_6027506.511.99 × 10−7P4501.92189 × 10−86
LL_337840019.9037.01 × 10−6Dehydrogenase3.7909 × 10−41LL_46525948.3622.18 × 10−7P4501.13525 × 10−46
LL_384743216.8371.67 × 10−6Dehydrogenase4.9207 × 10−59LL_45106764.2594.38 × 10−6P4501.76105 × 10−43
LL_66104946.8131.11 × 10−6Dehydrogenase4.0672 × 10−61LL_186989511.0181.59 × 10−5P4506.25503 × 10−97
LL_57748410.5934.94 × 10−7Dehydrogenase2.3462 × 10−97LL_40675273.5241.07 × 10−6Peroxidase2.14959 × 10−68
LL_520548935.0977.93 × 10−7Dehydrogenase9.053 × 10−45LL_25336785.7962.33 × 10−6Phosphate synthase7.8801 × 10−81
LL_605152224.2571.17 × 10−6Dehydrogenase1.1249 × 10−44LL_47245693.0011.30 × 10−6Reductase/Peptidase2.53791 × 10−66
LL_234075312.2151.62 × 10−5Dehydrogenase8.624 × 10−148LL_2684402.0827.69 × 10−6Reductase/Peptidase2.5354 × 10−42
LL_44677582.0043.99 × 10−6Dehydrogenase4.0349 × 10−51LL_561388210.0582.94 × 10−6Reductase/Peptidase3.3655 × 10−134
LL_378672413.9532.99 × 10−4Dehydrogenase1.718 × 10−82LL_37954214.7882.01 × 10−4Reductase4.80605 × 10−35
LL_2665772.2583.83 × 10−6Dehydrogenase5.5356 × 10−42LL_319263632.8611.02 × 10−4Reductase1.13827 × 10−84
LL_343667010.4944.49 × 10−7Dehydrogenase1.3348 × 10−56LL_539150122.7228.77 × 10−7Reductase5.91618 × 10−36
LL−66646636.3773.27 × 10−5Dehydrogenase5.0621 × 10−45LL_56483332.4291.73 × 10−6Reductase1.39958 × 10−37
LL_29796552.2782.60 × 10−6Dehydrogenase1.4154 × 10−38LL_44204672.4094.83 × 10−4Reductase4.50782 × 10−23
LL−56671518.1713.05 × 10−6Dehydrogenase8.2028 × 10−79LL_23587225.5339.06 × 10−7Reductase6.72123 × 10−60
LL−34366711.4213.59 × 10−4Dehydrogenase2.51 × 10−128LL_2029893.3714.49 × 10−7Reductase2.685 × 10−117
LL_32978464.1336.27 × 10−7Dehydrogenase1.668 × 10−149LL_36005912.2562.75 × 10−5Reductase6.34142 × 10−81
LL_390139722.2581.41 × 10−6Dehydrogenase3.1323 × 10−34LL_517260812.7811.48 × 10−5Reductase2.30481 × 10−8
LL_37985022.5411.68 × 10−6Dehydrogenase5.2771 × 10−98LL_36145839.6785.35 × 10−7Transferase2.08268 × 10−51
LL_35114513.3342.06 × 10−6Dehydrogenase8.5979 × 10−12LL_325756010.4759.42 × 10−6Transferase7.80857 × 10−66
LL_17074907.0333.80 × 10−7Dehydrogenase8.0481 × 10−28LL_28556916.4242.71 × 10−6Transferase4.25986 × 10−36
LL_53627783.0715.35 × 10−6Dehydrogenase5.9194 × 10−81LL_35776586.5812.99 × 10−7Transferase1.00583 × 10−60
LL_57245442.0545.44 × 10−6Dehydrogenase2.8814 × 10−37LL_60526695.9693.22 × 10−5Transferase2.22505 × 10−67
LL_7137394.586.67 × 10−5Dehydrogenase1.094 × 10−112LL_562941717.0123.67 × 10−7Transferase4.18095 × 10−18
LL_6997885.9952.68 × 10−3Esterase0LL_61264612.4923.95 × 10−7Transferase2.42378 × 10−32
LL_25088644.1721.03 × 10−6Esterase9.7275 × 10−60LL_39866392.741.58 × 10−5Transferase4.9962 × 10−26
LL_40104422.2767.49 × 10−7Esterase7.7999 × 10−15LL_64045032.3852.71 × 10−6Transferase2.58015 × 10−9
LL_65227724.7112.07 × 10−5Esterase5.4832 × 10−60LL_284644423.1127.11 × 10−7Transferase8.4084 × 10−64
LL_21938113.4243.58 × 10−4Esterase2.19 × 10−60LL_23506263.1072.23 × 10−6Transferase1.41107 × 10−22
LL_2274222.861.95 × 10−6Esterase2.9057 × 10−8LL_50505372.6611.20 × 10−6Transferase7.62917 × 10−90
LL_62846765.8389.42 × 10−7GST1.4326 × 10−98LL_22248255.4412.30 × 10−7Transferase6.54044 × 10−41
LL_67161517.4625.11 × 10−6GST9.2649 × 10−41LL_66303353.9373.54 × 10−6Transferase2.36292 × 10−21
LL_1424224.1712.82 × 10−6GST1.8419 × 10−35LL_236551518.721.71 × 10−6Transferase3.40881 × 10−20
LL_48476252.1586.43 × 10−6GST1.2083 × 10−46LL_338881315.7974.11 × 10−6Transferase1.64364 × 10−25
LL_66035323.9311.84 × 10−6GST1.6255 × 10−25LL_8031263.4013.03 × 10−6Transferase1.11026 × 10−10
LL_176888027.8162.92 × 10−6Hydrolase1.2626 × 10−80LL_7324013.845.48 × 10−7Transferase1.32524 × 10−67
Table 3. Up-regulation is shown for Arct2175FF and relevant genes’ major roles in metabolic pathways (KEGG analysis www.blast2go.com (https://www.blast2go.com (accessed on 1 April 2023)).
Table 3. Up-regulation is shown for Arct2175FF and relevant genes’ major roles in metabolic pathways (KEGG analysis www.blast2go.com (https://www.blast2go.com (accessed on 1 April 2023)).
PathwaySeqs in PathwaySeqs of EnzymeSequence IDEnzymeEnzyme ID
Oxidative phosphorylation6837LL_95, LL_96, LL_98, LL_99, LL_100, LL_101, LL_102, LL_103, LL_104, LL_105, LL_106, LL_107, LL_218, LL_219, LL_220, LL_250, LL_946, LL_947, LL_949, LL_950, LL_951, LL_953, LL_954, LL_987, LL_1021, LL_1598, LL_1617, LL_1819, LL_1898, LL_1929, LL_5018, LL_6054, LL-61, LL-103, LL-105, LL-113, LL-654oxidaseec:1.9.3.1
Oxidative phosphorylation6823LL_36, LL_61, LL_258, LL_260, LL_727, LL_890, LL_967, LL_981, LL_1097, LL_1154, LL_1608, LL_1645, LL_1676, LL_1680, LL_1921, LL_2307, LL_2319, LL_2381, LL_2417, LL_2943, LL_3008, LL_4690, LL-690reductase (H+-translocating)ec:1.6.5.3
Oxidative phosphorylation682LL_50, LL_2389dehydrogenaseec:1.6.99.3
Oxidative phosphorylation684LL_435, LL_2313, LL_4448, LL_4995reductaseec:1.10.2.2
Oxidative phosphorylation681LL_1997ATPaseec:3.6.3.6
Oxidative phosphorylation681LL_3027diphosphataseec:3.6.1.1
Glutathione metabolism11LL_2258transferaseec:2.5.1.18
Drug metabolism—cytochrome P45011LL_2258transferaseec:2.5.1.18
Metabolism of xenobiotics by cytochrome P45011LL_2258transferaseec:2.5.1.18
Table 4. Down-regulation is shown for Arct2175FF and relevant genes’ major roles in metabolic pathways (KEGG analysis www.blast2go.com (https://www.blast2go.com (accessed on 1 April 2023)).
Table 4. Down-regulation is shown for Arct2175FF and relevant genes’ major roles in metabolic pathways (KEGG analysis www.blast2go.com (https://www.blast2go.com (accessed on 1 April 2023)).
PathwaySeqs in PathwaySeqs of EnzymeSequence IDEnzymeEnzyme ID
Glutathione metabolism41LL_577dehydrogenase (NADP+)ec:1.1.1.42
Glutathione metabolism41LL_5224glutathione peroxidaseec:1.11.1.12
Glutathione metabolism42LL_4067, LL_5224peroxidaseec:1.11.1.9
Glutathione metabolism41LL_6284transferaseec:2.5.1.18
Oxidative phosphorylation242LL_791, LL-759oxidaseec:1.9.3.1
Oxidative phosphorylation242LL_3847, LL_6610dehydrogenase (ubiquinone)ec:1.3.5.1
Oxidative phosphorylation243LL_268, LL_4724, LL_5613reductaseec:1.10.2.2
Oxidative phosphorylation2412LL_131, LL_820, LL_1657, LL_1710, LL_2125, LL_2671, LL_3315, LL_5109, LL_5308, LL_5515, LL-362, LL-665ATPaseec:3.6.3.6
Oxidative phosphorylation245LL_3378, LL_4889, LL_5665, LL-379, LL-756reductase (H+-translocating)ec:1.6.5.3
Drug metabolism—other enzymes11LL_2533phosphoribosyltransferaseec:2.4.2.10
Drug metabolism—cytochrome P45011LL_6284transferaseec:2.5.1.18
Metabolism of xenobiotics by cytochrome P45011LL_6284transferaseec:2.5.1.18
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Zhu, Y.-C.; Du, Y.; Yao, J.; Liu, X.F.; Wang, Y. Detect Cytochrome C Oxidase- and Glutathione-S-Transferase-Mediated Detoxification in a Permethrin-Resistant Population of Lygus lineolaris. Toxics 2023, 11, 342. https://0-doi-org.brum.beds.ac.uk/10.3390/toxics11040342

AMA Style

Zhu Y-C, Du Y, Yao J, Liu XF, Wang Y. Detect Cytochrome C Oxidase- and Glutathione-S-Transferase-Mediated Detoxification in a Permethrin-Resistant Population of Lygus lineolaris. Toxics. 2023; 11(4):342. https://0-doi-org.brum.beds.ac.uk/10.3390/toxics11040342

Chicago/Turabian Style

Zhu, Yu-Cheng, Yuzhe Du, Jianxiu Yao, Xiaofen F. Liu, and Yanhua Wang. 2023. "Detect Cytochrome C Oxidase- and Glutathione-S-Transferase-Mediated Detoxification in a Permethrin-Resistant Population of Lygus lineolaris" Toxics 11, no. 4: 342. https://0-doi-org.brum.beds.ac.uk/10.3390/toxics11040342

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