A Preliminary Study on the Resistance Mechanism of Pleurotus ostreatus to Mitigate the Impact of Insecticides

Abstract

Pleurotus ostreatus cultivation is often affected by pest infestations, which contaminate the bag by eating nutrients and mycelium. This contamination eventually leads to a decline in the quality and yield of edible mushrooms and affects farmers’ income. Therefore, pesticides are commonly used for pest control. To examine the impact of insecticides on the growth of P. ostreatus, this study quantified the activities of antioxidant enzymes, including catalase (CAT), peroxidase (POD), superoxide dismutase (SOD), and phenylalanine deaminase (PAL), in the mushroom under different insecticide treatments. Additionally, transcriptome sequencing was performed to investigate the underlying regulatory mechanisms. The findings indicated that dinotefuran, diflubenzuron, chlorantraniliprole, and beta-cypermethrin treatments resulted in a significant reduction in catalase and peroxidase activities in P. ostreatus. Conversely, the application of beta-cypermethrin and chlorantraniliprole significantly enhanced PAL and SOD activities in the mycelium. PAL activity was significantly increased in all the mixed substrates, whereas only spray treatments with diflubenzuron resulted in a significant increase in PAL activity. SOD activity in the substrates was reduced by diflubenzuron in the mixed treatment and chlorantraniliprole in the spray treatment. In contrast, all other treatments resulted in a significant increase in SOD activity in the substrates. Transcriptome sequencing revealed that differential genes were predominantly enriched in valine, leucine, and isoleucine degradation, fatty acid degradation, tyrosine metabolism, ascorbate and aldarate metabolism, and histidine metabolism, among others. These biological processes are hypothesized to be involved in the growth regulatory effects of insecticides on the mycelium and ascospores of P. ostreatus. The reliability of the transcriptomic data was also validated through quantitative real-time polymerase chain reaction.

1. Introduction

Pleurotus ostreatus is classified within the Agaricales and the family Pleurotaceae [1]. A simple and efficient cultivation technique has been developed for P. ostreatus, resulting in a relatively short cycle time and a high nutritional value [2]. It is one of the most widely cultivated varieties in China. The total output of edible mushrooms in China reached 43.3604 million tonnes in 2023. However, the cultivation of P. ostreatus is frequently infested by pests such as Collembola, Diptera, and Araneae [3]. The larvae of these pests bore into the culture material of the mushroom bag and feed on the mycelium, resulting in the appearance of yellow fecal matter. This contamination hinders the development of the mushroom, ultimately leading to reduced quality and a 20–30% yield reduction of edible mushrooms [4], as well as affecting the profitability of mushroom growers. Pesticide control represents a commonly used approach for managing these pests. However, pesticide use exposes P. ostreatus to a range of abiotic stresses [5].

Changes in the activity of defense enzymes are one of the most important indicators of plant defense responses. Catalase (CAT), an antioxidant enzyme, serves as a biomarker of oxidative stress due to its ability to protect the structure and function of biomolecules [6]. Peroxidase (POD) has the dual role of eliminating the toxicity of hydrogen peroxide and facilitating the oxidation of phenols and amines [7]. Superoxide dismutase (SOD) plays a vital role in cellular protection, plant growth and development, and protection against adversity stress [8]. Phenylalanine deaminase (PAL) is an important class of immune resistance enzymes in plants [9]. In this study, we analyzed the effects of different insecticide treatments on the activities of antioxidant enzymes (CAT, POD, SOD, and PAL) in P. ostreatus to further elucidate the mechanisms by which P. ostreatus responds to abiotic stress and to provide a theoretical basis for its production.

Insecticides have been shown to affect the growth of P. ostreatus, but the specific regulatory mechanisms remain unclear [10]. Transcriptome analysis uses high-throughput sequencing or microarray technology to study all transcript characteristics in specific samples under specific states, with the core of revealing the selective activation and transformation of genomic genetic information [11]. Transcriptome sequencing and biological analyses can help to study related genes and elucidate molecular mechanisms. Transcriptomic analysis shows that 226 genes of Phellinus linteus, an edible and medicinal mushroom, are upregulated and 370 genes are downregulated under light, demonstrating how light is involved in signaling pathway regulation [12]. Additionally, whole-genome sequencing studies of Lentinus edodes and Hericium erinaceus have been carried out in response to abiotic stresses such as high temperature, salinity, and drought [13,14]. Many previous studies have used transcriptomics to investigate pesticide resistance in pests, but relatively few have been applied to edible fungi [15,16].

In the present study, we used transcriptome sequencing to analyze the differentially expressed genes and related pathways in the mycelium and fruiting bodies of the P. ostreatus under different insecticide treatments. The objective was to preliminarily uncover the mechanism by which insecticides regulate the growth of P. ostreatus, thereby providing a theoretical basis for the functional development of the related genes in this species.

2. Materials and Methods

2.1. Materials

The test strain was Pleurotus ostreatus, which was provided by the Jiangsu Key Laboratory for Horticultural Crop Genetic Improvement, Institute of Vegetable Crop, Jiangsu Academy of Agricultural Sciences. The culture medium was potato dextrose agar (PDA) solid medium, purchased from Biochem Co. (Shanghai, China), and the cottonseed husk culture substrate was composed of 84% (w/w) cottonseed husk, 15% (w/w) wheat bran, and 1% (w/w) lime powder, with a water content of 65% (w/w). The test agents comprised formulations containing the following active ingredients: 25% diflubenzuron wettable powder (WP, Shanxi Compose exploit Biological Technology Co., Taiyuan, China), 20% dinotefuran suspension concentrate (SC, Jiangsu Sword Agrochemicals Co., Nanjing, China), 20% chlorantraniliprole suspension concentrate (SC, Anyang Ruipu Agrochemical Co., Anyang, China), and 10% beta-cypermethrin suspension concentrate (SC, Jiangsu Gongcheng Biotechnology Co., Nanjing, China). For mycelium collection, the concentration of each of the four agents was 500 mg/L, whereas, for fruiting body collection, the concentration was increased to 1000 mg/L.

The assay kits for determining enzymatic activities were purchased from Nanjing Mofan Biotechnology Co., Ltd. (Nanjing, China). The specific kits used were as follows: Peroxidase (POD, Cat# PMHA1-M96); Catalase (CAT, Cat#PMHA2-M96); Superoxide Dismutase (SOD, Cat# PMHA4-M96); and Phenylalanine Ammonia-Lyase (PAL, Cat# PMHA9-M96). RNA extraction was performed using the Hi-Pure Polysaccharide Polyphenol Plant Total RNA Kit (TSP0202) from Tsingke Biotechnology Co., Ltd. (Nanjing, China).

2.2. Experimental Design

For mycelium collection, PDA powder was added to four pre-prepared pesticide solutions, each of which had an active ingredient concentration of 500 mg/L, to prepare solid media. The mixture was poured into 90 mm Petri dishes (20 mL per dish). Activated P. ostreatus strains were then inoculated onto the plates using a 5 mm cork borer and incubated at 25 °C for 15 days until full mycelial coverage was achieved. A control group was set up using medium with distilled water. Each treatment was replicated three times, with three plates per replicate. Then, 0.5 g of mycelium from each treatment was collected into 5 mL cryotubes, flash-frozen in liquid nitrogen, and stored at −80 °C [17]. The designations of the treatment groups are provided in

Table 1. Designations of experimental treatments in the mycelial and fruiting body collection trials.

	Test Agent	25% Diflubenzuron (WP)	20% Dinotefuran (SC)	20% Chlorantraniliprole (SC)	10% Beta-Cypermethrin (SC)	Distilled Water
Experimental Treatment
Mycelium collection		HC	HF	HL	HG	HCK
Fruiting body collection—Mixing		MC	MF	ML	MG	MCK
Fruiting body collection—Spraying		AC	AF	AL	AG	ACK

.

Fruiting body collection involved mixing and spraying treatment methods. Aqueous solutions of the four test agents were prepared at an active ingredient concentration of 1000 mg/L using distilled water. The solutions were mixed with cottonseed hull substrate according to the formulation to achieve a moisture content of 65%. Polyethylene bags (3 cm × 13 cm × 26 cm) were filled with 570 g of the mixed substrate per bag. Each treatment included three replicates with 15 bags per replicate. A control group was prepared by adding distilled water to the substrate instead of agent solutions. Substrates were sterilized (121 °C, 2 h), aseptically inoculated, and colonized at 26 ± 1 °C in darkness. Fruitbody management at 16 ± 1 °C and 95% RH under darkness and low CO₂ conditions was conducted, with only the first flush harvested for experimental analysis [18]. The designations of each treatment group are listed in Table 1.

In the spray treatment, the cottonseed hull substrate was mixed with distilled water. Post-inoculation, mycelial cultivation and fruiting management procedures were consistent with those used in the mixing treatment. After full mycelial colonization and primordia formation, the bags were opened and uniformly sprayed with the test agents prepared at a concentration of 1000 mg/L. A control group was sprayed with distilled water. Samples (0.5 g) from each treatment were collected into 5 mL cryotubes, flash-frozen in liquid nitrogen, and stored at −80 °C for subsequent analysis. The designations of all treatment groups are provided in Table 1.

2.3. Effect of Insecticides on Enzyme Activities Associated with P. ostreatus

The samples of mycelium containing 500 mg/L and fruiting bodies containing 1000 mg/L of insecticide active ingredient were collected, wiped clean of water and impurities, cut into pieces, and put into a mortar and pestle with the addition of liquid nitrogen. The samples were ground into powder, accurately weighed, and extracted using a tissue crusher in an ice bath at 8000 g. The homogenate was centrifuged at 4 °C for 10 min, and the supernatant was collected and kept on ice to be measured. Kits for CAT, POD, SOD, and PAL were used to determine enzyme activity. Enzyme activity assays were strictly performed according to the manufacturer’s instructions of the assay kits. The data were analyzed using SPSS version 26.0 and plotted using Origin 2024. The threshold for statistical significance was set at p < 0.05.

2.4. Transcriptome Sequencing Analysis

Total RNA was extracted following the kit protocol, and its quality was assessed using an Epoch BioTek microplate reader (BioTek Instruments, Inc., Winooski, VT, USA). RNA samples meeting quality standards were used to construct a common mRNA-seq library. Preliminary quantification of the established library was performed using Qubit 3.0, and quantitative polymerase chain reaction (qPCR) was used to provide accurate quantification of the effective concentration of the library. This study evaluates the randomness of mRNA fragmentation, mRNA integrity, and data sufficiency by analyzing the genomic distribution of inserted fragments, their length dispersion, and library saturation. Sequencing was performed using the Illumina Hi Seq sequencing platform in PE150 mode. The raw image data files obtained from the Illumina Hi Seq were converted into raw data via CASAVA Base Calling analysis. Sequencing quality control was then conducted to acquire high-quality, validated sequencing data, and the resulting clean reads were aligned to the reference genome using Hisat2—this step yielded positional information of the reads on the reference genome or genes, as well as sample-specific sequence characteristics, for subsequent analyses. The reference genome was sourced from the National Center for Biotechnology Information (NCBI) under Taxonomy ID 5322.

2.5. Enrichment Analysis of Differentially Expressed Genes (DEGs) in P. ostreatus

Fragments per kilobase of transcript per million fragments mapped (FPKM) was used as a measure of transcript or gene expression level. Differential analysis was performed using edge R, with screening criteria set at Fold Change ≥ 2 and false discovery rate (FDR) < 0.01. The Gene Ontology database was used to classify DEGs into molecular function, cellular component, and biological process. Pathway significance enrichment analysis was performed by selecting the top 20 pathways with the most significant (smallest) q-value in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database based on the pathway unit.

2.6. qRT-PCR Verification

To further verify the accuracy of the transcriptome sequencing results, five DEGs from the mycelium and seven of the shared DEGs from the fruiting bodies were selected for qRT-PCR analysis. Primer design was conducted using Primer-BLAST from the NCBI website (https://www.ncbi.nlm.nih.gov/tools/primer-blast/, accessed on 15 September 2024), and the designed primers were synthesized by Beijing Prime Biotechnology Co. (Beijing, China). The relative expression levels of each gene were calculated using the 2^−ΔΔCT method, with actin used as the internal reference gene. The primer sequences are presented in

Table 2. Primers for qRT-PCR of differentially expressed genes.

Gene ID	Primer Sequence (5′-3′) F	Primer Sequence (5′-3′) R
PC9H_000946	ACATGCCTCTGACTGTCGTG	GCACCACCGTCCTTCTTGTA
PC9H_001669	GCTGGGAGCAGTACACCTTT	TTCCCACCACGGTTAAGCTC
PC9H_006010	TCAAGCGTGCTACCGATGTT	TTCCCACCACGGTTAAGCTC
PC9H_005162	TCGAAAAGATCCCCACACCG	TTCACGAGAACTACCGCACC
PC9H_008699	GCAGACAAGATCACCGGACA	TCCAAGGGATGATTTGGCCC
PC9H_000924	ATCCGTCGTTGGCAGAGTTT	TTCCGTGGTTTCATCGAGGG
PC9H_008783	GGCACGGTTTTCATGCTGTT	GGTCCAAAGGTCCCTCACAG
PC9H_005235	TAGTCGCCTATTCCAACGCC	CTCTGATACCAGGGCTGTGC
PC9H_002076	AAGAGATCTTTGGGCCGGTG	GCATGAGCTACTCGCAAAGC
PC9H_004133	CAGCGTCGAAAGAAGACCCT	CTTCTTGAGCCATGCCCTGA
PC9H_008358	TCCTGGGGCCATGATGAGTA	CGGTGCCATGGGTAGAAACT
PC9H_001143	TCGGCGGTTTATCTACGCTC	CATGCCTTTGTTTGGTGGGG
actin	TCCGTCTGGATTGGTGGTTC	AAGCACTCTGCGACTCCATC

.

3. Results

3.1. Effect of Insecticides on Enzyme Activity of P. ostreatus

The results of enzyme activities in the mycelial and fruiting body stages of P. ostreatus are presented in Figure 1. Pesticides exert a certain inhibitory effect on the mycelial growth of Pleurotus ostreatus (Figure S1). At concentrations of 500 mg/L in the mycelium and 1000 mg/L in the fruiting bodies of the active ingredient, beta-cypermethrin and chlorantraniliprole significantly increased CAT activity in the mycelium of P. ostreatus. In contrast, the four insecticide treatments decreased CAT activity during the fruiting bodies stage of P. ostreatus. PAL activity was significantly increased in the mycelium of P. ostreatus by beta-cypermethrin and chlorantraniliprole, while diflubenzuron showed no significant effect. In the fruiting bodies, PAL activity was significantly increased by all four insecticide treatments in the mixed cultivation. However, under spray treatment, only diflubenzuron significantly increased the PAL activity in the fruiting bodies.

Dinotefuran, beta-cypermethrin, and chlorantraniliprole increased POD activity in mycelium, and all four insecticide treatments increased POD activity in fruiting bodies. Under spray treatment, only diflubenzuron decreased POD activity in ascospores. Beta-cypermethrin and chlorantraniliprole increased SOD activity in the mycelium. In the fruiting bodies, SOD activity was reduced by diflubenzuron in the mixed treatment and chlorantraniliprole in the spray treatment. In the fruiting bodies, SOD activity was significantly increased by all other treatments.

3.2. Quality Analysis of Transcriptome Sequencing Data

Five mycelium samples yielded 35.59 Gb of data, with more than 95.10% Q30 bases. Nine fruiting body samples produced 57.69 Gb of data, with over 90.83% Q30 bases. The GC content was approximately 52% for each sample.

Statistical Results of DEGs

The gene expression levels in P. ostreatus mycelium and fruiting bodies changed significantly under different treatments (Figure 2). At the mycelial stage, 1914 DEGs were screened in the HC treatment group compared with the control, of which 1159 were upregulated and 755 were downregulated (Figure 2A). In the HF treatment group, 1772 DEGs were screened, of which 936 were upregulated and 836 were downregulated. The HG treatment group yielded 1400 DEGs, of which 836 were upregulated and 564 were downregulated. The HL treatment yielded 1661 DEGs, of which 986 were upregulated and 675 were downregulated (Figure 2A).

At the fruiting bodies stage, 3374 DEGs were identified in the MC treatment group compared with the control, of which 1835 were upregulated and 1539 were downregulated (Figure 2B). In the MF treatment group, 4709 DEGs were screened, of which 2409 were upregulated and 2300 were downregulated. In the MG treatment group, 2897 DEGs were screened, of which 1446 were upregulated and 1451 were downregulated. The ML treatment group yielded 2779 DEGs, of which 1540 were upregulated and 1239 were downregulated. In the AC treatment group, 4113 DEGs were identified compared with the control, of which 2266 were upregulated and 1847 were downregulated. The AF treatment group yielded 2982 DEGs, of which 1687 were upregulated and 1295 were downregulated. In the AG treatment group, 3598 DEGs were identified, of which 1970 were upregulated and 1628 were downregulated. In the AL treatment group, 3194 DEGs were screened, of which 1707 were upregulated and 1487 were downregulated (Figure 2B).

The results showed that the number of differentially expressed genes (DEGs) in P. ostreatus changed significantly under different treatments compared to the water control (Figure 3). Among the four treatment agents, diflubenzuron induced the greatest number of DEGs in the mycelium (Figure 3A). At the fruiting bodies stage, the mixing treatment with dinotefuran caused the highest number of DEGs (Figure 3B). In the spray treatment, the highest number of DEGs was caused by diflubenzuron (Figure 3C). The expression levels based on DEGs effectively distinguish the different treatment groups, indicating that the samples in each group showed different expression patterns.

3.3. Venn Analysis Results

The DEGs in the mycelium of the CK group were compared to those in the other groups treated with the four test agents using Venn analysis (Figure 4). The results identified 213 shared DEGs, including 96 upregulated genes and 117 downregulated genes. It was hypothesized that these genes were related to the influence of the test agent on P. ostreatus mycelial growth. Among them, upregulated genes included gene-PC9H_001669, gene-PC9H_006010, and gene-PC9H_000946 and downregulated genes included gene-PC9H_008699 and gene-PC9H_005162.

The DEGs in the fruiting bodies of the CK group and four treatment groups were analyzed using Upset plot (Figure 5). The results showed that there were 413 shared DEGs, including 210 upregulated genes and 203 downregulated genes. These genes were related to the influence of the test agent on the growth of P. ostreatus fruiting bodies. The shared upregulated genes included gene-PC9H_000924, gene-PC9H_008783, gene-PC9H_005235, gene-PC9H_002076, and gene-PC9H_004133 and the downregulated included gene-PC9H_008358 and gene-PC9H_001143.

3.4. Functional Enrichment Analysis of DEG

To understand the enrichment pathways of DEGs in edible mushrooms in response to insecticide exposure, the genes were functionally annotated using the Gene Ontology (GO) database (Table S1). GO enrichment analyses of differential genes in each treatment group were performed separately, and the results were categorized into biological process, cellular component, and molecular function.

In the comparison between PO_HC and CK, 1171 differential genes were annotated (Figure 6A). Within the biological process category, there was significant enrichment in the DNA catabolic process, cellular amino acid biosynthetic process, and alpha-amino acid metabolic process. In the cellular component processes, significant enrichment was found in the cell wall, intracellular part, and organelle. In the molecular function category, significant enrichment was found in oxidoreductase activity, nucleotide binding, and tetrapyrrole binding.

In the comparison between PO_HF and CK, 1011 differential genes were annotated (Figure 6B). Within the biological process category, there was significant enrichment in cellular detoxification, positive regulation of DNA binding, and cellular amino acid metabolic process. In the cellular component category, DEGs were significantly enriched in the intrinsic component of membrane, rough endoplasmic reticulum membrane, and cell wall. In the molecular function category, DEGs were significantly enriched in oxidoreductase activity and structural molecules.

In the comparison between PO_HG and CK, 804 DEGs were annotated (Figure 6C). In the biological process category, these genes were significantly enriched in cellular detoxification, glutathione metabolic process, and tRNA aminoacylation for protein translation. In the cellular components, DEGs were significantly enriched in the intrinsic component of membrane, cell wall, and plasma membrane. In the molecular function category, DEGs were significantly enriched in oxidoreductase.

In the comparison between PO_HL and CK, 945 DEGs were annotated (Figure 6D). In the biological process category, DEGs were significantly enriched in cellular detoxification, ergosterol metabolic process, and microtubule metabolic process. In the cellular component domain, enrichments were observed in intracellular non-membrane-bound organelle and cell wall. In the molecular function category, there were significant enrichments in antioxidant activity, catalytic activity, and oxidoreductase activity.

In the PO_MC vs. CK comparison, 1895 DEGs were annotated (Figure 7A). These DEGs were enriched in the biological processes of ion transmembrane transport, amino acid transport, and cellular detoxification. In the cellular components category, they were enriched in the intrinsic component of membrane and cell periphery. Regarding molecular function, significant enrichment was observed in oxidoreductase activity, nucleotide binding, and hydrolase activity.

In the comparison between PO_MF and CK, 2771 DEGS were annotated (Figure 7B). These DEGs were significantly enriched in biological processes, including the small-molecule metabolic process, organic acid metabolic process, and carboxylic acid metabolic process. In the cellular component category, significant enrichment was observed in the intracellular organelle, organelle, and intracellular membrane-bound organelle. In the molecular function category, there was significant enrichment in catalytic activity, oxidoreductase activity, and nucleoside phosphate binding.

In the PO_MG vs. CK comparison, 1596 DEGs were annotated (Figure 7C). There was significant enrichment in biological processes of alpha-amino acid metabolic process, cellular respiration, and hexose metabolic process. In the cellular component category, enrichments included the intrinsic component of membrane, mitochondrion, and proton-transporting two-sector ATPase complex. In the molecular function category, significant enrichments were observed in nucleotide binding, structural molecule activity, and DNA-binding transcription factor activity.

In the PO_ML vs. CK comparison, 1549 DEGs were annotated (Figure 7D). DEGs were significantly enriched in the biological process of aminoglycan metabolic process, amino acid transport, and RNA phosphodiester bond hydrolysis. In the cellular component domain, there were significant enrichments in the intrinsic component of the membrane, ribonucleoprotein complex, and preribosome. In the molecular function category, DEGs showed significant enrichment in protein binding, nucleotide binding, and structural molecule activity.

In the PO_AC vs. CK comparison, 2403 DEGs were annotated (Figure 8A). These genes were significantly enriched in the biological processes of the cell cycle, DNA repair, and cellular component assembly. In the cellular component category, significant enrichment was observed in the cell, cell part, and intracellular cellular component. For molecular function, DEGs were significantly enriched in oxidoreductase activity, structural molecule activity, and monooxygenase activity.

In the comparison between PO_AF and CK, 1647 DEGs were annotated (Figure 8B). DEGs were significantly enriched in the biological processes of purine-containing compound metabolic process, purine-containing compound biosynthetic process, and purine nucleotide biosynthetic process. For the cellular component, there was significant enrichment in the intrinsic component of the membrane, cell, and cell part. For molecular function, significant enrichment was observed in structural molecule activity, oxidoreductase activity, and nucleotide binding.

In the PO_ AG vs. CK comparison, 2091 DEGs were annotated (Figure 8C). These genes showed significant enrichment in biological processes of monocarboxylic acid metabolic process, cellular detoxification, and carbohydrate derivative catabolic process. For the cellular component category, significant enrichment was found in the intrinsic component of the membrane, intracellular organelle, and organelle. For molecular functions, significant enrichment was found in catalytic activity, oxidoreductase activity, and nucleotide binding.

In the PO_AL vs. CK comparison, 1797 DEGs were annotated and were significantly enriched in biological processes involving the oxidation–reduction process, ion transmembrane transport, and detoxification (Figure 8D). For the cellular component, there were significant enrichments in the intrinsic component of the membrane, cell part, and intracellular. For the molecular function category, there were significant enrichments in oxidoreductase activity, nucleotide binding, and structural molecule activity.

3.5. KEGG Pathway Enrichment Analysis

KEGG pathway functional enrichment analysis was performed for DEGs from the mycelium and ascospores of P. ostreatus under different insecticide treatments to explore their functional role. In PO_HC vs. CK treatment, there were 345 genes annotated to 103 metabolic pathways (Figure 9A). The top 20 KEGG-enriched pathways, ranked by ascending q-value, included biosynthesis of cofactors, pantothenate and CoA biosynthesis, glycerolipid metabolism, fatty acid degradation, and ascorbate and aldarate metabolism.

In the PO_HF vs. CK comparison, 261 genes were annotated to 101 metabolic pathways (Figure 9B). The most significantly enriched pathways, in order of increasing q-value, included from smallest to largest, were nitrogen metabolism, arachidonic acid metabolism, cysteine and methionine metabolism, ascorbate and aldarate metabolism, and pyruvate metabolism.

For the PO_HG vs. CK comparison, 217 genes were annotated to 94 metabolic pathways (Figure 9C). In order of ascending q-value, the most significant pathways included aminoacyl-tRNA biosynthesis, penicillin and cephalosporin biosynthesis, D-arginine and D-ornithine metabolism, valine, leucine, and isoleucine biosynthesis, and arginine and proline metabolism.

For the PO_HL vs. CK comparison, 237 genes were annotated to 97 metabolic pathways (Figure 9D). In descending order according to q-value, the most significant pathways included steroid biosynthesis, biosynthesis of amino acids, glutathione metabolism, histidine metabolism, and tryptophan metabolism.

In PO_MC vs. CK comparison, 514 genes were annotated in 109 metabolic pathways (Figure 10A). The most significant pathways, in descending order of q-value, included glycerolipid metabolism, pyruvate metabolism, sulfur metabolism, glycosphingolipid metabolism, sulfur metabolism, glycosphingolipid biosynthesis, and MAPK signaling pathway—yeast.

In the PO_MF vs. CK treatment comparison, 893 genes were annotated to 117 metabolic pathways (Figure 10B). The top enriched pathways, in ascending order of the q-value, included glycolysis/gluconeogenesis, steroid glycolysis/gluconeogenesis, steroid biosynthesis, DNA replication, arginine and proline metabolism, and mismatch repair.

For the PO_MG vs. CK comparison, 474 genes were annotated in 105 metabolic pathways (Figure 10C). The chief pathways, ranked by descending q-value, included oxidative phosphorylation, carbon metabolism, glyoxylate and dicarboxylate metabolism, amino sugar and nucleotide sugar metabolism, and phenylalanine metabolism.

In the PO_ML vs. CK comparison, 410 genes were annotated to 103 metabolic pathways (Figure 10D). The top pathways, ordered by q-value from smallest to largest, included ribosome, MAPK signaling pathway—yeast, ascorbate and aldarate metabolism, folate biosynthesis, and fructose and mannose metabolism.

In the PO_AC vs. CK treatment comparison, 767 genes were annotated to 114 metabolic pathways (Figure 11A). The top enriched pathways, ranked by q-value, included ribosome, mismatch repair, pentose and glucuronate interconversions, and steroid biosynthesis.

In the PO_AF vs. CK comparison, 481 genes were annotated to 112 metabolic pathways (Figure 11B). The top pathways, in descending order of q-value, included oxidative phosphorylation, valine, leucine, and isoleucine degradation, fatty acid degradation, sphingolipid metabolism, and MAPK signaling pathway—yeast.

In the PO_AG vs. CK treatment, 625 genes were annotated to 112 metabolic pathways (Figure 11C). The most enriched pathways, in descending order of q-value, included fatty acid degradation, peroxisome, pentose and glucuronate interconversions, pyruvate metabolism, and valine, leucine, and isoleucine degradation.

In the PO_AL vs. CK comparison, 526 genes were annotated to 109 metabolic pathways (Figure 11D). The most significant pathways, in order of ascending q-value, included oxidative phosphorylation, valine, leucine, and isoleucine degradation, beta-alanine metabolism, fatty acid degradation, and sphingolipid metabolism.

3.6. qRT-PCR Validation of Transcriptomic Data

To validate the RNA-Seq data of P. ostreatus insecticide stress, 12 genes were selected for qRT-PCR analysis, with five genes chosen from the mycelium and seven from the fruiting bodies sharing DEGs (

Table 3. Statistics of gene information on Pleurotus ostreatus in response to insecticide stress.

Gene ID	Name	Length (bp)	Function	GenBank ID
PC9H_000946	SAM2	1484	Cysteine and methionine metabolism	PV690236
PC9H_001669	ADH1_1	1687	Glycolysis/gluconeogenesis	PV690235
PC9H_006010	SAH1	1843	Cysteine and methionine metabolism	PV690234
PC9H_005162	LEU1	2685	Valine, leucine, and isoleucine biosynthesis	PV690238
PC9H_008699	ALD5_3	2033	Glycolysis/gluconeogenesis	PV690237
PC9H_000924	TRP1	1483	Tryptophan metabolism	PV690239
PC9H_008783	GAL1	2042	Galactose metabolism	PV690240
PC9H_005235	FAD1	981	Fatty acid degradation	PV690243
PC9H_002076	GLY1	2226	Glycolysis/gluconeogenesis	PV690242
PC9H_004133	GPMT1	911	Glycerophospholipid metabolism	PV690245
PC9H_008358	ALD1	1219	Ascorbate and aldarate metabolism	PV690244
PC9H_001143	CDC25	1372	MAPK signaling pathway—yeast	PV690241

). In the mycelium, gene-PC9H_001669, gene-PC9H_006010, and gene-PC9H_000946 were upregulated, while gene-PC9H_008699 and gene-PC9H_005162 were downregulated (Figure 12A). In the fruiting bodies, gene-PC9H_000924, gene-PC9H_008783, gene-PC9H_005235, gene-PC9H_002076, and gene-PC9H_004133 were upregulated, while gene-PC9H_008358 and gene-PC9H_001143 were downregulated (Figure 12B,C). These findings were consistent with the RNA-Seq results, indicating that the transcriptome data was highly accurate.

4. Discussion

Under pesticide stress, mushrooms produce ROS, and the ascorbate and aldarate metabolism pathway maintains cellular homeostasis by scavenging ROS, which supports pesticide tolerance or degradation in mushrooms [19]. Enzymes such as APX may play a key role in the detoxification process. Ascorbic acid may be involved as a cofactor in regulating the activity of certain oxidoreductases (POD) in fungi that have been shown to degrade pesticides [20]. This study found that the activities of almost all antioxidant enzymes, including CAT, POD, SOD, and PAL, increased during the mycelial growth stage to reduce the damage caused by insecticides to the P. ostreatus. Chlorantraniliprole, a novel diamide insecticide, exhibited potent induction of multiple enzymatic activities in P. ostreatus mycelium. This phenomenon may be attributed to its interference with calcium ion homeostasis or activation of the MAPK signaling pathway, thereby indirectly triggering antioxidant defense systems [21]. In contrast, the neonicotinoid dinotefuran and benzoylurea diflubenzuron demonstrated inhibitory effects on CAT and POD activities, which might stem from their disruption of energy metabolism or direct enzymatic inhibition [22]. The results indicated that Pleurotus ostreatus (oyster mushroom) enhances the activity of its own antioxidant enzymes to scavenge reactive oxygen species (ROS), thereby alleviating insecticide-induced damage or adapting to environmental stress.

The authors’ previous study found that high concentrations of insecticides inhibit the growth of mycelium and fruiting bodies of P. ostreatus, with the inhibition rate on mycelia reaching 14.39%, but the underlying mechanisms had not been explored [23]. GO enrichment analysis revealed significant enrichment of ergosterol metabolism in P. ostreatus mycelium under chlorantraniliprole exposure. As ergosterol is a critical component of fungal cell membranes, this finding suggests that the insecticide may induce oxidative stress by compromising membrane integrity, thereby activating antioxidant-related genes. Concurrently, KEGG pathway analysis of the HL treatment group showed pronounced enrichment in steroid biosynthesis and glutathione metabolism, indicating that mycelia mitigate stress through enhanced antioxidant metabolism (glutathione synthesis) and membrane homeostasis restoration [24]. Previous studies have demonstrated the pivotal role of glutathione biosynthesis in antioxidant defense and xenobiotic detoxification. Long-term exposure via substrate-mixing (MF) markedly activated basal metabolism and detoxification pathways in P. ostreatus fruiting bodies. For instance, dinotefuran-treated substrate triggered gene enrichment in small molecule metabolism and carboxylic acid metabolic pathways. KEGG analysis further identified activated glycolysis/gluconeogenesis and steroid biosynthesis pathways, suggesting that mycelia counteract systemic pesticide stress by augmenting energy metabolism. In contrast, spray applications (AC) under acute localized exposure preferentially activated DNA repair and cell cycle regulation mechanisms. MAPK signaling pathways, known to regulate transcriptional responses through diverse transcription factors, were implicated in developmental processes across fungal species, including early morphogenesis in Hypsizygus marmoreus, primordium formation in Lentinula edodes, and fruiting body development in Pleurotus eryngii [25,26]. Notably, KEGG enrichment of mismatch repair and non-homologous end-joining pathways in sprayed samples implies direct DNA damage or replication interference as potential mechanisms for mycelial growth inhibition. Gene regulatory networks in fruiting bodies exhibited distinct profiles compared to mycelia. Substrate-mixed MC treatment activated transmembrane ion transport and amino acid transporter genes, whereas sprayed AC treatment enriched cell-cycle-related pathways. These findings highlight developmental-stage-specific responses; fruiting body maturation relies on nutrient transport systems vulnerable to pesticide permeation, while cellular division processes are susceptible to chemical disruption.

Experimental validation confirmed a high concordance between qRT-PCR and transcriptomic data. The expression trends of genes involved in amino acid synthesis (gene-PC9H_000946) and energy metabolism (gene-PC9H_006010, gene-PC9H_000946, and gene-PC9H_008699) corroborated the data’s reliability. The results suggest that Pleurotus ostreatus may activate multiple detoxification and defense mechanisms in response to insecticide stress. Genes involved in glycolysis/gluconeogenesis (e.g., PC9H_001669 and PC9H_008699) likely provide energy support; those associated with amino acid metabolism (e.g., PC9H_000946 and PC9H_005162) and lipid degradation (PC9H_005235) may contribute to toxin neutralization and cellular repair, while the MAPK signaling pathway gene (PC9H_001143) and ascorbate metabolism gene (PC9H_008358) potentially play key roles in regulating stress response and mitigating oxidative stress.

Among the shared DEGs in the mycelium, 96 upregulated genes were predominantly associated with stress responses, while 117 downregulated genes were mainly involved in basic metabolism. This indicates that pesticides may affect mycelial growth through a “metabolic suppression-defense activation” dual strategy. In fungi exposed to heavy metals, the concentrations of valine, leucine, and isoleucine decrease [27]. Amino acids are important for regulating osmotic stress and plant cell wall growth [28]. These findings provide a theoretical basis for understanding the molecular toxicity mechanisms of pesticides in edible fungi. This approach can be applied to other edible fungi to analyze changes in defensive enzyme activities in mycelium and fruiting bodies. It can also be used to study the molecular mechanisms after treatment with different concentrations of insecticides. This will deepen the understanding of the self-defense strategies and adaptive mechanisms of edible fungi under insecticide stress.

5. Conclusions

This study reveals stage-specific insecticide responses in P. ostreatus. In mycelia, certain treatments elevated antioxidant activities (CAT and SOD), while fruiting bodies showed inhibited catalase but induced PAL and peroxidase. Transcriptomics indicated mycelial sensitivity to diflubenzuron, enriching cell wall and oxidoreductase pathways, suggesting chitin disruption. Fruiting bodies responded to dinotefuran with glycolysis/DNA replication perturbations and to spray-applied diflubenzuron via ribosomal dysregulation. Core conserved DEGs highlighted amino acid metabolism and MAPK signaling as key stress-response networks across stages.

Functional enrichment further delineated stage-specific adaptation strategies; mycelia prioritized detoxification metabolism and cell wall repair, whereas fruiting bodies engaged in energy metabolism reprograming and developmental signaling. qRT-PCR validation confirmed strong concordance between transcriptional profiles and expression trends of genes implicated in cysteine-mediated pesticide degradation and glycolytic pathways, corroborating dataset reliability. Collectively, this work deciphers molecular mechanisms underlying pesticide toxicity in edible fungi and establishes a theoretical framework for rational pesticide application in mushroom cultivation. This study deciphers stage-specific molecular responses of P. ostreatus to insecticide stress, revealing that mycelia enhance antioxidant and cell wall repair pathways, while fruiting bodies reprogram energy and developmental signaling. These insights provide a theoretical basis for rational pesticide use in mushroom cultivation and identify key genetic targets for developing stress-resistant strains. Future work should focus on field validation and practical integration of these strategies to improve agricultural sustainability.