The Effects of Hypoxic Stress on the Growth and Lignocellulose-Degrading Capacity of Pleurotus ostreatus

Abstract

To achieve synchronous regulation of growth and lignocellulose degradation in Pleurotus ostreatus (PO-01) during fungal residue biorefining, we systematically evaluated O₂ gradients (5%, 20%, 40%) and N₂/CO₂ regarding mycelial development, lignocellulose degradation, and bioethanol potential. A total of 20% O₂ emerged as the critical threshold, balancing mycelial growth (which was faster than that under 5% O₂) and lignocellulose degradation (with lignin degradation rate reaching 15.29%). Metabolomics identified 53 aromatic derivatives related to lignin degradation, with their abundance correlating with actual lignin degradation rates. Meanwhile, it clarified the synergistic degradation mechanism and bioinformatics characteristics of key lignin-degrading enzymes and confirmed the AA9 gene associated with cellulose degradation at the molecular level. Measurements of polysaccharide content and ethanol yield revealed that the 20% O₂ environment led to a remarkably high ethanol yield of 101.90 L·ha⁻¹. In contrast, 5% and 40% O₂ concentrations not only reduced the polysaccharide content but also inhibited bioethanol production, highlighting O₂ as a crucial factor in regulating the synergy between growth and degradation. After comprehensive analysis, this study designated 20% O₂ as the optimal parameter for the integrated biorefining of fungal residues, offering a gas-phase solution to overcome industrial bottlenecks in biofuel production.

1. Introduction

Rapid global industrialization and urbanization have driven overreliance on fossil fuels, leading to severe air pollution and climate change. Amid growing energy demands and urgent sustainable development imperatives, bioethanol—a promising renewable energy source—has garnered significant attention. This bio-based alternative, intended to replace fossil fuels and waste plastics, embodies the sustainability of the bio-circular economy [1]. Bioethanol, derived from biomass, is more environmentally friendly than fossil fuels. It not only reduces greenhouse gas emissions but also helps alleviate the energy shortage problem. Typically, the production of bioethanol relies on food crops such as corn [2] and sugarcane [3]. However, this practice triggers food–energy competition, and large-scale monocropping risks environmental degradation. Thus, identifying alternative biomass feedstocks for bioethanol production is critical [4].

The production of biofuels from agro-forestry waste biomass, such as fungal residue, has long been a focus in the agricultural and environmental fields [5]. Fungal residue, one of the by-products from edible mushroom cultivation, was often discarded or incinerated in the past. This not only caused environmental pollution but also led to resource waste [6]. According to the data on the global edible fungi industry scale and distribution from 2020 to 2023 released by the China Edible Fungi Association, in 2021–2022 in the US, the total sales volume of mushroom crops was 702 million pounds, with a revenue of 1.02 billion dollars. The Netherlands, a major producer, has an annual output of about 300,000 metric tons. Poland’s edible mushroom industry is also notable, with an export volume of 280,000 metric tons in 2019. Meanwhile, China accounts for 70% of global output and produces about 6 million metric tons of fungal residues annually, making it key for agro-forestry waste biomass (fungal residues) utilization. Pleurotus ostreatus residue, with 40–60% organic matter post-harvest, provides polysaccharides and lignocellulose for first- and second-generation bioethanol, which is significant for resource recycling and environmental protection [7,8].

Lignocellulose, consisting of lignin, cellulose, and hemicellulose, possesses numerous functional groups and biodegradability. Lignin is divided into three types: guaiacyl lignin (G-lignin), syringyl lignin (S-lignin), and p-hydroxyphenyl lignin (H-lignin). Lignin creates a protective barrier around cellulose and hemicellulose, hindering enzymes from accessing and breaking down these polysaccharides [9]. As a white-rot fungus, P. ostreatus secretes extracellular enzymes (e.g., laccase, lignin peroxidase, manganese peroxidase) to decompose lignin, exposing cellulose and hemicellulose for degradation and improving conversion efficiency in saccharification and glucose fermentation into ethanol. Lytic polysaccharide monooxygenase (LPMO), a copper-dependent oxidase, oxidizes and cleaves crystalline polysaccharides in lignocellulose, providing more binding sites for glycoside hydrolases and enhancing degradation efficiency through synergy. In the CAZy database, LPMOs are classified into seven auxiliary activity (AA) families (AA9–AA11, AA13–AA16), with fungal AA9 being the core subfamily for cellulose degradation. AA9 oxidizes cellulose β-1,4 glycosidic bonds, and its gene expression is induced by lignocellulose substrates or environmental oxygen. Analyzing AA9’s molecular characteristics and regulatory mechanisms is critical for optimizing lignocellulose bioconversion [10,11,12,13].

The O₂ concentration and gas composition (CO₂, N₂) in the growth environment are crucial for the mycelial and fruiting body growth and metabolism of edible mushrooms. O₂, necessary for aerobic respiration, provides energy for growth and enzyme secretion. Increasing the O₂ concentration can accelerate mycelial growth and promote lignocellulose pyrolysis [14]. Moreover, gas components like CO₂ and N₂ also have a significant impact on the physiological activities of edible mushrooms. Research has revealed that high CO₂ concentration can restrain the stipe growth and sexual reproduction process of P. ostreatus [15].

Despite the potential of P. ostreatus-inoculated fungal residue for bioethanol production, the effects of O₂ concentration and gas composition on lignocellulose degradation and bioethanol yield remain unclear. Based on this, this study proposes the hypothesis that 20% O₂, as a critical threshold, can induce P. ostreatus to secrete lignocellulolytic enzymes under mild oxidation conditions. This serves as a survival mechanism to simultaneously promote mycelial growth and lignocellulose degradation, thereby enabling efficient bioethanol production. Conversely, a hypoxic (5% O₂) environment may inhibit enzyme production due to energy limitations, while a hyperoxic (40% O₂) environment may impede enzyme synthesis due to excessive oxidative stress. To test this hypothesis, this study sets the following objectives: (1) Identify strains, optimize culture conditions (pH, O₂, carbon/nitrogen sources) for activation and propagation, and select the optimal substrate type and ratio from 16 options. (2) Assess mycelial and fruiting body growth and eight agronomic traits under varying O₂ concentrations and gas compositions (CO₂, N₂). (3) Using metabolomics and bioinformatics, screen differential metabolites/pathways in lignin degradation and elucidate G/H/S-type lignin degradation mechanisms. (4) Validate the presence of the cellulose-degrading AA9 gene in strain PO-01 and characterize the structure/function of its expressed protein. (5) Evaluate lignin/cellulose/hemicellulose degradation rates in P. ostreatus-inoculated fungal residue and theoretical bioethanol yield.

2. Materials and Methods

2.1. Materials

2.1.1. Tested Strains

The tested PO-01 strain was collected by our research team in Jilin Province, China, in 2024, and our team was responsible for the isolation and purification of this strain. A part of the purified strain was used in this experiment, while the remaining strain was registered and preserved in the culture collection of the Engineering Research Center of Edible and Medicinal Fungi, Ministry of Education, Jilin Agricultural University.

2.1.2. Main Reagents and Instruments

Cryogenic High-throughput Tissue Grinder (Sakezi, Hefei, China, Model 48LR), PCR Amplifier (Heal Force, Shanghai, China, Model T960), Electrophoresis Apparatus (Dongfang Ruili, Beijing, China, Model DYY-300D), Ultra-micro Spectrophotometer (Quawell, Sunnyvale, CA, USA, Model Q5000), Automatic High-pressure Sterilizer (Zealway, Xiamen, China, Model GR85DA), Multiskan SkyHigh Microplate Spectrophotometer (Thermo Fisher Scientific, Shanghai, China, Model A51119500C), High-speed Centrifuge (Eppendorf, Shanghai, China, Model 5425 R), Vortex Mixer (Servicebio, Wuhan, China, Model MV-100), Constant Temperature/Oscillating Metal Bath (Novogene, Beijing, China, Model STP05), Illumination Incubator (CIMO, Shanghai, China, Model GZX-400BSH-III), N₂/CO₂/O₂ Gas Cylinder (Jilin Shengtai, Changchun, China, Model 40L), Gas Control Device (Peijia, Hangzhou, China, Model OMS-100A), and Single-row Single-control Three-hole Water Bath (Changzhou Guoyu, Changzhou, China, Model HH-3A).

Sodium Dodecyl Sulfate (SDS), Sodium Acetate (CH₃COONa), Ethylenediaminetetraacetic Acid (EDTA), Sodium Chloride (NaCl), Perchloric Acid (HClO4), Glacial Acetic Acid (C₂H₄O₂), Absolute Ethanol (C₂H₆O), Acetone (C₃H₆O), Concentrated Sulfuric Acid (H₂SO₄), and Phenol (C₆H₆O). All these chemical reagents were purchased from Tianjin Xinbote Chemical Co., Ltd. (Tianjin, China) and Tianjin Guangfu Technology Development Co., Ltd. (Tianjin, China).

2.1.3. Medium, Mushroom Cultivation Bags, and Sterilization Conditions

PDA (Potato Dextrose Agar) medium: Peeled potatoes 200 g, glucose 20 g, agar 15–20 g, distilled water 1000 mL, pH 6.0. Adjust the grams of each material proportionally according to the demand.

PDB (Potato Dextrose Broth) medium: Peeled potatoes 200 g, glucose 20 g, distilled water 1000 mL, pH 6.0. Calculate the grams of each component proportionally according to the demand.

Synthetic medium: Designed according to the different experimental protocols in Tables S1 and S2.

Cultivation medium: Prepared at a ratio of 55% water and 45% dry materials (the composition of dry materials is as shown in different experimental protocols in Tables S3 and S4).

Mushroom cultivation bags: Prepared at a ratio of 55% water and 45% dry materials (78% wood chips, 20% wheat bran, 1% lime, 1% gypsum).

Sterilization conditions: For sterilization, the high-pressure steam sterilization method was adopted. Specifically, the sterilization conditions for the medium were set as “121 °C for 30 min”, while the sterilization conditions for the mushroom cultivation bags were specified as “121 °C for 3 h”.

2.2. Methods

2.2.1. Isolation, Identification, and Phylogenetic Tree Construction of PO-01 Strain

Isolation of PO-01 Strain

The strain was isolated using the tissue isolation method. In a clean bench (operating voltage: 220 V, air velocity: 0.30–0.45 m/s) that had been sterilized by ultraviolet radiation for more than 30 min, the fruiting bodies were disinfected with 75% ethanol. A tissue block of approximately 0.5 cm × 0.5 cm was excised using a scalpel sterilized by high-pressure steam (121 °C for 30 min) and inoculated onto PDA medium. Subsequently, the cultures were incubated in a constant-temperature incubator (power: 1900 W, volume: 400 L, illuminance: 0–25,000 Lx) at 25 °C. Once white mycelia grew around the tissue block, the edge mycelia were immediately picked for purification and propagation. This process was repeated three times. Finally, purified mycelia were obtained and numbered as PO-01 for subsequent use.

Molecular Biological Identification and Construction of Phylogenetic Tree

Genomic DNA of PO-01 mycelia was extracted via the High Salt and Low pH Method [16]. Briefly, 0.5 g mycelia was placed in a 1.5 mL centrifuge tube, ground with a cryogenic grinder, then mixed with 1 mL 65 °C preheated extraction buffer (containing 1.4% SDS, 100 mmol/L sodium acetate, 50 mmol/L EDTA, 500 mmol/L NaCl) and incubated at 65 °C for 30 min. After centrifugation at 10,000× g for 10 min, 500 μL supernatant was mixed with 1.5 volumes of 2.5 mol/L potassium acetate (pH 4.8), incubated at 0 °C for 30 min, and centrifuged at 10,000× g (4 °C) for 10 min to precipitate proteins. Another 500 μL supernatant was mixed with 1.5 volumes of pre-chilled isopropanol (−20 °C, 0.5–2 h). The pellet was washed with 70% ethanol, air-dried, resuspended in 500 μL ddH₂O, and stored at −20 °C. Using the genomic DNA as a template, PCR amplification was performed with the universal fungal ITS primers ITS5 and ITS4. The total PCR reaction mixture volume was 25 μL. After verification by 1% agarose gel electrophoresis (70 V, 45 min), the target PCR products were excised from the gel and sent to Sangon Biotech (Shanghai) Co., Ltd. (Shanghai, China) for sequencing.

The obtained ITS sequences were assembled and edited using Sequencher software 5.4.5. After removing primer sequences and low-quality regions, the processed sequences were submitted to the NCBI database, and homology searches were conducted against known sequences using BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi, accessed on 21 October 2025). ITS sequences of related strains with high homology were downloaded. A phylogenetic tree was constructed using MEGA11 software with the Neighbor-Joining (NJ) method. Bootstrap analysis with 1000 replicates was performed to assess the reliability of tree branches, which clarified the phylogenetic relationship between this strain and other related strains. Based on these results and morphological analysis, PO-01 was identified as Pleurotus ostreatus.

2.2.2. Screening of Optimal Conditions for Activation and Propagation of PO-01 Strain

Single-Factor Experiment

To screen optimal conditions for PO-01 activation, propagation and cultivation, a single-factor design (four factors, five levels each) was used. Each group had six replicates (measuring longitudinal and transverse mycelial length) to test carbon sources, nitrogen sources, pH, and O₂ concentrations (five levels per factor in Table S1). For carbon/nitrogen sources, control groups (CK) without the respective nutrients were set; pH/O₂ had no extra CK, with groups serving as mutual controls. Following the single-variable principle (other parameters fixed per basic medium), activated PO-01 was inoculated into different media with the same inoculum size and cultured at an appropriate temperature. Mycelial length and density were measured regularly; cultivation ended when mycelia fully covered the medium, with results photographed.

Orthogonal Experiment

Based on the results of the previous single-factor experiment, three optimal levels were selected from the five levels of each factor to construct an orthogonal experiment with four factors and three levels [L₉(3⁴)]. Each group included six replicates (with measurements of both longitudinal and transverse mycelial length). The definitions of factors and levels, as well as the specific experimental protocols, are detailed in Table S2. This experiment aimed to clarify the degree of influence of each factor on mycelial growth rate and screen out the optimal combination of levels.

2.2.3. Screening of Optimal Culture Substrate and Its Ratio for Cultivation of PO-01 Strain

To screen PO-01’s optimal culture substrate, two single-factor experiments (16 groups total) were conducted. First, seven substrates (single or wood chip–wheat bran combinations) were tested, with “78% wood chips and 20% wheat bran” being optimal. Second, four wood chip–wheat bran ratios (all with 1% lime and 1% gypsum) were optimized, yielding “78% wood chips, 20% wheat bran, 1% lime, 1% gypsum” as best. Activated strains were inoculated into materials (same inoculum size, six replicates per group) and cultured under appropriate conditions. Mycelial length/density were monitored; cultivation ended when mycelia fully covered the medium, with results photographed (Table S3 for details).

2.2.4. Mycelia Cultivation Under Different O₂ Concentrations and Gas Compositions

The mycelia of the PO-01 strain were selected as experimental subjects. Initially, they were inoculated into PDA medium for strain activation. Subsequently, the activated mycelia were transferred to the cultivation medium to observe mycelial growth under varying oxygen (O₂) concentrations and gas compositions, with three to six replicates per group. The experiment on different O₂ concentrations was divided into three groups: the high-O₂ group (40% O₂), the low-O₂ group (5% O₂), and the normal-O₂ concentration group (Ctrl1). The experiment on different gas compositions was divided into five groups: the CO₂-only group (CO₂), the N₂-only group (N₂), the group with O₂ restored after 3-day CO₂ ventilation (FYCO₂), the group with O₂ restored after 3-day N₂ ventilation (FYN₂), and the normal air-ventilation group (Ctrl2) (Table S4).

During mycelia cultivation, a gas controller precisely regulated O₂/gas in sealed incubators, with a gas analyzer monitoring in real time. Aseptic operation prevented contamination. Daily mycelial growth was recorded; cultivation stopped when medium was covered, with length measured via cross-method to calculate growth rate.

2.2.5. Fruiting Body Cultivation Under Different Gas Compositions

In a clean bench, the activated PO-01 strain was inoculated into the mushroom cultivation bags prepared according to the ratio of 55% water and 45% dry materials (78% wood chips, 20% wheat bran, 1% lime, 1% gypsum) and sterilized. During the cultivation process, conditions such as temperature and humidity were strictly controlled. After the mycelia fully covered the bags, mushroom-fruiting management was carried out, with 5–6 repeated inoculations for each group. When the first-flush and second-flush mushrooms in the modeling groups (CO₂ group, N₂ group, Ctrl2 group) and the O₂-restoration groups (FYCO₂ group, FYN₂ group) were mature, morphometric parameters (cap length, cap width, cap thickness), yield components (biological efficiency, yield, water content), and petal number and pattern length (stipe length) were determined.

2.2.6. Analysis of Differential Metabolites and Metabolic Pathways of Mycelia

In this study, ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) was used to detect metabolites in mycelia. Five groups of mycelia samples of P. ostreatus were selected (CO₂ group, N₂ group, Ctrl2 group, FYCO₂ group, FYN₂ group). Three replicate samples were randomly collected from each group; differential metabolite analysis of the mycelia was carried out. Through detailed analysis of the up-/down-regulation patterns of differential metabolites and KEGG pathway enrichment across seven comparison groups (Ctrl vs. CO₂, Ctrl vs. FYCO₂, Ctrl vs. FYN₂, Ctrl vs. N₂, FYCO₂ vs. CO₂, FYN₂ vs. N₂, N₂ vs. CO₂), 53 aromatic derivatives associated with three lignin types [guaiacyl (G), p-hydroxyphenyl (H), and syringyl (S)] were identified. The value changes in their up-/down-regulation were statistically calculated. The up-/down-regulation profiles of 12 lignin-related metabolites were analyzed to elucidate the degradation pathway.

2.2.7. Determination of Lignocellulose Contents (Cellulose, Lignin, Hemicellulose) in P. ostreatus-Inoculated Residue

To evaluate the degradation ability of P. ostreatus mycelia on lignocellulose in residue during the growth process, we collected the remaining fungal residue after mycelia cultivation. The collected residues were crushed using a pulverizer (220 V, 550 W, 35,000 r/min, 50 Hz), then sieved through a 40-mesh sieve. The powdered residue samples were collected for subsequent experiments to determine the contents of three different lignocellulosic components. To assess the effect of O₂ concentration on the degradation of lignocellulose in fungal residue, the samples were divided into four groups, NO group, 40% O₂ group, 5% O₂ group, and Ctrl1 group, with three replicate experiments for each group. To evaluate the effect of different gas compositions on the degradation of lignocellulose in fungal residue, the samples were divided into six groups, the NO group, CO₂ group, N₂ group, FYCO₂ group, FYN₂ group, and Ctrl2 group, and each group also had three replicate experiments. Data are presented as mean ± standard error (SE) of three independent experiments.

Determination of the Percentage Content of Lignin

The phenolic hydroxyl groups in lignin are acetylated to yield acetylated lignin, which exhibits a characteristic absorption peak at 280 nm. Based on this property, an acetylation-based method was employed for the quantitative determination of lignin content; specific experimental procedures are shown in Table S16 [17] and combined with the aromatic derivatives of corresponding lignin types screened in the aforementioned metabolomics analysis to illustrate the impact of different gas conditions on lignin degradation.

Degradation Mechanisms of Four Lignin-Degrading Enzymes and Their Bioinformatics Analysis

To investigate the structure–function characteristics of lignin peroxidase (LiP, EC 1.11.1.14), manganese peroxidase (MnP, EC 1.11.1.13), laccase (Lac, EC 1.10.3.2), and versatile peroxidase (VP, EC 1.11.1.16), we retrieved and screened experimentally validated protein sequences from the model white-rot fungal organisms Sporotrichum pruinosum, Coriolus versicolor, and Pleurotus eryngii via the UNIPROT database (https://www.uniprot.org/, accessed on 21 October 2025). Based on the ProtParam module of the ExPASy proteomics platform (https://web.expasy.org/protparam/, accessed on 21 October 2025), systematic evaluations were performed on physicochemical parameters of the enzymes, including molecular weight, isoelectric point, and amino acid composition. SignalP 6.0 (https://services.healthtech.dtu.dk/services/SignalP-6.0/, accessed on 21 October 2025) was used for the prediction of cleavage sites of secretory signal peptides. Three-dimensional (3D) spatial conformations were constructed using the SWISS-MODEL homology modeling server (https://swissmodel.expasy.org/, accessed on 21 October 2025). Additionally, bioinformatics identification of N-linked glycosylation modification sites was conducted via NetNGlyc 1.0 (https://services.healthtech.dtu.dk/services/NetNGlyc-1.0/, accessed on 21 October 2025). Meanwhile, using the “Functional Protein Association Networks” module of the STRING database (https://cn.string-db.org/, accessed on 21 October 2025), a systematic protein–protein interaction network analysis was performed on three lignin-degrading enzymes—MnP, Lac, and VP—in the PC15 strain of P. ostreatus (NCBI: txid1137138).

Determination of the Percentage Content of Cellulose

The cellulose content was determined using the acid hydrolysis–anthrone method. Under acidic conditions, cellulose undergoes hydrolysis to β-D-glucose, which is subsequently dehydrated in a strongly acidic environment to form β-furfural derivatives. These derivatives further react with anthrone through dehydration–condensation to produce a blue–green chromogenic compound. It is detected that it has a characteristic absorption peak at 620 nm, and the cellulose content is calculated; specific experimental procedures are shown in Table S16 and Figure S3 [18].

Sequence Alignment of AA9 Genes in the LPMOS Gene Family and Bioinformatics Analysis of the Protein

For the AA9 protein sequence from the PC9 strain of P. ostreatus (GenBank: KAF7440563.1), the NCBI BLAST tool was used to align it with the experimentally validated protein sequence from S. pruinosum (GenBank: BAL43430.1), thereby preliminarily inferring the function of this protein. Based on the AA9 gene sequence of P. ostreatus available in NCBI (Gene ID: 59370750), primers were designed to preliminarily verify the presence of the corresponding AA9 gene in our sample PO-01 strain. Furthermore, using the ProtParam module of ExPASy (https://web.expasy.org/protparam/, accessed on 21 October 2025), SignalP 6.0, NetNGlyc 1.0, and the SWISS-MODEL homology modeling server, the physicochemical parameters of the protein (including molecular weight, isoelectric point, and amino acid composition) were evaluated. Meanwhile, the cleavage sites of secretory signal peptides and N-linked glycosylation modification sites were predicted, and its three-dimensional spatial conformation was constructed.

Determination of the Percentage Content of Hemicellulose

The hemicellulose content was determined using the DNS (3,5-dinitrosalicylic acid) colorimetric method. Hemicellulose was first acid-hydrolyzed to reduce sugars, which subsequently reacted with DNS reagent under alkaline conditions to form a reddish-brown chromogenic complex. It was detected that it had a characteristic absorption peak at 540 nm, and the hemicellulose content was calculated; specific experimental procedures are shown in Table S16 and Figure S4 [19].

2.2.8. Determination of Polysaccharide Content in P. ostreatus-Inoculated Residue and Analysis of Coupled Bioethanol Yield

In this section, the total polysaccharide content in P. ostreatus-inoculated residue was first extracted and determined using the phenol-sulfuric acid method (Figure S5): after crushing the fungal residue through a 40-mesh sieve, 1 g of residue dry powder was weighed. The water extraction and alcohol precipitation method (liquid–solid ratio of 40:1, water bath at 90 °C for 3 h, followed by precipitation with three volumes of 95% ethanol at 4 °C for 24 h) was utilized to extract total polysaccharides. Under the action of sulfuric acid, polysaccharides were hydrolyzed into monosaccharides, which were rapidly dehydrated to form furfural derivatives. These derivatives further reacted with phenol to generate an orange–yellow compound, and the sugar content in 1 g of fungal residue was calculated according to the experimental dilution factor [20].

Subsequently, the bioethanol yield was analyzed based on the two theoretical formulas in Table S16: referring to the research findings of the Japan Institute of Energy in 2006, the ethanol yields (unit: L·ha⁻¹) from the conversion of polysaccharides, cellulose, and hemicellulose in fungal residues to ethanol were calculated via the formulas, respectively. All data were expressed as mean ± standard error (SE) [21].

3. Results

3.1. Isolation, Identification, and Phylogenetic Tree Construction

The genomic DNA of the sample was extracted by the High Salt and Low pH Method. Then, a Quawell Q5000 ultramicro spectrophotometer was used to quantify and analyze the purity of the extracted DNA. The results showed a DNA concentration of 209.450 ng/μL, with A₂₆₀/A₂₈₀ and A₂₆₀/A₂₃₀ absorbance ratios of 1.905 and 1.832, respectively, indicating high DNA purity with minimal contamination and impurities and meeting the requirements of subsequent molecular biology experiments. Moreover, agarose gel electrophoresis analysis of the PCR amplification products showed a single, bright specific band for strain PO-01 between 500 bp and 750 bp, demonstrating that the ITS4/5 primers could efficiently and specifically amplify the ITS sequence fragment of this strain (Figure 1A).

The ITS sequence of sample PO-01 showed 99.83% similarity to P. ostreatus sequences (MG819739.1 and OP936994.1) in the NCBI database, with an E-value near zero. The full-length ITS sequence of PO-01 was 667 bp, and 585 bp after removing primer sequences and low-quality regions. Ten sequences with >99% similarity from NCBI were selected, and a phylogenetic tree of PO-01 was constructed using the Neighbor-Joining method in MEGA11. Based on the tree and morphological photos, PO-01 clustered with two P. ostreatus strains. In fruiting body morphology, it had a clustered distribution, milky-white fan-shaped to subcircular pilei with regular margins, and laterally attached stipes with adherent bases. These characteristics were consistent with the white phenotype of P. ostreatus, validating molecular identification results. Thus, the PO-01 strain was identified as Pleurotus ostreatus (Figure 1B,C).

3.2. Screening of Optimal Conditions, Culture Substrates, and Ratios for Strain Activation, Propagation, and Cultivation

3.2.1. Single-Factor Experiments for Strain Activation and Propagation

Based on mycelial growth measurements and image analysis, P. ostreatus grew better in neutral-to-slightly alkaline environments (pH: 8 > 9 > 7) than acidic conditions, inhibiting acidophilic contaminants and buffering metabolic organic acids. A 15% O₂ concentration was more conducive to growth than normal air (meeting respiratory needs while avoiding oxidative damage), with optimal O₂ levels of 15% > 10% > 5% (screened in 10 experiments). Carbon sources impacted growth less than nitrogen sources (minor mycelial length/density differences). Nitrogen deficiency severely inhibited growth; P. ostreatus had low urea utilization, while (NH₄)₂HPO₄ showed the strongest promotion. Through screening in 12 groups of experiments, the optimal levels were identified as follows. Carbon sources: glucose, dextrin, maltose; nitrogen sources: (NH₄)₂HPO₄, NH₄Cl, yeast powder (Figure 2A,D; Tables S6–S9 and S24–S27).

3.2.2. Orthogonal Experiments for Strain Activation and Propagation

A L₉(3⁴) orthogonal test analyzed pH, O₂ concentration, and carbon and nitrogen sources’ effects on P. ostreatus mycelial growth. Results showed nitrogen source (R = 38.98) and O₂ concentration (R = 22.94) had much higher range values than carbon source (R = 19.79) and pH (R = 19.10), making them key growth factors. The theoretical optimal combination was “pH 7, 15% O₂, glucose, yeast powder”. The discrepancy from single-factor experiments reflected the O₂ interaction with other factors—e.g., in Group No. 4 (low O₂ (5%), pH 8, (NH₄)₂HPO₄, dextrin), and mycelia did not grow, remaining at 7.51 mm. Since O₂ is regulable and its interaction affects growth, subsequent studies will take O₂ as the starting point to explore different O₂ concentrations’ mechanism (Figure 2B,E; Tables S5, S10 and S28).

3.2.3. Screening of Optimal Culture Substrates and Ratios for Mycelial Cultivation

Based on single-factor experiments and mycelial growth photos, “78% wood chips and 20% wheat bran” was identified as the optimal culture substrate—here, mycelia fully covered the medium first and had high density. Comparing seven single substrates (98%) and six mixed combinations (78% substrate and 20% wheat bran), adding wheat bran significantly enhanced mycelial density and growth rate. The 98% wheat bran and 98% wood chips groups showed the most obvious density difference, confirming wheat bran’s promotion. Thus, “78% wood chips, 20% wheat bran, 1% lime, 1% gypsum” was selected. Among four wood chip–wheat bran ratios, 88% wood chips and 10% wheat bran performed worst, while 78% and 20% was best, so this combination was used for subsequent experiments on O₂/gas effects on mycelial growth, fruiting body development, and lignocellulose degradation (Figure 2C,F; Tables S11 and S29–S31).

3.3. Agronomic Trait Analysis of P. ostreatus Mycelia and Fruiting Bodies Under Different O₂ Concentrations and Gas Conditions

3.3.1. Mycelial Growth Under Different O₂ Concentrations and Gas Compositions

In previous experiments, the impact of O₂ on strain activation and propagation using synthetic medium as the substrate drew our attention. However, unlike synthetic medium, the effects of oxygen concentration (high or low oxygen levels) and gas composition (N₂ or CO₂) on mycelial growth of P. ostreatus in its cultivation substrate (78% wood chips, 20% wheat bran, 1% lime, 1% gypsum) remain unclear. Thus, this experiment aims to conduct in-depth investigations into these two key gas factors.

O₂ concentration had a significant impact on the growth rate of P. ostreatus mycelia at different cultivation times. From day 1 to day 5, the mycelial growth rate was slow under 5% O₂, which was significantly lower than that in the Ctrl1 group and the 40% O₂ group. In the first two days, the growth rates of mycelia in the Ctrl1 group and the 40% O₂ group were close, and both were higher than that in the 5% O₂ group. From day 3 to day 5, the mycelial growth rate in the 40% O₂ group remained at a high level, especially on the 5th day; its growth rate was significantly higher than other groups. The growth rate of mycelia in the Ctrl1 group also showed an increasing trend during the cultivation process, but the increase was smaller compared to that in the 40% O₂ group. In conclusion, low-oxygen treatment inhibited P. ostreatus mycelial growth rate, while high-oxygen promoted it—contrasting with our prior finding that low O₂ favored growth in synthetic medium. This is likely because synthetic medium has simple nutrients and low metabolic demand: moderate low O₂ avoids oxidative damage to match this demand. In contrast, complex substrates (wood chips, wheat bran) require lignocellulose degradation, relying on lignocellulolytic enzyme synthesis/metabolism (e.g., laccase, cellulase). High O₂ provides energy for enzyme processes and compensates for insufficient O₂ diffusion in substrates, supporting degradation. Low O₂ fails to meet high energy/O₂ demands, inhibiting growth. This reflects a substrate-driven adaptation: mycelia adjust O₂ response, low O₂ avoids oxidative stress in simple substrates, and high O₂ ensures efficient degradation in complex ones (Figure 3A(a)).

As observed from Figure 3A(b), during the 1–5 days, the mycelial growth rate of the Ctrl2 group was markedly higher than the N₂ and CO₂ groups. Notably, on the 5th day, the mycelia in the Ctrl2 group fully covered the culture medium first, indicating that natural air is the most beneficial for the growth of P. ostreatus mycelia. In contrast, in the treatment groups with N₂ or CO₂ ventilation, the mycelial growth was slower, and their growth rates were consistently lower than the Ctrl2 group within 5 days. This implies that a single high concentration of N₂ or CO₂ inhibits the growth of P. ostreatus mycelia, with CO₂ exerting a stronger inhibitory effect. After 3-day ventilation of N₂ or CO₂ followed by 2-day restoration of O₂ ventilation, the mycelial growth rate changed. At this point, the differences in mycelial growth rates between the FYCO₂ and FYN₂ groups and the Ctrl2 group diminished, suggesting that after the initial exposure to an adverse gas environment, restoring O₂ ventilation can promote mycelial growth (Figure 3A(c)).

3.3.2. The Growth of Fruiting Body with Different Gas Compositions

Comprehensive analysis of the eight groups of bar graphs in Figure 3B revealed that the effects of different gas compositions on the agronomic traits of P. ostreatus fruiting bodies exhibited a regular pattern. In terms of yield, both for the first flush and the second flush of mushrooms, the fruiting body yield in the Ctrl group was significantly higher than that in the CO₂ group and N₂ group. The change trends of cap width and cap length were consistent with those of yield, as the caps in the CO₂ group and N₂ group were narrower and shorter than those in the control group. In contrast, stipe length showed an opposite pattern, with the stipe length in the CO₂ group and N₂ group being significantly longer than that in the control group. The petal number in each treatment group decreased. There was no significant difference in fruiting body water content among all groups. Biological efficiency in the treatment groups was lower than that in the Ctrl group, while no obvious change in germinate time was observed among the groups.

In the heatmap of the first-flush mushrooms, the CO₂ and N₂ treatment groups exhibited cool-color regions, showing negative correlations with morphological parameters, yield components, and petal number, but positive correlations with stipe length. This indicates that high concentrations of CO₂ or N₂ inhibited the fruiting body formation of P. ostreatus, specifically manifested as abnormal cap morphology, excessive stipe elongation, and reduced reproductive output. Such inhibition may result from dysregulation of fungal respiratory metabolism and nutrient allocation. In contrast, the normal air group displayed warm-color regions, showing positive correlations with most indicators, except for stipe length [22]. The heatmap of the second-flush mushrooms showed a similar yet distinct trend. At the second flush stage, the inhibitory effect of high-concentration CO₂ or N₂ was alleviated. The normal air group displayed positive correlations with six indicators and exhibited a significant promoting effect, indicating that normal air continuously provided suitable growth conditions. In summary, normal air conditions are conducive to the growth of P. ostreatus, and the two types of gas stress have similar negative impacts on P. ostreatus; from a statistical perspective, it also suggests that the resource allocation of P. ostreatus under gas stress is biased (Figure 3C,D).

3.3.3. Relationship Between Experimental Treatments and Agronomic Traits

Through the above-mentioned experimental analysis, appropriately increasing the O₂ concentration can promote mycelial growth, while high-concentration N₂ or CO₂ inhibits mycelial growth and fruiting body development. During the cultivation process, precisely regulating the gas environment according to different growth stages (mycelia, first-flush mushrooms, second-flush mushrooms, etc.) and exploring the effects of different gas–concentration combinations and a dynamically changing gas environment on the growth and development of P. ostreatus are of great significance for improving the yield and quality of P. ostreatus.

3.4. Metabolomic Analysis

3.4.1. Quality Control of QC Samples and Verification of Data Reliability

In this study, metabolites in mycelia were detected using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). After metabolite extraction and instrumental analysis, the quality control results showed that the retention time and response intensity of internal standards in QC samples exhibited good stability; no obvious peaks of internal standards were detected in blank samples, indicating controllable cross-contamination; QC samples showed good clustering in the PCA score plot, with the one-dimensional distribution of PCA-X falling within ±2 standard deviations (STD); high correlation was observed; and the median relative standard deviation (RSD) of internal standard responses was ≤10%. In summary, the sample quality, experimental methodology, and system stability were all satisfactory (Figure S1).

3.4.2. Analysis of Differential Mycelial Metabolites and Metabolic Pathways

A differential analysis was performed on mycelia metabolites in different gas compositions. Five sample groups (CO₂, Ctrl2, FYCO₂, FYN₂, N₂) were set up, with three biological replicates each, making 15 samples in total. Metabolomics technology was used for comprehensive analysis, and seven sets of metabolite comparative analyses were conducted: Ctrl2 vs. CO₂, Ctrl2 vs. FYCO₂, Ctrl2 vs. FYN₂, Ctrl2 vs. N₂, FYCO₂ vs. CO₂, FYN₂ vs. N₂, and N₂ vs. CO₂. Differential metabolite analysis identified 2077 samples in 12 Super Classes. The relative expression levels of metabolites differed among sample groups. Using K-Means clustering, differential metabolites were divided into nine clusters. Metabolites in each cluster exhibited specific normalized content variation trends across the five groups (Figure 4A,B,D). The Ctrl2 group was similar to the CO₂ group in metabolite types and contents, and the N₂ group was similar to the FYN₂ group, but there was a large metabolic difference compared to the FYCO₂ group (Figure 4C). Then, a detailed analysis of differential metabolites and their correlations was carried out, and differential metabolites like vanillic acid and ferulic acid, closely related to lignin metabolite transformation, were screened (Figure 4E).

Using Figure 4F,G and Figure S2, and Table S12, we analyzed P. ostreatus mycelial metabolic pathways. “Carbohydrate metabolism” (including “Galactose metabolism” and “Glyoxylate and dicarboxylate metabolism”) is key, providing energy, carbon sources, and supporting growth, material transformation, and cell structure [23,24,25]. “Amino acid metabolism” is highly enriched, critical for growth, development, protein synthesis, enzyme production, and signal transduction [26]. “Membrane transport” involves “ABC transporters” for nutrient uptake and waste excretion, ensuring intracellular stability [27,28]. Nicotinic acid and nicotinamide in “Metabolism of cofactors and vitamins” assist enzymatic reactions [29]. “D-Amino acid metabolism” aids cell wall synthesis and signal transduction [30]. “Aminoacyl-tRNA biosynthesis” is vital for protein translation. “Global and overview maps” reflect metabolic complexity and diversity. Grouped pathway analysis based on Figure 4F revealed the regulatory patterns of environmental stress: under CO₂/N₂ stress, the enrichment levels of pathways such as carbohydrate metabolism (e.g., galactose metabolism) and amino acid metabolism significantly decreased (as indicated by lighter colors and smaller squares). This indicated that energy and carbon flow were impeded, directly hindering the synthesis of substances related to lignin degradation and energy supply. In contrast, under O₂ recovery treatments (FYCO₂/FYN₂), metabolic processes including β-alanine metabolism were significantly activated, which offset the inhibition of amino acid synthesis to maintain enzymatic reactions and promoted the oxidation of lignin derivatives (e.g., up-regulation of salicylic acid). Comparisons between treatments (e.g., FYCO₂vsCO₂, FYN₂vsN₂) revealed that the recovery of pathways such as “amino sugar and nucleotide sugar metabolism” and “glycolysis-gluconeogenesis” further confirmed that O₂ can reverse the inhibitory effects of CO₂/N₂.

3.4.3. Metabolomics Data Analysis of Multiple Derivatives During Degradation of Three Types of Lignin (G-Lignin, S-Lignin, H-Lignin)

Lignin, a core aromatic polymer in plant cell walls formed by three phenylpropane monomers (guaiacyl, syringyl, and p-hydroxyphenyl) into a three-dimensional network via β-O-4 ether and C-C bonds, gives plants mechanical strength but hinders biomass conversion. Thus, elucidating efficient lignin degradation is key for high-value biomass utilization. White-rot fungi fully mineralize lignin by secreting laccase (Lac), manganese peroxidase (MnP), and lignin peroxidase (LiP), which break lignin’s aromatic rings and bonds via free radical reactions to produce aromatic derivatives. We analyzed metabolomics data from seven comparison groups. The chemical structures of six typical aromatic derivatives produced during lignin degradation are presented in Figure 5C and Table S13. Additionally, 53 aromatic derivatives related to the degradation of three types of lignin were selected for comparative study [31]. The heatmap visually illustrates the differences in relative abundance of 53 types of aromatic metabolites among different treatment groups via normalized relative quantitative analysis. Observing metabolite-related content in bar graphs and heatmaps, most aromatic derivatives in non-control groups (e.g., CO₂, N₂) decreased, while those in the Ctrl group were higher. This suggests gas regulation (high CO₂/N₂) may weaken lignin degradation key steps (e.g., aromatic ring epoxidation, β-O-4 ether bond cleavage) by inhibiting white-rot fungi’s degrading enzyme activity. Reduced lignin degradation efficiency lowered downstream aromatic derivatives (e.g., 4-Hydroxybenzoic acid, vanillic acid), making treatment groups’ metabolite content much lower than the Ctrl group. In summary, gas regulation inhibited lignin degradation and reduced aromatic derivative accumulation (Figure 5A,B, Tables S14, S15 and S32).

Figure 6 illustrates lignin’s metabolic mechanism via three hierarchical processes (branch metabolism, funneling, fission pathway) integrated into the tricarboxylic acid (TCA) cycle. The differential abundance of 53 aromatic metabolites across treatments is explained by this cascade: First, structurally diverse lignin-derived metabolites (e.g., p-coumaric acid, ferulic acid) in branch metabolism cause initial abundance variations. Then, the funneling pathway channels them into core intermediates (e.g., protocatechuate, catechol). Next, the fission pathway uses multiple aromatic ring-cleavage routes to break these intermediates into small molecules, which finally enter the TCA cycle for energy production or precursor synthesis. This cascade explains how treatments (e.g., O₂, CO₂, N₂ regulation) modulate aromatic metabolite abundance [32,33,34].

3.5. Effects of Different O₂ Concentrations and Gas Compositions on the Degradation of Lignocellulose in P. ostreatus-Inoculated Residue

The degradation efficacy of P. ostreatus on three lignocellulose components (cellulose, hemicellulose, and lignin) in fungal residue under varying O₂ concentrations and gas compositions was systematically evaluated based on quantitative analysis.

3.5.1. Effects on Lignin Degradation

Compared with the NO group (non-inoculated), all groups inoculated with P. ostreatus had lower lignin content in fungal residue, confirming that P. ostreatus effectively decomposes lignin. Among inoculated groups with different gases, lignin content changes varied significantly: the Ctrl2 group showed the largest decrease (57.62% → 42.33%), indicating its gas environment best supports P. ostreatus’ lignin-degrading ability. This aligns with downregulated lignin degradation products in metabolomics data (Tables S14 and S15; Figure 5A,B), likely because the gas meets P. ostreatus’ optimal growth and enzyme secretion needs. The 40% O₂ and N₂ groups also had significant decreases (7.87% and 11.01%, respectively), showing that high oxygen or single N₂ benefits lignin decomposition. In contrast, 5%O₂, CO₂, FYCO₂, and FYN₂ groups had smaller decreases—low oxygen/high CO₂ may limit P. ostreatus’ respiration, enzyme activity, and metabolism, with early gas impacts persisting post-O₂ restoration (Figure 7;

Table 1. Percentage contents of lignocellulose in P. ostreatus-inoculated residue of different groups.

Group	Percentage Contents (%)
	Lignin	Cellulose	Hemicellulose
NO	57.62 ± 2.12	9.46 ± 0.67	11.17 ± 0.10
Ctrl1	51.65 ± 0.56	8.49 ± 0.15	10.16 ± 0.95
40%O2	49.75 ± 3.19	8.45 ± 0.42	10.02 ± 0.07
5%O2	53.93 ± 2.06	7.96 ± 0.29	10.35 ± 0.58
Ctrl2	42.33 ± 3.37	8.48 ± 1.55	9.79 ± 0.37
CO2	54.02 ± 0.76	6.03 ± 1.96	10.32 ± 0.29
FYCO2	55.47 ± 3.61	3.69 ± 0.37	9.78 ± 0.13
N2	46.61 ± 0.31	9.07 ± 1.02	9.56 ± 0.30
FYN2	54.73 ± 1.55	6.95 ± 1.10	10.64 ± 0.12

).

Mechanisms of Action of Enzymes During Lignin Degradation

Previous studies showed that gas environment regulates P. ostreatus’ lignin degradation efficiency by affecting its secreted lignin-degrading enzymes (LiP, MnP, Lac, VP; Figure 8). LiP, a heme-based enzyme, starts peroxidase-catalyzed oxidation with H₂O₂: H₂O₂ oxidizes LiP to 2-electron-losing LiP Compound I, which oxidizes aromatic substrates and gains 1 electron to form LiP Compound II, which then gains another electron to return LiP to its initial state. MnP, a glycosylated ferroheme protein (key for lignin degradation), oxidizes lignin’s aromatic rings via H₂O₂. It oxidizes Mn²⁺ to Mn³⁺, which complexes with carboxylic acids to degrade phenolics. Lac, a blue copper-containing monomeric glycoprotein, catalyzes O₂-centered redox reactions via four consecutive single-electron oxidations. Electrons transfer to O₂ to form water, with no reactive oxygen radicals, and Lac reverts to initial state. VP, a new heme peroxidase, fuses MnP and LiP functions. It has unique binding/catalytic sites and low-redox-potential substrate sites (breaking substrate limits), important for lignin degradation and refractory pollutant treatment [35,36,37,38,39,40,41,42].

Bioinformatics Characterization of Lignin-Degrading Enzymes as Biological Macromolecules

Integrating bioinformatics results, the four lignin-degrading enzymes exhibit high structural and functional synergism and substrate adaptability (Tables S17 and S18). LiP’s hydrophilicity facilitates liquid-phase diffusion, while MnP, Lac, and VP’s hydrophobicity enhances binding to solid lignocellulose. Lac’s high structural stability and multi-copper center support lignin and phenolics oxidation. Functional site analysis shows LiP’s Fe³⁺-binding site, MnP’s Mn²⁺-binding pocket, Lac’s multi-copper centers, and VP’s metal–heme composite binding site are catalytic cycle cores. Their three-dimensional arrangement optimizes substrate binding and electron transfer, forming a “metal dependence-structural adaptation-substrate specificity” degradation mechanism (Tables S19 and S20; Figure 9A–D). Signal peptide and N-glycosylation predictions explain enzyme secretion and function maintenance. All four have Sec/SPI-type signal peptides, secreted extracellularly via the Sec pathway (fitting “extracellular lignin degradation”), and N-glycosylation sites ensure activity by enhancing secretion stability, protecting catalytic centers, and strengthening substrate adsorption (Figure 9E–L). Figure 9M–R shows VP3 and MnP3 have similar protein interaction networks (overlapping core proteins) and rely on RNA metabolism-related proteins to clear RNA-DNA hybrids and regulate physiology via phosphatidylinositol [43]. LACC9 = POX1’s unique network involves lignin degradation, enzyme homeostasis, copper transporters, and vesicle transport (multi-system regulation), complementing VP3/MnP3 to build a multi-dimensional lignin degradation network.

3.5.2. Effects on Cellulose Degradation

Compared with the NO group (non-inoculated, cellulose content 9.46%), all P. ostreatus-inoculated groups had lower cellulose content in fungal residue (3.69–9.07%), confirming P. ostreatus can decompose cellulose (Figure 7; Table 1). Gas environment significantly affected its cellulose-degrading ability: FYCO₂ and CO₂ groups showed the most significant decrease, most conducive to cellulose decomposition—likely due to CO₂ environment and subsequent O₂ restoration enhancing cellulolytic enzyme secretion and activity [44]. The N₂ group had cellulose content similar to the NO group; a single N₂ environment restricted P. ostreatus’ metabolic activities, hindering its decomposing ability. Among groups with different O₂ concentrations, the 5% O₂ group had a more significant cellulose decrease, indicating O₂ concentration changes affect P. ostreatus’ respiratory metabolism and enzyme activity, thereby promoting cellulose decomposition. In summary, inoculation with P. ostreatus reduced cellulose content in fungal residue.

PCR and Protein Alignment-Based Functional Analysis of the AA9 Gene

Differences in degradation rates across groups show that gases (especially O₂) can regulate lignocellulose degradation activity by affecting mycelial growth and lignocellulose derivative metabolism. AA9, a copper-dependent redox enzyme in the lytic polysaccharide monooxygenase family (auxiliary activity family 9), mediates filamentous fungal lignocellulose degradation. It activates O₂/H₂O₂, couples with electron donors to catalyze cellulose C1/C4 oxidative cleavage, enhancing lignin–cellulose complex degradation efficiency [45].

To analyze the molecular basis of AA9 family polysaccharide monooxygenases in P. ostreatus, we investigated the P. ostreatus PC9 strain, whose whole-genome sequencing has been completed. An AA9 gene retrieved from NCBI was named PC9H_000909 (Gene ID: 59370750; encodes 310 amino acids, full-length 1565 bp). To confirm this gene in strain PO-01, PCR primers were designed targeting its 363 bp conserved functional domain: forward (F: 5′-GCCTATCACCGATGTCACTTC-3′), reverse (R: 5′-CACTTGCCATCAGAGGTAAGAC-3′), Tm 55 °C, expected product 294 bp. Results showed a single bright specific band (250–500 bp) in PO-01, matching the expected length. This proved PC9 F/R primers efficiently amplified the target, preliminarily verifying the AA9 gene (for cellulose degradation) in PO-01 at the molecular level (Figure 10A). To investigate AA9 family protein function in P. ostreatus, this study used NCBI BLAST to align PC9 strain’s AA9 protein (GenBank: KAF7440563.1) with S. pruinosum’s validated AA9 (GenBank: BAL43430.1) (Table S17). Results showed that their core functional domain (amino acids 43–236) is significantly conserved: purple bands in alignment scores cover key catalytic regions (a conservation hotspot); sequence identity is 38% (75/199); and positivity rate 52% (105/199). Despite amino acid differences, similar chemical properties maintain catalytic center spatial conformation (e.g., copper-binding motifs), supporting lytic polysaccharide monooxygenase function. Alignment dot plots showed high-density matching sites concentrate at amino acids 100–200, verifying polysaccharide degradation function conservation (Figure 10B–D).

Bioinformatics Analysis of the AA9 Protein

Bioinformatics analysis of the AA9 proteins from S. pruinosum and P. ostreatus was performed (Table S17). Functional site annotation revealed that S. pruinosum AA9 contains binding sites for Cu²⁺ (positions 19/94/178) and O₂ (positions 167/176), which mediate metal ion binding and monooxygenase activity, thereby participating in cellulose decomposition. Although the functional sites of P. ostreatus AA9 are not fully annotated, annotations related to “cellulase activity” and “cellulose binding” suggest convergence in their catalytic mechanisms. Physicochemical property analysis showed interspecific differentiation; differences in molecular weight and hydrophilicity/hydrophobicity of S. pruinosum AA9 may be related to preferences for lignin substrate types. Three-dimensional structure prediction revealed that both proteins adopt an α/β fold as the core conformation. SignalP 6.0 prediction indicated that both AA9 proteins contain Sec/SPI-type signal peptides (with a probability > 0.999), with cleavage sites located at positions 17–18 (P. ostreatus) and 18–19 (S. pruinosum), respectively, suggesting efficient secretion extracellularly via the Sec pathway. NetNGlyc 1.0 prediction found that P. ostreatus AA9 scored > 0.5 at positions such as 27/35/57, while S. pruinosum AA9 showed high scores at positions such as 44/48/68. These potential N-glycosylation sites may regulate enzymatic activity (Figure 11A–F; Tables S21 and S22).

3.5.3. Effects on Hemicellulose Degradation

When comparing the NO group with each inoculated group, the hemicellulose content in the non-inoculated group was 11.17%, while that in each treatment group after inoculation with P. ostreatus fluctuated between 9.56% and 10.64%, with a decrease ranging from 0.53% to 1.61%. Specifically, the content in the Ctrl2 group, FYCO₂ group, and N₂ group decreased by 1.38%, 1.39%, and 1.61%, respectively. Although the decrease in these groups was slightly larger than that in other groups, the advantage was not prominent. This indicates that P. ostreatus has limited ability to decompose the hemicellulose in fungal residue, and its decomposition effect on hemicellulose is weaker than that on lignin. This may be more determined by its own physiological characteristics and basic metabolic mechanisms rather than changes in gas conditions (Figure 7 and Table 1).

3.6. Effects of Gas Environment on Polysaccharide Accumulation and Bioethanol Potential in P. ostreatus-Inoculated Residue

Taking the NO group’s fungal residue polysaccharide content (8.76 mg/g) as a reference, the N₂ and CO₂ groups had significantly higher content (16.82 mg/g, 16.41 mg/g). After O₂ restoration, FYN₂ and FYCO₂ groups decreased by 6.68 mg/g and 9.31 mg/g, indicating high N₂/CO₂ promote polysaccharide accumulation (possibly stimulating synthesis/inhibiting decomposition [46]). The Ctrl1 group rose to 9.77 mg/g, while Ctrl2 remained stable (8.78 mg/g). Though 40% O₂ and 5% O₂ groups’ data were out of range, O₂’s effect on P. ostreatus metabolism (altering polysaccharide content) led to their inclusion in subsequent bioethanol yield calculation (Figure 12;

Table 2. Bioethanol yields in P. ostreatus-inoculated residue of different groups.

Group	Percentage Contents (%)		Theoretical Yield of Ethanol (L·ha−1)		Total
	Cellulose and Hemicellulose	Polysaccharides in Fungal Residue	From Cellulose and Hemicellulose	From Polysaccharides
Ctrl1	18.65 ± 1.10	0.98 ± 0.08	96.57 ± 5.67	5.36 ± 0.45	101.90 ± 5.38
40%O2	18.46 ± 0.40	0.09 ± 0.04	95.57 ± 2.07	0.51 ± 0.20	96.09 ± 2.26
5%O2	18.31 ± 0.38	0.08 ± 0.01	94.79 ± 1.98	0.43 ± 0.05	95.23 ± 2.01
Ctrl2	18.27 ± 1.87	0.88 ± 0.01	94.61 ± 9.67	4.82 ± 0.07	99.43 ± 9.68
CO2	16.35 ± 1.73	1.64 ± 0.03	84.67 ± 8.96	9.00 ± 0.14	93.67 ± 8.86
FYCO2	13.47 ± 0.26	0.71 ± 0.10	69.74 ± 1.36	3.90 ± 0.57	73.63 ± 1.89
N2	18.63 ± 1.29	1.68 ± 0.02	96.46 ± 6.67	9.23 ± 0.10	105.70 ± 6.77
FYN2	17.59 ± 0.99	1.01 ± 0.10	91.09 ± 5.11	5.56 ± 0.54	96.65 ± 5.46

and Table S33).

Polysaccharides in fungal residue are key for bioethanol, whose content impacts yield. This experiment calculated ethanol yields from cellulose, hemicellulose, and polysaccharides in residue via formulas (Table S16). The residue, once non-recyclable after P. ostreatus cultivation, can produce bioethanol after treatment/optimization, broadening raw material sources for agro-forestry waste utilization [47,48]. Residues in different gas groups showed significant indicator fluctuations: bioethanol yield ranged 73.63–105.70 L·ha⁻¹, with FYCO₂ lowest, N₂ highest, and Ctrl1/Ctrl2/FYN₂ similar—due to conversion efficiencies of cellulose, hemicellulose, and polysaccharides (the FYCO₂ group had high cellulose and hemicellulose decomposition but polysaccharide conversion problems, while the N₂ group had balanced components and high efficiency) [49,50]. Figure S6 and Table S23 show P. ostreatus’ advantages in ethanol fermentation: as a white-rot fungus, it secretes enzymes to ferment monosaccharides into ethanol via consolidated bioprocessing (CBP), eliminating the need for exogenous glycosidases and reducing costs to enable a more economical route [51].

4. Discussion

In this study, the PO-01 strain was identified as P. ostreatus to ensure experimental material reliability. Through single-factor and orthogonal experiments, optimal culture conditions and substrates were screened to establish a stable experimental system. Optimized parameters eliminated nutritional limitations for accurate evaluation of gas effects on fungal physiology. Moderate oxygenation (e.g., 40%O₂) accelerates mycelial growth by promoting aerobic respiration and energy production, consistent with oxygen’s role in enzyme secretion and redox reactions. For example, LiP initiates the oxidation cycle via electron transfer, Lac transfers electrons to O₂ to generate water, and AA9 proteins activate oxygen and oxidize cellulose. In contrast, high N₂/CO₂ concentrations disrupt gas exchange and metabolic balance, inhibit mycelial and fruiting body development, and cause abnormal cap, elongated stipes, and reduced reproductive output. This shows the need for stage-specific gas management: increase oxygen during mycelial colonization and avoid inhibitory gases during fruiting body formation to maximize biomass and enzyme production.

Metabolomics analysis showed the up- and down-regulation trends of 53 aromatic derivatives during G/H/S-lignin degradation, focusing on 12 key metabolites’ regulation and pathways. The down-regulation of key metabolites like vanillic acid in the N₂/CO₂ group suggested that gas stress reduced lignin degradation efficiency. Mechanistically, it aligns with bioinformatics analysis of lignin-degrading enzymes (LiP, MnP, Lac, VP), which rely on metal-driven catalytic cycles and Sec pathway secretion. Their conserved functional sites and N-glycosylation modifications emphasize the importance of gas conditions for enzyme structure and activity. It is worth discussing the paradox where the N₂ group has a high lignin degradation rate and the highest ethanol yield, yet metabolomics shows down-regulation of aromatic derivatives. We propose that the core mechanism is the synergistic interaction between lignin degradation and downstream metabolism: under N₂ conditions, lignin degrades, producing aromatic intermediate metabolites. These metabolites do not accumulate but are decomposed via central metabolic pathways like the TCA cycle, and the carbon flux is directed towards ethanol synthesis. In subsequent studies, we will measure key TCA cycle enzyme activity and conduct isotope tracing experiments on aromatic metabolites to verify the metabolic flow and carbon flux distribution rules.

To systematically integrate the differential regulatory mechanisms of gas signals on enzyme systems, we propose a gas signal-mediated differential regulation model of enzyme systems. Fungi perceive gas signals (e.g., low O₂, high N₂/CO₂) and initiate signaling through changes in intracellular redox homeostasis, heme-dependent oxygen-sensing proteins, or key metabolic intermediate concentrations. Then, the initial signal is transduced by activating relevant signaling and ion concentration-dependent pathways to regulate specific transcription factor activity. For lignin-degrading enzymes (e.g., LiP, MnP, Lac, VP), their metal ion-dependent catalytic cycles and protein secretion are sensitive to intracellular redox balance and energy supply. Under low O₂, cellular aerobic respiration efficiency drops, energy production is limited, and metal ion homeostasis is disrupted, impairing enzyme catalytic core stability or secretion efficiency and downregulating their synthesis and secretion. Future studies will focus on validating key model links, such as identifying core components for gas signal perception in fungi, dissecting key transcription factors and their target genes, and clarifying the molecular mechanisms of gas signal transduction and differential enzyme system regulation.

Beyond lignin degradation, exploring cellulose mechanisms enriches understanding of fungal metabolic responses to gas. AA9 (copper-dependent LPMO) oxidizes C1/C4 to enhance cellulose accessibility, synergizing with lignin-degrading enzymes—explaining higher cellulose degradation in FYCO₂/FYN₂ post-reoxygenation. Hemicellulose degradation is limited (<1.61%, needing pretreatment). Gas regulates polysaccharides to affect bioethanol potential; P. ostreatus integrates enzyme production, hydrolysis, and fermentation, simplifying industrial processes [6,52,53]. Future research will focus on dynamic gas regulation, metabolic engineering, and combined pretreatment. The phased gas regulation strategy in this study is feasible: in the initial stage, high O₂ (e.g., 40% O₂) promotes mycelial growth and lignin degradation, preparing for later fermentation; in the final stage, microaerobic conditions like N₂ shift carbon flux to polysaccharide metabolism and ethanol synthesis. This dynamic approach suits different physiological stages, and subsequent studies will verify its effect on ethanol yield via phased regulation experiments.

5. Conclusions

In conclusion, strain PO-01, isolated by tissue—cultured and identified as P. ostreatus—has been comprehensively studied. Optimal propagation conditions (pH 7, 15% O₂, glucose, yeast powder) and cultivation substrate formula (78% wood chips and 20% wheat bran) were determined through single-factor and orthogonal experiments. Oxygen concentration gradient (5%, 20%, 40%) and N₂/CO₂ regulation experiments indicated that moderate oxygenation benefits mycelial growth, while high concentrations of N₂/CO₂ are inhibitory to mycelial development and fruiting body formation. Metabolomics identified 53 aromatic derivatives related to G/H/S-lignin degradation and further clarified the metabolic pathways of G/H/S-lignin. Lignin degradation, which relies on the synergistic action of LiP, MnP, Lac, and VP, reached a rate of 15.29%, while cellulose degradation rate was 5.77% and the presence of a cellulose-degradation-related AA9 gene was confirmed by PCR amplification. Hemicellulose degradation is relatively weak at 1.61%. Oxygen concentrations of 5% and 40% significantly inhibit polysaccharide content and ethanol yield, while the N₂ group enables efficient ethanol production due to balanced substrate conversion. Specifically, a two-stage gas regulation strategy—first utilizing moderate oxygen to boost biomass accumulation and lignin pretreatment, then switching to N₂ to direct metabolic flux toward fermentation—shows great potential for enhancing bioethanol production.