实验室条件下不规则根孢囊霉（Rhizophagus irregularis）与哈茨木霉（Trichoderma harzianum）共接种对甘草生长及代谢影响的原始数据

本套数据为探究不规则根孢囊霉（Rhizophagus irregularis，Ri）与哈茨木霉（Trichoderma harzianum，Th）共接种对甘草（Glycyrrhiza uralensis）干旱耐受性、次生代谢物积累及基因表达的调控机制提供完整原始数据支撑，涵盖植物生长、次生代谢、渗透调节、营养化学计量比及基因表达五大核心维度，具体如下：
1. 数据内容
数据来源于 8 个处理组（2 种水分条件 ×2 种 Ri 接种处理 ×2 种 Th 接种处理），每组设 5 次生物重复，核心指标及意义如下：
生物量指标：地上部干重（g pot⁻¹、g plant⁻¹）、根系干重（g pot⁻¹、g plant⁻¹），直接反映不同处理对甘草生长的影响；
次生代谢物指标：甘草酸（Glycyrrhizin）浓度（mg g⁻¹）与单株含量（mg plant⁻¹）、甘草苷（liquiritin）浓度（mg g⁻¹）与单株含量（mg plant⁻¹），为评价甘草药用品质提供关键依据；
渗透调节指标：脯氨酸浓度（mg g⁻¹），表征甘草对干旱胁迫的生理响应能力；
营养及化学计量指标：根系碳（C）、氮（N）、磷（P）浓度（mg g⁻¹ DW）及 C:N、C:P、N:P 比值，体现微生物接种对甘草营养吸收与利用效率的调控作用；
基因表达指标：甘草酸合成关键基因 SQS1、甘草苷合成关键基因 CHS、水分转运基因 PIP 的相对表达量，揭示微生物调控甘草抗逆及次生代谢的分子机制。
8 个处理组具体为：WW/-M/CK（正常水分 + 不接 Ri + 不接 Th）、WW/-M/Th（正常水分 + 不接 Ri + 接 Th）、WW/+M/CK（正常水分 + 接 Ri + 不接 Th）、WW/+M/Th（正常水分 + 接 Ri + 接 Th）、DS/-M/CK（干旱胁迫 + 不接 Ri + 不接 Th）、DS/-M/Th（干旱胁迫 + 不接 Ri + 接 Th）、DS/+M/CK（干旱胁迫 + 接 Ri + 不接 Th）、DS/+M/Th（干旱胁迫 + 接 Ri + 接 Th），各组数据对应文档 2 中 “Group” 列的 1-8 组。
2. 数据来源及加工方法
数据来源：实验室可控盆栽实验。甘草种子经 50% H₂SO₄浸种 30 min（破除休眠）、10% H₂O₂灭菌 10 min 后，于 25℃黑暗条件下萌发 2-3 天；种植于 γ 射线灭菌土壤（采集自甘肃武威甘草种植基地，pH 8.3，有效 N 26.0 mg kg⁻¹、有效 P 6.8 mg kg⁻¹、有效 K 59.6 mg kg⁻¹），每盆装土 400 g 并添加基础肥料（120 mg kg⁻¹ N、20 mg kg⁻¹ P、120 mg kg⁻¹ K）；按 “水分 + 微生物接种” 设置处理，其中 Ri 接种量为 30 g / 盆（含 67 孢子 g⁻¹ 土壤的接种物），Th 接种量为 40 mL / 盆（3×10⁶ conidia mL⁻¹ 的孢子悬浮液），先培养 90 天（土壤含水率 16%，即 60% 饱和含水率），再分别维持正常水分（WW，16% 含水率）或干旱胁迫（DS，11% 含水率）28 天后收获、、。
加工方法：生物量通过 75℃烘干至恒重后用电子天平称重；甘草酸与甘草苷用 70% 甲醇超声提取 30 min，经 0.45 μm 滤膜过滤后，用 HPLC（Agilent-1200，ZORBAX Eclipse XDB-C18 柱）定量（以国家药品标准品制作标曲，甘草酸标品批号 110731，甘草苷标品批号 11610）；脯氨酸用酸性茚三酮比色法测定；C、N 浓度用元素分析仪（Vario MAX）测定，P 浓度经硝酸微波消解后用 ICP-OES（Prodigy）测定；基因表达用 RNeasy Plant Mini Kit 提取总 RNA，经 DNase I 处理后反转录为 cDNA，通过 qPCR（LightCycler 480II）测定，以 Actin2 为内参基因，采用 2⁻ΔΔCt 法计算相对表达量。所有数据经人工核对重复样本一致性，缺失数据标注为 “——”，整理为 Excel 表格格式。
3. 数据质量描述
数据可靠性与规范性满足科研分析需求：
重复性：每组设 5 次生物重复，关键指标（如甘草酸浓度、根系 P 浓度）重复测定的变异系数（CV）＜15%；
准确性：HPLC 定量标曲 R²＞0.99，qPCR 扩增效率为 90%-110% 且溶解曲线单一，元素分析用 NIST SRM 1575a 标准物质校准，误差＜5%；
完整性：数据无异常离群值（经 Shapiro-Wilk 正态性检验和 Levene 方差齐性检验验证），缺失值明确标注，可直接用于统计分析；
一致性：所有指标单位统一（如质量单位为 “g”“mg”，浓度单位为 “mg g⁻¹”），处理组命名与实验设计完全对应，便于跨数据关联分析。
4. 数据应用成果及前景
已支撑成果：数据已用于验证 “Ri 与 Th 共接种可协同提升甘草干旱耐受性与药用品质” 的核心结论，如干旱条件下共接种使甘草酸产量提高 93.7%，并上调 SQS1、CHS 基因表达，同时优化根系 C:P 比值以提升营养利用效率。

This dataset provides complete raw data support for exploring the regulatory mechanism of co-inoculation with Rhizophagus irregularis (Ri) and Trichoderma harzianum (Th) on drought tolerance, secondary metabolite accumulation and gene expression of Glycyrrhiza uralensis, covering five core dimensions: plant growth, secondary metabolism, osmotic regulation, nutritional stoichiometry, and gene expression, as detailed below:

1. Data Content
The dataset is derived from 8 treatment groups (2 water regimes × 2 R. irregularis inoculation treatments × 2 T. harzianum inoculation treatments), with 5 biological replicates per group. The core indicators and their significances are as follows:
- Biomass indices: Aboveground dry weight (g pot⁻¹, g plant⁻¹) and root dry weight (g pot⁻¹, g plant⁻¹), which directly reflect the effects of different treatments on the growth of G. uralensis;
- Secondary metabolite indices: Glycyrrhizin concentration (mg g⁻¹) and per-plant content (mg plant⁻¹), liquiritin concentration (mg g⁻¹) and per-plant content (mg plant⁻¹), which provide key evidence for evaluating the medicinal quality of G. uralensis;
- Osmotic regulation indices: Proline concentration (mg g⁻¹), which characterizes the physiological response of G. uralensis to drought stress;
- Nutritional and stoichiometric indices: Root carbon (C), nitrogen (N), phosphorus (P) concentrations (mg g⁻¹ DW) and C:N, C:P, N:P ratios, reflecting the regulatory effect of microbial inoculation on nutrient uptake and utilization efficiency of G. uralensis;
- Gene expression indices: Relative expression levels of key glycyrrhizin synthesis gene SQS1, key liquiritin synthesis gene CHS, and water transport gene PIP, revealing the molecular mechanism by which microbes regulate stress resistance and secondary metabolism of G. uralensis.

The 8 treatment groups are specifically: WW/-M/CK (Well-watered, no R. irregularis inoculation, no T. harzianum inoculation), WW/-M/Th (Well-watered, no R. irregularis inoculation, T. harzianum inoculation), WW/+M/CK (Well-watered, R. irregularis inoculation, no T. harzianum inoculation), WW/+M/Th (Well-watered, R. irregularis inoculation, T. harzianum inoculation), DS/-M/CK (Drought stress, no R. irregularis inoculation, no T. harzianum inoculation), DS/-M/Th (Drought stress, no R. irregularis inoculation, T. harzianum inoculation), DS/+M/CK (Drought stress, R. irregularis inoculation, no T. harzianum inoculation), DS/+M/Th (Drought stress, R. irregularis inoculation, T. harzianum inoculation). Data of each group correspond to Groups 1–8 in the "Group" column of Document 2.

2. Data Source and Processing Methods
Data Source: This dataset comes from a controlled laboratory pot experiment. Seeds of G. uralensis were soaked in 50% H₂SO₄ for 30 min to break seed dormancy, sterilized with 10% H₂O₂ for 10 min, then germinated at 25℃ in darkness for 2–3 days. The seedlings were planted in γ-ray sterilized soil collected from a G. uralensis planting base in Wuwei, Gansu Province, with pH 8.3, available N 26.0 mg kg⁻¹, available P 6.8 mg kg⁻¹, available K 59.6 mg kg⁻¹. Each pot was filled with 400 g of soil and supplemented with basal fertilizer (120 mg kg⁻¹ N, 20 mg kg⁻¹ P, 120 mg kg⁻¹ K). Treatments were set according to "water regime + microbial inoculation": R. irregularis inoculum was applied at 30 g per pot (containing 67 spores g⁻¹ soil), and T. harzianum spore suspension (3×10⁶ conidia mL⁻¹) was added at 40 mL per pot. The plants were pre-cultivated for 90 days with soil moisture content at 16% (i.e., 60% of saturated water holding capacity), then maintained under well-watered (WW, 16% moisture) or drought stress (DS, 11% moisture) conditions for 28 days before harvest.

Processing Methods: Biomass was weighed using an electronic balance after drying to constant weight at 75℃. Glycyrrhizin and liquiritin were extracted with 70% methanol via ultrasonic extraction for 30 min, filtered through a 0.45 μm membrane, and quantified by HPLC (Agilent-1200, ZORBAX Eclipse XDB-C18 column) with standard curves prepared using national pharmaceutical reference standards (glycyrrhizin reference standard batch number: 110731; liquiritin reference standard batch number: 11610). Proline was determined by acid ninhydrin colorimetry. Concentrations of C and N were measured using an elemental analyzer (Vario MAX), while P concentration was determined via ICP-OES (Prodigy) after nitric acid microwave digestion. For gene expression analysis, total RNA was extracted using the RNeasy Plant Mini Kit, treated with DNase I, reverse-transcribed into cDNA, and quantified by qPCR (LightCycler 480II). Actin2 was used as the reference gene, and relative expression levels were calculated using the 2⁻ΔΔCt method. All data were manually checked for consistency across biological replicates, missing values were marked as "——", and the dataset was compiled into Excel spreadsheets.

3. Data Quality Description
The reliability and standardization of this dataset meet the requirements of scientific research analysis:
- Repeatability: Each group has 5 biological replicates, and the coefficient of variation (CV) of repeated measurements for key indicators (e.g., glycyrrhizin concentration, root P concentration) is <15%;
- Accuracy: The R² of HPLC standard curves for quantification is >0.99; the qPCR amplification efficiency ranges from 90% to 110% with a single melting curve; elemental analysis is calibrated using NIST SRM 1575a reference material, with an error of <5%;
- Completeness: There are no abnormal outliers in the dataset (verified by Shapiro-Wilk normality test and Levene's homogeneity of variance test), and missing values are clearly labeled, making the data directly applicable for statistical analysis;
- Consistency: All indicators use unified units (e.g., mass units: "g", "mg"; concentration units: "mg g⁻¹"), and the naming of treatment groups fully corresponds to the experimental design, facilitating cross-data correlation analysis.

4. Data Application Achievements and Prospects
Published supported research: This dataset has been used to verify the core conclusion that co-inoculation with R. irregularis and T. harzianum synergistically improves drought tolerance and medicinal quality of G. uralensis. For example, co-inoculation under drought conditions increased glycyrrhizin yield by 93.7%, upregulated the expression of SQS1 and CHS genes, and optimized the root C:P ratio to enhance nutrient utilization efficiency.

搜集汇总

背景与挑战

背景概述

该数据集提供了实验室条件下不规则根孢囊霉与哈茨木霉共接种对甘草影响的原始数据，涵盖生长、次生代谢、渗透调节、营养和基因表达五个维度的指标，基于8个处理组的盆栽实验设计。数据集旨在探究两种微生物共接种如何协同增强甘草的干旱耐受性和次生代谢物生产，已用于验证共接种可显著提高甘草酸产量并优化相关基因表达。