Effect of Solanum rostratum Dunal litter extract on its seedling growth

Effect of Solanum rostratum Dunal litter extract on its seedling growth | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Effect of Solanum rostratum Dunal litter extract on its seedling growth Yuxuan Ma, Lamei Jiang, Shuai Liu, Huixian Liu, Guohao Zhai, Juan Qiu, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6829445/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Allelopathy is one of the important mechanisms for the spread and expansion of invasive alien plants. The current research mainly focuses on interspecific allelopathy, while there are relatively few studies on intraspecific allelopathy. Solanum rostratum Dunal is an annual invasive plant with strong invasiveness, the secondary metabolites produced by the litter of S. rostratum can accumulate in the soil, and may affect the growth of its own seedlings. Therefore, it is of great significance to clarify the intraspecific allelopathy of S. rostratum for understanding the invasion mechanism or proposing new prevention and control strategies. In this study, the extract of S. rostratum litter was used to treat its seedlings, and the soil physical and chemical properties, soil metabolites, and soil microorganisms were measured to analyze their correlation with the growth of seedlings. The results showed that 0.1 and 1 g/L treatment significantly promoted the leaf area and biomass of seedlings, while 10 g/L treatment significantly inhibited plant height, leaf area index, biomass, net photosynthetic rate, transpiration rate, and stomatal conductance. Some bacteria, such as Brevundimonas alba , Brevundimonas , Altererythribacter , Novosphingobium resinovorum , and Novosphingobium exhibited a higher abundance under 10 g/L treatment, showed a negative correlation with seedling growth. And 25 metabolites detected in the soil, such as 2-Aminobenzoic acid, 2, 6-dibromophenol and palmitaldehyde, might be the potential auto-toxicity. The results can not only supplement the invasion mechanism of invasive plants from the perspective of intraspecific allelopathy, but also provide theoretical support for formulating control strategies for the S. rostratum . Biological sciences/Ecology/Biodiversity Biological sciences/Ecology/Invasive species Biological sciences/Ecology Biological sciences/Plant sciences Solanum rostratum Dunal Intraspecific allelopathy Seedling growth Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Alien invasive plants are plants that spread from their original place to another environment through natural or human means to settle, reproduce and spread, and eventually significantly affect the ecological environment of the place of migration 1 . Now the the invasion mechanism and control measures of invasive plants are one of the important contents of current research. New weapon hypothesis holds that the invasive alien plant can produce some allelochemicals, which are released into the environment through root secretion and litter, and inhibit the growth of native plants 2 . Allelopathy refers to the process in which plants release chemicals into the surrounding environment, affecting the growth of surrounding plants 3 , 4 . Allelopathy can be divided into interspecific allelopathy and intraspecific allelopathy 5 . On the one hand, invasive alien plants can alter the chemical composition of the soil through root secretions and decomposition from litter, thereby inhibiting seed germination and seedling growth of native plants 6 . On the other hand, the chemical substances produced by invasive plants can affect the population size, community structure or function of the soil microorganisms, which can disturb the interaction and symbiotic relationship between plants and soil microorganisms, and then promote or inhibit their diffusion and spread 1 , 7 – 9 . Studies have found that the extracts of invasive plants can display stronger allelopathic activity on the germination and seedling growth of native species, while performed little autotoxic effects 10 , 11 . However, allelopathy produced by invasive species does not necessarily remain unchanged during invasion 8 . For example, the survival rate, biomass and competitiveness of invasive species are lower in environments with longer invasion time 1 , 9 . In addition, autotoxicity may occur in invasive plants, which is significant for the regulation of intraspecific populations density 12 , 13 . Therefore, studying the intraspecific allelopathy of invasive plants, especially the autotoxicity, is of great significance for their invasion mechanism and control. Solanum rostratum Dunal is an annual invasive plant with strong invasiveness and has a strong inhibitory effect on native plants 14 , 15 (Fig. S1 ). The entire plant is prickly and contains toxic substances that may poison livestock and cause death 16 . S. rostratum is highly competitive for resources and significantly negatively impacts the environment and agriculture 17 , 18 . Moreover, S. rostratum is also the host plant of the pest potato beetle ( Leptinotarsa decemlineata ) and a potential host plant for the tomato brown rugose fruit virus, wihch can increase crop damage risk 19 , 20 . S. rostratum originates in North America and has since spread to South America, Asia, Europe, Africa, and Oceania 21 , 22 . In China, it has spread to Jilin, Beijing, Hebei, Shanxi, Inner Mongolia, Xinjiang, and other areas 23 , 24 . The research on this plant mainly focuses on its biological characteristics 21 , and potential hazards 25 , and allelopathy on native plants 26 – 27 . For example, the essential oil extracted from S. rostratum exhibited suppressive effect on seed germination and seedling growth of other species 17 , 28 . However, the intraspecific allelopathy of S. rostratum remains unclear. In Xinjiang, the plants of S. rostratum will wither and fall in October and they will be covered with snow in early November. By mid-March, when the snow melts, the secondary metabolites in litters may be released into the soil under the effects of leaching and decomposition (Fig. S1 ). So non-target metabolomics based on liquid chromatography-mass spectrometry (LC-MS/MS) was used to analyze the content of secondary metabolites in the soil of 9 sample sites in this invaded area. The results showed that the soil contained a large amount of secondary metabolites such as alkaloids, flavonols, amino acids, and amides (Fig. S1 ). Among them, the relative abunences of Quercetin 3'-methyl ether, Coumaroyl tyramine, 3-(4-Hydroxyphenyl)-N-[2-(4-hydroxyphenyl)-2-methoxyethyl]-acrylamide, Pyridoxine were relatively high. Additionally, these compounds are mostly poorly water-soluble and had been detected in the plants of the S. rostratum 29 , this might be caused by the release of secondary metabolites from the litter of S. rostratum into the soil. Therefore, we propose the following hypothesis: In the fragile arid ecosystem of Xinjiang, the chemical substances produced by the litter of S. rostratum can accumulate in the soil, thereby affecting the growth of its own seedlings. In this study, we aimed to (1) study the effect of different concentrations of litter ethanol extract of S. rostratum on its seedling growth; (2) detect the change of soil microorganisms and metabolites under different treatment; (3) analyse the correlation between soil microorganisms/metabolites and seedling growth indicators, discuss the mechanism of S. rostratum from the perspective of intraspecific allelopathy and provide theoretical support for formulating control strategies for the S. rostratum . Methods Collection and treatment of soil and plants Solanum rostratum and soil were collected from the Shuimogou District, Urumqi City, Xinjiang, China (43°49′ N, 87°46′ E), altitude is 950 m. S. rostratum was identified by Dr. Juan Qiu at the College of Life Sciences, Xinjiang Agricultural University. A voucher specimen (No. 20230620001) was deposited at the Specimen Museum of Xinjiang Agricultural University (Fig. S2). The soil was collected in the area without the growth of S. rostratum at the edge of invading area. Debris, such as gravel and residual roots, were removed from the soil, which was then passed through a 10-mesh sieve after air-drying and used for potted experiments. Ground the litter and sieved it through a 60-mesh sieve. Preparation of the ethanol extract of litter Litter (5012.53 g) grindings were soaked in 95% ethanol (1:4 w/v) for 24 h at 25℃, then filtered and collected, the extraction process was repeated seven times. The resulting extract was rotary evaporated at 50℃, which were then dried in an electrothermal constant-temperature dry box at 50℃ for 48 h to obtain the ethanol extract (316.62 g), with yields of 6.32% 30,31 . The extract were stored at 4℃ for subsequent experiments. Seedling growth experiment Solanum rostratum seeds were sterilized for 10 min in 3% sodium hypochlorite and rinsed 3–5 times with distilled water, then for 10 min in 75% ethanol and 3–5 times with distilled water. The method for breaking seed dormancy by Wei et al. 14 was slightly modified by immersing the seeds in a 400 mg/L gibberellin solution at a constant temperature of 30℃ for 24 h to break S. rostratum seed dormancy. Next, the ethanol extract was dissolved in distilled water to prepare a 10 g/L mother liquor, and perform gradient dilution to obtain solutions of 0.1, 1, and 10 g/L 32,33 . After which 10 seeds were sown in a 11.5-cm diameter and 9.5-cm high flowerpot filled with 500 g of soil to a depth of 1 cm and placed on a plant culture frame with 30℃ day/20℃ night, 12 h of light/12h of darkness, and 350 µmol/m 2 /s of photosynthetically active radiation. Watering with distilled water in the early stage. After the seedlings were unearthed, every 3 days, 30 mL of ethanol extract solution with concentration gradients of 0.1, 1, and 10 g/L (equivalent to the substances extracted from 0.0475 g, 0.475 g, and 4.75 g of litter, respectively) was added to each pot, and distilled water was used as a blank control. In total, 20 pots were used, each with 3 concentrations and 5 replicates, along with 5 control pots. Indicator measurement On the 50th day of the pot experiment, the photosynthetic indexes of seedlings were measured at 9 a.m. 34 . On the 55th day, the pot experiment was completed, and the root length (RL), plant height (PH), leaf area index (LAI), biomass (B, 30 replicates for each treatment of the above morphological indicators), antioxidant enzyme activity, and malondialdehyde (MDA) content of the seedlings were measured (10 replicates for each treatment of the above physiological index). Among them, the antioxidant enzyme activity includes superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) activity. Measure SOD 35 , POD 36 , CAT 37 , and MDA 38 according to previous methods. After the plant samples are harvested, mix all the soil in the pot evenly and remove impurities such as residual roots 39 . Collect the soil and divide it into three sub samples. The first soil sample is sieved after natural air drying for the determination of soil physical and chemical properties (3 replicates per treatment). Soil total carbon (TC) and organic carbon (SOC) was determined following the dry combustion method. Soil total nitrogen (TN) was determined following the Kjeldahl’s method. Soil total phosphorus (TP) was determined following the acid digestion method. Soil ammonium nitrogen (NH 4 + -N) was determined following the KCl extraction method. Soil pH is determined by a glass electrode with a soil/water ratio of 1:2.5 40 . Available phosphorus (AP) was measured following the Olsen method 41 . The second soil sample was sent to Hongxu Biotechnology Co, Ltd (Shanghai, China), which was used to determine soil metabolites (3 replicates per treatment). Accurately weigh an appropriate amount of sample into a 2 mL centrifuge tube, add 600 µL MeOH (Containing 2-Amino-3-(2-chloro-phenyl)-propionic acid (4 ppm), vortex for 30 s. Add steel balls and placed in a tissue grinder for 120 s at 50 Hz. Room temperature ultrasound for 10 min. Centrifuge for 10 min at 12,000 rpm and 4℃, filter the supernatant by 0.22-µm filter membrane and transfer into the detection bottle for LC-MS detection. The LC analysis was performed on a Vanquish UHPLC System (Thermo Fisher Scientific, USA). Chromatography was carried out with an ACQUITY UPLC ® HSS T3 (2.1×100 mm, 1.8 µm) (Waters, Milford, MA, USA, details of LC-MS/MS conditions is seen in the supplementary materials section). Convert the original mass spectrometer file to mzXML file format using the MSConvert tool in the Proteowizard software package (v3.0.8789) 42 . Using the R XCMS software package for peak detection, peak filtering, and peak alignment processing 43 , obtain a quantitative list of substances. The third soil sample was sent to Hongxu Biotechnology Co, Ltd (Shanghai, China), which was used to determine soil microbial (3 replicates per treatment). Extracting bacterial genomic DNA from soil samples using a genomic DNA isolation kit (Omega Bio tek, Norcross, GA, U.S.) The V3-V4 regions of the bacterial 16S rRNA gene were amplified with the primers 338F and 806R by a thermocycler PCR system (GeneAmp 9700, ABI, Foster, CA, U.S.), and Illumina sequencing was performed, followed by quality control of the raw fastq data. Low quality base and adapter sequences were trimmed, and the sequences were subjected to OTU clustering based on 97% similarity using Vsearch software (version 2.22.1) to obtain OTUs and feature tables. Select the representative sequence with the highest frequency from OTU clustering and annotate it using the Mothur and SSUrRNA databases from SILVA138 44 . Data analysis Seedling growth, soil physical and chemical properties data were organized using Microsoft Excel 2021 software (Microsoft Corporation, Redmond, WA, USA), and the data were analyzed using SPSS 25 software (SPSS Inc., Chicago, IL, USA) to compare the differences between treatments using the LSD method in analysis of variance. The data are expressed as mean ± standard deviation with the significance level set at α = 0.05. OriginPro 2021 software (OriginLab, Northampton, MA, USA) was used for graphing. The data of soil metabolites were analyzed using the R software package Ropls 45 for principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) to reduce the dimensionality of the sample data. The statistical significance of P.value was obtained by statistical test between groups. Finally, combined with P.value, VIP (OPLS-DA variable projection importance) and FC (multiple of difference between groups) to screen biomarker metabolites. By default, when P value 1, we think that metabolite were considered to have significant differential expression. Pathway enrichment analysis used the hypergeometric distribution enrichment analysis method to perform functional pathway enrichment and topological analysis of metabolites 46 . The identified metabolites in metabolomics were then mapped to the KEGG pathway for biological interpretation of higher-level systemic functions. The metabolites and corresponding pathways were visualized using KEGG Mapper tool. The statistical analysis and data visualization of soil bacteria were conducted in R, using R packages including vegan (v2.6-4), phyloss (v1.38.0), tidyverse (v1.3.2), ggpubr (v0.5.0), ComplexHeatmap (v2.10.0), and corrplot (v0.92). Alpha diversity was estimated using the ACE, Chao1, Shannon and Simpson indices. Principal coordinates analysis (PCoA) based on bray-curtis matrices with statistical significance determined by permutational multivariate analysis of variance (PERMANOVA) was conducted to assess the differences in beta diversity between groups. For comparing the relative abundance of different taxa between groups, linear discriminant analysis (LDA) effect size (LEfSe) method was performed with a p-value < 0.05 for the Kruskal-Wallis test and a size-effect threshold of 2.0 on the logarithmic LDA score. Results Effect of ethanol extract from the litter of S. rostratum on its own seedling growth The effect of ethanol extract from litter on seedling growth is shown in Fig. 1 . There was no significant difference in root length among the seedlings under various treatments ( p > 0.05). The plant height under CK, 0.1 and 1 g/L treatment was significantly higher than that under 10 g/L treatment ( p < 0.05). Compared with the CK, the plant height decreased by 37.46% under the 10 g/L treatment. The leaf area index and biomass under CK and 1 g/L treatment were significantly lower than those under 0.1 g/L treatment, but significantly higher than those under 10 g/L treatment ( p < 0.05). The leaf area index and biomass of the 0.1 g/L treatment increased by 42.22% and 33.53% respectively compared to the CK, while the 10 g/L treatment had the lowest, decreasing by 72.12% and 46.21% respectively compared to the control. The superoxide dismutase activity under CK and 1g/L treatment was significantly higher than that under 0.1 g/L treatment, but significantly lower than that under 10 g/L treatment ( p < 0.05). The 0.1g/L treatment decreased by 6.98% compared to CK, while the 10 g/L treatment increased by 15.87% compared to CK. The peroxidase activity under CK and 1g/L treatment was significantly lower than that under 10 g/L treatment ( p < 0.05), and the 10 g/L treatment increased by 56.82% compared to CK. The catalase activity under CK and 0.1 g/L treatments was significantly lower than that under 1 and 10 g/L treatments ( p < 0.05). Compared with CK, the 1 and 10 g/L treatment increased by 32.25% and 42.06%, respectively. The content of malondialdehyde under the treatment of CK, 0.1 and 1 g/L was significantly lower than that of 10 g/L ( p < 0.05). The 10 g/L treatment increased by 36.01% compared to CK. The net photosynthetic rate under CK treatment was significantly higher than the three treatments of 0.1, 1, and 10 g/L ( p < 0.05). Compared with CK, treatment with 1 g/L and 10 g/L resulted in a decrease of 52.15% and 68.82%, respectively. The transpiration rate and stomatal conductance of CK treatment were significantly higher than those of 0.1, 1, and 10 g/L treatments ( p < 0.05). The transpiration rate and stomatal conductance under 10 g/L treatment decreased by 63.04% and 78.08%, respectively, compared to the CK treatment. The intercellular CO 2 concentration under CK, 0.1 and 1 g/L treatment was significantly lower than that under 10 g/L treatment (p < 0.05). The 10g/L treatment increased by 95.30% compared to CK. Effect of ethanol extract from litter on soil physical and chemical properties The effect of different concentrations of litter treatment on soil physical and chemical properties vary (Table 1 ). There were no significant differences in total phosphorus, available phosphorus, and pH among different concentrations ( p > 0.05), but with increasing concentration, soil total carbon, total nitrogen, organic carbon, and ammonium nitrogen all increased, and there were significant differences ( p < 0.05). Among them, the soil total carbon and total nitrogen contents under 1 g/L and 10 g/L treatments were 11.41, 12.90 g/kg and 2.33, 2.44 g/kg, respectively, which increased by 3.16%, 16.64%, and 48.41%, 55.41% compared to CK, respectively. The content of soil organic carbon and ammonium nitrogen under the treatment of 10 g/L ethanol extract of litter was 8.01 g/kg and 7.83 mg/kg, respectively, which increased by 39.06% and 80.00% compared with CK. Table 1 Effect of ethanol extract from litter of Solanum rostratum on soil physical and chemical properties Concen tration (g/L) TC (g/kg) TN (g/kg) TP (g/kg) SOC (g/kg) NH 4 + -N (mg/kg) AP (mg/kg) pH CK 11.06 ± 0.33bc 1.57 ± 0.45b 0.35 ± 0.02a 5.76 ± 0.38b 4.35 ± 0.27b 5.54 ± 1.28a 7.67 ± 0.09a 0.1 10.70 ± 0.16c 1.75 ± 0.15b 0.32 ± 0.01a 5.95 ± 0.39b 4.92 ± 0.81b 5.85 ± 1.22a 7.44 ± 0.08a 1 11.41 ± 0.25b 2.33 ± 0.14a 0.32 ± 0.02a 6.06 ± 0.27b 4.58 ± 0.11b 5.38 ± 1.74a 7.68 ± 0.21a 10 12.90 ± 0.55a 2.44 ± 0.21a 0.33 ± 0.04a 8.01 ± 0.67a 7.83 ± 0.47a 4.73 ± 0.82a 7.56 ± 0.13a Note: TC: total carbon, TN: total nitrogen, TP: total phosphorus, SOC: soil organic matter, NH 4 + -N: ammonium nitrogen, AP: available phosphorus. Data are presented as mean ± SD. Different lowercase letters indicate significant differences between different treatment ( p < 0.05). Spearman test was used to evaluate the correlation between soil physical and chemical properties and seedling growth related indicators (Fig. 2 ). We found that ammonium nitrogen, soil organic matter, total carbon, and total nitrogen showed a negative correlation with seedling growth ( p < 0.05). Effect of ethanol extract from the litter of S. rostratum on soil metabolites Soil metabolite analysis was conducted on soil treated with ethanol extract from litter using non- target metabolomics, and a total of 515 compounds were identified (Table 2 ). Among them, the number of lipids and lipid molecules is the highest, reaching 164, while the number of lignans, new lignans, and related compounds is the lowest, with 2. Analysis of the relative abundance of metabolites in each treatment revealed that Lipids and lipid like molecules had the highest content, while Phenylpropanoids and polyketides had the lowest content. As the concentration of ethanol extract from litter increased, the content of Nucleosides, nucleotides, and analogues gradually increased. Table 2 The categories and quantities of soil metabolites treated with ethanol extract from the litter of Solanum rostratum . Metabolite categories Metabolite quantity Metabolite proportion (%) CK 0.1 g/L 1 g/L 10 g/L Lipids and lipid-like molecules 164 28.99 56.16 48.36 28.25 Organic acids and derivatives 37 5.03 3.17 3.17 6.69 Organoheterocyclic compounds 38 4.08 2.47 2.59 3.05 Benzenoids 45 5.51 5.51 5.17 8.79 Phenylpropanoids and polyketides 3 0.05 0.10 0.03 0.07 Organic oxygen compounds 44 7.69 4.34 6.12 8.92 Organic nitrogen compounds 15 8.39 4.37 8.41 13.20 Nucleosides, nucleotides, and analogues 4 0.03 0.16 0.26 0.83 Alkaloids and derivatives 3 0.47 0.34 0.19 0.91 Lignans, neolignans and related compounds 2 0.76 0.29 0.60 0.59 Organosulfur compounds 5 2.71 1.65 2.13 2.36 Hydrocarbon derivatives 3 0.40 0.39 0.25 0.38 Homogeneous non-metal compounds 6 0.58 0.39 0.46 0.55 Other 146 35.31 20.67 22.27 25.42 According to the PCA and OPLS-DA results (Fig. 3 a-d), the soil metabolites under the four treatments were differentiated, indicating that their metabolic characteristics were different. Differential metabolite screening can be performed based on the VIP values obtained. Further validate the reliability of the OPLS-DA model using permutation testing (Fig. 3 e, f). R 2 Y and Q 2 in both positive and negative ion modes were lower than the original model, indicating that the model is meaningful and can be used for subsequent analysis. Select differential metabolites based on P 1. There are 38 different metabolites produced by the four treatment (Fig. 3 g). In differential metabolite analysis, compared with CK treatment, 10 g/L upregulated 31 differential metabolites and downregulated 9 differential metabolites (Fig. 3 h). Cluster heatmap shows a overview of 38 different metabolic characteristics (Fig. 3 i). KEGG pathway enrichment analysis was performed on differential metabolites (Fig. 3 j), and the results showed that, Retrograde endocannabinoid signaling, Nitrogen metabolism, Carbapenem biosynthesis, Cyanoamino acid metabolism, Biosynthesis of various other secondary metabolites were the 5 metabolic pathways significantly enriched and most correlated. Spearman test was used to evaluate the correlation between differential metabolites and seedling growth related indicators (Fig. 4 ). We found that 8 metabolites including Imazethapyr, Sotalol, L-Glutamic acid, 4-isopropyl-7-methyloxepan-2-one, and eccysone palmate, were significant positively correlated with seedling growth ( p < 0.05). 25 metabolites including 2-Aminobenzoic acid, Rhizocticin A, and 1,3,4,6-Tetrachloro-1,4-cyclohexadiene, were significant negative correlated with seedling growth ( p < 0.05). Effect of ethanol extract from litter on soil microorganisms The sequencing results showed that under different concentrations of ethanol extract from litter, the bacterial community shared 1048 OTUs. The unique OTUs numbers of bacterial communities under different concentration treatments were 13, 11, 15, and 8, respectively (Fig. S3). All OTUs data were used for subsequent statistical analysis. The Chao1, ACE, Shannon, and Simpson indices of alpha diversity showed that 10 g/L of litter ethanol extract treatment (10 g/L) significantly reduced the alpha diversity of soil bacteria ( p < 0.05, Fig. 5 a-d). Compared with CK, 10 g/L of litter ethanol extract treatment reduced Chao1 index by 30.39%, ACE index by 30.92%, Shannon index by 35.98%, and Simpson index by 11.97%. PCoA and ANOSIM analyses also showed significant differences between the groups ( p < 0.05, Fig. 5 e-f). At the phylum level (Fig. 5 g), Proteobacteria had the highest relative abundance, followed by Bacteroidetes. However, 10 g/L treatment significantly affected the community structure of soil bacteria ( p < 0.05). Compared with CK, 10 g/L treatment increased the relative abundance of Proteobacteria by 83.83%, while the relative abundance of Bacteroidetes decreased by 77.51%. In addition, the relative abundance of other gate levels decreased under 10 g/L treatment. At the genus level (Fig. 5 h), the relative abundance of Pseudomonas was the highest, followed by Sphingobium . Similarly, there was a significant difference ( p < 0.05) between the 10 g/L 10 g/L treatment and CK. Compared with CK, the 10 g/L treatment increased the relative abundance of Pseudomonas by 104.99% and Sphingobium by 4355.45%. Using LEfSe analysis to further investigate the effect of ethanol extract from litter on soil bacterial community structure, a total of 30 biomarkers were identified (Fig. 5 i-j). The Gemmatimonas was identified as a biomarker under CK treatment. Under 0.1 g/L treatment, Gaiellales, Acidobbia, Solirubrobacterales, Pontibacters , Hymenobacteriaceae, Thermolipophilia, and Alphaprobacter were identified as biomarkers. Under 1 g/L treatment, Azospirillales, Sphingobium , Saccharimonadaceae, and TM7a were identified as biomarkers. Under 10 g/L treatment, Brevundimonas alba , Brevundimonas , Altererythrobacter , Novosphingobium resinovorum , and Novosphingobium were identified as biomarkers. Using differential analysis of metabolic pathway LEfSe to investigate the effect of ethanol extract from litter on soil bacterial community function, a total of 20 functional characteristics of differences were identified (Fig. 5 k). The soil metabolites under CK treatment are related to the process of synthesizing polysaccharide units in organisms. The soil metabolites under 0.1 g/L treatment are related to the process of homologous recombination, tetracycline biosynthesis, fatty acid biosynthesis, pyrimidine metabolism, drug metabolism-other enzymes, lipoic acid metabolism and biosynthesis of vancomycin group antibiotics. The soil metabolites under 1 g/L treatment are related to the process of D-Arginine and D-ornithine metabolism. The soil metabolites under 10 g/L treatment are related to the process of Propionic acid metabolism, phenylalanine metabolism, glyceride metabolism, xylene degradation, lysine degradation, valine, leucine, and isoleucine degradation, glycine, serine, and threonine metabolism, limonene and pinene degradation, fatty acid metabolism, benzoate degradation, and caprolactam degradation. Spearman test was used to evaluate the correlation between differential microorganisms and seedling growth related indicators (Fig. 6 ). Combined with the bacteria at genus and species levels with significant differences in LEfSe results, we found that Pontibacter and Gemmatimonas showed a positively correlated with seedling growth ( p < 0.05). And Brevundimonas alba , Brevundimonas , Altererythribacter , Novosphingobium resinovorum , and Novosphingobium showed a negative correlation with seedling growth ( p < 0.05) . Discussion In this study, the allelopathy intensity and concentration of ethanol extract from litter on seedlings were closely related, displayed a low-concentration promoting and high-concentration inhibitory effect. Other studies have also shown this 47 – 49 . Low concentration treatment significantly increased the leaf area index and biomass of seedlings, high concentration treatment significantly inhibited the plant height, leaf area index, biomass, net photosynthetic rate, transpiration rate, stomatal conductance of seedlings, and high concentration increased the antioxidant enzyme activity and malondialdehyde content of seedlings. This may be due to the slight interference of a small amount of allelochemicals in the low concentration treatment on the seedlings, triggering a self repair mechanism and ultimately exhibiting a promoting effect 50 , while the high concentration treatment has a high content of allelochemicals, damaging the internal structure of the seedlings 51 , affecting photosynthesis 52 , and ultimately inhibiting seedling growth. In this study, high concentration treatment of ethanol extract from the litter of S. rostratum significantly promoted soil total carbon, total nitrogen, organic carbon, and ammonium nitrogen content, indicating that litter decomposition affects soil soil physical and chemical properties, such as increasing soil soluble organic carbon content 53 , which is also true for invasive plants 54 . In addition, during the decomposition process of litter, allelochemicals are released into the soil 55 , which can also affect soil physical and chemical properties 56 . Therefore, the allelochemicals in the ethanol extract of S. rostratum litter may also have an impact on soil physical and chemical properties. Moreover, the overall changes in soil physical and chemical properties are negatively correlated with seedling growth, which confirms that the improvement of soil fertility cannot alleviate plant self toxicity 57 . Similarly, in other studies, the water extract treatment of Cinnamomum migao H. W. Li supplemented soil fertility, but did not alter the inhibitory effect of leaf water extract on seedling growth 51 . This may be due to the accumulation of a large amount of secondary metabolites in the soil, which can reduce the activity of soil microorganisms 58 . This study conducted metabolite analysis on soil treated with ethanol extract from litter, and 515 compounds were identified, of which 31 compounds were negatively correlated with seedling growth. Among them, 2-Aminobenzoic acid showed a negative correlation with the activity of superoxide dismutase activity and intercellular CO 2 concentration in seedlings. And The relative abundance of this substance was significantly higher in high concentration treatments than in other treatments. In addition, Previous studies have shown that 2-Aminobenzoic acid has inhibitory effect on the growth of Lactuca sativa and Arabidopsis thaliana seedlings 59 , 60 . Therefore, 2-Aminobenzoic acid is likely a potential autotoxins in the ethanol extract of S. rostratum litter. Additionally, alien invasive plants can release allelochemicals to the soil through litter, which can affect the structure and function of soil microbial community 61 , and soil microbial changes will affect plant growth and form plant-soil feedback 62 . In this study, high concentration of ethanol extract from S. rostratum litter reduced the diversity of soil bacteria and altered the community structure of soil bacteria. High diversity of soil microbial communities is beneficial for the stability and sustainability of ecosystems, while low diversity can lead to a decrease in ecosystem stability, making it more susceptible to external environmental disturbances 63 and making seedlings more susceptible to the inhibitory effects of autotoxins. This is consistent with previous research findings. For example, the autotoxins in Cucumis sativus reduced the diversity of rhizosphere bacteria, but increased fungal diversity, altered the composition of bacterial and fungal communities, and reduced the positive impact of cucumber rhizosphere microbiota on cucumber seedling growth 64 . In addition, the allelochemicals produced by invasive plants can reduce the number of microorganisms and thereby affect the growth of plants. For example, Alliaria petiolata can produce glucosinolate through the degradation of litter in the soil, indirectly changing the soil microbial community structure, resulting in a significant reduction in the amount of soil arbuscular mycorrhizal fungi, causing the gradual degradation of the local plant community 65 , 66 . And in this study, Brevundimonas alba , Brevundimonas , Altererythribacter , Novosphingobium resinovorum , and Novosphingobium showed a negative correlation with seedling growth. Interestingly, there are seventeen metabolites, which showed higher relative abundance in the soil samples treated at 10 mg/mL treatment, such as 2, 6-dibromophenol and palmitaldehyde, are positively correlated with these microorganism (Fig. S4). On the other hand, Pontibacter and Gemmatimonas showed a positively correlated with seedling growth. Some metabolites with higher abundance under low-concentration treatment, such as ecdysone palmitate, performanced a significant positive correlation with these microorganisms (Fig. S4). Conclusion The ethanol extract from the litter of S. rostratum displayed a low-concentration promoting and high-concentration inhibitory effect on seedling growth. And, ethanol extract from litter also affect the growth of seedlings by influencing the soil metabolites and microorganism. The above research results can provide theoretical support for the development of control strategies for S. rostratum . Declarations Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author Contribution Conceptualization, S. Wang and D. Tan; methodology, S. Wang; formal analysis, Y. Ma, H. Liu and L. Jiang; investigation, Y. Ma, L. Jiang, H. Liu and G. Zhai; resources, Y. Ma, and J. Qiu; data curation, Y. Ma, L. Jiang and S. L; writing—original draft preparation and the revision of the article, Y. Ma, L. Jiang, S. W; writing—review and editing, S. Wang and D. Tan; supervision, S. Wang and D. Tan; project administration, S. Wang and D. Tan; funding acquisition, S. Wang and D. Tan All the authors have read and agreed to the published version of the manuscript. Acknowledgements This research was supported by a special grant from the Natural Science Foundation of the Xinjiang Uygur Autonomous Region (grant number: 2023D01B37), the National Natural Science Foundation of China (32460684) and the Xinjiang Key Laboratory of Soil and Plant Ecological Processes (grant number: 23XJTRZW19). Data Availability The sequencing data have been deposited in the National Center for Biotechnology Information Sequence Read Archive database (http://www.ncbi.nlm.nih.gov/sra) with BioProject accession number PRJNA1274989. 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Data are presented as mean ± SD. Different lowercase letters indicate significant differences between different concentrations (\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05) .\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6829445/v1/94b94c295ed2442a13c700e0.png"},{"id":84916293,"identity":"acdb22cc-7408-4f20-a68e-95e56f094d18","added_by":"auto","created_at":"2025-06-18 18:23:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":931603,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis between soil physical and chemical properties and seedling growth indicators. LAI: leaf area index, RL: root length, PH: plant height, B:biomass, Pn: net photosynthetic rate, Tr: transpiration rate, Gs: stomatal conductance, Ci: intercellular CO\u003csub\u003e2\u003c/sub\u003e concentration, SOD: superoxide dismutase activity, POD: peroxidase activity, CAT: catalase activity, MDA: malondialdehyde content, TC: total carbon, TN: total nitrogen, TP: total phosphorus, SOC: soil organic matter, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N: ammonium nitrogen, AP: available phosphorus. Significance is indicated as * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6829445/v1/ff99d2bcf12fd2f3e9616ee9.png"},{"id":84916290,"identity":"ea8d9d6f-eba4-464a-acc8-6e87175da7e6","added_by":"auto","created_at":"2025-06-18 18:23:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":601792,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of ethanol extract from \u003cem\u003eSolanum rostratum \u003c/em\u003elitter on soil metabolites. \u003cstrong\u003ea\u003c/strong\u003e PCA analysis in positive ion mode, \u003cstrong\u003eb\u003c/strong\u003e PCA analysis in negative ion mode, \u003cstrong\u003ec\u003c/strong\u003e OPLS-DA analysis in positive ion mode, \u003cstrong\u003ed\u003c/strong\u003eOPLS-DA analysis in negative ion mode, \u003cstrong\u003ee\u003c/strong\u003e permutation test in positive ion mode, \u003cstrong\u003ef \u003c/strong\u003epermutation test in negative ion mode,\u003cstrong\u003e g\u003c/strong\u003e upset venn diagram of differential metabolites, \u003cstrong\u003eh\u003c/strong\u003e Statistical bar chart of differential metabolites, \u003cstrong\u003ei \u003c/strong\u003ecluster heat map of differential metabolites, \u003cstrong\u003ej\u003c/strong\u003e bubble chart of factors influencing metabolic pathways.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6829445/v1/d2edc94837bd7962dffc65d9.png"},{"id":84916454,"identity":"2024fb2d-361b-4569-99cd-743ddb5dcfdf","added_by":"auto","created_at":"2025-06-18 18:31:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":250190,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis between differential metabolites and seedling growth indicators. LAI: leaf area index, RL: root length, PH: plant height, B: biomass, Pn: net photosynthetic rate, Tr: transpiration rate, Gs: stomatal conductance, Ci: intercellular CO\u003csub\u003e2\u003c/sub\u003e concentration, SOD: superoxide dismutase activity, POD: peroxidase activity, CAT: catalase activity, MDA: malondialdehyde content. Significance is indicated as * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6829445/v1/1c463ecbcf540586cc784159.png"},{"id":84916291,"identity":"2979b37e-8f22-4c87-8fde-95b0d3d2f47d","added_by":"auto","created_at":"2025-06-18 18:23:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":660430,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of ethanol extract from \u003cem\u003eSolanum rostratum \u003c/em\u003elitter on soil bacteria. \u003cstrong\u003ea\u003c/strong\u003e Chao1 index, \u003cstrong\u003eb\u003c/strong\u003e ACE index, \u003cstrong\u003ec\u003c/strong\u003e Shannon index, \u003cstrong\u003ed\u003c/strong\u003e Simpson index, \u003cstrong\u003ee\u003c/strong\u003e principal coordinates analysis (PCoA), \u003cstrong\u003ef\u003c/strong\u003eanalysis of similarities (ANOSIM), \u003cstrong\u003eg\u003c/strong\u003e relative abundance of soil bacteria at the phylum level, \u003cstrong\u003eh\u003c/strong\u003e relative abundance of soil bacteria at the genus level, \u003cstrong\u003ei \u003c/strong\u003ecladogram of LEfSe analysis, \u003cstrong\u003ej \u003c/strong\u003ebar plot of LEfSe analysis, \u003cstrong\u003ek\u003c/strong\u003e differential analysis of metabolic pathway LEfSe. Data are presented as mean ± SD. Different lowercase letters indicate significant differences (\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05) between different concentrations.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6829445/v1/0a3f1a1ca0e3402105d6767e.png"},{"id":84916296,"identity":"39a4e4af-d59c-4b16-8da1-bfd3c8a4b00a","added_by":"auto","created_at":"2025-06-18 18:23:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":99869,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis between differential microorganisms and seedling growth indicators. LAI: leaf area index, RL: root length, PH: plant height, B:biomass, Pn: net photosynthetic rate, Tr: transpiration rate, Gs: stomatal conductance, Ci: intercellular CO\u003csub\u003e2\u003c/sub\u003e concentration, SOD: superoxide dismutase activity; POD: peroxidase activity, CAT: catalase activity, MDA: malondialdehyde content. Significance is indicated as * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6829445/v1/3b1451ef906df59ac31e0938.png"},{"id":101152427,"identity":"e2edc779-8d75-4c04-95b2-040b5ea69001","added_by":"auto","created_at":"2026-01-26 16:11:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4038596,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6829445/v1/628e5f18-9b78-4408-b569-17f7be678542.pdf"},{"id":84916314,"identity":"e3bb93c0-35b7-4d5b-8b79-97a798ea7a68","added_by":"auto","created_at":"2025-06-18 18:23:47","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":54723204,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-6829445/v1/b6ddd62e44e2577f4f548f1b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effect of Solanum rostratum Dunal litter extract on its seedling growth","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlien invasive plants are plants that spread from their original place to another environment through natural or human means to settle, reproduce and spread, and eventually significantly affect the ecological environment of the place of migration\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Now the the invasion mechanism and control measures of invasive plants are one of the important contents of current research. New weapon hypothesis holds that the invasive alien plant can produce some allelochemicals, which are released into the environment through root secretion and litter, and inhibit the growth of native plants\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Allelopathy refers to the process in which plants release chemicals into the surrounding environment, affecting the growth of surrounding plants\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Allelopathy can be divided into interspecific allelopathy and intraspecific allelopathy\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. On the one hand, invasive alien plants can alter the chemical composition of the soil through root secretions and decomposition from litter, thereby inhibiting seed germination and seedling growth of native plants\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. On the other hand, the chemical substances produced by invasive plants can affect the population size, community structure or function of the soil microorganisms, which can disturb the interaction and symbiotic relationship between plants and soil microorganisms, and then promote or inhibit their diffusion and spread\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Studies have found that the extracts of invasive plants can display stronger allelopathic activity on the germination and seedling growth of native species, while performed little autotoxic effects\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. However, allelopathy produced by invasive species does not necessarily remain unchanged during invasion\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. For example, the survival rate, biomass and competitiveness of invasive species are lower in environments with longer invasion time\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In addition, autotoxicity may occur in invasive plants, which is significant for the regulation of intraspecific populations density\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Therefore, studying the intraspecific allelopathy of invasive plants, especially the autotoxicity, is of great significance for their invasion mechanism and control.\u003c/p\u003e \u003cp\u003e \u003cem\u003eSolanum rostratum\u003c/em\u003e Dunal is an annual invasive plant with strong invasiveness and has a strong inhibitory effect on native plants\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e (Fig.\u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The entire plant is prickly and contains toxic substances that may poison livestock and cause death\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eS. rostratum\u003c/em\u003e is highly competitive for resources and significantly negatively impacts the environment and agriculture\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Moreover, \u003cem\u003eS. rostratum\u003c/em\u003e is also the host plant of the pest potato beetle (\u003cem\u003eLeptinotarsa decemlineata\u003c/em\u003e) and a potential host plant for the tomato brown rugose fruit virus, wihch can increase crop damage risk\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eS. rostratum\u003c/em\u003e originates in North America and has since spread to South America, Asia, Europe, Africa, and Oceania\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In China, it has spread to Jilin, Beijing, Hebei, Shanxi, Inner Mongolia, Xinjiang, and other areas\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The research on this plant mainly focuses on its biological characteristics\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, and potential hazards\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, and allelopathy on native plants\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. For example, the essential oil extracted from \u003cem\u003eS. rostratum\u003c/em\u003e exhibited suppressive effect on seed germination and seedling growth of other species\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. However, the intraspecific allelopathy of \u003cem\u003eS. rostratum\u003c/em\u003e remains unclear. In Xinjiang, the plants of \u003cem\u003eS. rostratum\u003c/em\u003e will wither and fall in October and they will be covered with snow in early November. By mid-March, when the snow melts, the secondary metabolites in litters may be released into the soil under the effects of leaching and decomposition (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). So non-target metabolomics based on liquid chromatography-mass spectrometry (LC-MS/MS) was used to analyze the content of secondary metabolites in the soil of 9 sample sites in this invaded area. The results showed that the soil contained a large amount of secondary metabolites such as alkaloids, flavonols, amino acids, and amides (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Among them, the relative abunences of Quercetin 3'-methyl ether, Coumaroyl tyramine, 3-(4-Hydroxyphenyl)-N-[2-(4-hydroxyphenyl)-2-methoxyethyl]-acrylamide, Pyridoxine were relatively high. Additionally, these compounds are mostly poorly water-soluble and had been detected in the plants of the \u003cem\u003eS. rostratum\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, this might be caused by the release of secondary metabolites from the litter of \u003cem\u003eS. rostratum\u003c/em\u003e into the soil. Therefore, we propose the following hypothesis: In the fragile arid ecosystem of Xinjiang, the chemical substances produced by the litter of \u003cem\u003eS. rostratum\u003c/em\u003e can accumulate in the soil, thereby affecting the growth of its own seedlings.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to (1) study the effect of different concentrations of litter ethanol extract of \u003cem\u003eS. rostratum\u003c/em\u003e on its seedling growth; (2) detect the change of soil microorganisms and metabolites under different treatment; (3) analyse the correlation between soil microorganisms/metabolites and seedling growth indicators, discuss the mechanism of \u003cem\u003eS. rostratum\u003c/em\u003e from the perspective of intraspecific allelopathy and provide theoretical support for formulating control strategies for the \u003cem\u003eS. rostratum\u003c/em\u003e.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCollection and treatment of soil and plants\u003c/h2\u003e \u003cp\u003e \u003cem\u003eSolanum rostratum\u003c/em\u003e and soil were collected from the Shuimogou District, Urumqi City, Xinjiang, China (43\u0026deg;49\u0026prime; N, 87\u0026deg;46\u0026prime; E), altitude is 950 m. \u003cem\u003eS. rostratum\u003c/em\u003e was identified by Dr. Juan Qiu at the College of Life Sciences, Xinjiang Agricultural University. A voucher specimen (No. 20230620001) was deposited at the Specimen Museum of Xinjiang Agricultural University (Fig. S2). The soil was collected in the area without the growth of \u003cem\u003eS. rostratum\u003c/em\u003e at the edge of invading area. Debris, such as gravel and residual roots, were removed from the soil, which was then passed through a 10-mesh sieve after air-drying and used for potted experiments. Ground the litter and sieved it through a 60-mesh sieve.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePreparation of the ethanol extract of litter\u003c/h3\u003e\n\u003cp\u003eLitter (5012.53 g) grindings were soaked in 95% ethanol (1:4 w/v) for 24 h at 25℃, then filtered and collected, the extraction process was repeated seven times. The resulting extract was rotary evaporated at 50℃, which were then dried in an electrothermal constant-temperature dry box at 50℃ for 48 h to obtain the ethanol extract (316.62 g), with yields of 6.32%\u003csup\u003e30,31\u003c/sup\u003e. The extract were stored at 4℃ for subsequent experiments.\u003c/p\u003e\n\u003ch3\u003eSeedling growth experiment\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eSolanum rostratum\u003c/em\u003e seeds were sterilized for 10 min in 3% sodium hypochlorite and rinsed 3\u0026ndash;5 times with distilled water, then for 10 min in 75% ethanol and 3\u0026ndash;5 times with distilled water. The method for breaking seed dormancy by Wei et al.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e was slightly modified by immersing the seeds in a 400 mg/L gibberellin solution at a constant temperature of 30℃ for 24 h to break \u003cem\u003eS. rostratum\u003c/em\u003e seed dormancy. Next, the ethanol extract was dissolved in distilled water to prepare a 10 g/L mother liquor, and perform gradient dilution to obtain solutions of 0.1, 1, and 10 g/L\u003csup\u003e32,33\u003c/sup\u003e. After which 10 seeds were sown in a 11.5-cm diameter and 9.5-cm high flowerpot filled with 500 g of soil to a depth of 1 cm and placed on a plant culture frame with 30℃ day/20℃ night, 12 h of light/12h of darkness, and 350 \u0026micro;mol/m\u003csup\u003e2\u003c/sup\u003e/s of photosynthetically active radiation. Watering with distilled water in the early stage. After the seedlings were unearthed, every 3 days, 30 mL of ethanol extract solution with concentration gradients of 0.1, 1, and 10 g/L (equivalent to the substances extracted from 0.0475 g, 0.475 g, and 4.75 g of litter, respectively) was added to each pot, and distilled water was used as a blank control. In total, 20 pots were used, each with 3 concentrations and 5 replicates, along with 5 control pots.\u003c/p\u003e\n\u003ch3\u003eIndicator measurement\u003c/h3\u003e\n\u003cp\u003eOn the 50th day of the pot experiment, the photosynthetic indexes of seedlings were measured at 9 a.m.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. On the 55th day, the pot experiment was completed, and the root length (RL), plant height (PH), leaf area index (LAI), biomass (B, 30 replicates for each treatment of the above morphological indicators), antioxidant enzyme activity, and malondialdehyde (MDA) content of the seedlings were measured (10 replicates for each treatment of the above physiological index). Among them, the antioxidant enzyme activity includes superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) activity. Measure SOD\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, POD\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, CAT\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, and MDA\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e according to previous methods.\u003c/p\u003e \u003cp\u003eAfter the plant samples are harvested, mix all the soil in the pot evenly and remove impurities such as residual roots\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Collect the soil and divide it into three sub samples.\u003c/p\u003e \u003cp\u003eThe first soil sample is sieved after natural air drying for the determination of soil physical and chemical properties (3 replicates per treatment). Soil total carbon (TC) and organic carbon (SOC) was determined following the dry combustion method. Soil total nitrogen (TN) was determined following the Kjeldahl\u0026rsquo;s method. Soil total phosphorus (TP) was determined following the acid digestion method. Soil ammonium nitrogen (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N) was determined following the KCl extraction method. Soil pH is determined by a glass electrode with a soil/water ratio of 1:2.5\u003csup\u003e40\u003c/sup\u003e. Available phosphorus (AP) was measured following the Olsen method\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe second soil sample was sent to Hongxu Biotechnology Co, Ltd (Shanghai, China), which was used to determine soil metabolites (3 replicates per treatment). Accurately weigh an appropriate amount of sample into a 2 mL centrifuge tube, add 600 \u0026micro;L MeOH (Containing 2-Amino-3-(2-chloro-phenyl)-propionic acid (4 ppm), vortex for 30 s. Add steel balls and placed in a tissue grinder for 120 s at 50 Hz. Room temperature ultrasound for 10 min. Centrifuge for 10 min at 12,000 rpm and 4℃, filter the supernatant by 0.22-\u0026micro;m filter membrane and transfer into the detection bottle for LC-MS detection. The LC analysis was performed on a Vanquish UHPLC System (Thermo Fisher Scientific, USA). Chromatography was carried out with an ACQUITY UPLC \u0026reg; HSS T3 (2.1\u0026times;100 mm, 1.8 \u0026micro;m) (Waters, Milford, MA, USA, details of LC-MS/MS conditions is seen in the supplementary materials section). Convert the original mass spectrometer file to mzXML file format using the MSConvert tool in the Proteowizard software package (v3.0.8789)\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Using the R XCMS software package for peak detection, peak filtering, and peak alignment processing\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, obtain a quantitative list of substances.\u003c/p\u003e \u003cp\u003eThe third soil sample was sent to Hongxu Biotechnology Co, Ltd (Shanghai, China), which was used to determine soil microbial (3 replicates per treatment). Extracting bacterial genomic DNA from soil samples using a genomic DNA isolation kit (Omega Bio tek, Norcross, GA, U.S.) The V3-V4 regions of the bacterial 16S rRNA gene were amplified with the primers 338F and 806R by a thermocycler PCR system (GeneAmp 9700, ABI, Foster, CA, U.S.), and Illumina sequencing was performed, followed by quality control of the raw fastq data. Low quality base and adapter sequences were trimmed, and the sequences were subjected to OTU clustering based on 97% similarity using Vsearch software (version 2.22.1) to obtain OTUs and feature tables. Select the representative sequence with the highest frequency from OTU clustering and annotate it using the Mothur and SSUrRNA databases from SILVA138\u003csup\u003e44\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eSeedling growth, soil physical and chemical properties data were organized using Microsoft Excel 2021 software (Microsoft Corporation, Redmond, WA, USA), and the data were analyzed using SPSS 25 software (SPSS Inc., Chicago, IL, USA) to compare the differences between treatments using the LSD method in analysis of variance. The data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation with the significance level set at α\u0026thinsp;=\u0026thinsp;0.05. OriginPro 2021 software (OriginLab, Northampton, MA, USA) was used for graphing.\u003c/p\u003e \u003cp\u003eThe data of soil metabolites were analyzed using the R software package Ropls\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e for principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) to reduce the dimensionality of the sample data. The statistical significance of P.value was obtained by statistical test between groups. Finally, combined with P.value, VIP (OPLS-DA variable projection importance) and FC (multiple of difference between groups) to screen biomarker metabolites. By default, when P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and VIP value\u0026thinsp;\u0026gt;\u0026thinsp;1, we think that metabolite were considered to have significant differential expression. Pathway enrichment analysis used the hypergeometric distribution enrichment analysis method to perform functional pathway enrichment and topological analysis of metabolites\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. The identified metabolites in metabolomics were then mapped to the KEGG pathway for biological interpretation of higher-level systemic functions. The metabolites and corresponding pathways were visualized using KEGG Mapper tool.\u003c/p\u003e \u003cp\u003eThe statistical analysis and data visualization of soil bacteria were conducted in R, using R packages including vegan (v2.6-4), phyloss (v1.38.0), tidyverse (v1.3.2), ggpubr (v0.5.0), ComplexHeatmap (v2.10.0), and corrplot (v0.92). Alpha diversity was estimated using the ACE, Chao1, Shannon and Simpson indices. Principal coordinates analysis (PCoA) based on bray-curtis matrices with statistical significance determined by permutational multivariate analysis of variance (PERMANOVA) was conducted to assess the differences in beta diversity between groups. For comparing the relative abundance of different taxa between groups, linear discriminant analysis (LDA) effect size (LEfSe) method was performed with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for the Kruskal-Wallis test and a size-effect threshold of 2.0 on the logarithmic LDA score.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eEffect of ethanol extract from the litter of\u003c/b\u003e \u003cb\u003eS. rostratum\u003c/b\u003e \u003cb\u003eon its own seedling growth\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe effect of ethanol extract from litter on seedling growth is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There was no significant difference in root length among the seedlings under various treatments (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The plant height under CK, 0.1 and 1 g/L treatment was significantly higher than that under 10 g/L treatment (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Compared with the CK, the plant height decreased by 37.46% under the 10 g/L treatment. The leaf area index and biomass under CK and 1 g/L treatment were significantly lower than those under 0.1 g/L treatment, but significantly higher than those under 10 g/L treatment (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The leaf area index and biomass of the 0.1 g/L treatment increased by 42.22% and 33.53% respectively compared to the CK, while the 10 g/L treatment had the lowest, decreasing by 72.12% and 46.21% respectively compared to the control.\u003c/p\u003e \u003cp\u003eThe superoxide dismutase activity under CK and 1g/L treatment was significantly higher than that under 0.1 g/L treatment, but significantly lower than that under 10 g/L treatment (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The 0.1g/L treatment decreased by 6.98% compared to CK, while the 10 g/L treatment increased by 15.87% compared to CK. The peroxidase activity under CK and 1g/L treatment was significantly lower than that under 10 g/L treatment (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and the 10 g/L treatment increased by 56.82% compared to CK. The catalase activity under CK and 0.1 g/L treatments was significantly lower than that under 1 and 10 g/L treatments (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Compared with CK, the 1 and 10 g/L treatment increased by 32.25% and 42.06%, respectively. The content of malondialdehyde under the treatment of CK, 0.1 and 1 g/L was significantly lower than that of 10 g/L (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The 10 g/L treatment increased by 36.01% compared to CK. The net photosynthetic rate under CK treatment was significantly higher than the three treatments of 0.1, 1, and 10 g/L (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Compared with CK, treatment with 1 g/L and 10 g/L resulted in a decrease of 52.15% and 68.82%, respectively. The transpiration rate and stomatal conductance of CK treatment were significantly higher than those of 0.1, 1, and 10 g/L treatments (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The transpiration rate and stomatal conductance under 10 g/L treatment decreased by 63.04% and 78.08%, respectively, compared to the CK treatment. The intercellular CO\u003csub\u003e2\u003c/sub\u003e concentration under CK, 0.1 and 1 g/L treatment was significantly lower than that under 10 g/L treatment (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The 10g/L treatment increased by 95.30% compared to CK.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eEffect of ethanol extract from litter on soil physical and chemical properties\u003c/h3\u003e\n\u003cp\u003eThe effect of different concentrations of litter treatment on soil physical and chemical properties vary (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There were no significant differences in total phosphorus, available phosphorus, and pH among different concentrations (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), but with increasing concentration, soil total carbon, total nitrogen, organic carbon, and ammonium nitrogen all increased, and there were significant differences (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Among them, the soil total carbon and total nitrogen contents under 1 g/L and 10 g/L treatments were 11.41, 12.90 g/kg and 2.33, 2.44 g/kg, respectively, which increased by 3.16%, 16.64%, and 48.41%, 55.41% compared to CK, respectively. The content of soil organic carbon and ammonium nitrogen under the treatment of 10 g/L ethanol extract of litter was 8.01 g/kg and 7.83 mg/kg, respectively, which increased by 39.06% and 80.00% compared with CK.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of ethanol extract from litter of \u003cem\u003eSolanum rostratum\u003c/em\u003e on soil physical and chemical properties\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcen\u003c/p\u003e \u003cp\u003etration\u003c/p\u003e \u003cp\u003e(g/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003cp\u003e(g/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003cp\u003e(g/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTP\u003c/p\u003e \u003cp\u003e(g/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSOC\u003c/p\u003e \u003cp\u003e(g/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAP\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.85\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote: TC: total carbon, TN: total nitrogen, TP: total phosphorus, SOC: soil organic matter, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N: ammonium nitrogen, AP: available phosphorus. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Different lowercase letters indicate significant differences between different treatment (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSpearman test was used to evaluate the correlation between soil physical and chemical properties and seedling growth related indicators (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). We found that ammonium nitrogen, soil organic matter, total carbon, and total nitrogen showed a negative correlation with seedling growth (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eEffect of ethanol extract from the litter of\u003c/b\u003e \u003cb\u003eS. rostratum\u003c/b\u003e \u003cb\u003eon soil metabolites\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSoil metabolite analysis was conducted on soil treated with ethanol extract from litter using non- target metabolomics, and a total of 515 compounds were identified (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among them, the number of lipids and lipid molecules is the highest, reaching 164, while the number of lignans, new lignans, and related compounds is the lowest, with 2. Analysis of the relative abundance of metabolites in each treatment revealed that Lipids and lipid like molecules had the highest content, while Phenylpropanoids and polyketides had the lowest content. As the concentration of ethanol extract from litter increased, the content of Nucleosides, nucleotides, and analogues gradually increased.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe categories and quantities of soil metabolites treated with ethanol extract from the litter of \u003cem\u003eSolanum rostratum\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMetabolite categories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMetabolite quantity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eMetabolite proportion (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1 g/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 g/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 g/L\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipids and lipid-like molecules\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganic acids and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganoheterocyclic compounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzenoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenylpropanoids and polyketides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganic oxygen compounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganic nitrogen compounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNucleosides, nucleotides, and analogues\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlkaloids and derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLignans, neolignans and related compounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganosulfur compounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydrocarbon derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomogeneous non-metal compounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAccording to the PCA and OPLS-DA results (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-d), the soil metabolites under the four treatments were differentiated, indicating that their metabolic characteristics were different. Differential metabolite screening can be performed based on the VIP values obtained. Further validate the reliability of the OPLS-DA model using permutation testing (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee, f). R\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003eY and Q\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e in both positive and negative ion modes were lower than the original model, indicating that the model is meaningful and can be used for subsequent analysis. Select differential metabolites based on \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and VIP\u0026thinsp;\u0026gt;\u0026thinsp;1. There are 38 different metabolites produced by the four treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg). In differential metabolite analysis, compared with CK treatment, 10 g/L upregulated 31 differential metabolites and downregulated 9 differential metabolites (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eh). Cluster heatmap shows a overview of 38 different metabolic characteristics (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ei). KEGG pathway enrichment analysis was performed on differential metabolites (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ej), and the results showed that, Retrograde endocannabinoid signaling, Nitrogen metabolism, Carbapenem biosynthesis, Cyanoamino acid metabolism, Biosynthesis of various other secondary metabolites were the 5 metabolic pathways significantly enriched and most correlated.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSpearman test was used to evaluate the correlation between differential metabolites and seedling growth related indicators (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). We found that 8 metabolites including Imazethapyr, Sotalol, L-Glutamic acid, 4-isopropyl-7-methyloxepan-2-one, and eccysone palmate, were significant positively correlated with seedling growth (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). 25 metabolites including 2-Aminobenzoic acid, Rhizocticin A, and 1,3,4,6-Tetrachloro-1,4-cyclohexadiene, were significant negative correlated with seedling growth (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eEffect of ethanol extract from litter on soil microorganisms\u003c/h3\u003e\n\u003cp\u003eThe sequencing results showed that under different concentrations of ethanol extract from litter, the bacterial community shared 1048 OTUs. The unique OTUs numbers of bacterial communities under different concentration treatments were 13, 11, 15, and 8, respectively (Fig. S3). All OTUs data were used for subsequent statistical analysis.\u003c/p\u003e \u003cp\u003eThe Chao1, ACE, Shannon, and Simpson indices of alpha diversity showed that 10 g/L of litter ethanol extract treatment (10 g/L) significantly reduced the alpha diversity of soil bacteria (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-d). Compared with CK, 10 g/L of litter ethanol extract treatment reduced Chao1 index by 30.39%, ACE index by 30.92%, Shannon index by 35.98%, and Simpson index by 11.97%. PCoA and ANOSIM analyses also showed significant differences between the groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee-f).\u003c/p\u003e \u003cp\u003eAt the phylum level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eg), Proteobacteria had the highest relative abundance, followed by Bacteroidetes. However, 10 g/L treatment significantly affected the community structure of soil bacteria (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Compared with CK, 10 g/L treatment increased the relative abundance of Proteobacteria by 83.83%, while the relative abundance of Bacteroidetes decreased by 77.51%. In addition, the relative abundance of other gate levels decreased under 10 g/L treatment. At the genus level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eh), the relative abundance of \u003cem\u003ePseudomonas\u003c/em\u003e was the highest, followed by \u003cem\u003eSphingobium\u003c/em\u003e. Similarly, there was a significant difference (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between the 10 g/L 10 g/L treatment and CK. Compared with CK, the 10 g/L treatment increased the relative abundance of Pseudomonas by 104.99% and Sphingobium by 4355.45%.\u003c/p\u003e \u003cp\u003eUsing LEfSe analysis to further investigate the effect of ethanol extract from litter on soil bacterial community structure, a total of 30 biomarkers were identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ei-j). The \u003cem\u003eGemmatimonas\u003c/em\u003e was identified as a biomarker under CK treatment. Under 0.1 g/L treatment, Gaiellales, Acidobbia, Solirubrobacterales, \u003cem\u003ePontibacters\u003c/em\u003e, Hymenobacteriaceae, Thermolipophilia, and Alphaprobacter were identified as biomarkers. Under 1 g/L treatment, Azospirillales, \u003cem\u003eSphingobium\u003c/em\u003e, Saccharimonadaceae, and \u003cem\u003eTM7a\u003c/em\u003e were identified as biomarkers. Under 10 g/L treatment, \u003cem\u003eBrevundimonas alba\u003c/em\u003e, \u003cem\u003eBrevundimonas\u003c/em\u003e, \u003cem\u003eAltererythrobacter\u003c/em\u003e, \u003cem\u003eNovosphingobium resinovorum\u003c/em\u003e, and \u003cem\u003eNovosphingobium\u003c/em\u003e were identified as biomarkers.\u003c/p\u003e \u003cp\u003eUsing differential analysis of metabolic pathway LEfSe to investigate the effect of ethanol extract from litter on soil bacterial community function, a total of 20 functional characteristics of differences were identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ek). The soil metabolites under CK treatment are related to the process of synthesizing polysaccharide units in organisms. The soil metabolites under 0.1 g/L treatment are related to the process of homologous recombination, tetracycline biosynthesis, fatty acid biosynthesis, pyrimidine metabolism, drug metabolism-other enzymes, lipoic acid metabolism and biosynthesis of vancomycin group antibiotics. The soil metabolites under 1 g/L treatment are related to the process of D-Arginine and D-ornithine metabolism. The soil metabolites under 10 g/L treatment are related to the process of Propionic acid metabolism, phenylalanine metabolism, glyceride metabolism, xylene degradation, lysine degradation, valine, leucine, and isoleucine degradation, glycine, serine, and threonine metabolism, limonene and pinene degradation, fatty acid metabolism, benzoate degradation, and caprolactam degradation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSpearman test was used to evaluate the correlation between differential microorganisms and seedling growth related indicators (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Combined with the bacteria at genus and species levels with significant differences in LEfSe results, we found that \u003cem\u003ePontibacter\u003c/em\u003e and \u003cem\u003eGemmatimonas\u003c/em\u003e showed a positively correlated with seedling growth (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). And \u003cem\u003eBrevundimonas alba\u003c/em\u003e, \u003cem\u003eBrevundimonas\u003c/em\u003e, \u003cem\u003eAltererythribacter\u003c/em\u003e, \u003cem\u003eNovosphingobium resinovorum\u003c/em\u003e, and \u003cem\u003eNovosphingobium\u003c/em\u003e showed a negative correlation with seedling growth (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) .\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, the allelopathy intensity and concentration of ethanol extract from litter on seedlings were closely related, displayed a low-concentration promoting and high-concentration inhibitory effect. Other studies have also shown this\u003csup\u003e\u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Low concentration treatment significantly increased the leaf area index and biomass of seedlings, high concentration treatment significantly inhibited the plant height, leaf area index, biomass, net photosynthetic rate, transpiration rate, stomatal conductance of seedlings, and high concentration increased the antioxidant enzyme activity and malondialdehyde content of seedlings. This may be due to the slight interference of a small amount of allelochemicals in the low concentration treatment on the seedlings, triggering a self repair mechanism and ultimately exhibiting a promoting effect\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, while the high concentration treatment has a high content of allelochemicals, damaging the internal structure of the seedlings\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, affecting photosynthesis\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e, and ultimately inhibiting seedling growth.\u003c/p\u003e \u003cp\u003eIn this study, high concentration treatment of ethanol extract from the litter of \u003cem\u003eS. rostratum\u003c/em\u003e significantly promoted soil total carbon, total nitrogen, organic carbon, and ammonium nitrogen content, indicating that litter decomposition affects soil soil physical and chemical properties, such as increasing soil soluble organic carbon content\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, which is also true for invasive plants\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. In addition, during the decomposition process of litter, allelochemicals are released into the soil\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, which can also affect soil physical and chemical properties\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Therefore, the allelochemicals in the ethanol extract of \u003cem\u003eS. rostratum\u003c/em\u003e litter may also have an impact on soil physical and chemical properties. Moreover, the overall changes in soil physical and chemical properties are negatively correlated with seedling growth, which confirms that the improvement of soil fertility cannot alleviate plant self toxicity\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. Similarly, in other studies, the water extract treatment of \u003cem\u003eCinnamomum migao\u003c/em\u003e H. W. Li supplemented soil fertility, but did not alter the inhibitory effect of leaf water extract on seedling growth\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. This may be due to the accumulation of a large amount of secondary metabolites in the soil, which can reduce the activity of soil microorganisms\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study conducted metabolite analysis on soil treated with ethanol extract from litter, and 515 compounds were identified, of which 31 compounds were negatively correlated with seedling growth. Among them, 2-Aminobenzoic acid showed a negative correlation with the activity of superoxide dismutase activity and intercellular CO\u003csub\u003e2\u003c/sub\u003e concentration in seedlings. And The relative abundance of this substance was significantly higher in high concentration treatments than in other treatments. In addition, Previous studies have shown that 2-Aminobenzoic acid has inhibitory effect on the growth of \u003cem\u003eLactuca sativa\u003c/em\u003e and \u003cem\u003eArabidopsis thaliana\u003c/em\u003e seedlings\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e,\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Therefore, 2-Aminobenzoic acid is likely a potential autotoxins in the ethanol extract of \u003cem\u003eS. rostratum\u003c/em\u003e litter.\u003c/p\u003e \u003cp\u003eAdditionally, alien invasive plants can release allelochemicals to the soil through litter, which can affect the structure and function of soil microbial community\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e, and soil microbial changes will affect plant growth and form plant-soil feedback\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. In this study, high concentration of ethanol extract from \u003cem\u003eS. rostratum\u003c/em\u003e litter reduced the diversity of soil bacteria and altered the community structure of soil bacteria. High diversity of soil microbial communities is beneficial for the stability and sustainability of ecosystems, while low diversity can lead to a decrease in ecosystem stability, making it more susceptible to external environmental disturbances\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e and making seedlings more susceptible to the inhibitory effects of autotoxins. This is consistent with previous research findings. For example, the autotoxins in \u003cem\u003eCucumis sativus\u003c/em\u003e reduced the diversity of rhizosphere bacteria, but increased fungal diversity, altered the composition of bacterial and fungal communities, and reduced the positive impact of cucumber rhizosphere microbiota on cucumber seedling growth\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. In addition, the allelochemicals produced by invasive plants can reduce the number of microorganisms and thereby affect the growth of plants. For example, \u003cem\u003eAlliaria petiolata\u003c/em\u003e can produce glucosinolate through the degradation of litter in the soil, indirectly changing the soil microbial community structure, resulting in a significant reduction in the amount of soil arbuscular mycorrhizal fungi, causing the gradual degradation of the local plant community\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. And in this study, \u003cem\u003eBrevundimonas alba\u003c/em\u003e, \u003cem\u003eBrevundimonas\u003c/em\u003e, \u003cem\u003eAltererythribacter\u003c/em\u003e, \u003cem\u003eNovosphingobium resinovorum\u003c/em\u003e, and \u003cem\u003eNovosphingobium\u003c/em\u003e showed a negative correlation with seedling growth. Interestingly, there are seventeen metabolites, which showed higher relative abundance in the soil samples treated at 10 mg/mL treatment, such as 2, 6-dibromophenol and palmitaldehyde, are positively correlated with these microorganism (Fig. S4). On the other hand, \u003cem\u003ePontibacter\u003c/em\u003e and \u003cem\u003eGemmatimonas\u003c/em\u003e showed a positively correlated with seedling growth. Some metabolites with higher abundance under low-concentration treatment, such as ecdysone palmitate, performanced a significant positive correlation with these microorganisms (Fig. S4).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe ethanol extract from the litter of \u003cem\u003eS. rostratum\u003c/em\u003e displayed a low-concentration promoting and high-concentration inhibitory effect on seedling growth. And, ethanol extract from litter also affect the growth of seedlings by influencing the soil metabolites and microorganism. The above research results can provide theoretical support for the development of control strategies for \u003cem\u003eS. rostratum\u003c/em\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDeclaration of Competing Interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, S. Wang and D. Tan; methodology, S. Wang; formal analysis, Y. Ma, H. Liu and L. Jiang; investigation, Y. Ma, L. Jiang, H. Liu and G. Zhai; resources, Y. Ma, and J. Qiu; data curation, Y. Ma, L. Jiang and S. L; writing\u0026mdash;original draft preparation and the revision of the article, Y. Ma, L. Jiang, S. W; writing\u0026mdash;review and editing, S. Wang and D. Tan; supervision, S. Wang and D. Tan; project administration, S. Wang and D. Tan; funding acquisition, S. Wang and D. Tan All the authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis research was supported by a special grant from the Natural Science Foundation of the Xinjiang Uygur Autonomous Region (grant number: 2023D01B37), the National Natural Science Foundation of China (32460684) and the Xinjiang Key Laboratory of Soil and Plant Ecological Processes (grant number: 23XJTRZW19).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe sequencing data have been deposited in the National Center for Biotechnology Information Sequence Read Archive database (http://www.ncbi.nlm.nih.gov/sra) with BioProject accession number PRJNA1274989.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDost\u0026aacute;l, P., M\u0026uuml;llerov\u0026aacute;, J., Pyšek, P., Pergl, J. \u0026amp; Klinerov\u0026aacute;, T. 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The current research mainly focuses on interspecific allelopathy, while there are relatively few studies on intraspecific allelopathy. \u003cem\u003eSolanum rostratum\u003c/em\u003e Dunal is an annual invasive plant with strong invasiveness, the secondary metabolites produced by the litter of \u003cem\u003eS. rostratum\u003c/em\u003e can accumulate in the soil, and may affect the growth of its own seedlings. Therefore, it is of great significance to clarify the intraspecific allelopathy of \u003cem\u003eS. rostratum\u003c/em\u003e for understanding the invasion mechanism or proposing new prevention and control strategies. In this study, the extract of \u003cem\u003eS. rostratum\u003c/em\u003e litter was used to treat its seedlings, and the soil physical and chemical properties, soil metabolites, and soil microorganisms were measured to analyze their correlation with the growth of seedlings. The results showed that 0.1 and 1 g/L treatment significantly promoted the leaf area and biomass of seedlings, while 10 g/L treatment significantly inhibited plant height, leaf area index, biomass, net photosynthetic rate, transpiration rate, and stomatal conductance. Some bacteria, such as \u003cem\u003eBrevundimonas alba\u003c/em\u003e, \u003cem\u003eBrevundimonas\u003c/em\u003e, \u003cem\u003eAltererythribacter\u003c/em\u003e, \u003cem\u003eNovosphingobium resinovorum\u003c/em\u003e, and \u003cem\u003eNovosphingobium\u003c/em\u003e exhibited a higher abundance under 10 g/L treatment, showed a negative correlation with seedling growth. And 25 metabolites detected in the soil, such as 2-Aminobenzoic acid, 2, 6-dibromophenol and palmitaldehyde, might be the potential auto-toxicity. The results can not only supplement the invasion mechanism of invasive plants from the perspective of intraspecific allelopathy, but also provide theoretical support for formulating control strategies for the \u003cem\u003eS. rostratum\u003c/em\u003e.\u003c/p\u003e","manuscriptTitle":"Effect of Solanum rostratum Dunal litter extract on its seedling growth","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-18 18:23:39","doi":"10.21203/rs.3.rs-6829445/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-08T06:25:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-02T17:10:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"279287390782609689638461338171225399326","date":"2025-11-16T03:16:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"146312960085473616404518981943585330991","date":"2025-10-12T15:53:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-02T14:35:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"138389269060785781072343860038179309069","date":"2025-06-30T11:51:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"100401064230533880718348540903500065137","date":"2025-06-16T07:01:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-16T02:49:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-16T02:47:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-12T12:46:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-12T05:14:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-06-05T12:58:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4d172816-d036-49c3-ba97-83b0b320559c","owner":[],"postedDate":"June 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":50194715,"name":"Biological sciences/Ecology/Biodiversity"},{"id":50194716,"name":"Biological sciences/Ecology/Invasive species"},{"id":50194717,"name":"Biological sciences/Ecology"},{"id":50194718,"name":"Biological sciences/Plant sciences"}],"tags":[],"updatedAt":"2026-01-26T16:08:25+00:00","versionOfRecord":{"articleIdentity":"rs-6829445","link":"https://doi.org/10.1038/s41598-026-36746-1","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-01-21 15:58:00","publishedOnDateReadable":"January 21st, 2026"},"versionCreatedAt":"2025-06-18 18:23:39","video":"","vorDoi":"10.1038/s41598-026-36746-1","vorDoiUrl":"https://doi.org/10.1038/s41598-026-36746-1","workflowStages":[]},"version":"v1","identity":"rs-6829445","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6829445","identity":"rs-6829445","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}