Impact of Heavy Metals and Polystyrene Microplastics on the Bacterial Communities in Rhizosphere and Bulk Soil and the Physiological Health of Allium fistulosum

Impact of Heavy Metals and Polystyrene Microplastics on the Bacterial Communities in Rhizosphere and Bulk Soil and the Physiological Health of Allium fistulosum | 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 Research Article Impact of Heavy Metals and Polystyrene Microplastics on the Bacterial Communities in Rhizosphere and Bulk Soil and the Physiological Health of Allium fistulosum Jazbia Shirin, Nazish Jabeen Abbasi, Syeda Anber Zahra, Azhar Hussain Shah, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6139376/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Microplastics (MPs) are emerging as significant global pollutants due to their persistence, versatility, and resilience across diverse ecosystems. However, research focusing on their combined impact with heavy metals (HMs), their relations with soil microbial communities, particularly saprophytes and pathogenic species, and their influence on terrestrial plants and soil physicochemical properties remains scarce. This study aimed to examine the combined effects of HMs (copper, arsenic, zinc, cadmium, and lead) in contaminated soils from Tongling City and polystyrene microplastics (PS-MP) of varying sizes (13 µm, 50 µm, and 106 µm). The research evaluated changes in soil physiochemical properties, bacterial diversity and composition, plant and animal pathogens, saprotrophs in both bulk and rhizosphere soils, as well as the impact on antioxidant activity and the growth of Allium fistulosum . The blend of PS-MPs and heavy metals was lethal for the spring onion. The smallest MP treatment significantly increased soil organic matter, pH, total carbon, electric conductivity, zinc, copper, and cadmium and significantly reduced total nitrogen, ammonia, and nitrate, and also brutally impeded the growth indicators of spring onion including plant height, leaves length, fresh weight of root, dry weight of leaves and root. However, MP did not affect the length, fresh, and dry weight of stem and root length. Small MP treatment also reduced relative water content, and increased antioxidant activity and electrolytic leakage of the spring onion. Treatment with smaller MP at the middle point (at day 20) increased the bacterial diversity as compared to the final point (at day 40). Microplastic also played a crucial role in the reduction of saprotrophs and increased plant and animal pathogens especially in the small MP treatment and in rhizosphere soil. Our findings revealed that the interaction of heavy metals (HMs) with smaller-sized microplastics (MPs) posed greater harm to soil bacterial communities and the growth of spring onion. This study also highlights critical knowledge gaps and underscores the need for further research into the ecological risks associated with PS-MPs and HMs. Allium fistulosum Heavy Metals Polystyrene Microplastic Bacteria Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Plastics are extensively utilized in everyday life, contributing significantly to environmental pollution. In 2021, worldwide, plastic manufacturing reached 390.7 million tons, with China as the leading manufacturer, generating over 20% of the total (approximately 83 million tons). Microplastics, plastic fragments with a diameter of less than 5 mm, have recently gained considerable attention in environmental research. These smaller fragments are capable of adsorbing and transporting a higher concentration of pollutants and toxic substances compared to larger plastics, posing serious ecological risks [ 1 , 2 , 3 , 4 ] . Research on microplastics (MPs) initially concentrated on aquatic ecosystems. However, growing concerns have emerged regarding the high prevalence of microplastics in soils and their potential to affect the ecological atmosphere through interactions within the soil-plant system, drawing increased attention from researchers [ 5 , 6 , 7 , 8 ] . Microplastic contamination has been identified in soils globally, primarily due to the extensive use of plastic mulch in agriculture, irrigation with sewage water, disposal of waste in landfills, and activities related to industrial production [ 9 , 10 ] . Pang et al. [ 11 ] have reported a variety of MP kinds in agroecosystems, including polystyrene (PS), polyethylene (PE), polypropylene (PP), and polyvinyl chloride (PVC). Furthermore, Li et al. [ 12 ] documented that the average levels of PE, PS, and PP microplastics in farmland soils on the Northeast side of China were 685.55 µg/g, 1069.98 µg/g, and 864.23 µg/g, respectively. After entering the soil, MPs can affect plant growth by altering the soil's physiochemical properties, structure, and plants [ 13 , 14 ] . Microplastics can interfere with soil's physical, biological, and chemical functions by modifying its structure and impacting microbial communities [ 15 , 16 , 17 , 18 ] . Microplastics present in soil can adhere to plant root surfaces, possibly blocking root pores. This blockage can obstruct the uptake of water and other essential nutrients, as well as their transportation within the plant [ 19 , 20 ] . Additionally, MPs in the soil can operate as an extra source of nutrients or carbon, promoting soil microbial activity and intensifying the struggle for nutrients between microbes and plants, which in turn impacts plant biomass [ 21 , 22 ] . Some studies indicate that microplastics (MPs) can influence the composition of soil microbial communities, leading to a reduction in both the diversity and abundance of bacteria [ 23 ] . Moreover, in the rhizosphere, MPs can carry and also provide an exceptional environment for soil microorganisms, especially pathogens, encouraging microbial colonization and enrichment [ 24 , 25 ] . In addition, differences in microplastics, including size, polymer type, and shape, along with soil characteristics, can influence soil microbial communities, physicochemical properties, soil organisms, and plant growth. These impacts may be beneficial, harmful, or negligible [ 26 ] . Microplastics can adversely affect various plant biochemical and physiological processes, such as root trait changes, biomass reduction, seed germination, growth inhibition, fruit yield reduction, photosynthesis interference, genotoxicity, and oxidative damage [ 19 , 22 , 27 , 28 ] . Furthermore, MPs can adsorb a variety of hazardous compounds and influence plant growth and soil properties [ 29 , 30 ] . Microplastics are novel pollutants in terrestrial ecosystems but there is little information available about the effect of HM and PS-MPs (that range in size from 200 to 500 µm) on vascular plants, which could lead to significant variability [ 31 ] . Heavy metal (HM) pollution of soil has been a global environmental concern; it can occur naturally or enter the environment due to many anthropogenic activities, including mining, industry, agriculture, vehicle exhaust, and other activities. Because of the possible toxicity, non-biodegradability, and persistence of heavy metals, the buildup of HMs in soil has caused substantial concern in current decades, raising problems for both human health and soil ecosystems [ 32 , 33 ] . Research has shown that when microplastics (MPs) enter the soil environment, they can adsorb or interact with heavy metals, leading to combined toxic effects. For instance, MPs can alter metal availability by modifying soil properties and influencing the structure and functions of bacterial communities [ 34 , 35 ] . The combined impact of MPs and HMs on terrestrial plants and soil health markers like soil microbiota and plant enzyme activity remains limited [ 31 , 36 ] . Recent research has reported that MPs can be a significant driver for HMs in soils due to their hydrophobic nature and large surface area; when both are present together in soil, they can affect HMs' behavior, availability to living organisms, and toxicity; which leads to potential danger to the microbiota of the soil. However, the complex interaction between microplastics and heavy metals in the soil environment is influenced by several factors, such as microplastic size, heavy metal type, and experimental conditions [2, 11, 14; 37, 38, 39] . According to Shen et. al [ 40 ] , the Tongling region of China is well-known for its plentiful copper deposits, which date back more than 3,000 years to the Shang and Zhou dynasties. The first copper mine at Tongguanshan has been in operation since 1949 [ 41 ] . According to Wang et.al [ 42 ] , it is also impossible to overlook the fact that Pb and Cd have the most effects on human health in this area. Spring onions ( Allium fistulosum ) are a most cultivated member of the Amaryllidaceae family, characterized by their distinct flavors, high nutritional benefits, anti-obesity effects, dietary fiber, and vitamin C. Moreover, it has immense medicinal value and is useful in fever, dropsy, catarrh, and chronic bronchitis [ 43 , 44 ] . Spring onion ranks second after tomato in the list of worldwide cultivated vegetables and China is the world's top spring-onion-producing country, with an estimated production area exceeding 500,000 ha [ 43 , 45 ] . No previous research has reported on the combined effect of polystyrene microplastic and heavy metals on the spring onion and to the best of our knowledge, research on the impact of microplastics on higher plants remains limited. Therefore, our study will concentrate on examining the combined impact of heavy metals (HMs) contaminated soil in Tongling and various sizes of polystyrene (PS) microplastics on soil attributes (physiochemical), bacterial diversity, compositions, plant and animal pathogens in the soil, saprophytes as well as their influence on the growth and enzymatic activity of spring onion. This will be achieved through a greenhouse experiment. The aims of this study are to (1) Investigate changes in soil health attributes caused by the combination of PS-MPs and HMs. (2) Evaluate the effects of HMs and PS-MPs on the growth performance and parameters of spring onions. (3) Analyze the influence of different PS-MPs sizes on bacterial diversity, composition, and pathogenicity in rhizosphere and bulk soil within contaminated environments with HMs (4) Identify the connections between changes in soil bacterial communities caused by microplastic-heavy metal interactions and their effects on the growth and health of spring onions. Significance: (1) This study enhances our understanding of soil microecological responses to the combined existence of heavy metals and microplastics. (Ⅱ) The results offer important insights into the complex interactions between these contaminants and their combined effects on terrestrial ecosystems, serving as a scientific basis for ecological risk assessments. 2. Materials and Methods 2.1 Study Area Tongling City, situated in the central region of Anhui, China, experiences subtropical humid weather with distinct monsoon physiognomies. The area receives an average yearly precipitation of 1390 mm, with a yearly mean temperature of 16.2°C. The relative humidity ranges from 75% to 81% on a monthly average throughout the year. Tongling is known for its rich and diverse mineral resources, significant mining activities, and substantial reserves. This region has endured extensive pollution from the mining industry over an extended period. 2.2 Sample collection Soil samples were obtained from the copper mine tailings disposal site (N30°53′55.3″, E117°55′7.0″) at a depth of 0–20 cm. The collected soil was alienated into two portions: one portion was air-dried, ground, sieved, and stored at two different temperatures (4°C and -80°C) for subsequent analysis, while the other portion was sifted and directly utilized for the pot experiment in the greenhouse. 2.3 Experimental Setup We chose PS-MPs and spring onion seedlings for the pot experiment. Spring onion’s seedlings were purchased from the local supermarket in Hefei, China; and green onion seedlings were cut 2 cm above the roots, and the roots were then used for the pot experiment. This spring onion was carefully chosen due to its vast nutritional benefits, widespread cultivation, and adaptable nature to diverse environmental situations [43] . Morphology and other detailed information on PS-MPs are given in supplementary figure 1. We used three different sizes of PS-MPs which are described in Table 1. A total of 20 pots, each with five replications, were used in this experiment. Each pot was filled with 7 kg of soil, and 1.4 g of microplastics per kilogram of soil was added to all pots except the control (C). Five uniformly sized seedlings were planted in each pot within a greenhouse, and consistent agronomic practices such as irrigation, weeding, and plant protection were implemented uniformly across all treatments. 2.4 Soil Sampling Soil samples from the bulk and rhizosphere soil were carefully collected after 20 days of seedling growth to analyze the bacterial community. After 40 days, spring onions were reaped, and again soil samples were taken to evaluate soil physicochemical indicators, heavy metal concentrations, and community composition of bacteria. Plant physical parameters were also recorded during the experiment. 2.5 Soil Physiochemical Analyses We used different soil physiochemical parameters which are described in Table 2. 2.6 Plant physiochemical analyses Measurements were taken for plant height, leaf diameter and length, stem and root length, as well as the fresh and dry weight of leaves, stem, and root. The relative water content (RWC) of spring onion leaves was assessed following the method described by Mayak et al. [55] , while electrolytic leakage (ELL) was evaluated using the approach outlined by Ahmad et al. [56] . 2.7 Biochemical Parameters Peroxidase activity was measured using the KIT Biosharp (Product No. BL1064B) from Hefei, China, and superoxide dismutase was assessed using the KIT Biosharp (Product No. BL901A), also from Hefei, China. 2.8 DNA Extraction, PCR Ampli fi cation and Sequencing The genomic DNA was extracted by using the TIANamp Soil DNA Kit (Tiangen, China), by following their directives and NanoDrop ND-1000 (Thermo Scientific, United States) was used to qualify the extracted DNA. For bacterial 16S rRNA sequencing, primers 515F/ 907R (5’- GTGCCAGCMGCCGCGG-3’) and (5’- CCGTCAATTCMTTTRAGTTT-3’) were used. The PCR amplification was carried out using the following protocol on an Applied Biosystems GeneAmp 9700 thermocycler: an initial denaturation at 95°C for 5 minutes, followed by 27 cycles of 95°C for 30 seconds, 55°C for 30 seconds, and 72°C for 45 seconds, with a last extension at 72°C for 30 seconds. The purified PCR products were sequenced using the Illumina MiSeq platform at Shanghai Biozeron Technology Co., Ltd. (Shanghai, China). 2.9 Biochemical and Statistical Analysis The quantitative insight into Microbial Ecology 1.9.2 (QIIME) software was utilized analyze the bacterial 16S rRNAraw sequence data by following the removal of short sequences (<200bp), mismatched primers, and indicated chimers. The retained high-quality sequences were matched with their specific individual by relying on the primer and barcode details. The subsequent analysis of these sequences involved grouping them into clusters according to 97% similarity criteria and splitting them into amplicon sequence variants or operational taxonomic units. Following that, the representative sequences underwent phylogenetic analysis and classification identification, which allowed for a comprehensive understanding of the makeup of the bacterial community found in the samples. Alpha diversity metrics, including Chao1, PD, observed species, and Shannon indices, were utilized. The alpha diversity analysis was conducted using the online platform GenesCloud Tools (https://www.genescloud.cn). Additionally, plant and animal pathogenic microorganisms were identified using the Pathogen Detection database from NCBI and relevant literature. For the beta diversity, NMDS was used to visualize the bacterial community between different treatments, and the LDA and LEfSe analyses were performed on an online platform huttenhower.sph.harvard.edu/galaxy to determine the differential abundance taxonomic features. Redundancy analysis (RDA) was conducted using the vegan package in RStudio (version 1.2.1335) to assess the relationship between the microbial community and environmental factors. Statistical significance was evaluated using Duncan's multiple range test (p < 0.05) and analysis of variance (ANOVA) in SPSS 22.0. The results were visualized using GraphPad Prism 6.0 (GraphPad Software, Inc., San Diego, CA) and Venn diagrams were constructed to show the abundance in between different treatments. 3. Results 3.1 Soil physiochemical properties and contaminants (HMs and PS-MPs) There were significant variations in the soil physicochemical properties across different treatments, influenced by the presence of heavy metals and PS-microplastics (Figure 1, Figure S2). The average pH values differed notably between the HMs-enriched soils and those contaminated with PS-MPs. The utmost pH value (7.71) was observed in the T3 treatment, while the lowermost pH (7.50) was noted in the C treatment. Additionally, the mean electrical conductivity (EC) value in the T3 treatment (920 μS cm− 1) was notably higher compared to the other treatments while the lowest EC (812 μS cm− 1) was recorded in the C treatment (Figure 1B). Soil organic matter (SOM), and total phosphorus (TP) were higher in treatment T2 (1.1333 mg/kg, 96.5000 mg/kg) while there was no significant difference regarding OM (organic matter) between T2 treatment and T3 treatment. Total carbon (TC) was observed highest (.6300 mg/kg) in T3 treatment. In contrast, the lowest values of SOM, TP, and TC were recorded in C treatment (.6733 mg/kg), (84.1567 mg/kg), and (.4333 mg/kg) respectively (Figure 1A). The control treatment exhibited the highest average concentrations of total nitrogen (TN) and total ammonium nitrogen, with values of 488.67 mg/kg and 4.56 mg/kg, respectively. In contrast, the T1 treatment showed higher levels of total nitrate (0.29 mg/kg) and total nitrite (1.58 mg/kg). However, the lowermost concentrations of total nitrogen (265.6667 mg/kg), total ammonium nitrogen (2.1933 mg/kg) and nitrate (.3333 mg/kg) were observed in the T3 treatment. The lowest concentration of nitrite (.1767 mg/kg) was recorded in T2 treatment. (Table 3, Figure 1C, Figure 1D). The concentration of the heavy metals Pb (487.6667 mg/kg) and As (1009.0000 mg/kg) was greater in the T2 treatment and Cd (6.5333 mg/kg), Zn (1450.3333 mg/kg) and Cu (988.3333 mg/kg) in the T3 treatment. The lowest concentration of Cu (900.0000 mg/kg) and Pb (402.3333 mg/kg) was recorded in T1 treatment while the lowest concentration of Cd (4.0500 mg/kg), Zn (898.6667 mg/kg) and As (798.3333 mg/kg) in C (control) treatment. (Figure S2). 3.2 Plant Physiochemical Parameters Significant variations were observed in the physicochemical attributes of spring onion across different treatments, influenced by HMs and PS-MPs. The treatment with the smallest PS-MPs (T3) notably (p ≤ 0.05) inhibited the growth physiognomies of spring onion (Table 3). The maximum decline was observed in plant height (27.7111 cm), leaf length (20.99778 cm), leaves fresh weight (6.3167 g), leaves dry weight (.8100 g), stem length (4.8778 cm), stem fresh weight (.7967 g), stem dry weight (.8833 g), root length (8.6444 cm), root fresh weight (1.0656 g) and root dry weight (1.567 g) was recorded in T3 treatment. The highest plant height (33.3000 cm), leaf length (24.2667 cm), leaves dry weight (1.8267 g), root fresh weight (2.1478 g), and root dry weight (.7633 g) was observed in C(control) treatment. Though, there were no significant differences in root length, stem length, stem fresh and dry weight (Table 3). 3.3 Plant Biochemical Parameters The study revealed that HMs and PS-MPs had a detrimental effect on spring onions. RWC (relative water content), EL (electrolytic leakage), and enzymatic activity (SOD and POD) of spring onion leaves revealed significant differences ( p ≤ 0.05) in different treatments. In the case of SOD, more elevation (3.0397 U mg-1 protein) was detected in the T3 treatment as compared to the other treatments, while the lowest was recorded (1.7382 U mg-1 protein) in C (control) treatment. POD activity and ELL also showed the same trend as SOD, here the uppermost POD value (329.4667 ΔOD470/min/g) and ELL (33.3400) was recorded in the T3 treatment. The more declined POD activity (54.1333 ΔOD470/min/g) and ELL (28.7133) were noted in Control (Figure 2). 3.4 Effect of MPs and HMs on the Soil Bacterial Diversity Overall bulk soil bacterial alpha diversity was higher (67181.3) than the rhizosphere bacterial soil alpha diversity (66601.1) and the middle point showed higher alpha diversity (68801.58) than the alpha diversity at the final point (64981.36). The alpha diversity in rhizosphere soil showed no significant difference in all treatments except T3RM. The highest alpha diversity was (5440.6193), (.8343), and (6.8711) in T1BM (Chao1 index, Pielou_J index, Shannon index, ANOVA, Duncan test) respectively. In the observed species, the highest alpha diversity was observed in CBM treatment (3809.3333), however, there were no significant differences in CBM and T1BM. In rhizosphere soil at the final point C (control), CBM and T1BM treatment revealed significant difference from all other treatments (Shannon index, Pielou_J index). In the Observed species CBM, CBF, and T1BM revealed significant difference from all other treatments while in the Chao1 index, CBF and T1BM also revealed significant differences from all other treatments (Figure 3, Table S1). 3.5 Effect of Contaminants on the Soil Microbial Composition The most plentiful bacteria phylum in our study were Proteobacteria (36.12%) followed by Acidobacteriota (15.92 %), Chloroflexi (11.57%), Actinobacteria (8.35%), Bacteroidota (6.07%), Gemmatimonadota (6.01%), Planctomycetota (3.73%), Myxococcota (3.45%), Desulfobacterota (1.45%) and Armatimonadota (0.89%). The highest abundance of Proteobacteria was recorded in CRM treatment followed by T3RM and the lowest abundance was recorded in T1RF followed by T2BF and T3BF. The highest abundance of Acidobacteria was observed in T3BF followed by T2RF and the lowest abundance was recorded in T3RM followed by CRM and CRF. The uppermost abundance of Actinobacteriota was detected in treatment T1RF and Chloroflexi in T3RM (Figure S3, Figure 4A). The most abundant class in our data was Gammaproteobacteria followed by Alphaproteobacteria, Actinobacteria, Vicinamibacteria, Bacteroidia, Gemmatimonadetes, and Anaerolineae. Class Gammaproteobacteria was most abundant in the CRF (44.69577) followed by CRM (44.29609). Class Alphaproteobacteria was present in the highest abundance in the T3RM (15.73665) followed by T2RM (15.33795). Class Actinobacteria was present in the highest abundance in T1RF (12.05461) followed by T3RM (11.07263) (Figure 4B, Figure S4). Linear discriminant analysis (LDA) effect size (LEfSe) analysis was implemented to identify further specific taxa changes in the soil (rhizosphere and bulk) bacterial compositions between different treatments across the mid and final point using phylum to order level data. A total of 101 bacterial taxa revealed LDA scores larger than 2 in all the treatments including rhizosphere and bulk and two different sampling points (middle and final). The results showed that rhizosphere soil exhibited a higher significant abundance of bacterial taxa as compared to the other bulk soil, specifically in T3 treatment followed by T1 and C (control). T3 treatment had an abundance of one class (Bacteroidia), two orders (i.e., Rhodobacterales and Opitutales), eight genera (i.e., Brevundimonas, Pseudoxanthomonas, Sphingopyxis, Devosia, Dyadobacter, Qipengyuania, Bosea and Sphingobium) and seven families (i.e., Caulobacteraceae, Rhodobacteraceae, Devosiaceae, Spirosomaceae, Alcaligenaceae, Moraxellaceeae and Spongiibacteraceae). While on the other hand, in the bulk soil, C(control) treatment showed highest abundance. It had an abundance of three phyla (Myxococcota, Elusimicrobia and Firmicutes), two classes (Polyangia and Holophagae), three orders (i.e., Acidiferrobacterales, Haliangiales and Myxococcales), four genera (i.e., Sulfurifustis, Haliangium, Myxococcia and Phaselicystis) and four families (i.e., Crocinitomicaceae, Phaselicystidaceae, Haliangiaceae and Acidiferrobacteraceae). In the comparison of the treatments, C (control) treatment showed higher abundance than the other treatments (T1, T2 and T3). It had an abundance of four phyla (i.e., Bacteroidota, Myxococcota, Elusimicrobia, Firmicutes), two classes (i.e., Polyangia and Holophagae), three orders (i.e., Acidiferrobacterales, Haliangiales and Myxococcales) fifteen genus (i.e., Flavobacterium, Lacibacter, Azoarcus , Rhodobacter , Dechloromonas, Caenimonas, Rhizobacter, Methylovorus, Flavihumibacter, Acidovorax, Pseudomonas, Sulfurifustis, Haliangium, Myxococcia and Phaselicystis) and six families (i.e., Flavobacteriaceae, Pseudomonadaceae, Crocinitomicaceae, Phaselicystidaceae, Haliangiaceae and Acidiferrobacteraceae). In the comparison of two sampling points middle (M) and final (F), middle showed highest abundance especially in CBM treatment which had an abundance of two phyla (i.e., Myxococcota and Elusimicrobia), two classes (i.e., Polyangia and Holophagae), three orders (i.e., Acidiferrobacterales, Haliangiales and Myxococcales) four genus (i.e., Sulfurifustis, Haliangium, Myxococcia and Phaselicystis) and four families (i.e., Crocinitomicaceae, Phaselicystidaceae, Haliangiaceae and Acidiferrobacteraceae) (Figure S5, Figure S6). 3.6 Pathogenicity Our results showed that the alterations also extended to microbial pathogens, with rhizosphere soil and treatments involving small PS-MPs being more enriched in pathogens (Figure 11, Figure 12). Bacterial plant pathogens were found to be more abundant in rhizosphere soil compared to bulk soil. Overall total bacterial plant pathogens were more enriched in the T3R (27%) followed by T2R (20%), T1R (13%), T1B (13%), T3B (7%), T2B (7%), CR (7%) and CB (6%). Across all treatments, three bacterial plant pathogens were identified at the species level. The utmost abundant bacterial plant pathogen was Xanthomonas campestris . It was present in high abundance in T2R followed by T3R. Rathayibacter toxicus was present T1B followed by T1R and it was present only in C and T1 treatments in both rhizosphere and bulk soil. Surprisingly we found Acidovorax avenae only in T3R treatment (Figure S7A, Figure 5A). Bcaterial animal pathogens were also more enriched in the rhizosphere soil and T3 treatment. Overall total bacterial animal pathogens were more enriched in the T3R (22%) followed by T3B (21%), T2R (14%), T1R (14%), CR (10%), CB (7%), T2B (6%) and T1B (6%). A total of eight bacterial animal pathogens were found across all the treatments at the specie level. The most abundant bacterial animal pathogen was Xanthomonas campestris . It was present in high abundance in T2R followed by T3R. Rathayibacter toxicus was present T1B followed by T1R and it was present only in C and T1 treatments in both bulk and rhizosphere soil. Astonishingly we found Acidovorax avenae only in T3R treatment (Figure 10B, Figure 11B). Acinetobacter nosocomialis was the utmost abundant animal pathogen species followed by Legionella sp. Acinetobacter nosocomialis , Burkholderia cepacia , Escherichia coli and Legionella sp. were more enriched in T3R than other treatments while surprisingly Escherichia coli was not present in control treatment in both bulk and rhizosphere soil (Figure 7B, Figure 5B). 3.7 Saprotrophs Bacterial saprotrophic species showed more abundance in bulk soil than in rhizosphere soil and it revealed a decreasing trend while decreasing the microplastic size Overall bacterial saprotrophs were more enriched in the CB (18%) followed by CR (16%), T1R (13%), T1B (13%), T3B (13%), T2B (12%), T2R (8%) and T3R (7%). The most dominant saprotroph species was Intrasporangium calvum DSM 43043 followed by Intrasporangium calvum , Artrobacter sp. And Flavobacterium johnsoniae UW101 . Intrasporangium calvum DSM 43043 was present in the highest abundance in CB treatment followed by CR. Intrasporangium calvum was present in high abundance in CR treatment followed by CB. However, Flavobacterium johnsoniae UW101 was present only in T1B and T1R; Flexibacter flexilis subsp. Pelliculosus was also present only in T2R. Arthrobacter sp. were present in higher abundance in T1R followed by CB while Cytophaga hutchinsonii ATCC 33406 was present only in CB and T1B treatment (Figure 6). 3.8 Relationship between soil physiochemical variables, Micro plastic, HMs and bacterial community The relationship between environmental factors, bacterial alpha diversity, and communities was evaluated using redundancy analysis, heatmaps, and a correlation matrix (Figure 7, Figure 8, Figure S8, Table S2, Table S3, and Table S4). The first two RDA dimensions revealed an 81.68% variation in bacterial communities and environmental factors such as TP, Cd, OM nitrate, nitrite, ammonia and TN were positively correlated with RDA1. Furthermore, T1R species were positively influenced by the environmental indicators in the direction of RDA1. CR and T1R also differed from the other treatments (Figure 7). The relationship between environmental indicators (TP, OM, TC, EC, pH, TN, NH 4 + , NO 3 - , NO 2 - , Cd, Cu, Pb, Zn, As) and alpha diversity (Chao1 index, Observed species, Pielou_J index, and Shannon index) were conducted by correlation analysis. According to this analysis, Chao1 index revealed a negative correlation with TP, OM, TC, EC, TN, Cd, Cu, Pb, and As. However, observed species, Pielou_J index, and Shannon index showed a negative correlation with TN, NH 4 + , NO 3 - and NO 2 - only (Table S2). This study also conducted a correlation analysis to check the relationship between environmental indicators (TP, OM, TC, EC, pH, TN, NH 4 + , NO 3 - , NO 2 - , Cd, Cu, Pb, Zn, As) and bacterial communities at phylum and class level (Figure 8, Figure S8, Table S3, Table S4). Heatmap and correlation table showed a stronger positive correlation by Chloroflexi with As; Myxococcota with As, Pb, TP, and OM; Firmicutes with NH 4 + , NO 3 - and NO 2 - ; Methylomirabilota with As, pH and OM and Sumerlaeota with OM. Stronger negative correlation was showed by Myxococcota with NO 2 - ; Firmicutes with As, Zn, Pb, Cu, Cd, pH and TC; Methylomirabilota with NH 4 + and Fibrobacterota with NO 3 - at the phylum level (Figure 8, Table S3). At the class level stronger negative correlation was revealed by Actinobacteria with Cu; Thermoanaerobaculia with NH 4 + ; Polyangia with NH 4 + and NO 3 - ; Chloroflexia with NH 4 + and TN; Acidimicrobiia with NO 2 - and Methylomirabilia with NH 4 + . Stronger positive correlation was showed by Thermoanaerobaculia with As, Zn, Cd, pH and OM; Polyangia with As, Zn, Pb, Cu, TP, pH and OM; Chloroflexia with As, Zn, TC, Zn, pH, TP and OM; Acidimicrobiia with Zn and Cu and Methylomirabilia with As, pH and OM (Figure S8, Table S4). 4 Discussion 4.1 PS-MPs affected soil health indicators The addition of PS-MP and soil contaminated with heavy metals (HMs) altered the study's soil health metrics (Figure 1, Figure S2). Up until now, there has been an increased interest in mixing soil contaminated with microplastics and heavy metals. Their interactions may influence changes in the physicochemical qualities of soils containing both MPs and HMs, either directly or indirectly. The metal concentrations were assumed to vary, rather than remain constant due to the non-uniform nature of the soil [31, 57, 58, 59, 60] . Previous research indicates that various variables, including the type of HMs, experimental settings, and MP characteristics, influence the complex relationship between HMs and MPs in the soil environment. Among these variables, the type and dose of MPs received considerable attention in combined polluted environments. The experimental settings may also influence the way MPs and HMs interact in soils. It is difficult, nonetheless, to investigate every potential element affecting the coupled effects between HMs and MPs by concurrent experimentation [2,31,61] . Changes in soil pH, organic content, mineral composition, and microbial communities can impact the processes taking place in the rhizosphere [62,63] . Our findings show that MPs increased the pH of the soil compared to the control (treatment without MPs). The lowest size MPs treatment (T3) had the greatest pH (Figure 1). This went against the generally acknowledged theory that MPs can decrease as a result of heavy metal pollution [31] . One possible explanation is that Smaller microplastics have a greater surface area relative to their volume compared to larger microplastics. This increased surface area may enhance interactions with soil components, such as the release of basic compounds or adsorption of acidic substances, potentially raising the pH in comparison to other conditions. Our findings validated the interactions between HMs and MPs. MPs have the potential to change how heavy metals behave in the environment, including how they dissolve, precipitate, hydrolyze, and sorb, as well as how they affect soil pH. The addition of MPs changed the pH of the soil, although the effects varied according to MP size. Regardless of HMs, soil pH gradually rose as PS-MP size decreased. This observation sanctions that the co-occurrence of MPs with HMs can alter their effects on soil qualities. Our findings indicate that the addition of PS-MPs significantly altered the HM-contaminated soil microenvironment, with the T3 treatment demonstrating a significant increase in both SOM and EC. (Figure 1A, 1B). According to Li et al. [64] , the introduction of PE-MPs could have triggered the activation of soil pools of organic carbon (C), nitrogen (N), and phosphorus (P), promoting their integration into soil organic matter. SOM is essential for sustaining soil quality and facilitating plant growth. However, many questions remain unanswered regarding the interactions between microplastics and soil nutrients. Researchers are actively investigating the mechanisms and impacts of nanoplastics within soil ecosystems. Plants may absorb nutrients differently due to the influence of microplastics. Treatment T3 showed the highest total carbon (TC), while treatment T2 showed the highest soil total phosphorus (TP). On the other hand, the C treatment showed the lowest values of TP and TC (Figure 1A). The intriguing results of our experiment show that the presence of polystyrene microplastics (PS-MPs), especially the smaller ones, significantly impacted the soil's total carbon (TC) and total phosphorus (TP) levels. Smaller PS-MP particles exhibit a higher surface area relative to their unit volume compared to larger particles. This larger surface area may improve interactions between organic matter and soil particles, which could result in a greater soil carbon retention rate. In addition, the larger surface area may provide greater opportunities for microbial colonization, which could hasten the breakdown of organic waste and the cycling of nutrients, raising TC levels. Less microbial activity and the absence of microplastics in the control treatment likely contributed to the lowest TP and TC levels. Additionally, as the MPs' size decreased, so did total nitrogen (TN), total ammonium nitrogen, total nitrate, and total nitrite (Figure 1C, Figure 1D). It is possible that smaller PS-MPs hastened the transformation of nitrogen compounds by increasing microbial activity. For instance, the depletion of nitrate, ammonium, and nitrite in the soil may result from increased nitrification or denitrification processes. Microbes may have been able to quickly change ammonium into nitrate and nitrite, and then into nitrogen gas, thanks to the huge surface area of small PS-MPs. This process is called denitrification, and it would have lowered the amount of nitrogen in the soil. The treatment sans microplastics had the lowest concentration of heavy metals. This might be due to that PS-MPs and heavy metals have bonded to form complexes that make the metals more soluble in soil solutions and raise their concentrations in soil treated with microplastics. 4.2 PS-MPs affect physiochemical attributes and antioxidant activity of spring onion MPs have a direct or indirect impact on the growth of plants, as they are a critical part of the soil ecosystem [65] . In this study, HMs and PS-MPs considerably altered the physiochemical properties of spring onion. The T3 treatment resulted in a significant reduction in plant height, leaf length, fresh and dry weights, stem length, stem fresh and dry weights, as well as root length, fresh weight, and dry weight. This showed that MP size played a big role in slowing the growth of spring onion (Table S3). Additionally, prior research has shown that MPs have a negative impact on plant physiology, growth, and both direct and indirect toxicity [ 64, 66, 67] . Li et al. [64] further verified that the greater the inhibition of plant growth caused by MPs, the smaller the particle size. Furthermore, smaller MP particles tend to have a greater ability to adsorb metal ions, which could contribute to reduced plant growth. Due to their hydrophobic nature, MPs can easily adsorb various pollutants [68, 69] . In contrast to the other treatments, the T3 treatment in our study showed a greater increase in ELL (electrolytic leakage) and enzymatic activity (SOD and POD) of spring onion leaves, whereas the control group exhibited a greater reduction in POD, SOD, and ELL (Figure 2). This finding indicates unequivocally that MPs have the ability to compromise plant cell membrane integrity and that plants are abler to withstand HM stress than MPs. When compared to the control, the plants' relative water content showed a significant reduction in physiology due to pollutants. Damage to the membrane may be the cause of this parameter drop (ELL). Our findings demonstrated significant membrane leakage in T3 and suggested that stress-induced membrane damage occurred in Allium fistulosum . These findings are sustained by the other research [70,71,71] . The authors argued that ROS created by heavy metals and MPs stress led to oxidative stress, increased membrane leakage, and MDA generation. Our findings revealed that the hydrophobic nature of heavy metals and MPs has subjected spring onion to a variety of environmental stressors, including drought. This has made the plant more susceptible to these stressors, which may affect its ability to fight off oxidative stress. This phenomenon has also been previously documented and explained [71, 72] . 4.3 PS-MPs effect on soil bacterial diversity and composition Soil microorganisms are critical to the operation of soil ecosystems because they participate in soil nutrient cycling and energy flows, micro-ecology management, and sustainable soil productivity [73] . At the middle and end points of our study, we looked at how the interaction between PS-MPs and HMs impacts saprotrophs, higher plant species ( Allium fistulosum ), bacterial diversity, and composition in both the rhizosphere and bulk soil. This is the first study to do so. In our study, bulk soil had a higher alpha diversity than rhizosphere soil, and the alpha diversity at the middle point was greater than that at the final point. (Table S1, Figure 3). Our research aligns with earlier investigations. The microbial community in the soil plastisphere is much different from that in other soil compartments, according to research by Rillig et al. [74] . If the environment in the rhizosphere changes, it can have a direct effect on the microbes and chemicals in the soil [35] . According to Yi et al. [75] , adding membrane-like PE and fibrous PP changed the alpha diversity and soil microbial communities in a big way. Rong et al. [76] found that varying amounts of polyethylene-microplastics only marginally impacted soil bacterial diversity, despite variations at the genus level. The middle point of our investigation had a higher alpha diversity than the end point. This could be the result of exposure time. According to Huffer et al. [77] , differences in MP type size, soil, and exposure period can have positive, negative, or negligible effects on soil microbial communities and plant growth. We discovered the highest abundance of the most prevalent phylum Proteobacteria in the CRM treatment, followed by T3RM, and the lowest abundance in the T1RF treatment, with T2BF and T3BF following. In our investigation, the PS-MPs did not significantly impact the composition of the bacterial community. Furthermore, the class with the highest abundance in our data was Gammaproteobacteria, which was most prevalent in the CRF and then the CRM. Thus, our findings indicate that MP exposure duration had a greater impact on Proteobacteria, but that at a middle point, PS-MP contamination prevailed. Class Gammaproteobacteria may have a tolerance against HMs by various mechanisms (including by metal-binding proteins, changing efflux pumps, and other adaptations). However, when PS-MPs and HMs combine, the composition of bacteria remains largely unknown. In their investigation, Qi et al. [78] similarly failed to discover any appreciable variations in the variety and composition of bacteria. The results of linear discriminant analysis (LDA) effect size (LEfSe) analysis indicated that, particularly in the T3 treatment, the bacterial taxa in the rhizosphere soil were much more abundant than in the bulk soil. However, the C treatment exhibited the highest abundance in the bulk soil; a comparison of the treatments revealed that the C treatment outperformed the other treatments in terms of abundance, and a comparison of the two sampling points revealed that the middle point displayed the highest abundance. In a former study, Zeb et al. [35] also specified that changes in the rhizosphere environment may have a direct effect on the rhizosphere soil microbial community. 4.4 PS-MPs effect on soil bacterial pathogens and saprotrophs Our study demonstrated that the observed alterations also extended to bacterial pathogens. Treatments involving rhizosphere soil and small MPs showed a higher enrichment of microbial pathogens (Figure 5, Figure S7). Both bacterial plant and animal pathogens were found to be more abundant in the rhizosphere soil compared to bulk soil. Overall both total bacterial plant and animal pathogens were more enriched in the T3R. Pathogens may also be the reason behind the growth decline of spring onion. Across all treatments, a total of eight bacterial animal pathogens and three bacterial plant pathogens were identified at the species level. The most abundant bacterial plant pathogen was Xanthomonas campestris followed by Rathayibacter toxicus and Acidovorax avenae . Acinetobacter nosocomialis was the most abundant animal pathogen species followed by Legionella sp. Acinetobacter nosocomialis, Burkholderia cepacia, Escherichia coli. Hence, it verified that PS-MPs can hinder with bacterial pathogens and small sized MPs can greatly impact the rhizosphere soil. The direct reason may be that small-sized polystyrene microplastics have a bigger surface area, which provides more sites for microbial colonization, including pathogens. This may directly promote the growth and prevalence of pathogenic microorganisms in the rhizosphere soil. The indirect reason may be that stress induced by the presence of small PS-MPs and HMs weaken plant defenses, and make them more susceptible to pathogens. Weaker plants may release more root exudates, which could serve as additional nutrients for pathogenic microorganisms in the rhizosphere. However, there are not so much data is available on the MP's effect on the bacterial pathogens. More research work is required in this aspect. In a previous study, Azeem et al. and Shirin et al. [24, 79] stated that in the rhizosphere, MPs can provide an exceptional environment for soil microorganisms, especially pathogens, encouraging microbial colonization and enrichment. Soil fungi and bacteria play a major role in agroecosystems by influencing soil nutrient cycling and sensitivity. In the soil ecosystem, soil bacteria play a significant role as decomposers of organic matter. They release specific extracellular enzymes that transform important organic compounds into monomers, which plants then absorb [80, 81] . Bacterial saprotrophic species were less common as the microplastics got smaller in our study. They were more common in bulk soil than in rhizosphere soil. In general, the CB and CR had higher concentrations of bacterial saprotrophs (Figure 6). Our findings contradict the 2019 Huang et al. study, which suggested that MPs might increase the microbial populations involved in self-degradation. This might be because the rhizosphere, which attracts a diverse range of microorganisms, including pathogens, is a highly competitive environment because of the presence of root exudates. In this nutrient-rich zine, the pathogens may outcompete the saprotrophic bacteria, which break down organic matter. This might be the reason that saprotrophic bacteria were more common in bulk soil. 4.5 Correlations between PS-MPS, HMs, shifts in soil bacterial communities and soil physiochemical indicators The relationship between environmental factors, bacterial alpha diversity, and communities was evaluated using redundancy analysis, heatmaps, and a correlation matrix (Figure 7, Figure 8, Figure S8, Table S2, Table S3, and Table S4). Our results revealed that the environmental indicators alter the bacterial alpha diversity and community. The first two RDA dimensions exhibited an 81.68% variation in bacterial communities. Environmental factors such as Cd, nitrate, nitrite, ammonia, TP, TN, and OM were positively correlated with RDA1. Moreover, T1R species were positively influenced by the environmental indicators in the direction of RDA1. CR and T1R also differed from the other treatments (Figure 7). According to correlation analysis, Chao1 index revealed a negative correlation with TP, OM, TC, EC, TN, Cd, Cu, Pb, and As. However, observed species, Pielou_J index, and Shannon index showed a negative correlation with TN, NH 4 + , NO 3 - and NO 2 - only (Table S2). Heatmap and correlation table showed a stronger positive correlation by Chloroflexi with As; Myxococcota with As, Pb, TP, and OM; Firmicutes with NH 4 + , NO 3 - and NO 2 - ; Methylomirabilota with As, pH and OM and Sumerlaeota with OM. Stronger negative correlation was showed by Myxococcota with NO 2 - ; Firmicutes with As, Zn, Pb, Cu, Cd, pH and TC; Methylomirabilota with NH 4 + and Fibrobacterota with NO 3 - at the phylum level (Figure 8, Table S3). At the class level stronger negative correlation was revealed by Actinobacteria with Cu; Thermoanaerobaculia with NH 4 + ; Polyangia with NH 4 + and NO 3 - ; Chloroflexia with NH 4 + and TN; Acidimicrobiia with NO 2 - and Methylomirabilia with NH 4 + . Stronger positive correlation was showed by Thermoanaerobaculia with As, Zn, Cd, pH and OM; Polyangia with As, Zn, Pb, Cu, TP, pH and OM; Chloroflexia with As, Zn, Cd, TC, TP, pH and OM; Acidimicrobia with Zn and Cu and Methylomirabilia with As, pH and OM (Figure S8, Table S4) According to Mataruga et al. [20] , the soil's pH significantly affects how efficiently it binds to copper. Raising the soil's pH to 7-8 resulted in a decrease in the amount of accessible copper in the soil. The recent research, which indicates a positive link between pH and Cu content, is in conflict with these findings. Additionally, this study revealed both competitive and synergistic relationships between bacterial communities and soil physiochemical characteristics, which is explained above. Previous studies have shown that MPs are capable of absorbing a variety of pollutants [83, 84] . Obayomi et al [85] report that microplastics of different particle sizes can absorb varying types and amounts of pollutants., and they observe a strong correlation between soil bacterial abundance and contaminants in the soil. As a result, we believe that the pollutants that MPs adsorb contribute to the diversity of microbial communities in MP-contaminated environments. The findings of this study indicate that differences in bacterial community distribution could serve as an ecological marker for evaluating soil environmental health. 5. Conclusion In this study, we focused on the combined influence of polystyrene microplastic and heavy metals on the soil health indicators; bacterial diversity, and composition at two different points and also in the two different types of soil (rhizosphere and bulk); and the growth indicators of Allium fistulosum . This study revealed that soil physiochemical properties were altered by the addition of microplastic. The smallest microplastic treatment (T3) significantly increased soil organic matter, pH, total carbon, electric conductivity, zinc, copper, cadmium and significantly reduced total nitrogen, ammonia and nitrate. The combination of polystyrene microplastic and heavy metals was also more lethal for the spring onion. Polystyrene microplastic with small size brutally impeded the growth indicators of Allium fistulosum including plant height, leaf length, fresh weight of root and stem, dry weight of leaves and root. However, microplastic did not affect the dry and fresh weight of stem and length of stem and root. Small microplastic treatment also reduced relative water content, and increased antioxidant activity and electrolytic leakage of the leaves. Our study also identified both cooperative and competitive relationships between soil health indicators and bacterial diversity and composition. Exposure to small microplastics at the intermediate stage led to a higher bacterial diversity compared to the final stage. So, our study confirms that microplastic, different types of soil, and different time zones play a vital role in bacterial diversity. We also observed that microplastic played an important role in reducing saprophytes, especially in the smaller microplastic treatment and in rhizosphere soil. Microplastic also increased plant and animal pathogen species especially in the small microplastic treatment and rhizosphere soil. Recommendations We recommend conducting detailed and thorough research focusing on how other environmental stressors, such as drought, salinity, or nutrient deficiency, interact with microplastics and heavy metals to influence soil and plant health and to assess the impact of combined microplastic and heavy metal pollution on ecosystem services such as soil fertility, water retention, and plant productivity, to understand the broader ecological implications of these pollutants. This will provide a broader understanding of the ecological implications and help in developing more resilient agricultural practices. Declarations Conflict of interest The authors declare no competing interests. Funding This work was supported by the Higher Education Institution Collaborative Innovation Project of Anhui Province, China (No. GXXT-2021–061). This work was also supported by the China Scholarship Council (CSC: 2019GXZ014633 to Jazbia Shirin). Author Contribution Authors ContributionJazbia Shirin: Writing – original draft, writing – review & editing, Conceptualization, Data curation, Formal analysis, Software, Validation, Visualization, Nazish Jabeen Abbasi: Formal analysis, Data curation, and Software, Syeda Anber Zahra: review and editing, formal analysis, Azhar Hussain Shah: Writing – review & editing, Muhammad Afzal: Formal analysis, Qiyong Xu: Conceptualization, Supervision, Visualization, Writing – review & editing. Acknowledgement AcknowledgmentThe authors are thankful to Prof. Qingye Sun, Anhui University, Hefei, for providing funding and the basic instruments and space for conducting this study, and to Dr. Rizwan Abbasi CGTN, for his continuous support and guidance. Data Availability Data will be provided if required. References Thacharodi, A., Meenatchi, R., Hassan, S., Hussain, N., Bhat, M.A., Arockiaraj, J., Ngo, H.H., Le, Q.H. and Pugazhendhi, A., 2024. 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Biological roles of soil microbial consortium on promoting safe crop production in heavy metal (loid) contaminated soil: a systematic review. Sci. Total Environ. 912, 168994. Fu, Z.; Zhou, L.; Chen, P.; Du, Q.; Pang, T.; Song, C.; Wang, X.; Liu, W.; Yang, W.; Yong, T. Effects of maize-soybean relay intercropping on crop nutrient uptake and soil bacterial community. J. Integr. Agr. 2019, 18 , 2006–2018. [CrossRef] Rillig, M.C., Kim, S.W., Zhu, Y.G., 2023. The soil plastisphere. Nat. Rev. Microbiol. 1–11. Yi M, Zhou S, Zhang L, Ding S. The effects of three different microplastics on enzyme activities and microbial communities in soil. Water Environ. Res. 2021;93:24–32. https://doi.org/10.1002/wer.1327 Rong, L., Zhao, L., Zhao, L., Cheng, Z., Yao, Y., Yuan, C., Wang, L. and Sun, H., 2021. LDPE microplastics affect soil microbial communities and nitrogen cycling. Science of the Total Environment , 773 , p.145640. Hüffer, T., Metzelder, F., Sigmund, G., Slawek, S., Schmidt, T. C., and Hofmann, T. (2019). Polyethylene Microplastics Influence the Transport of Organic Contaminants in Soil. Sci. Total Environ. 657, 242–247. doi:10.1016/j.scitotenv.2018.12.047 Qi, Y., Ossowicki, A., Yergeau, É., Vigani, G., Geissen, V., Garbeva, P. (2022). Plastic mulch film residues in agriculture: impact on soil suppressiveness, plant growth, and microbial communities. FEMS Microbiol. Ecol. 98, fiac017. doi: 10.1093/femsec/fiac017 Shirin J, Chen Y, Hussain Shah A, Da Y, Zhou G and Sun Q (2024) Micro plastic driving changes in the soil microbes and lettuce growth under the influence of heavy metals contaminated soil. Front. Plant Sci. 15:1427166. doi: 10.3389/fpls.2024.1427166. Gong, W., Zhang, W., Jiang, M., Li, S., Liang, G., Bu, Q., Xu, L., Zhu, H. and Lu, A., 2021. Species-dependent response of food crops to polystyrene nanoplastics and microplastics. Science of the Total Environment , 796 , p.148750. Gong, X., Wang, Y., Huang, D. and Zhang, J., 2022. Effects of microplastics of different sizes on the Chlorella vulgaris-Ganoderma lucidum co-pellets formation processes. Science of The Total Environment , 820 , p.153266. Mataruga, Z., Jarić, S., Marković, M., Pavlović, M., Pavlović, D., Jakovljević, K., ... & Pavlović, P. (2020). Evaluation of Salix alba, Juglans regia and Populus nigra as biomonitors of PTEs in the riparian soils of the Sava River. Environmental monitoring and assessment , 192 , 1-20. https://doi.org/10.1007/s10661-020-8085-9. Ahmad, M., Li, J. L., Wang, P. D., Hozzein, W. N., & Li, W. J. (2020). Environmental perspectives of microplastic pollution in the aquatic environment: a review. Marine Life Science & Technology , 2 , 414-430. Zhao, M., Huang, L., Arulmani, S. R. B., Yan, J., Wu, L., Wu, T., ... & Xiao, T. (2022). Adsorption of different pollutants by using microplastic with different influencing factors and mechanisms in wastewater: A review. Nanomaterials , 12 (13), 2256. Obayomi, O., Edelstein, M., Safi, J., Mihiret, M., Ghazaryan, L., Vonshak, A., ... & Gillor, O. (2020). The combined effects of treated wastewater irrigation and plastic mulch cover on soil and crop microbial communities. Biology and Fertility of Soils , 56 , 729-742. Tables Table 1 Different size of polystyrene microplastics used in the study. Treatments Size of PS-MPs C No MPs T1 106 µm T2 50 µm T3 13 µm Table 2 Soil physiochemical parameters determined in the study. While EC=electric conductivity, SOM= soil organic matter, TN= total nitrogen, NO 3 -= nitrate, NO 2 - = nitrite, TP= total phosphorus, TC= total carbon, Cu= copper, Pb= lead, As= arsenic, Cd= cadmium, Zn= zinc Soil Physicochemical Parameters Instrument/procedure pH pH meter (Metro-pH320; Mettler Toledo Instruments Ltd., Shanghai, China) EC Conductivity meter SOM K2CrO7–H2SO4 oxidation method [46] Ammonia Potassium chloride solution extraction spectrophotometry [47] NO 3 -, and NO 2 - ultraviolet spectrophotometry [48] TN Kjeldahl’s method (HJ 717—2014) [49] TP Lu method [50] TC dry combustion method [51] Cu, Pb, Zn flame atomic absorption spectrophotometry HJ 491-2019 [52] Cd Soil-Quality-Determination of Lead, Cadmium-Graphite Furnaces atomic absorption spectrophotometry GB/T 17141-1997 [53] As GB/T 22105.2-2008 [54] Table 3 Plant physical parameters in different treatments Treatments Plant physiochemical parameters C T1 T2 T3 Plant height (cm) 33.2000 ± 1.58430 a 30.3778 ± .90523 b 29.5222 ± .64377 b 27.7111 ± .58190 c Leaf length (cm) 24.2667 ± 1.52315 a 23.6000 ± 3.07652 ab 22.3556 ± 4.77627 ab 20.9778 ± 1.28722 c Leaves fresh weight (g) 7.9800 ± .57166 a 8.2233 ± .17673 a 6.5733 ± .03786 b 6.3167 ± .05508 b Leaves dry weight (g) 1.8267 ± .01155 a 1.8100 ± .01000 a .8600 ± .00000 b .8100 ± 01000 c Stem Length (cm) 5.9444 ± .47463 a 6.1222 ± 1.50564 a 5.2778 ± 2.46971 a 4.8778 ± .59745 a Stem fresh weight (g) 1.6033 ± 1.27240 a 1.3156 ± .97700 a .8544 ± .23564 a .7967 ± .32179 a Stem dry weight (g) .8933 ± .00577 a .8900 ± .01000 a .8867 ± .00577 a .8833 ± .00577 a Root Length (cm) 9.3333 ± 3.22762 a 9.0667 ± 2.79598 a 8.6889 ± 1.15914 a 8.6444 ± 3.09843 a Root fresh weight (g) 2.1478 ± .52682 a 2.0389 ± .65202 a 1.0733 ± .34612 b 1.0656 ± .37829 b Root dry weight (g) .7633 ± .00577 a .7533 ± .00577 a .2467 ± .00577 b .1567 ± .00577 c Footnote: Mean ± SD values at ANOVA and Duncan’s test, significant P -value < 0.05 Abbreviations: C = control, T1 = PS 106 µm, T2= PS 50 µm, T3 = PS 13 µm Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6139376","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":423843295,"identity":"059f0645-b5c6-4b38-afd7-7b7894156d51","order_by":0,"name":"Jazbia Shirin","email":"data:image/png;base64,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","orcid":"","institution":"Peking University Shenzhen Graduate School, University Town","correspondingAuthor":true,"prefix":"","firstName":"Jazbia","middleName":"","lastName":"Shirin","suffix":""},{"id":423843296,"identity":"32e7a76b-a42a-4561-ada4-5a187b542cc6","order_by":1,"name":"Nazish Jabeen Abbasi","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Nazish","middleName":"Jabeen","lastName":"Abbasi","suffix":""},{"id":423843297,"identity":"b832177e-0d5f-4bea-a4d4-2f36f7883462","order_by":2,"name":"Syeda Anber Zahra","email":"","orcid":"","institution":"Shanghai Zhongqiao Vocational and Technical University","correspondingAuthor":false,"prefix":"","firstName":"Syeda","middleName":"Anber","lastName":"Zahra","suffix":""},{"id":423843298,"identity":"c109d33a-979e-4a80-ad57-74394d7304d5","order_by":3,"name":"Azhar Hussain Shah","email":"","orcid":"","institution":"Hazara University","correspondingAuthor":false,"prefix":"","firstName":"Azhar","middleName":"Hussain","lastName":"Shah","suffix":""},{"id":423843299,"identity":"57b52e05-96cd-4be4-a9be-eca1fd0e839a","order_by":4,"name":"Muhammad Afzal","email":"","orcid":"","institution":"South China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Afzal","suffix":""},{"id":423843300,"identity":"e34481d3-82d8-4a69-8727-7c04a75698e3","order_by":5,"name":"Qiyong Xu","email":"","orcid":"","institution":"Peking University Shenzhen Graduate School, University Town","correspondingAuthor":false,"prefix":"","firstName":"Qiyong","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2025-03-02 12:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6139376/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6139376/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":77954923,"identity":"fd10e344-292e-44fc-a017-706e7618dedc","added_by":"auto","created_at":"2025-03-07 08:00:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":96657,"visible":true,"origin":"","legend":"\u003cp\u003eSoil physiochemical properties. Figure a represents TP (total phosphorus), TC (total carbon), OM (organic matter), figure b represents pH, EC (electric conductivity), figure c represents NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e (nitrate), NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e (nitrite), figure d represents TN (total nitrogen) and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e (ammonia). Small letters indicate significant differences at ANOVA and Duncan’s test, P-value \u0026lt; 0.05 while T1 = PS 106 µm, T2 = PS 50 µm, T3 = PS 13 µm\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6139376/v1/0d9256ab296b7b54c63ab1a2.png"},{"id":77955713,"identity":"f63f4176-c641-4db8-85c6-7db82c0a99d0","added_by":"auto","created_at":"2025-03-07 08:08:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":67642,"visible":true,"origin":"","legend":"\u003cp\u003ePlant biochemical parameters. Figures a represents electrolytic leakage (ELL) and relative water content (RWC), and figure b represents the SOD, and POD activity of leaves respectively. Small letters indicate significant differences at ANOVA and Duncan’s test, \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.05\u003cem\u003e \u003c/em\u003ewhile C = control, T1 = PS 106 µm, T2 = PS 50 µm, T3 = PS 13 µm\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6139376/v1/580161197de17e1d01ab9ffd.png"},{"id":77954924,"identity":"ac032198-e102-4efe-89a9-25a2a07142e0","added_by":"auto","created_at":"2025-03-07 08:00:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":205502,"visible":true,"origin":"","legend":"\u003cp\u003eAlpha diversity Figure a represents Chao1, figure b represents observed species, figure c represents pielou_j and figure d represents Shannon index. Small letters indicate significant differences at ANOVA and Duncan’s test, P-value \u0026lt; 0.05 while R = rhizosphere soil, B = bulk soil, M = middle point, F = final point, C = control, T1 = PS 106 µm, T2 = PS 50 µm, T3 = PS 13 µm\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6139376/v1/848807ffe7886b1d86159d03.png"},{"id":77954926,"identity":"20c40b91-72bf-4672-a1b3-e1f76d30aa78","added_by":"auto","created_at":"2025-03-07 08:00:45","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":755509,"visible":true,"origin":"","legend":"\u003cp\u003eCommunity composition. Figure a represents bacterial community compositions at phylum level and figure b represents bacterial community compositions at the class level while R= rhizosphere soil, B= bulk soil, M= middle point, F= final point, C= control, T1= PS 106 µm, T2= PS 50 µm, T3= PS 13 µm\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6139376/v1/96ab52cbfa4c24e6032378e6.jpeg"},{"id":77954941,"identity":"fecd94b1-4654-4346-9aa7-3d4919f967b4","added_by":"auto","created_at":"2025-03-07 08:00:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":127225,"visible":true,"origin":"","legend":"\u003cp\u003eBacterial plant and animal pathogens. Figure a represents bacterial plant pathogenic species and Figure b represents the bacterial animal pathogenic species in different soil and treatments. While R= rhizosphere soil, B= bulk soil, C= control, T1= PS 106 µm, T2= PS 50 µm, T3= 13 µm\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6139376/v1/5772f1d805149e7d17354b83.png"},{"id":77954931,"identity":"7be5b1da-78df-4583-884e-309fe0ac9322","added_by":"auto","created_at":"2025-03-07 08:00:45","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":136488,"visible":true,"origin":"","legend":"\u003cp\u003eBacterial saprotrophs. Figure a represents bacterial saprotrophic species and Figure b represents the pie chart for the total average of bacterial saprotrophic species. While R= rhizosphere soil, B= bulk soil, C= control, T1= PS 106 µm, T2= PS 50 µm, T3= PS 13 µm\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6139376/v1/bd6840aaffd6a8b432aba6bb.png"},{"id":77954934,"identity":"931253a7-49fe-451a-acc7-0bec0e20adfe","added_by":"auto","created_at":"2025-03-07 08:00:45","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":101379,"visible":true,"origin":"","legend":"\u003cp\u003eRDA analysis represents the effect of environmental factors on bacterial composition While B = bulk soil, R = rhizosphere soil, C = control, T1= PS 106 µm, T2 = PS 50 µm, T3 = PS 13 µm, TP = total phosphorus, OM = organic matter, TC = total carbon, EC = electric conductivity, pH, TN=total nitrogen, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+ \u003c/sup\u003e= ammonia, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e- \u003c/sup\u003e= nitrate,\u003csup\u003e \u003c/sup\u003eNO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e- \u003c/sup\u003e= nitrite, Cd = cadmium, Cu = copper, Pb = lead, Zn = zinc and As = arsenic\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-6139376/v1/d737a599100c9b838353540f.png"},{"id":77955717,"identity":"0f160697-b0e6-4021-a297-82c304da528f","added_by":"auto","created_at":"2025-03-07 08:08:45","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":151074,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap between soil parameters including TP (total phosphorus), OM (organic matter), TC (total carbon), EC (electric conductivity), pH, TN (total nitrogen), NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e (ammonia), NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e (nitrate), NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e (nitrite), Cd (cadmium), Cu (copper), Pb (iron), Zn (zinc), As (arsenic) and bacterial phyla.\u003cem\u003e \u003c/em\u003eNote：R\u0026gt;0：positive correlation，R\u0026lt;0 ：negative correlation，R=0：uncorrelated，|R|\u0026lt;0.4indicates low linear correlation，0.4≤|R|\u0026lt;0.7indicates significant correlation，0.7≤|R|\u0026lt;1 indicates a highly linear correlation\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-6139376/v1/6f2fb4f5be72a06ac554a943.png"},{"id":82541888,"identity":"18305c50-41c9-487d-8225-ea8c8f3f4198","added_by":"auto","created_at":"2025-05-12 17:01:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2797447,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6139376/v1/38f783da-924a-4efe-803e-ccbee156e374.pdf"},{"id":77955719,"identity":"b9962df5-9146-4f7a-9c5f-36dfc2e576ef","added_by":"auto","created_at":"2025-03-07 08:08:46","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2282285,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary2.docx","url":"https://assets-eu.researchsquare.com/files/rs-6139376/v1/f38f4829d9c574c0a7e8de2c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of Heavy Metals and Polystyrene Microplastics on the Bacterial Communities in Rhizosphere and Bulk Soil and the Physiological Health of Allium fistulosum","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePlastics are extensively utilized in everyday life, contributing significantly to environmental pollution. In 2021, worldwide, plastic manufacturing reached 390.7\u0026nbsp;million tons, with China as the leading manufacturer, generating over 20% of the total (approximately 83\u0026nbsp;million tons). Microplastics, plastic fragments with a diameter of less than 5 mm, have recently gained considerable attention in environmental research. These smaller fragments are capable of adsorbing and transporting a higher concentration of pollutants and toxic substances compared to larger plastics, posing serious ecological risks \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Research on microplastics (MPs) initially concentrated on aquatic ecosystems. However, growing concerns have emerged regarding the high prevalence of microplastics in soils and their potential to affect the ecological atmosphere through interactions within the soil-plant system, drawing increased attention from researchers \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Microplastic contamination has been identified in soils globally, primarily due to the extensive use of plastic mulch in agriculture, irrigation with sewage water, disposal of waste in landfills, and activities related to industrial production \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Pang et al. \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e have reported a variety of MP kinds in agroecosystems, including polystyrene (PS), polyethylene (PE), polypropylene (PP), and polyvinyl chloride (PVC). Furthermore, Li et al. \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e documented that the average levels of PE, PS, and PP microplastics in farmland soils on the Northeast side of China were 685.55 \u0026micro;g/g, 1069.98 \u0026micro;g/g, and 864.23 \u0026micro;g/g, respectively. After entering the soil, MPs can affect plant growth by altering the soil's physiochemical properties, structure, and plants \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Microplastics can interfere with soil's physical, biological, and chemical functions by modifying its structure and impacting microbial communities \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Microplastics present in soil can adhere to plant root surfaces, possibly blocking root pores. This blockage can obstruct the uptake of water and other essential nutrients, as well as their transportation within the plant \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAdditionally, MPs in the soil can operate as an extra source of nutrients or carbon, promoting soil microbial activity and intensifying the struggle for nutrients between microbes and plants, which in turn impacts plant biomass \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Some studies indicate that microplastics (MPs) can influence the composition of soil microbial communities, leading to a reduction in both the diversity and abundance of bacteria \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Moreover, in the rhizosphere, MPs can carry and also provide an exceptional environment for soil microorganisms, especially pathogens, encouraging microbial colonization and enrichment \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. In addition, differences in microplastics, including size, polymer type, and shape, along with soil characteristics, can influence soil microbial communities, physicochemical properties, soil organisms, and plant growth. These impacts may be beneficial, harmful, or negligible \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Microplastics can adversely affect various plant biochemical and physiological processes, such as root trait changes, biomass reduction, seed germination, growth inhibition, fruit yield reduction, photosynthesis interference, genotoxicity, and oxidative damage \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFurthermore, MPs can adsorb a variety of hazardous compounds and influence plant growth and soil properties \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. Microplastics are novel pollutants in terrestrial ecosystems but there is little information available about the effect of HM and PS-MPs (that range in size from 200 to 500 \u0026micro;m) on vascular plants, which could lead to significant variability \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. Heavy metal (HM) pollution of soil has been a global environmental concern; it can occur naturally or enter the environment due to many anthropogenic activities, including mining, industry, agriculture, vehicle exhaust, and other activities. Because of the possible toxicity, non-biodegradability, and persistence of heavy metals, the buildup of HMs in soil has caused substantial concern in current decades, raising problems for both human health and soil ecosystems \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. Research has shown that when microplastics (MPs) enter the soil environment, they can adsorb or interact with heavy metals, leading to combined toxic effects. For instance, MPs can alter metal availability by modifying soil properties and influencing the structure and functions of bacterial communities \u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. The combined impact of MPs and HMs on terrestrial plants and soil health markers like soil microbiota and plant enzyme activity remains limited \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e. Recent research has reported that MPs can be a significant driver for HMs in soils due to their hydrophobic nature and large surface area; when both are present together in soil, they can affect HMs' behavior, availability to living organisms, and toxicity; which leads to potential danger to the microbiota of the soil. However, the complex interaction between microplastics and heavy metals in the soil environment is influenced by several factors, such as microplastic size, heavy metal type, and experimental conditions \u003csup\u003e[2, 11, 14; 37, 38, 39]\u003c/sup\u003e.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAccording to Shen et. al \u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e, the Tongling region of China is well-known for its plentiful copper deposits, which date back more than 3,000 years to the Shang and Zhou dynasties. The first copper mine at Tongguanshan has been in operation since 1949 \u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e. According to Wang et.al \u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e, it is also impossible to overlook the fact that Pb and Cd have the most effects on human health in this area.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eSpring onions (\u003cem\u003eAllium fistulosum\u003c/em\u003e) are a most cultivated member of the Amaryllidaceae family, characterized by their distinct flavors, high nutritional benefits, anti-obesity effects, dietary fiber, and vitamin C. Moreover, it has immense medicinal value and is useful in fever, dropsy, catarrh, and chronic bronchitis \u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e. Spring onion ranks second after tomato in the list of worldwide cultivated vegetables and China is the world's top spring-onion-producing country, with an estimated production area exceeding 500,000 ha \u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eNo previous research has reported on the combined effect of polystyrene microplastic and heavy metals on the spring onion and to the best of our knowledge, research on the impact of microplastics on higher plants remains limited. Therefore, our study will concentrate on examining the combined impact of heavy metals (HMs) contaminated soil in Tongling and various sizes of polystyrene (PS) microplastics on soil attributes (physiochemical), bacterial diversity, compositions, plant and animal pathogens in the soil, saprophytes as well as their influence on the growth and enzymatic activity of spring onion. This will be achieved through a greenhouse experiment. The aims of this study are to (1) Investigate changes in soil health attributes caused by the combination of PS-MPs and HMs. (2) Evaluate the effects of HMs and PS-MPs on the growth performance and parameters of spring onions. (3) Analyze the influence of different PS-MPs sizes on bacterial diversity, composition, and pathogenicity in rhizosphere and bulk soil within contaminated environments with HMs (4) Identify the connections between changes in soil bacterial communities caused by microplastic-heavy metal interactions and their effects on the growth and health of spring onions. Significance: (1) This study enhances our understanding of soil microecological responses to the combined existence of heavy metals and microplastics. (Ⅱ) The results offer important insights into the complex interactions between these contaminants and their combined effects on terrestrial ecosystems, serving as a scientific basis for ecological risk assessments.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study Area\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTongling City, situated in the central region of Anhui, China, experiences subtropical humid weather with distinct monsoon physiognomies. The area receives an average yearly precipitation of 1390 mm, with a yearly mean temperature of 16.2\u0026deg;C. The relative humidity ranges from 75% to 81% on a monthly average throughout the year. Tongling is known for its rich and diverse mineral resources, significant mining activities, and substantial reserves. This region has endured extensive pollution from the mining industry over an extended period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Sample collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSoil samples were obtained from the copper mine tailings disposal site (N30\u0026deg;53\u0026prime;55.3\u0026Prime;, E117\u0026deg;55\u0026prime;7.0\u0026Prime;) at a depth of 0\u0026ndash;20 cm. The collected soil was alienated into two portions: one portion was air-dried, ground, sieved, and stored at two different temperatures (4\u0026deg;C and -80\u0026deg;C) for subsequent analysis, while the other portion was sifted and directly utilized for the pot experiment in the greenhouse.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Experimental Setup\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe chose PS-MPs and\u0026nbsp;spring onion\u0026nbsp;seedlings for the pot experiment.\u0026nbsp;Spring onion\u0026rsquo;s seedlings were purchased from the local supermarket in Hefei, China; and green onion seedlings were cut 2 cm above the roots, and the roots were then used for the pot experiment.\u003c/p\u003e\n\u003cp\u003eThis spring onion was carefully chosen due to its vast nutritional benefits, widespread cultivation, and adaptable nature to diverse environmental situations \u003csup\u003e[43]\u003c/sup\u003e. Morphology and other detailed information on PS-MPs are given in supplementary figure 1. We used three different sizes of PS-MPs which are described in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA total of 20 pots, each with five replications, were used in this experiment. Each pot was filled with 7 kg of soil, and 1.4 g of microplastics per kilogram of soil was added to all pots except the control (C). Five uniformly sized seedlings were planted in each pot within a greenhouse, and consistent agronomic practices such as irrigation, weeding, and plant protection were implemented uniformly across all treatments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Soil Sampling\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSoil samples from the bulk and rhizosphere soil were carefully collected after 20 days of seedling growth to analyze the bacterial community. After 40 days, spring onions were reaped, and again soil samples were taken to evaluate soil physicochemical indicators, heavy metal concentrations, and community composition of bacteria. Plant physical parameters were also recorded during the experiment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Soil Physiochemical Analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used different soil physiochemical parameters which are described in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Plant physiochemical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMeasurements were taken for plant height, leaf diameter and length, stem and root length, as well as the fresh and dry weight of leaves, stem, and root. The relative water content (RWC) of spring onion leaves was assessed following the method described by Mayak et al. \u003csup\u003e[55]\u003c/sup\u003e, while electrolytic leakage (ELL) was evaluated using the approach outlined by Ahmad et al. \u003csup\u003e[56]\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.7\u003c/strong\u003e \u003cstrong\u003eBiochemical Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeroxidase activity was measured using the KIT Biosharp (Product No. BL1064B) from Hefei, China, and superoxide dismutase was assessed using the KIT Biosharp (Product No. BL901A), also from Hefei, China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8 DNA Extraction, PCR Ampli\u003c/strong\u003e\u003cstrong\u003efi\u003c/strong\u003e\u003cstrong\u003ecation and Sequencing\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe genomic DNA was extracted by using the TIANamp Soil DNA Kit (Tiangen, China), by following their directives and NanoDrop ND-1000 (Thermo Scientific, United States) was used to qualify the extracted DNA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor bacterial 16S rRNA sequencing, primers 515F/ 907R (5\u0026rsquo;- GTGCCAGCMGCCGCGG-3\u0026rsquo;) and (5\u0026rsquo;- CCGTCAATTCMTTTRAGTTT-3\u0026rsquo;) were used. The PCR amplification was carried out using the following protocol on an Applied Biosystems GeneAmp 9700 thermocycler: an initial denaturation at 95\u0026deg;C for 5 minutes, followed by 27 cycles of 95\u0026deg;C for 30 seconds, 55\u0026deg;C for 30 seconds, and 72\u0026deg;C for 45 seconds, with a last extension at 72\u0026deg;C for 30 seconds. The purified PCR products were sequenced using the Illumina MiSeq platform at Shanghai Biozeron Technology Co., Ltd. (Shanghai, China).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.9 Biochemical and Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe quantitative insight into Microbial Ecology 1.9.2 (QIIME) software was utilized analyze the bacterial 16S rRNAraw sequence data by following the removal of short sequences (\u0026lt;200bp), mismatched primers, and indicated chimers.\u003c/p\u003e\n\u003cp\u003eThe retained high-quality sequences were matched with their specific individual by relying on the primer and barcode details. The subsequent analysis of these sequences involved grouping them into clusters according to 97% similarity criteria and splitting them into amplicon sequence variants or operational taxonomic units. Following that, the representative sequences underwent phylogenetic analysis and classification identification, which allowed for a comprehensive understanding of the makeup of the bacterial community found in the samples.\u003c/p\u003e\n\u003cp\u003eAlpha diversity metrics, including Chao1, PD, observed species, and Shannon indices, were utilized. The alpha diversity analysis was conducted using the online platform GenesCloud Tools (https://www.genescloud.cn). Additionally, plant and animal pathogenic microorganisms were identified using the Pathogen Detection database from NCBI and relevant literature.\u003c/p\u003e\n\u003cp\u003eFor the beta diversity, NMDS was used to visualize the bacterial community between different treatments, and the LDA and LEfSe analyses were performed on an online platform huttenhower.sph.harvard.edu/galaxy to determine the differential abundance taxonomic features.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRedundancy analysis (RDA) was conducted using the vegan package in RStudio (version 1.2.1335) to assess the relationship between the microbial community and environmental factors. Statistical significance was evaluated using Duncan\u0026apos;s multiple range test (p \u0026lt; 0.05) and analysis of variance (ANOVA) in SPSS 22.0. The results were visualized using GraphPad Prism 6.0 (GraphPad Software, Inc., San Diego, CA) and Venn diagrams were constructed to show the abundance in between different treatments. \u0026nbsp; \u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Soil physiochemical properties and contaminants (HMs and PS-MPs)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were significant variations in the soil physicochemical properties across different treatments, influenced by the presence of heavy metals and PS-microplastics (Figure 1, Figure S2). The average pH values differed notably between the HMs-enriched soils and those contaminated with PS-MPs. The utmost pH value (7.71) was observed in the T3 treatment, while the lowermost pH (7.50) was noted in the C treatment. Additionally, the mean electrical conductivity (EC) value in the T3 treatment (920 \u0026mu;S cm\u0026minus; 1) was notably higher compared to the other treatments while the lowest EC (812 \u0026mu;S cm\u0026minus; 1) was recorded in the C treatment (Figure 1B). Soil organic matter (SOM), and total phosphorus (TP) were higher in treatment T2 (1.1333\u0026nbsp;mg/kg, 96.5000 mg/kg) while there was no significant difference regarding OM (organic matter) between T2 treatment and T3 treatment. Total carbon (TC) was observed highest (.6300 mg/kg) in T3 treatment.\u0026nbsp;In contrast, the lowest values of SOM, TP, and TC were recorded in C treatment (.6733 mg/kg), (84.1567\u0026nbsp;mg/kg), and (.4333\u0026nbsp;mg/kg) respectively\u0026nbsp;(Figure 1A).\u0026nbsp;The control treatment exhibited the highest average concentrations of total nitrogen (TN) and total ammonium nitrogen, with values of 488.67 mg/kg and 4.56 mg/kg, respectively. In contrast, the T1 treatment showed higher levels of total nitrate (0.29 mg/kg) and total nitrite (1.58 mg/kg). However, the lowermost concentrations of total nitrogen (265.6667 mg/kg), total ammonium nitrogen (2.1933 mg/kg) and nitrate (.3333 mg/kg) were observed in the T3 treatment. The lowest concentration of nitrite (.1767 mg/kg) was recorded in T2 treatment. (Table 3, Figure 1C, Figure 1D). The concentration of the heavy metals Pb (487.6667 mg/kg) and As (1009.0000 mg/kg) was greater in the T2 treatment and Cd (6.5333 mg/kg), Zn (1450.3333 mg/kg) and Cu (988.3333 mg/kg) in the T3 treatment. The lowest concentration of Cu (900.0000 mg/kg) and Pb (402.3333 mg/kg) was recorded in T1 treatment while the lowest concentration of Cd (4.0500 mg/kg), Zn (898.6667 mg/kg) and As (798.3333 mg/kg) in C (control) treatment. (Figure S2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Plant Physiochemical Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSignificant variations were observed in the physicochemical attributes of spring onion across different treatments, influenced by HMs and PS-MPs. The treatment with the smallest PS-MPs (T3) notably (p \u0026le; 0.05) inhibited the growth physiognomies of spring onion\u0026nbsp;(Table 3).\u003c/p\u003e\n\u003cp\u003eThe maximum decline was observed in plant height (27.7111 cm), leaf length (20.99778 cm), leaves fresh weight (6.3167 g), leaves dry weight (.8100 g), stem length (4.8778 cm), stem fresh weight (.7967 g), stem dry weight (.8833 g), root length (8.6444 cm), root fresh weight (1.0656 g) and root dry weight (1.567 g) was recorded in T3 treatment. \u0026nbsp;The highest plant height (33.3000 cm), leaf length (24.2667 cm), leaves dry weight (1.8267 g), root fresh weight (2.1478 g), and root dry weight (.7633 g) was observed in C(control) treatment. Though, there were no significant differences in root length, stem length, stem fresh and dry weight (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Plant Biochemical Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study revealed that HMs and PS-MPs had a detrimental effect on spring onions. RWC (relative water content), EL (electrolytic leakage), and enzymatic activity (SOD and POD) of spring onion leaves revealed significant differences (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026le; 0.05) in different treatments. In the case of SOD,\u0026nbsp;more elevation (3.0397\u0026nbsp;U mg-1 protein) was detected in the T3 treatment as compared to the other treatments, while the lowest was recorded (1.7382\u0026nbsp;U mg-1 protein) in C (control) treatment. POD activity and ELL also showed the same trend as SOD, here the uppermost POD value (329.4667\u0026nbsp;\u0026Delta;OD470/min/g) and ELL (33.3400)\u0026nbsp;was recorded\u0026nbsp;in the T3 treatment. The more declined POD activity (54.1333\u0026nbsp;\u0026Delta;OD470/min/g) and ELL (28.7133) were noted in Control (Figure 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Effect of MPs and HMs on the Soil Bacterial Diversity\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall bulk soil bacterial alpha diversity was higher (67181.3) than the rhizosphere bacterial soil alpha diversity (66601.1) and the middle point showed higher alpha diversity (68801.58) than the alpha diversity at the final point (64981.36). The alpha diversity in rhizosphere soil showed no significant difference in all treatments except T3RM. The highest alpha diversity was (5440.6193), (.8343), and (6.8711) in T1BM (Chao1 index, Pielou_J index, Shannon index, ANOVA, Duncan test) respectively. In the observed species, the highest alpha diversity was observed in CBM treatment (3809.3333), however, there were no significant differences in CBM and T1BM. In rhizosphere soil at the final point C (control), CBM and T1BM treatment revealed significant difference from all other treatments (Shannon index, Pielou_J index). In the Observed species CBM, CBF, and T1BM revealed significant difference from all other treatments while in the Chao1 index, CBF and T1BM also revealed significant differences from all other treatments (Figure 3, Table S1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Effect of Contaminants on the Soil Microbial Composition\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe most plentiful bacteria phylum in our study were Proteobacteria (36.12%) followed by Acidobacteriota (15.92 %), Chloroflexi (11.57%), Actinobacteria (8.35%), Bacteroidota (6.07%), Gemmatimonadota (6.01%), Planctomycetota (3.73%), Myxococcota (3.45%), Desulfobacterota (1.45%) and Armatimonadota (0.89%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe highest abundance of Proteobacteria was recorded in CRM treatment followed by T3RM and the lowest abundance was recorded in T1RF followed by T2BF and T3BF. The highest abundance of Acidobacteria was observed in T3BF followed by T2RF and the lowest abundance was recorded in T3RM followed by CRM and CRF. The uppermost abundance of Actinobacteriota was detected in treatment T1RF and Chloroflexi in T3RM (Figure S3, Figure 4A).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe most abundant class in our data was Gammaproteobacteria followed by Alphaproteobacteria, Actinobacteria, Vicinamibacteria, Bacteroidia, Gemmatimonadetes, and Anaerolineae. Class Gammaproteobacteria was most abundant in the CRF (44.69577) followed by CRM (44.29609). Class Alphaproteobacteria was present in the highest abundance in the T3RM (15.73665) followed by T2RM (15.33795). Class Actinobacteria was present in the highest abundance in T1RF (12.05461) followed by T3RM (11.07263) (Figure 4B, Figure S4).\u003c/p\u003e\n\u003cp\u003eLinear discriminant analysis (LDA) effect size (LEfSe) analysis was implemented to identify further specific taxa changes in the soil (rhizosphere and bulk) bacterial compositions between different treatments across the mid and final point using phylum to order level data. A total of 101 bacterial taxa revealed LDA scores larger than 2 in all the treatments including rhizosphere and bulk and two different sampling points (middle and final). The results showed that rhizosphere soil exhibited a higher significant abundance of bacterial taxa as compared to the other bulk soil, specifically in T3 treatment followed by T1 and C (control).\u003c/p\u003e\n\u003cp\u003eT3 treatment had an abundance of one class (Bacteroidia), two orders (i.e., Rhodobacterales and Opitutales), eight genera (i.e., Brevundimonas, Pseudoxanthomonas, Sphingopyxis, Devosia, Dyadobacter, Qipengyuania, Bosea and Sphingobium) and seven families (i.e., Caulobacteraceae, Rhodobacteraceae, Devosiaceae, Spirosomaceae, Alcaligenaceae, Moraxellaceeae and Spongiibacteraceae). While on the other hand, in the bulk soil, C(control) treatment showed highest abundance. It had an abundance of three phyla (Myxococcota, Elusimicrobia and Firmicutes), two classes (Polyangia and Holophagae), three orders (i.e., Acidiferrobacterales, Haliangiales and Myxococcales), four genera (i.e., Sulfurifustis, Haliangium, Myxococcia and Phaselicystis) and four families (i.e., Crocinitomicaceae, Phaselicystidaceae, Haliangiaceae and Acidiferrobacteraceae). In the comparison of the treatments, C (control) treatment showed higher abundance than the other treatments (T1, T2 and T3). It had an abundance of four phyla (i.e., Bacteroidota, Myxococcota, Elusimicrobia, Firmicutes), two classes (i.e., Polyangia and Holophagae), three orders (i.e., Acidiferrobacterales, Haliangiales and Myxococcales) fifteen genus (i.e., Flavobacterium, Lacibacter, Azoarcus , Rhodobacter , Dechloromonas, Caenimonas, Rhizobacter, Methylovorus, Flavihumibacter, Acidovorax, Pseudomonas, Sulfurifustis, Haliangium, Myxococcia and Phaselicystis) and \u0026nbsp;six families (i.e., Flavobacteriaceae, Pseudomonadaceae, Crocinitomicaceae, Phaselicystidaceae, Haliangiaceae and Acidiferrobacteraceae). In the comparison of two sampling points middle (M) and final (F), middle showed highest abundance especially in CBM treatment which had an abundance of two phyla (i.e., Myxococcota and Elusimicrobia), two classes (i.e., Polyangia and Holophagae), three orders (i.e., Acidiferrobacterales, Haliangiales and Myxococcales) four genus (i.e., Sulfurifustis, Haliangium, Myxococcia and Phaselicystis) and four families (i.e., Crocinitomicaceae, Phaselicystidaceae, Haliangiaceae and Acidiferrobacteraceae) (Figure S5, Figure S6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 Pathogenicity\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur results showed that the alterations also extended to microbial pathogens, with rhizosphere soil and treatments involving small PS-MPs being more enriched in pathogens\u0026nbsp;(Figure 11, Figure 12).\u0026nbsp;Bacterial plant pathogens were found to be more abundant in rhizosphere soil compared to bulk soil.\u0026nbsp;Overall total bacterial plant pathogens were more enriched in the T3R (27%) followed by T2R (20%), T1R (13%), T1B (13%), T3B (7%), T2B (7%), CR (7%) and CB (6%).\u0026nbsp;Across all treatments, three bacterial plant pathogens were identified at the species level.\u0026nbsp;The utmost abundant bacterial plant pathogen was \u003cem\u003eXanthomonas campestris\u003c/em\u003e. It was present in high abundance in T2R followed by T3R. \u003cem\u003eRathayibacter\u0026nbsp;\u003c/em\u003e\u003cem\u003etoxicus\u003c/em\u003e was present T1B followed by T1R and it was present only in C and T1 treatments in both rhizosphere and bulk soil. Surprisingly we found \u003cem\u003eAcidovorax avenae\u003c/em\u003e only in T3R treatment (Figure S7A, Figure 5A).\u003c/p\u003e\n\u003cp\u003eBcaterial animal pathogens were also more enriched in the rhizosphere soil and T3 treatment.\u003c/p\u003e\n\u003cp\u003eOverall total bacterial animal pathogens were more enriched in the T3R (22%) followed by T3B (21%), T2R (14%), T1R (14%), CR (10%), CB (7%), T2B (6%) and T1B (6%).\u003c/p\u003e\n\u003cp\u003eA total of eight bacterial animal pathogens were found across all the treatments at the specie level. The most abundant bacterial animal pathogen was \u003cem\u003eXanthomonas campestris\u003c/em\u003e. It was present in high abundance in T2R followed by T3R. \u003cem\u003eRathayibacter toxicus\u003c/em\u003e was present T1B followed by T1R and it was present only in C and T1 treatments in both bulk and rhizosphere soil. Astonishingly we found \u003cem\u003eAcidovorax avenae\u003c/em\u003e only in T3R treatment (Figure 10B, Figure 11B). \u003cem\u003eAcinetobacter nosocomialis\u003c/em\u003e was the utmost abundant animal pathogen species followed by Legionella sp. \u003cem\u003eAcinetobacter nosocomialis\u003c/em\u003e,\u003cem\u003e\u0026nbsp;Burkholderia cepacia\u003c/em\u003e,\u003cem\u003e\u0026nbsp;Escherichia coli\u0026nbsp;\u003c/em\u003eand Legionella sp.\u003cem\u003e\u0026nbsp;\u003c/em\u003ewere more enriched in T3R than other treatments while surprisingly \u003cem\u003eEscherichia coli\u0026nbsp;\u003c/em\u003ewas not present in control treatment in both bulk and rhizosphere soil (Figure 7B, Figure 5B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.7 Saprotrophs\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBacterial saprotrophic species showed more abundance in bulk soil than in rhizosphere soil and it revealed a decreasing trend while decreasing the microplastic size Overall bacterial saprotrophs were more enriched in the CB (18%) followed by CR (16%), T1R (13%), T1B (13%), T3B (13%), T2B (12%), T2R (8%) and T3R (7%). The most dominant saprotroph species was \u003cem\u003eIntrasporangium calvum DSM 43043\u003c/em\u003e followed by \u003cem\u003eIntrasporangium calvum\u003c/em\u003e, Artrobacter sp. And \u003cem\u003eFlavobacterium johnsoniae UW101\u003c/em\u003e. \u003cem\u003eIntrasporangium calvum DSM 43043\u0026nbsp;\u003c/em\u003ewas present in the highest abundance in CB treatment followed by CR. \u003cem\u003eIntrasporangium calvum\u0026nbsp;\u003c/em\u003ewas present in high abundance in CR treatment followed by CB. However, \u003cem\u003eFlavobacterium johnsoniae UW101\u003c/em\u003e was present only in T1B and T1R; \u003cem\u003eFlexibacter flexilis\u003c/em\u003e subsp. Pelliculosus was also present only in T2R. Arthrobacter sp. were present in higher abundance in T1R followed by CB while \u003cem\u003eCytophaga hutchinsonii ATCC 33406\u0026nbsp;\u003c/em\u003ewas present only in CB and T1B treatment (Figure 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8 Relationship between soil physiochemical variables, Micro plastic, HMs and bacterial community\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe relationship between environmental factors, bacterial alpha diversity, and communities was evaluated using redundancy analysis, heatmaps, and a correlation matrix (Figure 7, Figure 8, Figure S8, Table S2, Table S3, and Table S4). The first two RDA dimensions revealed an 81.68% variation in bacterial communities and environmental factors such as TP, Cd, OM nitrate, nitrite, ammonia and TN were positively correlated with RDA1. \u0026nbsp;Furthermore, T1R species were positively influenced by the environmental indicators in the direction of RDA1. CR and T1R also differed from the other treatments (Figure 7).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe relationship between environmental indicators (TP, OM, TC, EC, pH, TN, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e,\u0026nbsp;NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eNO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e, Cd, Cu, Pb, Zn, As) and\u0026nbsp;alpha\u0026nbsp;diversity (Chao1 index, Observed species, Pielou_J index, and Shannon index) were conducted by correlation analysis. According to this analysis, Chao1 index revealed a negative correlation with TP, OM, TC, EC, TN, Cd, Cu, Pb, and As. However, observed species, Pielou_J index, and Shannon index showed a negative correlation with TN,\u0026nbsp;NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e,\u0026nbsp;NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e and\u003csup\u003e\u0026nbsp;\u003c/sup\u003eNO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e only (Table S2). This study also conducted\u0026nbsp;a correlation analysis to check the relationship between environmental indicators (TP, OM, TC, EC, pH, TN,\u0026nbsp;NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e,\u0026nbsp;NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eNO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e, Cd, Cu, Pb, Zn, As) and bacterial communities at phylum and class level (Figure 8, Figure S8, Table S3, Table S4). Heatmap and correlation table showed a stronger positive correlation by Chloroflexi with As; Myxococcota with As, Pb, TP, and OM; Firmicutes with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e,\u0026nbsp;NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u0026nbsp;\u003c/sup\u003eand\u0026nbsp;NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e; Methylomirabilota with As,\u0026nbsp;pH and OM and Sumerlaeota with OM. Stronger negative correlation was showed by Myxococcota with\u0026nbsp;NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e; Firmicutes with As, Zn, Pb, Cu, Cd,\u0026nbsp;pH and TC;\u0026nbsp;Methylomirabilota with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and Fibrobacterota with\u0026nbsp;NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e at the phylum level (Figure 8, Table S3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt the class level stronger negative correlation was revealed by Actinobacteria with Cu; Thermoanaerobaculia with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e; Polyangia with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and\u0026nbsp;NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e; Chloroflexia with\u0026nbsp;NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and\u0026nbsp;TN; Acidimicrobiia with\u0026nbsp;NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e and Methylomirabilia with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e. Stronger positive correlation was showed by Thermoanaerobaculia with As, Zn, Cd, pH and OM; Polyangia with As, Zn, Pb, Cu, TP, pH and OM; Chloroflexia with As, Zn, TC, Zn, pH, TP and OM; Acidimicrobiia with Zn and Cu and Methylomirabilia with As, pH and OM (Figure S8, Table S4).\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003e\u003cstrong\u003e4.1 PS-MPs affected soil health indicators\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe addition of PS-MP and soil contaminated with heavy metals (HMs) altered the study\u0026apos;s soil health metrics (Figure 1, Figure S2). Up until now, there has been an increased interest in mixing soil contaminated with microplastics and heavy metals. Their interactions may influence changes in the physicochemical qualities of soils containing both MPs and HMs, either directly or indirectly. The metal concentrations were assumed to vary, rather than remain constant due to the non-uniform nature of the soil \u003csup\u003e[31, 57, 58, 59, 60]\u003c/sup\u003e. Previous research indicates that various variables, including the type of HMs, experimental settings, and MP characteristics, influence the complex relationship between HMs and MPs in the soil environment. Among these variables, the type and dose of MPs received considerable attention in combined polluted environments. The experimental settings may also influence the way MPs and HMs interact in soils.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt is difficult, nonetheless, to investigate every potential element affecting the coupled effects between HMs and MPs by concurrent experimentation \u003csup\u003e[2,31,61]\u003c/sup\u003e. Changes in soil pH, organic content, mineral composition, and microbial communities can impact the processes taking place in the rhizosphere \u003csup\u003e[62,63]\u003c/sup\u003e. Our findings show that MPs increased the pH of the soil compared to the control (treatment without MPs). The lowest size MPs treatment (T3) had the greatest pH (Figure 1). This went against the generally acknowledged theory that MPs can decrease as a result of heavy metal pollution \u003csup\u003e[31]\u003c/sup\u003e. One possible explanation is that Smaller microplastics have a greater surface area relative to their volume compared to larger microplastics. This increased surface area may enhance interactions with soil components, such as the release of basic compounds or adsorption of acidic substances, potentially raising the pH in comparison to other conditions. Our findings validated the interactions between HMs and MPs. MPs have the potential to change how heavy metals behave in the environment, including how they dissolve, precipitate, hydrolyze, and sorb, as well as how they affect soil pH. The addition of MPs changed the pH of the soil, although the effects varied according to MP size. Regardless of HMs, soil pH gradually rose as PS-MP size decreased. This observation sanctions that the co-occurrence of MPs with HMs can alter their effects on soil qualities. Our findings indicate that the addition of PS-MPs significantly altered the HM-contaminated soil microenvironment, with the T3 treatment demonstrating a significant increase in both SOM and EC. (Figure 1A, 1B). According to Li et al. \u003csup\u003e[64]\u003c/sup\u003e, the introduction of PE-MPs could have triggered the activation of soil pools of organic carbon (C), nitrogen (N), and phosphorus (P), promoting their integration into soil organic matter. SOM is essential for sustaining soil quality and facilitating plant growth. However, many questions remain unanswered regarding the interactions between microplastics and soil nutrients. Researchers are actively investigating the mechanisms and impacts of nanoplastics within soil ecosystems. Plants may absorb nutrients differently due to the influence of microplastics. Treatment T3 showed the highest total carbon (TC), while treatment T2 showed the highest soil total phosphorus (TP). On the other hand, the C treatment showed the lowest values of TP and TC (Figure 1A). The intriguing results of our experiment show that the presence of polystyrene microplastics (PS-MPs), especially the smaller ones, significantly impacted the soil\u0026apos;s total carbon (TC) and total phosphorus (TP) levels. Smaller PS-MP particles exhibit a higher surface area relative to their unit volume compared to larger particles. This larger surface area may improve interactions between organic matter and soil particles, which could result in a greater soil carbon retention rate. In addition, the larger surface area may provide greater opportunities for microbial colonization, which could hasten the breakdown of organic waste and the cycling of nutrients, raising TC levels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLess microbial activity and the absence of microplastics in the control treatment likely contributed to the lowest TP and TC levels. Additionally, as the MPs\u0026apos; size decreased, so did total nitrogen (TN), total ammonium nitrogen, total nitrate, and total nitrite (Figure 1C, Figure 1D). It is possible that smaller PS-MPs hastened the transformation of nitrogen compounds by increasing microbial activity. For instance, the depletion of nitrate, ammonium, and nitrite in the soil may result from increased nitrification or denitrification processes. Microbes may have been able to quickly change ammonium into nitrate and nitrite, and then into nitrogen gas, thanks to the huge surface area of small PS-MPs. This process is called denitrification, and it would have lowered the amount of nitrogen in the soil. The treatment sans microplastics had the lowest concentration of heavy metals. This might be due to that PS-MPs and heavy metals have bonded to form complexes that make the metals more soluble in soil solutions and raise their concentrations in soil treated with microplastics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2 PS-MPs affect physiochemical attributes and antioxidant activity of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003espring onion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMPs have a direct or indirect impact on the growth of plants, as they are a critical part of the soil ecosystem \u003csup\u003e[65]\u003c/sup\u003e. In this study, HMs and PS-MPs considerably altered the physiochemical properties of spring onion. The T3 treatment resulted in a significant reduction in plant height, leaf length, fresh and dry weights, stem length, stem fresh and dry weights, as well as root length, fresh weight, and dry weight. This showed that MP size played a big role in slowing the growth of spring onion\u0026nbsp;(Table S3). Additionally, prior research has shown that MPs have a negative impact on plant physiology, growth, and both direct and indirect toxicity \u003csup\u003e[ 64, 66, 67]\u003c/sup\u003e. Li et al. \u003csup\u003e[64]\u003c/sup\u003e further verified that the greater the inhibition of plant growth caused by MPs, the smaller the particle size.\u003c/p\u003e\n\u003cp\u003eFurthermore, smaller MP particles tend to have a greater ability to adsorb metal ions, which could contribute to reduced plant growth. Due to their hydrophobic nature, MPs can easily adsorb various pollutants \u003csup\u003e[68, 69]\u003c/sup\u003e. In contrast to the other treatments, the T3 treatment in our study showed a greater increase in ELL (electrolytic leakage) and enzymatic activity (SOD and POD) of spring onion\u0026nbsp;leaves, whereas the control group exhibited a greater reduction in POD, SOD, and ELL (Figure 2). This finding indicates unequivocally that MPs have the ability to compromise plant cell membrane integrity and that plants are abler to withstand HM stress than MPs. When compared to the control, the plants\u0026apos; relative water content showed a significant reduction in physiology due to pollutants. Damage to the membrane may be the cause of this parameter drop (ELL). Our findings demonstrated significant membrane leakage in T3 and suggested that stress-induced membrane damage occurred in \u003cem\u003eAllium fistulosum\u003c/em\u003e. These findings are sustained by the other research \u003csup\u003e[70,71,71]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe authors argued that ROS created by heavy metals and MPs stress led to oxidative stress, increased membrane leakage, and MDA generation. Our findings revealed that the hydrophobic nature of heavy metals and MPs has subjected spring onion\u0026nbsp;to a variety of environmental stressors, including drought. This has made the plant more susceptible to these stressors, which may affect its ability to fight off oxidative stress. This phenomenon has also been previously documented and explained \u003csup\u003e[71, 72]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3 PS-MPs effect on soil bacterial diversity and composition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSoil microorganisms are critical to the operation of soil ecosystems because they participate in soil nutrient cycling and energy flows, micro-ecology management, and sustainable soil productivity \u003csup\u003e[73]\u003c/sup\u003e. At the middle and end points of our study, we looked at how the interaction between PS-MPs and HMs impacts saprotrophs, higher plant species (\u003cem\u003eAllium fistulosum\u003c/em\u003e), bacterial diversity, and composition in both the rhizosphere and bulk soil. This is the first study to do so. In our study, bulk soil had a higher alpha diversity than rhizosphere soil, and the alpha diversity at the middle point was greater than that at the final point. (Table S1, Figure 3). Our research aligns with earlier investigations. The microbial community in the soil plastisphere is much different from that in other soil compartments, according to research by Rillig et al. \u003csup\u003e[74]\u003c/sup\u003e. If the environment in the rhizosphere changes, it can have a direct effect on the microbes and chemicals in the soil \u003csup\u003e[35]\u003c/sup\u003e. According to Yi et al. \u003csup\u003e[75]\u003c/sup\u003e, adding membrane-like PE and fibrous PP changed the alpha diversity and soil microbial communities in a big way. Rong et al. \u003csup\u003e[76]\u003c/sup\u003e found that varying amounts of polyethylene-microplastics only marginally impacted soil bacterial diversity, despite variations at the genus level.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe middle point of our investigation had a higher alpha diversity than the end point. This could be the result of exposure time. According to Huffer et al. \u003csup\u003e[77]\u003c/sup\u003e, differences in MP type size, soil, and exposure period can have positive, negative, or negligible effects on soil microbial communities and plant growth. We discovered the highest abundance of the most prevalent phylum Proteobacteria in the CRM treatment, followed by T3RM, and the lowest abundance in the T1RF treatment, with T2BF and T3BF following. In our investigation, the PS-MPs did not significantly impact the composition of the bacterial community. Furthermore, the class with the highest abundance in our data was Gammaproteobacteria, which was most prevalent in the CRF and then the CRM. Thus, our findings indicate that MP exposure duration had a greater impact on Proteobacteria, but that at a middle point, PS-MP contamination prevailed. Class Gammaproteobacteria may have a tolerance against HMs by various mechanisms (including by metal-binding proteins, changing efflux pumps, and other adaptations). However, when PS-MPs and HMs combine, the composition of bacteria remains largely unknown. In their investigation, Qi et al. \u003csup\u003e[78]\u0026nbsp;\u003c/sup\u003esimilarly failed to discover any appreciable variations in the variety and composition of bacteria. The results of linear discriminant analysis (LDA) effect size (LEfSe) analysis indicated that, particularly in the T3 treatment, the bacterial taxa in the rhizosphere soil were much more abundant than in the bulk soil. However, the C treatment exhibited the highest abundance in the bulk soil; a comparison of the treatments revealed that the C treatment outperformed the other treatments in terms of abundance, and a comparison of the two sampling points revealed that the middle point displayed the highest abundance. In a former study, Zeb et al. \u003csup\u003e[35]\u003c/sup\u003e also specified that changes in the rhizosphere environment may have a direct effect on the rhizosphere soil microbial community.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4 PS-MPs effect on soil bacterial pathogens and saprotrophs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study demonstrated that the observed alterations also extended to bacterial pathogens. Treatments involving rhizosphere soil and small MPs showed a higher enrichment of microbial pathogens\u0026nbsp;(Figure 5, Figure S7).\u0026nbsp;Both bacterial plant and animal pathogens were found to be more abundant in the rhizosphere soil compared to bulk soil.\u0026nbsp;Overall both total bacterial plant and animal pathogens were more enriched in the T3R. Pathogens may also be the reason behind the growth decline of\u0026nbsp;spring onion.\u003c/p\u003e\n\u003cp\u003eAcross all treatments, a total of eight bacterial animal pathogens and three bacterial plant pathogens were identified at the species level. The most abundant bacterial plant pathogen was \u003cem\u003eXanthomonas campestris\u003c/em\u003e followed by \u003cem\u003eRathayibacter toxicus\u003c/em\u003e and \u003cem\u003eAcidovorax avenae\u003c/em\u003e. \u003cem\u003eAcinetobacter nosocomialis\u003c/em\u003e was the most abundant animal pathogen species followed by Legionella sp. \u003cem\u003eAcinetobacter nosocomialis, Burkholderia cepacia, Escherichia coli.\u0026nbsp;\u003c/em\u003eHence, it verified that PS-MPs can hinder with bacterial pathogens and small sized MPs can greatly impact the rhizosphere soil. The direct reason may be that small-sized polystyrene microplastics have a bigger surface area, which provides more sites for microbial colonization, including pathogens. This may directly promote the growth and prevalence of pathogenic microorganisms in the rhizosphere soil.\u0026nbsp;The indirect reason may be that stress induced by the presence of small PS-MPs and HMs weaken plant defenses, and make them more susceptible to pathogens. Weaker plants may release more root exudates, which could serve as additional nutrients for pathogenic microorganisms in the rhizosphere.\u0026nbsp;However, there are not so much data is available on the MP\u0026apos;s effect on the bacterial pathogens. More research work is required in this aspect. In a previous study, Azeem et al. and Shirin et al. \u003csup\u003e[24, 79]\u003c/sup\u003e stated that\u0026nbsp;in the rhizosphere, MPs can provide an exceptional environment for soil microorganisms, especially pathogens, encouraging microbial colonization and enrichment.\u003c/p\u003e\n\u003cp\u003eSoil fungi and bacteria play a major role in agroecosystems by influencing soil nutrient cycling and sensitivity. In the soil ecosystem, soil bacteria play a significant role as decomposers of organic matter. They release specific extracellular enzymes that transform important organic compounds into monomers, which plants then absorb \u003csup\u003e[80, 81]\u003c/sup\u003e. Bacterial saprotrophic species were less common as the microplastics got smaller in our study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThey were more common in bulk soil than in rhizosphere soil. In\u0026nbsp;general,\u0026nbsp;the\u0026nbsp;CB\u0026nbsp;and\u0026nbsp;CR\u0026nbsp;had\u0026nbsp;higher\u0026nbsp;concentrations\u0026nbsp;of\u0026nbsp;bacterial\u0026nbsp;saprotrophs\u0026nbsp;(Figure\u0026nbsp;6). Our findings contradict the 2019 Huang et al. study, which suggested that MPs might increase the microbial populations involved in self-degradation. This might be because the rhizosphere, which attracts a diverse range of microorganisms, including pathogens, is a highly competitive environment because of the presence of root exudates. In this nutrient-rich zine, the pathogens may outcompete the saprotrophic bacteria, which break down organic matter. This might be the reason that saprotrophic bacteria were more common in bulk soil.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.5 Correlations between PS-MPS, HMs, shifts in soil bacterial communities and soil physiochemical indicators\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe relationship between environmental factors, bacterial alpha diversity, and communities was evaluated using redundancy analysis, heatmaps, and a correlation matrix\u0026nbsp;(Figure 7, Figure 8, Figure S8, Table S2, Table S3, and Table S4).\u0026nbsp;Our results revealed that the environmental indicators alter the bacterial alpha diversity and community.\u0026nbsp;The first two RDA dimensions exhibited an 81.68% variation in bacterial communities. Environmental factors such as Cd, nitrate, nitrite, ammonia, TP, TN, and OM were positively correlated with RDA1. \u0026nbsp;Moreover, T1R species were positively influenced by the environmental indicators in the direction of RDA1. CR and T1R also differed from the other treatments (Figure 7).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccording to correlation analysis, Chao1 index revealed a negative correlation with TP, OM, TC, EC, TN, Cd, Cu, Pb, and As. However, observed species, Pielou_J index, and Shannon index showed a negative correlation with TN, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e and\u003csup\u003e\u0026nbsp;\u003c/sup\u003eNO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e only (Table S2). Heatmap and correlation table showed a stronger positive correlation by Chloroflexi with As; Myxococcota with As, Pb, TP, and OM; Firmicutes with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u0026nbsp;\u003c/sup\u003eand NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e; Methylomirabilota with As, pH and OM and Sumerlaeota with OM. Stronger negative correlation was showed by Myxococcota with NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e; Firmicutes with As, Zn, Pb, Cu, Cd, pH and TC; Methylomirabilota with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and Fibrobacterota with NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e at the phylum level (Figure 8, Table S3). At the class level stronger negative correlation was revealed by Actinobacteria with Cu; Thermoanaerobaculia with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e; Polyangia with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e; Chloroflexia with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and TN; Acidimicrobiia with NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e and Methylomirabilia with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e. Stronger positive correlation was showed by Thermoanaerobaculia with As, Zn, Cd, pH and OM; Polyangia with As, Zn, Pb, Cu, TP, pH and OM; Chloroflexia with As, Zn, Cd, TC, TP, pH and OM; Acidimicrobia with Zn and Cu and Methylomirabilia with As, pH and OM (Figure S8, Table S4)\u003c/p\u003e\n\u003cp\u003eAccording to Mataruga et al. \u003csup\u003e[20]\u003c/sup\u003e, the soil\u0026apos;s pH significantly affects how efficiently it binds to copper. Raising the soil\u0026apos;s pH to 7-8 resulted in a decrease in the amount of accessible copper in the soil. The recent research, which indicates a positive link between pH and Cu content, is in conflict with these findings. Additionally, this study revealed both competitive and synergistic relationships between bacterial communities and soil physiochemical characteristics, which is explained above. Previous studies have shown that MPs are capable of absorbing a variety of pollutants \u003csup\u003e[83, 84]\u003c/sup\u003e. Obayomi et al \u003csup\u003e[85]\u003c/sup\u003e report that microplastics of different particle sizes can absorb varying types and amounts of pollutants., and they observe a strong correlation between soil bacterial abundance and contaminants in the soil. As a result, we believe that the pollutants that MPs adsorb contribute to the diversity of microbial communities in MP-contaminated environments. The findings of this study indicate that differences in bacterial community distribution could serve as an ecological marker for evaluating soil environmental health.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn this study, we focused on the combined influence of polystyrene microplastic and heavy metals on the soil health indicators; bacterial diversity, and composition at two different points and also in the two different types of soil (rhizosphere and bulk); and the growth indicators of \u003cem\u003eAllium fistulosum\u003c/em\u003e. This study revealed that soil physiochemical properties were altered by the addition of microplastic. The smallest microplastic treatment (T3) significantly increased soil organic matter, pH, total carbon, electric conductivity, zinc, copper, cadmium and significantly reduced total nitrogen, ammonia and nitrate. The combination of polystyrene microplastic and heavy metals was also more lethal for the spring onion. Polystyrene microplastic with small size brutally impeded the growth indicators of \u003cem\u003eAllium fistulosum\u003c/em\u003e including plant height, leaf length, fresh weight of root and stem, dry weight of leaves and root. However, microplastic did not affect the dry and fresh weight of stem and length of stem and root. Small microplastic treatment also reduced relative water content, and increased antioxidant activity and electrolytic leakage of the leaves. Our study also identified both cooperative and competitive relationships between soil health indicators and bacterial diversity and composition. Exposure to small microplastics at the intermediate stage led to a higher bacterial diversity compared to the final stage. So, our study confirms that microplastic, different types of soil, and different time zones play a vital role in bacterial diversity. We also observed that microplastic played an important role in reducing saprophytes, especially in the smaller microplastic treatment and in rhizosphere soil. Microplastic also increased plant and animal pathogen species especially in the small microplastic treatment and rhizosphere soil.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRecommendations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe recommend conducting detailed and thorough research focusing on how other environmental stressors, such as drought, salinity, or nutrient deficiency, interact with microplastics and heavy metals to influence soil and plant health and to assess the impact of combined microplastic and heavy metal pollution on ecosystem services such as soil fertility, water retention, and plant productivity, to understand the broader ecological implications of these pollutants. This will provide a broader understanding of the ecological implications and help in developing more resilient agricultural practices.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Higher Education Institution Collaborative Innovation Project of Anhui Province, China (No. GXXT-2021\u0026ndash;061). This work was also supported by the China Scholarship Council (CSC: 2019GXZ014633 to Jazbia Shirin).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthors ContributionJazbia Shirin: Writing \u0026ndash; original draft, writing \u0026ndash; review \u0026amp; editing, Conceptualization, Data curation, Formal analysis, Software, Validation, Visualization, Nazish Jabeen Abbasi: Formal analysis, Data curation, and Software, Syeda Anber Zahra: review and editing, formal analysis, Azhar Hussain Shah: Writing \u0026ndash; review \u0026amp; editing, Muhammad Afzal: Formal analysis, Qiyong Xu: Conceptualization, Supervision, Visualization, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eAcknowledgmentThe authors are thankful to Prof. Qingye Sun, Anhui University, Hefei, for providing funding and the basic instruments and space for conducting this study, and to Dr. Rizwan Abbasi CGTN, for his continuous support and guidance.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData will be provided if required.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eThacharodi, A., Meenatchi, R., Hassan, S., Hussain, N., Bhat, M.A., Arockiaraj, J., Ngo, H.H., Le, Q.H. and Pugazhendhi, A., 2024. 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The combined effects of treated wastewater irrigation and plastic mulch cover on soil and crop microbial communities. \u003cem\u003eBiology and Fertility of Soils\u003c/em\u003e, \u003cem\u003e56\u003c/em\u003e, 729-742.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 Different size of polystyrene microplastics used in the study.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatments\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSize of PS-MPs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eNo MPs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e106 \u0026micro;m\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e50 \u0026micro;m\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e13 \u0026micro;m\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 Soil physiochemical parameters determined in the study. While EC=electric conductivity, SOM= soil organic matter, TN= total nitrogen, NO\u003csub\u003e3\u003c/sub\u003e-= nitrate, NO\u003csub\u003e2\u003c/sub\u003e- = nitrite, TP= total phosphorus, TC= total carbon, Cu= copper, Pb= lead, As= arsenic, Cd= cadmium, Zn= zinc\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"696\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSoil Physicochemical Parameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInstrument/procedure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003epH meter\u0026nbsp;(Metro-pH320; Mettler Toledo Instruments Ltd., Shanghai, China)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eEC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eConductivity meter\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eSOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eK2CrO7\u0026ndash;H2SO4 oxidation method \u003csup\u003e[46]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eAmmonia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003ePotassium chloride solution extraction spectrophotometry \u003csup\u003e[47]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eNO\u003csub\u003e3\u003c/sub\u003e-, and\u0026nbsp;NO\u003csub\u003e2\u003c/sub\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eultraviolet spectrophotometry \u003csup\u003e[48]\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eKjeldahl\u0026rsquo;s method (HJ 717\u0026mdash;2014) \u003csup\u003e[49]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eTP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eLu method \u003csup\u003e[50]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003edry combustion method \u003csup\u003e[51]\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eCu, Pb, Zn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eflame atomic absorption spectrophotometry HJ 491-2019 \u003csup\u003e[52]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eSoil-Quality-Determination of Lead, Cadmium-Graphite Furnaces atomic absorption spectrophotometry GB/T 17141-1997 \u003csup\u003e[53]\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 348px;\"\u003e\n \u003cp\u003eGB/T 22105.2-2008 \u003csup\u003e[54]\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 Plant physical parameters in different treatments\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"654\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 654px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatments\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlant physiochemical parameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003ePlant height (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e33.2000\u0026nbsp;\u0026plusmn;\u0026nbsp;1.58430 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e30.3778\u0026nbsp;\u0026plusmn;\u0026nbsp;.90523 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e29.5222\u0026nbsp;\u0026plusmn;\u0026nbsp;.64377 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e27.7111\u0026nbsp;\u0026plusmn;\u0026nbsp;.58190 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eLeaf length (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e24.2667\u0026nbsp;\u0026plusmn;\u0026nbsp;1.52315 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e23.6000\u0026nbsp;\u0026plusmn;\u0026nbsp;3.07652 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e22.3556\u0026nbsp;\u0026plusmn;\u0026nbsp;4.77627 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e20.9778\u0026nbsp;\u0026plusmn;\u0026nbsp;1.28722 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eLeaves fresh weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e7.9800\u0026nbsp;\u0026plusmn;\u0026nbsp;.57166 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e8.2233\u0026nbsp;\u0026plusmn;\u0026nbsp;.17673 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e6.5733 \u0026plusmn; .03786 \u0026nbsp;b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e6.3167\u0026nbsp;\u0026plusmn;\u0026nbsp;.05508 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eLeaves dry weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e1.8267\u0026nbsp;\u0026plusmn;\u0026nbsp;.01155 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.8100\u0026nbsp;\u0026plusmn;\u0026nbsp;.01000 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e.8600\u0026nbsp;\u0026plusmn;\u0026nbsp;.00000 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e.8100\u0026nbsp;\u0026plusmn;\u0026nbsp;01000 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eStem Length (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e5.9444\u0026nbsp;\u0026plusmn;\u0026nbsp;.47463 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e6.1222\u0026nbsp;\u0026plusmn;\u0026nbsp;1.50564 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e5.2778\u0026nbsp;\u0026plusmn;\u0026nbsp;2.46971 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e4.8778\u0026nbsp;\u0026plusmn;\u0026nbsp;.59745 a\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eStem fresh weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e1.6033\u0026nbsp;\u0026plusmn;\u0026nbsp;1.27240 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.3156\u0026nbsp;\u0026plusmn;\u0026nbsp;.97700 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e.8544\u0026nbsp;\u0026plusmn;\u0026nbsp;.23564 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e.7967\u0026nbsp;\u0026plusmn;\u0026nbsp;.32179 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eStem dry weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e.8933\u0026nbsp;\u0026plusmn;\u0026nbsp;.00577 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e.8900 \u0026plusmn; .01000 \u0026nbsp;a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e.8867\u0026nbsp;\u0026plusmn;\u0026nbsp;.00577 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e.8833\u0026nbsp;\u0026plusmn;\u0026nbsp;.00577 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRoot Length (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e9.3333\u0026nbsp;\u0026plusmn;\u0026nbsp;3.22762 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e9.0667\u0026nbsp;\u0026plusmn;\u0026nbsp;2.79598 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e8.6889\u0026nbsp;\u0026plusmn;\u0026nbsp;1.15914 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e8.6444\u0026nbsp;\u0026plusmn;\u0026nbsp;3.09843 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRoot fresh weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e2.1478\u0026nbsp;\u0026plusmn;\u0026nbsp;.52682 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e2.0389\u0026nbsp;\u0026plusmn;\u0026nbsp;.65202 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.0733\u0026nbsp;\u0026plusmn;\u0026nbsp;.34612 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e1.0656\u0026nbsp;\u0026plusmn;\u0026nbsp;.37829 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRoot dry weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e.7633\u0026nbsp;\u0026plusmn;\u0026nbsp;.00577 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e.7533\u0026nbsp;\u0026plusmn;\u0026nbsp;.00577 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e.2467\u0026nbsp;\u0026plusmn;\u0026nbsp;.00577 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e.1567\u0026nbsp;\u0026plusmn;\u0026nbsp;.00577 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFootnote: Mean \u0026plusmn; SD values at ANOVA and Duncan\u0026rsquo;s test, significant \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.05\u003c/p\u003e\n\u003cp\u003eAbbreviations: C = control, T1 = PS 106 \u0026micro;m, T2= PS 50 \u0026micro;m, T3 = PS 13 \u0026micro;m\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Allium fistulosum, Heavy Metals, Polystyrene Microplastic, Bacteria","lastPublishedDoi":"10.21203/rs.3.rs-6139376/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6139376/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicroplastics (MPs) are emerging as significant global pollutants due to their persistence, versatility, and resilience across diverse ecosystems. However, research focusing on their combined impact with heavy metals (HMs), their relations with soil microbial communities, particularly saprophytes and pathogenic species, and their influence on terrestrial plants and soil physicochemical properties remains scarce. This study aimed to examine the combined effects of HMs (copper, arsenic, zinc, cadmium, and lead) in contaminated soils from Tongling City and polystyrene microplastics (PS-MP) of varying sizes (13 \u0026micro;m, 50 \u0026micro;m, and 106 \u0026micro;m). The research evaluated changes in soil physiochemical properties, bacterial diversity and composition, plant and animal pathogens, saprotrophs in both bulk and rhizosphere soils, as well as the impact on antioxidant activity and the growth of \u003cem\u003eAllium fistulosum\u003c/em\u003e. The blend of PS-MPs and heavy metals was lethal for the spring onion. The smallest MP treatment significantly increased soil organic matter, pH, total carbon, electric conductivity, zinc, copper, and cadmium and significantly reduced total nitrogen, ammonia, and nitrate, and also brutally impeded the growth indicators of spring onion including plant height, leaves length, fresh weight of root, dry weight of leaves and root. However, MP did not affect the length, fresh, and dry weight of stem and root length. Small MP treatment also reduced relative water content, and increased antioxidant activity and electrolytic leakage of the spring onion. Treatment with smaller MP at the middle point (at day 20) increased the bacterial diversity as compared to the final point (at day 40). Microplastic also played a crucial role in the reduction of saprotrophs and increased plant and animal pathogens especially in the small MP treatment and in rhizosphere soil.\u003c/p\u003e \u003cp\u003eOur findings revealed that the interaction of heavy metals (HMs) with smaller-sized microplastics (MPs) posed greater harm to soil bacterial communities and the growth of spring onion. This study also highlights critical knowledge gaps and underscores the need for further research into the ecological risks associated with PS-MPs and HMs.\u003c/p\u003e","manuscriptTitle":"Impact of Heavy Metals and Polystyrene Microplastics on the Bacterial Communities in Rhizosphere and Bulk Soil and the Physiological Health of Allium fistulosum","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-07 08:00:40","doi":"10.21203/rs.3.rs-6139376/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9b66c194-e400-41a1-b601-8a9a201cd3f7","owner":[],"postedDate":"March 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-12T16:53:33+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-07 08:00:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6139376","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6139376","identity":"rs-6139376","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}