1 INTRODUCTION

Plastics pollution has become a global issue since these plastic particles are distributed all over the world, even in the deep ocean (Waller et al., 2017; Zhang et al., 2020). Among these plastic litters, particles in diameter less than 5 mm is defi ned as microplastics (MPs) (Thompson et al., 2004), which originate mainly from personal care products or breakdown of large plastics (Auta et al., 2017). As a kind of strong and durable material, MPs are hard to degradation and able to exit for decades in the environment. MPs can cause several serious environmental problems, making it a global concern. The small size of these pollutants are often taken by mistake in marine organisms due sometimes to the similarity to their food (Mbedzi et al., 2020). MPs have been detected in a wide range of organisms, from large marine animals such as beluga whales to microscopic life such as zooplankton (Moore et al., 2020; Zheng et al., 2020). MPs also act as vectors for other chemical contaminants and facilitate their transport in the environment. Heavy metal adsorption has been observed on diff erent MPs polymers from the coastal south India (Selvam et al., 2021). The ubiquitous MPs are considered as ideal carriers for polycyclic aromatic hydrocarbons to spread in the nature (Yu et al., 2020). During MPs retention in the environment, some additives such as phthalates introduced in plastic manufacture are easily released via physical dispersion (Ye et al., 2020). Similar to natural substrates in the environment, MPs also act as habitats for biota to colonize and serve as vectors for pathogens, resulting in potential environmental and ecological risks (Wu et al., 2019).

In marine coastal environment, microorganisms serve as pioneering colonizers and participate in critical ecosystem processes, such as biogeochemical cycling and primary production (Dang et al., 2008). Because MPs have a longer half-life than most natural substrates, they can present a unique habitable environment for microorganism to colonize, which is so called "Plastisphere" (Zettler et al., 2013; Huang et al., 2019b). Previous studies have reported the interactions between MPs and their colonized microorganisms. For examples, MPs from cotton fields are colonized by various microorganisms, the structure of which is significantly different from those in the surrounding soil (Zhang et al., 2019). High-throughput sequencing results indicate that microorganisms on MPs are less diverse than those in water, and pathogens are richer in MPs (McCormick et al., 2014). Moreover, eukaryotic life containing more than 500 taxa are detected on MPs, which is significantly distinct from wood and water in the coastal Baltic Sea (Kettner et al., 2019). Selective enrichment of bacteria by MPs may alter the microbiota communities of surrounding environment, including sediment and water (Kettner et al., 2017; Jiang et al., 2018). As microorganisms play critical roles in ecosystems, the change of MPs to microorganisms might influence the ecosystem services and functions (Chen et al., 2020). Therefore, investigation into the interaction between microbiota on MPs and the environment can help us gain further insight into the potential ecological risks of MPs.

Mangrove ecosystem is an important boundary between land and sea, acting as a potential convergence area of MPs caused by marine and terrestrial activities (Deng et al., 2021). As vegetated coastal habitats, mangroves can sequester MPs in their sediments because they generally support high sediment accretion rates (Nor and Obbard, 2014). Along the south-eastern coast of China, different shapes of MPs are observed in the mangrove sediments in various colors and a major size less than 2 mm (Zhou et al., 2020). MPs are also widely distributed in mangrove forests in the southern Iran, most of them are black and made of polystyrene. Different types of studied area and sediment texture resulted in distinct frequency of MPs (Maghsodian et al., 2021). Thus, the characteristics, distribution, and retention rates of MPs in mangroves are influenced by both anthropic activities (i.e., tourism, aquaculture, coastal dumping) and natural factors (i.e., sediment grain size, mangrove density, water hydrodynamics) (Lima et al., 2016; Zhou et al., 2020). Zhujiang (Pearl) River estuary (ZRE) is one of the largest estuaries of China, and the developed economy and rapid urbanization in the Zhujiang River delta have caused serious MPs pollution (Yan et al., 2019). Mangroves are also distributed in this subtropical estuary, serving as a sink for MPs. High abundance of MPs was observed in mangrove sediments sampled from ZRE in 2015 (Zuo et al., 2020). Despite these available reports on MPs pollution in mangroves, studies focusing on microbial colonization on MPs and in ambient environment of mangroves are scarce.

As a distinct substrate emerging in the mangroves, MPs may be colonized by various of bacteria at surface. Bacteria from MPs and the ambient environment may be characterized by distinct communities and functions, and then cause unpredictable influences on mangrove ecosystems. We first reported the difference of bacterial communities, functions and complexity compared MPs with surrounding sediments from mangroves in ZRE. Via detailed study and in-depth discussion on microbiota will provide insights into the microorganisms on MPs in mangroves ecosystems and related consequences for ecological function.

2 MATERIAL AND METHOD 2.1 Sample collection

Sediment samples (n=21) were collected from seven sampling sites in the ZRE of Guangdong Province, China in January 2021. Seven sampling sites include Qi'ao Island Mangrove Nature Reserve in Zhuhai City (n=9) (S1–S3), Mangrove Wetland Park in Seagull Island in Guangzhou City (n=6) (S4–S5), and Mangrove Seaside Ecological Park (S6), and West Bay Coastal Park in Shenzhen City (n=6) (S7) (Fig. 1). Detailed descriptions for the sampling sites are shown in Supplementary Table S1. For the sampling methods please refer to our previous report (Yan et al., 2021). Briefly, a stainless shovel was used to randomly collect three samples (each 500 g) with a depth of 0–20 mm at each site and stored at 4 ℃. For each sampling site, 10-g sediment was separated from each sample and thoroughly mixed to one sample per site and stored at -80 ℃ for DNA extraction. Sterilized forceps were used to pick up 20 individual MPs (> 1 mm) directly at each site (Zhang et al., 2019). These MPs were rinsed with sterilized water for six times and stored in 1.5-mL centrifuge tubes at -80 ℃ before DNA extraction of microorganisms on MPs.

2.2 Isolation of microplastics in sediments

Sediments were dried at 70 ℃ for 48 h before MPs extraction. To float dense polymers, 100-mL zinc chloride (1.5 g/cm³) was added to 10-g oven-dried sediments from each sediment sample and settled for 24 h for density separation (Coppock et al., 2017). The supernatant was collected and filtered using a nitrocellulose filter with 0.45-μm pore size under vacuum. The filtered MPs were transferred to glass dishes and air-dried before observation. To prevent airborne MPs, three parallel treatments with Milli-Q water were conducted to act as a control group throughout the whole experiment.

2.3 Characterization of microplastics

A dissecting microscope (Optec SZ680, China) was applied to observe the appearance feature of MPs, including their size (i.e., diameter), shape, and color. Their sizes were measured by S-EYE software. Their shapes can be divided into four types: film, pellet, fiber, and fragment. Fiber was a slender strip. The fragments were debris with certain thickness. Pellets were three-dimensional round beads. A film is a piece of slice (Nie et al., 2019). The surface morphology of MPs was investigated by scanning electron microscope (SEM; Verios 460, FEI, USA). Briefly, several fibers were selected and rinsed with sterile water. After dehydrated by graded ethanol, MPs samples were dried in a critical-point dryer (EM CPD300, Leica, German) and coated with evaporated gold before analysis (Yan et al., 2021). To investigate the polymer type of MPs, we employed Micro-Fourier transformed infrared spectroscopy (μ-FTIR) (Nicolet iN10, Thermo Fisher Scientific, USA) to analyze the major composition of MPs randomly selected from sediment samples (Zhou et al., 2020). A total of 83 particles were identified by μ-FTIR. The recorded spectrum was compared with that in the standard FTIR spectrum databases and the level of certainty was set up to 70%. Overall, 14.46% of the particles were identified as false MPs. Thus, we recalculated the abundance of MPs by excluding the false ones.

2.4 DNA extraction and sequencing

DNA of organisms was extracted from microplastics (n=20) and sediments (1 g) using the DNeasy PowerSoil Kit (Qiagen, Shanghai, China) according to the protocols. The quality of the extracted DNA was evaluated by 1% agarose gel electrophoresis. The concentration of the total DNA was measured by NanoVuePlus Spectrophotometer (GE Healthcare, USA). Two specific primers, 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′), was designed to amplify the V4 region of 16S rRNA gene (Zeng et al., 2017). The PCR was performed according to a previous study (Ren et al., 2020). The PCR products were purified by QIAquick™ Gel Extraction Kit (Qiagen, Germany) and used for further sequencing by Illumina Hiseq2500 platform of Novogene Bioinformatics Technology Co., Ltd. (Beijing, China).

2.5 Bioinformatics analysis

Raw sequences were filtered by Quantitative Insights Into Microbial Ecology (QIIME, http://qiime.org/index.html) (Caporaso et al., 2010). Sequences were assigned to the same operational taxonomic units (OTUs) with 97% similarity by Uparse (Version 7.0.1001, http://drive5.com/uparse/). The representative sequence indicated the highest frequency sequences in OTUs. GreenGene Database (http://greengenes.lbl.gov/) was used to align the sequences. The taxonomic information was annotated by Ribosomal Database Project (RDP) classifier (Version 2.2, http://sourceforge.net/projects/rdp-classifier/) with 80% confidence threshold. Data of OTUs abundance was normalized by the standard sample with the minimum sequences (Yan et al., 2021). Alpha diversity metrics were calculated to compare the richness and evenness via QIIME. Significance tests of alpha diversity index were carried out using Wilcox test in R (Version 3.5.1). The unique and shared OTUs between two groups were analyzed by the Draw Veen Diagram online tool (http://bioinformatics.psb.ugent.be/webtools/Venn/). Beta diversity was visualized using unweighted pair-group method with arithmetic means (UPGMA) tree via QIIME. Principal coordinates analysis (PCoA) was calculated via Unweighted UniFrac distance. Analysis of ANOSIM and PERMANOVA, were carried out using R package Vegan (Anderson et al., 2006). PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) was employed to predict metabolic function of bacteria that colonized on MPs and sediments (Chai et al., 2020). Analysis of different OTUs were performed by a negative binomial generalized linear model according to a previous study (Shi et al., 2020). Manhattan plots were constructed by online tool (https://hiplot.com.cn). Two networks were constructed to analyze the pairwise correlations of OTUs (average abundance > 0.1%), using the "psych" R package to calculate the P-values (P < 0.05) and spearman's rank correlation (the Spearman's correlation coefficient > 0.8). Results were visualized by Gephi (Jiang et al., 2017a).

2.6 Statistical analysis

The abundance of MPs was expressed as mean values±standard deviation (SD). The comparison of MPs abundance in different areas were conducted by one-way ANOVA analysis and Duncan's multiple range test using SPSS software (Ver. 20.0; SPSS Inc., USA), and the difference of the communities and the functional composition between microorganism on MPs and sediments were analyzed by two tailed t-test. The differences were significant at P < 0.05 in all cases. In the network analysis, correlational relationships (the Spearman's correlation coefficient > 0.8 and P < 0.05) were established (Jiang et al., 2017b).

3 RESULT 3.1 Microplastics abundance

Microplastics were detected in seven sampling sites with the average abundance of 2 991±1 586 items per kg dry weight (items/kg dw). In the sediments of mangrove in Zhujiang River estuary, the concentration of MPs ranged from 1 057±86 items/kg dw to 6 103±881 items/kg dw. The lowest concentration of MPs was observed in S1 that located in Qi'ao Island Mangrove Nature Reserve. While the highest abundance was detected in S6 that located in Mangrove Seaside Ecological Park, followed by S7 (3 600±181 items/kg dw) in West Bay Coastal Park in Shenzhen (Fig. 1a). In addition, the average MPs abundance in mangrove of Shenzhen (mean 4 852 items/kg dw) was over two times higher than that in Guangzhou (mean 2 548 items/kg dw) and Zhuhai (mean 2 046 items/kg dw), with a significant difference among them (P < 0.05) (Fig. 1b). Therefore, MPs were widely distributed in the mangrove in Zhujiang River estuary, and the MPs pollution in Shenzhen was more serious than that in Guangzhou and Zhuhai.

3.2 Characteristics of microplastics

According to their appearance, MPs can be divided into four shapes: film, pellet, fiber, and fragment (Fig. 2a). Fiber is the most prevalent shape in all samples, accounting for 77.77% of the total particles, followed by film and fragment, the proportion of which was 14.17% and 7.81%, respectively (Fig. 2b). Pellets were barely observed in this study, only accounting for 0.24% of the total. Regarding particle size, size less than 0.5 mm was the most prevalent in nearly all samples, except S1, in which size range of 0.5–1 mm was the most common (Fig. 2c). Overall, 48.13% of the MPs were less than 0.5 mm. A high proportion of MPs of 0.5–1 mm and 1–2 mm was also observed here, accounting for 30.49% and 16.48%, respectively. As the length increased, the abundance of MPs decreased. Only a small amount of MPs in ranges of 2–3 mm (3.54%), 3–4 mm (1.08%), and 4–5 mm (0.27%) was detected in all samples. The color of MPs was also recorded in this study (Fig. 2d). Transparent and grey were the most common color, the proportion of them were 60.29% and 13.31% respectively. White and blue items were also prevalent here, constituting 7.43% and 4.89% of the total. To further investigate the particles, their polymer type and surface morphology were also characterized here (Fig. 2e). Results indicate that MPs were mainly composed of polyethylene (PE, 25.35%), followed by rayon (21.13%), acrylic (19.72%), polypropylene (15.49%), and cotton (15.49%). A few particles were identified as nylon. Besides, the surface morphology of several typical MPs from the mangrove were investigated by SEM (Fig. 2f). Complicated weathered surface of the selected MPs were observed, exhibited rough cracks and scratches. These surfaces were full of flakes, pits, and grooves, with a large amount of bacterial microorganisms attached to them.

3.3 Taxonomic classification and bacterial diversity

The total operational taxonomic units (OTUs) were obtained by clustering the high-quality sequences using a genetic distance of 97%, with a range from 2 721 to 5 347 and a mean of 4 099 OTUs (Supplementary Table S2). The rarefaction curve approached the plateau in each sample, which indicates a near-complete sampling of the bacterial microorganisms (Supplementary Fig.S1). The Venn diagram revealed that the co-shared OTUs in two groups were 4 752, and the independent OTUs in mangrove and MPs were 6 049 and 3 138, accounting for 56.00% and 39.77% of the total, respectively (Supplementary Fig.S2a). To investigate the community complexity of samples, five alpha diversity indices of bacterial communities were calculated, including observed-species, Simpson, Shannon, Chao1, and ACE index (Supplementary Table S3). The observed-species, Chao1, and ACE index of microbiota in sediments were significantly higher than that on microplastics. The Shannon diversity index was also higher in sediments but without significant difference. The higher values of these indices indicated that richness and diversity in sediments group were relatively higher. To further demonstrate the patterns of separation of microbiota, a principal coordinate analysis (PCoA) was conducted and the results show strong clustering of microorganisms according to different groups in the plot (Supplementary Fig.S3). Consistent with the PCoA results, UPGMA clustering also exhibited separation between two groups, indicating the remarkable difference in their bacterial communities (Supplementary Fig.S4). Accordingly, ANOSIM analysis also revealed the significant difference between two groups (R=1, P=0.003).

3.4 Bacterial community composition

The relative abundance of microbiota on phylum level was also investigated. In the mangrove sediments, the proportion of Proteobacteria (27.35%) is larger than the proportion of Desulfobacterota (15.77%), and Cyanobacteria (7.25%) (Fig. 3a). In the MPs group, Proteobacteria was more abundant, accounting for 53.77% of all phylotypes. Unlike microbiota in sediments, the dominant phyla on MPs included Bacteroidetes, Cyanobacteria, and Actinobacteria, accounting for 10.07%, 7.33%, and 7.05%, respectively. The most dominant phylum across most samples was Proteobacteria, except for samples S3 and S4 (Fig. 3b). Additionally, there was significant difference between the abundance of five dominant phyla (t-test, P < 0.01). The abundance of Proteobacteria, Bacteroidetes, and Actinobacteria on MPs were significantly higher than that in mangrove sediments, whereas Desulfobacterota and Acidobacteria were more abundant in the sediments (Fig. 3c).

3.5 Function of bacteria

PICRUSt was employed to predict the function of bacteria in mangrove and MPs by using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results show that bacterial metagenome was mainly associated with "Metabolism", "Genetic information processing", "Environmental information processing", and "Cellular processes" (Supplementary Table S4). In KEGG level 1, 50.76% of the KEGG orthologs (KOs) on MPs and 48.54% of the KOs in sediments were associated with "Metabolism", which mainly consisted of "Amino acid metabolism", "Carbohydrate metabolism", "Energy metabolism", and "Metabolism of cofactors and vitamins" in KEGG level 2. Genetic information processing (over 15%) was also dominant in the predicted function, including genetic information processing and translation. The Venn diagram show that the independent functional categories accounted for a small proportion of the total predicted microbial functions (Supplementary Fig.S2b). In KEGG level 2, significant difference was observed in 23 KOs between two groups (Fig. 4). Within "Human Disease", abundance of "Neurodegenerative disease" and "Cancer" in MPs group was significant higher. Within "Metabolism", the largest difference was found in the level 2 term "Xenobiotics biodegradation and metabolism" in two groups (45.11% higher in MPs group). These bacteria were mainly associated with "Aminobenzoate degradation", "Benzoate degradation" and "Caprolactam degradation", in KEGG level 3, the abundance of them on MPs was nearly two times of that in sediments. Besides, PCA plot also revealed strong clustering of bacterial function according to different groups (Supplementary Fig.S3b), indicating the remarkable difference in bacterial function between mangrove sediments and MPs.

3.6 Differences between bacteria on MPs and mangrove sediments

To determine the different OTUs between two groups, we created a negative binomial generalized linear model to compare the enriched (more abundant) or depleted (less abundant) OTUs on MPs, taking the OTUs from mangrove sediment as a control (Fig. 5a). There were 652 OTUs enriched and 1 445 OTUs depleted on MPs, indicating that MPs might provide distinct special spaces for microbiota in the mangrove. Furthermore, we constructed a Manhattan plot to illustrate the bacterial differences by arranging OTUs based on their taxonomy at phylum level (Fig. 5b). Microplastics significantly enriched most of Proteobacteria, Bacteroidetes, Actinobacteria, and depleted most of the Desulfobacterota, Verrucomicrobiota, Chloroflexi, and Firmicutes. To better understand the difference of microbiota colonized on MPs, two bacterial co-occurrence networks were constructed to reveal the potential interactions of microbiota and the keystone species in each group. The network of communities on MPs differed greatly from that of mangrove sediment (Fig. 6). Topological parameters also demonstrated the different complexity of two networks, including nodes, edges, and average degree (Table 1). 193 nodes and 1 517 edges were observed in bacteria on MPs, which are much higher than that in mangrove sediment (119 nodes and 594 edges). Besides, network of sediments exhibited a lower average degree and higher modularity than that of MPs. Sphaerochaeta and Geothermobacter were identified as keystone species in the sediment, whereas Devosia and Limibaculum were keystone species on MPs (Supplementary Table S5).

4 DISCUSSION

As a buffer zone between marine ecosystem and terrestrial ecosystem, mangrove is considered as a potential sink for MPs originated from both ocean and land-based anthropogenic activities. According to our results, the concentration of MPs in ZRE mangroves was higher than that of mangroves in other regions (Supplementary Table S6). The abundance of MPs in our study was almost ten times of that in mangroves located in the Muara Angke Wildlife Reserve of Indonesia (28.09±10.28 items/kg dw), the Persian Gulf of Iran (19.5–34.5 items/kg dw), and coast of Singapore (36.8±23.6 items/kg dw) (Nor and Obbard, 2014; Naji et al., 2019; Cordova et al., 2021). The concentration of MPs in mangrove of ZRE is also much higher than that in mangrove of semi-enclosed Maowei Sea and south-eastern coastal zones in China, Java Sea in Indonesia, as well as Ciénaga Grande de Santa Marta in Colombia (Garcés-Ordóñez et al., 2019; Li et al., 2019; Yona et al., 2019; Zhou et al., 2020). A study conducted in Qinzhou Bay showed an average abundance of 2 174.5 items/kg dw, which is slightly lower than that in this study (Li et al., 2018). The high concentration of MPs in mangroves of ZRE may result from the extremely abundant MPs in the upstream of the Zhujiang River, as reported previously (Yan et al., 2019). Furthermore, large amount of MPs might be released to the ZRE because of the repaid economic development and large population in this region, which was home to estimated 60 million people (Li et al., 2020). Earlier MPs monitoring studies reported a much lower concentration in sediments from ZRE (851±177 items/kg dw) sampled in 2015 and Futian mangroves of Shenzhen city (2 249±747 items/kg dw) sampled in 2017 (Li et al., 2020; Zuo et al., 2020), compared to our results, indicating that MPs pollution has become more serious in the coastal environment of Guangdong Province in recent years. Our results also reveal that the abundance of MPs was highest in mangroves of Shenzhen, followed by Guangzhou and Zhuhai. This might be caused by the reason that mangroves of Shenzhen and Guangzhou are located in the upstream of the ZRE with a lower water exchange capacity. In addition, MPs contamination was lower where human activities was less (Nor and Obbard, 2014). The sampling sites in Shenzhen were more closed to the center, and distance from populated centers have also been proved to be positively correlated with the concentration of MPs in mangroves (Garcés-Ordóñez et al., 2019).

Like most previous studies, fibers are the most common type identified in the mangrove sediment and pellets are barely found (Garcés-Ordóñez et al., 2019; Naji et al., 2019; Li et al., 2020). Results indicate that MPs in mangroves of ZRE might mostly originate from secondary sources, including fibers derived from fishing activities and synthetic textiles, as well as fragments or films broken down from large plastic particles. The properties of sediments also play vital roles in the characteristics of MPs in the mangroves. Fibers and fragments are proved to be more abundant in muddy sediments inside mangrove areas than sand sediments (Cordova et al., 2021). The smaller size of MPs accounted for a higher proportion in mangroves of ZRE, because small particles are more difficult to remove by water flow and then accumulate in the environment (Yan et al., 2019), which promote the potential risk to the organisms in mangroves by easily mistaking these small particles as food (Lehtiniemi et al., 2018). In terms of color, transparent is also reported frequently in mangroves sediments in previous studies (Li et al., 2019; Yona et al., 2019). The high proportion of transparent MPs in mangroves might result from bleaching out colourings during the degradation of lager plastics. As for the composition, PE was the most dominant polymer type in our study. Similar results were obtained in sediments of mangrove in the northern coast of the Persian Gulf and semi-enclosed Maowei Sea of China (Li et al., 2019; Naji et al., 2019). The composition might be one of the factors influencing the bacterial communities colonized on MPs, because their chemical compounds might act as a nutritional sources for certain species, thus resulting in selection of specific species (De Tender et al., 2015; Chai et al., 2020). In mangrove environment, MPs are possibly more susceptible to light and weathering than those on the sea floor, resulting in loss of physical integrity and increase of roughness, making them more likely to be colonized by various microorganisms (Reisser et al., 2014).

When compared the microbiota colonized on MPs with that in mangrove sediments, over 60% of OTUs on MPs were co-shared OTUs, indicated that bacteria colonized on MPs predominantly originated from the sediments. Understandably, the dominant phyla in these two groups were similar, both including Proteobacteria and Cyanobacteria. The predominance of these phyla is also observed in many studies about microbiota of coastal water and sediments worldwide (He et al., 2017; Sachithanandam et al., 2020). Since MPs are able to drift with ocean currents for long-distances migration, the originally colonized bacteria might change during their transfer (De Tender et al., 2015). The significantly higher diversity of sediment microbiota and strong clustering of microorganisms from two groups both indicated their remarkable difference in bacterial communities, which can be directly demonstrated by higher abundance of several specific taxa such as Proteobacteria, Bacteroidetes, and Actinobacteria in our study. MPs have been proved to harbor distinct bacteria compared with ambient environment (McCormick et al., 2014). The community of MPs biofilm and mangrove soil microorganism varies as the season changes (Xie et al., 2021). MPs from mulching film can enrich a wide range of phyla compared with the farmland soil, such as Actinobacteria, Bacteroidetes, and Proteobacteria, consistent with our results (Zhang et al., 2019). The phyla Actinobacteria are widely distributed in the environment, some of which have the ability to degrade polyethylene by synthesis of hydrolytic enzymes (Wei et al., 2014; Muhonja et al., 2018). While many species of Bacteroidetes can biodegrade various organic polymer compounds, such as cellulose (Bauer et al., 2006; Naas et al., 2014). Thus, it is reasonable to observe special microbiota related with plastic decomposition that dominated on MPs. Given that the MPs had unique OTUs and distinct bacterial communities, MPs themselves could form a new ecological niche in mangrove environment and thus influence the bacteria diversity in mangrove ecosystem.

Distinct bacterial communities adhered on MPs might exhibit different functions compared with those in mangrove sediments. Though high proportion of co-shared bacterial functions were observed in Venn diagram, a remarkable separation and different functional diversity indicated the functional distinction between two groups (Yan et al., 2021). "Metabolism" is the most abundant KOs both on MPs and mangrove sediment. Likewise, the bacteria attached to MPs from intertidal locations of the Changjiang (Yangtze) River estuary were mainly related to metabolic pathways (Jiang et al., 2018). Except for metabolism, genetic information processing and environmental information processing were also dominant components in our study, which was consistent with the bacterial functions on MPs in typical urban water environment (Wang et al., 2020). Here, most KOs associated with metabolism were increased in MPs group, especially "Xenobiotics Biodegradation and Metabolism", as reported previously (Jiang et al., 2018; Chai et al., 2020). Of note is the improved capacity of microbial community for benzoate degradation and caprolactam degradation on MPs. Benzoate usually acts as plasticizer in plastic production to improve the performance of synthetic materials (Chai et al., 2020). Caprolactam is a monomer used for the synthesis of nylon-6, one of the commonly used plastics in food packing (Jang et al., 2019). The enrichment of plastic-associated communities on MPs might be important during the further degradation of these particles into smaller MPs (Yuan et al., 2020; Niu et al., 2021), which were easier to be mistaken by organisms living in mangroves. Besides, increase was also observed in metagenomics potential of bacteria on MPs in terms of human disease, compared with the natural substrate in mangroves. MPs have ability to enrich potential pathogen from the surrounding environment (Kirstein et al., 2016; Wu et al., 2020). It has been reported that human pathogenic bacteria, Pseudomonas genus, was detected on the MPs and significantly different from water and sediment (Hu et al., 2021). The bacteria associated with human disease colonized on MPs can enter the food chain and possibly be transferred to different trophic levels, leading to unpredictable impacts on mangrove ecosystems and human health.

Enrichment and depletion of specific species adhered to MPs, compared with the mangrove sediments, were further investigated to reveal the difference of bacterial communities between two groups. Consistently, MPs enriched a wide range of bacterial phyla, including Proteobacteria, Bacteroidetes, and Actinobacteria. As detailed before, some species of Bacteroidetes and Actinobacteria have the ability to degrade plastic polymers such as PE and cellulose, resulting in continuous input of smaller MPs introduced into the mangrove environment (Bauer et al., 2006; Naas et al., 2014; Wei et al., 2014; Muhonja et al., 2018). Likewise, in urban river sediments, more plastic-degrading bacteria were colonized on MPs than sediments (Niu et al., 2021). Interestingly, depletion of Desulfobacterota, Verrucomicrobiota, Chloroflexi, and Firmicutes were also observed here. Some members of Desulfobacterota and Firmicutes can produce polyhydroxyalkanoates (PHAs) enzymes mediating PHA biodegradation, while PHA are microbially made polyesters commercialized as biodegradable plastics (Viljakainen and Hug, 2021). Accordingly, the composition of MPs in mangrove sediments were most PE and rayon, a semi-synthetic material composed of regenerated cellulose, but without PHAs. Thus, we speculated MPs composition may have effects on the "plasticsphere". Though it has been reported that the biofilms on MPs formed mainly through random process, selection may also be responsible for the prokaryotic assembly (Xu et al., 2019; Zhang et al., 2022). However, more specific reasons for their selective enrichment should be further studied.

The bacterial communities between two groups differed not only in abundance and diversity, but also in their complexity. Herein, we constructed two networks to demonstrate the potential biotic interactions among microbiota on MPs or mangrove sediments. Unlike in the sediments and MPs from farmland (Zhang et al., 2019), the keystone species on MPs and mangrove sediment were different. Members of Sphaerochaeta and Geothermobacter genus were inferred to be keystone species in mangrove sediment, whereas Devosia and Limibaculum were keystone species on MPs. These keystone species were barely reported on MPs or natural substrate in previous studies (Jiang et al., 2018; Wang et al., 2021). Different keystone species may be resulted from different environmental conditions or stress on microorganisms attached to MPs and sediments, since bacteria shift violently in different environments (Huang et al., 2019a). Topological properties of co-occurring bacterial networks could serve as indicators for the size and complexity of the bacterial network, such as nodes, edges, average degree and modularity (Berry and Widder, 2014; Shi et al., 2020). A greater number of nodes and edges, and a lower average degree and higher modularity in MPs network all indicated that network of bacteria colonized on MPs was bigger and more complex than that of mangrove sediment, despite MPs bacteria had a lower diversity. Therefore, the bacterial communities on MPs could form closer connections than the surrounding natural substrate. Consistent with previous reports, a complex correlation network was observed on bacteria of MPs in the intertidal zone of the Changjiang River estuary (Jiang et al., 2018). Bacterial network of MPs from cotton fields was also larger and more complex than that of plant litter and microplastics (Zhang et al., 2019). These results may be caused by two reasons. First, compared with the mangrove sediment, the weathered surfaces of MPs with increased roughness could provide fairly suitable habitat for various microorganism, supporting more complex interactions of bacteria colonized on their surfaces (Reisser et al., 2014). Secondly, the formation of bacterial network is influenced by various factors, especially the environmental conditions such as the availability of food. During their long-term degradation, MPs were not only cleaved into smaller molecules, but also released plasticizers, flame retardants and fillers such as calcium carbonate and talc on their surface, providing extensive carbon sources for bacteria (Arias-Andres et al., 2018; Chai et al., 2020). Thus, rough surfaces and abundant food sources might be responsible for the high complexity of bacteria colonized on MPs. The mechanism of how microplastics enrich plastic-degrading bacteria and exhibit greater complexity needs further investigation.

5 CONCLUSION

This study investigated the MPs pollution in mangrove of ZRE and fi rstly reported the diff erence of bacterial communities, functions, and complexity compared MPs with ambient sediment in mangrove of ZRE. The results indicate that MPs widely distributed in mangrove sediment of ZRE, mostly small-size and transparent particles mainly in form of fi bers and composed of PE. The bacterial diversity, function, and complexity were signifi cantly diff erent between MPs and mangrove sediments, suggesting that MPs could form a new ecological niche in mangrove environment. Some bacteria associated with plastic-degrading and human diseases that enriched on MPs may promote MPs degradation and spread of diseases, posing potential risk to mangrove ecosystems and human health. The mechanism of how microplastics enrich distinct bacteria and act as vectors for pathogens needs further investigation. The results of this study suggeste that MPs in mangrove sediment can act as a distinct habitat for specific bacterial species and potentially pose effects on mangrove ecosystems.

6 DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Electronic supplementary material

Supplementary material (Supplementary Tables S1–S6 and Figs.S1–S4) is available in the online version of this article at https://doi.org/10.1007/s00343-021-1300-x.