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. 2025 Feb 18;10(8):7597–7608. doi: 10.1021/acsomega.4c00645

Mixture Effects of Polystyrene Microplastics on the Gut Microbiota in C57BL/6 Mice

Bei Gao 1,2, Xiaochun Shi 3, Meng Zhao 3, Fangfang Ren 4, Weichen Xu 5, Nan Gao 4, Jinjun Shan 5, Weishou Shen 3,6,*
PMCID: PMC11886427  PMID: 40060808

Abstract

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Microplastics are plastic particles with sizes of less than 5 mm. The ubiquity of microplastics in the environment has raised serious public health concerns. Microplastics could disturb the composition of the gut microbiota due to both chemical composition and physical interactions, which might further influence the metabolism and immune function of the host. However, most of the exposure studies chose microplastics of specific sizes. In the natural environment, living organisms are exposed to a mixture of microplastics of various sizes. In this study, male C57BL/6 mice were exposed to polystyrene (PS) microplastics with different sizes, including microplastics with diameters of 0.05–0.1 μm (PS0.1 group, 100 ppb), 9–10 μm (PS10 group, 100 ppb), and microplastic mixtures of both 0.05–0.1 and 9–10 μm (PSMix group) at a total concentration of 100 ppb (50 ppb for each size). Mixture effects of microplastics were investigated on the composition of bacteria and fungi as well as functional metagenome and microbial genes encoding antibiotic resistance and virulence factors. We found that some bacteria, fungi, and microbial metabolic pathways were only altered in the PSMix group, not in the PS0.1 or PS10 group, suggesting the toxic effects of the microplastic mixture on the composition of fungi and bacteria, and the functional metagenome is different from the effects of microplastics at specific sizes. Meanwhile, altered genes encoding antibiotic resistance and virulence factors in the PSMix group were shared with the PS0.1 and PS10 groups, possibly due to functional redundancy. Our findings help improve the understanding of the toxic effects of the microplastic mixture on the gut microbiome.

Introduction

Microplastics are plastic particles with a diameter of less than 5 mm.1 Microplastics are produced in the terrestrial environment and released from waste and consumer products.2 Due to their small sizes, microplastics are difficult to efficiently remove from water bodies, air, and sediments with available techniques.3 Microplastics are widespread contaminants found not only in marine ecosystems but also in soil, atmosphere, and nearly all environmental compartments, including the indoor environment.4 The concentration of microplastics in farmlands and rivers varies up to eight orders of magnitude, from 10–4 to 104 n/L.5 Microplastics have been considered an emerging source of air pollution.6 High concentrations of airborne microplastics have been detected.7 In addition, microplastics have been detected in commercial seafood,8 table salts,9 and drinking water.10,11 The ubiquity of microplastics in the environment leads to inevitable human exposure, which has raised public health concerns about their implications for human health.

Human exposure to microplastics may occur through ingestion, dermal contact, and inhalation. Based on the consumption of foodstuff, it is estimated that the microplastic annual intake is 39,000–52,000 particles per person, and these estimates increase up to 74,000–121,000 when inhalation is taken into consideration.12 Microplastics have been detected in human placenta,13 human stool,14 human lung tissue,15 cirrhotic liver tissue,16 human thrombi,17 and the blood of healthy volunteers.18 The mean of the sum quantifiable concentration was 1.6 μg/mL for plastic particles in human blood, among which polymers of styrene including polystyrene (PS) were widely encountered microplastics.18 The range of PS microplastics in human blood was 0–4.8 μg/mL.18 The presence of nanoplastics in human peripheral blood has been reported in a cohort of 196 individuals.19 Microplastics are associated with inflammatory lesions and oxidative stress,20 as well as human diseases such as cardiovascular disease21 and inflammatory bowel disease.22

Gut microbiota is a community of microorganisms living along the gastrointestinal tract, which plays an essential role in the health and diseases of the host, including the digestion of dietary nutrients and the transformation and synthesis of lipids.23 The negative effects of microplastics on the gut microbiota have recently attracted the attention of the scientific community. In the natural environment, living organisms are exposed to a mixture of microplastics of various sizes. However, most laboratory exposure studies on the gut microbiota choose microplastics of specific sizes.24−31 Dysbiosis of the gut microbiota was observed in both 0.5 and 50 μm PS microplastic exposure groups when Institute of Cancer Research (ICR) mice were exposed to 1000 μg/L PS via drinking water for 5 weeks.27 Six-week exposure of 5 μm PS microplastics via drinking water at concentrations of 100 and 1000 μg/L changed the gut microbiota composition in ICR mice.28 5 μm PS microplastic exposure through drinking water at the concentrations of 100 and 1000 μg/L for 90 days altered the composition of the gut microbiota, the fecal transplantation of which induced reproductive dysfunction in the recipient mice.29 Oral gavage of 5 μm PS microplastics at the concentration of 0.1 mg/day for 6 weeks induced alterations in the composition and diversity of the gut microbiota.30 A 5-week 10–150 μm polyethylene microplastic exposure through diet administration at a concentration of 200 μg/g disturbed the distribution of gut microbiota in C57BL/6 mice.31

Our previous study demonstrated that PS microplastics’ impact on the gut microbiota is size dependent.32 However, the mixture effect of microplastics at different sizes is still not well studied. In this study, we investigated the mixture effect of microplastics at different sizes (0.05–0.1 μm microsphere and 9–10 μm microsphere) on the gut fungi, bacteria, and the functional metagenome. Responses of microbial genes encoding antibiotic resistance and virulence factors were also examined. The findings from this study are helpful to improve our understanding of mixture effects of the microplastics.

Materials and Methods

Animals and Exposure

Five-week-old specific pathogen-free C57BL/6 male mice (Qinglongshan Laboratory, Nanjing, China) were housed in the animal facility, where they could consume tap water ad libitum (n = 36). The study design is shown in Figure 1. The mice were randomly assigned to different cages once a week for 4 weeks. When the mice were 9 weeks old, the exposure experiment started. At the beginning of the experiment, mice were randomly assigned to control (n = 12), PS0.1 (n = 8), PS10 (n = 8), or PSMix group (n = 8), with two to three mice cohoused in one cage. The diameters of PS microplastics were 0.05–0.1 and 9–10 μm in the PS0.1 and PS10 groups, respectively. PS microplastics (PS, 2.5%, w/v, Baseline Chromtech Research Center, Tianjin) were administered to mice in drinking water at a concentration of 100 ppb in each exposure group for 12 weeks. The drinking water in the PSMix group contained 50 ppb of 0.05–0.1 μm PS microplastics and 50 ppb of 9–10 μm PS microplastics. PS microplastic stock solution went through a series of dilutions with deionized water and was finally added to the drinking water of mice. To fully suspend the microplastics, they were sonicated for 30 min before use. The mice’s water consumption and body weight were monitored weekly throughout the exposure period. Fecal samples were collected at the end of the exposure period. Control mice received drinking water without the addition of PS. The animal facility was maintained at 22 °C and 40–70% humidity, with a light–dark cycle of 12:12 h. The protocol was approved by the Institutional Animal Care and Use Committee (ID:202139), and the mice were treated humanely.

Figure 1.

Figure 1

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Study design of the microplastic exposure experiment.

Internal Transcribed Spacer (ITS) and 16S rRNA Sequencing

Total DNA was extracted from fecal samples using HiPure Soil DNA Mini Kit (Magen, Guangdong, China) according to the manufacturer’s instructions. For ITS sequencing, the ITS1 region was amplified using the following primers: forward 5′-CTTGGTCATTTAGAGGAAGTAA-3′; reverse 5′-GCTGCGTTCTTCATCGATGC-3′.33 For 16S rRNA sequencing, V3–V4 regions of the 16S rRNA gene were amplified using the following primers: 341F 5′-CCTAYGGGRBGCASCAG-3′; 806R 5′-GGACTACNNGGGTATCTAAT-3′.34 Library preparation and sequencing were performed by Genedenovo (Guangdong, China).

ITS and 16S rRNA Sequencing Data Analysis

QIIME2 (version 2022.8) was used to analyze the ITS and 16S rRNA sequencing data.35 Raw sequencing reads were denoised via DADA2 and then clustered into operational taxonomic units (OTUs). For ITS sequencing analysis, OTU representative sequences were aligned to the UNITE database (version 2021) with the scikit-learn Naive Bayes-based machine-learning classifier at 99% sequence identity.36 For 16S rRNA sequencing analysis, the SILVA database (version 138) was used with the scikit-learn Naive Bayes-based machine-learning classifier at 99% sequence identity.37 The Phyloseq package in R was used for the diversity analysis.38

Metagenomics Sequencing

Total DNA was extracted from fecal samples, as described above. Metagenomics sequencing was performed at Genedenovo with a NovaSeq 6000 platform, which generated 150 bp paired-end sequencing reads. Trimmomatic version 0.38 was used for quality control with the default setting. Filtered sequencing data was processed with HUMAnN3.639 with the MetaCyc metabolic pathway database. Antibiotic Resistance Factors Database (version 2017) and Virulence Factors Database version 0.9.3 were used for the profiling of antibiotic resistance genes and virulence factors, respectively, using ShortBRED40 with default settings. The output was expressed in the unit of reads per kilobase of reference sequences per million sample reads (RPKMs).

Statistical Analysis

MaAsLin2 was used to detect the significant bacteria, fungi, microbial pathways, and genes encoding antibiotic resistance and virulence factors with both p-values and q-values calculated.41 The correlation network between fungal genera was performed using Gephi software.42 The co-occurrence network between bacteria and fungi was performed using the igraph v.1.3.2 package in R.43 The Spearman correlation was calculated for the network analysis. The absolute value of the correlation coefficient was represented by the edge weights. The correlation cutoff was set at p-values less than 0.05 and correlation coefficients greater than 0.6. The significance level was set at p-values less than 0.05 unless specifically indicated otherwise.

Results

PS Exposure Altered the Gut Fungal Composition

There was no statistical difference in water consumption (Supporting Information Figure S1A). The body weight gain of mice was not significantly altered during the exposure period (Supporting Information Figure S1B). A total of 31, 23, and 33 fungal genera were significantly altered in the PS0.1, PS10, and PSMix groups, respectively (Figure 2A, Supporting Information Table S1, q-value <0.05). Among 33 altered fungal genera in the PSMix group, 14 fungal genera were only found in the PSMix group, not in the PS0.1 or PS10 group. Lower Shannon and Simpson indexes were observed in the PS10 group compared with the control group, while not in the PS0.1 or PSMix group (Figure 2B). Beta diversity was not significantly altered in the three groups (Supporting Information Figure S2).

Figure 2.

Figure 2

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Response of intestinal fungi to PS microplastics. (A) Significantly altered intestinal fungal composition at the genus level (q-value <0.05). The blue color indicates that different group comparisons shared the changes; the black color indicates that the changes were only found in one exposure group compared with the control group. (B) α-Diversity analysis of intestinal fungi (p-values were indicated in the figure). The line inside the box represents the median. The interquartile range represents the difference between the third quartile (the 75th percentile) and the first quartile (the 25th percentile).

PS Exposure Altered the Gut Bacterial Composition

At the phylum level, the relative abundance of Campylobacterota was only increased in the PSMix group, not in the PS0.1 or PS10 group (Figure 3A, Supporting Information Table S2, q-value <0.05). Some phyla altered in the PSMix group were shared with other groups. For instance, Proteobacteria and Cyanobacteria were significantly reduced in the PS0.1, PS10, and PSMix groups compared with the control group. Synergistota was increased in both PS10 and PSMix groups (Figure 3A). Meanwhile, Actinobacteriota was only increased in PS0.1, not in the PSMix group (Figure 3A). At the genus level, a total of 10, 8, and 11 bacterial genera were significantly altered in the PS0.1, PS10, and PSMix groups, respectively (Figure 3B, Supporting Information Table S3, q-value <0.05). Among 11 bacterial genera disturbed in the PSMix group, five were only altered in the PSMix group, not in the PS0.1 or PS10 group. A lower Simpson index was observed in the PS0.1 group compared with the control group, while not in the PS10 or PSMix group (Supporting Information Figure S3A). Beta diversity was not significantly altered (Supporting Information Figure S3B,C).

Figure 3.

Figure 3

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Response of intestinal bacteria to PS microplastics. (A) Significantly altered intestinal bacteria at the phylum level (q-value <0.05). The line inside the box represents the median. The interquartile range represents the difference between the third quartile (the 75th percentile) and the first quartile (the 25th percentile). (B) Significantly altered intestinal bacteria at the genus level (q-value <0.05). The blue color indicates different group comparisons shared the changes; the black color indicates that the changes were only found in one exposure group compared with the control group.

PS Exposure Altered the Correlation between Gut Bacteria and Fungi

In the control group, we identified correlations of varying strengths (Figure 4A). Positive correlations were found between Alistipes and Humicola, Ruminococcus and Trichoderma, Lactobacillus and Alternaria, Blautia and Fusarium, Clostridia vadinBB60 group and Cladosporium. Negative correlations were found between Paludicold and Botryotrichum, Bacteroidetes and Fusarium, Hydrogenoanaerobacterium and Zopfiella, Eubacterium oxidoreducens group and Leohumicola, Christensenellaceae and Plectosphaerella (Figure 4A). In the PS10 group, positive correlations were found between the Eubacterium oxidoreducens group and Holtermanniella, Bacteroidetes vadinHA17 and Mortierella, Bacteroidetes vadinHA17 and Saitozyma (Figure 4B). Bacteria and fungi interaction was not found in PS0.1 or PSMix groups, suggesting that the correlation between bacteria and fungi was disrupted (Figure 4C,D).

Figure 4.

Figure 4

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Co-occurrence network of intestinal bacteria and fungi in mice: (A) control group; (B) P10 group; (C) PS0.1 group; (D) PSMix group. The size of the node was based on the relative abundance of bacteria or fungi. The length of the edge was based on the correlation coefficient. The blue node represents bacteria; the orange node represents fungi. The red edge represents a positive correlation; the blue edge represents a negative correlation.

PS Exposure Altered the Metabolic Pathways of the Gut Microbiota

A total of 26, 19, and 14 metabolic pathways were significantly altered in the PS0.1, PS10, and PSMix groups, respectively (Figure 5A–C, Supporting Information Table S4, q-value <0.05). Six metabolic pathways were altered exclusively in the PSMix group, including DAPLYSINESYN-PWY: l-lysine biosynthesis I, PWY-5676: acetyl-CoA fermentation to butanoate II, FUCCAT-PWY: fucose degradation, PWY-621: sucrose degradation III (sucrose invertase), PWY0-1297: superpathway of purine deoxyribonucleosides degradation, and GLUCARDEG-PWY: d-glucarate degradation I (Figure 5C, D). In addition, some pathways altered in the PSMix group were shared with other groups. For instance, PWY 622: starch biosynthesis and GlUCOSE1PMETAB-PWY: glucose and glucose-1-phosphate degradation were altered in three groups (Figure 4D).

Figure 5.

Figure 5

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Response of microbial pathways to PS microplastics. (A) Significantly altered microbial pathways in the PS0.1 group (q-value <0.05). (B) Significantly altered microbial pathways in the PS10 group (q-value <0.05). (C) Significantly altered microbial pathways in the PSMix group (q-value <0.05). The blue color indicates that different group comparisons shared the changes; the black color indicates that the changes were only found in one exposure group compared with the control group. (D) Venn diagram of significantly altered microbial pathways in three groups (q-value <0.05). The full name of the metabolic pathways is provided in Supporting Information Table S4.

PS Exposure Altered Antibiotic Resistance Genes and Virulence Factors

Significantly altered genes encoding antibiotic resistance in the PS0.1, PS10, and PSMix groups are shown in Figure 6A–C (Supporting Information Table S5, p-value <0.05). Two significant genes were shared among all three groups, including cat and Enterobacter cloacae acrA (Figure 6D). Three significant genes were shared between the PSMix group and the PS0.1 group; meanwhile, two significant genes were shared between the PSMix group and the PS10 group (Figure 6D). One and four resistance genes were exclusively altered in the PS0.1 and PS10 groups, respectively (Figure 6D). Significantly altered genes encoding virulence factors are shown in Figure 7A–C (Supporting Information Table S6, p-value <0.05). A total of 13 significant genes were shared among all three groups (Figure 7D). In addition, 12 significant genes were altered in both the PS0.1 group and the PS10 group (Figure 7D). Five and three significant genes were exclusively altered in the PS0.1 and PS10 groups, respectively (Figure 7D).

Figure 6.

Figure 6

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Response of antibiotic resistance genes to PS microplastics. (A) Significantly altered antibiotic resistance genes in the PS0.1 group (p-value <0.05). (B) Significantly altered antibiotic resistance genes in the PS10 group (p-value <0.05). (C) Significantly altered antibiotic resistance genes in the PSMix group (p-value <0.05). The blue color indicates that different group comparisons shared the changes; the black color indicates that the changes were only found in one exposure group compared with the control group. The line inside the box represents the median. The interquartile range represents the difference between the third quartile (the 75th percentile) and the first quartile (the 25th percentile). (D) Venn diagram of significantly altered antibiotic resistance genes in three groups (p-value <0.05).

Figure 7.

Figure 7

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Response of genes encoding virulence factors to PS microplastics. (A) Significantly altered genes encoding virulence factors in PS0.1 group (p-value <0.05). (B) Significantly altered genes encoding virulence factors in the PS10 group (p-value <0.05). (C) Significantly altered genes encoding virulence factors in the PSMix group (p-value <0.05). The blue color indicates that different group comparisons shared the changes; the black color indicates that the changes were only found in one exposure group compared with the control group. (D) Venn diagram of significantly altered genes encoding virulence factors in three groups (p-value <0.05).

Discussion

The mixture effects of microplastic exposure on the gut microbiota were investigated using C57BL/6 mice in this study. Intestinal fungi play an important role in human health and disease. Dysregulation of fungi might disrupt the balance of the immune system, triggering the development of diseases.44 In the present study, some fungal genera (such as Alternaria, Sterigmatomyces, Bipolaris, Thermomyces, and Wickerhamomyces) were only increased in the PSMix group but not in the PS0.1 or PS10 group. Alternaria is known as a potential allergen.45 Host-specific toxins could be produced by certain Alternaria spp., which contribute to their virulence and pathogenicity.46 Certain Alternaria spp. could cause opportunistic human infections, including cutaneous and subcutaneous infections and oculomycosis.47 Enrichment of Alternaria was found in patients with gastric carcinogenesis.48 In addition, Alternaria has also been reported as one of the most prevalent fungi detected in patients with Alzheimer’s disease.49Sterigmatomyces is known as a human pathogen, which could cause liver abscess.50 Enrichment of Sterigmatomyces was also found in patients with ulcerative colitis.51 Bipolaris sp. could cause mycotic keratitis.52 The increase of Bipolaris was associated with low levels of prostate-specific antigens in patients with prostate cancer.53 Elevated triglyceride concentrations and hepatic lipid deposition were correlated with the increase of Thermomyces in mice.54 An increased abundance of Wickerhamomyces has been considered a health hazard for horses.55

Some fungal genera altered in the PSMix group were shared with the other groups. For instance, the relative abundance of Curvularia was increased in both the PSMix and PS0.1 groups. Curvularia is known as a rare human pathogen, which has been detected in severely immunocompromised pediatric patients.56 Various diseases were associated with Curvularia infection, such as keratitis57 and allergic bronchopulmonary aspergillosis.58 The relative abundance of Curvularia was higher in patients with nonalcoholic fatty liver disease compared with control subjects.59 Moreover, there were some fungal genera that were only altered in the PS0.1 group or PS10 group, instead of the PSMix group. For instance, the relative abundance of Nigrosporai was increased in the PS0.1 group, which was known as human pathogens.60Nigrospora was positively correlated with colonic pro-inflammatory cytokine expressions and Baron score in patients with ulcerative colitis.51 Meanwhile, the relative abundance of Schizophyllum was increased in the PS10 group compared with the control group. Schizophyllum sp. could cause various diseases, such as allergic bronchopulmonary mycosis, allergic fungal rhinosinusitis, and hypertrophic pachymeningitis.61Schizophyllum sp. was enriched in patients with Alzheimer’s disease.62

The effect of the microplastic mixture on the intestinal bacteria was similar to that of the intestinal fungi. At the phylum level, Campylobacterota was increased in the PSMix group, while not altered in either the PS0.1 or PS10 group. A higher abundance of Campylobacterota was found in patients with nodular lymphoid hyperplasia.63 Meanwhile, some altered bacterial phyla were shared among the three groups. For instance, the level of Proteobacteria was decreased in three groups compared with the control group. Decreased Proteobacteria was found in discus fish exposed to nanoplastics.64 In addition, the level of Actinobacteria was increased only in the PS0.1 group instead of the PSMix group. Increased Actinobacteria was also observed in mice exposed to an antibacterial agent triclosan.65

At the genus level, Faecalibacterium was significantly reduced in the PSMix group compared with the control group while not significantly altered in the PS0.1 or PS10 group. Faecalibacterium has been considered a next-generation probiotic with promising health applications, and low levels of Faecalibacterium were correlated with gastrointestinal diseases or disorders.66Parabacteroides and Ruminococcaceae were decreased in the PSMix group, compared with controls, while not in the PS0.1 or PS10 group. Parabacteroides is involved in the carbohydrate metabolism and production of short-chain fatty acids, which has a close relationship with the health status of the host.67Ruminococcaceae is also known as producer of short-chain fatty acids.68 Lower abundance of Ruminococcaceae was found in patients with cystic fibrosis.69 Decreased Ruminococcaceae was found in rats exposed to environmentally relevant levels of a flame retardant 2,2′,4,4′-tetrabromodiphenyl ether (PBDE-47).70

Some bacterial genera altered in the PSMix group were shared with other group. For instance, the relative abundance of Barnesiella was reduced in both PS10 and PSMix groups. Barnesiella was enriched in patients with autism spectrum disorder compared with control subjects.71Gastranaerophilales and Bacteroides were decreased in three groups. Decreased Gastranaerophilales were found in a mouse model of intestinal cancer.72Bacteroides is known as a short fatty acid producer.73Bacteroides were reduced in mice fed with a high-fat diet74 and in mice fed with a high-fat/high-cholesterol diet.75

There were some bacterial genera altered only in the PS0.1 group or PS10 group instead of in the PSMix group. For instance, Methylobacterium-methylorubrum and Blautia were decreased in the PS0.1 group compared with the control group. Reduction of Methylobacterium-methylorubrum was found in black-spotted frogs exposed to three per- and poly-fluoroalkyl substances.76Methylobacterium-methylorubrum was also reduced in silkworms after tolfenpyrad exposure.77Blautia widely occurs in the intestines and feces of mammals, which shows probiotic characteristics.78 Reduced Blautia was found in mice exposed to a plasticizer, di-isononyl phthalate.79 Dysregulation of gut microbiota might have adverse implications for the health of the host. Gut microbiota has been reported to participate in hepatic injuries induced by PS microplastics through the modulation of the gut–liver axis.80 Fecal transplantation of PS microplastic-disturbed gut microbiota triggered the testicular disorder in male mice.29

The relative abundance of some microbial genes encoding antibiotic resistance and virulence factors was altered in both the PSMix group and the individual exposure groups. For instance, the relative abundance of gene encoding Neisseria gonorrheae porin PIB was increased in the PS0.1 and PSMix groups. PIB plays an essential in the mediation of antibiotic resistance to tetracycline and penicillin.81 Meanwhile, some genes were altered only in the PS0.1 or PS10 group instead of the PSMix group. For instance, the relative abundance of the gene encoding LnuC was increased in the PS0.1 group. LnuC is a nucleotidyltransferase mediated by transposon, which confers resistance to lincomycin.82 Moreover, genes encoding Tet(32) and Tet(40) were increased in the PS10 group. Tet(32) confers a high level of resistance to tetracycline.83 Enrichment of Tet(32) was found in patients with chronic periodontitis compared with control subjects.84 Tet(40) is an efflux pump belonging to the major facilitator superfamily, which exports tetracycline from bacterial cells.85 Tet(40) was increased in mice exposed to microcystin-LR.86 Tet(40) has been suggested to serve as a marker for children with autism spectrum disorder.87 The relative abundance of the gene encoding aminoglycoside phosphotransferase was also increased in the PS10 group. Aminoglycoside antibiotics are an important class of drugs used in clinics. The presence of modifying enzymes such as aminoglycoside phosphotransferase enables aminoglycoside resistance. Aminoglycoside phosphotransferase modifies aminoglycoside antibiotics through the phosphorylation with NTPs as cofactors.88 Although altered genes encoding antibiotic resistance and virulence factors in the PSMix group were shared with PS0.1 and/or PS10 groups, the toxic effects of the microplastic mixture on the composition of fungi and bacteria and the functional metagenome are different from the effects of microplastics at specific sizes. Size-effects of microplastics have been reported in different studies, and smaller-sized particles with larger specific surface areas might be more toxic. For instance, smaller-size microplastics induced more severe liver damage in zebrafish fed with polyethylene microplastics.89 Smaller sizes of PS microplastics induced greater damage in the guts and gills of shrimp than larger particles.90 Small-sized PS microplastics enhanced the cardiac defect and disruption of vessel formation in larvae on the combined toxicity of benz[a]anthracene, the effect of which was different from medium-sized and large-sized PS microplastics.91 The degree of damage in the carp’s heart was negatively correlated with the particle size of PS nanoplastics.92 The retention time of microplastics in the gut of barnacle naupliar larvae significantly increased with decreasing size.93 The excretion of smaller microplastics slower than the larger ones in rats.94 The gut retention time of microplastics might be one possible mechanism of the size effect observed in this study, as more microbial pathways were affected in the PS0.1 exposure group than in the PS10 exposure group. In the natural environment, microplastics are colonized by a variety of microbes, including both bacteria and fungi.95 The disturbance of the gut microbial distribution by microplastics at specific sizes has been reported.27,31 However, the responses of gut bacteria and fungi to the microplastic mixture in the intestinal ecosystem were not clear. The size of PS0.1 was closer to the size of gut bacteria; meanwhile, the size of PS10 was closer to the size of gut fungi. Usually, the gut fungi interact with the gut bacteria to maintain the homeostasis of the ecosystem.96

This study has several limitations. First, the zeta potential of the microplastics was not measured. Second, the sedimentation of microplastics in the water over time was not monitored. Further studies are needed to understand the long-term effects of chronic microplastic exposure on the gut microbiome in the PSMix group as well as to reveal the impact of microplastics on the overall health of the host. Despite these limitations, the findings from this study improved our understanding of the toxic effects of the microplastic mixture at various sizes on the gut microbiota.

Acknowledgments

We acknowledge the High Performance Computing Center of Nanjing University of Information Science and Technology for their support of this work.

Data Availability Statement

The sequencing data is available at the EBI metagenomics repository (https://www.ebi.ac.uk/ena), under project number PRJEB74218.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.4c00645.

  • (Figure S1) Water consumption and body weight gain of mice; (Figure S2) beta diversity analysis of intestinal fungal genera; (Figure S3) diversity analysis of intestinal bacterial genera; (Table S1) statistical analysis of gut fungi at genus level; (Table S2) statistical analysis of gut bacteria at phylum level; (Table S3) statistical analysis of gut bacteria at genus level; (Table S4) statistical analysis of microbial metabolic pathways; (Table S5) statistical analysis of genes encoding antibiotic resistance; and (Table S6) statistical analysis of genes encoding virulence factors (PDF)

Author Contributions

Formal analysis, X.S.; investigation, F.R., J.S., W.X. and M.Z.; writing—original draft preparation, B.G.; writing—review and editing. N.G. and W.S. All authors have read and agreed to the published version of the manuscript.

This research was funded by the National Natural Science Foundation of China (grant no. 42107459), Science and Technology Innovation Project for Returned Overseas Individuals of Nanjing City (R2022LZ06), and startup funding of Nanjing University of Information Science and Technology.

The authors declare no competing financial interest.

Supplementary Material

ao4c00645_si_001.pdf (307.1KB, pdf)

References

  1. Arthur C.; Baker J. E.; Bamford H. A.. Proceedings of the International Research Workshop on the Occurrence, Effects, and Fate of Microplastic Marine Debris. Sept 9–11, 2008. NOAA Technical Memorandum NOS-OR&R-30; NOAA: 2009. [Google Scholar]
  2. Dissanayake P. D.; Kim S.; Sarkar B.; Oleszczuk P.; Sang M. K.; Haque M. N.; Ahn J. H.; Bank M. S.; Ok Y. S. Effects of Microplastics on the Terrestrial Environment: A Critical Review. Environ. Res. 2022, 209, 112734 10.1016/j.envres.2022.112734. [DOI] [PubMed] [Google Scholar]
  3. Tirkey A.; Upadhyay L. S. B. Microplastics: An Overview on Separation, Identification and Characterization of Microplastics. Mar. Pollut. Bull. 2021, 170, 112604 10.1016/j.marpolbul.2021.112604. [DOI] [PubMed] [Google Scholar]
  4. Salthammer T. Microplastics and Their Additives in the Indoor Environment. Angew. Chem., Int. Ed. Engl. 2022, 61 (32), e202205713 10.1002/anie.202205713. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Koutnik V. S.; Leonard J.; Alkidim S.; DePrima F. J.; Ravi S.; Hoek E. M. V.; Mohanty S. K. Distribution of Microplastics in Soil and Freshwater Environments: Global Analysis and Framework for Transport Modeling. Environ. Pollut. 2021, 274, 116552 10.1016/j.envpol.2021.116552. [DOI] [PubMed] [Google Scholar]
  6. Sridharan S.; Kumar M.; Singh L.; Bolan N. S.; Saha M. Microplastics as an Emerging Source of Particulate Air Pollution: A Critical Review. J. Hazard Mater. 2021, 418, 126245 10.1016/j.jhazmat.2021.126245. [DOI] [PubMed] [Google Scholar]
  7. Tran T. V.; Jalil A. A.; Nguyen T. M.; Nguyen T. T. T.; Nabgan W.; Nguyen D. T. C. A Review on the Occurrence, Analytical Methods, and Impact of Microplastics in the Environment. Environ. Toxicol Pharmacol 2023, 102, 104248 10.1016/j.etap.2023.104248. [DOI] [PubMed] [Google Scholar]
  8. Mercogliano R.; Avio C. G.; Regoli F.; Anastasio A.; Colavita G.; Santonicola S. Occurrence of Microplastics in Commercial Seafood under the Perspective of the Human Food Chain. A Review. J. Agric. Food Chem. 2020, 68 (19), 5296–5301. 10.1021/acs.jafc.0c01209. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Iñiguez M. E.; Conesa J. A.; Fullana A. Microplastics in Spanish Table Salt. Sci. Rep 2017, 7 (1), 8620. 10.1038/s41598-017-09128-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Kosuth M.; Mason S. A.; Wattenberg E. V. Anthropogenic Contamination of Tap Water, Beer, and Sea Salt. PLoS One 2018, 13 (4), e0194970 10.1371/journal.pone.0194970. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Oni B. A.; Sanni S. E. Occurrence of Microplastics in Borehole Drinking Water and Sediments in Lagos, Nigeria. Environ. Toxicol. Chem. 2022, 41 (7), 1721–1731. 10.1002/etc.5350. [DOI] [PubMed] [Google Scholar]
  12. Cox K. D.; Covernton G. A.; Davies H. L.; Dower J. F.; Juanes F.; Dudas S. E. Human Consumption of Microplastics. Environ. Sci. Technol. 2019, 53 (12), 7068–7074. 10.1021/acs.est.9b01517. [DOI] [PubMed] [Google Scholar]
  13. Ragusa A.; Svelato A.; Santacroce C.; Catalano P.; Notarstefano V.; Carnevali O.; Papa F.; Rongioletti M. C. A.; Baiocco F.; Draghi S.; D’Amore E.; Rinaldo D.; Matta M.; Giorgini E. Plasticenta: First Evidence of Microplastics in Human Placenta. Environ. Int. 2021, 146, 106274 10.1016/j.envint.2020.106274. [DOI] [PubMed] [Google Scholar]
  14. Schwabl P.; Köppel S.; Königshofer P.; Bucsics T.; Trauner M.; Reiberger T.; Liebmann B. Detection of Various Microplastics in Human Stool: A Prospective Case Series. Ann. Int. Med. 2019, 171 (7), 453–457. 10.7326/M19-0618. [DOI] [PubMed] [Google Scholar]
  15. Jenner L. C.; Rotchell J. M.; Bennett R. T.; Cowen M.; Tentzeris V.; Sadofsky L. R. Detection of Microplastics in Human Lung Tissue Using μFTIR Spectroscopy. Sci. Total Environ. 2022, 831, 154907 10.1016/j.scitotenv.2022.154907. [DOI] [PubMed] [Google Scholar]
  16. Horvatits T.; Tamminga M.; Liu B.; Sebode M.; Carambia A.; Fischer L.; Püschel K.; Huber S.; Fischer E. K. Microplastics Detected in Cirrhotic Liver Tissue. EBioMedicine 2022, 82, 104147 10.1016/j.ebiom.2022.104147. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Wu D.; Feng Y.; Wang R.; Jiang J.; Guan Q.; Yang X.; Wei H.; Xia Y.; Luo Y. Pigment Microparticles and Microplastics Found in Human Thrombi Based on Raman Spectral Evidence. J. Adv. Res. 2023, 49, 141–150. 10.1016/j.jare.2022.09.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Leslie H. A.; van Velzen M. J. M.; Brandsma S. H.; Vethaak A. D.; Garcia-Vallejo J. J.; Lamoree M. H. Discovery and Quantification of Plastic Particle Pollution in Human Blood. Environ. Int. 2022, 163, 107199 10.1016/j.envint.2022.107199. [DOI] [PubMed] [Google Scholar]
  19. Salvia R.; Rico L. G.; Bradford J. A.; Ward M. D.; Olszowy M. W.; Martínez C.; Madrid-Aris Á. D.; Grífols J. R.; Ancochea Á.; Gomez-Muñoz L.; Vives-Pi M.; Martínez-Cáceres E.; Fernández M. A.; Sorigue M.; Petriz J. Fast-Screening Flow Cytometry Method for Detecting Nanoplastics in Human Peripheral Blood. MethodsX 2023, 10, 102057 10.1016/j.mex.2023.102057. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Prata J. C.; da Costa J. P.; Lopes I.; Duarte A. C.; Rocha-Santos T. Environmental Exposure to Microplastics: An Overview on Possible Human Health Effects. Sci. Total Environ. 2020, 702, 134455 10.1016/j.scitotenv.2019.134455. [DOI] [PubMed] [Google Scholar]
  21. Marfella R.; Prattichizzo F.; Sardu C.; Fulgenzi G.; Graciotti L.; Spadoni T.; D’Onofrio N.; Scisciola L.; La Grotta R.; Frigé C.; Pellegrini V.; Municinò M.; Siniscalchi M.; Spinetti F.; Vigliotti G.; Vecchione C.; Carrizzo A.; Accarino G.; Squillante A.; Spaziano G.; Mirra D.; Esposito R.; Altieri S.; Falco G.; Fenti A.; Galoppo S.; Canzano S.; Sasso F. C.; Matacchione G.; Olivieri F.; Ferraraccio F.; Panarese I.; Paolisso P.; Barbato E.; Lubritto C.; Balestrieri M. L.; Mauro C.; Caballero A. E.; Rajagopalan S.; Ceriello A.; D’Agostino B.; Iovino P.; Paolisso G. Microplastics and Nanoplastics in Atheromas and Cardiovascular Events. N Engl J. Med. 2024, 390 (10), 900–910. 10.1056/NEJMoa2309822. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Yan Z.; Liu Y.; Zhang T.; Zhang F.; Ren H.; Zhang Y. Analysis of Microplastics in Human Feces Reveals a Correlation between Fecal Microplastics and Inflammatory Bowel Disease Status. Environ. Sci. Technol. 2022, 56 (1), 414–421. 10.1021/acs.est.1c03924. [DOI] [PubMed] [Google Scholar]
  23. Brown E. M.; Clardy J.; Xavier R. J. Gut Microbiome Lipid Metabolism and Its Impact on Host Physiology. Cell Host Microbe 2023, 31 (2), 173. 10.1016/j.chom.2023.01.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Djouina M.; Vignal C.; Dehaut A.; Caboche S.; Hirt N.; Waxin C.; Himber C.; Beury D.; Hot D.; Dubuquoy L.; Launay D.; Duflos G.; Body-Malapel M. Oral Exposure to Polyethylene Microplastics Alters Gut Morphology, Immune Response, and Microbiota Composition in Mice. Environ. Res. 2022, 212 (Pt B), 113230 10.1016/j.envres.2022.113230. [DOI] [PubMed] [Google Scholar]
  25. Zhang Q.; Lv Y.; Liu J.; Chang L.; Chen Q.; Zhu L.; Wang B.; Jiang J.; Zhu W. Size Matters Either Way: Differently-Sized Microplastics Affect Amphibian Host and Symbiotic Microbiota Discriminately. Environ. Pollut. 2023, 328, 121634 10.1016/j.envpol.2023.121634. [DOI] [PubMed] [Google Scholar]
  26. Zhang X.; Wen K.; Ding D.; Liu J.; Lei Z.; Chen X.; Ye G.; Zhang J.; Shen H.; Yan C.; Dong S.; Huang Q.; Lin Y. Size-Dependent Adverse Effects of Microplastics on Intestinal Microbiota and Metabolic Homeostasis in the Marine Medaka (Oryzias Melastigma). Environ. Int. 2021, 151, 106452 10.1016/j.envint.2021.106452. [DOI] [PubMed] [Google Scholar]
  27. Lu L.; Wan Z.; Luo T.; Fu Z.; Jin Y. Polystyrene Microplastics Induce Gut Microbiota Dysbiosis and Hepatic Lipid Metabolism Disorder in Mice. Sci. Total Environ. 2018, 631–632, 449–458. 10.1016/j.scitotenv.2018.03.051. [DOI] [PubMed] [Google Scholar]
  28. Jin Y.; Lu L.; Tu W.; Luo T.; Fu Z. Impacts of Polystyrene Microplastic on the Gut Barrier, Microbiota and Metabolism of Mice. Sci. Total Environ. 2019, 649, 308–317. 10.1016/j.scitotenv.2018.08.353. [DOI] [PubMed] [Google Scholar]
  29. Wen S.; Zhao Y.; Liu S.; Yuan H.; You T.; Xu H. Microplastics-Perturbed Gut Microbiota Triggered the Testicular Disorder in Male Mice: Via Fecal Microbiota Transplantation. Environ. Pollut. 2022, 309, 119789 10.1016/j.envpol.2022.119789. [DOI] [PubMed] [Google Scholar]
  30. Tu P.; Xue J.; Niu H.; Tang Q.; Mo Z.; Zheng X.; Wu L.; Chen Z.; Cai Y.; Wang X. Deciphering Gut Microbiome Responses upon Microplastic Exposure via Integrating Metagenomics and Activity-Based Metabolomics. Metabolites 2023, 13 (4), 530. 10.3390/metabo13040530. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Li B.; Ding Y.; Cheng X.; Sheng D.; Xu Z.; Rong Q.; Wu Y.; Zhao H.; Ji X.; Zhang Y. Polyethylene Microplastics Affect the Distribution of Gut Microbiota and Inflammation Development in Mice. Chemosphere 2020, 244, 125492 10.1016/j.chemosphere.2019.125492. [DOI] [PubMed] [Google Scholar]
  32. Gao B.; Shi X.; Li S.; Xu W.; Gao N.; Shan J.; Shen W. Size-Dependent Effects of Polystyrene Microplastics on Gut Metagenome and Antibiotic Resistance in C57BL/6 Mice. Ecotoxicol Environ. Saf 2023, 254, 114737 10.1016/j.ecoenv.2023.114737. [DOI] [PubMed] [Google Scholar]
  33. Toju H.; Tanabe A. S.; Yamamoto S.; Sato H. High-Coverage ITS Primers for the DNA-Based Identification of Ascomycetes and Basidiomycetes in Environmental Samples. PLoS One 2012, 7 (7), e40863 10.1371/journal.pone.0040863. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Stevens B. M.; Creed T. B.; Reardon C. L.; Manter D. K. Comparison of Oxford Nanopore Technologies and Illumina MiSeq Sequencing with Mock Communities and Agricultural Soil. Sci. Rep 2023, 13 (1), 9323. 10.1038/s41598-023-36101-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Bolyen E.; Rideout J. R.; Dillon M. R.; Bokulich N. A.; Abnet C. C.; Al-Ghalith G. A.; Alexander H.; Alm E. J.; Arumugam M.; Asnicar F.; Bai Y.; Bisanz J. E.; Bittinger K.; Brejnrod A.; Brislawn C. J.; Brown C. T.; Callahan B. J.; Caraballo-Rodríguez A. M.; Chase J.; Cope E. K.; Da Silva R.; Diener C.; Dorrestein P. C.; Douglas G. M.; Durall D. M.; Duvallet C.; Edwardson C. F.; Ernst M.; Estaki M.; Fouquier J.; Gauglitz J. M.; Gibbons S. M.; Gibson D. L.; Gonzalez A.; Gorlick K.; Guo J.; Hillmann B.; Holmes S.; Holste H.; Huttenhower C.; Huttley G. A.; Janssen S.; Jarmusch A. K.; Jiang L.; Kaehler B. D.; Kang K. B.; Keefe C. R.; Keim P.; Kelley S. T.; Knights D.; Koester I.; Kosciolek T.; Kreps J.; Langille M. G. I.; Lee J.; Ley R.; Liu Y.-X.; Loftfield E.; Lozupone C.; Maher M.; Marotz C.; Martin B. D.; McDonald D.; McIver L. J.; Melnik A. V.; Metcalf J. L.; Morgan S. C.; Morton J. T.; Naimey A. T.; Navas-Molina J. A.; Nothias L. F.; Orchanian S. B.; Pearson T.; Peoples S. L.; Petras D.; Preuss M. L.; Pruesse E.; Rasmussen L. B.; Rivers A.; Robeson M. S.; Rosenthal P.; Segata N.; Shaffer M.; Shiffer A.; Sinha R.; Song S. J.; Spear J. R.; Swafford A. D.; Thompson L. R.; Torres P. J.; Trinh P.; Tripathi A.; Turnbaugh P. J.; Ul-Hasan S.; van der Hooft J. J. J.; Vargas F.; Vázquez-Baeza Y.; Vogtmann E.; von Hippel M.; Walters W.; Wan Y.; Wang M.; Warren J.; Weber K. C.; Williamson C. H. D.; Willis A. D.; Xu Z. Z.; Zaneveld J. R.; Zhang Y.; Zhu Q.; Knight R.; Caporaso J. G. Reproducible, Interactive, Scalable and Extensible Microbiome Data Science Using QIIME 2. Nat. Biotechnol. 2019, 37 (8), 852–857. 10.1038/s41587-019-0209-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Nilsson R. H.; Larsson K.-H.; Taylor A. F. S.; Bengtsson-Palme J.; Jeppesen T. S.; Schigel D.; Kennedy P.; Picard K.; Glöckner F. O.; Tedersoo L.; Saar I.; Kõljalg U.; Abarenkov K. The UNITE Database for Molecular Identification of Fungi: Handling Dark Taxa and Parallel Taxonomic Classifications. Nucleic Acids Res. 2019, 47 (D1), D259–D264. 10.1093/nar/gky1022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Quast C.; Pruesse E.; Yilmaz P.; Gerken J.; Schweer T.; Yarza P.; Peplies J.; Glöckner F. O. The SILVA Ribosomal RNA Gene Database Project: Improved Data Processing and Web-Based Tools. Nucleic Acids Res. 2013, 41 (D1), D590–D596. 10.1093/nar/gks1219. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. McMurdie P. J.; Holmes S. Phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS One 2013, 8 (4), e61217 10.1371/journal.pone.0061217. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Beghini F.; McIver L. J.; Blanco-Míguez A.; Dubois L.; Asnicar F.; Maharjan S.; Mailyan A.; Manghi P.; Scholz M.; Thomas A. M.; Valles-Colomer M.; Weingart G.; Zhang Y.; Zolfo M.; Huttenhower C.; Franzosa E. A.; Segata N. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. elife 2021, 10, e65088 10.7554/eLife.65088. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Kaminski J.; Gibson M. K.; Franzosa E. A.; Segata N.; Dantas G.; Huttenhower C. High-Specificity Targeted Functional Profiling in Microbial Communities with ShortBRED. PLoS Comput. Biol. 2015, 11 (12), e1004557 10.1371/journal.pcbi.1004557. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Mallick H.; Rahnavard A.; McIver L. J.; Ma S.; Zhang Y.; Nguyen L. H.; Tickle T. L.; Weingart G.; Ren B.; Schwager E. H.; Chatterjee S.; Thompson K. N.; Wilkinson J. E.; Subramanian A.; Lu Y.; Waldron L.; Paulson J. N.; Franzosa E. A.; Bravo H. C.; Huttenhower C. Multivariable Association Discovery in Population-Scale Meta-Omics Studies. PLoS Comput. Biol. 2021, 17 (11), e1009442 10.1371/journal.pcbi.1009442. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Bastian M.; Heymann S.; Jacomy M. Gephi: An Open Source Software for Exploring and Manipulating Networks. Proceedings of the International AAAI Conference on Web and Social Media 2009, 3 (1), 361–362. 10.1609/icwsm.v3i1.13937. [DOI] [Google Scholar]
  43. Csárdi G.; Nepusz T.. The Igraph Software Package for Complex; Network Research: 2006. [Google Scholar]
  44. Wang H.; Wu H.; Li K.-D.; Wang Y.-Y.; Huang R.-G.; Du Y.-J.; Jin X.; Zhang Q.-R.; Li X.-B.; Li B.-Z. Intestinal Fungi and Systemic Autoimmune Diseases. Autoimmun Rev. 2023, 22 (2), 103234 10.1016/j.autrev.2022.103234. [DOI] [PubMed] [Google Scholar]
  45. Ding L.-J.; Zhou X.-Y.; Zhu Y.-G. Microbiome and Antibiotic Resistome in Household Dust from Beijing. China. Environ. Int. 2020, 139, 105702 10.1016/j.envint.2020.105702. [DOI] [PubMed] [Google Scholar]
  46. Pinto V. E. F.; Patriarca A. Alternaria Species and Their Associated Mycotoxins. Methods Mol. Biol. 2017, 1542, 13–32. 10.1007/978-1-4939-6707-0_2. [DOI] [PubMed] [Google Scholar]
  47. Pastor F. J.; Guarro J. Alternaria Infections: Laboratory Diagnosis and Relevant Clinical Features. Clin Microbiol Infect 2008, 14 (8), 734–746. 10.1111/j.1469-0691.2008.02024.x. [DOI] [PubMed] [Google Scholar]
  48. Zhong M.; Xiong Y.; Zhao J.; Gao Z.; Ma J.; Wu Z.; Song Y.; Hong X. Candida Albicans Disorder Is Associated with Gastric Carcinogenesis. Theranostics 2021, 11 (10), 4945–4956. 10.7150/thno.55209. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Yadav P.; Lee Y. H.; Panday H.; Kant S.; Bajwa N.; Parashar R.; Jha S. K.; Jha N. K.; Nand P.; Lee S. S.; Jha A. K. Implications of Microorganisms in Alzheimer’s Disease. Curr. Issues Mol. Biol. 2022, 44 (10), 4584. 10.3390/cimb44100314. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Imashioya T.; Kodama Y.; Ooka T.; Nakagawa S.; Nishikawa T.; Tanabe T.; Okamoto Y.; Imuta N.; Kirishima M.; Tanimoto A.; Koriyama T.; Nishi J.; Kawano Y. Liver Abscess Due to Sterigmatomyces Halophilus in a Boy with Acute Lymphoblastic Leukemia. J. Infect Chemother 2019, 25 (12), 1047–1049. 10.1016/j.jiac.2019.05.021. [DOI] [PubMed] [Google Scholar]
  51. Qiu X.; Ma J.; Jiao C.; Mao X.; Zhao X.; Lu M.; Wang K.; Zhang H. Alterations in the Mucosa-Associated Fungal Microbiota in Patients with Ulcerative Colitis. Oncotarget 2017, 8 (64), 107577–107588. 10.18632/oncotarget.22534. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Saha R.; Das S. Bipolaris Keratomycosis. Mycoses 2005, 48 (6), 453–455. 10.1111/j.1439-0507.2005.01151.x. [DOI] [PubMed] [Google Scholar]
  53. Wang X.; Zhou Z.; Turner D.; Lilly M.; Ou T.; Jiang W. Differential Circulating Fungal Microbiome in Prostate Cancer Patients Compared to Healthy Control Individuals. J. Immunol. Res. 2022, 2022, 2574964 10.1155/2022/2574964. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Mims T. S.; Abdallah Q. A.; Stewart J. D.; Watts S. P.; White C. T.; Rousselle T. V.; Gosain A.; Bajwa A.; Han J. C.; Willis K. A.; Pierre J. F. The Gut Mycobiome of Healthy Mice Is Shaped by the Environment and Correlates with Metabolic Outcomes in Response to Diet. Commun. Biol. 2021, 4 (1), 281. 10.1038/s42003-021-01820-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Wang Y.; Li X.; Chen X.; Kulyar M. F.-E.-A.; Duan K.; Li H.; Bhutta Z. A.; Wu Y.; Li K. Gut Fungal Microbiome Responses to Natural Cryptosporidium Infection in Horses. Front Microbiol 2022, 13, 877280 10.3389/fmicb.2022.877280. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Chang Y.-C.; Graf E.; Green A. M. Invasive Curvularia Infection in Pediatric Patients With Hematologic Malignancy Identified by Fungal Sequencing. J. Pediatric Infect Dis Soc. 2019, 8 (1), 87–91. 10.1093/jpids/piy092. [DOI] [PubMed] [Google Scholar]
  57. Khurana A.; Chanda S.; Bhagat P.; Aggarwal S.; Sharma M.; Chauhan L. Clinical Characteristics, Predisposing Factors, and Treatment Outcome of Curvularia Keratitis. Indian J. Ophthalmol 2020, 68 (10), 2088–2093. 10.4103/ijo.IJO_90_20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Knutsen A. P.; Bush R. K.; Demain J. G.; Denning D. W.; Dixit A.; Fairs A.; Greenberger P. A.; Kariuki B.; Kita H.; Kurup V. P.; Moss R. B.; Niven R. M.; Pashley C. H.; Slavin R. G.; Vijay H. M.; Wardlaw A. J. Fungi and Allergic Lower Respiratory Tract Diseases. J. Allergy Clin Immunol 2012, 129 (2), 280–291. 10.1016/j.jaci.2011.12.970. [DOI] [PubMed] [Google Scholar]
  59. You N.; Xu J.; Wang L.; Zhuo L.; Zhou J.; Song Y.; Ali A.; Luo Y.; Yang J.; Yang W.; Zheng M.; Xu J.; Shao L.; Shi J. Fecal Fungi Dysbiosis in Nonalcoholic Fatty Liver Disease. Obesity (Silver Spring) 2021, 29 (2), 350–358. 10.1002/oby.23073. [DOI] [PubMed] [Google Scholar]
  60. Wang M.; Liu F.; Crous P. W.; Cai L. Phylogenetic Reassessment of Nigrospora: Ubiquitous Endophytes, Plant and Human Pathogens. Persoonia 2017, 39, 118–142. 10.3767/persoonia.2017.39.06. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Machida M.; Nakamura I.; Sato A.; Nakamura S.; Miyazaki Y.; Watanabe H. Hypertrophic Pachymeningitis Caused by Schizophyllum Sp.: A Novel Case Report. Infection 2021, 49 (4), 775–779. 10.1007/s15010-020-01544-y. [DOI] [PubMed] [Google Scholar]
  62. Ling Z.; Zhu M.; Liu X.; Shao L.; Cheng Y.; Yan X.; Jiang R.; Wu S. Fecal Fungal Dysbiosis in Chinese Patients With Alzheimer’s Disease. Front Cell Dev Biol. 2021, 8, 631460 10.3389/fcell.2020.631460. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Jiang Q.-L.; Lu Y.; Zhang M.-J.; Cui Z.-Y.; Pei Z.-M.; Li W.-H.; Lu L.-G.; Wang J.-J.; Lu Y.-Y. Mucosal Bacterial Dysbiosis in Patients with Nodular Lymphoid Hyperplasia in the Terminal Ileum. World J. Gastroenterol 2022, 28 (8), 811–824. 10.3748/wjg.v28.i8.811. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Huang J.-N.; Wen B.; Xu L.; Ma H.-C.; Li X.-X.; Gao J.-Z.; Chen Z.-Z. Micro/Nano-Plastics Cause Neurobehavioral Toxicity in Discus Fish (Symphysodon Aequifasciatus): Insight from Brain-Gut-Microbiota Axis. J. Hazard Mater. 2022, 421, 126830 10.1016/j.jhazmat.2021.126830. [DOI] [PubMed] [Google Scholar]
  65. Hao Y.; Meng L.; Zhang Y.; Chen A.; Zhao Y.; Lian K.; Guo X.; Wang X.; Du Y.; Wang X.; Li X.; Song L.; Shi Y.; Yin X.; Gong M.; Shi H. Effects of Chronic Triclosan Exposure on Social Behaviors in Adult Mice. J. Hazard. Mater. 2022, 424 (Pt C), 127562 10.1016/j.jhazmat.2021.127562. [DOI] [PubMed] [Google Scholar]
  66. Martín R.; Rios-Covian D.; Huillet E.; Auger S.; Khazaal S.; Bermúdez-Humarán L. G.; Sokol H.; Chatel J.-M.; Langella P. Faecalibacterium: A Bacterial Genus with Promising Human Health Applications. FEMS Microbiol Rev. 2023, 47 (4), fuad039. 10.1093/femsre/fuad039. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Cui Y.; Zhang L.; Wang X.; Yi Y.; Shan Y.; Liu B.; Zhou Y.; Lü X. Roles of Intestinal Parabacteroides in Human Health and Diseases. FEMS Microbiol Lett. 2022, 369 (1), fnac072. 10.1093/femsle/fnac072. [DOI] [PubMed] [Google Scholar]
  68. Sencio V.; Machelart A.; Robil C.; Benech N.; Hoffmann E.; Galbert C.; Deryuter L.; Heumel S.; Hantute-Ghesquier A.; Flourens A.; Brodin P.; Infanti F.; Richard V.; Dubuisson J.; Grangette C.; Sulpice T.; Wolowczuk I.; Pinet F.; Prévot V.; Belouzard S.; Briand F.; Duterque-Coquillaud M.; Sokol H.; Trottein F. Alteration of the Gut Microbiota Following SARS-CoV-2 Infection Correlates with Disease Severity in Hamsters. Gut Microbes 2022, 14 (1), 2018900. 10.1080/19490976.2021.2018900. [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Dayama G.; Priya S.; Niccum D. E.; Khoruts A.; Blekhman R. Interactions between the Gut Microbiome and Host Gene Regulation in Cystic Fibrosis. Genome Med. 2020, 12 (1), 12. 10.1186/s13073-020-0710-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Qiu H.; Gao H.; Yu F.; Xiao B.; Li X.; Cai B.; Ge L.; Lu Y.; Wan Z.; Wang Y.; Xia T.; Wang A.; Zhang S. Perinatal Exposure to Low-Level PBDE-47 Programs Gut Microbiota, Host Metabolism and Neurobehavior in Adult Rats: An Integrated Analysis. Sci. Total Environ. 2022, 825, 154150 10.1016/j.scitotenv.2022.154150. [DOI] [PubMed] [Google Scholar]
  71. Liu S.; Li E.; Sun Z.; Fu D.; Duan G.; Jiang M.; Yu Y.; Mei L.; Yang P.; Tang Y.; Zheng P. Altered Gut Microbiota and Short Chain Fatty Acids in Chinese Children with Autism Spectrum Disorder. Sci. Rep 2019, 9 (1), 287. 10.1038/s41598-018-36430-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Shang J.; Guo H.; Li J.; Li Z.; Yan Z.; Wei L.; Hua Y.; Lin L.; Tian Y. Exploring the Mechanism of Action of Sanzi Formula in Intervening Colorectal Adenoma by Targeting Intestinal Flora and Intestinal Metabolism. Front Microbiol 2022, 13, 1001372. 10.3389/fmicb.2022.1001372. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Clarke G.; Stilling R. M.; Kennedy P. J.; Stanton C.; Cryan J. F.; Dinan T. G. Minireview: Gut Microbiota: The Neglected Endocrine Organ. Mol. Endocrinol. 2014, 28 (8), 1221–1238. 10.1210/me.2014-1108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Li X.; Shi W.; Xiong Q.; Hu Y.; Qin X.; Wan G.; Zeng Q. Leptin Improves Intestinal Flora Dysfunction in Mice with High-Fat Diet-Induced Obesity. J. Int. Med. Res. 2020, 48 (6), 0300060520920062 10.1177/0300060520920062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Zhang X.; Coker O. O.; Chu E. S.; Fu K.; Lau H. C. H.; Wang Y.-X.; Chan A. W. H.; Wei H.; Yang X.; Sung J. J. Y.; Yu J. Dietary Cholesterol Drives Fatty Liver-Associated Liver Cancer by Modulating Gut Microbiota and Metabolites. Gut 2021, 70 (4), 761–774. 10.1136/gutjnl-2019-319664. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Lin H.; Wu H.; Liu F.; Yang H.; Shen L.; Chen J.; Zhang X.; Zhong Y.; Zhang H.; Liu Z. Assessing the Hepatotoxicity of PFOA, PFOS, and 6:2 Cl-PFESA in Black-Spotted Frogs (Rana Nigromaculata) and Elucidating Potential Association with Gut Microbiota. Environ. Pollut. 2022, 312, 120029 10.1016/j.envpol.2022.120029. [DOI] [PubMed] [Google Scholar]
  77. Wang Q.; Sun Z.; Huang Z.; Ma S.; Chen K.; Ju X. Effects of Tolfenpyrad Exposure on Development and Response Mechanism in the Silkworm, Bombyx Mori. Pestic. Biochem. Physiol. 2023, 189, 105280 10.1016/j.pestbp.2022.105280. [DOI] [PubMed] [Google Scholar]
  78. Liu X.; Mao B.; Gu J.; Wu J.; Cui S.; Wang G.; Zhao J.; Zhang H.; Chen W. Blautia-a New Functional Genus with Potential Probiotic Properties?. Gut Microbes 2021, 13 (1), 1–21. 10.1080/19490976.2021.1875796. [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Chiu K. K.; Bashir S. T.; Abdel-Hamid A. M.; Clark L. V.; Laws M. J.; Cann I.; Nowak R. A.; Flaws J. A. Isolation of DiNP-Degrading Microbes from the Mouse Colon and the Influence DiNP Exposure Has on the Microbiota, Intestinal Integrity, and Immune Status of the Colon. Toxics 2022, 10 (2), 75. 10.3390/toxics10020075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Zhang K.; Yang J.; Chen L.; He J.; Qu D.; Zhang Z.; Liu Y.; Li X.; Liu J.; Li J.; Xie X.; Wang Q. Gut Microbiota Participates in Polystyrene Microplastics-Induced Hepatic Injuries by Modulating the Gut-Liver Axis. ACS Nano 2023, 17 (15), 15125–15145. 10.1021/acsnano.3c04449. [DOI] [PubMed] [Google Scholar]
  81. Olesky M.; Zhao S.; Rosenberg R. L.; Nicholas R. A. Porin-Mediated Antibiotic Resistance in Neisseria Gonorrhoeae: Ion, Solute, and Antibiotic Permeation through PIB Proteins with penB Mutations. J. Bacteriol. 2006, 188 (7), 2300–2308. 10.1128/JB.188.7.2300-2308.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Achard A.; Villers C.; Pichereau V.; Leclercq R. New Lnu(C) Gene Conferring Resistance to Lincomycin by Nucleotidylation in Streptococcus Agalactiae UCN36. Antimicrob. Agents Chemother. 2005, 49 (7), 2716–2719. 10.1128/AAC.49.7.2716-2719.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Melville C. M.; Scott K. P.; Mercer D. K.; Flint H. J. Novel Tetracycline Resistance Gene, Tet(32), in the Clostridium-Related Human Colonic Anaerobe K10 and Its Transmission in Vitro to the Rumen Anaerobe Butyrivibrio Fibrisolvens. Antimicrob. Agents Chemother. 2001, 45 (11), 3246–3249. 10.1128/AAC.45.11.3246-3249.2001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Collins J. R.; Arredondo A.; Roa A.; Valdez Y.; León R.; Blanc V. Periodontal Pathogens and Tetracycline Resistance Genes in Subgingival Biofilm of Periodontally Healthy and Diseased Dominican Adults. Clin Oral Investig 2016, 20 (2), 349–356. 10.1007/s00784-015-1516-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Kazimierczak K. A.; Rincon M. T.; Patterson A. J.; Martin J. C.; Young P.; Flint H. J.; Scott K. P. A New Tetracycline Efflux Gene, Tet(40), Is Located in Tandem with Tet(O/32/O) in a Human Gut Firmicute Bacterium and in Metagenomic Library Clones. Antimicrob. Agents Chemother. 2008, 52 (11), 4001–4009. 10.1128/AAC.00308-08. [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Saha P.; Bose D.; Stebliankin V.; Cickovski T.; Seth R. K.; Porter D. E.; Brooks B. W.; Mathee K.; Narasimhan G.; Colwell R.; Scott G. I.; Chatterjee S. Prior Exposure to Microcystin Alters Host Gut Resistome and Is Associated with Dysregulated Immune Homeostasis in Translatable Mouse Models. Sci. Rep 2022, 12 (1), 11516. 10.1038/s41598-022-15708-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  87. Kovtun A. S.; Averina O. V.; Alekseeva M. G.; Danilenko V. N. Antibiotic Resistance Genes in the Gut Microbiota of Children with Autistic Spectrum Disorder as Possible Predictors of the Disease. Microb Drug Resist 2020, 26 (11), 1307–1320. 10.1089/mdr.2019.0325. [DOI] [PubMed] [Google Scholar]
  88. Wright G. D.; Thompson P. R. Aminoglycoside Phosphotransferases: Proteins, Structure, and Mechanism. Front. Biosci. 1999, 4, D9–21. 10.2741/A408. [DOI] [PubMed] [Google Scholar]
  89. Yu Z.; Yan C.; Qiu D.; Zhang X.; Wen C.; Dong S. Accumulation and Ecotoxicological Effects Induced by Combined Exposure of Different Sized Polyethylene Microplastics and Oxytetracycline in Zebrafish. Environ. Pollut. 2023, 319, 120977 10.1016/j.envpol.2022.120977. [DOI] [PubMed] [Google Scholar]
  90. Zhou N.; Wang Z.; Yang L.; Zhou W.; Qin Z.; Zhang H. Size-Dependent Toxicological Effects of Polystyrene Microplastics in the Shrimp Litopenaeus Vannamei Using a Histomorphology, Microbiome, and Metabolic Approach. Environ. Pollut. 2023, 316 (Pt 2), 120635 10.1016/j.envpol.2022.120635. [DOI] [PubMed] [Google Scholar]
  91. Sim Y.; Cho H.-J.; Lee J.-S.; Lee W. S.; Kim H.; Jeong J. Combined Effects of Microplastics and Benz[a]Anthracene on Cardiotoxicity in Zebrafish (Danio Rerio) Larvae: Size Matters. Chemosphere 2023, 330, 138723 10.1016/j.chemosphere.2023.138723. [DOI] [PubMed] [Google Scholar]
  92. Wu H.; Guo J.; Yao Y.; Xu S. Polystyrene Nanoplastics Induced Cardiomyocyte Apoptosis and Myocardial Inflammation in Carp by Promoting ROS Production. Fish Shellfish Immunol 2022, 125, 1–8. 10.1016/j.fsi.2022.04.048. [DOI] [PubMed] [Google Scholar]
  93. Yu S.-P.; Nakaoka M.; Chan B. K. K. The Gut Retention Time of Microplastics in Barnacle Naupliar Larvae from Different Climatic Zones and Marine Habitats. Environ. Pollut. 2021, 268, 115865 10.1016/j.envpol.2020.115865. [DOI] [PubMed] [Google Scholar]
  94. Peng C.; He N.; Wu Y.; Lu Y.; Sun H.; Wang L. Excretion Characteristics of Nylon Microplastics and Absorption Risk of Nanoplastics in Rats. Ecotoxicol Environ. Saf 2022, 238, 113586 10.1016/j.ecoenv.2022.113586. [DOI] [PubMed] [Google Scholar]
  95. Gkoutselis G.; Rohrbach S.; Harjes J.; Obst M.; Brachmann A.; Horn M. A.; Rambold G. Microplastics Accumulate Fungal Pathogens in Terrestrial Ecosystems. Sci. Rep 2021, 11 (1), 13214. 10.1038/s41598-021-92405-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  96. Sam Q. H.; Chang M. W.; Chai L. Y. A. The Fungal Mycobiome and Its Interaction with Gut Bacteria in the Host. Int. J. Mol. Sci. 2017, 18 (2), 330. 10.3390/ijms18020330. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

ao4c00645_si_001.pdf (307.1KB, pdf)

Data Availability Statement

The sequencing data is available at the EBI metagenomics repository (https://www.ebi.ac.uk/ena), under project number PRJEB74218.

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