Polystyrene micro- and nanoplastics aggravates colitis in a mouse model – effects on biodistribution, macrophage polarization, and gut microbiome

doi:10.21203/rs.3.rs-4467515/v1

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Research Article

Polystyrene micro- and nanoplastics aggravates colitis in a mouse model – effects on biodistribution, macrophage polarization, and gut microbiome

https://doi.org/10.21203/rs.3.rs-4467515/v1

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Background

The increasing prevalence of inflammatory bowel disease (IBD) and rising pollution from micro- and nanoplastic (MNP) particles has prompted investigations on their potential interconnection. To elucidate the complex relationship between IBD and exposure to MNPs, we induced colitis in mice using dextran sodium sulfate (DSS) and orally administered a solution of differently sized polystyrene (PS) MNPs (diameter 10, 1, and 0.29 µm). These particles facilitated a detailed examination of MNP biodistribution, macrophage response, and gut microbiome alterations under inflammatory conditions.

Results

Specifically nanosized PS particles accumulated in the bloodstream and excretory organs, with enhanced accumulation in the colitis model. Macrophages shifted towards a pro-inflammatory phenotype, with decreased anti-inflammatory markers highlighting the intricate effects of MNPs on inflammation and immune cell behavior. Moreover, MNPs significantly disrupted the gut microbiome, reducing microbial diversity and shifting bacterial populations towards pro-inflammatory and potentially pathogenic species.

Conclusions

These changes suggest that MNP exposure could exacerbate colitis through complex interactions involving MNPs, immune responses, and microbial dynamics. The fast growing exposure to MNPs underscores the urgent need for comprehensive public health strategies to address MNP pollution, its implications for disease and potential impacts on public health.

Micro- and nanoplastic

polystyrene

colitis mouse model

gut microbiome

The increasing presence of plastics in our environment, especially micro- and nanoplastics (MNPs), has emerged as a profound concern, impacting not only the environment but also various species, including humans.[1, 2] The gastrointestinal (GI) ingestion of plastics, whether directly or through trophic level transfer, has been shown to cause a variety of mechanical, chemical, and biological impacts.[3] For years it has been described that in marine organisms, such as cetaceans, turtles, and birds, the accumulation of large plastic masses can lead to GI blockage and even death.[4] An initial pilot study revealed the presence of plastic particles in human stool samples.[5] Since then, the spotlight has been on the GI tract and associated pathologies following exposure to MNPs. However, our current understanding of the toxic profile of MNPs remains limited due to the high complexity of these particles. Variations in chemical composition, additives, shape, size, and other parameters make comparisons between studies challenging.[6] However, it is evident that size matters, as mainly the smaller fractions of plastic particles in the low micro- to nanometer range pose a more insidious threat due to their potential to accumulate and translocate within the body.[7, 8]

PS MNPs, a common type of environmental plastic particle pollutant, have been shown to cross biological barriers,[9, 10] leading to immune and inflammatory responses in organisms. Several studies already described the interplay of acute colitis and MNPs.[10–14] The incidence of inflammatory bowel disease (IBD), including conditions like ulcerative colitis and Crohn's disease, is dramatically increasing. These complex diseases are influenced by genetic, environmental, immunological, and microbial factors.[15] The dextran sulfate sodium (DSS) mouse model, which closely mimics the clinical and histological features of human IBD, is an invaluable tool for investigating this. It allows for controlled administration of PS MNPs, enabling a systematic exploration of their effects on the disease. Besides the investigation of biodistribution and inflammatory processes, one critical factor is influenced by chronic ingestion of MNPs over long periods of time: the gut microbiome. The gut microbiome, a critical component of an organism's health, is not immune to the influence of these pollutants. MNPs can alter the gut microbial community composition and function, potentially disrupting the delicate balance of host-microbiome interactions.[16] After exposing zebrafish to polyethylene, a gut microbiome-associated increase in oxidative stress and inflammation was already described.[17] Recently, studies have drawn a connection between gut microbiome and liver toxicity caused by PS MNPs in healthy mice.[18–20] The oxidative stress induced by inflammation can favor the bloom of more resistant bacterial groups, such as the members of Enterobacteriaceae, altering the gut's microbial ecosystem. MNPs serve as vectors for microbial dispersal, potentially introducing pathogens into the gut. The formation of biofilms on plastic particles can enhance microbial survival and facilitate horizontal gene transfer, increasing the risk of disease transmission. The 'plastisphere'—the microbial communities associated with plastic particles—has recently been recognized for its distinctive taxonomic and functional diversity.[21] However, the implications of the plastisphere as a microbial reservoir for gut colonization and health remain poorly understood.

DSS-induced colitis model demonstrated that intestinal inflammation is accompanied by major changes in the composition and function of the intestinal microbiota, a key aspect often overlooked in chronic DSS colitis models.[22–24] This refined model of chronic DSS-induced colitis, which mirrors human IBD symptoms without the severe weight loss typically observed in DSS models, has revealed significant microbial shifts. In parallel, microplastics can alter the gut microbiome, potentially exacerbating or ameliorating colitis symptoms. The gut microbiome has a major and unequivocal dual role in biology. First, it is one of the largest and richest biomes. Second, its evolutionary integration into the host renders its host's physiology, development, resistance to pathogens, and immune response heavily dependent on the healthy state of the gut bacterial communities. Also, the complex relationships between the microbiota and its host suggest that different bacterial species may exert positive or negative effects on different hosts and their physical states. In general, any disturbance that upsets the balance of the gut bacteria causes dysbiosis – a condition commonly triggered by gut inflammation and/or infections.[25] The DSS model provides an opportunity to delve into these interactions and understand how changes in microbial diversity due to microplastics influence intestinal inflammation and immune response. Besides the gut microbiome, the macrophage polarization is also crucial to IBD progression and in the IBD inflammatory response.[26] A range of studies has explored the influence of different materials on macrophage polarization. For instance, carboxyl- and amino-functionalized polystyrene or polyurethane nanoparticles can skew macrophage polarization towards an anti-inflammatory phenotype, while biodegradable polyurethane nanoparticles can inhibit pro-inflammatory macrophage polarization.[27]

In this study, we investigate the effects of orally administered PS MNPs in a model of colitis on the extent of biodistribution, IBD morphology, gut microbiome and metabolome, and macrophage polarization. We aim to shed light on the potential health implications of microplastic exposure and contribute to the growing body of knowledge on this critical environmental issue.

Despite the known presence of microplastics in the environment, their specific effects on diseases like IBD are not well understood. The DSS mouse model of colitis offers a possible pathway to fill this knowledge gap, with potential implications for future clinical research and interventions. This research is crucial for understanding the connection between environmental factors and gut health in inflammatory bowel diseases.

Polystyrene particles and characterization

Commercially available labelled PS particles with a diameter of 10.39 ± 0.13 µm (spherical, aqueous suspension, 5% w/v, blue colored), 1.14 ± 0.03 µm (spherical, aqueous suspension 2.5% w/v, ex/em = 530/607 nm) and 0.293 ± 0.008 µm (spherical, aqueous suspension 2.5% w/v, ex/em = 502/518 nm) were obtained from Microparticles GmbH (Berlin, Germany). PS particle characterization was performed by measuring ζ potential, size, and polydispersity index (PDI) on a Zetasizer Pro device (Malvern Pananalytical, Malvern, United Kingdom).[28] Data analysis was performed by using ZS Xplorer software. ζ potential, size and PDI were measured in deionized (DI) water (conductivity of 0.055 µS/cm), 1 mM KCl solution, 1:9 and 1:99 diluted with phosphate buffered saline (PBS).

Microscopy and spectroscopy

A correlative microscopy and spectroscopy were employed to characterize the PS particles. In order to determine the size and surface morphology of the particles, a Scanning Electron Microscopy (SEM) (Zeiss Crossbeam 550) equipped with a Secondary Electrons Secondary Ions (SESI) detector was used at a low voltage of 1 kV to avoid changes caused by electrons. A confocal micro-Raman spectrometer (HORIBA LabRAM HR Evo-Nano) was utilized for spontaneous Raman spectroscopy to confirm the chemical composition and identify the most prominent Raman peak (found at ~ 1001 cm^-1) of the PS particles. For Raman excitation and collection in backscattering geometry, a 785 nm laser with a power of 5.3 mW focused through a 100x objective was applied. Chemical imaging was done applying Stimulated Raman Scattering (SRS) (Leica Stellaris 8) at the selected Raman peak corresponding to a laser excitation of 934.5 nm with a 20x objective. SRS is a resonantly enhanced process giving a much more efficient signal of several orders of higher magnitude than that of a spontaneous Raman scattering.[29] Fluorescence images of particles were taken at a Zeiss LSM 700.

Fluorescence images of tissue sections and blood smears were taken at a Zeiss Axio Imager M2 microscope (63x objective). Respective image processing was done using Zeiss Zen blue software (version 3.5).

For electron microscopy, tissue was fixed in 2.5% glutaraldehyde in 0.1 M cacodylate buffer at pH 7.3 for 3 to 4 hours. After dehydration, the tissue was embedded in resin (AGAR-100, Agar Scientific). Ultrathin sections (80 nm) were contrasted with uranyl acetate/lead citrate and studied with a Zeiss EM 900 electron microscope.

Mouse model

Male C57Bl/6J mice were bred in-house and kept under standard conditions (ambient temperature at 12 h light/dark cycle, food and water provided ad libitum). All experiments were conducted according to Austrian animal welfare legislation (license 2022 − 0.257.045), and experimental setups were approved by the local animal ethics committee. MNPs were applied as a mixture containing all three sizes at equal weight concentrations, prepared in sterile water. MNP mix was applied according to scheme as a 100 µl gavage with a concentration of 0.3 mg/size/dose (total 0.9 mg MNPs/dose). For proof of MNP uptake into the GI tract, 6 healthy wild-type mice were used (n = 2/group). Mice were either left untreated (Ctr) or received a single dose of 100 µl MNP mix and were sacrificed after 2 or 4 h. Small intestine (si) and colon (co) were collected and processed for histology and TEM as described in the respective sections. For the main experiment, at the age of weaning (~ 3 weeks) mice from different litters were randomized into 4 groups (n = 8) in order to compensate for litter specific microbiome effects. Treatment was initiated at 6–8 weeks of age according to the treatment scheme. Group 1 (Ctr) received sterile water, group 2 (MNP) was treated with MNP, group 3 (DSS) was treated with DSS and group 4 (DSS + MNP) received both DSS and MNP treatment. In detail, mice received a daily gavage of 100 µl sterile drinking water or MNP mix (all three sizes mixed at equal weight concentrations of 0.3 mg/size/dose in sterile water) for 10 days. For the colitis model, groups 3 and 4 were additionally treated for the first 5 days with 2.5% DSS in their drinking water (ad libitum),[30] parallel to the daily gavage. After these initial 5 days of DSS colitis induction, mice again received regular drinking water until the end of the experiment. Mice were sacrificed at day 10 (~ 24 h after the last gavage) and blood (terminal heart puncture under anesthesia, EDTA) and organs were collected. For microbiome analysis, stool samples were collected on day 0 prior to treatment start and on day 10 before mice were sacrificed.

Histology

The intestine were gently flushed with PBS and 4.5% PFA and fixed as swiss rolls.[31] Organs (heart, lung, liver, kidney, spleen, brain, testicles) were collected and parts were stored in histological cassettes as well. Samples were processed according to a modified isopropanol protocol [32] and embedded in paraffin. 3 µm sections were cut from tissue blocks and used for staining. Fluorescence staining for identification of PS particles were performed according to isopropanol protocol with DAPI nuclear counterstain (Merck Darmstadt, Germany). Blood smears from EDTA blood samples were performed according to standard protocol. Immunohistochemistry (IHC) and hematoxylin/eosin staining (H&E) were performed using standard protocols. The following antibodies were used for IHC: F4/80 (Cell Signaling, #70076, 1:120), iNOS (Cell Signaling, #68186, 1:1000) and Arg1 (Cell Signaling, #93668, 1:100). Tissue slides were scanned by a SCAN II digital slide scanner (3d Histech, Budapest, Hungary) using a 20X objective.

Colitis score from H&E scans was evaluated by an experienced pathologist in a blinded fashion as previously reported by Crnčec et al. (2018).[30] In brief, colons were scored according to inflammation (0: rare or no inflammatory cells in lamina propria, 1: increased numbers of granulocytes in lamina propria, 2: confluence of inflammatory cells extending to submucosa, 3: transmural extension of inflammatory infiltrate), crypt damage (0: none, 1: loss of basal 1/3 of the crypt, 2: loss of basal 2/3 of the crypt, 3: entire crypt loss, 4: change in epithelial surface with erosion, 5: confluent erosion), ulceration (0: none, 1: 1–2 ulcers focally, 2: 3–4 ulcers focally, 3: confluent ulceration). Individual scores were added up and multiplied by the score for the affected area (1: 0–25% of the colon, 2: 25–50% of the colon, 3: 50–75% of the colon, 4: 75–100%). Digitized IHC tissue sections were subsequently analyzed using the Definiens® TissueStudio® histomorphometry software or QuPath software (version 0.4.3). Nuclei and cells were identified using the software’s cell detection algorithms and categorized as negative or positive based on the staining intensity. The same thresholds were applied to all tissue sections and the percentage of positive cells per area of analyzed tissue was determined and compared across groups.

Isolation of monocytes from peripheral blood mononuclear cells (PBMCs) of healthy donors

PBMCs were obtained from whole-blood samples of three healthy volunteers using a standard protocol involving LymphoPrep (Stemcell Technologies) and density gradient centrifugation. Subsequently, monocytes were separated from PBMCs by adhering them to ultra-low attachment culture dishes (Corning) and then underwent a 6-day differentiation into macrophages in RPMI-1640 supplemented with 10% FCS (Thermo Fisher Scientific), 1% Penicillin-Streptomycin (Thermo Fisher Scientific), and 20 ng/ml human recombinant M-CSF (Peprotech) with two medium changes. On the sixth day, macrophages were exposed to 5 ng/mL MNP particles and subjected to further analysis after a 24-hour incubation period.

Confocal microscopy of macrophages

For microscopy imaging macrophages were plated in µ-Slide 8 Wells (ibidi) and exposed to green-labeled 0.29 µm MNPs for 24 hours. Following formalin fixation, slides were rinsed in 0.1% PBS-Tween 20 (PBS-T), permeabilized in 0.3% Triton X-100 in PBS-T and blocked with a blocking solution (10% goat serum in 0.1% Triton X-100 in PBS-T). The primary antibody targeting CD14 (CatNo. # 14-0149-82, Thermo Fisher Scientific) was diluted 1:400 in the blocking solution and incubated overnight at 4°C. Afterward, slides were subjected to secondary antibody incubation (Alexa Fluor 594 goat anti-rabbit, CatNo. A-11012; Thermo Fisher Scientific), followed by counterstaining with DAPI (Serva Electrophoresis). Three representative images were captured using LSM 5 Exciter (Zeiss) with a 63X oil immersion objective. Image processing was performed using ImageJ.

In vitro analysis and flow cytometry

To quantify the uptake of MNPs, macrophages were exposed to fluorescently labeled MNP particles at a concentration of 5 ng/µL for 24 h. Concurrently, the evaluation of surface markers indicating macrophage polarization was conducted in technical replicates of equivalent samples treated with non-labeled MNPs. Cells were subsequently blocked using 40% human AB serum for 5 minutes at room temperature. For phagocytosis quantification, cells previously incubated with fluorescent beads were stained with Zombie Violet™ (CatNo: 423114, Biolegend) as well as an APC-Cy7 conjugated anti-CD11b antibody (CatNo: 101226, Biolegend). For marker expression, cells previously incubated with non-fluorescent beads were stained with Zombie Violet™, an Alexa Fluor™ 488 conjugated anti-CD206 antibody (CatNo: 53-2069-42, Thermo Fisher Scientific), a PerCP-eFluor™ 710 conjugated anti-CD163 antibody (CatNo: 46-1639-42, Thermo Fisher Scientific), a PE-Cy7 conjugated anti-4-1BBL antibody (CatNo: 311512, Biolegened), an APC conjugated anti-SIRPα antibody (CatNo: 372106, Biolegend), an Alexa Fluor™ 700 conjugated anti-CD45 antibody (CatNo: 368514, Biolegend), the APC-Cy7 conjugated anti-CD11b antibody, a Brilliant Violet 510™ conjugated anti-HLA-DR antibody (CatNo: 307646, Biolegend), a Brilliant Violet 650™ conjugated anti-CD86 antibody (CatNo: 305428, Biolegend) and a Brilliant Violet 785™ conjugated anti-PD-L1 antibody (CatNo: 329736, Biolegend). Flow cytometry was performed using the DxFlex flow cytometer (Beckman Coulter Inc.) and CytExpert software. Compensation was performed using single stainings of respective cell types treated with 5% Tween 20 for 5 min for viability stains, as well as single stainings of UltraComp eBeads compensation beads (CatNo: 01-2222-42, Thermo Fisher Scientific) with respective antibody stains. Gating, compensation matrix calculation and data visualization was performed in Kaluza analysis (Becton Dickinson).

Microbiome analysis

DNA from stool samples was extracted using the QIAamp Fast DNA stool mini kit automated on the QIAcube. Approximately 200 mg stool were transferred to 0.70 mm Garnet Bead tubes filled with 1 ml InhibitEx buffer. Subsequently, bead beating was performed using a SpeedMill PLUS for 45 s at 60 Hz. Samples were then heated to 95°C for 5 min and centrifuged for 1 min at 10,000 rpm. 200 µl of the resulting supernatant were transferred to a 1.5 ml microcentrifuge tube, which was placed in the QIAcube for follow-up automated DNA isolation according to the manufacturer’s protocol. DNA was eluted from the QIAamp silica-gel membrane with 200 µl TE buffer.

Isolated DNA was used to amplify hypervariable regions V3 and V4 of the 16S rRNA gene using the primer pair 357F-806R in a dual-barcoding approach according to Caporaso et al.[33] 3 µl DNA were used for amplification and PCR-products were verified via agarose gel electrophoresis. PCR products were normalized using the SequalPrep Normalization Plate Kit (Thermo Fischer Scientific, Waltham, MA, USA), pooled equimolarily and sequenced on the Illumina MiSeq v3 2x300bp (Illumina Inc., San Diego, CA, USA). Demultiplexing after sequencing was based on 0 mismatches in the barcode sequences. Initially, an average of 33293.5 ± 10552.0 raw reads were available per sample. After quality filtering, denoising, merging and removal of chimera, 14272.0 ± 4889.9 reads per sample were used for analysis; minimum read count and therefore rarefaction depth was 9710 reads. Resulting fastq files were used for bioinformatic preprocessing using QIIME2 tools which have been implemented on a local Galaxy instance (https://galaxy.medunigraz.at/). Amplicon sequencing variants (ASV) were identified using the dada2 inference algorithm, taxonomic assignment was done with a naïve Bayesian classifier trained on the SILVA database V132 with release at 99% identity. Cyanobacteria were regarded as possible contamination and therefore removed from the data set. For statistical analysis, count table, taxonomy and sample data were handed off to phyloseq. Alpha diversity was estimated from an even count table, rarefied to the minimum read count per sample, using the metrics observed OTUs, Shannon index (implemented in the phyloseq::estimate_richness() function) and evenness (calculated as Shannon-index/log(observed OTUs). The influence of DSS-induced colitis, ingestion of MNP over time was tested for their statistical significance using a mixed effect model (using the R package lme4). For beta-diversity analysis, ASV were agglomerated on genus level to avoid extremely sparse data sets, using the phyloseq::tax_glom() function. Bray-Curtis dissimilarity was used as foundation for the distance matrix, calculated with the phyloseq::ordinate() function and permutational multivariate analysis of variance using distance matrices was used to determine whether there was significant clustering among the test groups, using the vegan::adonis2() function, and principal coordinate analysis (PCoA) was used for low-dimensional visualization (phyloseq::plot_ordination()). Redundancy analysis (RDA) was performed on a Hellinger-transformed abundance table to determine influencing factors on the microbiome composition, using the vegan::rda() function. To test whether there were significant differences in the overall change of the microbiome, the pldist R package was used to determine the intra-individual change between timepoints. Bray-Curtis dissimilarities were calculated and PCoA/adonis as well as distance-based redundancy analysis (vegan::dbrda()) were performed to identify significant influences on the microbiome changes during the experiment. To describe changes in the microbiome in more detail, multivariate association analysis (MaAsLin2) was applied on microbiome changes over time as obtained with pldist-tools.

In addition to the above-mentioned R packages, the following packages were used: readxl, tidyverse, ggpubr, lmerTest, writexl, ggplotify, ggConvexHull, ggrepel, ggh4x.

MNP characterization and verification of gastrointestinal tissue accumulation

For this study, three different sizes of PS particles were used which were supposed to have different interaction and uptake properties according to their size (10.39 ± 0.13 µm spherical, aqueous suspension, 5% w/v, blue colored; 1.14 ± 0.03 µm spherical, aqueous suspension 2.5% w/v, ex/em = 530/607 nm; 0.293 ± 0.008 µm spherical, aqueous suspension 2.5% w/v, ex/em = 502/518 nm). Particles were thoroughly characterized by their chemical composition and fluorescence properties, surface texture and charge. The distinct Raman spectrum (Fig. 1A) of the employed pristine particles showed the highest characteristic peak at ~ 1001 cm^− 1) for PS that was used for specific scanning of the particle samples using SRS at 934.5 nm laser excitation. SRS images of 10.39 µm and 1.14 µm particles gave a clear PS specific signal and individual particles were clearly distinguishable (Fig. 1B). 0.29 µm nanoparticles tend to aggregate in hydrophilic solutions and, due to methodological limitations, single particles were not resolved. Particle size and surface morphology were further analyzed by SEM. As depicted in Fig. 1C, pristine particles were equally round shaped spheres of respective size and had a smooth surface. All PS particles (Fig. 1D) were either colored or fluorescently labelled. 10.39 µm particles were blue colored spheres, whereas the two smaller PS particles were fluorescently labelled. The nanometer particles (0.29 µm) had distinct signal in the green channel (ex/em 488/529–555 nm), while the small microplastic particles (1.14 µm) had signal in the orange/red channel (ex/em 488/> 560 nm) as well as some slight crosstalk into the green channel (not shown). All particles exhibited a negative ζ-potential in 1 mM KCl solution, whereas the fluorescently labelled particles showed a higher negatively charged surface than the 10.39 µm particles (Supplementary Table S1). For application in mouse experiments, a mixture of all three PS particle sizes was prepared to mimic a rather natural exposure with different sized particles in water. The daily gavage dose was extrapolated from estimates of human MNP exposure[34] and the three different sized PS particles were mixed in equal weight concentrations (0.3 mg/size/day, total dose 0.9 mg MNP mix/day). In order to prove the uptake of our experimental PS MNPs into the GI tract, we performed a pilot study, where healthy C57Bl/6J mice were gavaged with a single dose of the MNP mix. Si and co were collected after 2 and 4 h. Immunofluorescence microscopy revealed an uptake of both 1.14 µm and 0.29 µm PS particles already after 2 h into GI tissues (Fig. 1E). Although sparsely distributed, nanoplastic particles (0.29 µm) seemed to be more frequently taken up into the tissue than 1.14 µm particles. The bigger 10 µm particles were not detected within the tissue using regular brightfield microscopy. This aligns with TEM analysis of small intestine tissue and the observed appearance of PS particles at the brush border of enterocytes after two hours of gavage. The accretion of 1.14 and 0.29 µm PS predominantly takes place (Fig. 1F)

DSS + MNP model showed distinct signs of colitis

With the initial proof that MNP particles with sizes < 1.2 µm penetrate the GI tissue, we investigated their distribution throughout the body as a key factor of toxicokinetic. Given the growing number of studies describing inflammatory effects of MNP in tissue, we utilized a colitis mouse model (DSS-induced colitis) alongside a healthy control group to examine the distribution under both healthy and pathological conditions. In the diseased cohort, colitis was induced by application of 2.5% DSS in drinking water over five days, followed by an additional five days of recovery during which the mice continued to exhibit signs of colitis. Both healthy and colitis cohorts received oral gavage for ten days of either vehicle (drinking water as negative control) or a PS MNP mix (0.3 mg/size/day). The exact treatment scheme for these four groups is shown in Fig. 2A. Histo-morphological analysis revealed structural changes of colon tissue of mice in the control, MNP, DSS and DSS + MNP groups (Fig. 2B). A series of pathological changes occurred in the DSS and MNP + DSS groups compared with the control and MNP groups. In the colon mucosa of DSS and DSS + MNP treated mice, the number of goblet cells was decreased, the inflammatory cells including macrophages, lymphocytes, eosinophils, and occasional neutrophils infiltrated into the stroma (see arrows), and changes of crypt architecture were observed. These findings were more pronounced in the DSS + MNP mice, where infiltrating lymphocytes were also found in the mucosal epithelial cells. Furthermore, in DSS + MNP mice, the colon tissue presented with more focal erosions (indicated by E) in the mucosa, and submucosal edemas (indicated by eSM), primarily due to local inflammatory cell infiltrations. Accordingly, the combined colitis scores, assessed from tissue sections of the GI tracts (si + co) from DSS + MNP treated mice, were strongly elevated compared to DSS only treated mice (18.5 vs. 10.14) (Fig. 2C). The healthy control group (Ctrl) and the mice treated only with MNP showed no signs of colitis, severe tissue damage, or inflammation (Fig. 2C). A similar trend was observed in the individual parameters of the colitis score including inflammation, crypt damage, ulceration and affected area (Fig. 2D). For all four parameters, colitis mice treated with MNP showed an overall higher score, compared to the DSS only cohort. This suggests that while MNPs alone might not induce severe effects on the GI tract during short-term application (10 days), MNPs exacerbated histopathological signs of colitis in an inflammatory disease model. However, due to the small sample number (n = 7) and heterogeneity of the DSS model, differences were not statistically significant.

MNPs are distributed to blood, liver, kidney and brain

Toxicokinetics is facilitated by the uptake of MNPs in the blood stream followed by subsequent particle distribution throughout the body. Qualitative fluorescence evaluation of blood and tissue sections was performed to evaluate the uptake of MNPs across the intestinal lining into the blood and potential distribution across various organs. As described for the previous experiment, MNPs were found to be taken up into the colon tissue of the MNP treated mice (Fig. 3A), however, at much lower numbers compared to the previous experiment (compare Fig. 1E). As mice were sampled in this experiment 24 h after the last gavage (10 days), the lower amount observed within the tissue might be either due to the fact, that MNPs have naturally moved through the GI tract and were excreted via feces, or MNPs might have surpassed the intestinal barrier and were distributed throughout the body. No signs of MNP accumulations within the colon have been observed.

To prove the hypothesis of uptake of MNPs into the blood stream, smears of EDTA sampled blood were performed and evaluated under the microscope for the specific fluorescence signal of the 0.29 and 1.14 µm MNP particles. 0.29 µm NPs were observed in the blood smears in both groups treated with the MNP mix (Fig. 3B). While in the healthy mouse model only few NPs were observed in the blood samples, in the DSS-treated colitis mice exposed to MNPs exhibited strongly increased numbers of 0.29 µm NPs and 1.14 µm MPs in their blood samples (Fig. 3B). This suggests that more NPs and even larger-sized MP particles could potentially cross the compromised intestinal barrier in the colitis cohort and circulate in the blood stream.

As MNPs were observed in the blood, we analyzed also peripheral organs that can be reached by MNPs via the bloodstream. Figure 3C shows representative pictures from liver, kidney and brain tissues. Except for brain tissues, 0.29 µm NP particles were both observed in healthy and DSS-induced colitis mice. Furthermore, 0.29 µm NPs were also detected in the following organs investigated: heart, lung, spleen and testicles (not shown). Bigger 1.14 µm particles were not observed in peripheral organs, highlighting the invasiveness of the nanoparticle fraction.

MNP treatment promotes macrophage infiltration and pro-inflammatory phenotype

Based on the IHC results and the respective increase in the inflammatory parameter in the MNP and DSS treated cohort, we analyzed the colon of all four treatment groups for further inflammatory parameters, with a special focus on macrophages infiltration. The F4/80 + macrophages increased slightly in healthy and diseased models following administration of MNPs (Fig. 4A and 4B). Further analysis was conducted to evaluate the shift in macrophage polarization phenotype following exposure to MNPs in colon tissue. While anti-inflammatory Arg1 + cells decreased slightly in both MNPs challenged cohorts compared to their respective controls (Fig. 4C and 4D), pro-inflammatory iNOS + cells increased especially in the MNP-treated colitis mouse model (Fig. 4E and 4F). Overall, the numbers of pro- and anti-inflammatory macrophages were almost similar in Ctr and DSS groups, with a slightly overall increased numbers of Arg1 + cells in the latter. In both MNP-treated groups, there was a decrease in overall infiltration of anti-inflammatory Arg1 + cells, while the counter iNOS + cell phenotype increased.

When calculating the “pro/anti-inflammatory” (former “M1/M2” ratio) for each individual mouse (Fig. 4G), we observed that for the healthy and DSS-induced colitis control mice the ratio was rather balanced and close to 1, while for the DSS + MNP treated mice, the ratio was shifted toward the pro-inflammatory side (> 1), which was less pronounced in the healthy mouse model and stronger in the DSS-induced colitis model.

Further in vitro studies were conducted to assess the impact of MNPs on macrophage polarization in naïve human PBMCs. At an exposure concentration of 5 ng/µl, MNPs were taken up by the macrophages in a size-dependent way (Fig. 5A and 5B). Macrophages exhibited a pronounced preference for the 0.29 µm nanoparticles, with 99.88% of macrophages demonstrating uptake of these particles, while the 1.14 µm microparticles were only taken up by 83.97% of macrophages. Additionally, the expression levels of markers linked to both anti-inflammatory and pro-inflammatory states of macrophage activation were examined. The anti-inflammatory macrophage markers CD206 and PD-L1 were significantly downregulated following treatment with both particle sizes (Fig. 5C). Despite the varying size preferences for 0.29 µm nanoparticles, both MNP treatment groups showed a decrease in anti-inflammatory markers, with no significant differences observed in the downregulation between them. Conversely, the pro-inflammatory macrophage marker 4-1BBL showed significant upregulation compared to the control only when incubated with the 0.29 µm MNPs (Fig. 5D). CD86, an additional marker associated with pro-inflammatory macrophage activation, remained unchanged in response to MNPs (Fig. 5D). Taken together, these results can partially explain the tendency for M1 pro-inflammatory differentiation observed in vivo.

MNPs modulate the microbial communities in DSS-induced colitis model

Finally, the influence of MNPs ingestion on the gut microbiota in a healthy state and during colitis, stool microbiomes of the four treatment groups were profiled via 16S rDNA sequencing. In total, 5172 distinct ASV, 113 genera and 9 phyla were detected across all samples.

Analysis of the microbiome composition indicated that the microbial richness decreased significantly during DSS treatment (p < 0.001), while the ingestion of MNPs did not show a significant effect on this alteration (p = 0.583). Similar patterns were observed for Shannon index (DSS: p < 0.001; MNPs: p = 0.912), and Evenness (DSS: p < 0.001; MNPs: p = 0.950), see Fig. 6A. When analyzing the development of alpha diversity estimators in each group separately, microbial richness and Shannon index significantly decreased in both DSS-treated groups with and without MNPs, while evenness was significantly decreased in mice treated with DSS + MNP. Evenness decreased in the DSS-group without microplastic comparable to the DSS + MNP group, even though the decrease did not reach statistical significance (p = 0.056; Fig. 6A). Exploratory network analysis, redundancy analysis and principal coordinate analysis indicated that DSS treatment significantly altered the gut microbiome composition irrespective of the ingestion of MNPs (Fig. 6B-C, Supplementary Fig. 2). Next, we aimed to investigate which bacterial taxa were differentially represented in the four groups. The DSS-treatment (in the presence or absence of MNPs) led to an increase in the representatives of Bacteroides and Parabacteroides (Fig. 6D and 6E). For Bacteroides, also the presence of MNPs alone (DSS-untreated) led to a significant increase in this genus compared to untreated controls (Fig. 6D). Furthermore, also the abundance of Clostridium sensu stricto 1 and Turicibacter significantly increased in mice treated with DSS, however the effects appeared to be less pronounced for the cohort treated additionally with MNP (Fig. 6F-G). Notably, the Enterococcus and Escherichia-Shigella generally displayed significantly higher abundance in the DSS-treated mice in the presence of MNPs (Fig. 6H and I). While the abundance of Escherichia-Shigella was also significantly higher in the DSS treated group without MNP, the abundance was markedly higher in mice simultaneously treated with MNPs (Fig. 6I). However, for all of these 4 taxa (Clostridium sensu stricto 1, Turicibacter, Enterococcus and Escherichia-Shigella) the differences between DSS and DSS + MNP treated groups were not statistically significant. Of note, certain bacterial genera were below the level of detection in one or more groups of mice (Supplementary Table 2). For example, in the mouse group with induced colitis, the presence of MNPs reduced the levels of the representatives of Lachnospiraceae below detection, unlike the other three groups. On the other hand, the group treated only with MNPs had representatives of Odoribacter and the RC9 group below the limit of detection.

In recent years, inflammatory diseases of the GI tract have been on the rise.[15] As the GI tract belongs to the main organ group being exposed to increasing levels of MNPs exposure, we focused our study on the interconnection of colitis and MNPs toxicity for short- and medium-term exposure.

Investigation of the effects of PS-MNPs on healthy mice and DSS-induced colitis mouse model revealed that short-term exposure to MNPs showed a trend to higher colitis indicators. This exacerbation was noted across all evaluated colitis sub-parameters (inflammation, crypt damage, ulceration, and affected area), with DSS + MNP-treated mice displaying heightened severity compared to DSS-only counterparts. An exacerbated MNP-associated colitis in mice aligns with previously reported studies.[12–14] Notably, in healthy mice subjected to MNP treatment for ten days, we detected no histopathological alterations, suggesting MNPs alone do not induce overt tissue damage. However, an increased infiltration of macrophages into colon tissue was observed, indicating a profound chronic inflammatory response. This response was particularly pronounced for smaller nanoparticles (0.29 µm), the uptake of which was preferred by human PBMC-derived macrophages, leading to significant variations in macrophage activation markers. This size-dependent modulation of pro-inflammatory and anti-inflammatory markers, inversely correlated with particle size, and is consistent to Fuchs et al. [27] A rapid uptake of MNPs by gut tissues was observed already two hours after exposure to particles below the size of 1.2 µm. Long-term distribution of MNPs after ten days of treatment showed a different distribution of the MNPs particles within the MNP treated healthy mice compared to the colitis-model. Translocation into the blood stream of the MNPs in healthy mice was constrained to the nanoparticle fraction, whereas also the 1 µm MNPs were detected in blood in the colitis model. Additionally, MNPs were mainly found in the excretory organs, like kidney and liver, for the healthy model. On the contrast, due to the facilitated uptake under inflammatory conditions, MNPs were also observed in other peripheral organs, like the brain.

Hence, an existing colitis facilitates the uptake of MNPs into the blood and distribution in distant organs and underscores the potential of MNPs to aggravate inflammatory conditions, as evidenced by an increase in pro-inflammatory iNOS + and a decrease in anti-inflammatory Arg1 + macrophages in the DSS colitis model. Our data align with previously published results for similar experiments using 5 µm PS particles in larger mouse cohorts or longer MNP treatment regimen.[12, 13] For healthy mice treated with MNPs for 10 days, no histopathological changes were observed, when compared to H&E sections of the control group. However, when analyzing the number of macrophages present in colon tissue, we observed increased amounts in both healthy and DSS-colitis mice when treated with MNPs. This pro-inflammatory shift, reflected in the elevated M1/M2 ratio in MNP-treated mice, particularly under DSS-induced conditions in a size-dependent manner emphasizes the critical role of nanoparticle characteristics and the physiological state in determining their biological impact. Our findings necessitate a nuanced understanding of nanoparticle-macrophage interactions, underlining the importance of considering both nanoparticle properties and the host's physiological condition in evaluating the health implications of nanoparticle exposure, especially in inflammatory conditions with compromised barrier functions. The gut microbiome's response to MNP exposure, particularly in the context of DSS-induced colitis, revealed significant dysbiosis characterized by reduced evenness and shifts in specific bacterial genera, including Bacteroides, Parabacteroides, Clostridium, Turicibacter, Enterococcus, and Escherichia/Shigella. The functional changes in the distal colon caused by DSS treatment, where particularly more pronounced in the mucus-associated microbiota than in the microbiota present in the distal colon content, underscore the complexity of these interactions and the need for comprehensive analysis approaches.

In detail, there were two types of changes in the microbiota. The first type was induced only by DSS, and the microbial upshift was observed in the DSS-treated mice in the presence and absence of MNPs. The landmark of the inflamed gut was represented by the bloom of the members of Escherichia/Shigella, the increased levels of which have been implicated in a pro-inflammatory immune response.[25] The effect was more evident when the mice were treated with DSS in the presence of MNPs. The increase in Bacteroides, Parabacteroides and Clostridium, core components of the gut microbiota, might indicate a compensatory mechanism, i.e., an adaptive response, to the altered environmental conditions caused by these pollutants. In the animal intestine, most members of the Clostridium group, one of the richest gut bacterial lineages, are commensals, which positively affect their host.[35] An increase in Parabacteroides has been shown to exert an anti-inflammatory effect on their host, while the over-abundance of Bacteroides may also be linked to the degradation of mucus released during the DSS treatment and can potentially serve as a reservoir for extraintestinal infections.[36–38] It is worth mentioning that we detected a decrease in Bacteroides when the mice were exposed only to MNPs, which was previously associated with gastroenterological pathologies due to either inflammation or infection.[37–39]

The second type of changes was observed only in the group of DSS-treated mice in the presence of MNPs and is exemplified by the Gram-positive bacteria Turicibacter and Enterococcus. Normally, the members of Turicibacter are low abundant, and they have been demonstrated to have a protective effect against infections, e.g., with Citrobacter rodentium and to be one of the main regulators of the bile acid metabolism and 5-hydroxytryptamine production.[40–42] Interestingly, one of the few studies showing significantly endogenously elevated levels of these bacteria is linked to CD8 + T-cell deficiency [43], suggesting that the MNPs together with the DSS might negatively impact on cytotoxic T-cells. The members of the genus Enterococcus, also found to be significantly increased in the DSS-treated mice in the presence of MNPs, are notoriously known for their multidrug resistance and ability to cause extraintestinal infections.[44] Moreover, some representatives of this genus are implicated in inflammatory processes, e.g., colitis in immunocompromised hosts, such as Il10^−/− mice.[45]

The 'diversity begets diversity' (DBD) hypothesis, as explored by Calcogno et al.[46] and Schluter et al.[47], proposes that higher levels of community diversity can increase the rate of speciation or diversification. This is particularly relevant in our study, where the introduction of MNPs could disrupt these ecological interactions, potentially altering the course of microbial evolution and diversification within the gut. The contrasting 'ecological controls' (EC) hypothesis posits that competition for limited niches at high levels of community diversity results in a negative effect on further diversification, a concept supported by metabolic models[48] and empirical data from the Earth Microbiome Project.[49] Our findings, indicating a reduction in microbial diversity due to MNP exposure, could be interpreted through the lens of these hypotheses. The presence of MNPs may create new selective pressure and niches, potentially leading to eco-evolutionary feedback that are yet to be fully understood. This is particularly relevant considering the stronger support for DBD in animal guts compared to more diverse microbiomes like soils and sediments.[49] The fine-scale strain-level variation within microbial communities, as discussed by Goyal et al.[50] and Martiny et al.[51], highlights the complexity of these interactions and the potential for microplastics to influence microbial evolution in ways that are not immediately apparent.

The implications of our study also resonate with the objectives of global health policies aimed at mitigating environmental pollution. Initiatives by the United Nations and the European Union to reduce plastic pollution align with our findings, emphasizing the need for stringent regulations to reduce MNP exposure. Enhancing these policies with our research findings could lead to more effective strategies for protecting public health against the backdrop of increasing plastic pollution.

Our findings contribute to the expanding body of knowledge regarding the impact of PS MNPs on macrophage polarization and gut microbiome diversity in the context of GI inflammatory processes. Our results underscore that MNPs not only exacerbate existing colitis but also lead to increased MNP biodistribution, reduced microbial evenness, and downregulation of anti-inflammatory macrophage markers. The observed decrease in microbial diversity by PS MNPs particles in the DSS mouse model highlight the necessity for further research to comprehensively grasp the effects of MNPs on gut health and disease. This study elucidates the intricate interplay between MNP exposure, GI inflammatory diseases, microbial interactions, and the potential for MNPs to impact microbial evolution and gut metabolism in ways that may not be immediately apparent.

Ethics approval and consent to participate

All animal experiments were conducted according to Austrian animal welfare legislation, and experimental setups were approved by the local animal ethics committee. (license 2022- 0.257.045)

Consent for publication

Not applicable

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

The work was mainly supported from MicroONE, a COMET Modul under the lead of CBmed GmbH, which is funded by the federal ministries BMK and BMDW, the provinces of Styria and Vienna, and managed by the Austrian Research Promotion Agency (FFG) within the COMET—Competence Centers for Excellent Technologies—program. Financial and scientific support was also received from the Austrian Federal Ministry of Science, Research and Economy, the National Foundation for Research, Technology and Development, and the Christian Doppler Research Association, as well as Siemens Healthineers. L.K. was also supported by a European Union Horizon 2020 Marie Sklodowska-Curie Doctoral Network grants (ALKATRAS, n. 675712; FANTOM, n. P101072735 and eRaDicate, n. 101119427) as well as BM Fonds (n. 15142), the Margaretha Hehberger Stiftung (n. 15142), the Christian-Doppler Lab for Applied Metabolomics (CDL-AM), and the Austrian Science Fund (grants FWF: P26011, P29251, P 34781 as well as the International PhD Program in Translational Oncology IPPTO 59.doc.funds). Additionally, this research was funded by the Vienna Science and Technology Fund (WWTF), grant number LS19-018, and L.K. and G.E. are members of the European Research Initiative for ALK-Related Malignancies (www.erialcl.net). G.E. was supported by the Austrian Science Foundation FWF (SFB F83), the City of Vienna Fund for Innovative Interdisciplinary Cancer Research (P 21118), and The Austrian Research Promotion Agency - FFG (P 879481). S.C. was supported by the European Union’s H2020 research and innovation program under the Marie Sklodowska-Curie grant agreement AIMed, n. 861138. G.S. and S.C. acknowledge the financial support from the European Union within the research projects 4D + nanoSCOPE, n. 810316, LRI n. C10, STOP n. 101057961, and by the “Freistaat Bayern” and European Union within the project Analytiktechnikum für Gesundheits- und Umweltforschung AGEUM, StMWi-43-6623-22/1/3. The financial support for O.H. by the National Research, Development and Innovation Office through the project OTKA-FK 138823 is gratefully acknowledged. Furthermore, O.H. is grateful for the support from the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, and the ÚNKP-22-5 and ÚNKP-23-5 New National Excellence Program from the National Research, Development and Innovation Fund.

Authors’ contribution

(first author) Verena Kopatz Investigation, formal analysis, data curation, visualization, writing – original draft

Kristina Draganic Investigation, writing original draft

Angela Horvath Formal analysis, visualization, writing – original draft

Janette Pfneissl Investigation

Julijan Kabiljo Investigation

Bernadette Mödl Methodology

Gerald Timelthaler Formal analysis, software

Julia Wallner Investigation

Zeynab Mirzaei Methodology, investigation

Saule Beratlyte Formal analysis

Michaela Schlederer Investigation

Oldamur Holloczki Validation, writing – review & editing

Martin Raigel Methodology

Joachim Widder Resources, writing-review and editing

Ulrike Resch writing – review & editing

Iris Kufferath Investigation

Wolfgang Wadsak writing – review & editing, resources

George Sarau Methodology, Investigation, writing-review&editing

Silke Christiansen Methodology, resources

Nikola Zlatkov Kolev Investigation

Robert Eferl Methodology

Gerda Egger Resources, Supervision, writing-review and editing

Vanessa Stadlbauer-Köllner Formal analysis, Resources, writing – review&editing

(corresponding) Verena Pichler conceptualization, data curation, supervision, writing – original draft, writing – review&editing

(senior, corresponding) Lukas Kenner Conceptualization, Resources, Formal analysis

Acknowledgements

C. Bapp and L. Kogler for DLS and z-potential measurements, as well as C. Rademacher for the access to the Zetasizer Pro.

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Polystyrene micro- and nanoplastics aggravates colitis in a mouse model – effects on biodistribution, macrophage polarization, and gut microbiome

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Version 1

Abstract

Background

Results

Conclusions

Figures

INTRODUCTION

MATERIAL AND METHODS

Polystyrene particles and characterization

Microscopy and spectroscopy

Mouse model

Histology

Isolation of monocytes from peripheral blood mononuclear cells (PBMCs) of healthy donors

Confocal microscopy of macrophages

In vitro analysis and flow cytometry

Microbiome analysis

RESULTS

MNP characterization and verification of gastrointestinal tissue accumulation

DSS + MNP model showed distinct signs of colitis

MNPs are distributed to blood, liver, kidney and brain

MNP treatment promotes macrophage infiltration and pro-inflammatory phenotype

MNPs modulate the microbial communities in DSS-induced colitis model

DISCUSSION

CONCLUSION AND FUTURE PROSPECTS

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1