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Article

Size-Dependent Disruption of Lipid Metabolism by Polystyrene Micro- and Nanoplastics in Caenorhabditis elegans Revealed Through Multi-Omics and Functional Genetic Validation

by
Zhi Qu
1,2,†,
Xihua Feng
1,†,
Yalu Wang
2,
Rui Wang
2 and
Nan Liu
1,2,3,*
1
Institute of Environment and Health, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, China
2
School of Nursing and Health, Henan University, Kaifeng 475004, China
3
College of Public Health, Zhengzhou University, Zhengzhou 540001, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Toxics 2026, 14(2), 170; https://doi.org/10.3390/toxics14020170
Submission received: 9 January 2026 / Revised: 7 February 2026 / Accepted: 9 February 2026 / Published: 13 February 2026
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Abstract

Microplastics (MPs) are pervasive contaminants that enter the food chain and cause health issues. However, the size-dependent effects of MPs on lipid metabolism remain inadequately characterized. Using Caenorhabditis elegans (C. elegans), we investigated the size-dependent toxicity of polystyrene (PS)-MPs as model contaminants with sizes of 100 nm and 1 μm, respectively. We evaluated multiple phenotypic endpoints, including lifespan, growth (body length and width), locomotion (head thrashes and body bends), reproduction, and intestinal lipofuscin. The expression of representative lipid metabolism-related transcripts was validated by quantitative PCR. Untargeted metabolomics profiling detected 831 differential metabolites (451down-regulated and 380 up-regulated) across both PS particle exposure groups, with over-representation of lipid metabolic pathways. Integration of multi-omics (transcriptomics and metabolomics) highlighted acdh-1, ech-6, hach-1, and sur-5 as core lipid-metabolism genes; RNA interference confirmed that knockdown of these target genes abolished the size-dependent differences in fat accumulation induced by MPs. Notably, it revealed elevated linoleic acid and taurocholic acid, signature metabolites indicative of disrupted lipid turnover by our metabolomic profiling. Collectively, our findings demonstrate that exposure to PS-MPs disrupts lipid homeostasis in C. elegans by perturbing mitochondrial function and key metabolic pathways, which in turn impairs growth, development, feeding, and reproductive capacity. Critically, these disruptive effects exhibit a strong size dependency, with 100 nm PS particles inducing more severe perturbations than the 1 μm particles, and provide novel mechanistic insight into MP-induced metabolic abnormalities, underscoring the importance of considering particle size in assessing the environmental and health risks of MP contamination.

Graphical Abstract

1. Introduction

Global plastic production and use have escalated over recent decades owing to low cost, versatility, and durability, resulting in ubiquitous environmental contamination. Common polymers such as polyethylene (PE), polypropylene (PP), polystyrene (PS), polyvinyl chloride (PVC), and polyethylene terephthalate (PET) are particularly pervasive [1]. These plastics can degrade into minute fragments with a size of less than 5 mm, which are defined as microplastics (MPs) [2], over time due to physicochemical factors such as erosion, corrosion, and light exposure. Smaller particles in the sub-micrometer range are often designated nanoplastics (NPs) [3]. Micro- and nanoplastics (MNPs) have been detected across environmental media and consumer products, raising concern about chronic human exposure [4]. Entry routes include ingestion, inhalation, dermal contact [5], etc. Consistent with these pathways, plastic particles have been reported in human feces, blood, thrombi, placenta, lung tissue, breast milk, and sperm [6], underscoring their potential for systemic distribution [7,8,9,10] and highlighting the potential for widespread internal distribution. Beyond the intrinsic toxicity of polymer particles themselves, the composite nature of MNPs further amplifies their biological hazards and damage effects. It was reported that diethylhexyl phthalates and bisphenols are widely used as plasticizers and monomers, and are well-documented endocrine-disrupting chemicals that interfere with hormone signaling pathways, leading to reproductive dysfunction, developmental abnormalities, and metabolic disorders [11,12]. Additionally, MNPs can adsorb toxic heavy metals including lead, cadmium, and arsenic, and persistent organic pollutants from the environment, which bioaccumulate in organisms and induce oxidative stress, DNA damage, and neurotoxicity [13,14]. The biological effects of MNPs appear multifaceted, encompassing oxidative stress, inflammatory responses, reproductive toxicity, cytotoxicity, and metabolic disruptions [15].
Toxicity is modulated by particle concentration, chemical composition, and exposure duration [16] and critically by particle size. However, there are differences in the biological effects attributable to the size of MNPs. While smaller particles are generally thought to penetrate tissues more readily and bioaccumulate, producing greater toxicity, some studies have reported stronger metabolic effects for larger particles, indicating that size–toxicity relationships are not uniform across contexts [17]. Clarifying size-dependent metabolic effects is therefore a priority for risk assessment. Here, C. elegans was selected as the animal model for this investigation due to its well-established relevance to both environmental risk assessment and human health, coupled with its unique advantages for mechanistic studies of metabolic disruption.
Lipid metabolism is uniquely dynamic, functioning as a central hub for energy storage, membrane integrity, cell signaling, and adaptive responses to physiological and environmental fluctuations. This finely tuned system is highly sensitive to perturbation by exogenous stressors. Environmental contaminants—particularly those with high persistence and bioavailability—can perturb lipid metabolic pathways through diverse mechanisms [18], including direct incorporation into lipid bilayers, modulation of lipid-synthesizing and -catabolizing enzymes, induction of oxidative stress, impairment of mitochondrial fatty acid β-oxidation, and disruption of transcriptional and epigenetic regulators of lipid homeostasis. Persistent dysregulation of these pathways can precipitate pathological lipid accumulation, generation of lipotoxic intermediates, and compromised cellular architecture, ultimately impairing organismal health and survival. Importantly, the lipid metabolic pathways of C. elegans are evolutionarily conserved with mammals, including humans, with over 60% of its genes having human homologs—particularly those regulating lipid synthesis, degradation, and homeostasis, which are the core focus of this study. Its fat reserves are dynamically controlled by mitochondrial β-oxidation, peroxisomal ω-oxidation, and nuclear-hormone-receptor-mediated transcriptional circuits [19], processes that are evolutionarily conserved and respond rapidly to environmental insults. Additionally, C. elegans exhibits a short life cycle, high fecundity, and ease of laboratory cultivation, facilitating high-throughput phenotypic assessments and functional genetic manipulations (e.g., RNA interference, RNAi).
Owing to the small size, hydrophobic surface, and high surface-area-to-volume ratio of MNPs, these particles can translocate across epithelial barriers, accumulate in tissues, and interact with cellular organelles [20,21]. Experimental evidence across multiple taxa demonstrates that exposure to MNPs can trigger oxidative and endoplasmic reticulum stress, mitochondrial injury, alterations in membrane composition, and dysregulation of immune, endocrine, and metabolic signaling [11,12,14]. Importantly, lipid metabolism has been increasingly recognized as a sensitive target of MNP toxicity [22]. Observations in mammalian models, aquatic vertebrates, and invertebrates reveal MNP-induced alterations in lipid droplet morphology, shifts in fatty acid oxidation and synthesis, changes in phospholipid composition, and dysregulation of lipid-related transcription factors—processes that frequently converge with oxidative and inflammatory pathways to exacerbate cellular dysfunction [23].
Recent investigations have provided compelling evidence that MNPs are readily bioavailable to C. elegans, where they accumulate within the intestinal lumen, consequently impairing pharyngeal pumping and feeding efficiency [24,25], reducing reproductive output [26], and disrupting neuromuscular coordination [25]. These characteristics collectively render C. elegans an ideal model to elucidate the toxic effects of MNPs on lipid metabolism, with findings that can inform both environmental risk evaluations and our understanding of potential human metabolic perturbations.
Current studies on the toxic effects on C. elegans largely focus on the concentration-based impact of MPs, with limited research on the size-dependent toxic effects and underlying metabolic mechanisms. While preliminary evidence suggests that MNPs can alter lipid storage patterns in C. elegans, the molecular cascades and regulatory nodes underlying these disturbances remain insufficiently defined. However, whether these metabolic anomalies are governed by particle size remains contentious. It is hypothesized that smaller MPs lead to greater membrane disruption and mitochondrial impairment, yet comparative analyses controlling for surface chemistry and exposure regimen are lacking. Crucially, no study has integrated organismal energy metrics with transcript-level regulation and metabolite fingerprints to dissect size-dependent mechanisms of lipid dysregulation. Closing this knowledge gap is prerequisite for accurate hazard ranking of plastic debris and for identifying conserved molecular initiating events that may translate to higher organisms. Addressing this gap is essential for elucidating how environmental MNP exposure perturbs conserved metabolic systems, with implications extending from ecosystem health to human disease risk.
Accumulation of MNPs in the intestinal lumen of C. elegans simultaneously compromises energy acquisition and perturbs systemic redox balance. We therefore quantified lifespan, body size, reproductive output and age-pigment accumulation as integrative indicators of energy allocation and somatic maintenance—traits that are transcriptionally governed by insulin/IGF-1, nuclear-hormone-receptor and mitochondrial signaling networks [27]. Locomotor metrics (head thrash and body bend frequencies) were included because neuromuscular performance is metabolically expensive and declines when β-oxidation is impaired. These phenotypic anchors were prerequisite for the multi-omics design: transcriptomic interrogation was expected to reveal dose- and size-dependent re-programming of mitochondrial fatty-acid β-oxidation genes (e.g., acdh-1 and ech-6), while untargeted metabolomics was anticipated to detect downstream shifts in acyl-carnitines, linoleate and bile-acid conjugates that directly reflect the measured lipid accumulation and reproductive deficit. Thus, the selected endpoints are not merely descriptive; they constitute the phenotypic scaffold that enables mechanistic linkage between particle-size-dependent bioenergetic disruption and its molecular underpinnings.
Given the established role of RNAi in dissecting C. elegans gene function, and the uncharacterized mechanisms linking MNP exposure to lipid dysregulation [28], the present study aimed to clarify the size-dependent effects of difference sizes of PS-MNPs (100 nm vs. 1 μm) on lipid metabolism in C. elegans. The multi-omics analysis set can provide essential clues regarding the abnormal manifestations of lipid metabolism disorders, especially the differences in mechanisms between transcriptomics and metabolomics. This work not only provides novel mechanistic insights into MNP-induced metabolic abnormalities but also underscores the importance of considering particle size when assessing the environmental and health risks associated with MNP contamination.

2. Material and Methods

2.1. Chemicals and Materials

PS microbeads with sizes of 100 nm and 1 μm (referred to as 100-PS and 1000-PS) were purchased from Janus New Materials (Nanjing, China). Particle morphology was examined using scanning electron microscopy (Thermo-Fisher Scientific, Waltham, MA, USA). Hydrodynamic diameters were measured by dynamic light scattering (DLS) with a Zetasizer Nano (Laser particle size and Zeta potential analyzer, Nano ZS-90, Malvern Instruments, Malvern, UK). Polymeric composition was analyzed using Fourier-transform infrared spectroscopy (FTIR, FTIR-650S, Tianjin Gangdong Technology Co., Ltd., Tianjin, China), recording spectra of 400–4000 cm−1 at 4 cm−1 resolution over 32 scans. Prior to characterization, particles were dispersed in K-medium (32 mM KCl, 51 mM NaCl) via probe sonication.

2.2. C. elegans Strains and Exposure Protocols

Wild-type strain C. elegans (N2) specimens were obtained from the Caenorhabditis Genetics Center (University of Minnesota, Minneapolis, MN, USA). Worms were maintained on nematode growth medium (NGM) agar plates seeded with Escherichia coli (E. coli) OP50 under standard culture conditions [29]. For RNAi assays, E. coli HT115 clones were obtained from the Dharmacon C. elegans RNAi feeding library [30]. Synchronized worms were obtained by bleaching gravid adults with alkaline hypochlorite solution (5% NaOCl: 1 N NaOH = 2:5, v/v). L1 larvae were exposed to 100-PS or 1000-PS suspensions at final concentrations of 1, 10, or 100 μg/L in K-medium. Exposures were performed for 5 days in two independent parallel experiments [31]. Post-exposure, worms were washed three times with K-buffer prior to subsequent assays.

2.3. Physiological Endpoints and Lipofuscin Accumulation

Physiological endpoints were assessed as previously described [18,32,33], including lifespan, head thrashes and body bends, body length and width, and brood size, pharyngeal pumping, and intestinal autofluorescent lipofuscin accumulation. Synchronized L1 larvae of C. elegans were exposed to PS-MPs as above. After 5 days of exposure, worms were transferred to fresh NGM plates (day 0). Survival was scored daily until all individuals had died. Head thrashes were counted for 30 s following a 1 min recovery from transfer. Body bends were quantified as complete sinusoidal movements over a 30 s period. Body length and width were imaged under an inverted fluorescent microscope (ECLIPSE Ti2-U, Nikon, Tokyo, Japan) and subsequently quantified with ImageJ 1.53t (National Institutes of Health, Bethesda, MD, USA). Brood size was determined as the total number of offspring produced per worm. Pumping rate was quantified under a stereomicroscope (S9i; Leica Microsystems, Wetzlar, Germany). Worms were immobilized on glass slides with 30 µL of 5 mM levamisole hydrochloride, covered with a coverslip, and imaged using the inverted fluorescence microscope noted above. The red channel was isolated in ImageJ, and red fluorescence intensity was quantified to assess accumulation of the autofluorescent age pigment, i.e., lipofuscin [18,34].

2.4. Whole Transcriptome Sequencing

Whole-transcriptome profiling was performed on worms exposed to 100 nm and 1 μm PS-MPs for 5 days. Worms were washed three times in M9 buffer; progeny were removed by gravity settling and decanting. RNA was extracted [18], and quality was assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) and quantified using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Library preparation and sequencing were performed by Biomarker Technologies Co., Ltd. (Shanghai, China) on an Illumina NovaSeq 6000 using the S4 300-cycle kit, generating 150 bp paired-end reads. Sequencing libraries of various samples were denatured to ssDNA using 0.1 M NaOH, diluted to 8 pM. Quality control was conducted using FastQC (v0.11.7). Adapter-trimmed reads were aligned to the C. elegans reference genome (WBcel235) with HISAT2 (v2.1.0). Transcript abundance was estimated with StringTie (v1.3.3). Circular RNAs were quantified with CIRCexplorer2 (v2.3.2). Differential expression analyses were conducted in R (v3.5.0) with edgeR, and differentially expressed mRNAs (DE-mRNAs) were defined as those with |log2 fold change| > 0.358 and p < 0.05 [35].

2.5. KEGG Pathway Enrichment Analysis

KEGG pathway enrichment analysis was conducted by mapping DEGs to the KEGG database, with significance determined using Fisher’s exact test (p < 0.05). Enrichment strength was quantified by the enrichment score [−log10(p value)] and gene ratio (DEGs in pathway/total DEGs). Results were visualized using bar plots (top 10 pathways by enrichment score), dot plots (top 10 pathways by enrichment score or gene ratio), and pathway maps (red = upregulated genes, green = downregulated genes, white = no significance).

2.6. Volcano Plots

Volcano plots were created to visualize differential gene expression between the 100 nm and 1000 nm PS-MP groups. The x-axis shows the log2(Fold Change) (expression change magnitude), and the y-axis shows −log10(p value) (significance). Genes were classified as significantly upregulated (red dots), downregulated (green dots), or non-significant (gray dots) using thresholds of |log2(Fold Change)| ≥ 1 and p < 0.05. Plots were generated using the ggplot2 package in R software.

2.7. GO Enrichment Analysis

GO enrichment analysis was performed using the topGO package (Bioconductor). Fisher’s exact test was used to identify significantly enriched GO terms (p ≤ 0.05) among differentially expressed genes, with false discovery rate (FDR) adjusted by the Benjamini–Hochberg method. GO terms were categorized into three domains: Biological Process, Cellular Component, and Molecular Function.

2.8. Metabolomics Analysis

For metabolomic profiling, C. elegans exposed to 100 nm PS (NPS) and 1 μm PS (MPS), the MP-exposed groups, were selected for comparative analysis. Following a 5 day exposure, nematodes were harvested and washed three times with M9 buffer, and allowed to sediment by gravity. The supernatant was discarded, and the resulting pellet was stored at −80 °C for subsequent analysis. Approximately 50 mg worm biomass was extracted in 500 µL pre-cooled 80% methanol with stainless-steel beads, homogenized, incubated at −20 °C for 30 min, and centrifuged (20,000× g, 15 min, 4 °C). Supernatants were lyophilized and reconstituted in 100 µL 50% cold methanol for analysis. Quality control (QC) samples were generated by pooling equal volumes from each sample. Metabolic profiling was performed using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) on a Vanquish Flex UHPLC system (Thermo-Fisher Scientific, USA) equipped with an ACQUITY UPLC HSS T3 column (100 Å, 1.8 µm, 2.1 × 100 mm; Waters, Milford, MA, USA). Details of DNA extraction, Illumina MiSeq sequencing, and amplicon sequence processing are provided in Text S1.
Metabolites were identified by matching mass-to-charge ratio (m/z) values to reference spectral databases. Quantification was performed using the area under the primary chromatographic peak. Significant metabolic differences were defined as fold change (FC) > 1.5 or <0.67, with p < 0.05. Data structure and sample separation were evaluated using principal component analysis (PCA) and hierarchical clustering.
Internal standards application: To ensure data quality, correct for instrument variability, and enable semi-quantitative analysis, a mixture of internal standards was added to each biological sample prior to the extraction step.
Types of standards used: The mixture included both stable isotope-labeled internal standards and chemical analogs not endogenous to C. elegans.

2.9. Quantitative PCR (qPCR)

Total RNA was extracted from C. elegans using a commercial RNA kit (Vazyme International LLC., Nanjing, China), and complementary DNA (cDNA) was synthesized via reverse transcription using the HiScript III RT SuperMix (Vazyme International LLC., China). The resulting cDNA was diluted 20-fold and used as a template for qPCR conducted with the AceQ Universal SYBR qPCR Master Mix (Vazyme International LLC., China). Gene-specific primers were designed based on sequences obtained from the NCBI sequences listed in Table 1. Relative gene expression levels were quantified using the 2−ΔΔCT method [36], with normalization to the housekeeping gene act-1.

2.10. Fat Accumulation Testing by Oil Red O Staining

To assess fat accumulation, Oil Red O staining was utilized, adapted from a previously published protocol [37]. Synchronized L1 larvae were exposed to MNPs for 5 days, washed in M9 buffer, fixed in 40% isopropanol for 3 min [38], stained with Oil Red O solution (Beyotime Biotech., Shanghai, China) for 2 h under gentle agitation, and washed. Worms were imaged under a Leica S9i stereomicroscope (55× magnification). Images were converted to grayscale in ImageJ, and lipid levels were quantified as mean optical density.

2.11. Rhodamine 6G (R6G) Staining

Synchronized L1 worms were exposed to the PS-MP suspensions for 5 days [39], then incubated on an NGM plate containing R6G for 4 h to facilitate dye uptake. After staining, nematodes were mounted on agar pads, immobilized with 5 mM levamisole hydrochloride [18], and imaged. Consistent fluorescence thresholds were applied in ImageJ to quantify mean gray intensity [40].

2.12. RNAi-Mediated Gene Knockdown

To assess the functional roles of transcripts dysregulated by PS-MP exposure, RNAi experiments were conducted following our established protocols [29]. Briefly, dsRNA constructs targeting acdh-1 (C55B7.4), ech-6 (T05G5.6), hach-1 (F09F7.4), and sur-5 (K03A1.5) were obtained from the C. elegans RNAi feeding library (E. coli HT115 strains) and included the following gene targets: acdh-1 (C55B7.4), ech-6 (T05G5.6), hach-1 (F09F7.4), and sur-5 (K03A1.5). Bacterial cultures were grown in LB medium containing 100 mg/L ampicillin overnight at 37 °C, and dsRNA expression was induced with 1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG, Sigma-Alderich Co., Ltd., Shanghai, China) for 4 h prior to seeding onto RNAi agar plates (containing ampicillin and IPTG). Gravid adult nematodes were transferred to RNAi-seeded plates for egg laying to obtain synchronized progeny, which were subsequently subjected to PS-MPs.

2.13. Statistical Analysis

All data were initially assessed for normality and homogeneity of variance. For comparisons among multiple groups, one-way analysis of variance (ANOVA) was used for normally distributed data with equal variances, whereas the Kruskal–Wallis test was applied for non-normally distributed data. For comparisons between two groups, the Student’s t-test was employed for normally distributed data, and the Mann–Whitney U test was used for data that did not meet normality assumptions. Survival analyses were performed using the Kaplan–Meier method, and differences between survival curves were assessed with the log-rank test. All statistical analyses and data visualizations in this study were conducted in R software (version 4.3.1). A two-sided p value of <0.05 was considered statistically significant.

3. Results

3.1. Characterization of PS-MPs

As shown in Figure 1A,B, scanning electron microscopy images revealed the uniformly spherical morphology of the PS-MP particles. Dynamic light scattering (DLS) analysis using a Nano Zetasizer further confirmed a particle size of 1004.0 ± 42.6 nm for the 1 μm PS-MPs and 110.1 ± 2.8 nm for the 100 nm PS-MPs, respectively (Figure 1C,D). The FTIR spectroscopy validated the chemical identity of PS (Figure 1E,F), with characteristic absorption peaks observed at approximately 3025 cm−1, 1600 cm−1, 755 cm−1, and 698 cm−1, which correspond to the aromatic C-H, C=C, and strong C-H bending vibrations.

3.2. Physiological Effects and Lipofuscin Accumulation of PS-MPs Exposure in C. elegans

Exposure to PS-MPs induced a dose-dependent decrease in the lifespan of C. elegans. Notably, both the 100 nm and 1 μm PS-MPs significantly reduced lifespan, by 5.57% and 8.71%, respectively, compared to the control group, though no significant difference was observed between the two particle sizes (Figure 2A). After 5 days of exposure, both body length and width of C. elegans were significantly reduced relative to controls. The inhibitory effect was more pronounced in the 1 μm PS-MPs group compared to the 100 nm group (Figure 2B,C). Similarly, locomotor behavior was impaired following exposure, as evidenced by a decrease in frequencies of both head swing and body bending in the PS-MP groups, although no significant difference was observed between the two exposure groups (Figure 2D,E). These results suggested that PS-MP exposure, regardless of particle size, adversely affects neuromuscular function in C. elegans. In addition, we found that reproductive output was also affected. Following 2 days of exposure, brood size was significantly reduced in both groups compared to controls, with a more severe impairment observed in worms exposed to 1 μm PS-MPs (Figure 2F). Moreover, PS-MP exposure led to a significant increase in intestinal lipofuscin accumulation, which is a biomarker associated with aging and oxidative stress in C. elegans, in both the 100 nm and 1 μm groups compared with control (Figure 2G).

3.3. Transcriptomic Alterations Induced by PS-MP Exposure

Comparative transcriptomic profiling revealed that, relative to the 1 μm PS-MP group, exposure to 100 nm PS-MP yielded 473 DE-mRNAs, comprising 39 upregulated and 434 downregulated transcripts (Figure 3A). KEGG enrichment of the downregulated set identified eight significantly overrepresented pathways, predominantly metabolic, including general metabolic pathways, β-alanine metabolism, valine, leucine, isoleucine degradation, and pyrimidine metabolism, among others (Figure 3B).
Gene Ontology (GO) enrichment of the downregulated genes across three functional domains: Molecular Function (MF), Biological Process (BP), and Cellular Component (CC) highlighted terms ranked by significance (top 10 per category shown in Figure 3C). The GO profile indicated perturbations in stress-response programs and mitochondrial functions in C. elegans, suggesting that particle size modulates the toxicological response. Consistently, STRING-based functional association networks of DE-mRNAs further demonstrated prominent modules related to lipid metabolism, stress response, and mitochondrial transport (Figure 3D–F). These findings highlight a size-dependent transcriptomic response of C. elegans to PS-MP exposure that converges on key pathways involved in energy metabolism and cellular homeostasis.

3.4. Metabolic Profiles of C. elegans Following PS-MP Exposure

Figure 4 presents comprehensive bioinformatic analyses of the metabolomic profiles in C. elegans following exposure to PS-MNPs with distinct particle sizes (100 nm and 1 μm), aiming to dissect the size-dependent metabolic perturbations induced by PS particles. The systematic analyses, including principal component analysis, hierarchical clustering of differential metabolites, volcano plot visualization, and KEGG pathway enrichment analysis, collectively unraveled the size-specific disruption of metabolic homeostasis in the nematodes, with a particular focus on lipid metabolism-related processes.
PCA was performed to evaluate the overall variability of metabolomic profiles across all experimental samples. It revealed the distinct metabolic profiles of C. elegans exposed to 100 nm and 1 μm PS-MNPs, with a clear separation between the two exposure groups (Figure 4A). This distinct clustering pattern indicates that PS particles of different sizes exert divergent effects on the global metabolic networks of C. elegans, thus constituting foundational evidence for size-dependent metabolic perturbation. Hierarchical clustering analysis of metabolites (Figure 4B) further delineated the differential expression patterns of metabolic intermediates between the two exposure groups. Quantitative analysis revealed that a total of 14 metabolites exhibited significant dysregulation in the 100 nm group compared with the 1 μm group. A heatmap visualization of these differentially regulated metabolites highlighted divergent trends in metabolic regulation between the two groups (Figure 4C). Certain metabolites, including 3-methyl-2-oxovaleric acid, heptadecasphinganine, alanyl-phenylalanine, and uracil, displayed prominent upregulation or downregulation in a size-specific manner. Notably, lipid-related metabolites such as oleic acid, 1-palmitoyl-2-linoleoyl-sn-glycero-3-phosphocholine, and C17 sphingosine were among the differentially regulated molecules, implying that lipid metabolism might be a core target of size-dependent PS particle toxicity.
To elucidate the biological significance of the differentially expressed metabolites, KEGG pathway enrichment analysis was conducted. The results uncovered multiple differentially expressed metabolites and identified several metabolic pathways that were significantly enriched (p < 0.05), including pyrimidine metabolism, β-alanine metabolism, linoleic acid metabolism, fatty acid biosynthesis, unsaturated fatty acid biosynthesis, and pantothenate and CoA biosynthesis (Figure 4D). Among these enriched pathways, linoleic acid metabolism, fatty acid biosynthesis, and biosynthesis of unsaturated fatty acids are key branches of lipid metabolism, which is consistent with the differential regulation of lipid-related metabolites observed in the present study. Additionally, pantothenate and CoA biosynthesis provides essential cofactors for fatty acid synthesis and oxidation. These results further support the notion that PS-MNPs distinctly perturb lipid metabolism in C. elegans in a size-dependent manner.
The size-dependent differences in metabolic phenotypic profiles, such as differential metabolite expression patterns, and enriched metabolic pathways indicate that the toxicological effects of PS-MNPs on C. elegans metabolism are tightly associated with particle size. These findings lay a critical foundation for further deciphering the molecular mechanisms underlying the size-dependent toxicity of PS-MNPs, and provide novel insights into the metabolic targets of plastic particle-induced toxicity in aquatic invertebrates.

3.5. Effects of PS-MPs on Fat Accumulation and Mitochondrial Activity in C. elegans

Fat accumulation in C. elegans was significantly increased following 5 days of PS-MP exposure (Figure 5A). Notably, the 100 nm PS-MP group exhibited greater lipid accumulation than the 1 μm group, suggesting a stronger impact of smaller particles on lipid metabolism. Pharyngeal pumping frequency, a proxy for feeding behavior, was significantly reduced in both PS-MP groups compared with controls, but no significant difference was found between the two particle sizes (Figure 5B), indicating that differences in fat accumulation were not due to altered food intake.
Based on transcriptomic and metabolomic analyses, several differentially expressed genes related to lipid metabolism were screened out, and the expression levels were verified by qPCR (Figure 5C). Results showed that compared with the 1 μm PS-MP exposure group, the expression levels of metabolism-related genes were significantly decreased in the 100 nm PS-MP exposure group. Expression of key lipid metabolism genes, including acdh-1, ech-6, hach-1, and sur-5, was significantly reduced in the 100 nm PS-MP group compared to the 1 μm group. Integrated transcriptomic and metabolomic analysis identified overlapping enriched pathways, including β-alanine metabolism and pyrimidine metabolism. As β-alanine is closely linked to fatty acid metabolism, it is hypothesized that PS-MPs may modulate lipid accumulation through perturbations in this pathway. To test this, RNAi was used to knock down acdh-1, ech-6, hach-1, and sur-5. After gene silencing, no significant difference in fat accumulation was observed between these two PS-MP exposure groups (Figure 5D), implicating these genes as mediators of PS-MP-induced lipid metabolism disruption.
Given that both acdh-1 and ech-6 localize to mitochondria and are involved in β-oxidation of fatty acids, we assessed mitochondrial activity in PS-MP-exposed C. elegans. Mitochondrial function was significantly reduced after 5 days of exposure to either particle size, with more pronounced impairment observed in the 100 nm group (Figure 5E). These findings suggest that 100 nm PS-MPs may impair mitochondrial β-oxidation via suppression of acdh-1 and ech-6, leading to the increased fat accumulation.
Long-term exposure effects were also evaluated across generations. Fat accumulation levels in the three groups were different. In the control group, it showed no significantly differences between F0–F2 generations. In the 100 nm group, fat levels trended downward from F0 to F2, becoming statistically indistinguishable from controls in the F2 generation. This suggests that prolonged and low-dose PS-MP exposure may trigger adaptive stress responses in C. elegans. In the F1 generation, the two exposure groups both showed significantly increased fat accumulation, and smaller size (100 nm) group revealed more serious damage (Figure 5F). However, no generational differences in fat accumulation were observed in the F2 generation in all groups (Figure 5G). Interestingly, in the 1 μm group, fat accumulation increased significantly from F0 to F1, but declined in the F2 generation to control levels (Figure 5H). These results suggest that chronic exposure to PS-MPs, regardless of particle size, may initially disrupt lipid homeostasis but eventually induce protective physiological adaptations that normalize fat metabolism across generations.

4. Discussion

This study elucidated the size-dependent toxicological effects of PS-MPs on C. elegans. Our findings demonstrated that exposure to PS-MPs could induce fat accumulation in C. elegans and that the effect varies according to particle size (Figure 6).
In this work, exposures to two sizes of MPs were both shown to reduce the lifespan of C. elegans, consistent with previous studies [41]. While smaller particles are often assumed to be more toxic due to greater cellular uptake, our data align with earlier findings that 1 μm particles can exert equal or even greater toxicity [42]. This may be attributed to their similarity in size to E. coli OP50, the natural food source of C. elegans, leading to enhanced ingestion and accumulation. The 5 day exposure duration was selected based on the biological characteristics of C. elegans and consistency with established protocols for MNP exposure. As demonstrated in our previous study [29], this duration covers the full larval-to-adult developmental period of C. elegans, which is a stage highly sensitive to NP exposure. A 5 day window ensures that we capture both the accumulation of PS-MPs in tissues, such as intestine and neurons, and the subsequent toxicological and metabolic responses, including perturbations in locomotion behavior, sensory perception, and neuronal development, as observed in our previous study [29]. The 5 day exposure protocol and 100 nm/L μm particle size were selected to mimic chronic environmental exposure scenarios relevant to soil nematodes [43], not to simulate human exposure conditions. This duration also aligns with the 4–7 day exposure window commonly adopted in C. elegans by studies of MNP exposure, ensuring comparability with the existing literature and avoiding confounding factors from senescence or overgrowth that would occur with longer exposures.
Lipid metabolism in C. elegans is tightly regulated by β-oxidation of fatty acids, which breaks down triglycerides (TGs) to supply energy. Impairment in this pathway leads to excess lipid accumulation [44]. Our findings showed that PS-MP exposure increases lipid content in C. elegans, with the 100 nm group exhibiting more pronounced fat accumulation than that of the 1 μm group. Previous study [45] supports these results. Other studies [46,47,48] have also exhibited an increase in fat accumulation across species. The frequency of pharyngeal pumping reflects the feeding capacity of C. elegans and is a key mechanism by which C. elegans controls the absorption of food and other particles. Notably, although the pharyngeal pumping rate of nematodes was restrained by MP exposure, no significant difference was observed between the two particle size groups. This suggests that differences in fat accumulation are not attributable to altered food intake but rather to disrupted metabolic pathways.
Fatty acid β-oxidation is a critical metabolic pathway involving sequential enzymatic steps—dehydrogenation, hydration, re-dehydrogenation, and thiolysis. These steps require enzymes involving acyl-CoA dehydrogenase in mitochondria or acyl-CoA oxidase in peroxisome, enoyl-CoA hydratase, 3-hydroxylactoyl-CoA dehydrogenase, and 3-ketoyl-CoA thioase [19]. Transcriptomic analysis in this study revealed significant downregulation of key genes associated with lipid metabolism (acdh-1, ech-6, hach-1, and sur-5) in the 100 nm PS-MP group. acdh-1 and ech-6, both mitochondrial genes, encode enzymes involved in β-oxidation: acyl-CoA dehydrogenase and enoyl-CoA hydratase, respectively. Reduced expression of these genes has been associated with impaired β-oxidation and subsequent fat accumulation. mdt-15 is known to activate acdh-1 and regulate lipid homeostasis of C. elegans [49], while ech-6 also directly influences fat storage [50]. sur-5 is involved in fatty acid metabolism, and hach-1 regulates valine degradation, and both fatty acid β-oxidation and valine can reduce fat content. If the level of related genes decreases, the fat content in C. elegans increases [51].
Consistent with the transcriptomic findings, mitochondrial activity was significantly reduced in PS-MP-exposed C. elegans, particularly in the 100 nm group. Since both acdh-1 and ech-6 are localized in mitochondria, their downregulation may be a direct consequence of mitochondrial dysfunction in both PS-MP-exposed groups. These results suggest that smaller PS-MPs may more profoundly impair mitochondrial function, thereby reducing β-oxidation capacity and promoting lipid accumulation.
To elucidate the molecular mechanisms underlying the toxic effects of PS-MPs on C. elegans, we conducted comprehensive transcriptomic sequencing on nematodes exposed to 100 nm and 1 μm PS-MPs. GO enrichment analysis revealed that the differentially expressed genes (DEGs) were predominantly associated with stress response, mitochondria, lipid modification, etc. KEGG pathway enrichment further indicated that these DEGs significantly clustered within metabolic pathways, specifically highlighting perturbations in lipid metabolism. Among these, four lipid metabolism-related genes, namely acdh-1, ech-6, hach-1, and sur-5, were identified within metabolic and β-alanine metabolism pathways. NHR-10 directly binds and activates acdh-1, consistent with previous findings demonstrating that nuclear hormone receptors (NHRs) serve as lipid sensors [52]. The ech-6 gene encodes an enoyl-CoA hydratase gene implicated in mitochondrial transport and fatty acid β oxidation [50]. Additionally, acdh-1, ech-6, and hach-1 participate in the metabolic shunting pathway of propionic acid, a short-chain saturated fatty acid [51]. Previous research has reported analogous disruptions in lipid metabolism pathways in mice exposed to PS-MPs [53]. Nevertheless, the precise mechanisms by which MPs of different particle sizes influence lipid metabolism in C. elegans remain incompletely understood and warrant further investigation.
To probe the involvement of these candidate genes in lipid accumulation changes induced by PS-MP exposure, we utilized RNAi to specifically knock down gene expression. This suggests that these genes play an important role in fat metabolism in C. elegans. It is therefore hypothesized that exposure to MPs of varying particle sizes modulates fat accumulation in C. elegans via regulating the genes acdh-1, ech-6, hach-1, sur-5, and ech-6, as well as the β-alanine metabolic pathway gene hach-1.
Emerging evidence demonstrates that MP exposure broadly disrupts biological metabolism. It was reported that, zebrafish exposed to PP MP fibers of differing lengths exhibited altered metabolites primarily in sphingolipid metabolism, glycerophospholipid metabolism, and adipocytokine signaling, all integral components of lipid metabolism [54]. Additionally, studies on diverse model organisms, including Daphnia magna and mice, further substantiate MP-induced disruption of lipid metabolism pathways [17,55]. Consistent with these findings, our results indicated that TG levels significantly increased in the control group exposed to larger-sized PS-MPs, confirming the adverse impacts on lipid metabolic pathways in C. elegans. Metabolomic studies [56,57] further support that PS-MP exposure perturbs amino acid metabolism, purine metabolism, and the citric acid cycle in C. elegans. Currently, metabolomics-based investigations on the metabolic impacts of MP exposure in C. elegans remain limited. Beyond lipid metabolism, the broader mechanisms and regulatory networks affected by MPs across various metabolic pathways remain unclear, underscoring the need for expanded research using additional models and advanced analytical approaches.
Chronic, low-dose exposure to PS-MPs in C. elegans mimics environmentally relevant conditions and likely represents a long-term, low-toxicity stressor. Such exposure appears to activate endogenous protective mechanisms, including stress response pathways, which may help mitigate physiological damage over time. Previous studies on mammals have reported transgenerational metabolic effects following PS-MP exposure [58]. It was found that maternal exposure to PS-MPs (1, 5 and 25 μg/μL) during pregnancy led to significantly lower birth weights and elevated hepatic TG levels in female offspring, but not male offspring at medium and high doses, suggesting a sex-specific susceptibility to metabolic disruption.
Luo [59] observed increased TG levels in pregnant mice exposed to 100 and 1000 μg/L PS-MPs, whereas TG content significantly decreased in female offspring, potentially due to adaptive stress responses elicited by low-dose exposure—findings that are consistent with our observations. However, most existing studies have focused solely on maternal exposure and its direct effects on offspring, without examining the consequences of sustained PS-MP exposure in subsequent generations. In C. elegans, intergenerational studies have mainly focused on reproductive toxicity [60,61,62], while the long-term impact of exposure to low concentrations of PS-MPs on lipid metabolism across generations remains poorly understood. Our findings highlight the need for expanded research into the molecular and physiological mechanisms underlying transgenerational metabolic alterations induced by MP exposure.

5. Conclusions

This study demonstrated that exposure to different sizes of MNPs impaired growth, development, feeding, and reproduction in C. elegans. Importantly, multi-omics analyses converged on lipid metabolic dysregulation: transcriptomics and metabolomics consistently indicated perturbation of mitochondrial function and lipid-handling pathways. Differential expression of the metabolic genes acdh-1, ech-6, hach-1, and sur-5 was associated with altered fat accumulation, implicating these targets in particle-induced metabolic toxicity. The magnitude and character of these effects were size-dependent, with results supporting a central role for mitochondrial dysfunction in mediating lipid homeostasis under PS particle exposure. Together, these findings delineate a mechanistic link between particle size and lipid metabolic disruption in C. elegans, suggest potential intergenerational consequences of chronic exposure, and motivate further evaluation under long-term and low-dose conditions that reflect environmental realities.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/toxics14020170/s1, Text S1: Details of DNA extraction, Illumina MiSeq sequencing, and amplicon sequence processing.

Author Contributions

Conceptualization, N.L. and Z.Q.; methodology, X.F. and Y.W.; software, X.F.; validation, Y.W.; formal analysis, X.F. and R.W.; investigation, Z.Q. and X.F.; writing—original draft preparation, Z.Q., X.F. and N.L.; writing—review and editing, Z.Q. and N.L.; visualization, Y.W.; supervision, N.L. and Z.Q.; funding acquisition, N.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work received financial support from the National Natural Science Foundation of China (No. 81872584), Natural Science Foundation of Shenzhen (No. JCYJ20250604182049064), Sanming Project of Medicine in Shenzhen (No. SZSM202211009), and Henan Province’s Key R&D and Promotion Projects (Scientific and Technological Research) Projects (No. 252102310075).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

acdh-1Acyl-CoA dehydrogenase-1
BPBiological process
CCCellular component
cDNAComplementary DNA
C. elegansCaenorhabditis elegans
CoACoenzyme A
DEGsDifferentially expressed genes
DE-mRNAsDifferentially expressed mRNAs
DLSDynamic light scattering
dsRNADouble-stranded RNA
E. coliEscherichia coli
ech-6Enoyl-CoA hydratase-6
FCFold change
FTIRFourier-transform infrared spectroscopy
GOGene Ontology
hach-1Hydroxyacyl-CoA dehydrogenase-1
IGF-1Insulin-like Growth Factor 1
IPTGIsopropyl β-D-1-thiogalactopyranoside
KEGGKyoto Encyclopedia of Genes and Genomes
LBLuria–Bertani medium
MF Molecular function
mdt-15Mediator complex subunit 15
MNPsMicro- and nanoplastics
MPsMicroplastics
NCBI National Center for Biotechnology Information
NGMNematode growth medium
NHR-10Nuclear hormone receptor-10
NHRsNuclear hormone receptors
NPsNanoplastics
PCA Principal component analysis
PCRPolymerase chain reaction
PEPolyethylene
PETPolyethylene terephthalate
PPPolypropylene
PP MPsPolypropylene microplastics
PSPolystyrene
PS-MNPsPolystyrene micro- and nanoplastics
PS-MPsPolystyrene microplastics
PVCPolyvinyl chloride
QCQuality control
qPCRQuantitative PCR
R6GRhodamine 6G
RNARibonucleic acid
RNAiRNA interference
RTReverse transcription
SEMScanning electron microscopy
ssDNASingle-stranded DNA
sur-5Suppressor of ras-5
TGs Triglycerides
UHPLC-HRMSUltra-high-performance liquid chromatography coupled with high-resolution mass spectrometry

References

  1. Fan, Y.V.; Jiang, P.; Tan, R.R.; Aviso, K.B.; You, F.; Zhao, X.; Lee, C.T.; Klemeš, J.J. Forecasting plastic waste generation and interventions for environmental hazard mitigation. J. Hazard. Mater. 2022, 424, 127330. [Google Scholar] [CrossRef]
  2. Thompson, R.C.; Courtene-Jones, W.; Boucher, J.; Pahl, S.; Raubenheimer, K.; Koelmans, A.A. Twenty years of microplastic pollution research-what have we learned? Science 2024, 386, eadl2746. [Google Scholar] [CrossRef] [PubMed]
  3. Koelmans, A.A.; Nor, N.H.M.; Hermsen, E.; Kooi, M.; Mintenig, S.M.; De France, J. Microplastics in freshwaters and drinking water: Critical review and assessment of data quality. Water Res. 2019, 155, 410–422. [Google Scholar] [CrossRef]
  4. Schwabl, P.; Koeppel, S.; Koenigshofer, P.; Bucsics, T.; Trauner, M.; Reiberger, T.; Liebmann, B. Detection of Various Microplastics in Human Stool A Prospective Case Series. Ann. Intern. Med. 2019, 171, 453–457. [Google Scholar] [CrossRef]
  5. Zarus, G.M.; Muianga, C.; Hunter, C.M.; Pappas, R.S. A review of data for quantifying human exposures to micro and nanoplastics and potential health risks. Sci. Total Environ. 2021, 756, 144010. [Google Scholar] [CrossRef] [PubMed]
  6. Liu, W.; Qu, Z.; Wang, X.; Feng, H.; Ma, S.; Zheng, Y.; Lin, G.; Huang, S.; Yang, Q.; Feng, X.; et al. Microplastic exposure is associated with male reproductive health. Med. Rev. 2024, 4, 549–552. [Google Scholar] [CrossRef] [PubMed]
  7. Ragusa, A.; Svelato, A.; Santacroce, C.; Catalano, P.; Notarstefano, V.; Carnevali, O.; Papa, F.; Rongioletti, M.C.A.; Baiocco, F.; Draghi, S.; et al. Plasticenta: First evidence of microplastics in human placenta. Environ. Int. 2021, 146, 106274. [Google Scholar] [CrossRef]
  8. 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. [Google Scholar] [CrossRef]
  9. 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. [Google Scholar] [CrossRef]
  10. Liu, S.; Lin, G.; Liu, X.; Yang, R.; Wang, H.; Sun, Y.; Chen, B.; Dong, R. Detection of various microplastics in placentas, meconium, infant feces, breastmilk and infant formula: A pilot prospective study. Sci. Total Environ. 2022, 854, 158699. [Google Scholar] [CrossRef]
  11. Chen, Y.; Nan, Y.; Xu, L.; Dai, A.; Orteg, R.M.M.; Ma, M.; Zeng, Y.; Li, J. Polystyrene nanoplastics exposure induces cognitive impairment in mice via induction of oxidative stress and ERK/MAPK-mediated neuronal cuproptosis. Part. Fibre Toxicol. 2025, 22, 13. [Google Scholar] [CrossRef]
  12. Asmaa, L.; Al Mehdi, K.; Khadija, A.; Jawad, L.; Rachida, R. Effects of exposure to micro/nanoplastics of polystyrene on neuronal oxidative stress, neuroinflammation, and anxiety-like behavior in mice: A Systematic Review. Emerg. Contam. 2025, 11, 100442. [Google Scholar] [CrossRef]
  13. Xu, H.; Wang, J.; Wang, Q.; Tu, W.; Jin, Y. Co-exposure to polystyrene microplastics and cypermethrin enhanced the effects on hepatic phospholipid metabolism and gut microbes in adult zebrafish. J. Hazard. Mater. 2024, 465, 133051. [Google Scholar] [CrossRef]
  14. Yoo, J.W.; Choi, T.J.; Park, J.S.; Lee, Y.H.; Hwang, D.H.; Kim, C.B.; Jeong, T.Y.; Lee, Y.M. Comparative impacts of fragmented versus spherical microplastics on the marine rotifer Brachionus koreanus: Multigenerational chronic toxicity and multi-omics perspective. J. Hazard. Mater. 2025, 495, 139094. [Google Scholar] [CrossRef] [PubMed]
  15. Kasmuri, N.; Tarmizi, N.A.A.; Mojiri, A. Occurrence, impact, toxicity, and degradation methods of microplastics in environment-a review. Environ. Sci. Pollut. Res. Int. 2022, 29, 30820–30836. [Google Scholar] [CrossRef]
  16. 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. [Google Scholar] [CrossRef]
  17. Wang, P.; Li, Q.Q.; Hui, J.; Xiang, Q.Q.; Yan, H.; Chen, L.Q. Metabolomics reveals the mechanism of polyethylene microplastic toxicity to Daphnia magna. Chemosphere 2022, 307, 135887. [Google Scholar] [CrossRef]
  18. Guo, P.; Wang, P.; Liu, L.; Wang, P.; Lin, G.; Qu, Z.; Yu, Z.; Liu, N. Naringin Alleviates Glucose-Induced Aging by Reducing Fat Accumulation and Promoting Autophagy in Caenorhabditis elegans. Nutrients 2023, 15, 907. [Google Scholar] [CrossRef] [PubMed]
  19. Watts, J.L.; Ristow, M. Lipid and Carbohydrate Metabolism in Caenorhabditis elegans. Genetics 2017, 207, 413–446. [Google Scholar] [CrossRef] [PubMed]
  20. Dawson, A.L.; Kawaguchi, S.; King, C.K.; Townsend, K.A.; King, R.; Huston, W.M.; Bengtson Nash, S.M. Turning microplastics into nanoplastics through digestive fragmentation by Antarctic krill. Nat. Commun. 2018, 9, 1001. [Google Scholar] [CrossRef]
  21. Toussaint, B.; Raffael, B.; Angers-Loustau, A.; Gilliland, D.; Kestens, V.; Petrillo, M.; Rio-Echevarria, I.M.; Van den Eede, G. Review of micro- and nanoplastic contamination in the food chain. Food Addit. Contam. Part A Chem. Anal. Control Expo. Risk Assess. 2019, 36, 639–673. [Google Scholar] [CrossRef]
  22. Liu, Z.; Bian, Q.; Wang, D. 6-PPD quinone induces response of nuclear hormone receptors in the germline associated with formation of reproductive toxicity in Caenorhabditis elegans. J. Hazard. Mater. 2025, 495, 138815. [Google Scholar] [CrossRef]
  23. Horton, A.A.; Walton, A.; Spurgeon, D.J.; Lahive, E.; Svendsen, C. Microplastics in freshwater and terrestrial environments: Evaluating the current understanding to identify the knowledge gaps and future research priorities. Sci. Total Environ. 2017, 586, 127–141. [Google Scholar] [CrossRef] [PubMed]
  24. Pan, Y.; Zhang, H.; Zhu, L.; Tan, J.; Wang, B.; Li, M. The role of gut microbiota in MP/NP-induced toxicity. Environ. Pollut. 2024, 359, 124742. [Google Scholar] [CrossRef] [PubMed]
  25. Wu, T.; He, J.; Ye, Z.; Xia, J.; Chen, M.; Chen, S.; Liu, K.; Xing, P.; Yang, J.; Qian, Y.; et al. Aged Biodegradable Nanoplastics Enhance Body Accumulation Associated with Worse Neuronal Damage in Caenorhabditis elegans. Environ. Sci. Technol. 2025, 59, 4352–4363. [Google Scholar] [CrossRef] [PubMed]
  26. Chen, H.; Yang, Y.; Wang, C.; Hua, X.; Li, H.; Xie, D.; Xiang, M.; Yu, Y. Reproductive toxicity of UV-photodegraded polystyrene microplastics induced by DNA damage-dependent cell apoptosis in Caenorhabditis elegans. Sci. Total Environ. 2022, 811, 152350. [Google Scholar] [CrossRef]
  27. Anisimov, V.N.; Bartke, A. The key role of growth hormone-insulin-IGF-1 signaling in aging and cancer. Crit. Rev. Oncol. Hematol. 2013, 87, 201–223. [Google Scholar] [CrossRef]
  28. Qu, Z.; Wang, P.; Wang, Y.; Guo, P.; Lin, G.; Wang, P.; Yu, Z.; Liu, N. Polychlorinated biphenyls-153 induces fat accumulation and lifespan shortening through CYP450 family genes in Caenorhabditis elegans. J. Environ. Sci. 2025, 158, 72–83. [Google Scholar] [CrossRef]
  29. Qu, Z.; Liu, L.; Wu, X.; Guo, P.; Yu, Z.; Wang, P.; Song, Y.; Zheng, S.; Liu, N. Cadmium-induced reproductive toxicity combined with a correlation to the oogenesis process and competing endogenous RNA networks based on a Caenorhabditis elegans model. Ecotoxicol. Environ. Saf. 2023, 268, 115687. [Google Scholar] [CrossRef]
  30. Kamath, R.S.; Fraser, A.G.; Dong, Y.; Poulin, G.; Durbin, R.; Gotta, M.; Kanapin, A.; Le Bot, N.; Moreno, S.; Sohrmann, M.; et al. Systematic functional analysis of the Caenorhabditis elegans genome using RNAi. Nature 2003, 421, 231–237. [Google Scholar] [CrossRef]
  31. Hammell, C.M.; Hannon, G.J. Inducing RNAi in C. elegans by feeding with dsRNA-expressing E. coli. Cold Spring Harb. Protoc. 2012, 2012, pdb-prot072348. [Google Scholar] [CrossRef]
  32. Shang, X.; Lu, J.; Feng, C.; Ying, Y.; He, Y.; Fang, S.; Lin, Y.; Dahlgren, R.; Ju, J. Microplastic (1 and 5 μm) exposure disturbs lifespan and intestine function in the nematode Caenorhabditis elegans. Sci. Total Environ. 2020, 705, 135837. [Google Scholar] [CrossRef]
  33. Zhao, Y.; Chen, H.; Yang, Y.; Wu, Q.; Wang, D. Graphene oxide disrupts the protein-protein interaction between Neuroligin/NLG-1 and DLG-1 or MAGI-1 in nematode Caenorhabditis elegans. Sci. Total Environ. 2020, 700, 134492. [Google Scholar] [CrossRef]
  34. Komura, T.; Yamanaka, M.; Nishimura, K.; Hara, K.; Nishikawa, Y. Autofluorescence as a noninvasive biomarker of senescence and advanced glycation end products in Caenorhabditis elegans. npj Aging Mech. Dis. 2021, 7, 12. [Google Scholar] [CrossRef] [PubMed]
  35. Liu, X.; Zheng, X.; Zhang, L.; Li, J.; Li, Y.; Huang, H.; Fan, Z. Joint toxicity mechanisms of binary emerging PFAS mixture on algae (Chlorella pyrenoidosa) at environmental concentration. J. Hazard. Mater. 2022, 437, 129355. [Google Scholar] [CrossRef] [PubMed]
  36. Schmittgen, T.D.; Livak, K.J. Analyzing real-time PCR data by the comparative C(T) method. Nat. Protoc. 2008, 3, 1101–1108. [Google Scholar] [CrossRef] [PubMed]
  37. Escorcia, W.; Ruter, D.L.; Nhan, J.; Curran, S.P. Quantification of Lipid Abundance and Evaluation of Lipid Distribution in Caenorhabditis elegans by Nile Red and Oil Red O Staining. J. Vis. Exp. 2018, 133, 57352. [Google Scholar] [CrossRef]
  38. Soukas, A.A.; Kane, E.A.; Carr, C.E.; Melo, J.A.; Ruvkun, G. Rictor/TORC2 regulates fat metabolism, feeding, growth, and life span in Caenorhabditis elegans. Genes. Dev. 2009, 23, 496–511. [Google Scholar] [CrossRef]
  39. Yang, Y.; Dong, W.; Wu, Q.; Wang, D. Response of G protein-coupled receptor CED-1 in germline to polystyrene nanoparticles in Caenorhabditis elegans. Nanoscale Adv. 2021, 3, 1997–2006. [Google Scholar] [CrossRef]
  40. Liu, Q.; Chen, C.; Li, M.; Ke, J.; Huang, Y.; Bian, Y.; Guo, S.; Wu, Y.; Han, Y.; Liu, M. Neurodevelopmental Toxicity of Polystyrene Nanoplastics in Caenorhabditis elegans and the Regulating Effect of Presenilin. ACS Omega 2020, 5, 33170–33177. [Google Scholar] [CrossRef] [PubMed]
  41. Qiu, Y.; Luo, L.; Yang, Y.; Kong, Y.; Li, Y.; Wang, D. Potential toxicity of nanopolystyrene on lifespan and aging process of nematode Caenorhabditis elegans. Sci. Total Environ. 2020, 705, 135918. [Google Scholar] [CrossRef]
  42. Le, L.; Liu, M.; Song, Y.; Lu, S.; Hu, J.; Cao, C.; Xie, B.; Shi, H.; He, D. Polystyrene (nano)microplastics cause size-dependent neurotoxicity, oxidative damage and other adverse effects in Caenorhabditis elegans. Environ. Sci.-Nano 2018, 5, 2009–2020. [Google Scholar] [CrossRef]
  43. Leung, M.C.; Williams, P.L.; Benedetto, A.; Au, C.; Helmcke, K.J.; Aschner, M.; Meyer, J.N. Caenorhabditis elegans: An emerging model in biomedical and environmental toxicology. Toxicol. Sci. 2008, 106, 5–28. [Google Scholar] [CrossRef]
  44. Srinivasan, S. Regulation of body fat in Caenorhabditis elegans. Annu. Rev. Physiol. 2015, 77, 161–178. [Google Scholar] [CrossRef]
  45. Fueser, H.; Pilger, C.; Kong, C.; Huser, T.; Traunspurger, W. Polystyrene microbeads influence lipid storage distribution in C. elegans as revealed by coherent anti-Stokes Raman scattering (CARS) microscopy. Environ. Pollut. 2022, 294, 118662. [Google Scholar] [CrossRef]
  46. Jiang, Q.; Chen, X.; Jiang, H.; Wang, M.; Zhang, T.; Zhang, W. Effects of Acute Exposure to Polystyrene Nanoplastics on the Channel Catfish Larvae: Insights from Energy Metabolism and Transcriptomic Analysis. Front. Physiol. 2022, 13, 923278. [Google Scholar] [CrossRef]
  47. Shiu, H.T.; Pan, X.; Liu, Q.; Long, K.; Cheng, K.K.Y.; Ko, B.C.; Fang, J.K.; Zhu, Y. Dietary exposure to polystyrene nanoplastics impairs fasting-induced lipolysis in adipose tissue from high-fat diet fed mice. J. Hazard. Mater. 2022, 440, 129698. [Google Scholar] [CrossRef]
  48. Zhao, Y.; Qin, Z.; Huang, Z.; Bao, Z.; Luo, T.; Jin, Y. Effects of polyethylene microplastics on the microbiome and metabolism in larval zebrafish. Environ. Pollut. 2021, 282, 117039. [Google Scholar] [CrossRef]
  49. Arda, H.E.; Taubert, S.; MacNeil, L.T.; Conine, C.C.; Tsuda, B.; Van Gilst, M.; Sequerra, R.; Doucette-Stamm, L.; Yamamoto, K.R.; Walhout, A.J. Functional modularity of nuclear hormone receptors in a Caenorhabditis elegans metabolic gene regulatory network. Mol. Syst. Biol. 2010, 6, 367. [Google Scholar] [CrossRef] [PubMed]
  50. Liu, Y.J.; Gao, A.W.; Smith, R.L.; Janssens, G.E.; Panneman, D.M.; Jongejan, A.; van Weeghel, M.; Vaz, F.M.; Silvestrini, M.J.; Lapierre, L.R.; et al. Reduced ech-6 expression attenuates fat-induced lifespan shortening in C. elegans. Sci. Rep. 2022, 12, 3350. [Google Scholar] [CrossRef] [PubMed]
  51. Nanda, S.; Jacques, M.A.; Wang, W.; Myers, C.L.; Yilmaz, L.S.; Walhout, A.J. Systems-level transcriptional regulation of Caenorhabditis elegans metabolism. Mol. Syst. Biol. 2023, 19, e11443. [Google Scholar] [CrossRef]
  52. MacNeil, L.T.; Watson, E.; Arda, H.E.; Zhu, L.J.; Walhout, A.J. Diet-induced developmental acceleration independent of TOR and insulin in C. elegans. Cell 2013, 153, 240–252. [Google Scholar] [CrossRef]
  53. Wang, Q.; Wu, Y.; Zhang, W.; Shen, T.; Li, H.; Wu, J.; Zhang, L.; Qin, L.; Chen, R.; Gu, W.; et al. Lipidomics and transcriptomics insight into impacts of microplastics exposure on hepatic lipid metabolism in mice. Chemosphere 2022, 308, 136591. [Google Scholar] [CrossRef]
  54. Zhao, Y.; Qiao, R.; Zhang, S.; Wang, G. Metabolomic profiling reveals the intestinal toxicity of different length of microplastic fibers on zebrafish (Danio rerio). J. Hazard. Mater. 2021, 403, 123663. [Google Scholar] [CrossRef] [PubMed]
  55. Chen, G.; Xiong, S.; Jing, Q.; van Gestel, C.A.M.; van Straalen, N.M.; Roelofs, D.; Sun, L.; Qiu, H. Maternal exposure to polystyrene nanoparticles retarded fetal growth and triggered metabolic disorders of placenta and fetus in mice. Sci. Total Environ. 2022, 854, 158666. [Google Scholar] [CrossRef]
  56. Kim, H.M.; Long, N.P.; Min, J.E.; Anh, N.H.; Kim, S.J.; Yoon, S.J.; Kwon, S.W. Comprehensive phenotyping and multi-omic profiling in the toxicity assessment of nanopolystyrene with different surface properties. J. Hazard. Mater. 2020, 399, 123005. [Google Scholar] [CrossRef]
  57. Kim, H.M.; Lee, D.K.; Long, N.P.; Kwon, S.W.; Park, J.H. Uptake of nanopolystyrene particles induces distinct metabolic profiles and toxic effects in Caenorhabditis elegans. Environ. Pollut. 2019, 246, 578–586. [Google Scholar] [CrossRef]
  58. Wang, X.; Zhao, Z.; Wang, X.; Hu, W.; Chao, L.; Chu, X.; Qian, M.; Wang, R.; Yu, S.; Wu, Q.; et al. Effects of polystyrene nanoplastic gestational exposure on mice. Chemosphere 2023, 324, 138255. [Google Scholar] [CrossRef]
  59. Luo, T.; Wang, C.; Pan, Z.; Jin, C.; Fu, Z.; Jin, Y. Maternal Polystyrene Microplastic Exposure during Gestation and Lactation Altered Metabolic Homeostasis in the Dams and Their F1 and F2 Offspring. Environ. Sci. Technol. 2019, 53, 10978–10992. [Google Scholar] [CrossRef] [PubMed]
  60. Liu, H.; Tian, L.; Wang, S.; Wang, D. Size-dependent transgenerational toxicity induced by nanoplastics in nematode Caenorhabditis elegans. Sci. Total Environ. 2021, 790, 148217. [Google Scholar] [CrossRef] [PubMed]
  61. Sun, L.; Liao, K.; Wang, D. Comparison of transgenerational reproductive toxicity induced by pristine and amino modified nanoplastics in Caenorhabditis elegans. Sci. Total Environ. 2021, 768, 144362. [Google Scholar] [CrossRef] [PubMed]
  62. Yu, C.W.; Luk, T.C.; Liao, V.H. Long-term nanoplastics exposure results in multi and trans-generational reproduction decline associated with germline toxicity and epigenetic regulation in Caenorhabditis elegans. J. Hazard. Mater. 2021, 412, 125173. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. Physicochemical characterization of PS. (A) SEM image of 1 μm PS. (B) SEM image of 100 nm PS; (C) Size distribution by intensity of 1 μm PS; (D) Size distribution by intensity of 100 nm PS; (E) FTIR spectrum of 1 μm PS-MPs; (F) FTIR spectrum of 100 nm PS-MPs.
Figure 1. Physicochemical characterization of PS. (A) SEM image of 1 μm PS. (B) SEM image of 100 nm PS; (C) Size distribution by intensity of 1 μm PS; (D) Size distribution by intensity of 100 nm PS; (E) FTIR spectrum of 1 μm PS-MPs; (F) FTIR spectrum of 100 nm PS-MPs.
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Figure 2. Physiological and biochemical effects of PS-MP exposure in nematodes. (A) Survival curves under exposure to PS-MPs of different sizes and concentrations (n ≥ 92 worms/group). (B) Body length (n ≥ 28 worms/group); (C) Body width (n ≥ 28 worms/group); (D) Head thrashes (n ≥ 31 worms/group); (E) Body bends (n ≥ 33 worms/group); (F) Offspring number (n ≥ 17 worms/group); (G) Relative lipofuscin content (n ≥ 28 worms/group). * p < 0.05 and ** p < 0.01. μPS and 1000-PS mean the PS-MP particles with the size of 1 μm. NPS and 100-PS mean the PS-MP particles with the size of 100 nm.
Figure 2. Physiological and biochemical effects of PS-MP exposure in nematodes. (A) Survival curves under exposure to PS-MPs of different sizes and concentrations (n ≥ 92 worms/group). (B) Body length (n ≥ 28 worms/group); (C) Body width (n ≥ 28 worms/group); (D) Head thrashes (n ≥ 31 worms/group); (E) Body bends (n ≥ 33 worms/group); (F) Offspring number (n ≥ 17 worms/group); (G) Relative lipofuscin content (n ≥ 28 worms/group). * p < 0.05 and ** p < 0.01. μPS and 1000-PS mean the PS-MP particles with the size of 1 μm. NPS and 100-PS mean the PS-MP particles with the size of 100 nm.
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Figure 3. Bioinformatic analyses of whole-transcriptome sequencing after exposure to PS-MPs with sizes of 100 nm and 1 μm. Software used for transcriptomic-level analysis includes StringTie v2.2.3 (Johns Hopkins University, Baltimore, MD, USA), Ballgown v2.26.0 (Johns Hopkins University, Baltimore, MD, USA), CPAT v3.0.4 (University of Massachusetts Medical School, Worcester, MA, USA), rMATS v4.1.2 (University of California, Los Angeles, CA, USA), CIRCexplorer2 v2.3.8 (University of California, Los Angeles, CA, USA), edgeR v3.40.2 (Bioconductor, Fred Hutchinson Cancer Research Center, Seattle, WA, USA), and custom Python/R/Shell scripts. (A) Volcano plot of DEGs; (B) KEGG pathway enrichment of DE-mRNAs; (C) GO enrichment of DE-mRNAs. Top 10 categories of MF, BP and CC including high Stress_response_to_copper_ion [GO:1990169], Response_to_copper_ion [GO:0046688], Killing_of_cells_of_another_organism [GO:0031640], Ceramide_biosynthetic_process [GO:0046513], Stress_response_to_metal_ion [GO:0097501], Mitotic_spindle_assembly_checkpoint_signaling [GO:0007094], Mitochondrial_transport [GO:0006839], Lipid_modification [GO:0030258], Protein_acetylation [GO:0006473], Peptidyl-lysine_modification [GO:0018205], Intracellular_anatomical_structure [GO:0005622], Mitochondrion [GO:0005739], Cytoplasm [GO:0005737], Intracellular_membrane-bounded organelle [GO:0043231], Intracellular_organelle [GO:0043229], Membrane-bounded_organelle [GO:0043227], Organelle [GO:0043226], Condensed_chromosome [GO:0000793], Histone_acetyltransferase_complex [GO:0000123], Kinetochore [GO:0000776], Sphingolipid_delta-4_desaturase activity [GO:0042284], Flavin-linked_sulthydryl oxidase activity [GO:0016971], Thiol_oxidase_activity [GO:0016972], Thiolester_hydrolase_activity [GO:0016790], Thiosulfate_sulfurtransferase_activity [GO:0004792], Oxidoreductase activity [GO:0016717], N-acyltransferase_activity [GO:0016410], Exonuclease_activity [GO:0004527], 3′-5′_exonuclease_activity [GO:0008408], Protein-disulfide_reductase_activity [GO:0015035]; (D–F) GO enrichment chord diagrams for downregulated DEGs: biological process (BP) (D), cellular component (CC) (E), and molecular function (MF) (F).
Figure 3. Bioinformatic analyses of whole-transcriptome sequencing after exposure to PS-MPs with sizes of 100 nm and 1 μm. Software used for transcriptomic-level analysis includes StringTie v2.2.3 (Johns Hopkins University, Baltimore, MD, USA), Ballgown v2.26.0 (Johns Hopkins University, Baltimore, MD, USA), CPAT v3.0.4 (University of Massachusetts Medical School, Worcester, MA, USA), rMATS v4.1.2 (University of California, Los Angeles, CA, USA), CIRCexplorer2 v2.3.8 (University of California, Los Angeles, CA, USA), edgeR v3.40.2 (Bioconductor, Fred Hutchinson Cancer Research Center, Seattle, WA, USA), and custom Python/R/Shell scripts. (A) Volcano plot of DEGs; (B) KEGG pathway enrichment of DE-mRNAs; (C) GO enrichment of DE-mRNAs. Top 10 categories of MF, BP and CC including high Stress_response_to_copper_ion [GO:1990169], Response_to_copper_ion [GO:0046688], Killing_of_cells_of_another_organism [GO:0031640], Ceramide_biosynthetic_process [GO:0046513], Stress_response_to_metal_ion [GO:0097501], Mitotic_spindle_assembly_checkpoint_signaling [GO:0007094], Mitochondrial_transport [GO:0006839], Lipid_modification [GO:0030258], Protein_acetylation [GO:0006473], Peptidyl-lysine_modification [GO:0018205], Intracellular_anatomical_structure [GO:0005622], Mitochondrion [GO:0005739], Cytoplasm [GO:0005737], Intracellular_membrane-bounded organelle [GO:0043231], Intracellular_organelle [GO:0043229], Membrane-bounded_organelle [GO:0043227], Organelle [GO:0043226], Condensed_chromosome [GO:0000793], Histone_acetyltransferase_complex [GO:0000123], Kinetochore [GO:0000776], Sphingolipid_delta-4_desaturase activity [GO:0042284], Flavin-linked_sulthydryl oxidase activity [GO:0016971], Thiol_oxidase_activity [GO:0016972], Thiolester_hydrolase_activity [GO:0016790], Thiosulfate_sulfurtransferase_activity [GO:0004792], Oxidoreductase activity [GO:0016717], N-acyltransferase_activity [GO:0016410], Exonuclease_activity [GO:0004527], 3′-5′_exonuclease_activity [GO:0008408], Protein-disulfide_reductase_activity [GO:0015035]; (D–F) GO enrichment chord diagrams for downregulated DEGs: biological process (BP) (D), cellular component (CC) (E), and molecular function (MF) (F).
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Figure 4. Bioinformatic analysis for metabolomics after exposure to PS-MPs with sizes of 100 nm and 1 μm. Gene/transcript quantification was performed using StringTie v2.2.3 and Ballgown software v2.26.0 (Johns Hopkins University, Baltimore, MD, USA), while circRNA quantification utilized STAR v2.7.10b (Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA) and CIRCexplorer2 software v2.3.8 (University of California, Los Angeles, CA, USA). (A) Principal component analysis of all the samples; (B) Heatmap of metabolites in nematodes for different treatments; (C) Volcano plot showing differentially expressed metabolites; (D) KEGG classification analysis.
Figure 4. Bioinformatic analysis for metabolomics after exposure to PS-MPs with sizes of 100 nm and 1 μm. Gene/transcript quantification was performed using StringTie v2.2.3 and Ballgown software v2.26.0 (Johns Hopkins University, Baltimore, MD, USA), while circRNA quantification utilized STAR v2.7.10b (Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA) and CIRCexplorer2 software v2.3.8 (University of California, Los Angeles, CA, USA). (A) Principal component analysis of all the samples; (B) Heatmap of metabolites in nematodes for different treatments; (C) Volcano plot showing differentially expressed metabolites; (D) KEGG classification analysis.
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Figure 5. Effects of PS-MPs on lipid metabolism in C. elegans. (A) Fat accumulation (n ≥ 30 worms per group); (B) Pharyngeal pumping frequency (n ≥ 30 worms per group); (C) qPCR of lipid-related transcripts comparing 100 nm (100-PS) and 1 μm (1000-PS) PS-MPs (n = 3 samples/group); (D) PS-MP-induced fat accumulation abolished in RNAi strains targeting acdh-1 RNAi, ech-6 RNAi, hach-1 RNAi, and sur-5 (n ≥ 30 worms per group); (E) Reduced mitochondrial dysfunction with PS-MP exposure assessed by R6G staining; (F–H) Fat accumulation in the F1 ((F); n ≥ 31), F2 ((G); n ≥ 34), and across F0–F2 generations (H) of C. elegans. Asterisks denote statistical significance: * p < 0.05 and ** p < 0.01.
Figure 5. Effects of PS-MPs on lipid metabolism in C. elegans. (A) Fat accumulation (n ≥ 30 worms per group); (B) Pharyngeal pumping frequency (n ≥ 30 worms per group); (C) qPCR of lipid-related transcripts comparing 100 nm (100-PS) and 1 μm (1000-PS) PS-MPs (n = 3 samples/group); (D) PS-MP-induced fat accumulation abolished in RNAi strains targeting acdh-1 RNAi, ech-6 RNAi, hach-1 RNAi, and sur-5 (n ≥ 30 worms per group); (E) Reduced mitochondrial dysfunction with PS-MP exposure assessed by R6G staining; (F–H) Fat accumulation in the F1 ((F); n ≥ 31), F2 ((G); n ≥ 34), and across F0–F2 generations (H) of C. elegans. Asterisks denote statistical significance: * p < 0.05 and ** p < 0.01.
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Figure 6. The mechanisms of lipid metabolism affected by the two particle sizes of PS-MPs in the exposure groups.
Figure 6. The mechanisms of lipid metabolism affected by the two particle sizes of PS-MPs in the exposure groups.
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Table 1. Primer information.
Table 1. Primer information.
GenePrimer SequencePrimer Size (bp)
act-1F: CAATGAGCTTCGTGTTGCCC
R: AGGGAGAGGACAGCTTGGAT		153
ech-6F: TCTATGCCGGAGAGAAGGCT
R: CAACGCTGAGTACCTCCTGC		82
acdh-1F: TCTTTGCGGATACTGTTCGT
R: CGTCACAATCGGGCTCATTT		95
hach-1F: AAGGGTGCCGAGCCATTCTC
R: CCGCTAATTCTGGCCTCTACAAT		150
sur-5F: GCGGTGTAGAAATGCTCGGA
R: CCATGCCCTCTTCGACAAGT		147
acox-1.4F: TGATAACCCGGATCTCACCG
R: GCGGGCGAGCTTCTCAC		94
pmp-5F: ACGGAATTGACAACCCAGATCA
R: TCTCCCACACTCGTACTCCA		135
asns-2F: TCGCAAGTTGTCCAGAAGACA
R: GGGCTGTTCCTTGAAGTGGT		143
dpm-1F: TCGTTTGCACGTGGAGAATTT
R: CCTGTCACGATGTCGAGCTTAT		116
gst-28F: CTTAAAGACGGCGCCCCA
R: TGTTGGCAAGGTAGCGGATT		97
mboa-3F: CTGTTTGGCACGGAGTTTCG
R: TTGAGCGACGGAAGGTTTGA		90
ttm-5F: GCTCGACTGAAACGAAAGCC
R: ATGGTGGAGGAACCCTTCAA		87
ttx-7F: TCGTGTTCAGTTCGGCGAT
R: GCCAAACGAACGGTGTCCTC		94
cest-1.1F: TGAGCAATGCAACGAAAACTT
R: CCCTCCACCATGGACAATCA		140
fil-2F: GTACTTGGAGTAAAGCCGACGA
R: CGCTGAGTGGGATGAGAGAA		81
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Qu, Z.; Feng, X.; Wang, Y.; Wang, R.; Liu, N. Size-Dependent Disruption of Lipid Metabolism by Polystyrene Micro- and Nanoplastics in Caenorhabditis elegans Revealed Through Multi-Omics and Functional Genetic Validation. Toxics 2026, 14, 170. https://doi.org/10.3390/toxics14020170

AMA Style

Qu Z, Feng X, Wang Y, Wang R, Liu N. Size-Dependent Disruption of Lipid Metabolism by Polystyrene Micro- and Nanoplastics in Caenorhabditis elegans Revealed Through Multi-Omics and Functional Genetic Validation. Toxics. 2026; 14(2):170. https://doi.org/10.3390/toxics14020170

Chicago/Turabian Style

Qu, Zhi, Xihua Feng, Yalu Wang, Rui Wang, and Nan Liu. 2026. "Size-Dependent Disruption of Lipid Metabolism by Polystyrene Micro- and Nanoplastics in Caenorhabditis elegans Revealed Through Multi-Omics and Functional Genetic Validation" Toxics 14, no. 2: 170. https://doi.org/10.3390/toxics14020170

APA Style

Qu, Z., Feng, X., Wang, Y., Wang, R., & Liu, N. (2026). Size-Dependent Disruption of Lipid Metabolism by Polystyrene Micro- and Nanoplastics in Caenorhabditis elegans Revealed Through Multi-Omics and Functional Genetic Validation. Toxics, 14(2), 170. https://doi.org/10.3390/toxics14020170

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