Long-term Low-dose Nanoplastic Exposure Induces Neurotoxicity with Oxidative Brain Damage-Transcriptomics Data
Description
This study aims to investigate the long-term effects of chronic exposure to polystyrene nanoplastics (PS-NPs) on systemic molecular networks, with a particular focus on neurodegenerative. Transcriptomic analysis revealed significant upregulation of pathways associated with Alzheimer disease, Parkinson disease, even cardiovascular disease pathways like diabetic cardiomyopathy which is quite surprising, indicating systemic molecular network reorganization driven by prolonged PS-NPs exposure. Sample Information: Animal model: 5-week-old male C57BL/6J mice Experimental duration: 17 months Group design: Control group (n=3): standard sterile drinking water PS-NPs group (n=3): drinking water supplemented with polystyrene nanoplastics Exposure route: continuous oral administration via drinking water; water bottles replaced weekly Tissue collected: brain tissue Endpoint: upon the first natural death among all mice, the remaining animals were euthanized
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Bioinformatics Analysis Pipeline 1. Data quality control Raw FASTQ reads were processed using fastp to remove adapters, poly-N and low-quality reads, generating high-quality clean data. Q20, Q30 and GC content were calculated. 2. Read alignment Clean reads were aligned to the reference genome using HISAT2 (2.2.1) with splice-aware alignment. 3. Gene expression quantification Gene expression levels were quantified using featureCounts (2.0.6) and normalized as FPKM. 4. Differential expression analysis For samples with biological replicates, DESeq2 (1.42.0) was used. For samples without biological replicates, edgeR (4.0.16) was applied. Significantly differentially expressed genes were defined as |log₂(fold change)| ≥ 1 and adjusted p-value (Benjamini-Hochberg) ≤ 0.05. 5. Enrichment analysis GO and KEGG enrichment analyses were performed using clusterProfiler (4.8.1), with significance threshold of adjusted p-value < 0.05.
Institutions
- Sichuan UniversitySichuan, Chengdu