DOI: 10.5061/dryad.fn2z34v78
title: In vivo exposure of mixed microplastic particles in mice and its impacts on the murine gut microbiome and metabolome

description: Microplastics (MPs) are emerging environmental contaminants due to
 increasing global plastic production and waste. Microplastics, defined as
 plastic particles less than 5 mm in diameter, are formed through
 degradation of larger plastics via sunlight, weathering, and microbes.
 These plastic compounds are widely detected in water, soil, food, as well
 as human stool and blood. The gut microbiome, often referred to as our
 second genome, is important in human health and is the primary point of
 contact for orally ingested microplastics. To investigate the impact of
 ingested MPs on the gut microbiome and the metabolome, 8 weeks-old male
 and female C57/BL6 mice were orally gavaged mixed plastic (5 um) exposure
 consisting of polystyrene, polyethylene, and the
 biodegradable/biocompatible plastic, poly- (lactic-co-glycolic acid) twice
 a week for 4 weeks at 0, 2, or 4 mg/week (n = 8/group). Fecal pellets were
 collected for bacterial DNA extraction and metagenomic shotgun sequencing,
 and serum was subjected to targeted and untargeted metabolomics. MPs
 exposure resulted in significant sex-specific and dose-dependent changes
 to the gut microbiome composition along with substantial regulation of the
 predicted metabolic pathways. Untargeted metabolomics in serum showed that
 a low MPs dose displayed a more prominent effect on key metabolic pathways
 such as amino acid metabolism, mitochondrial function, and inflammation.
 Additionally, SCFA-targeted metabolomics showed significant changes in
 neuroprotective SCFAs levels in both sexes by MPs exposure. In conclusion,
 our study has demonstrated that microplastics dysregulate the gut
 microbiome and serum metabolome, providing critical insights into
 potential human disease risks associated with microplastic contamination.
  
description: # In vivo exposure of mixed microplastic particles in mice and its impacts
 on the murine gut microbiome and metabolome Dataset DOI:
 [10.5061/dryad.fn2z34v78](https://doi.org/10.5061/dryad.fn2z34v78) ##
 Description of the data and file structure This data set contains the data
 and codes needed to replicate analyses for the testing of the hypothesis
 of mixed microplastic particles differentially regulating the murine gut
 microbiome and the serum metabolome. To investigate the impact of ingested
 MPs on the gut microbiome and the metabolome, 8 weeks-old male and female
 C57/BL6 mice were orally gavaged mixed plastic (5 um) exposure consisting
 of polystyrene, polyethylene, and the biodegradable/biocompatible plastic,
 poly- (lactic-co-glycolic acid) twice a week for 4 weeks at 0, 2, or 4
 mg/week (n = 8/group).  Fecal pellets were collected for bacterial DNA
 extraction and metagenomic shotgun sequencing, and serum was subjected to
 targeted and untargeted metabolomics. Data set includes both raw and
 filtered count of bacterial taxa and associated predictive functional
 analysis from the metagenomic shotgun sequencing as well as raw values
 from both targeted (SCFA) and untargeted metabolomics from serum. MPs
 exposure resulted in significant sex-specific and dose-dependent changes
 to the gut microbiome composition along with substantial regulation of the
 predicted metabolic pathways. Untargeted metabolomics in serum showed that
 a low MPs dose displayed a more prominent effect on key metabolic pathways
 such as amino acid metabolism, mitochondrial function, and inflammation.
 Additionally, SCFA-targeted metabolomics showed significant changes in
 neuroprotective SCFAs levels in both sexes by MPs exposure. ### Files and
 variables **Bioinformatics R-script (.R files)**
 Code(bonferroni).R, Code(FDR).R, Kyle_normalize_untargeted_data.R, Kyle_untargeted_ANOVA_DUNCAN.R, Kyle_untargeted_ANOVA_FDR.R, One_way_ANOVA.R, PCA___elipses.R, PCA_plotting.R, Targeted_metabolite_ANOVA_boxplot.R, Untargeted_boxplot.R, up_down_barplot.R These .R files were all utilized throughout this project to generate the bioinformatics and associated visualization plots. **Raw sequencing files (.zip and .tar)** Sample columns are labeled with sample number followed by time course duration (ex. 1.4wk is sample 1 for 4 weeks time point group where wk signifies week) Archive.zip, fasta.tar, fastq.tar Fasta.tar contains three folders that contain the .log files of the initial screening and trimming (sequence data preparation) logs that were done by Diversigen Inc during the initial steps of the metagenomic shotgun sequencing (Step0, Step1, and Step2). The three .fn files contained within this .tar file are the raw output files of each trimming and preparation steps from Step_0, Step1, and Step_2. Fastq.tar contains .fq files which are the raw nucleotide sequences from the metagenomic shotgun sequencing after the original files were trimmed and prepared. .fq files are designated in a similar manner to the sample ID in the various raw counts files (ex. 1.4wk_1.fq is sample 1 for 4 weeks time point group where wk signifies week and 1 for forward read vs 2 for reverse read). **Raw targeted SCFA metabolomics dataset** These files contain the raw targeted SCFA metabolomics data set from this project. SCFA_raw_data_MPS_Calibration_curve.csv, SCFA_raw_data_MPS_Raw_Data.csv, SCFA_raw_data_MPS_Results.csv, SCFA_raw_data_MPS_Serum.csv **Raw count and relative abundance files (.txt files)** Sample columns are labeled with sample number followed by time course duration (ex. 1.4wk is sample 1 for 4 weeks time point group where wk signifies week) All_Levels_Filtered_Table_(relative_abundance).txt, All_levels_taxa_data_(count_data).txt, Alpha_Diversity_Table.txt, Kegg_Enzyme_(count_data).txt, Kegg_Enzyme_(relative_abundance).txt, Kegg_Enzyme_Bray-Curtis_distance_matrix.txt, Kegg_Enzymes_(count_data).txt, Kegg_Enzymes_(relative_abundance).txt, Kegg_level-2_pathways_(count_data).txt, Kegg_level-2_pathways_(relative_abundance).txt, Kegg_level-3_pathways_(count_data).txt, Kegg_level-3_pathways_(relative_abundance).txt, Kegg_modules_(count_data).txt, Kegg_modules_(relative_abundance).txt, Kegg_Modules_distance_matrix.txt, Kegg_Orthology_(count_data).txt, Kegg_Orthology_Groups_(count_data).txt, Species_Bray-Curtis_Distance_matrix.txt These .txt files contain either the raw or relative abundance values associated with the microbiome (and predictive) data sets from the metagenomic shotgun sequencing output. All data sets are formatted as sample groups in the columns and experimental parameters of interest in rows. **Microbiome associated stratified raw files (.tsv)** Sample columns are labeled with sample number followed by time course duration (ex. 1.4wk is sample 1 for 4 weeks time point group where wk signifies week) taxatable-class-absolute.tsv, taxatable-class-relative.tsv, taxatable-class-short-absolute.tsv, taxatable-class-short-relative.tsv, taxatable-family-absolute.tsv, taxatable-family-relative.tsv, taxatable-family-short-absolute.tsv, taxatable-family-short-relative.tsv, taxatable-genus-absolute.tsv, taxatable-genus-relative.tsv, taxatable-genus-short-absolute.tsv, taxatable-genus-short-relative.tsv, taxatable-kingdom-absolute.tsv, taxatable-kingdom-relative.tsv, taxatable-kingdom-short-absolute.tsv, taxatable-kingdom-short-relative.tsv, taxatable-order-absolute.tsv, taxatable-order-relative.tsv, taxatable-order-short-absolute.tsv, taxatable-order-short-relative.tsv, taxatable-phylum-absolute.tsv, taxatable-phylum-relative.tsv, taxatable-phylum-short-absolute.tsv, taxatable-phylum-short-relative.tsv, taxatable-species-absolute.tsv, taxatable-species-relative.tsv, taxatable-species-short-absolute.tsv, taxatable-species-short-relative.tsv, taxatable-strain-absolute.tsv, taxatable-strain-relative.tsv, taxatable-strain-short-absolute.tsv, taxatable-strain-short-relative.tsv These data sets contain microbiome associated datasets stratified by various parameters of interest (species specification and sample depth). All data sets are formatted as sample groups in the columns and experimental parameters of interest in rows. **Alternative sources to access data** Metabolomics Workbench data repository (metabolomics data set):  Project ID ST004200 (untargeted metabolomics) and ST004201 (targeted SCFA metabolomics) **Data set source** Diversigen Inc. (sequencing company)