DOI: 10.5061/dryad.sf7m0cgfg
title: Data from: Puerarin alleviates atherosclerosis via the inhibition of Prevotella copri and its trimethylamine production

description: Objective Puerarin (PU) is a natural compound that exhibits limited oral
 bioavailability but has shown promise in the treatment of atherosclerosis
 (AS). However, the precise mechanisms underlying its therapeutic effects
 remain incompletely understood. This study aimed to investigate the
 effects of PU and its mechanisms in mitigating AS in both mice and humans.
 Design The impact of PU on AS was examined in ApoE-/- mice fed a high-fat
 diet (HFD) and in human patients with carotid artery plaque. To explore
 the causal link between PU-associated gut microbiota and AS, faecal
 microbiota transplantation (FMT) and mono-colonization of mice with
 Prevotella copri (P. copri) were employed. Results PU alleviated AS by
 modulating the gut microbiota, as evidenced by alterations in gut
 microbiota composition and the amelioration of AS following FMT from
 PU-treated mice into ApoE-/- mice fed HFD. Specifically, PU reduced the
 abundance of P. copri, which exacerbated AS by producing trimethylamine
 (TMA). Prolonged mono-colonization of P. copri undermines the beneficial
 effects of PU on AS. In clinical, the plaque scores of AS patients were
 positively correlated with the abundance of P. copri and plasma
 trimethylamine-N-oxide (TMAO) levels. A 1-week oral intervention with PU
 effectively decreased P. copri levels and reduced TMAO concentrations in
 patients with carotid artery plaque. Conclusion PU may provide therapeutic
 benefits in combating AS by targeting P. copri and its production of TMA.
description: The RNA extraction, sequencing, and library construction were
 performed according to previously published methods with minor
 modifications.<sup>[1,2]</sup> In brief, total RNA was
 extracted from samples using commercial kits (Guangdong Magigene
 Biotechnology Co., Ltd, China), and RNA quantity was measured using Qubit
 3.0 (Thermo Fisher Scientific, MA, USA) and Nanodrop One (Thermo Fisher
 Scientific, MA, USA) instruments. Whole mRNAseq libraries were generated
 using the NEB Next® Ultra™ Nondirectional RNA Library Prep Kit for
 Illumina® (New England Biolabs, USA), following the manufacturer’s
 recommended protocol. The library was then sequenced using an Illumina
 NovaSeq 6000 platform. For mRNA analysis, raw data underwent quality
 control and the reads were mapped to a reference genome. After sequence
 alignment, gene expression levels were quantified and analyzed, and
 differentially expressed genes between two conditions/groups were
 identified using edgeR (version 3.16.5). The resulting p-values were
 adjusted using Benjamini and Hochberg’s approach to control the false
 discovery rate. Candidate genes were defined as those with FDR≤0.05 and
 |log2(fold change)|≥1, and these genes were subjected to enrichment
 analysis. Finally, differentially expressed genes were analyzed by GO
 (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway
 enrichment analysis using the cluster Profiler (version 3.4.4) package.
 Enrichment analysis was considered significant when FDR≤0.05.
 <strong>References</strong> [1]
 Hao Y, Liao X, Wang X, Lao S, Liao W. The biological regulatory activities
 of Flammulina velutipes polysaccharide in mice intestinal microbiota,
 immune repertoire and heart transcriptome. Int J Biol Macromol.
 2021;185:582-591. [2] Lavelle A, Hoffmann TW, Pham HP,
 Langella P, Guédon E, Sokol H. Baseline microbiota composition modulates
 antibiotic-mediated effects on the gut microbiota and host. Microbiome.
 2019;7(1):111.
description: # Data from: Puerarin Alleviates Atherosclerosis via the Inhibition of
 Prevotella copri and its Trimethylamine Production
 [https://doi.org/10.5061/dryad.sf7m0cgfg
 ](https://doi.org/10.5061/dryad.sf7m0cgfg) **Description of the Data and
 file structure** The file contains the results of RNA-seq analysis from
 the study titled "Puerarin Alleviates Atherosclerosis via the
 Inhibition of Prevotella copri and Its Trimethylamine Production."
 The samples include normal Prevotella copri cultures (Control) and
 Prevotella copri cultures treated with Puerarin (Treament). RNA was
 extracted and sequenced using next-generation sequencing. The raw data was
 analyzed using bioinformatics tools. RNA seq data from 5 normal Prevotella
 copri cultures and 5 Prevotella copri cultures treated with Puerarin. The
 comparison report contains the following information: Result
 |——1_Quality_Control\ Data Quality Control |————data_stat.xls Data Quality
 Statistics Table |——2_Alignment\ Alignment Statistics
 |————rRNA_alignment_stat.xls Reads Alignment Statistics for Samples
 Compared to Ribosomal References |————ref_alignment_stat.xls Reads
 Alignment Statistics for Samples Compared to Reference Genome
 |——3_Sample_statistics\ Sample Correlation Analysis |————count.xls Reads
 Count Results Statistics Table |————fpkm.xls FPKM Results Statistics Table
 |——4_Diff_statistics\ Differential Expression Analysis |————Diff_exp\
 |——————Treament.vs.Control\ |————————Treament.vs.Control.xls Differential
 Expression Genes Statistics Table Between Samples
 |————————Treament.vs.Control.fil.xls Significant Differential Genes
 Statistics Table Between Samples |————Heatmap\
 |——————Treament.vs.Control\Gene list |————GO\ |——————GO_annotation.xl
 Functional Annotation Results of Differential Genes
 |——————Control.vs.Treament\ |————————DEGs_in_all_level.xls GO Term
 Distribution Statistics of Differential Genes |————————DEGs_in_level2.xls
 GO Term (Level 2) Statistics of Differential Genes
 |————————enrichment\ Gene Ontology (GO) enrichment analysis results
 |——————————*.GO_enrichment.xls BP, CC, MF Enrichment Analysis Statistics
 Table |——————————*.GO_enrichment.fil.xls Filtered BP, CC, MF Enrichment
 Analysis Statistics Table |——————————*.gse.xls GSEA Statistics Table for
 BP, CC, MF |——————————*.gse.fil.xls Filtered GSEA Statistics Table for BP,
 CC, MF |————KEGG\ |——————ko_annotation.xls KEGG Pathway Annotation Results
 of Differential Genes |——————Control.vs.Treament\
 |————————DEGs_in_A_Class.xls Statistics Table of Differential Genes in
 KEGG A Class |————————DEGs_in_ko.xls Statistics Table of Differential
 Genes in KEGG Pathways |————————enrichment\ Pathway enrichment analysis
 using KEGG pathways |——————————kegg_enrichment.xls KEGG Enrichment
 Statistics Table of Differential Genes |——————————kegg_enrichment.fil.xls
 Filtered KEGG Enrichment Statistics Table of Differential Genes
 |——————————KEGG_gse.xls GSEA Statistics Table |——————————KEGG_gse.fil.xls
 Filtered GSEA Statistics Table |————————KEGG_Graph\\* KEGG Pathway Maps of
 Differential Genes |——5_Advanced_analysis\ |————operons.xls Operon
 Structure Prediction Results |————transcripts.xls Transcript Structure
 Prediction Results  **Usage notes** The file is compatible with Microsoft
 Excel.