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Next Generation Sequencing Facilitates Quantitative Analysis of control and PS micro-/nanoplastics stressed E. faecalis OG1RF , E. faecalis OG1RS , E. coli DH5α and pCF10 plasmid Transcriptomes

ABSTRACT: Next Generation Sequencing Facilitates Quantitative Analysis of control and PS micro-/nanoplastics stressed E. faecalis OG1RF , E. faecalis OG1RS , E. coli DH5α and pCF10 plasmid Transcriptomes

PROVIDER: PRJNA1267009 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR33690900_1.fastq.gz	Fastqsanger.gz
	SRR33690900_2.fastq.gz	Fastqsanger.gz
	SRR33690901_1.fastq.gz	Fastqsanger.gz
	SRR33690901_2.fastq.gz	Fastqsanger.gz
	SRR33690902_1.fastq.gz	Fastqsanger.gz

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Next Generation Sequencing Facilitates Quantitative Analysis of control and PS micro-/nanoplastics stressed E. faecalis OG1RF , E. faecalis OG1RS , E. coli DH5α and pCF10 plasmid Transcriptomes

Project description:The goals of this study are to use Next-generation sequencing (NGS) to detect bacterial mRNA profiles of E. faecalis OG1RF , E. faecalis OG1RS , E. coli DH5α and plasmid pCF10, and their mRNA response under the exposure of different sizes of Polystyrene (PS), including 20 nm, 120 nm and 1 μm. The concentrations were 0.1, 1, 10 mg/L for every size of PS. The group without adding PS was the control group. Each concentration was conducted in triplicate. By comparing the mRNA profiles of experimental groups and control group, the effects of these 3 sizes of PS on transcriptional levels can be revealed. Illumina HiSeq PE150 was applied. NEBNextő Ultra II Directional RNA Library Prep Kit for Illumina was used for library construction. Then, the sequence reads consisting of at least 85% bases were progressively trimmed at the 3’-ends until a quality value ≥ 20 were kept. Downstream analyses were performed using the generated clean reads of no shorter than 75 bp. The clean reads of each sample were aligned to the E. faecalis OG1RF reference genome (NC_017316.1), E. coli DH5α reference genome (GCF_000982435.1), and plasmid pCF10 reference genome (NC_006827.2) using Bowtie2. RSeQC was used to calculate the strand-specific coverage for each gene, and to analyze the differential expression in triplicate bacterial cell cultures. The statistical analyses and visualization were conducted using CummeRbund package in R (http://compbio.mit.edu/cummeRbund/). Gene expression was calculated as fragments per kilobase of a gene per million mapped reads (FPKM, a normalized value generated from the frequency of detection and the length of a given gene.

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