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ABSTRACT: Evolution of streamlined genome variants of Acinetobacter baylyi ADP1

PROVIDER: PRJNA989175 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR25072700_1.fastq.gz	Fastqsanger.gz
	SRR25072700_2.fastq.gz	Fastqsanger.gz
	SRR25072800_1.fastq.gz	Fastqsanger.gz
	SRR25072800_2.fastq.gz	Fastqsanger.gz
	SRR25072701_1.fastq.gz	Fastqsanger.gz

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The effect of transcription factor AtfA on gene expression

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Next Generation Sequencing Facilitates Quantitative Analysis of E. coli K-12 LE392, P. putida KT2440, and Acinetobacter baylyi ADP1 Transcriptomes under various antidepressant exposure

Project description:The goals of this study are to use Next-generation sequencing (NGS)to detect bacterial mRNA profiles of E. coli K-12 LE392, P. putida KT2440 and Acinetobacter baylyi ADP1 in response to various antidepressant concentrations for 2 h, in triplicate, using Illumina HiSeq 2500.The NGS QC toolkit (version 2.3.3) was used to treat the raw sequence reads to trim the 3’-end residual adaptors and primers, and the ambiguous characters in the reads were removed. 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. coli reference genome (NC_000913), Pseudomonas putida KT2440 genome (NCBI:txid160488) and Acinetobacter baylyi ADP1 genome (NCBI:txid62977) using SeqAlto (version 0.5). Cufflinks (version 2.2.1) 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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Project description:The goals of this study are to use Next-generation sequencing (NGS) to detect bacterial mRNA profiles of wild-type Acinetobacter baylyi ADP1 and Pwh1266 plasmid, and their mRNA response under the exposure of four artificial sweeteners, including saccharin, sucralose, aspartame, and acesulfame potassium. 3 mg/L of each sweetener was used to treat the mixture of bacteria cell and plasmid. The group without dosing any artificial sweeteners was the control group. Each sample was conducted in triplicate. By comparing the mRNA profiles of experimental groups and control group, the effects of these four artificial sweeteners on the transcriptional levels can be revealed. Illumina HiSeq 2500 was applied. The NGS QC toolkit (version 2.3.3) was used to treat the raw sequence reads to trim the 3’-end residual adaptors and primers, and the ambiguous characters in the reads were removed. 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 Acinetobacter baylyi ADP1 reference genome (NC_005966) using SeqAlto (version 0.5). Cufflinks (version 2.2.1) was used to calculate the strand-specific coverage for each gene, and to analyze the differential expression in triplicate bacterial cell culture. 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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Project description:The goals of this study are to use SWATH-MS to detect bacterial proteomic profiles of wild-type Acinetobacter baylyi ADP1, and its protein response under the exposure of non-antibiotic pharmaceuticals, including ibuprofen, naproxen, gemfibrozil, diclofenac, propanolol, and iopromide. The concentrations were 0.5 mg/L for ibuprofen, naproxen, gemfibrozil, diclofenac, propanolol, and 1.0 mg/L for iopromide. The group without dosing pharmaceutical was the control group. Each concentration was conducted in triplicate. By comparing the proteomic profiles of experimental groups and control group, the effects of non-antibiotic pharmaceuticals on translational levels can be revealed.

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