Ontology highlight
ABSTRACT:
PROVIDER: PRJNA962005 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR24308230_1.fastq.gz | Fastqsanger.gz | |||
| SRR24308230_2.fastq.gz | Fastqsanger.gz | |||
| SRR24308231_1.fastq.gz | Fastqsanger.gz | |||
| SRR24308231_2.fastq.gz | Fastqsanger.gz | |||
| SRR24308232_1.fastq.gz | Fastqsanger.gz |
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Project description:Based on a simple E.coli growth inhibition assay, the authors trained a model capable of identifying antibiotic potential in compounds structurally divergent from conventional antibiotic drugs. One of the predicted active molecules, Halicin (SU3327), was experimentally validated in vitro and in vivo.
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https://github.com/ersilia-os/eos4e40
2024-04-22 | MODEL2404080001 | BioModels
Project description:The goals of this study are to use SWATH-MS to detect bacterial proteomic profiles of E. coli K-12 LE392 with conjugative RP4 plasmid, P. putida KT2440, and their protein response under the exposure of six kinds of non-antibiotic pharmaceuticals, i.e., ibuprofen (ibu), naproxen (nap), gemfibrozil (gem), iopromide (iop), diclofenac (dic), propanolol (pro). Each treatment condition was conducted in triplicate. By comparing the proteomic profiles of experimental groups and control group, the effects of these non-antibiotic pharmaceuticals on translational levels can be revealed.
2022-02-15 | PXD012642 | Pride
Project description:We analyzed gene expression during conjugative transfer of plasmid RP4. Pairs of rifampicin-susceptible (RifS) and -resistance (RifR) strains of Pseudomonas putida KT2440 were conjugated for 10 minute on filter membrane in the presence of rifampicin to discriminate the expression changes in the donor and recipient cells.
2020-03-13 | GSE146879 | GEO
Project description:Purpose: We investigate the evolutionary footprints of a bacteria-plasmid association consisting of Escherichia coli K-12 MG1655 and plasmid RP4 undergoing a long-term sub-MIC antibiotic stress. Methods: Bacterial mRNA profiles of evolved RP4-carrying strains (E:H:p) and ancestral RP4-carrying strains (A:H:p) were generated by deep sequencing on an Illumina Hiseq platform. The sequence reads that passed quality filters were analyzed by Burrows–Wheeler Aligner (BWA), followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays Results: Using an optimized data analysis workflow, we mapped about 15 million sequence reads of E:H:p and 12 million sequence reads of A:H:p to the E. coli MG1655 genome (GCF_000801205.1) and differential expressed genes were identified with TopHat workflow. RNA-seq data showed that approximately 15% of the transcripts showed differential expression between the E:H:p and A:H:p strains, with a fold change ≥1 and p value <0.005. Altered expression of 26 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Data analysis with bowtie and TopHat workflows provided complementary insights in transcriptome profiling. Conclusions: Our study showed the coevolved bacteria-plasmid pairs has colonization traits superior to the wild-type parent strain. Antibiotic stress was necessary for bacterial evolution and evolved strains mostly employed transcriptional modifications to reduce plasmid-related cost in evolutionary adaptations. Several genes related to chromosome-encoded efflux pumps were transcriptionally upregulated, while most plasmid-harboring genes were downregulated based on RNA gene sequencing. These transcriptional modifications endowed evolved strains with resistant phenotype modifications, including the enhanced bacterial growth and biofilm formation.
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Project description:Horizontal gene transfer (HGT) is the major mechanism responsible for spread of antibiotic resistance. Antibiotic treatment has been suggested to promote HGT, either by directly affecting the conjugation process itself or by selecting for conjugations subsequent to DNA transfer. However, recent research suggests that the effect of antibiotic treatment on plasmid conjugation frequencies, and hence the spread of resistance plasmids, may have been overestimated. We addressed the question by quantifying transfer proteins and conjugation frequencies of a blaCTX-M-1 encoding IncI1 resistance plasmid in Escherichia coli MG1655 in the presence and absence of therapeutically relevant concentrations of cefotaxime (CTX). Analysis of the proteome by iTRAQ labeling and liquid chromatography tandem mass spectrometry revealed that Tra proteins were significantly up regulated in the presence of CTX. The up-regulation of the transfer machinery was confirmed at the transcriptional level for five selected genes. The CTX treatment did not cause induction of the SOS39 response as revealed by absence of significantly regulated SOS associated proteins in the proteome and no significant up-regulation of recA and sfiA genes. The frequency of plasmid conjugation, measured in an antibiotic free environment, increased significantly when the donor was pre-grown in broth containing CTX compared to growth without this drug, regardless of whether blaCTX-M-1 was located on the plasmid or in trans on the chromosome. The results shows that antibiotic treatment can affect expression of a plasmid conjugation machinery and subsequent DNA transfer.
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Project description:<p>The study of antimicrobial resistance (AMR) in infectious diarrhea has generally been limited to cultivation, antimicrobial susceptibility testing and targeted PCR assays. When individual strains of significance are identified, whole genome shotgun (WGS) sequencing of important clones and clades is performed. Genes that encode resistance to antibiotics have been detected in environmental, insect, human and animal metagenomes and are known as "resistomes". While metagenomic datasets have been mined to characterize the healthy human gut resistome in the Human Microbiome Project and MetaHIT and in a Yanomani Amerindian cohort, directed metagenomic sequencing has not been used to examine the epidemiology of AMR. Especially in developing countries where sanitation is poor, diarrhea and enteric pathogens likely serve to disseminate antibiotic resistance elements of clinical significance. Unregulated use of antibiotics further exacerbates the problem by selection for acquisition of resistance. This is exemplified by recent reports of multiple antibiotic resistance in Shigella strains in India, in Escherichia coli in India and Pakistan, and in nontyphoidal Salmonella (NTS) in South-East Asia. We propose to use deep metagenomic sequencing and genome level assembly to study the epidemiology of AMR in stools of children suffering from diarrhea. Here the epidemiology component will be surveillance and analysis of the microbial composition (to the bacterial species/strain level where possible) and its constituent antimicrobial resistance genetic elements (such as plasmids, integrons, transposons and other mobile genetic elements, or MGEs) in samples from a cohort where diarrhea is prevalent and antibiotic exposure is endemic. The goal will be to assess whether consortia of specific mobile antimicrobial resistance elements associate with species/strains and whether their presence is enhanced or amplified in diarrheal microbiomes and in the presence of antibiotic exposure. This work could potentially identify clonal complexes of organisms and MGEs with enhanced resistance and the potential to transfer this resistance to other enteric pathogens.</p> <p>We have performed WGS, metagenomic assembly and gene/protein mapping to examine and characterize the types of AMR genes and transfer elements (transposons, integrons, bacteriophage, plasmids) and their distribution in bacterial species and strains assembled from DNA isolated from diarrheal and non-diarrheal stools. The samples were acquired from a cohort of pediatric patients and controls from Colombia, South America where antibiotic use is prevalent. As a control, the distribution and abundance of AMR genes can be compared to published studies where resistome gene lists from healthy cohort sequences were compiled. Our approach is more epidemiologic in nature, as we plan to identify and catalogue antimicrobial elements on MGEs capable of spread through a local population and further we will, where possible, link mobile antimicrobial resistance elements with specific strains within the population.</p>
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Project description:This project conducted proteomics on A.baylyi ADP1, E. coli K12 and P. putita KT2440 after treated with a few commonly-prescribed antidepressant (duloxetine, sertraline, fluoxetine, bupropion, escitalopram and agomelatine). The results with help to reveal how those antidepressants can promote the transfer of antibiotic resistance genes in those treated bacteria.
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