Ontology highlight
ABSTRACT:
PROVIDER: PRJNA753719 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR15413440_1.fastq.gz | Fastqsanger.gz | |||
| SRR15413440_2.fastq.gz | Fastqsanger.gz | |||
| SRR15413441_1.fastq.gz | Fastqsanger.gz | |||
| SRR15413441_2.fastq.gz | Fastqsanger.gz | |||
| SRR15413442_1.fastq.gz | Fastqsanger.gz |
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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>
| phs001260 | dbGaP
Project description:Understanding constraints which shape antibiotic resistance is key for predicting and controlling drug resistance. Here, we performed high-throughput laboratory evolution of Escherichia coli. The transcriptome, resistance, and genomic profiles for the evolved strains in 48 environments were quantitatively analyzed. By analyzing the quantitative datasets through interpretable machine learning techniques, the emergence of low dimensional phenotypic states within the 192 strains was observed. Further analysis revealed the underlying biological processes responsible for the distinct states. We also report a novel constraint which leads to decelerated evolution. These findings bridge the genotypic, gene expression, and drug resistance space, and lead to a comprehensive understanding of constraints for antibiotic resistance.
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Project description:Human DNA replication relies on the activation of thousands of origins distributed along the genome. Their organization and the functional significance of their distribution remains unknown. To map large number of origins in human cells, we have localized the distribution of short nascent DNA using a high-resolution DNA tiling array platform covering 33.9Mb. Results with three different cell lines reveal that origins are very closely spaced (average interval 3-5kb), and that their positions are largely conserved among the cell lines studied. Origins are non-randomly distributed, being preferentially enriched at the 5’-end of expressed genes and at evolutionary intergenic sequences. In MCF7 cells, a strong correlation is also found between origin positioning and histone H3K4me3 and of PolII binding to chromatin. This study provides a large scale view of the organization of DNA replication origins in human chromosomes and suggests a link between this distribution and underlying chromatin features related to chromosome structure, and gene expression Keywords: nascent strand DNA, histone, Pol-II ChIP-chip.
2011-05-13 | GSE10917 | GEO
Project description:We used a DNA microarray chip covering 369 resistance types to investigate the relation of antibiotic resistance gene diversity with humans’ age. Metagenomic DNA from fecal samples of 123 healthy volunteers of four different age groups, i.e. pre-school Children (CH), School Children (SC), High School Students (HSS) and Adults (AD) were used for hybridization. The results showed that 80 different gene types were recovered from the 123 individuals gut microbiota, among which 25 were present in CH, 37 in SC, 58 in HSS and 72 in AD. Further analysis indicated that antibiotic resistance genes in groups of CH, SC and AD can be independently clustered, and those ones in group HSS are more divergent. The detailed analysis of antibiotic resistance genes in human gut is further described in the paper DNA microarray analysis reveals the antibiotic resistance gene diversity in human gut microbiota is age-related submitted to Sentific Reports
2014-01-16 | GSE54070 | GEO
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2011-05-13 | E-GEOD-10917 | biostudies-arrayexpress
Project description:A collection of 61 Salmonella enterica serovar Typhimurium (S. Typhimurium) of animal and human origin, matched as closely as possible by phage type, antimicrobial resistance pattern and place / time of isolation, and sourced from farms or hospitals in Scotland, were analysed by antimicrobial susceptibility testing, phage typing, pulsed field gel electrophoresis (PFGE), plasmid profiling and DNA microarrays. PFGE of all 61 isolates revealed ten PFGE profiles, which clustered by phage type and antibiotic resistance pattern, with human and animal isolates distributed between PFGE profiles. Analysis of 23 representative S. Typhimurium strains hybridised to a composite Salmonella DNA microarray identified a small number of specific regions of genome variation between different phage types and PFGE profiles. These variable regions of DNA were typically located within prophage-like elements. Simple PCR assays were subsequently designed to discriminate between different isolates from the same geographical region.
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