Ontology highlight
ABSTRACT:
PROVIDER: PRJNA802121 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Metagenomic Epidemiology of Antibiotic Resistance in Infectious Diarrhea
| PRJNA358637 | ENA
Project description:Metagenomic Epidemiology of Antibiotic Resistance in Infectious Diarrhea
| PRJNA358636 | ENA
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:Molecular epidemiology of gram-negative bacteria and genetic of antibiotic resistance
| PRJNA374794 | ENA
Project description:Using Nanopore sequencing, our study has revealed a close correlation between genomic methylation levels and antibiotic resistance rates in Acinetobacter Baumannii. Specifically, the combined genome-wide DNA methylome and transcriptome analysis revealed the first epigenetic-based antibiotic-resistance mechanism in A. baumannii. Our findings suggest that the precise location of methylation sites along the chromosome could provide new diagnostic markers and drug targets to improve the management of multidrug-resistant A. baumannii infections.
2023-09-01 | E-MTAB-13272 | biostudies-arrayexpress
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
Project description:In a given bacterial population, antibiotic treatment kills a large portion of the population, while a small, tolerant subpopulation survives. Tolerant cells disrupt the efficacy of antibiotic treatment and increase the likelihood that a population gains antibiotic resistance. Antibiotic tolerance is different from resistance because tolerant cells cannot grow and replicate in the presence of the antibiotic, but when the antibiotic is removed, they begin to propagate. When a population becomes resistant, the antibiotic becomes ineffective, which is a major health concern. Since antibiotic tolerance often leads to antibiotic resistance, we have taken a systems biology approach to examine how regulatory networks respond to antibiotic stress so that cells can survive and recover after antibiotic treatment. We have compared gene expression with and without ampicillin in E. coli.
2020-12-04 | GSE156896 | GEO
Project description:Cationic antimicrobial peptides (CAPs) are promising novel alternatives to conventional antibacterial agents, but the overlap in resistance mechanisms between small-molecule antibiotics and CAPs is unknown. Does evolution of antibiotic resistance decrease (cross-resistance) or increase (collateral sensitivity) susceptibility to CAPs? We systematically addressed this issue by studying the susceptibilities of a comprehensive set of antibiotic resistant Escherichia coli strains towards 24 antimicrobial peptides. Strikingly, antibiotic resistant bacteria frequently showed collateral sensitivity to CAPs, while cross-resistance was relatively rare. We identified clinically relevant multidrug resistance mutations that simultaneously elevate susceptibility to certain CAPs. Transcriptome and chemogenomic analysis revealed that such mutations frequently alter the lipopolysaccharide composition of the outer cell membrane and thereby increase the killing efficiency of membrane-interacting antimicrobial peptides. Furthermore, we identified CAP-antibiotic combinations that rescue the activity of existing antibiotics and slow down the evolution of resistance to antibiotics. Our work provides a proof of principle for the development of peptide based antibiotic adjuvants that enhance antibiotic action and block evolution of resistance.
2018-03-29 | GSE96706 | GEO
Project description:We used a DNA microarray chip covering 369 resistance types to investigate the relation of antibiotic resistance gene diversity with humansM-bM-^@M-^Y 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 The antibiotic resistance gene microarray is custom-designed (Roche NimbleGen), based on a single chip containing 3 internal replicated probe sets of 12 probes per resistance gene, covering the whole 315K 12-plex platform spots.
2014-01-16 | E-GEOD-54070 | biostudies-arrayexpress
Project description:With the global increase in the use of carbapenems, several gram-negative bacteria have acquired carbapenem resistance, thereby limiting treatment options. Klebsiella pneumoniae is one of such notorious pathogen that is being widely studied to find novel resistance mechanisms and drug targets. These antibiotic-resistant clinical isolates generally harbor many genetic alterations, and identification of causal mutations will provide insights into the molecular mechanisms of antibiotic resistance. We propose a method to prioritize mutated genes responsible for antibiotic resistance, in which mutated genes that also show significant expression changes among their functionally coupled genes become more likely candidates. For network-based analyses, we developed a genome-scale co-functional network of K. pneumoniae genes, KlebNet (www.inetbio.org/klebnet). Using KlebNet, we could reconstruct functional modules for antibiotic-resistance, and virulence, and retrieved functional association between them. With complementation assays with top candidate genes, we could validate a gene for negative regulation of meropenem resistance and four genes for positive regulation of virulence in Galleria mellonella larvae. Therefore, our study demonstrated the feasibility of network-based identification of genes required for antimicrobial resistance and virulence of human pathogenic bacteria with genomic and transcriptomic profiles from antibiotic-resistant clinical isolates.
2018-06-10 | GSE115539 | GEO