Plant Metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA588037 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10431748_1.fastq.gz | Fastqsanger.gz | |||
| SRR10431749_1.fastq.gz | Fastqsanger.gz | |||
| SRR10431750_1.fastq.gz | Fastqsanger.gz | |||
| SRR10431751_1.fastq.gz | Fastqsanger.gz | |||
| SRR10431752_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:Microarrays have become a powerful tool for DNA-based molecular diagnostics and identification of pathogens. However, most of them target a limited range of organisms and are generally based on only one or very few genes for organism identification. Although such microarrays are proven tools for species identification, they suffer from the fact that identification is only possible for organisms for which probes were specifically pre-developed. Furthermore, this approach often leads to problems with taxonomic-level resolution with insufficient diagnostic differences between closely related taxa found in the commonly used DNA sequences. An alternative strategy is to use the hybridisation pattern generated by many different anonymous markers distributed over the entire genome for identification based on comparison to a type database. We realised this strategy using a high density microarray containing 95,000 different 13-mer probes. Here, we demonstrate the specificity of our microarray based on results obtained with nine different bacterial species and strains. The hybridisation patterns allowed clear differentiation at the strain and even variant level. The reproducibility of our system was high as shown by high correlation coefficients between replicates, despite the occurrence of mismatch hybridisation. The results indicate the potential for identification of all bacterial taxa at the subspecies level using our universal microarray.
2010-03-16 | GSE15391 | GEO
Project description:Microarrays have become a powerful tool for DNA-based molecular diagnostics and identification of pathogens. However, most of them target a limited range of organisms and are generally based on only one or very few genes for organism identification. Although such microarrays are proven tools for species identification, they suffer from the fact that identification is only possible for organisms for which probes were specifically pre-developed. Furthermore, this approach often leads to problems with taxonomic-level resolution with insufficient diagnostic differences between closely related taxa found in the commonly used DNA sequences. An alternative strategy is to use the hybridisation pattern generated by many different anonymous markers distributed over the entire genome for identification based on comparison to a type database. We realised this strategy using a high density microarray containing 95,000 different 13-mer probes. Here, we demonstrate the specificity of our microarray based on results obtained with nine different bacterial species and strains. The hybridisation patterns allowed clear differentiation at the strain and even variant level. The reproducibility of our system was high as shown by high correlation coefficients between replicates, despite the occurrence of mismatch hybridisation. The results indicate the potential for identification of all bacterial taxa at the subspecies level using our universal microarray. Hybridisation patterns of DNA from bacterial type strains (E. coli strains K12 and B, Pantoea agglomerans strains ATCC27155T and C9-1, Pantoea stewartii pv stewartii strain DC283, Salmonella Typhimurium strains LT2 and DT204 and Micrococcus luteus) were compared to each other. Using GeneSpring v7.3.1, cluster analyses were performed as well as ANOVA in order to determine the more discriminative probes out of our 95,000-probe panel.
2010-05-06 | E-GEOD-15391 | biostudies-arrayexpress
Project description:Investigation of whole genome gene expression level changes in the bacterial wilt pathogen Ralstonia solanacearum, strain GMI1000 at 20°C and 28°C in culture and in planta. The tropical strain GMI1000 cannot wilt tomato plants at 20°C although it can cause full-blown disease at 28°C.
2012-01-15 | GSE33657 | GEO
Project description:Investigation of whole genome gene expression level changes in the bacterial wilt pathogen Ralstonia solanacearum, strain UW551 at 20°C and 28°C in culture and in planta. The temperatel strain UW551 can wilt and cause full-blown disease on tomato plants at 28°C as well as at 20°C.
2012-01-15 | GSE33661 | GEO
Project description:A method based on a modified broad-range PCR and an oligonucleotide microarray for the simultaneous detection and identification of 12 bacterial pathogens at the species level.
2009-08-31 | GSE17221 | GEO
Project description:<p>Traveler's diarrhea (TD) is caused by enterotoxigenic Escherichia coli (ETEC), other pathogenic gram-negative pathogens, norovirus and some parasites. Nevertheless, standard diagnostic methods fail to identify pathogens in more than 30% of TD patients, so it is predicted that new pathogens or groups of pathogens may be causative agents of disease. A comprehensive metagenomic study of the fecal microbiomes from 23 TD patients and seven healthy travelers was performed, all of which tested negative for the known etiologic agents of TD in standard tests. Metagenomic reads were assembled and the resulting contigs were subjected to semi-manual binning to assemble independent genomes from metagenomic pools. Taxonomic and functional annotations were conducted to assist identification of putative pathogens. We extracted 560 draft genomes, 320 of which were complete enough to be enough characterized as cellular genomes and 160 of which were bacteriophage genomes. We made predictions of the etiology of disease in individual subjects based on the properties and features of the recovered cellular genomes. Three subtypes of samples were observed. First were four patients with low diversity metagenomes that were predominated by one or more pathogenic E. coli strains. Annotation allowed prediction of pathogenic type in most cases. Second, five patients were co-infected with E. coli and other members of the Enterobacteriaceae, including antibiotic resistant Enterobacter, Klebsiella, and Citrobacter. Finally, several samples contained genomes that represented dark matter. In one of these samples we identified a TM7 genome that phylogenetically clustered with a strain isolated from wastewater and carries genes encoding potential virulence factors. We also observed a very high proportion of bacteriophage reads in some samples. The relative abundance of phage was significantly higher in healthy travelers when compared to TD patients. Our results highlight that assembly-based analysis revealed that diarrhea is often polymicrobial and includes members of the Enterobacteriaceae not normally associated with TD and have implicated a new member of the TM7 phylum as a potential player in diarrheal disease. </p>
| phs001352 | dbGaP