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PROVIDER: PRJNA1147001 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Total bacterial DNA was isolated from water and sediment samples from a local watershed and 16S rRNA sequences were analyzed using the Illumina MiSeq v3 platform in order to generate snapshots of bacterial community profiles.
2016-01-01 | GSE73842 | GEO
Project description:Total bacterial DNA was isolated from water and sediment samples from a local watershed and 16S rRNA sequences were analyzed using the Illumina MiSeq v3 platform in order to generate snapshots of bacterial community profiles. A total of 56 samples were collected that represent water and sediment samples from 14 sample sites over two different time points (November 18 and 25, 2011).
2016-07-03 | E-GEOD-73842 | biostudies-arrayexpress
Project description:Understanding the bacterial community structure, and their functional analysis for active bioremediation process is essential to design better and cost effective strategies. Microarray analysis enables us to simultaneously study the functional and phylogenetic markers of hundreds of microorganisms which are involved in active bioremediation process in an environment. We have previously described development of a hybrid 60-mer multibacterial microarray platform (BiodegPhyloChip) for profiling the bacterial communities and functional genes simultaneously in environments undergoing active bioremediation process (Pathak et al; Appl Microbiol Biotechnol,Vol. 90, 1739-1754). The present study involved profiling the status of bacterial communities and functional (biodegradation) genes using the developed 60-mer oligonucleotide microarray BiodegPhyloChip at five contaminated hotspots in the state of Gujarat, in western India. The expression pattern of functional genes (coding for key enzymes in active bioremediation process) at these sites was studied to understand the dynamics of biodegradation in the presence of diverse group of chemicals. The results indicated that the nature of pollutants and their abundance greatly influence the structure of bacterial communities and the extent of expression of genes involved in various biodegradation pathways. In addition, site specific factors also play a pivotal role to affect the microbial community structure as was evident from results of 16S rRNA gene profiling of the five contaminated sites, where the community structure varied from one site to another drastically.
2012-12-01 | GSE38004 | GEO
Project description:The microbiota plays a crucial role in protecting plants from pests and pathogens. The protection provided by the microbiota constitutes not just the plant’s first line of defense, but possibly its most potent one, as experimental disruptions to the microbiota cause plants to succumb to otherwise asymptomatic infections. To understand how microbial plant defense is deployed, we applied a complex and tractable plant-soil-microbiome microcosm. This system, consisting of Arabidopsis plants and a 150-member bacterial synthetic community, provides a platform for the discovery of novel bacterial plant-beneficial traits, under a realistically complex microbial community context. To identify which components of the plant microbiota are critical for plant defense, we deconstructed this microcosm top-down, removing different microbial groups from the community to examine their protective effect on the plant when challenged with the leaf pathogen Pseudomonas syringae. This process of community deconstruction revealed a critical role for the genus Bacillus in protecting the plant from infection. Using plant RNA-seq and bacterial co-culturing experiments, we demonstrated that Bacillus-provided plant protection is independent of plant immune system activation. We also show that the level of plant protection is strongly dependent on the diversity of the protective inoculum. We show that deconstructing the microbiome top-down is a powerful tool for identifying and prioritizing microbial taxa with specific functions within it.
2025-01-01 | GSE285599 | GEO
Project description:Previous molecular and mechanistic studies have identified several principles of prokaryotic transcription, but less is known about the global transcriptional architecture of bacterial genomes. Here we perform a comprehensive study of a cyanobacterial transcriptome, that of Synechococcus elongatus PCC 7942, generated by combining three high-resolution data sets: RNA sequencing, tiling expression microarrays, and RNA polymerase chromatin immunoprecipitation (ChIP) sequencing. We report absolute transcript levels, operon identification, and high-resolution mapping of 5' and 3' ends of transcripts. We identify several interesting features at promoters, within transcripts and in terminators relating to transcription initiation, elongation, and termination. Furthermore, we identify many putative non-coding transcripts. We provide a global analysis of a cyanobacterial transcriptome. Our results uncover insights that reinforce and extend the current views of bacterial transcription. RNA Sequencing of the cyanobacterium Synechococcus elongatus PCC 7942 RNA polymerase ChIP Sequencing of the cyanobacterium Synechococcus elongatus PCC 7942 Tiling Microarray of the cyanobacterium Synechococcus elongatus PCC 7942
2011-05-16 | E-GEOD-29264 | biostudies-arrayexpress
Project description:To explore the bacterial community profile of the gut of the African palm weevil and to identify the abundance and diversity of lignin degradation-associated bacteria in each gut segment.
2025-01-01 | E-MTAB-13719 | biostudies-arrayexpress
Project description:Aim: We aim to compare current (MeDIP-seq), new (Illumina Infinium 450K BeadChip) and future (PacBio) methods for whole genome DNA methylation analysis. As the interest in determination of disease methylation profiles increases, the scope, advantages and limitations of these methods requires assessment. There are key questions to answer and specific challenges to overcome. For example, how much detail/resolution is sufficient to identify regions of differential methylation and regions of biological/medical significance within a sample? How much coverage of the genome is required for accurate methylation analysis? Is it important to confirm which regions of the genome are unmethylated in addition to focusing on those that are methylated? Loss of methylation may be of equal importance within the cell since this may also contribute to disease pathogenesis. A multi-method (affinity enrichment/bisulphite-conversion based/direct sequencing of methyl-cytosine) and technology platform (Illumina HiSeq/PacBio/Illumina Infinium BeadChip) comparison will enable us to determine the strengths and weakness of each method. We propose to compare four methods using two DNA samples from the Coriell Institute for Cell Repository to assess both current and future capabilities for whole genome methylation analysis in parallel: A) MeDIP-seq using Illumina HiSeq B) Illumina Infinium HumanMethylation 450K BeadChip and C) whole genome methylation sequencing using PacBio. Existing single molecule deep bisulphite sequencing data generated previously from these same samples at the WTSI for targeted regions (30-40 genes) on the human X chromosome will be used to assess performance of each method. The methods selected for this study will generate data covering a range of resolutions from a whole genome scan to array (target defined) resolution and up to single base pair, single molecule resolution; the highest level of detail possible with methods currently available.Samples: DNA from sibling pair GM01240 (female) and GM01240 (male).Requirements: Both samples will be analysed using;A.MeDIP-seq using Illumina HiSeq (one HiSeq lane, 75bp paired end, per sample) B.Illumina Infinium HumanMethylation 450K BeadChipWe are expecting a potentially unnecessary high coverage using one HiSeq lane per sample. However, for the MeDIP procedure we do not have a multiplexing procedure in place. Our requirements for PacBio sequencing have been discussed with and will be supported by the Sequencing Technology Development group.
2013-01-22 | E-ERAD-139 | biostudies-arrayexpress
Project description:Understanding the bacterial community structure, and their functional analysis for active bioremediation process is essential to design better and cost effective strategies. Microarray analysis enables us to simultaneously study the functional and phylogenetic markers of hundreds of microorganisms which are involved in active bioremediation process in an environment. We have previously described development of a hybrid 60-mer multibacterial microarray platform (BiodegPhyloChip) for profiling the bacterial communities and functional genes simultaneously in environments undergoing active bioremediation process (Pathak et al; Appl Microbiol Biotechnol,Vol. 90, 1739-1754). The present study involved profiling the status of bacterial communities and functional (biodegradation) genes using the developed 60-mer oligonucleotide microarray BiodegPhyloChip at five contaminated hotspots in the state of Gujarat, in western India. The expression pattern of functional genes (coding for key enzymes in active bioremediation process) at these sites was studied to understand the dynamics of biodegradation in the presence of diverse group of chemicals. The results indicated that the nature of pollutants and their abundance greatly influence the structure of bacterial communities and the extent of expression of genes involved in various biodegradation pathways. In addition, site specific factors also play a pivotal role to affect the microbial community structure as was evident from results of 16S rRNA gene profiling of the five contaminated sites, where the community structure varied from one site to another drastically. Agilent one-color CGH experiment and one-color Gene Expresssion expereiment,Organism: Genotypic designed Agilent-17159 Genotypic designed Agilent Multibacterial 8x15k Array , Labeling kits: Agilent Genomic DNA labeling Kit (Part Number: 5190-0453) and Agilent Quick Amp Kit PLUS (Part number: 5190-0442).
2012-12-01 | E-GEOD-38004 | biostudies-arrayexpress
Project description:Spatial transcriptome uncovers rich coordination of metabolism and signaling in bacterial community (data 2)
2023-03-01 | GSE213531 | GEO