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Gene Expression in Prokaryotic Microbial Assemblages Across Salinity Gradients in the Columbia River Coastal Margin

ABSTRACT: Analysis of microbial gene expression in response to physical and chemical gradients forming in the Columbia River, estuary, plume and coastal ocean was done in the context of the environmental data base. Gene expression was analyzed for 2,234 individual genes that were selected from fully sequenced genomes of 246 prokaryotic species (bacteria and archaea) as related to the nitrogen metabolism and carbon fixation. Seasonal molecular portraits of differential gene expression in prokaryotic communities during river-to-ocean transition were created using freshwater baseline samples (268, 270, 347, 002, 006, 207, 212).

ORGANISM(S): Archaea uncultured prokaryote Bacteria

PROVIDER: GSE18303 | GEO | 2010/09/10

SECONDARY ACCESSION(S): PRJNA118035

REPOSITORIES: GEO

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Gene Expression in Prokaryotic Microbial Assemblages Across Salinity Gradients in the Columbia River Coastal Margin

Project description:Analysis of microbial gene expression in response to physical and chemical gradients forming in the Columbia River, estuary, plume and coastal ocean was done in the context of the environmental data base. Gene expression was analyzed for 2,234 individual genes that were selected from fully sequenced genomes of 246 prokaryotic species (bacteria and archaea) as related to the nitrogen metabolism and carbon fixation. Seasonal molecular portraits of differential gene expression in prokaryotic communities during river-to-ocean transition were created using freshwater baseline samples (268, 270, 347, 002, 006, 207, 212). Total RNA was isolated from 64 filtered environmental water samples collected in the Columbia River coastal margin during 4 research cruises (14 from August, 2007; 17 from November, 2007; 18 from April, 2008; and 16 from June, 2008), and analyzed using microarray hybridization with the CombiMatrix 4X2K format. Microarray targets were prepared by reverse transcription of total RNA into fluorescently labeled cDNA. All samples were hybridized in duplicate, except samples 212 and 310 (hybridized in triplicate) and samples 336, 339, 50, 152, 157, and 199 (hybridized once). Sample location codes: number shows distance from the coast in km; CR, Columbia River transect in the plume and coastal ocean; NH, Newport Hydroline transect in the coastal ocean at Newport, Oregon; AST and HAM, Columbia River estuary locations near Astoria (river mile 7-9) and Hammond (river mile 5), respectively; TID, Columbia River estuary locations in the tidal basin (river mile 22-23); BA, river location at Beaver Army Dock (river mile 53) near Quincy, Oregon; UP, river location at mile 74.

2010-09-10 | E-GEOD-18303 | biostudies-arrayexpress

Denitrifying bacterial assemblages respond to environmental conditions of a shallow estuary

Project description:Molecular analysis of dissimilatory nitrite reductase genes (nirS) was conducted using a customized microarray containing 165 nirS probes (archetypes) to identify members of sedimentary denitrifying communities. The goal of this study was to examine denitrifying community responses to changing environmental variables over spatial and temporal scales in the New River Estuary (NRE), NC, USA. Multivariate statistical analyses revealed three denitrifier assemblages and uncovered “generalist” and “specialist” archetypes based on the distribution of archetypes within these assemblages. Generalists, archetypes detected in all samples during at least one season, were commonly world-wide found in estuarine and marine ecosystems, comprised 11-29% of the abundant NRE archetypes. Archetypes found in a particular site, “specialists”, were found to co-vary based on site specific conditions. Archetypes specific to the lower estuary in winter were designated Cluster I and significantly correlated by sediment Chl a and porewater Fe2+. A combination of specialist and more widely distributed archetypes formed Clusters II and III, which separated based on salinity and porewater H2S, respectively. The co-occurrence of archetypes correlated with different environmental conditions highlights the importance of habitat type and niche differentiation among denitrifying communities and supports the essential role of individual community members in overall ecosystem function.

2017-05-02 | GSE98190 | GEO

Columbia River coastal margin 'omics

Project description:Coupled metagenomic and metatransciptomic study of the Columbia River coastal margin salinity gradient

| PRJEB9136 | ENA

Prokaryotic Proteogenomics

Project description:Prokaryotic Proteogenomics

| PRJNA66995 | ENA

An optimized RNA amplification method for prokaryotic expression profiling analysis

Project description:Conventional prokaryotic RNA labeling method usually requires large amounts of starting materials and tends to generate high background signals. Recently, two novel methods based on amplification systems were introduced. Here, we compared three alternative strategies: direct labeling method, ployadenylation-involved oligo-dT priming amplification method and random priming amplification method (hereafter referred to as DL, PAOD and RPA method in this article) for prokaryotic RNA labeling employing the expression profiling investigation in Escherichia coli (E. coli) heat shock model.

2009-07-25 | GSE17074 | GEO

Columbia River coastal margin 'omics metagenomic assembly

Project description:EMG produced TPA metagenomics assembly of the Coupled metagenomic and metatransciptomic study of the Columbia River coastal margin salinity gradient (Columbia River coastal margin 'omics) data set

| PRJEB22509 | ENA

Prokaryotic Single-Cell RNA Sequencing by In Situ Combinatorial Indexing

Project description:We present Prokaryotic Expression-profiling by Tagging RNA In Situ and sequencing (PETRI-seq), a high-throughput prokaryotic scRNA-seq pipeline. We demonstrated that PETRI-seq effectively barcoded single bacterial cells in a species-mixing experiment with E. coli (MG1655) and S. aureus (USA300). Within the S. aureus population, we found rare prophage induction in 0.04% of cells. We further demonstrated that PETRI-seq was able to distinguish between E. coli growth phases based on mRNA expression patterns by combining stationary E. coli with exponential E. coli in multiple experiments.

2020-05-25 | GSE141018 | GEO

prokaryotic metagenome

Project description:prokaryotic metagenome Metagenome

| PRJNA608846 | ENA

Pacific salmon gill samples

Project description:This SuperSeries is composed of the following subset Series: GSE22171: Pacific salmon gill samples: fate tracking in river, sampled in ocean GSE22177: Pacific salmon gill samples: fate tracking in river GSE22347: Pacific salmon gill samples: fate tracking at spawning grounds Refer to individual Series

2010-12-31 | E-GEOD-22179 | biostudies-arrayexpress

Open ocean and coastal strains of the N2-fixing cyanobacterium UCYN-A have distinct transcriptomes

Project description:Although N2 fixation can occur in free-living cyanobacteria, the unicellular endosymbiotic cyanobacterium Candidatus Atelocyanobacterium thalassa (UCYN-A) is considered to be a dominant N2-fixing species in marine ecosystems. Four UCYN-A sublineages are known from partial nitrogenase (nifH) gene sequences. However, few studies have investigated their habitat preferences and regulation by their respective hosts in open-ocean versus coastal environments. Here, we compared UCYN-A transcriptomes from oligotrophic open-ocean versus nutrient-rich coastal waters. UCYN-A1 metabolism was more impacted by habitat changes than UCYN-A2. However, across habitats and sublineages genes for nitrogen fixation and energy production were highly transcribed. Curiously these genes, critical to the symbiosis for the exchange of fixed nitrogen for fixed carbon, maintained the same schedule of diel expression across habitats and UCYN-A sublineages, including UCYN-A3 in the open-ocean transcriptomes. Our results undersore the importance of nitrogen fixation in UCYN-A symbioses across habitats, with consequences for community interaction and global biogeochemical cycles.

2023-02-23 | GSE206403 | GEO

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