Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1119375 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:During initial colonization of the airways, MAH form microaggregates composed of 3-20 bacteria on human respiratory epithelial cells, which provides an environment for phenotypic changes leading to efficient mucosal invasion. DNA microarray was employed to identify genes associated with the microaggregate phenotype. Bacteria were incubated with Hep-2 epithelial cells for 24 hrs to form microaggregates or incubated in tissue culture media alone as the control (planktonic bacteria). Bacterial RNA was isolated, purified using MicrobeEnrich, and amplified using Abmbion's Bacterial MessageAMP kit. RNA was hybridized to Affymetrix custom made mycobacterium avium 104 microarrays
2014-02-15 | E-GEOD-55010 | biostudies-arrayexpress
Project description:To determine whether flow alters the gene expression of planktonic P. aeruginosa, we designed a long microfluidic channel that enabled us to expose bacteria to flow for significant lengths of time and then be fixed as they exit the channel. The experiments mimic the kinds of shear flows characteristic of a wide variety of confined flow configurations. Using this microfluidic system, we performed bulk RNA-Seq analysis of planktonic bacteria that flowed for 55 min at a shear rate of 20 per second, and compared gene expression of this population with a control population of planktonic bacteria under similar conditions with no flow.
2024-07-03 | GSE271426 | GEO
Project description:Epiphytic and planktonic bacteria diversity Targeted Locus (Loci)
| PRJNA231013 | ENA
Project description:The transcriptome of Actinobacillus pleuropneumoniae biofilms was compared to the transcriptome of planktonic bacteria
2013-05-20 | GSE43821 | GEO
Project description:The transcriptome of Actinobacillus pleuropneumoniae biofilms was compared to the transcriptome of planktonic bacteria
2013-05-20 | GSE43820 | GEO
Project description:Connecting genes to phenotypic traits in bacteria is often challenging because of a lack of environmental cues in laboratory settings. However, laboratory-based model ecosystems offer a means to better account for natural conditions compared to standard planktonic cultures, aiding in the linking of genotypes and phenotypes. Here, we present a simple, cost-effective, laboratory-based model ecosystem to study aerobic methane-oxidizing bacteria (methanotrophs). This system, referred to as the gradient syringe, is made by inoculating bacteria into semi-solid agarose held within a disposable syringe. Empty space at one end of the syringe is flushed with methane gas, while the other end is open to the atmosphere through a sterile filter. We show this system replicates the methane-oxygen counter gradient typically found in the natural soil environment of methanotrophs. Culturing the methanotroph Methylomonas sp. strain LW13 in this system produced a distinct horizontal band at the intersection of the counter gradient, which we discovered was due not to increased cell growth at this location but instead to an increased amount of extracellular polymeric substances (EPS). We also discovered that different methanotrophic taxa formed EPS bands with distinct locations and morphologies when grown in the methane-oxygen counter gradient. By comparing transcriptomic data from LW13 growing within and surrounding this EPS band, we identified genes implicated in cell growth and EPS formation within the gradient syringe, and validated the involvement of these genes with knockout strains. This work highlights the use of a laboratory-based model ecosystem that more closely mimics the natural environment to uncover methanotroph phenotypes missing from standard planktonic cultures, and link these phenotypes their genetic determinants.
2023-10-05 | GSE243827 | GEO
Project description:Purpose: The goal of this study was to use RNA-seq to define the Klebsiella pneumoniae transcriptome recorded under 5 different experimental conditions, and to identify signature genes of each condition by comparing global transcriptional profiles. Methods: mRNA profiles were generated for Klebsiella pneumoniae CH1034 clinical isolate, in triplicate, by deep sequencing. Total RNAs were harvested from bacteria cultured at 37°C in M63B1 minimal media under different conditions: (i) planktonic aerobic condition at OD 620nm=0.250 (exponential growth-phase), (ii) overnight planktonic aerobic condition (stationnary growth-phase), (iii) biofilm in a flow-cell chamber after 7 hours of incubation (7-hours old biofilm), (iv) biofilm in a flow-cell chamber after 13 hours of incubation (13-hours old biofilm), (v) bacteria self-dispersed from biofilm recovered in the flow-cell effluent (biofilm-dispersed bacteria). Ribosomal RNAs were removed using the Bacteria Ribo-Zero Magnetic kit (Epicentre Biotechnologies). Libraries were prepared using the TruSeq Stranded mRNA Sample Preparation kit (Illumina), and 50bp single-reads were obtained by HiSeq 2000 (Illumina).The sequence reads that passed FastQC quality filters were mapped to the CH1034 genome using BurrowsâWheeler Aligner (BWA) (0.7.12-r1039 version). The transcript levels were determined using HTSeq-count (0.6.1p1 version) with union mode followed by DESeq (1.16.0 version) analysis. qRTâPCR validation was performed using SYBR Green assays. Results: We found that each condition has a specific transcriptional profile, and we identify 4 robust signature genes for each. Conclusion: Our study represents the first detailed analysis of K. pneumoniae transcriptomes under different experimental conditions generated by RNA-seq technology. The data reported here should permit the dissection of complex biologic functions involved in the transition between the sessile and planktonic modes of growth. Determination of the transcriptional profiling of Klebsiella pneumoniae under 5 different experimental conditions. mRNA profiles were generated for bacteria under exponential planktonic growth-phase, stationary planktonic growth-phase, 7 hours-old biofilm, 13 hours-old biofilm and biofilm-dispersed modes, each in three biological replicates, by deep sequencing using Illumina HiSeq
2016-03-03 | E-GEOD-71754 | biostudies-arrayexpress
Project description:Opioids such as morphine have many beneficial properties as analgesics, however, opioids may induce multiple adverse gastrointestinal symptoms. We have recently demonstrated that morphine treatment results in significant disruption in gut barrier function leading to increased translocation of gut commensal bacteria. However, it is unclear how opioids modulate the gut homeostasis. By using a mouse model of morphine treatment, we studied effects of morphine treatment on gut microbiome. We characterized phylogenetic profiles of gut microbes, and found a significant shift in the gut microbiome and increase of pathogenic bacteria following morphine treatment when compared to placebo. In the present study, wild type mice (C57BL/6J) were implanted with placebo, morphine pellets subcutaneously. Fecal matter were taken for bacterial 16s rDNA sequencing analysis at day 3 post treatment. A scatter plot based on an unweighted UniFrac distance matrics obtained from the sequences at OTU level with 97% similarity showed a distinct clustering of the community composition between the morphine and placebo treated groups. By using the chao1 index to evaluate alpha diversity (that is diversity within a group) and using unweighted UniFrac distance to evaluate beta diversity (that is diversity between groups, comparing microbial community based on compositional structures), we found that morphine treatment results in a significant decrease in alpha diversity and shift in fecal microbiome at day 3 post treatment compared to placebo treatment. Taxonomical analysis showed that morphine treatment results in a significant increase of potential pathogenic bacteria. Our study shed light on effects of morphine on the gut microbiome, and its role in the gut homeostasis.
2018-04-16 | E-MTAB-5546 | biostudies-arrayexpress