Dataset Information

Comparative transcriptomic analysis of Pseudomonas aeruginosa isolates from ICU patients with acute and chronic pneumonia

ABSTRACT: In this study, a comparative analysis was performed on two clinical Pa strains from pneumonia patients, 1) an acute strain (CMC-115) and 2) a chronic multidrug- and carbapenem-resistant strain (CMC-097), with distinct phenotypic and genetic characteristics. A transcriptome analysis using both the Pseudomonas DNA GeneChip microarray and Illumina RNA-Seq technologies was carried out for both strains at early-stationary growth phase in laboratory culture. The comparative transcriptomic analysis identified 134 genes differentially expressed ≥4.0-fold by both technologies between the two strains, which included virulence genes such as flagellar, pyoverdine, and phenazine genes, that were higher in the acute strain, CMC-115, and type 3 secretory system (T3SS) and pyochelin biosynthesis genes, that were higher in the chronic strain, CMC-097. In particular, the DNA microarrays suggested and the RNA-Seq analysis confirms the type 3 secretory system genes were completely missing from the acute strain, CMC-115. The combined analysis using the RNA-Seq and DNA microarray methods also identified important genes that were either missing or highly divergent from the Reference PAO1 genome used for the DNA microarray design. For example, the RNA-Seq data identified an operon containing several multidrug resistance genes: aacA27, beta-lactamase (blaOXA-2), qacΔE, sul1, and GNAT-N, in the chronic strain, CMC-097.

ORGANISM(S): Pseudomonas aeruginosa

PROVIDER: GSE180499 | GEO | 2021/07/23

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Pathogenic mycobacteria have the ability to survive within macrophages and persist inside granulomas composed of host immune cells. The complex host-pathogen interactions that determine the outcome of a mycobacterial infection process result in marked alterations of the host gene expression profile. Here we used the zebrafish model to investigate the specificity of the host response to infections with two mycobacterium strains that give distinct disease outcomes: an acute disease with early lethality or a chronic disease with granuloma formation, caused by Mycobacterium marinum strains Mma 20 and E11, respectively. We performed a microarray study of different stages of disease progression in adult zebrafish and found that the acute and the chronic strains evoked partially overlapping host transcriptome signatures, despite that they induce profoundly different disease phenotypes. Both strains affected many signaling cascades, including Wnt and Tlr pathways. Interestingly, the strongest differences were observed at the initial stage of the disease. The immediate response to the acute strain was characterized by higher expression of genes encoding MHC class I proteins, matrix metalloproteinases, transcription factors, cytokines and other common immune response proteins. In contrast, small GTPase and histone gene groups showed higher expression in response to the chronic strain. We also found that nearly 1,000 mycobacterium-responsive genes overlapped between the expression signatures of infected zebrafish adults and embryos at different stages of granuloma formation. Since adult zebrafish possess an adaptive immune system similar to mammals and zebrafish embryos rely solely on innate immunity, this overlap indicates a major contribution of the innate component of the immune system in the response to mycobacterium infection. Taken together, our comparison of the transcriptome responses involved in acute versus chronic infections and in the embryonic versus adult situation provides important new leads for investigating the mechanism of mycobacterial pathogenesis.

Dataset Information

Comparative transcriptomic analysis of Pseudomonas aeruginosa isolates from ICU patients with acute and chronic pneumonia

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets