Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Early transcriptional landscapes of Chlamydia trachomatis-infected epithelial cells at single cell resolution

ABSTRACT: Early transcriptional landscapes of Chlamydia trachomatis-infected epithelial cells at single cell resolution

PROVIDER: PRJNA548292 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Early transcriptional landscapes of Chlamydia trachomatis-infected epithelial cells at single cell resolution

Project description:Here we examined host cell gene expression in response to Chlamydia trachomatis infection by applying scRNA-Seq to in vitro C. trachomatis-infected HEp-2 epithelial cells and time-matched uninfected cells over the early chlamydial developmental cycle (3, 6 and 12 hours). We collected 264 single cells across both conditions all time points. The aims of the experiment were examining host cell responses to infection at single cell resolution, and identifying early host cell signatures of infection.

2019-11-19 | GSE132525 | GEO

Transcriptional profiling of human epithelial cells infected with trachoma isolates of Chlamydia trachomatis

Project description:Hep-2C cells were infected with A/2497 or B/Tunis-864 strains of Chlamydia trachomatis to compare changes in host gene expression

2019-12-31 | GSE133358 | GEO

Progesterone activates multiple innate immune pathways in Chlamydia trachomatis-infected endocervical cells

Project description:In this project we examined the in-vitro effect of female sex hormones (estradiol and progesterone at average physiological concentrations) during a infection mediated by Chlamydia trachomatis serovar D, on the gene expression of human endometrial cell line ECC-1 The effects of the female sex hormones progesterone and oestradiol while infected by Chlamydia trachomatis were examined at two timepoints.

2011-08-02 | E-GEOD-31149 | biostudies-arrayexpress

Quantitative phospho-proteomic analysis of human endocervical epithelial cells infected with Chlamydia trachomatis

Project description:Human A2EN endocervical epithelial cells infected with Chlamydia trachomatis

2022-11-03 | MSV000090636 | MassIVE

Heat shock-induced transcriptomic response in Chlamydia trachomatis

Project description:Heat shock-induced transcriptomic response in Chlamydia trachomatis

2021-12-08 | GSE173366 | GEO

Progesterone activates multiple innate immune pathways in Chlamydia trachomatis-infected endocervical cells

2011-08-03 | GSE31149 | GEO

Microarray analysis of long noncoding RNA expression profile in HeLa cells infected Chlamydia trachomatis

Project description:Chlamydia trachomatis (C. trachomatis) is an intracellular bacterium, and is one of the main pathogens that cause sexually transmitted infections worldwide. Long non-coding RNAs (lncRNAs) have become vital regulators in many biological processes. However, few studies have shown that lncRNAs take part in the pathogenesis of C. trachomatis. Here, we used microarrays to study the expression profiles of lncRNAs and mRNAs in HeLa cells at 12, 24, and 40 hours pot-infection (hpi). Our study provides evidence that lncRNAs are involved in the interaction between C. trachomatis and hosts.

2021-07-28 | GSE165628 | GEO

Cell type-intrinsic differences in the host transcriptome of Chlamydia trachomatis-infected primary human endocervical epithelial cells and vaginal epithelial cells [HVE_seq]

Project description:To investigate the role of cell type-intrinsic gene expression to fibrotic sequelae of Chlamydia trachomatis (Ct) infection of the upper female genital tract, we compared the transcriptomic response of primary human endocervical epithelial cells (HCECs, see GSE198272) to that in vaginal epithelial cells (HVEs).

2023-09-27 | GSE228774 | GEO

Genome-wide analysis of Chlamydia trachomatis-infected cells

Project description:Chlamydia trachomatis is the most common sexually transmitted infection and the bacterial agent of trachoma globally. C. trachomatis undergoes a biphasic developmental cycle involving an infectious elementary body and a replicative reticulate body. Little is currently known about the expression of host cell mRNAs, lncRNAs, and miRNAs at different stages of C. trachomatis development. Here, we performed RNA-seq and miR-seq on HeLa cells infected with C. trachomatis serovar E at 20 hpi and 44 hpi with or without IFN-γ treatment. Our study identified and validated differentially expressed host cell mRNAs, lncRNAs, and miRNAs during infection. Infection at 20 hpi showed the most differential upregulation of both coding and non-coding genes while infection at 44 hpi in the presence of IFN-γ resulted in a dramatic downregulation of a large proportion of genes. Using RT-qPCR, we validated the top 5 stage-specific upregulated mRNAs and miRNAs. One of the commonly expressed miRNAs at all three stages, miR-193b-5p, showed significant expression in clinical serum samples of C. trachomatis-infected patients as compared to sera from healthy controls and HIV-1-infected patients. Furthermore, at 20 hpi we observed significant upregulation of antigen processing and presentation, and T helper cell differentiation pathways whereas T cell receptor, mTOR, and Rap1 pathways were modulated at 44 hpi. Treatment with IFN-γ at 44 hpi showed the regulation of cytokine-cytokine receptor interaction, FoxO signaling, and Ras signaling pathways. Our study documents a role for the stage-specific transcriptional manipulation of the host cell genome and important signaling pathways that are necessary for the survival of pathogen and could serve as potential biomarkers in the diagnosis and management of the disease.

2021-01-13 | GSE158814 | GEO

Early Transcriptional Landscapes of Chlamydia trachomatis-Infected Epithelial Cells at Single Cell Resolution.

Project description:Chlamydia are Gram-negative obligate intracellular bacterial pathogens responsible for a variety of disease in humans and animals worldwide. Chlamydia trachomatis causes trachoma in disadvantaged populations, and is the most common bacterial sexually transmitted infection in humans, causing reproductive tract disease. Antibiotic therapy successfully treats diagnosed chlamydial infections, however asymptomatic infections are common. High-throughput transcriptomic approaches have explored chlamydial gene expression and infected host cell gene expression. However, these were performed on large cell populations, averaging gene expression profiles across all cells sampled and potentially obscuring biologically relevant subsets of cells. We generated a pilot dataset, applying single cell RNA-Seq (scRNA-Seq) to C. trachomatis infected and mock-infected epithelial cells to assess the utility, pitfalls and challenges of single cell approaches applied to chlamydial biology, and to potentially identify early host cell biomarkers of chlamydial infection. Two hundred sixty-four time-matched C. trachomatis-infected and mock-infected HEp-2 cells were collected and subjected to scRNA-Seq. After quality control, 200 cells were retained for analysis. Two distinct clusters distinguished 3-h cells from 6- and 12-h. Pseudotime analysis identified a possible infection-specific cellular trajectory for Chlamydia-infected cells, while differential expression analyses found temporal expression of metallothioneins and genes involved with cell cycle regulation, innate immune responses, cytoskeletal components, lipid biosynthesis and cellular stress. We find that changes to the host cell transcriptome at early times of C. trachomatis infection are readily discernible by scRNA-Seq, supporting the utility of single cell approaches to identify host cell biomarkers of chlamydial infection, and to further deconvolute the complex host response to infection.

| S-EPMC6877545 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data