Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA322599 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR3579120_1.fastq.gz | Fastqsanger.gz | |||
| SRR3579120_2.fastq.gz | Fastqsanger.gz | |||
| SRR3579130_1.fastq.gz | Fastqsanger.gz | |||
| SRR3579130_2.fastq.gz | Fastqsanger.gz | |||
| SRR3579131_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 32 |
Similar Datasets
Project description:Next Generation Sequencing Facilitates Quantitative Analysis of HIV-1 Latency in Central Memory T Cells
| PRJNA322599 | ENA
Project description:HIV-1 persists in individuals on ART in infected central (CM), transitional (TM) and effector memory (EM) CD4+ T cells. We developed LARA (latency and reversion assay), which facilitates the examination of HIV latency reversal in CM, TM and EM subsets in a single assay. Studies with latency reversing agents (LRAs) revealed responses specific to each subset, including compounds that significantly reversed latency in all subsets but with a range of efficiency (bryostatin) to those that demonstrated subset specificity (IL-15). Significantly, LARA has allowed the demonstration that EM cells display a more activated profile compared to CM, which translated to enhanced efficiency in responsiveness to multiple LRAs and allowed the identification of mechanisms associated with the compounds that reactivate latent HIV in all subsets. Understanding the responsiveness of memory CD4+ T cells subsets to LRAs will accelerate the development of anti-latency therapy to interfering with viral persistence in vivo.
2018-01-26 | GSE94149 | GEO
Project description:HIV-1 persists in individuals on ART in infected central (CM), transitional (TM) and effector memory (EM) CD4+ T cells. We developed LARA (latency and reversion assay), which facilitates the examination of HIV latency reversal in CM, TM and EM subsets in a single assay. Studies with latency reversing agents (LRAs) revealed responses specific to each subset, including compounds that significantly reversed latency in all subsets but with a range of efficiency (bryostatin) to those that demonstrated subset specificity (IL-15). Significantly, LARA has allowed the demonstration that EM cells display a more activated profile compared to CM, which translated to enhanced efficiency in responsiveness to multiple LRAs and allowed the identification of mechanisms associated with the compounds that reactivate latent HIV in all subsets. Understanding the responsiveness of memory CD4+ T cells subsets to LRAs will accelerate the development of anti-latency therapy to interfering with viral persistence in vivo.
2018-01-26 | GSE94150 | GEO
Project description:Next Generation Sequencing Facilitates Quantitative Analysis of K562 cells treated with DMSO and TRIAC
2024-01-01 | GSE165769 | GEO
Project description:Next Generation Sequencing Facilitates Quantitative Analysis of THP-1 cells treated with DMSO and Decitabine
2024-05-10 | GSE200510 | GEO
Project description:Purpose: Next-generation sequencing (NGS) has become a powerful microscope to study cell models of HIV. The goals of this study is to analyze latent HIV infection in the TCM model of HIV latency described in Martins et al 2015 and to evaluate potential markers for HIV infection. Methods: Peripheral blood mononuclear cells were collected from 4 healthy donors. Naive CD4 T cells were isolated and utilized to generate a model of latent HIV infection. During model generation, cells were sorted and collected for RNA extraction 10 days post infection along with their uninfected counterparts. 2 days after this, cells were activated with CD3/CD28 stimulation and collected for study for a total of 16 samples from 4 donors. After cell collection, RNA was extracted from infected cells and their uninfected counterparts for deep sequencing by Expression Analysis. Sequence reads that passed quality filters were mapped using Tophat and counted using HTSeq. In addition to human transcripts, we utilized 92 ERCC spikes as negative controls. Any human gene which did not achieve at least 1 count per million reads in at least 4 samples or any ERCC that did not achieve at least 5 reads in at least 4 samples was discarded. Differential expression for activated samples was not performed, but rather used to demonstrate upregulation of T-cell activation markers along with changing to the type and abundance of HIV transcripts produced. Results: Using an custom built data analysis pipeline, 82 million reads per sample to the human genome (build hg38) and identified 13,534 human transcripts 67 ERCC spike in transcripts, and HIV NL43 transcripts were identified with the Tophat/HTSeq workflow. Differential expression analysis was performed between uninfected and latently infected cells. 826 genes were found to be differentially expressed, 275 downregulated and 551 upregulated (FDR < 0.05) with EdgeR. GO and Pathway analysis of differential expressed genes revealed significant dysregulation of genes involved in the p53 signaling pathway. Subsequent studies with pifithrin demonstrated a reduction in latently infected cell during model generation. Conclusions: This study represents the first detailed analysis of HIV latency with this cell model using next generations sequencing. These results demonstrate that the TCM model of HIV latency of Martins et al 2015 is truly reflective of HIV latency. This study also provides a framework for which to analyze future cell models of HIV latency using next generation sequencing. Finally, this work demonstrates that the p53 signaling pathway is a key pathway dysregulated in latency for this cell model with several genes dysregulated in HIV latency.
2016-11-01 | GSE81810 | GEO
Project description:Next Generation Sequencing Facilitates Quantitative Analysis of HCCC9810 cells transduced with control or KDM5C-expression vector.
2021-01-26 | GSE143781 | GEO
Project description:Next Generation Sequencing Facilitates Quantitative Analysis of MDA-MB-231 cells treated with Roscovitinen and DMSO
2024-07-25 | GSE210030 | GEO
Project description:BACKGROUND: Combination antiretroviral therapy (cART) is able to control HIV-1 viral replication, however long-lived latent infection in resting memory CD4+ T-cells persist. The mechanisms for establishment and maintenance of latent infection in resting memory CD4+ T-cells remain unclear. Previously we have shown that HIV-1 infection of resting CD4+ T-cells co-cultured with CD11c+ myeloid dendritic cells (mDC) produced a population of non-proliferating T-cells with latent infection. Here we asked whether different antigen presenting cells (APC), including subpopulations of DC and monocytes, were able to induce post-integration latent infection in resting CD4+ T-cells, and examined potential cell interactions that may be involved using RNA-seq. RESULTS: mDC (CD1c+), SLAN+ DC and CD14+ monocytes were most efficient in stimulating proliferation of CD4+ T-cells during syngeneic culture and in generating post-integration latent infection in non-proliferating CD4+ T-cells following HIV-1 infection of APC-T-cell co-cultures. In comparison, plasmacytoid DC (pDC) and B-cells did not induce latent infection in APC-T-cell co-cultures. We compared the RNA expression profiles of APC subpopulations that could and could not induce latency in non-proliferating CD4+ T-cells. Gene expression analysis, comparing the mDC, SLAN+ DC and CD14+ monocyte subpopulations to pDC identified 53 upregulated genes that encode proteins expressed on the plasma membrane that could signal to CD4+ T-cells via cell-cell interactions (32 genes), immune checkpoints (IC) (5 genes), T-cell activation (9 genes), regulation of apoptosis (5 genes), antigen presentation (1 gene) and through unknown ligands (1 gene). CONCLUSIONS: APC subpopulations from the myeloid lineage, specifically mDC subpopulations and CD14+ monocytes, were able to efficiently induce post-integration HIV-1 latency in non-proliferating CD4+ T-cells in vitro. Inhibition of key pathways involved in mDC-T-cell interactions and HIV-1 latency may provide novel targets to eliminate HIV latency. mRNA profiles of sorted, pure antigen presenting cells including, CD1c+ myleoid dendirtic cells (mDC), SLAN+ mDC, CD14+ monocytes and plasmacytoid DC (pDC), were generated using next generation sequencing in triplicate, using Illumina Illumina Hiseq 2000.
2015-12-23 | E-GEOD-70106 | biostudies-arrayexpress
Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Solanum lycopersicum bud and flower Transcriptomes
2021-02-27 | GSE164382 | GEO