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Expression profiling of THP-1 cells with and without infection by Francisella tularensis and with or without treatment with Dillapiole

GSE306199 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2025/10/06 Platform GPL18460
At a glance

RNA-seq (gene expression) · human · 20 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
20 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Dillapiole Dampens the Expression of the Major Virulence Genes of Francisella tularensisMolecules (Basel, Switzerland) · 2025
Summary (written by the submitters)
In order to assess the effect of treatment by Dillapiole on human monocyte THP-1 cells infected by Francisella tulerensis, we performed expression profiling by RNA sequencing on THP-1 cells with and without infection and with or without treatment. Differential expression analysis revealed 1174 genes whose expression was affected by the Dillapiole treatment differently in the infected cells when compared to the treatment effect in the uninfected cells. These genes identified 45 biological pathways, including an inhibitory effect on the TNF-receptor pathway.
Published in
Dillapiole Dampens the Expression of the Major Virulence Genes of Francisella tularensis
Collins EM, Sako A, Sikorsky K et al. · Molecules (Basel, Switzerland) 2025 · PMID 41097415 · doi:10.3390/molecules30193995
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE306199_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1309670 and SRA study SRP610735. Searching any of these in the dataset finder brings you back here.

Samples in this study

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