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Systematic transcriptome and molecular docking analyses reveals that Cirsium japonicum mitigates allergic nasal inflammation through regulation of NRF2-mediated mucin production in an allergic rhinitis mouse model

GSE246623 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2024/10/23 Platform GPL30215
At a glance

RNA-seq (gene expression) · mouse · 15 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
Mus musculus (mouse)
Samples
15 samples: 5 conditions, mostly in triplicateGroups are read from the sample names, not from the paper. Check the list below.
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
Cirsium japonicum mitigates allergic nasal inflammation by regulating NRF2-mediated mucin production: Systematic transcriptome and molecular docking analysesJournal of pharmaceutical analysis · 2024
Summary (written by the submitters)
Allergic rhinitis (AR) is a typical allergic disease mediated by immunoglobulin E (IgE), which greatly affects the quality of life and is more sensitive to change of seasons due to various nasal symptoms. AR worsening symptoms can lead to more dangerous diseases, there is an urgent need to develop safe and effective treatments. Cirsium japonicum (CSJ) is a plant that has been used in traditional medicine due to its various efficacy and safety; so far, the effects and major mechanisms of CSJ on AR have not been reported.
Read the full summary ↓
Therefore, the purpose of this study was to investigate the possible targets of CSJ for AR treatment and its underlying mechanisms. An ovalbumin (OVA)-induced AR mouse model was established and the therapeutic effects of CSJ were evaluated. CSJ reduced the production level of OVA-specific IgE, histamine, and Th2 cytokines in serum, and significantly alleviated the typical symptoms of AR and the level of inflammation in the nasal mucosa. In addition, we used transcriptome analysis in AR models to identify that O-linked glycosylation of mucins, MUC5AC, and NRF2 are key targets for CSJ related to AR. Then, we identified the active ingredients of CSJ for AR, and verified that the active core compounds of CSJ, cryptochromogenic acid and cirsimarin, could bind closely to potential key targets, NRF2-KEAP1, and MUC5AC using molecular docking analysis. In conclusion, our results suggest that CSJ may be a more effective candidate drug for the treatment of AR with dual function to regulate both NRF2 pathway and MUC5AC expression.
Published in
Cirsium japonicum mitigates allergic nasal inflammation by regulating NRF2-mediated mucin production: Systematic transcriptome and molecular docking analyses
Pyun BJ, Baek SJ, Jo K et al. · Journal of pharmaceutical analysis 2024 · PMID 39403679 · doi:10.1016/j.jpha.2024.101000
This dataset
Open GSE246623 in finder → Find more mouse RNA-seq datasets →
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.

Series matrix ↓
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 GSE246623_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1033992 and SRA study SRP469347. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39403679) ↗
Study design
5 conditions, mostly in triplicate
Nasal, Saline, ×3 Nasal, OVA-induced model, ×3 Nasal, OVA+dexamethasone, ×3 Nasal, OVA+CSJ, 100mg/kg, ×3 Nasal, OVA+CSJ, 300mg/kg, ×3

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 15 sample titles; they account for 15 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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