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CYP1B1-AS1 regulates CYP1B1 to promote Coxiella burnetii pathogenesis by inhibiting ROS and host cell death

GSE292317 Homo sapiens (human) RNA-seq (gene expression) 78 samples Submitted 2025/07/14 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 78 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
78 samples: 64 distinct titles, 1 of them repeatedGroups 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
CYP1B1-AS1 regulates CYP1B1 to promote Coxiella burnetii pathogenesis by inhibiting ROS and host cell deathNature communications · 2025
Summary (written by the submitters)
Coxiella burnetii (Cb), the causative agent of Q fever, replicates within host macrophages by modulating immune responses through poorly understood mechanisms. Long non-coding RNAs (lncRNAs) are crucial yet underexplored regulators of inflammation, particularly in Cb pathogenesis.
Read the full summary ↓
Employing a comparative transcriptomic analysis of THP-1 macrophages infected with 16 different microbes, we dissected a core set of immune-responsive lncRNAs such as MAILR, LINC01215, PACER, and MROCKI-common to human anti-pathogen responses, and distinguished them from lncRNAs specifically altered at early (1 h) time points in individual infections. In particular, our approach unveiled lncRNA CYP1B1-AS1 as specifically upregulated in a spatiotemporal manner along with CYP1B1 in cis during Cb infection. Promoter assays confirmed their co-regulation via a shared bidirectional promoter, while aryl hydrocarbon receptor (AHR)-lucia luciferase and nuclear translocation assays demonstrated that Cb infection activates AHR, driving their transcription. Knockdown of CYP1B1-AS1 or CYP1B1 alone disrupted mitochondrial homeostasis, increased ROS and mitochondrial dysfunction, and exacerbated apoptosis during infection. These findings position the CYP1B1-AS1/CYP1B1 axis as a key regulator of mitochondrial homeostasis under AHR signaling, supporting an intracellular environment that benefits Cb replication. Our results highlight the critical roles of lncRNAs in immune regulation and provide a valuable resource for future lncRNA research.
Published in
CYP1B1-AS1 regulates CYP1B1 to promote Coxiella burnetii pathogenesis by inhibiting ROS and host cell death
Arunima A, Niyakan S, Butler SM et al. · Nature communications 2025 · PMID 40796858 · doi:10.1038/s41467-025-62762-2
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 GSE292317_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 PRJNA1228654 and SRA study SRP566782. Searching any of these in the dataset finder brings you back here.

Study design
64 distinct titles, 1 of them repeated
Uninfected ×15

How we read this: Read from 78 sample titles: 64 distinct titles with little repetition. 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

+ 38 more — browse all 78 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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