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Vitamin D Enhances Antiviral Responses in Dengue Virus-Infected Macrophages by Modulating Early-Response Gene Expression

GSE297386 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/08/27 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 12 conditions, mostly in duplicateGroups 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
Vitamin D enhances antiviral responses in dengue virus-infected macrophages by modulating early-response gene expressionPloS one · 2025
Summary (written by the submitters)
Dengue virus (DENV), the etiological agent of dengue fever, remains a global health concern, leading to severe illness and death in the absence of any definitive cure. Research has shown that vitamin D may reduce DENV replication in vitro and that dengue patients with low or deficient vitamin D levels are at higher risk of severe dengue.
Read the full summary ↓
Studies indicate that viral replication is inhibited in human monocyte-derived macrophages (MDM) differentiated in the presence of vitamin D (D3MDM), suggesting that vitamin D may prevent DENV entry into host cells. However, despite these findings, the role of vitamin D in regulating the temporal expression patterns of genes as early, mid, and late transcriptional profile of DENV-infected macrophages remains unclear. Therefore, utilizing a kinetic transcriptomic profile is crucial. This approach provides detailed insights into the dynamic changes in gene expression over time, helping to clarify how vitamin D can modulate the immune response at critical stages of DENV infection. To address the transcriptional dynamics, we conducted a comprehensive analysis of gene expression patterns in MDM and D3MDM infected with Dengue virus serotype 2 (DENV-2). Utilizing bulk RNA sequencing alongside a standard viral growth curve, we systematically analyzed transcriptional kinetics by selecting key time points: 1.5, 3, 5.5, and 10 hours post-infection (h.p.i.) to monitor early viral entry and replication events and 24 h.p.i. to assess gene expression during peak viral particle production. Our temporal analysis revealed a progressive increase in cellular transcripts within the first hour of infection, with a more pronounced gene expression pattern in DENV-2-infected MDM compared to DENV-2-infected D3MDM at this early stage. Enrichment analysis indicated a reduced inflammatory response in DENV-2-infected D3MDM. Additionally, transcription factor analysis suggested diminished NF-κB signaling, but enhanced IRF5 activity was elevated in the DENV-2-infected D3MDM. High-dimensional clustering analysis identified nine unique gene clusters across both macrophage types, with notable upregulation of genes associated with antiviral activity, including IDO1, ISG20, OASL, IFI44L, RSAD2, IFIT1, MX1, EPSTI1, CXCL10, and CXCL11 in DENV-2-infected D3MDM at 1.5 h.p.i., suggesting an enhanced early antiviral response. These findings indicate that vitamin D modulates the magnitude and diversity of the early transcriptional responses, highlighting its potential as a therapeutic option to mitigate DENV severity.
Published in
Vitamin D enhances antiviral responses in dengue virus-infected macrophages by modulating early-response gene expression
Tamayo-Molina YS, Valdés-López JF, Fernandez GJ et al. · PloS one 2025 · PMID 40839599 · doi:10.1371/journal.pone.0330751
This dataset
Open GSE297386 in finder → Find more human 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 GSE297386_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 PRJNA1263729 and SRA study SRP586014. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40839599) ↗
Study design
12 conditions, mostly in duplicate
MDM_Mock_0H ×2 MDM_DENV_1.5H ×2 MDM_DENV_3H ×2 MDM_DENV_5.5H ×2 MDM_DENV_10H ×2 MDM_DENV_24H ×2 VD3_MDM_Mock_0H ×2 VD3_MDM_DENV_1.5H ×2 +4 more

Supports a between-group comparison across 24 samples.

How we read this: 12 replicated groups read from 24 sample titles; they account for 24 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
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