GEO series
Differential impact of inflammatory microglia signals and chronic HIV-1 Tat exposure on A1-like polarization of astrocytes
GSE291361
Homo sapiens (human)
RNA-seq (gene expression)
24 samples
Submitted 2025/06/25
Platform GPL21697
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: 24 samples, each with a distinct title — no replicated groupsGroups 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
- Inflammatory microglia signals drive A1-like polarization of astrocytes even in the presence of HIV-1 TatMolecular neurobiology · 2025
Summary (written by the submitters)
In the context of neurodegeneration, activated microglia facilitate inflammation via secretion of TNF-α, IL-1α, and C1q. Astrocytes exposed to this signaling array polarize to a reactive inflammatory phenotype, termed A1 or A1-like. Astrocytes are essential for neuronal survival, synaptic support, and blood-brain barrier (BBB) function, but A1-like astrocytes upregulate inflammatory gene expression, downregulate neurotrophic factors, and secrete neurotoxic signals.
Read the full summary ↓
The consequences of A1-like polarization on BBB function are unknown but may have etiological implications for some diseases. Frequently identified by upregulation of complement component 3 (C3), A1-like astrocytes have been characterized in neurodegenerative disorders like Alzheimer’s disease, with polarization correlated with disease progression and severity. However, the role of A1-like astrocytes in neurodegeneration associated with chronic viral infections, like HIV-1-associated neurocognitive disorder (HAND), remains unclear. An in vitro system using primary human astrocytes, as well as a BBB model featuring primary human brain microvascular endothelial cells (BMECs) co-cultured with astrocytes, was used to elucidate cellular and molecular consequences of chronic astrocyte activation. As measured by whole transcriptome analysis and protein expression assays, repeated treatment with TNF-α, IL-1α, and C1q induced A1-like polarization of astrocytes both in monoculture and in a BBB model, resulting in increased secretion of pro-inflammatory signals. No substantial change to BBB permeability was observed. In contrast, exposure to HIV-1 viral protein Tat did not independently induce A1-like polarization. Ongoing investigations into the effect of astrocyte polarization on BBB integrity and treatment with pathogenic proteins may provide insights into the role of neurotoxic astrocytes in neuroviral pathologies.
Published in
Lawrence JM, Dampier W, Mell JC et al.
· Molecular neurobiology 2025
· PMID 41345807
· doi:10.1007/s12035-025-05409-z
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 GSE291361_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 PRJNA1233235 and SRA study SRP568667. Searching any of these in the dataset finder brings you back here.
Study design
24 samples, each with a distinct title — no replicated groups
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 24 sample titles: 24 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
- GSM8833877 RNA from sample #3 from trial d, collected after 4 days of repeated exposure to treatment A (control)
- GSM8833878 RNA from sample #5 from trial d, collected after 4 days of repeated exposure to treatment A (control)
- GSM8833879 RNA from sample #3 from trial d, collected after 4 days of repeated exposure to treatment B (TIC)
- GSM8833880 RNA from sample #6 from trial d, collected after 4 days of repeated exposure to treatment B (TIC)
- GSM8833881 RNA from sample #1 from trial d, collected after 4 days of repeated exposure to treatment C (Tat-50ng)
- GSM8833882 RNA from sample #2 from trial d, collected after 4 days of repeated exposure to treatment C (Tat-50ng)
- GSM8833883 RNA from sample #3 from trial d, collected after 4 days of repeated exposure to treatment D (Tat-250ng)
- GSM8833884 RNA from sample #4 from trial d, collected after 4 days of repeated exposure to treatment D (Tat-250ng)
- GSM8833885 RNA from sample #1 from trial e, collected after 6 days of repeated exposure to treatment A (control)
- GSM8833886 RNA from sample #2 from trial e, collected after 6 days of repeated exposure to treatment A (control)
- GSM8833887 RNA from sample #3 from trial e, collected after 6 days of repeated exposure to treatment A (control)
- GSM8833888 RNA from sample #1 from trial e, collected after 6 days of repeated exposure to treatment B (TIC)
- GSM8833889 RNA from sample #2 from trial e, collected after 6 days of repeated exposure to treatment B (TIC)
- GSM8833890 RNA from sample #3 from trial e, collected after 6 days of repeated exposure to treatment B (TIC)
- GSM8833891 RNA from sample #1 from trial e, collected after 6 days of repeated exposure to treatment C (Tat-50ng)
- GSM8833892 RNA from sample #2 from trial e, collected after 6 days of repeated exposure to treatment C (Tat-50ng)
- GSM8833893 RNA from sample #3 from trial e, collected after 6 days of repeated exposure to treatment C (Tat-50ng)
- GSM8833894 RNA from sample #3 from trial f, collected after 4 days of repeated exposure to treatment A (control)
- GSM8833895 RNA from sample #2 from trial f, collected after 4 days of repeated exposure to treatment B (TIC)
- GSM8833896 RNA from sample #3 from trial f, collected after 4 days of repeated exposure to treatment C (Tat-50ng)
- GSM8833897 RNA from sample #1 from trial f, collected after 4 days of repeated exposure to treatment D (Tat-250ng)
- GSM8833898 RNA from sample #1 from trial f, collected after 4 days of repeated exposure to treatment E (TIC+Tat-50ng)
- GSM8833899 RNA from sample #2 from trial f, collected after 4 days of repeated exposure to treatment E (TIC+Tat-50ng)
- GSM8833900 RNA from sample #3 from trial f, collected after 4 days of repeated exposure to treatment E (TIC+Tat-50ng)
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Share this dataset
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.