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Knockdown of microglial iron import gene, DMT1, worsens cognitive function and alters microglial transcriptional landscape in a sex-specific manner in the APP/PS1 model of Alzheimer's disease

GSE269314 Mus musculus (mouse) RNA-seq (gene expression) 23 samples Submitted 2024/07/17 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 23 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
23 samples: 23 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
Knockdown of microglial iron import gene, DMT1, worsens cognitive function and alters microglial transcriptional landscape in a sex-specific manner in the APP/PS1 model of Alzheimer's diseaseResearch square · 2024
Summary (written by the submitters)
Background Microglial cell iron load and inflammatory activation are significant hallmarks of late-stage Alzheimer’s disease (AD). In vitro, microglia preferentially upregulate iron importer, divalent metal transporter 1 (DMT1, gene name Slc11a2) in response to inflammatory stimuli, and excess iron can augment cellular inflammation, suggesting a feed-forward loop between iron import mechanisms and inflammatory signaling.
Read the full summary ↓
However, it is not understood whether microglial iron import mechanisms directly contribute to inflammatory signaling and chronic disease in vivo. These studies determined the effects of knocking down microglial iron import gene, Slc11a2, on AD-related cognitive decline and microglial transcriptional phenotype. Methods In vitro experiments and RT-qPCR were used to assess a role for DMT1 in amyloid-β-associated inflammation. To determine the effects of microglial Slc11a2 knockdown on AD-related phenotypes in vivo, triple-transgenic Cx3cr1Cre-ERT2;Slc11a2flfl;APP/PS1+ or – mice were generated and administered corn oil or tamoxifen to induce knockdown at 5-6 months of age. Both sexes underwent behavioral analyses to assess cognition and memory (12-15 months of age). Hippocampal CD11b+ microglia were magnetically isolated from female mice (15-17 months) and bulk RNA-sequencing analysis was conducted. Results DMT1 inhibition in vitro robustly decreased Aβ-induced inflammatory gene expression and cellular iron levels in conditions of excess iron. In vivo, Slc11a2KD APP/PS1 female, but not male, mice displayed a significant worsening of memory function in Morris water maze and a fear conditioning assay, along with significant hyperactivity compared to control WT and APP/PS1 mice. Hippocampal microglia from Slc11a2KD APP/PS1 females displayed significant increases in genes Enpp2, Ttr, and iron-export gene, Slc40a1, compared to control APP/PS1 cells. Slc11a2KD cells from APP/PS1 females also exhibited decreased expression of markers related to disease-associated microglia (DAMs), such as Apoe, Ctsb, Csf1, and Hif1α. Conclusions This work suggests a sex-specific role for microglial iron import gene Slc11a2 in propagating behavioral and cognitive phenotypes in the APP/PS1 model of AD. These data also highlight an association between loss of a DAM-like phenotype in female microglia and cognitive deficits in Slc11a2KD APP/PS1 mice. Overall, this work illuminates an iron-related pathway in microglia that may serve a protective role during disease and offers insight into mechanisms behind disease-related sex differences.
Published in
Knockdown of microglial iron import gene, DMT1, worsens cognitive function and alters microglial transcriptional landscape in a sex-specific manner in the APP/PS1 model of Alzheimer's disease
Robertson KV, Rodriguez AS, Cartailler JP et al. · Research square 2024 · PMID 38978579 · doi:10.21203/rs.3.rs-4559940/v1
This dataset
Open GSE269314 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 GSE269314_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 PRJNA1121187 and SRA study SRP512387. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38978579) ↗
Study design
23 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 23 sample titles: 23 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
Datasets on a similar topic

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