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Mycobacterium abscessus infection in fetal liver derived alveolar-like macrophages activates distinct inflammatory responses compared to myeloid-derived macrophages

GSE264083 Mus musculus (mouse) RNA-seq (gene expression) 36 samples Submitted 2026/06/03 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 36 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
36 samples: 12 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.
Summary (written by the submitters)
Pulmonary infections caused by Mycobacterium abscessus (Mab), a rapidly growing nontuberculous mycobacterium (NTM), are on the rise in patients with chronic or acquired lung disease. In contrast to immunocompetent individuals, these patient cohorts exhibit abnormal pulmonary function that result from chronic inflammation and mucus build-up.
Read the full summary ↓
Treatment regimens rely on multi-drug cocktails yet Mab’s natural recalcitrance to common antibiotics extends treatment timelines and increases the frequency of treatment failures. Thus, it is important to understand the mechanisms by which immunocompetent individuals clear Mab with relative ease while susceptible individuals do not, to identify new treatment options that may protect at-risk patients. In the lungs, macrophages are the first immune cell Mab encounters following infection, with both resident alveolar macrophages and recruited myeloid derived macrophages playing important roles during infection control. However, the specific role of these distinct macrophage populations in regulating control and inflammatory responses during Mab remains limited due to a lack of ex vivo models that recapitulate the functions of different macrophage subsets. Here, we leverage a fetal-liver derived alveolar macrophage (FLAM) model to define the mechanistic interactions occurring at the Mab-macrophage interface compared to bone-marrow derived macrophages (BMDMs). Even though both FLAMs and BMDMs similarly control intracellular Mab, the inflammatory response between these macrophage populations is significantly different. While BMDMs robustly activated NF-κB transcriptional targets that include important chemokines and inflammatory cytokines like TNF, FLAMs transiently induced these genes following Mab infection. While activation of FLAMs or BMDMs with IFNγ prior to Mab infection did not alter Mab intracellular dynamics, it did drive FLAMs to be more inflammatory. However, while we found IFNγ activated FLAMs more robustly activate NF-κB during Mab infection, there remain important differences compared to BMDMs. This includes lower expression of the inducible nitric oxide synthase, which we found was reversed with chemical activation of HIF1α. We conclude that FLAMs and BMDMs differentially respond to Mab infection due to differences in signaling networks activated following innate immune sensing, with FLAMs being more hypo-inflammatory than BMDMs. More broadly our results highlight a key need to better understand the initial interactions with Mab and distinct macrophage populations to define pathways that contribute to pulmonary protection or disease during respiratory infections.
This dataset
Open GSE264083 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 GSE264083_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 PRJNA1100958 and SRA study SRP502124. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
FLAM_Uninf ×3 FLAM_6H ×3 FLAM_24H ×3 FLAM_IFNg_Uninf ×3 FLAM_IFNg_6H ×3 FLAM_IFNg_24H ×3 BMDM_Uninf ×3 BMDM_6H ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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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