GEO series

BCG educates hematopoietic stem cells to generate protective innate immunity against tuberculosis [scRNA-seq]

GSE108067 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2017/12/15 Platform GPL17021

At a glance

Single-cell RNA-seq · mouse · 2 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 2 samples
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)

The dogma that adaptive immunity is the only arm of the immune response with memory capacity has been recently challenged by several studies demonstrating evidence for memory-like innate immune training. However, the underlying mechanisms and location for generating such innate memory responses in vivo remains unknown.

Read the full summary ↓

Here we show that access of Bacillus Calmette-Guérin (BCG) to the bone marrow (BM) changes the transcriptional landscape of hematopoietic stem cells (HSC) and multipotent progenitors (MPP) leading to local cell expansion and enhanced myelopoiesis at the expense of lymphopoiesis. Importantly, BCG-educated HSCs generate epigenetically-modified macrophages that provide significantly better protection against virulent M. tuberculosis infection than naïve macrophages. By using parabiotic and chimeric mice as well as adoptive transfer approaches, we demonstrate that training of the monocyte/macrophage lineage via BCG-induced HSC reprogramming is sustainable in vivo. Our results indicate that targeting the HSC compartment provides a novel approach for vaccine development.

This dataset

Open GSE108067 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 GSE108067_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA422382 and SRA study SRP126737. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 29328912) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 2 more — browse all 2 samples with per-sample file links →

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