GEO series

Transcriptional profiling links unique human macrophage phenotypes to the growth of intracellular Salmonella enterica serovar Typhi

GSE267899 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/05/20 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 18 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: 18 samples: 6 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.
Paper: Transcriptional profiling links unique human macrophage phenotypes to the growth of intracellular Salmonella enterica serovar TyphiScientific reports · 2024

Summary (written by the submitters)

Macrophages provide a crucial environment for Salmonella enterica serovar Typhi (S. Typhi) to multiply during typhoid fever, yet our understanding of how human macrophages and S. Typhi interact remains limited. In this study, we delve into the dynamics of S. Typhi replication within human macrophages and the resulting heterogeneous transcriptomic responses of macrophages during infection.

Read the full summary ↓

Our study reveals key factors that influence macrophage diversity, uncovering distinct immune and metabolic pathways associated with different stages of S. Typhi intracellular replication in macrophages. Of note, we found that macrophages harboring replicating S. Typhi are skewed towards an M1 pro-inflammatory state, whereas macrophages containing non-replicating S. Typhi exhibit neither a distinct M1 pro-inflammatory nor M2 anti-inflammatory state. Additionally, macrophages with replicating S. Typhi were characterized by the increased expression of genes associated with STAT3 phosphorylation and the activation of the STAT3 transcription factor. Our results shed light on transcriptomic pathways involved in the susceptibility of human macrophages to intracellular S. Typhi replication, thereby providing crucial insight into host phenotypes that restrict and support S. Typhi infection.

Published in

Transcriptional profiling links unique human macrophage phenotypes to the growth of intracellular Salmonella enterica serovar Typhi

Schade R, Butler DSC, McKenna JA et al. · Scientific reports 2024 · PMID 38834738 · doi:10.1038/s41598-024-63588-6

This dataset

Open GSE267899 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 GSE267899_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 PRJNA1113598 and SRA study SRP508738. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38834738) ↗

Study design

6 conditions, mostly in triplicate

Bystander, biol ×3 Replicating, biol ×3 Host Killed, biol ×3 Mixed, biol ×3 Non Replicating, biol ×3 Uninfected, biol ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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

GSM8281288 Bystander, biol rep 1 Bystander, biol
GSM8281289 Bystander, biol rep 2 Bystander, biol
GSM8281290 Bystander, biol rep 3 Bystander, biol
GSM8281291 Replicating, biol rep 1 Replicating, biol
GSM8281292 Replicating, biol rep 2 Replicating, biol
GSM8281293 Replicating, biol rep 3 Replicating, biol
GSM8281294 Host Killed, biol rep 1 Host Killed, biol
GSM8281295 Host Killed, biol rep 2 Host Killed, biol
GSM8281296 Host Killed, biol rep 3 Host Killed, biol
GSM8281297 Mixed, biol rep 1 Mixed, biol
GSM8281298 Mixed, biol rep 2 Mixed, biol
GSM8281299 Mixed, biol rep 3 Mixed, biol
GSM8281300 Non Replicating, biol rep 1 Non Replicating, biol
GSM8281301 Non Replicating, biol rep 2 Non Replicating, biol
GSM8281302 Non Replicating, biol rep 3 Non Replicating, biol
GSM8281303 Uninfected, biol rep 1 Uninfected, biol
GSM8281304 Uninfected, biol rep 2 Uninfected, biol
GSM8281305 Uninfected, biol rep 3 Uninfected, biol

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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.