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Both host and parasite non-coding RNAs co-ordinate the regulation of macrophage gene expression to reduce pro-inflammatory immune responses and promote tissue repair pathways during infection with fasciola hepatica

GSE263895 Mus musculus (mouse) Non-coding RNA profiling 40 samples Submitted 2024/09/30 Platform GPL24247
At a glance

Non-coding RNA profiling · mouse · 40 samples

What it is
Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism
Mus musculus (mouse)
Samples
40 samples: 40 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
Both host and parasite non-coding RNAs co-ordinate the regulation of macrophage gene expression to reduce pro-inflammatory immune responses and promote tissue repair pathways during infection with fasciola hepaticaRNA biology · 2024
Summary (written by the submitters)
Parasitic worms (helminths) ensure their survival to establish chronic infection within mammalian hosts by strategically regulating their host s immune responses. Deciphering the mechanisms behind this immune modulation will inform the development of novel strategies for infection control. It is now understood that the co-ordinated control of gene expression by non-coding RNAs (ncRNA) underpins the activation and regulation of immune cells.
Read the full summary ↓
However, it is also clear that pathogens (including helminths) secrete their own ncRNAs to manipulate host gene expression and influence immune outcomes to infection. To discriminate the contribution of host and helminth derived ncRNAs to the activation and/or regulation of innate immune responses during infection, we examined ncRNA expression in the peritoneal macrophages from mice infected with Fasciola hepatica. This revealed an enrichment of several parasitic-derived miRNAs (fhe-miR-277b-3p, fhe-miR-71a-5p, fhe-miR-125b-5p, fhe-miR-125a-5p) within macrophages at 6hr and 18hr after infection which is coincident with the parasite s migration through the peritoneal cavity. Target prediction analysis indicated that these Fasciola miRNAs regulated host genes associated with the activation of host pro-inflammatory macrophages (Hif1 , Nod1, Nlrp6 and P2rx7). Concomitantly, there was a distinct shift in host ncRNA expression in response to infection, which was most significant at 5 days post-infection. Although, analysis suggested that these host ncRNAs target a different cohort of genes (Adar1, Igf1 and Plec) to the parasite miRNAs, the functional outcome was predicted to be the same, with a reduced pro-inflammatory response and the promotion of a reparative/tolerant phenotype. Combined, these observations uncover the interplay between host and parasitic ncRNAs and reveals a complementary regulation of the immune response that allows the parasite to evade immune detection and promotes tissue repair for the host. This level of characterisation of the ncRNA landscape during helminth infection is highly novel and provides a new understanding of the molecular impact that these parasites have on host immune cells.
Published in
Both host and parasite non-coding RNAs co-ordinate the regulation of macrophage gene expression to reduce pro-inflammatory immune responses and promote tissue repair pathways during infection with fasciola hepatica
Sais D, Chowdhury S, Dalton JP et al. · RNA biology 2024 · PMID 39344634 · doi:10.1080/15476286.2024.2408706
This dataset
Open GSE263895 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 GSE263895_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 ↗

Also filed as BioProject PRJNA1099694. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39344634) ↗
Study design
40 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 40 sample titles: 40 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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