Acute, reversible dietary effect on the transcriptomic profiles of intestinal epithelial cells
Download from source ↗Dataset overview
Dynamic Intestinal Stem Cell Plasticity and Lineage Remodeling by a Nutritional Environment Relevant to Human Risk for Tumorigenesis.
Abstract
New Western-style diet 1 (NWD1), a purified diet establishing mouse exposure to key nutrients recapitulating levels that increase human risk for intestinal cancer, reproducibly causes mouse sporadic intestinal and colonic tumors reflecting human etiology, incidence, frequency, and lag with developmental age. Complex NWD1 stem cell and lineage reprogramming was deconvolved by bulk and single-cell RNA sequencing, single-cell Assay for Transposase-Accessible Chromatin using sequencing, functional genomics, and imaging. NWD1 extensively, rapidly, and reversibly, reprogrammed Lgr5hi stem cells, epigenetically downregulating Ppargc1a expression, altering mitochondrial structure and function. This suppressed Lgr5hi stem cell functions and developmental maturation of Lgr5hi cell progeny as cells progressed through progenitor cell compartments, recapitulated by Ppargc1a genetic inactivation in Lgr5hi cells in vivo. Mobilized Bmi1+, Ascl2hi cells adapted lineages to the nutritional environment and elevated antigen processing and presentation pathways, especially in mature enterocytes, causing chronic, protumorigenic low-level inflammation. There were multiple parallels between NWD1 remodeling of stem cells and lineages with pathogenic mechanisms in human inflammatory bowel disease, also protumorigenic. Moreover, the shift to alternate stem cells reflects that the balance between Lgr5-positive and -negative stem cells in supporting human colon tumors is determined by environmental influences. Stem cell and lineage plasticity in response to nutrients supports historic concepts of homeostasis as a continual adaptation to environment, with the human mucosa likely in constant flux in response to changing nutrient exposures.<h4>Implications</h4>Although oncogenic mutations provide a competitive advantage to intestinal epithelial cells in clonal expansion, the competition is on a playing field dynamically sculpted by the nutritional environment, influencing which cells dominate in mucosal maintenance and tumorigenesis.
doi:10.1158/1541-7786.mcr-22-1000 ↗ PMID 37097719 ↗ PMC10390890 ↗
Study facts
- Organism
- Mus musculus
- Platform
- Illumina NovaSeq 6000
- Age group
- —
- Disease groups
- —
- Anatomical sites
- —
Data availability
- Raw counts
- Processed matrix
File types
H5
Files and samples
- filelist.txt ↗
- GSE188577_RAW.tar ↗
- GSM5685988_A10_filtered_feature_bc_matrix.h5 ↗
- GSM5685989_A11_filtered_feature_bc_matrix.h5 ↗
- GSM5685990_A14_filtered_feature_bc_matrix.h5 ↗
- GSM5685991_A20_filtered_feature_bc_matrix.h5 ↗
- GSM5685992_A40_filtered_feature_bc_matrix.h5 ↗
- GSM5685993_A41_filtered_feature_bc_matrix.h5 ↗
- GSM5685994_A43_filtered_feature_bc_matrix.h5 ↗
- GSM5685995_A7_filtered_feature_bc_matrix.h5 ↗
- GSM5685996_B32_filtered_feature_bc_matrix.h5 ↗
- index.html ↗
- Intestinal epithelial cells9
| Accession | Sample | Tissue | Molecule |
|---|---|---|---|
GSM5685988 |
A10 | Intestinal epithelial cells | total RNA |
GSM5685989 |
A11 | Intestinal epithelial cells | total RNA |
GSM5685990 |
A14 | Intestinal epithelial cells | total RNA |
GSM5685991 |
A20 | Intestinal epithelial cells | total RNA |
GSM5685992 |
A40 | Intestinal epithelial cells | total RNA |
GSM5685993 |
A41 | Intestinal epithelial cells | total RNA |
GSM5685994 |
A43 | Intestinal epithelial cells | total RNA |
GSM5685995 |
A7 | Intestinal epithelial cells | total RNA |
GSM5685996 |
B32 | Intestinal epithelial cells | total RNA |
Strengths & limitations for reuse
Strengths
- Raw counts are advertised
- Processed matrices are advertised
Limitations
- Not documented: cell metadata are advertised
- Not documented: participant counts are documented
Extraction evidence & provenance
Each extracted field is shown with the source excerpt and location used to resolve it.
Assay
| Field | Value | Evidence |
|---|---|---|
assay.assay_type |
single-cell RNA sequencing |
Here single-cell RNA sequencing (scRNA-seq) Section |
assay.library_chemistry |
10X Genomics Chromium Next GEM single cell 3′ kit |
Our single cell RNAseq (scRNAseq) libraries were made according to the manufacturer’s protocol for Chromium Next GEM (gel beads in emulsion) single cell 3′ kit (10X Genomics) Section |
assay.platform |
Illumina NovaSeq 6000 |
"instrument_model": {"Illumina NovaSeq 6000": 9} Section |
assay.reference_genome |
mm10 |
Genome_build: mm10 Section |
assay.sequencing_type |
scrna_seq |
"series_overall_design": "single cell RNAseq" Section |
Data_Assets
| Field | Value | Evidence |
|---|---|---|
data_assets.open_access |
True |
"series_status": "Public on Apr 12 2023" Section |
data_assets.participant_metadata |
True |
"characteristics": {"diet": {"AIN all time": 3, "after 3 months of AIN feeding, 4 days NWD1": 3, "after 3 months of AIN feeding, 4 days NWD1, switchback to AIN for 4 days": 3}} Section |
data_assets.processed_matrix |
True |
HDF5 Feature Barcode Matrix Format Section |
data_assets.raw_counts |
True inferred |
Supplementary_files_format_and_content: HDF5 Feature Barcode Matrix Format Section |
Processing
| Field | Value | Evidence |
|---|---|---|
processing.batch_correction_reported |
True inferred |
Cells from different samples were integrated using Seurat FindIntegrationAnchors and IntegrateData functions Section |
processing.cell_type_annotation_method |
Seurat marker-based annotation using FindMarkers |
Cell clusters were identified as cell intestinal cell types using established cell-type markers and cluster identification in Seurat FindMarkers function. Section |
processing.doublet_detection_reported |
True |
To discard doublets or dead cells Section |
processing.quality_control_reported |
True |
To discard doublets or dead cells, cells with gene counts <200 or >5,000, or a mitochondrial gene ratio >20%, were filtered out. Section |
Specimens
| Field | Value | Evidence |
|---|---|---|
specimens.number_of_samples |
9 |
"sample_count": 9 Section |