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The cellular states and fates of shed intestinal cells

Nature Metabolism volume 5, pages 1858–1869 (2023)Cite this article

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Abstract

The intestinal epithelium is replaced every few days1. Enterocytes are shed into the gut lumen predominantly from the tips of villi2,3 and have been believed to rapidly die upon their dissociation from the tissue4,5. However, technical limitations prohibited studying the cellular states and fates of shed intestinal cells. Here we show that shed epithelial cells remain viable and upregulate distinct anti-microbial programmes upon shedding, using bulk and single-cell RNA sequencing of male mouse intestinal faecal washes. We further identify abundant shedding of immune cells, which is elevated in mice with dextran sulfate sodium-induced colitis. We find that faecal host transcriptomics reflect changes in the intestinal tissue following perturbations. Our study suggests potential functions of shed cells in the intestinal lumen and demonstrates that host cell transcriptomes in intestinal washes can be used to probe tissue states.

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Fig. 1: Faecal wash host transcriptomes have distinct segment-dependent profiles.
Fig. 2: Differences in gene expression between the tissue and the shed cells.
Fig. 3: Single-cell analysis of faecal washes reveals diverse cell type presence.
Fig. 4: Faecal washes mirror perturbed tissue states.

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Data availability

All data generated in this study are available at the Zenodo repository at https://doi.org/10.5281/zenodo.7137319. GRCm38 genome (release 84; Ensembl) was used in this study (http://www.ensembl.org/Mus_musculus/Info/Index).

Code availability

Codes for unique analysis done in this study were uploaded to Zenodo (https://doi.org/10.5281/zenodo.7137319). All other common codes used in this study will be available upon request.

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Acknowledgements

We thank H. Shapiro and E. Elinav from the department of Systems Immunology, Weizmann Institute of Science, for help with experimental procedures of mice perturbations. We thank Y. Levin and A. Savidor from the INCPM proteomics unit, Weizmann Institute of Science, for help with the proteomics experiment. Y.K.K is supported by the JSMF Postdoctoral Fellowship in Understanding Dynamic and Multi-scale Systems (Award #https://doi.org/10.37717/2020-1428). S.I. is supported by the Moross Integrated Cancer Center, the Yad Abraham Research Center for Cancer Diagnostics and Therapy, the Helen and Martin Kimmel Institute for Stem Cell Research, the Minerva Stiftung grant, the Israel Science Foundation grants no. 908/21 and no. 3663/21, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme grant no. 768956, a Weizmann-Sheba joint research grant and a research grant from the Ministry of Innovation, Science and Technology, Israel.

Author information

Authors and Affiliations

  1. Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel

    Keren Bahar Halpern, Yotam Harnik, Adi Egozi, Oran Yakubovsky & Shalev Itzkovitz

  2. Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA

    Yael Korem Kohanim

  3. Department of Systems Immunology, Weizmann Institute of Science, Rehovot, Israel

    Adi Biram & Ziv Shulman

  4. Department of General Surgery and Transplantation, Sheba Medical Center, Tel-Hashomer, Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel

    Oran Yakubovsky

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Contributions

S.I. and K.B.H. conceived the study. K.B.H. performed all bulk, scRNA-seq, smFISH, mice perturbation experiments, cell viability and proteomics assays. A.B. and Z.S. performed intra-vital imaging. K.B.H. and Y.H. performed immunofluorescence experiments. K.B.H. and O.Y. performed Hoechst in vivo assay. K.B.H., A.E., Y.K.K. and S.I. performed all data analysis. S.I. and K.B.H. wrote the paper. All authors discussed the results and commented on the paper.

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Correspondence to Keren Bahar Halpern or Shalev Itzkovitz.

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Nature Metabolism thanks Jose Ordovas-Montanes and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Yanina-Yasmin Pesch, in collaboration with the Nature Metabolism team. Research briefing related to this: CSFV23069202A.

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Extended data

Extended Data Fig. 1 Differential gene expression between faecal washed to tissues.

a. Examples of genes that are only expressed in the small intestine but not in the colon tissue, yet are still observed in colonic faecal washes. These genes demonstrate a slow decline in gene expression of shed intestinal cells. Y axis is log10(Normalized RNA Expression), n = 10 mice. Medians are marked with white dot. Means are marked with x and connected with a dashed line. b, c Volcano plot showing differentially expressed genes between faecal washes and tissues in small (b) or large (c) intestine, each dot is a gene, x-axis is the log2- ratio of expression between faecal wash and tissue, y axis is –log10 (q value), where p value is computed using 2-sided Wilcoxon rank-sum tests and q- values computed using Benjamini- Hochberg FDR correction. Genes with corresponding q-values below 0.05 and fold change greater than 1.5 are marked in red or blue for faecal wash or tissue elevated genes respectively. Names of representative up-regulated genes are shown in red or blue for faecal wash or tissue respectively.

Source data

Extended Data Fig. 2 Protein and mRNA levels in small intestine faecal washes are correlated.

Correlation between protein levels and faecal wash mRNA levels of small intestine samples. Y axis shows the log10 relative protein expression (4 mice), X axis shows log10 relative mRNA expression (27 samples from 10 mice). Shown are names of cell type marker genes extracted from Fig. 3b in addition to the pancreatic genes AMY2A, PRSS2, CELA1 and CELA3B. Spearman correlation 2-sided test was used.

Source data

Extended Data Fig. 3 Sorting strategy for isolation of mouse intestinal cells from faecal washes.

a. FSC-A and SSC-A are used to select cells based on size. b. PI staining is used to gate out dead cells. C. Hoechst fluorescense is used to select eukaryotic cells while avoiding low DNA amount of bacteria cells. Numbers in A-C represent the percent of gated cells.

Source data

Extended Data Fig. 4 Faecal wash flushing preserves tissue cells and lead to minor cell shedding.

a. Schematic outline of the procedure. Created with BioRender.com b. Tissue cells after in-vivo Hoechst staining showing robust labeling of tissue cells. Scale bar 100 μm. image is representative of 3 independent experiments. c-d. FACS analysis of cells depicting gating strategy to exclude debris, dead cells, and fractionation according to the level of Hoechst 33342 uptake (dubbed as Hoechst positive [H+] and Hoechst negative [H−]) in tissue dissociated cells and in two faecal wash samples. e. Quantification of fraction of Hoechst positive and Hoechst negative cells in the samples indicated in d. f. Preservation of mucus and tissue morphology by Alcian blue and H&E staining respectively. Scale bar 100 μm. images are representative of 2 independent experiments.

Source data

Extended Data Fig. 5 Validation of cell viability of shed cells.

a. Fluorescence analysis showing representative faecal wash cells stained for apoptotic markers. White is CytoCalcein Violet 450, representative of live cells, magenta is Apopxin green Indicator, representative of apoptotic cells. b. Quantification of FACS analysis showing the percentage of live cells as measured by CytoCalcein Violet 450 levels and the percentage of apoptotic cells as measured by Apopxin Green in faecal wash samples from three mice. c. Mitochondrial health assessment demonstrate the existence of live host shed cells. Fluorescence analysis showing faecal wash host cells (white arrows) stained with marker of mitochondrial membrane potential (white, MitoHealth) and with non-viability stain (magenta Image-iT DEAD Green). Cells are also stained with Hoechst to mark the DNA (blue). White arrow-heads show auto-fluorescence of bacterial colonies. images are representative of 3 independent experiments.

Extended Data Fig. 6 Wide field view of a representative smFISH image.

Cells are stained for the epithelial markers Reg3g and Ada and the monocyte/macrophage marker Lyz1. Cells are Dapi positive and marked by white dashed line. In each panel, cells positive for the respective genes are outlined in red. Scale bar, 20 μm. Images are representative of 5 independent experiments.

Extended Data Fig. 7 Protein polarity of shed cells.

a-b. Intact mouse Jejunum tissue stained with an antibody against CD73 (green) and Dapi (grey), show apical polarity of CD73 at the villi tip. Other CD73 positive cells are monocytes/macrophages. Scale bar in a and b are 25μm and 10μm respectively. c. Dissociated mouse Jejunum tissue stained with anti EpCAM (magenta), anti CD73 (green) and Hoechst (grey). Both EpCAM and CD73 show cell polarity. d. Faecal wash cells stained with anti EpCAM (magenta), anti CD73 (green) and Hoechst (grey). Both EpCAM and CD73 show loss of cell polarity. Images are representative of at least 3 independent experiments.

Extended Data Fig. 8 Differential gene expression of faecal washes between control and mice pertubation.

Volcano plot showing differentially expressed genes between large intestine faecal wash in control (CT) and DSS (a) or ABX and CT (b), each dot is a gene, x-axis is the log2- ratio of expression between faecal wash and tissue, y axis is –log10 (q value), where p value is computed using 2-sided Wilcoxon rank-sum tests and q- values computed using Benjamini- Hochberg FDR correction. Genes with corresponding q-values below 0.05 and fold change garter than 1.5 are marked in red or blue for treatment or control elevated genes respectively. Names of representative up-regulated genes are shown in red or blue for treatment or control respectively.

Source data

Extended Data Fig. 9 Faecal washes mirror perturbed tissue states.

a. Scatter plot of log2 gene expression ratio between DSS and control mice in colon tissue (x-axis) or colon faecal washes (y-axis). Each dot is a gene. Red dots are inflammatory-related genes previously shown to be upregulated in faecal washes collected during lower endoscopies of ulcerative colitis patients16. Red dots mark the genes with AUC (area under the curve) value above 0.9 in Ungar et al.16 n = 16 biologically independent samples. Shown are the gene names of selected upregulated inflammatory-related genes. Spearman correlation 2-sided test was used correlation = 0.29, p-value = 3.1e-308. b. Violin plot showing the distribution of genes in a. Medians are marked with white circles. Two-sided kruskalwallis test was used.

Source data

Supplementary information

Reporting Summary

Supplementary Table 1

Control bulk RNA raw data.

Supplementary Table 2

Differential gene expression between faecal wash and tissue of small or large intestine.

Supplementary Table 3

Control mice SI proteomics of faecal washes.

Supplementary Table 4

Computational deconvolution.

Supplementary Table 5

GSEA results colon faecal wash of mice perturbation.

Supplementary Table 6

smFISH probes.

Supplementary Video 1

Active monocyte/macrophage shedding.

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Bahar Halpern, K., Korem Kohanim, Y., Biram, A. et al. The cellular states and fates of shed intestinal cells. Nat Metab 5, 1858–1869 (2023). https://doi.org/10.1038/s42255-023-00905-9

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