--------------------------------------------- # Figures for "Sonic Hedgehog Acts as a Macrophage Chemoattractant During Regeneration of the Gastric Epithelium." Preferred citation (DataCite format): Chakrabarti, Jayati; Dua-Awereh, Martha; Schumacher, Michael; C. Engevik, Amy; Zavros, Yana (2021). Figures for "Sonic Hedgehog Acts as a Macrophage Chemoattractant During Regeneration of the Gastric Epithelium." University of Arizona Research Data Repository. Figure. https://doi.org/10.25422/azu.data.16798171 Corresponding Author: Yana Zavros, Cellular and Molecular Medicine, yzavros@email.arizona.edu License: CC BY 4.0 DOI: https://doi.org/10.25422/azu.data.16798171 --------------------------------------------- ## Summary Sonic Hedgehog (Shh), secreted from gastric parietal cells, contributes to the regeneration of the epithelium. The recruitment of macrophages plays a central role in the regenerative process. The mechanism that regulates macrophage recruitment in response to gastric injury is largely unknown. Here we tested the hypothesis that **** Shh stimulates macrophage chemotaxis to the injured epithelium and contributes to gastric regeneration. A mouse model expressing a myeloid cell-specific deletion of Smoothened (LysMcre/+;Smof/f) was generated using transgenic mice bearing loxP sites flanking the Smo gene (Smo loxP) and mice expressing a Cre recombinase transgene from the Lysozyme M locus (LysMCre). Acetic acid injury was induced in the stomachs of both control and LysMcre/+;Smof/f (SmoKO) mice and gastric epithelial regeneration and macrophage recruitment analyzed over a period of 7 days post-injury. Bone marrow-derived macrophages (BM-Mø) were collected from control and SmoKO mice. Human-derived gastric organoid/macrophage co-cultures were established, and macrophage chemotaxis measured. Compared to control mice, SmoKO animals exhibited inhibition of ulcer repair and normal epithelial regeneration, that correlated with decreased macrophage infiltration at the site of injury. Bone marrow chimera experiments using SmoKO donor cells showed that control chimera mice transplanted with SmoKO bone marrow donor cells exhibited a loss of ulcer repair, and transplantation of control bone marrow donor cells to SmoKO mice rescued epithelial cell regeneration. Histamine stimulated Shh secretion in human organoid/macrophage co-cultures resulted in macrophage migration toward the gastric epithelium, a response that was blocked with Smo inhibitor Vismodegib. Shh-induced macrophage migration was mediated by AKT signaling. **** In conclusion, Shh signaling acts as a macrophage chemoattractant via a Smo-dependent mechanism during gastric epithelial regeneration in response to injury. --------------------------------------------- ## Files and Folders Figure 1: Generation of LysMCre/SmoKO mice. (a) The LysMCre/SmoKO mice were generated by crossing the LysMCre with the Smoflx/flx. The LysMCre knock-in allele has a nuclear-localized Cre recombinase inserted into the lysozyme 2 gene (Lyz2). When crossed with Smoflx/flx mice, that have loxP sites flanking exon 1 of the Smo gene, Cre-mediated recombination results in deletion of the targeted gene in the myeloid cell lineage. Deletion of Smo was analyzed by (b) genotyping, and (c) PCR using RNA extracted from bone marrow-derived macrophages for SMO expression. (d) Ulcer sizes (mm2) 1-7 days post-injury in control, SmoKO, control mice transplanted with bone marrow derived from SmoKO mice (ControlSmoKO), and SmoKO mice transplanted with bone marrow derived from control mice (LysMCre/SmoKOcon). Data shown as the mean + SEM. Figure 2: Expression of Shh and macrophage infiltration in control and LysMCre/SmoKO mice. Immunohistochemistry of Shh expression in (a) control, and (b) LysMCre/SmoKO mouse stomachs. Shh expression at the ulcer margin of (c, d) control, and (e,f) LysMCre/SmoKO mouse stomachs. (g) Shh concentrations (pg/mL) measured in plasma collected from in control and LysMCre/SmoKO mice. Macrophage numbers (CD11b+F4/80+Ly6Chi) within the uninjured and injured gastric epithelium of (h) control and (i) LysMCre/SmoKO mice 1-7 post-ulcer induction. *P<0.05 compared to day 1 post-injury, n = 6 mice per group. Data shown as the mean + SEM. Figure 3: Expression of CD44v9, IL33 and IL13 within the stomachs of control and LysMCre/SmoKO mice. Representative immunofluorescence staining using antibodies specific for CD44v9 (green), IL33 (red) and IL13 (grey) in the stomachs of (a, e, i) control, (b, f, j) SmoKO, (d, g, k) ControlSmoKO, and (d, h, l) LysMCre/SmoKOcon mice. Representative immunofluorescence staining using antibodies specific for CD44v9 (green), IL33 (red) and IL13 (grey) in the stomachs of (m) control and (n) LysMCre/SmoKOcon mice. Quantification of fluorescence intensity of (o) CD44v9, (p) IL33 and (q) IL13 in mouse experimental groups. *P<0.05 compared to control group, n = 6 mice per group. Data shown as the mean + SEM. Figure 4: Macrophage migration and CCR2 expression. Migration plots of trajectories in response to (a) medium and (b, c) rmShh gradient using macrophages cultured from the bone marrow of control and SmoKO mice. (d) Macrophage migration represented as Forward Migration Index (FMI). Representative immunofluorescence stains of actin (green) and nuclei (red) of bone marrow-derived macrophages cultured from (e) control and (f) SmoKO mice treated with vehicle, CCL2 or rmShh. Arrows indicate filopodia. (g) Representative immunofluorescence stain of CCR2 (red) and nuclei (Hoechst, blue) of bone marrow-derived macrophages cultured from control or SmoKO mice and treated with PBS, rmShh or MCP. (h) Quantitative RT-PCR of CCR2 expression using RNA collected from control or SmoKO bone marrow-derived mouse macrophages and treated with PBS, Shh, MCP1 or CXC3L1. *P<0.05 compared to PBS vehicle control, n = 6 individual cultures. Data shown as the mean + SEM. Figure 5: Macrophage migration in an organoid/macrophage co-culture model. (a) Immunofluorescence imaging demonstrating migration of CD68+ macrophages cultured from control (MFcon) and SmoKO (MFSmoKO) mice towards mouse gastric organoids. Co-cultures were treated with vehicle or gastrin. (b) Macrophage migration within the co-cultures was quantified by Forward Migration Index (FMI). *P<0.001 compared to vehicle, n = 6 individual co-culture experiments. Data shown as the mean + SEM. Figure 6: Human gastric organoid/macrophage co-cultures. (a) Acridine orange assay using gastric organoids treated with either vehicle or histamine. (b) Shift in F458 (red)/F488 (green) fluorescence ratio was measured in the organoid cultures treated with vehicle or histamine. (c) Quantitative RT-PCR measuring changes in Shh expression in the gastric organoids treated with vehicle (control) or histamine (Hist). *P<0.05 compared to control, n = 4 cultures generated from 4 individual patients. (d) Bright-field micrographs showing tissue-derived human fundic gastric organoids (huFGOs), PBMC-derived macrophages and representative co-culture. Magnetic separation was used to isolate epithelial and immune cells from treated human gastric organoid/macrophage co-cultures. (f) RT-PCR demonstrating expression of Shh in EpCAM positive and CD68 in macrophage fractions. Data shown as the mean + SEM. Figure 7: Expression of Shh, Ptch1, CCR2 and M1/M2 macrophage markers in organoid/macrophage co-cultures. (a) Expression of Shh in EpCAM fractions isolated from vehicle (Veh, 1), vismodegib (Vis, 2), Histamine (Hist, 3) or Vis+Hist (4) treated co-cultures. (b)Expression of Ptch1 in MF fractions isolated from Veh, Vis, Hist or Vis+Hist treated co-cultures. (c) Expression of M1 and M2 markers in MF fractions isolated from Veh, Vis, Hist or Vis+Hist treated co-cultures. (d) Expression of CCR2 in MF fractions isolated from Veh, Vis, Hist or Vis+Hist treated co-cultures. (e) Protein expression of AKT and pAKT in MF fractions isolated from Veh, Vis, Hist or Vis+Hist treated co-cultures. Quantification of immunoblots in (e) are shown in (f). *P<0.05 compared to vehicle. Data shown as the mean+ SEM. Figure 8: Changes in CCR2 in mouse and human monocytes in response to Smo chemical inhibition or gene knockdown. (a) Flow cytometric contour plots demonstrating the gating strategy for quantification of CD11b+F4/80+Ly6CHiCCR2+ macrophages. (b) Quantification of flow cytometry analysis for the expression of CD11b+F4/80+Ly6CHiCCR2+macrophages within tissues and PBMCs collected in response to acetic acid induced injury. Uninjured controls were subjected to surgery and stomachs exposed to PBS. (c) Quantitative RT814 PCR documenting knockdown of Smoothened (SMOKD) in human-derived monocyte cultures. (d) Immunofluorescence of M1 or M2 macrophages in control and SMOKD cultures for CCR2 expression (red). (e) Fluorescence intensity of images captured in (d). Quantitative RT-PCR using RNA collected from control and SMOKD cultures polarized to either M1 or M2 macrophages and treated with vehicle (Veh), MCP-1, Shh or CX3CL1. *P<0.05 compared to control or vehicle groups, n = 3 individual biological replicates. Data shown as the mean + SEM. Figure 9: Organoid/ILC2/monocyte Interactive Co-Culture Plates. (a) Interactive Co-Culture Plates were used to culture human gastric-derived organoids and ILC2s in the left chamber and monocytes in the right chamber. Conditioned medium collected from the organoid/ILC2 co-culture was used to measure changes in (b) Shh, (c) IL-33 and (d) IL-13 secretion. (e) Bright-field micrographs of monocytes after treatment with vehicle, histamine, histamine + vismodegib, anti IL-33 immuneutralization antibody + Histamine or anti-IL-33 alone. (f) Quantitative RT-PCR was used to measure changes in M1/M2 markers in the monocyte cultures. Expression of M2 markers in monocyte chamber isolated from Veh (1), Vis (2), Hist (3) or Vis+Hist (4), anti-IL33 (5), anti-IL33+Hist (6), anti-IL13 (7), and anti-IL13+ Hist (8), treated co-cultures. (g) Immunofluorescence staining for expression of CD44v9 (green), IL-33 (red) and Hoechst (blue) in organoid/ILC2 co-cultures treated with vehicle, histamine or histamine + Vismodegib. (h) Fluorescence intensity for CD44v9 and IL-33 was quantified in co-cultures. *P<0.05 compared to vehicle, n = 3 co-cultures prepared from 3 individual patients. Data shown as the mean + SEM. FigH. is showing all the raw FCS files which were used to analyze Fig. 8A and B --------------------------------------------- ## Materials & Methods - Graphpad PRISM was used to generate all the graphs and for statistical analysis - FlowJo was used to analyze the raw .fcs files from flowcytometry - Nikon Elements software was used to quantify immunofluorescence images --------------------------------------------- ## Contributor Roles The roles are defined by the CRediT taxonomy http://credit.niso.org/ - Jayati Chakrabarti, University of Arizona College of Medicine, Department of Cellular and Molecular Medicine, Tucson, AZ, USA: Conceptualization, Data curation, Formal Analysis, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. - Martha Dua-Awereh, University of Cincinnati, Department of Pharmacology and Systems Physiology, Cincinnati, OH, USA: Conceptualization, Data curation, Formal Analysis, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. - Michael Schumacher, Division of Gastroenterology, Children’s Hospital Los Angeles, Los Angeles, CA, USA: Conceptualization, Data curation, Formal Analysis, Methodology, Software, Validation, Visualization, Writing – review & editing. - Amy Engevik, Department of Regenerative Medicine and Cell Biology, Medical University of South Carolina, Charleston, SC, USA: Conceptualization, Data curation, Formal Analysis, Methodology, Software, Validation, Visualization, Writing – review & editing. - Jennifer Hawkins, Department of Pediatric Surgery, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA: Resources, Validation, Writing – review & editing. - Michael A. Helmrath, Department of Pediatric Surgery, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA: Conceptualization, Validation, Resources, Writing – review & editing. - Yana Zavros, University of Arizona College of Medicine, Department of Cellular and Molecular Medicine, Tucson, AZ, USA: Conceptualization, Data curation, Formal Analysis, Methodology, Software, Validation, Visualization, Funding acquisition, Investigation, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing.