Orally biomimetic metal-phenolic nanozyme with quadruple safeguards for intestinal homeostasis to ameliorate ulcerative colitis

Abstract

Background: Ulcerative colitis (UC) is defined by persistent inflammatory processes within the gastrointestinal tract of uncertain etiology. Current therapeutic approaches are limited in their ability to address oxidative stress, inflammation, barrier function restoration, and modulation of gut microbiota in a coordinated manner to maintain intestinal homeostasis.

Results: This study involves the construction of a metal-phenolic nanozyme (Cur-Fe) through a ferric ion-mediated oxidative coupling of curcumin. Cur-Fe nanozyme exhibits superoxide dismutase (SOD)-like and •OH scavenging activities, demonstrating significant anti-inflammatory and anti-oxidant properties for maintaining intracellular redox balance in vitro. Drawing inspiration from Escherichia coli Nissle 1917 (EcN), a biomimetic Cur-Fe nanozyme (CF@EM) is subsequently developed by integrating Cur-Fe into the EcN membrane (EM) to improve the in vivo targeting ability and therapeutic effectiveness of the Cur-Fe nanozyme. When orally administered, CF@EM demonstrates a strong ability to colonize the inflamed colon and restore intestinal redox balance and barrier function in DSS-induced colitis models. Importantly, CF@EM influences the gut microbiome towards a beneficial state by enhancing bacterial diversity and shifting the compositional structure toward an anti-inflammatory phenotype. Furthermore, analysis of intestinal microbial metabolites supports the notion that the therapeutic efficacy of CF@EM is closely associated with bile acid metabolism.

Conclusion: Inspired by gut microbes, we have successfully synthesized a biomimetic Cur-Fe nanozyme with the ability to inhibit inflammation and restore intestinal homeostasis. Collectively, without appreciable systemic toxicity, this work provides an unprecedented opportunity for targeted oral nanomedicine in the treatment of ulcerative colitis.

Keywords: Inflammation; Intestinal homeostasis; Metal-phenolic nanozyme; Oxidative stress; Ulcerative colitis.

Fig. 1

Schematic illustration showing the synthesis and action mechanisms of biomimetic Cur-Fe nanozyme against ulcerative colitis. (A) Preparation of biomimetic Cur-Fe nanozyme (CF@EM) inspired by the probiotic membrane. (B) The intestinal colonization capacity of the probiotic membrane increases the concentration and duration of action of CF@EM at the site of inflammation, synergistically alleviating oxidative stress, restoring intestinal barrier function, relieving inflammation, and modulating the gut microbiota to alleviate ulcerative colitis

Fig. 2

Characterization and ROS scavenging activities. (A) TEM images of Cur-Fe and CF@EM. The image on the right shows the element mapping of Cur-Fe. (B) The fluorescence of curcumin and Cur-Fe. (C) FTIR of curcumin and Cur-Fe. (D) XPS of Cur-Fe. (E) SDS-PAGE protein analysis of EM, Cur-Fe, and CF@EM. (F) Particle size distribution of Cur-Fe and CF@EM. (G) Zeta-potential of Cur-Fe and CF@EM. (H) ESR spectra of BMPO indicating O₂^•− scavenge with Cur-Fe. (I) SOD assay kit to determine the SOD-like activity of Cur-Fe. (J) DPPH radical scavenging ratio of Cur-Fe. (K) Schematic illustration of the TMB + •OH scavenging process and the scavenging ratio of Cur-Fe. (L) Schematic illustration of the ABTS radical scavenging process and the scavenging ratio of Cur-Fe. Data were expressed as the mean ± SD (n = 3)

Fig. 3

Anti-inflammatory and antioxidant effects of Cur-Fe in vitro. (A, B) Fluorescence images (A) and flow cytometry quantification (B) of DCF stained RAW 264.7 cells after different treatments. (C, D) Fluorescence images (C) and flow cytometry quantification (D) of DHE. (E) Fluorescence images of calcein-AM/PI. (F) Flow cytometry quantification of Annexin V-FITC/PI. (G) The cell death ratio was calculated based on the flow cytometry data in (F). (H) The mRNA expression of inflammatory cytokines (TNF-α, IL-6, IL-12, and IL-1β) in different groups. (I) Quantitative assessment of M1 macrophages after different treatments by flow cytometry. Data were expressed as the mean ± SD (n = 3). Statistical analysis was performed using a two-tailed Student’s t-test. *P < 0.05, **P < 0.01, and ***P < 0.001, represented different statistical significances, and ns represents no statistical difference

Fig. 4

Intestinal colonization of CF@EM. (A) Fluorescence images of normal mice, DSS-induced colitis mice, colon tissues, and organs at indicated time points after oral Cur-Fe and CF@EM. H: heart; Li: liver; S: spleen; Lu: lung; K: kidney. (B, C) Quantification of mean fluorescence intensity in normal (B) and DSS-induced colitis mice (C) in vivo. (D) Quantification of mean fluorescence intensity in colon tissues of normal and DSS-induced mice. Data were expressed as the mean ± SD (n = 3). Statistical analysis was performed using a two-tailed Student’s t-test. *P < 0.05, **P < 0.01, and ***P < 0.001, represented different statistical significances, and ns represents no statistical difference

Fig. 5

Therapeutic efficacy of CF@EM in DSS-induced colitis. (A) Schematic illustration of the establishment and treatment of DSS-induced colitis mice. (B, C) Weight change curves (B) and DAI curves (C) of mice within 12 days. (D) The spleen index of mice in different treatment groups. (E) The length of the colon. (F) Endoscopic images, colon images, and H&E staining of mice in different treatment groups. (G) The MPO activity of mice. (H) The survival rate of mice in different treatment groups. Data were expressed as the mean ± SD (n = 3). Statistical analysis was performed using a two-tailed Student’s t-test. *P < 0.05, **P < 0.01, and ***P < 0.001, represented different statistical significances, and ns represents no statistical difference

Fig. 6

CF@EM relieves inflammation and restores intestinal barrier function. (A-D) The mRNA expression of TNF-α (A), IL-6 (B), IL-1β (C), and IL-12 (D) in different groups. (E) Evaluation of the M1 macrophage in the colon of the colitis mice after the treatment. (F) Fluorescence images of DHE. (G) Immunofluorescence image of tight junction protein (occludin, ZO-1, and claudin-1). Data were expressed as the mean ± SD (n = 3). Statistical analysis was performed using a two-tailed Student’s t-test. *P < 0.05, **P < 0.01, and ***P < 0.001, represented different statistical significances, and ns represents no statistical difference

Fig. 7

Preventive effect of CF@EM in DSS-induced colitis. (A) Schematic illustration of the establishment and treatment of DSS-induced colitis mice. (B, C) Weight change curves (B) and DAI curves (C) of mice within 8 days. (D, E) The spleen index (D) and length of the colon (E) in different treatment groups. (F) Fecal Images, endoscopic images, colon images, and H&E staining of mice in different treatment groups. (G) The mRNA expression of TNF-α, IL-6, and IL-1β in different groups. Data were expressed as the mean ± SD (n = 6). Statistical analysis was performed using a two-tailed Student’s t-test. *P < 0.05, **P < 0.01, and ***P < 0.001, represented different statistical significances, and ns represents no statistical difference

Fig. 8

Regulation of gut microbiota by CF@EM. (A) The species accumulation boxplot. The horizontal coordinate is the number of samples, the vertical coordinate is the number of feature sequences after sampling, and the overall result reflects the rate at which new feature sequences appear under continuous sampling. (B, C) The Simpson diversity index (B) and principal component analysis (C) of the control group, DSS group, and CF@EM group. (D) The abundance at the phylum level. (E) Heatmap of the relative abundance of the 35 most abundant genus-level. (F-H) The abundance of Bacteroidetes (F), Lactobacillus (G), and Muribaculum (H). (I, J) linear discriminant analysis effect size (LEfSe) and cladogram based on LEfSe analysis. LDA (log₁₀) > 4 was used as the cutoff value to indicate higher relative abundance in the corresponding group. In a cladogram, circles radiating from the inside out represent taxonomic levels from phylum to genus (or species). Each small circle at a different taxonomic level represents a taxon at that level, and the size of the circle diameter is proportional to the relative abundance size. Species that are not significantly different are uniformly represented in yellow, and green, blue, and red nodes indicate microbial taxa that are significant in the control, DSS, and CF@EM groups. Data were expressed as the mean ± SD (n = 5). Statistical analysis was performed using a two-tailed Student’s t-test. *P < 0.05, **P < 0.01, and ns represents no statistical difference

Fig. 9

Regulation of gut microbial metabolites by CF@EM. (A) The principal component analysis of the control group, DSS group, and CF@EM group. (B) Venn diagram of differential metabolites for between-group comparison. (C) Volcano plot of DSS compared with CF@EM. (D) Metabolite changes were compared between groups (total metabolites = 1596). (E) Relative content of amino acids between control, DSS, and CF@EM groups. (F) Relative content of fatty acids and conjugates. (G-I) Relative content of indoles and derivatives (G), 5-hydroxyindole-3-acetic acid (H), and indole-3-acrylic acid (I). (J) KEGG pathway enrichment analysis of DSS compared with CF@EM. (K-N) Relative content of lithocholic acid 3-sulfate (K), taurodeoxycholic acid (L), 7-ketolithocholic acid (M), and lithocholic acid (N) between control, DSS and CF@EM groups. Data were expressed as the mean ± SD (n = 5). Statistical analysis was performed using a two-tailed Student’s t-test. *P < 0.05, **P < 0.01, and ***P < 0.001, represented different statistical significances, and ns represents no statistical difference