A multicellular self-organized probiotic platform for oral delivery enhances intestinal colonization

Abstract

Stable gut colonization of probiotics is essential for sustained therapeutic effects, however traditional oral probiotic supplements often fail to adapt to the gut environment. Here, based on the observation that multicellular microcolonies instead of planktonic bacteria display a more advantageous gene pattern for colonization, we design a system encapsulating multicellular self-organized probiotic microcolonies, termed Express Microcolony Service (EMS), for efficient oral delivery and enhanced gut colonization of probiotics. Utilizing the stress-relaxing and acid-resistant property of the covalent-ionic crosslinking alginate hydrogel microsphere, the micro-cargo provides tunable nutrient supply and extracellular matrix support to facilitate microcolony self-organization. Notably, we show that the variable spatial constraints of the stress-relaxing hydrogel could modulate the viability and colonization potential of microcolonies. In vitro, bacteria microcolonies in EMS show remarkable resistance to gastric acid, bile salts, and antibiotics, compared with planktonic probiotics. In vivo, the EMS strategy exhibits 89- and 52-fold higher colonization rate in the cecum and colon of mice, compared to conventional oral probiotics. The multicellular self-organized EMS system offers an innovative, efficient and clinically transformable alternative for probiotic therapy.

Fig. 1. Prokaryotic transcription sequencing between bacteria suspension and bacterial colony.

a Schematic illustration of the Express Microcolony Service (EMS) micro-cargo system which supports oral delivery of microcolony for biofilm formation of probiotics. Created in BioRender. Liu, H. (2025) https://BioRender.com/7lpn56z. b Schematic illustration of prokaryotic transcription sequencing. Created in BioRender. Liu, H. (2025) https://BioRender.com/h654r91. c The principal coordinate analysis between the colony group and the single bacterium group. d Volcano plot of the differential expressed genes (DEGs), analyzed by a two-tailed nbinomTest in DESeq. e Kyoto Encyclopedia of Gene and Genomes (KEGG) enrichment analysis, the colony group verse the single bacterium group. f Heatmap of biofilm formation-related gene expression. g Representative fluorescence image of colons (6 h after gavage). h IVIS radiant efficiency analysis displayed bacterial adhesion in the colon 3 h, 6 h, 12 h, 24 h after oral gavage. i Representative confocal image of intestinal mucosa with bacterial adhesion, scale bar 400 µm. Data in h were presented as mean ± SD (n = 3 biologically independent samples). Source data are provided as a Source Data file.

Fig. 2. Characteristics of stress-relaxed hydrogel and preparation of EMS micro-cargo.

a Schematic illustration of the design of dual-network hydrogel. Created in BioRender. Liu, H. (2025) https://BioRender.com/7lpn56z. b Evaluation of initial storage modulus of hydrogels under different crosslinking conditions (ion crosslink, covalent crosslink and double crosslink). c Stress-relaxation profiles of hydrogels with different Alginate to AlgMA ratios. d Relaxation half-time (τ1/2) of the AlgMA hydrogels. e Relative change in storage modulus (G’) compared to the initial storage modulus (G’₀) of the hydrogel during swelling in LB medium, expressed as G’/G’₀. f Weight change of swelling hydrogel in LB medium. g Weight change of swelling hydrogel in AGF and ASF. h Weight change of swelling hydrogel in ACF. i Schematic illustration of the preparation of EMS. Created in BioRender. Liu, H. (2025) https://BioRender.com/7lpn56z. j Optical image of the hydrogel micro-cargo. Scale bar 800 µm. k The size distribution of the micro-cargo. l Representative images of microcolonies in micro-cargo after being cultured for 2 h (I), 4 h (II), 6 h (III), and 8 h (IV), scale bar 200 µm. m Representative SEM image of the micro-cargo system (MS), primary micro-cargo system (PMS, encapsulated dispersed single bacteria) and the EMS micro-cargo system (encapsulated bacterial microcolonies). Representative images for 2j, l, m are shown, each experiment was repeated at least three times independently with similar results. Data in (d, g, h) were presented as mean ± SD (n = 5 independent samples). Source data are provided as a Source Data file.

Fig. 3. Gene-expression and biological behavior of microcolony from micro-cargo.

a mRNA level of quorum sensing-related gene sdiA of microcolony from different hydrogels. b mRNA level of adhesion-related gene csgA of microcolony from different hydrogels. c mRNA level of exopolysaccharide-related gene adrA of microcolony from different hydrogels. d mRNA level of stress response-related gene iraM of microcolony from different hydrogels.e Bacterial quantification in different hydrogel micro-cargoes. f Growth curve of bacteria after releasing from the hydrogel micro-cargoes. g mRNA level of colonization-related genes of microcolony from different hydrogels. h The principal coordinate analysis of bacterial transcriptome from 50% EMS group and the single bacterium group. i Volcano plot of DEGs of the two groups, analyzed by a two-tailed nbinomTest in DESeq. j Heat map of transcriptional differential genes of the two groups (important up-regulated genes of 50%EMS group were listed). k Up-regulated pathway of the 50% EMS group according to KEGG enrichment analysis. l Down-regulated pathway of the 50% EMS group according to KEGG enrichment analysis. For in k and l, the horizontal axis represents gene ratio, the vertical axis represents gene term, and the bubble size represents the enriched gene counts. The P-value was calculated by hypergeometric distribution method. Data in (a–d, g) were presented as mean ± SD (n = 3 independent samples). Source data are provided as a Source Data file.

Fig. 4. Formation and release of microcolony in hydrogel micro-cargoes.

a Representative image showing change of microcolony under different initial bacterial concentration (2 × 10⁵, 10⁶, or 5 × 10⁶ CFU/mL) and culture time (0 h, 2 h, 4 h, 6 h, 8 h, 12 h and 24 h). b Size analysis of microcolony according to the diameter. c The maximum diameter of the microcolony in hydrogel with different initial bacterial concentration. d Change of total bacteria in the micro-cargoes. e Live/Dead staining of microcolonies in hydrogel micro-cargoes. f Representative images of swelling and degradation process of hydrogel micro-cargo in ACF and the release of microcolony. The significance between the two groups was calculated utilizing a two-tailed Student’s t-test. Data are presented as mean ± SD (n = 10 independent samples for b, c; n = 3 independent samples for d). Source data are provided as a Source Data file.

Fig. 5. Evaluation of environmental resistance and colonization potential of microcolony.

a Schematic illustration of microcolony resistance to environmental assaults. Created in BioRender. Liu, H. (2025) https://BioRender.com/7u2jmla. b Spot assay showing the bacterial resistance against AGF, bile acid, and antibiotic. c Quantitative analysis of surviving bacteria after AGF treatment. d Quantitative analysis of surviving bacteria after bile acid treatment. e Quantitative analysis of surviving bacteria after antibiotic treatment. f Live/Dead staining of PMS after antibiotic treatment. g Live/Dead staining of EMS after antibiotic treatment. h Quantitative analysis of bacteria adhered to intestinal epithelial cell. i Quantitative analysis of EPS. j Representative image of crystal violet staining of biofilm, analyzing the biofilm-forming potential of PMS group, EMS group, PMS-D (dispersed) group, EMS-D group (dispersed means cells were dispersed and extracellular matrix was washed off). k Quantitative analysis of biofilm formation by measuring the crystal violet absorbance at 590 nm. l Timeline of mouse colonization model (n = 5). Created in BioRender. Liu, H. (2025) https://BioRender.com/jxkryqz. m Quantitative analysis of fecal EcN abundance within 3 days after gavage. n Quantitative analysis of fecal EcN abundance in small intestine (SI), cecum, and colon 3 days after gavage. The significance between the two groups was calculated utilizing the two-tailed Student’s t-test or Mann–Whitney U-test. Data are presented as mean ± SD (n = 3 independent samples for c–e, h, n = 5 independent samples for I; n = 6 independent samples for k; n = 5 independent animal samples for m, n). Source data are provided as a Source Data file.

Fig. 6. In vivo colonization analysis of EMS.

a Experimental design of DSS-induced colitis, all mice were randomly divided into 7 groups (n = 5 per group): healthy control, DSS group, DSS + 5-ASA group (positive control), DSS + EMS group (oral gavage of micro-cargo containing EcN microcolonies), DSS + PMS (oral gavage of micro-cargo containing EcN), DSS + EcN (oral gavage of EcN suspension), DSS + MS (oral gavage of blank micro-cargo). Created in BioRender. Liu, H. (2025) https://BioRender.com/jxkryqz. b Change of mice body weight at the end of modeling (day 9). c Daily changes of body weight of mice. d Analysis of disease activity index (DAI) score of each group. e Analysis of colon length of each group. f Macroscopic colon appearance. g Representative images of Hematoxylin and eosin (H&E) staining of colon tissue section. h Quantification of intestinal EcN abundance using qPCR method. i mRNA analysis of ZO-1 and Occludin of colon tissue. j mRNA analysis of IFN-γ, IL-1β, IL-6, TNF-alpha and MCP-1 of colon tissue. k Histogram of LDA value showing the difference of gut microbiota between the DSS and the EMS group. l Functional annotation clustering heat map showing the difference of gut microbiota between the DSS and the EMS group. m Schematic illustration of the colonization process of EcN from EMS and its beneficial effect. Created in BioRender. Liu, H. (2025) https://BioRender.com/7lpn56z. The significance between the two groups was calculated utilizing the two-tailed Student’s t-test. Data are presented as mean ± SD (n = 5 independent animal samples for b–e, h; n = 3 independent animal samples for i, j). Source data are provided as a Source Data file.