Intestinal organoid screen reveals that Bacillus velezensis PGM541 promotes epithelial proliferation via its metabolite butyric acid.

Skip to main content An official website of the United States government Here's how you know Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites. Search Log in Dashboard Publications Account settings Log out Search… Search NCBI Primary site navigation Search Logged in as: Dashboard Publications Account settings Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide PERMALINK Copy As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Microbiome . 2026 Mar 5;14:116. doi: 10.1186/s40168-026-02346-4 Search in PMC Search in PubMed View in NLM Catalog Add to search Intestinal organoid screen reveals that Bacillus velezensis PGM541 promotes epithelial proliferation via its metabolite butyric acid Yitong Zhang Yitong Zhang 1 Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, China Find articles by Yitong Zhang 1 , Qunbing Hu Qunbing Hu 1 Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, China Find articles by Qunbing Hu 1 , Xianglin Zeng Xianglin Zeng 1 Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, China Find articles by Xianglin Zeng 1 , Lanmei Yin Lanmei Yin 1 Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, China 2 Key Laboratory of Agro-Ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China Find articles by Lanmei Yin 1, 2 , Yan Tang Yan Tang 1 Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, China Find articles by Yan Tang 1 , Qiye Wang Qiye Wang 1 Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, China 3 Yuelushan Laboratory, Changsha, China Find articles by Qiye Wang 1, 3 , Jing Huang Jing Huang 1 Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, China Find articles by Jing Huang 1 , Jianzhong Li Jianzhong Li 1 Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, China Find articles by Jianzhong Li 1 , Huansheng Yang Huansheng Yang 1 Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, China 2 Key Laboratory of Agro-Ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China 3 Yuelushan Laboratory, Changsha, China Find articles by Huansheng Yang 1, 2, 3, ✉ Author information Article notes Copyright and License information 1 Hunan International Joint Laboratory of Animal Intestinal Ecology and Health, Laboratory of Animal Nutrition and Human Health, College of Life Sciences, Hunan Normal University, Changsha, China 2 Key Laboratory of Agro-Ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China 3 Yuelushan Laboratory, Changsha, China ✉ Corresponding author. Received 2025 Aug 22; Accepted 2026 Jan 12; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13072481  PMID: 41787561 Abstract Background Probiotics have been widely used for the regulation of intestinal health. Current screening methods for probiotics typically rely on animal or two-dimensional cell models. In this study, we employed intestinal organoids to identify a candidate probiotic strain. Furthermore, we investigated the potential mechanisms through which this strain and its active metabolites exert their effects, thereby evaluating the efficacy of this screening approach. Results Firstly, candidate probiotic strain PGM541 was identified from a porcine-derived Bacillus library by assessing organoid viability. Subsequently, to validate the organoid screening reliability, the potential mechanism of strain PGM541 on the intestinal epithelium was investigated; it was found to exhibit probiotic functions by regulating cell proliferation in both in vitro organoid and in vivo piglet models. Furthermore, organoid screening combined with metabolomic analysis identified butyric acid (BA) as the key bioactive metabolite responsible for driving epithelial proliferation. Whole-genome and transcriptomic analyses revealed the biosynthetic pathway of BA in strain PGM541. Importantly, BA receptor blockade experiments directly confirmed that BA enhances epithelial proliferation via interaction with the FFAR2 receptor, thereby validating its functional activity. Additionally, strain PGM541 exhibited protective effects against dextran sulfate sodium (DSS)-induced colitis, further validating the effectiveness of the intestinal organoid platform for probiotic screening. Conclusions The probiotic strain PGM541, which was screened using intestinal organoids, promotes intestinal epithelial cell proliferation via its metabolite BA activating the FFAR2 receptor. These findings demonstrate that the intestinal organoid model serves as an effective platform for both preliminary probiotic screening and mechanistic investigation. Your browser is not supporting the HTML5 <video> element. You may download that video as a file and play it with a player of you choice. Download video stream . Download video file (27.1MB, mp4) Open in a new tab Video Abstract Supplementary Information The online version contains supplementary material available at 10.1186/s40168-026-02346-4. Keywords: Bacillus PGM541, Butyric acid, FFAR2 receptor, Intestinal organoids, Probiotic screening, Epithelial proliferation Introduction Probiotics are microorganisms that confer health benefits to the host [ 1 ]. In recent years, they have attracted much attention due to their potential health benefits, including improved digestion, alleviation of gastrointestinal disorders, and maintenance of a healthy gut microbiome [ 2 ]. Among documented probiotics, Lactobacillus species have been extensively utilized as primary sources [ 3 ], while Bacillus species, due to their spore-forming ability, have the feasibility for large-scale production, high storage stability, and tolerance to the digestive tract environment, and have become an attractive additive for livestock production [ 4 , 5 ]. Notably, although a large number of fermented products can serve as sources of probiotics [ 6 ], host-derived microorganisms are considered the ideal choice due to their greater adaptability [ 7 ]. Consequently, strains isolated from the host itself often demonstrate superior colonization and functional performance [ 8 , 9 ]. Indeed, numerous probiotic strains have been successfully identified through the screening of feces from host animals [ 10 ]. Based on all of the above, we isolated and constructed a Bacillus strain library from porcine intestinal contents. Studies have shown that the safety and functionality of probiotics depend on both the species and the specific strain [ 11 ]. It is important to emphasize that while many Bacillus species have been confirmed to possess excellent probiotic properties, the genus also includes potentially pathogenic strains such as Bacillus cereus [ 12 , 13 ]. Therefore, the systematic screening of this strain library to identify novel probiotics that are both safe and effective represents a critical step in this study. Although most studies have focused on the effects of probiotics on the host, there is an increasing interest in understanding the molecular mediators that enable probiotics to exert their effects. Studies indicate that probiotic metabolites, specifically short-chain fatty acids (SCFAs), indole derivatives, conjugated linoleic acid, and bacteriocins, constitute primary factors in promoting gastrointestinal health [ 14 , 15 ]. These bioactive compounds directly or indirectly activate relevant receptors to induce cellular responses [ 16 , 17 ], thereby mediating antimicrobial, anti-inflammatory, immunomodulatory, antitumor, and barrier-protective effects in the host [ 18 ]. Recently, compared to live probiotics, components derived from probiotics have garnered increasing attention due to their high safety, high stability, and strong target specificity [ 14 , 19 ]. However, the extensive diversity of microbial metabolites combined with their complex interactions presents significant challenges for identifying key bioactive metabolites and characterizing their functions, making the discovery of core effector molecules a critical obstacle in deciphering probiotic mechanisms of action. Previous studies on the interaction between the intestinal microbiota and intestinal epithelial cells mostly used intestinal epithelial cell lines. However, these cell lines are difficult to truly simulate the complex environment within the intestine [ 20 ]. Exploring the effects of probiotics on host health through animal models has limitations such as low efficiency, insufficient accuracy, and high time and economic costs [ 21 , 22 ]. Therefore, it is imperative to develop an economical, efficient, and reliable probiotic screening technology. Intestinal organoids containing intestinal stem cells (ISCs) can differentiate into all intestinal epithelial cell lineages, such as absorptive cells, goblet cells, and Paneth cells [ 23 ]. Compared with single cell lines, organoids better recapitulate the reality of gut-microbiota interactions [ 24 ], while avoiding the high costs associated with animal models [ 25 ] and offering significant ethical advantages [ 26 ]. Thus, organoids serve as an ideal platform for screening beneficial bacterial strains. Furthermore, genomics enables comprehensive sequencing of microbial genomes [ 27 ], yet it cannot directly reveal transcriptional activity. Therefore, microbial transcriptomics has become an important tool for characterizing intestinal microbiota mRNA expression and predicting their metabolic potential [ 28 ]. And metabolomics further reflects the phenotypic output of genomic and transcriptomic regulation, allowing precise quantitative analysis of metabolites [ 29 , 30 ]. However, a single omics approach is insufficient to fully elucidate complex biological processes. Integrating multiple omics strategies has emerged as an advanced methodology for mining microbially derived bioactive compounds [ 31 , 32 ]. Given that ISCs play a central regulatory role when probiotic metabolites exert effects on the intestinal epithelium [ 33 ], and organoids serve as ideal models for studying ISCs [ 34 , 35 ], the combination of multi-omics technologies integrating genomics, transcriptomics, and metabolomics with organoid models represents a highly promising research direction for screening and functionally validating active effector molecules. In this study, we employed intestinal organoids to screen Bacillus species for identifying probiotics and their bioactive metabolites. We identified a new Bacillus strain PGM541 and demonstrated that the bioactive metabolite butyric acid (BA) derived from this strain significantly enhances intestinal epithelial cell proliferation. This research not only provides theoretical support for probiotic development but also validates the application value of organoid technology in exploring bioactive substances from probiotics. Materials and methods Establishment of a porcine-derived Bacillus library and preparation of cell-free supernatant To construct a porcine-derived Bacillus strain library, intestinal contents from the colon of healthy pigs were collected as samples. Approximately 1 g of sample was mixed with 10 mL of sterile saline (Meilun Biotech, Dalian, China), vortexed thoroughly, and allowed to stand for 30 min. The mixture was then heat-treated (80 °C, 20 min) to eliminate vegetative cells, serially diluted 100-fold with saline, and 100 µL was spread on LB Agar medium (Lysogeny Broth Agar, Sangon Biotech, Shanghai, China) followed by incubation at 37 °C for 24 h upside down. Single colonies with typical morphology and robust growth were selected for further purification. Purified strains were mixed with an equal volume of 40% (v/v) glycerol (Meilun Biotech, Dalian, China) and stored at − 80 °C. Finally, all isolates were molecularly identified by 16S rDNA sequencing, successfully establishing a germplasm resource library comprising multiple Bacillus strains. Optical density (OD) is often used to express the turbidity of microbial cultures, which is a representation of the cell density [ 36 ]. The strains were cultured in LB medium (Lysogeny Broth, Sangon Biotech, Shanghai, China) at 37 °C for 24 h. The OD of the bacterial culture was measured at a wavelength of 600 nm using fresh LB medium as a blank. The culture was then diluted with LB medium to adjust the OD₆₀₀ to 1.0. Subsequently, the cultures were centrifuged at 12,000 × g for 10 min to collect the supernatant, which was then filtered through a 0.22-μm Millex™-GP filter (Merck, Shanghai, China) to obtain the cell-free supernatant (CFS). Utilizing organoid platforms for probiotic selection The methods of isolation and culture of jejunal organoids were described by Wang et al. [ 37 ]. Briefly, the jejunum was dissected longitudinally and rinsed with PBS (Meilun Biotech, Dalian, China). A slide was used to gently scrape the jejunum villi, and then the jejunum was cut into small pieces. The jejunum fragments were transferred to a 50-mL tube and washed 3 times with PBS. Tissues were added to PBS containing 2.5 mM ethylenediaminetetraacetic acid disodium salt (Sigma-Aldrich, St. Louis, MO, USA) and placed on a 4 °C rotator for 30 min to facilitate epithelial separation. After removing the supernatant, PBS was used to gently agitate the tissue up and down 20 times to achieve high crypt purity. The suspension was filtered through a 70-μm filter, and the crypts were suspended in 10% (vol/vol) fetal calf serum (FCS; Thermo Fisher Scientific, Waltham, MA, USA). After centrifuging at 1200 × g for 5 min, the supernatant was discarded, and about 2-mL medium was added, which consisted of Advanced DMEM/F12 (Gibco, Grand Island, NE, USA), 1% of GlutaMAXTM Supplement (Gibco), 10 mM of HEPES (Gibco), 100 U/mL of penicillin (Gibco), 100 μg/mL streptomycin (Gibco), and 1000 × antibiotic (Gibco). The supernatant was then centrifuged at 600 × g for 5 min. Matrigel (Corning, Bedford, OH, USA) was added to suspend the crypts. Next, 40 μL of the Matrigel with crypts was added to the center of a preheated 24-well culture dish. After 20 min in an incubator at 37 °C, 500 μL of medium was added to each well following Matrigel solidification; the culture medium was supplemented with Wnt3a, Noggoin, R-spondin1 (WNR) conditioned medium, FCS, N2 supplement (Gibco), B27 supplement (Gibco), n-Acetyl Cysteine (Invitrogen), nicotinamide (Sigma–Aldrich), EGF (Sigma–Aldrich), A83-01 (TGF-beta inhibitor, Tocris), SB202190 (p38 inhibitor, R&D Systems), and Y27632 (Rho-kinase inhibitor, R&D Systems). The passaging was performed every 4 days with a 1:4 split ratio. The intestinal organoids were treated with 0.1% CFS (v/v; CFS/culture medium) from different Bacillus strains for 4 days, during which the culture medium remained unchanged. The organoids were observed under an inverted microscope on day 4. To quantify the morphological features of the organoids, we measured the budding efficiency, crypt depth, and the crypts per organoid. Budding efficiency was calculated as the ratio of budded organoids to the total number of organoids. Crypts per organoid were determined by counting the number of crypts on each organoid. Both budding efficiency and crypts per organoid were quantified by manual counting. Crypt depth was measured automatically using Image-Pro Plus 6.0 software (Leica Imaging Systems Ltd., Cambridge, UK). To facilitate standardized comparison, in the experiment screening for probiotics from the Bacillus library using organoids, the measurements for the LB control group were normalized, with their mean value set to 1. The corresponding values for all other groups were expressed as ratios relative to this LB control group and were defined as the relative budding efficiency, relative crypt depth, and relative crypts per organoid, respectively. Statistical analysis was performed with individual culture wells as independent experimental units, and all organoids contacting the image border were excluded from analysis. Each treatment condition included technical replicates from three independent culture wells. After multiple rounds of screening, the strain PGM541, which exhibited the most significant enhancement on organoid crypt depth, was selected. Organoids treated with the CFS of strain PGM541 were collected in 15-mL centrifuge tubes using ice-cold PBS. After centrifugation at 2000 × g for 10 min, the supernatant was discarded. The samples were fixed with 2 mL of neutral buffered formalin (Sigma-Aldrich, St. Louis, MO, USA) for 30 min, followed by gradient dehydration through 75%, 95%, and 100% ethanol (10 min per step). After dehydration, the samples were cleared with 2 mL of xylenes (Sigma-Aldrich, St. Louis, MO, USA) and subsequently transferred to embedding cassettes for paraffin embedding. Finally, the embedded organoid sections were subjected to immunohistochemistry (IHC) and Alcian Blue-periodic Acid Schiff (AB-PAS) staining. The organoids treated with strain PGM541-CFS were also collected in Trizol reagent (Takara, Tokyo, Japan) and subsequently subjected to transcriptome sequencing analysis and real-time quantitative PCR (RT-qpcr). Piglets and experimental procedures A total of 16 1-day-old male suckling piglets (Large White × Landrace × Duroc, weighing 1.50 ± 0.05 kg) were selected and randomly assigned to two groups. The groups were as follows: a control group (CON) that was administered normal saline and a treatment group that was administered a solution of strain PGM541 (10 9 CFU/kg body weight/day) via gavage for 21 days [ 38 ]. During the experimental period, all piglets were raised by mother sows (8 piglets per litter) and were given free access to milk in farrowing crates under conditions of approximately 70% humidity and a temperature of 30 ± 2 °C. The growth conditions of the piglets were recorded during the experiment. After the experiment, piglets were euthanized by intravenous injection of a lethal dose of sodium pentobarbital (100 mg/kg). Death was confirmed by verifying pupillary dilation and the complete cessation of heartbeat and respiration. Subsequently, colon contents as well as intestinal tissues from the jejunum and colon were collected, and jejunal and colonic organoids were isolated. In addition, colon organoids were isolated using the same method as for jejunal organoids, but the culture medium required the additional supplementation of Prostaglandin E2 (MedChemExpress, Monmouth Junction, NJ, USA) and gastrin (Thermo Fisher Scientific, Waltham, MA, USA). The experimental design and procedures in this study were reviewed and approved by the Animal Care and Use Committee of Hunan Normal University, Changsha, Hunan, China (permit number: CACAHU 2021–00116). Mice and experimental procedures The experimental protocol was reviewed and approved by the Animal Care and Use Committee of Hunan Normal University, Changsha City, Hunan, China (Approval number 2022–0016). Forty-eight male C57BL/6 mice (21 days old, with similar body weights) were housed under controlled conditions of temperature (23 °C), humidity (55% ± 10%), and light (12:12 light–dark cycle), and were provided free access to standard chow and tap water for a 1-week adaptation period. Subsequently, these mice were randomly divided into three groups (16 mice per group): normal control (CON), model control (DSS, dextran sulfate sodium; Merck KGaA, Darmstadt, Germany), and strain PGM541 group (DSS + 541). The CON and DSS groups were fed with the basal diet, while the DSS + 541 group was fed a custom diet (which was prepared by Jiangsu Xietong Medical Bioengineering Co., Ltd.) containing strain PGM541 at a dosage of 10 9 CFU per kg of basal diet daily, and the mice were provided free access to the diet throughout the study, for a duration of 3 weeks. On day 21, all mice except the CON (normal control) group were administered drinking water supplemented with 3% DSS for 7 days. Thereafter, body weight (BW), feed intake, and the presence of hematochezia were monitored and recorded for each mouse. BW, average daily gain (ADG), and average daily feed intake (ADFI) were determined using previously described methods to evaluate growth performance [ 39 ]. At the end of the experiment, mice were euthanized by placement in a carbon dioxide (CO 2 ) induction chamber. Compressed CO 2 was introduced at a flow rate of 30% chamber volume per minute until cessation of breathing was confirmed. Death was verified by the absence of a heartbeat and lack of response to a painful stimulus. Subsequently, intestinal indicators (small intestine length, relative small intestine length, small intestine weight, relative small intestine weight) were measured, and jejunal and colonic tissues were collected. Histomorphometric analysis Intestinal tissues were rinsed with PBS, fixed in 10% neutral buffered formalin, and stored at 4 °C until processing for H&E staining. The villus height (VH), villus width (VW), and crypt depth (CD) in the jejunum, as well as the CD in the colon, were measured using the Image-Pro Plus 6.0 software. Specifically, these parameters were measured at × 10 magnification for pigs and at × 20 magnification for mice. The reported values for jejunal parameters represent the mean of at least 30 well-oriented and intact villus-crypt axes, and the colonic CD values represent the mean of at least 30 complete crypts [ 40 ]. IHC and AB-PAS staining Paraffin-embedded sections of organoids, piglet jejunum, and mouse jejunum underwent antigen retrieval by boiling twice in citrate buffer (0.01 M, pH 6.0). Sections were blocked with 5% bovine serum albumin (BSA; Boster Biological Technology Co. Ltd, Wuhan, China) at 37 °C, followed by incubation with either Ki-67 antibody (Abcam, ab15580; 1:800 dilution) or chromogranin A antibody (ChgA; Abcam, ab45179; 1:600 dilution) for 90 min at 37 °C. Subsequently, sections were treated with goat anti-rabbit immunoglobulin G (IgG) secondary antibody (PV-6001, ZSGB-BIO, Beijing, China) for 50 min [ 41 ]. Positive cells were visualized using a diaminobenzidine (DAB) kit (ZSGB-BIO, Beijing, China), stained with hematoxylin, and finally mounted with Neutral Balsam (Beyotime Biotechnology, Shanghai, China) for long-term preservation. For goblet cell observation, sections were stained with AB-PAS (Nanjing Jiancheng Bioengineering Institute, Nanjing, China) according to the manufacturer’s protocol [ 42 ]. In brief, following deparaffinization, sections were hydrated through a graded ethanol series (from 95% to distilled water), immersing for 2 min at each gradient. Alcian blue staining solution was applied for 15 min, followed by treatment with periodic acid stain for 10 min. After rinsing with distilled water for 2 min, the sections were thoroughly air-dried. Schiff’s reagent was then applied and allowed to react for 5 min. This was followed by a gentle 5-min rinse under running tap water. Finally, after the sections on the glass slides were completely air-dried, they were mounted for light microscopic observation. The Image-Pro Plus 6.0 software was used to calculate the number of Chg A-positive cells and goblet cells in at least 30 well-oriented villi or crypts, as well as the number of Ki67-positive cells in the crypts [ 43 ]. Measurement of the SCFA concentrations The colonic contents were homogenized, and 1 g of each sample was diluted with distilled water. The mixture was then mechanically oscillated and centrifuged at 12,000 × g for 15 min. The supernatant was mixed with 25% metaphosphoric acid solution (Sigma-Aldrich, St. Louis, MO, USA) at a ratio of 9:1 and the mixture was allowed to stand overnight. Subsequently, the solution was centrifuged and filtered through a 0.22-μm microporous membrane (Sangon Biotech, Shanghai, China). The concentrations of SCFAs (acetic acid, AA; propionic acid, PA; BA; isobutyric acid, IBA; valeric acid, VA; isovaleric acid, IVA) in these samples were determined using gas chromatography (GC; Agilent Technologies 7890B system; Agilent) equipped with a DB-FFAP column (30 m × 250 μm × 0.25 μm) [ 44 – 46 ]. Furthermore, the CFS of strain PGM541 cultured to an OD 600 of 1 was mixed with a 25% metaphosphoric acid solution at a 9:1 ratio, fixed for 3 h, and subsequently subjected to BA concentration by GC. RNA extraction and RT-qPCR Total RNA was extracted from strain PGM541-treated organoids and jejunal tissues of piglets fed with PGM541. Total RNA was extracted using the Trizol reagent and dissolved in diethyl pyrocarbonate (DEPC)-treated water (Sangon Biotech, Shanghai, China). The quality of RNA was checked using agarose gel electrophoresis, and the concentration of RNA was measured with an Eppendorf Biophotometer (Eppendorf AG, Hamburg, Germany). cDNA was synthesized using the PrimeScript™ II 1 st Strand cDNA Synthesis Kit (TaKaRa, Shiga, Japan) according to the instructions of the manufacturer. Briefly, cDNA was synthesized through incubating 1.0 μg total RNA with DNase I for 2 min at 42 °C and was reverse-transcribed using Oligo (dT) primers for 15 min at 37 °C, for 5 s at 85 °C in a 20-μL reaction volume. Primers for selected differentially expressed genes were designed using Primer Premier (version 5.0) as shown in Table S1 (in Supplementary Material 1). Each of the PCR reactions was performed on a QuantStudio 5 RT-PCR System (Thermo Fisher Scientific Inc., Rockford, IL, USA) with 5 μL of SYBR Green mix, 0.3 μL of forward and 0.3 μL of reverse primers respectively, 3.4 μL of sterile double-distilled H 2 O, and 1 μL of cDNA. The PCR cycling conditions were as follows: pre-denaturation at 95 °C for 10 s; amplification for 40 cycles at 95 °C for 5 s and at 60 °C for 20 s. The melting curve and the amplification curve were checked to ensure the specificity of both primers and PCR products. The housekeeping gene (RPL4) was employed to normalize the expression of the target gene, with the gene expression values being calculated with the 2 −△△Ct method. All samples were prepared in triplicate on each 384-well plate. The values of each duplicate were averaged for subsequent statistical analyses [ 47 ]. 16S molecular biology identification Single colonies were selected from LB Agar plates and inoculated into LB liquid medium, followed by overnight incubation at 37 °C with shaking at 900 × g. Genomic DNA was extracted using the EasyPure Bacterial Genomic DNA Kit (TransGen Biotech, Beijing, China) according to the manufacturer’s instructions. The bacterial culture was centrifuged at 250 × g for 5 min, and the supernatant was discarded. The pellet was resuspended in 100 μL of lysis buffer by thorough mixing, after which 20 μL of proteinase K was added and mixed by vortexing. The mixture was incubated at room temperature for 2 min. Then, 500 μL of binding buffer was added, followed by vortexing for 5 s and incubation at room temperature for 10 min. The entire lysate was loaded into a spin column and centrifuged at 12,000 × g for 30 s. The flow-through was discarded. The column was washed sequentially with 500 μL of clean buffer and 500 μL of wash buffer (twice), with each wash step involving centrifugation at 12,000 × g for 30 s and discarding of the flow-through. After the final wash, the column was centrifuged at 12,000 × g for 2 min to remove residual buffer. DNA was eluted by adding 200 μL of pre-heated elution buffer (60 °C) to the center of the column membrane, incubating at room temperature for 1 min, and centrifuging at 12,000 × g for 1 min. The eluted DNA was stored at − 20 °C [ 48 ]. Using DNA extracted from the strain as a template, the 16S rDNA gene was amplified from the bacterial genomic DNA with universal bacterial primers 27 F (5′-AGAGTTTGATCCTGGCTCAG-3′) and 1492R (5′-GGTTACCTTGTTACGACTT-3′) [ 49 ]. The PCR conditions were as follows: 98℃ for 2 min; 98℃ for 10 s, 56℃ for 15 s, 72℃ for 1 min, a total of 35 cycles; 72℃ for 10 min for extension, and 16℃ for reaction termination. The amplified products were sent to Sangon Biotech (Shanghai, China) for sequencing. The spliced sequences were compared with data in the NCBI database, and phylogenetically related reference bacteria were analyzed using Molecular Evolutionary Genetics Analysis 6.0 software (MEGA; Arizona State University, USA) to construct a phylogenetic tree for visual observation of bacterial genera and species. Whole-genome sequencing of strain PGM541 The strain PGM541 was purified for more than five generations. The bacterial cell precipitates were collected by centrifugation at 1000 × g for 10 min, and then the whole-genome sequencing was completed by Bimalco Company (Beijing, China). The experimental process was carried out in accordance with the standard protocol provided by Oxford Nanopore Technologies (ONT), including sample quality testing, library construction, library quality testing, and library sequencing. In addition, the genomic components were analyzed, and genome functional annotations (such as databases like Clusters of Orthologous Genes, COG; Kyoto Encyclopedia of Genes and Genomes, KEGG) were conducted, and a genome map was provided [ 50 ]. The whole-genome sequence of the strain PGM541 has been deposited in the NCBI GenBank database under the accession number PRJNA1321332, with the BioSample accession number SAMN51204440. Transcriptome analysis The eukaryotic transcriptome analysis of organoids treated with strain PGM541 was conducted as described by Liu et al. [ 51 ]. Total RNA extraction and sequencing were performed by Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). The RNA-seq transcriptome library was constructed using the Illumina TruSeq™ RNA Sample Preparation Kit (San Diego, CA, USA). Sequences were annotated against multiple databases including Gene Ontology (GO) to identify functional genes and analyze metabolic pathways; gene set enrichment analysis (GSEA) was performed using the “clusterProfiler” package (version 3.14.3) in R (version 3.6.3), and expression pattern clustering heatmap analysis was conducted on genes/transcripts in selected gene sets to observe trends in gene expression changes. Additionally, the strain PGM541 was subjected to prokaryotic transcriptome analysis. The expression levels of genes and transcripts were quantified separately using the RSEM software (RNA-Seq by Expectation–Maximization, Bo Li and Colin Dewey, University of Wisconsin–Madison, USA) package for expression quantification. LC–MS/MS non-target metabolomics The culture of strain PGM541 was centrifuged at 12,000 × g for 10 min, and the supernatant was filtered through a 0.22-μm Millex™-GP filter. Used high-performance liquid chromatography (HPLC) technology (Agilent 1260, HPLC, CA, USA) to separate the LB medium and the strain PGM541-CFS. Separation was carried out on an ACQUITY UPLC® HSS T3 column (100 × 2.1 mm, 1.8 μm; Waters Corp., Milford, MA, USA) protected by a corresponding ACQUITY UPLC® HSS T3 VanGuard pre-column (5 × 2.1 mm, 1.8 μm; Waters). The mobile phase consisted of (A) water containing 0.1% formic acid and 10 mM ammonium formate and (B) acetonitrile, delivered at a constant flow rate of 0.35 mL/min. The gradient elution program was set as follows: 0–2 min, 95% B; 2–10 min, 95 → 30% B; 10–12 min, 30 → 10% B; 12–13 min, 10% B; 13–13.1 min, 10 → 95% B; 13.1–16 min, 95% B (column re-equilibration). The total running time is 16 min and the injection volume is 20 μL. Collected the samples at 2-min intervals, a total of 8 times [ 52 ]. Then, the bacterial supernatant of each time group was freeze-dried and used to treat jejunal organoids to determine the retention time of the effective metabolites. The supernatant of the time group (4–6 min) containing the active metabolites was sent to Shanghai Bioprofile Technology Company Ltd for non-target metabolomics analysis. Transferred 100 μL of the sample into an EP tube, added 400 μL of pre-cooled methanol–acetonitrile (v:v = 1:1), and vortex mix for 30 s. In the ultrasonic disruption instrument, operate at 30% power for 2 min (3 s on, 5 s off), then briefly centrifuge, and placed it in the − 20 °C refrigerator for 1 h; centrifuged the sample at 4 °C, 13,000 × g for 15 min; took the supernatant, filtered it through a 0.22-μm filter membrane, and placed it in the sample injection bottle for instrument detection. The original data were processed using the Agilent MassHunter Profinder software (Version 10.0.2) for peak identification, peak extraction, peak alignment, and integration, and the files were exported to the Agilent Mass Profiler Professional software (Version 15.1). Then, the metabolites were identified using the METLIN database, and a quantitative list including metabolite names, mass-to-charge ratio (m/z), retention time (rt), and peak area (area) was obtained [ 53 ]. Intestinal organoid treatment Jejunal organoids were treated separately as follows: (1) HPLC time-fractionated bacterial supernatants (8 fractions); (2) the top six metabolites (dimethyl sulfoxide, lauryldiethanolamine, aspartic acid, di-N-propylamine, BA, and PC (16:0/18:2)) identified by untargeted metabolomic analysis; (3) differential SCFAs from piglet colonic contents (isobutyric acid and valeric acid). On day 4, the organoids were observed using an inverted microscope. The contents of the piglets’ colons were homogenized in PBS (10% w/v), then centrifuged at 12,000 × g for 10 min (4 °C) and filtered through a 0.22-µM Millex™-GP filter in an aseptic environment to obtained colonic content-derived supernatant (CCS) [ 54 ]. The jejunal organoids (passage 3) were treated for 3 days with CCS diluted (1:250 v/v) in the organoid culture medium. Meanwhile, jejunal organoids were co-treated with CCS (1:250 v/v) and 120 μM GLPG0974 (the receptor antagonist of FFAR2 ; MedChemExpress, Shanghai, China), and the same co-treatment was applied with 0.1 mM BA and 120 μM GLPG0974. Organoids were observed with an inverted microscope on day 3, and organoids were collected from the BA-alone treatment group, the CCS + GLPG0974 combination treatment group, and the BA + GLPG0974 combination treatment group for paraffin sectioning and immunohistochemical detection. Statistical analysis All statistical analyses were performed using SPSS software (version 22.0; IBM Corp., Chicago, IL, USA). Any value that deviated more than 3 standard deviations from the standardized mean was excluded. For comparisons between two groups (strain PGM541-treated organoids and piglet experiments; HPLC fraction-treated organoid experiments), the Shapiro–Wilk test was used to assess normality. Data conforming to a normal distribution were analyzed by an independent samples Student’s t -test, while data not conforming to a normal distribution were analyzed by the Mann–Whitney U test. For comparisons among three or more groups (multi-strain screening and metabolite experiments in organoids; mouse DSS experiments), one-way analysis of variance (ANOVA) was performed for normally distributed data. If the data did not meet the assumption of normality, the Kruskal–Wallis test was applied. For experiments involving co-treatment with GLPG0974 and CCS or BA, two-way ANOVA was conducted, followed by Tukey’s multiple comparison test. Data were presented as the mean ± standard error of the mean (SEM). Differences with P < 0.05 were considered statistically significant. All figures in this study were generated using Graphpad Prism 6.0 (GraphPad Inc., San Diego, CA, USA). Results Screening of porcine-derived probiotics using organoids It is reported that probiotics can improve the intestinal health of the host [ 55 ]. To identify novel candidate probiotic strains, we co-cultured the CFS of Bacillus from the strain library with intestinal organoids (Fig. 1 A). We found that compared with the LB group, the CFS treatment of strains PGM47, PGM68, PGM92, PGM94, PGM99, PGM108, PGM110, PGM123, and PGM159 significantly increased the relative budding efficiency of the organoids ( P < 0.05). At the same time, the CFS of PGM47, PGM123, and PGM541 significantly increased the relative organoid crypt depth ( P < 0.05). However, there was no significant difference in the relative crypts per organoid ( P > 0.05) (Fig. 1 B). The pictures are shown in Figure S1 (Supplementary Material 1). Although multiple Bacillus species CFS had an impact on the organoids, strain PGM541 exerted the most substantial positive impact, markedly increasing the relative crypt depth. Therefore, we selected strain PGM541. Through repeated verification using organoids, it was found that compared with the LB group, the organoid crypt depth in the PGM541 group was significantly increased ( P < 0.05) (Fig. 1 C). Therefore, strain PGM541 was selected as a probiotic that affects the intestinal epithelium. Fig. 1. Open in a new tab Probiotic screening based on jejunal organoids. A Strains from the Bacillus species library were cultured, centrifuged, and filtered to obtain cell-free supernatant (CFS). The CFS was co-cultured with organoids for probiotic screening. B Relative organoid budding efficiency, relative crypts per organoids, and relative crypt depth of organoids treated with 0.1% CFS (v/v) from different strains ( n = 3). LB, lysogeny broth; 541, strain PGM541. The budding efficiency was calculated as the ratio of budded organoids to the total number of organoids. Crypts per organoid was determined by counting the crypts on each organoid. Crypt depth was measured as bud length. Relative organoid budding rate = budding rate of experimental group/budding rate of LB control group; relative crypts per organoids = bud number of experimental group/bud number of LB control group; relative crypt depth = crypt depth of experimental group/crypt depth of LB control group. C Crypt depth of organoids repeatedly treated with 0.1% (v/v) PGM541-CFS ( n = 12) and representative images (scale bar, 100 μm; magnification, × 50). * P < 0.05, ** P < 0.01 In vitro validation of the candidate probiotic strain PGM541 To validate the feasibility of organoid screening for probiotics, we investigated the potential mechanism of the strain PGM541 on intestinal epithelium. Transcriptome sequencing was performed on the organoids treated with strain PGM541-CFS. GO enrichment analysis revealed that differentially expressed genes were enriched in endonuclease activity, nuclease activity, and DNA polymerase activity (Fig. 2 A). GSEA showed the top 20 enriched gene sets (Fig. 2 B), and the results suggested the upregulation of the DNA replication ( P < 0.001), homologous recombination ( P = 0.01), and cell cycle ( P < 0.001) in organoids treated with strain PGM541-CFS (Fig. 2 C). Furthermore, the cluster heatmap analysis (red indicates high expression, blue indicates low expression) revealed that compared with the control group, genes related to G1, G2, S, M phases, and DNA replication, as well as cell cycle regulation, were significantly enriched in the organoids treated with strain PGM541-CFS (Fig. 2 D). DNA replication and cell cycle regulatory factors drive the proliferation of ISCs [ 56 ] and facilitate their differentiation into secretory lineage cells (goblet cells and ChgA cells) as well as absorptive enterocytes [ 57 – 59 ]. To assess whether strain PGM541 affects the proliferation and differentiation of epithelial cells, IHC and AB-PAS were used to examine the organoid sections. The results showed that compared with the LB control group, the CFS derived from strain PGM541 significantly increased the proportion of Ki67 and ChgA positive cells in the organoids ( P < 0.05), but did not affect the goblet cells ( P > 0.05) (Fig. 2 E–G). Furthermore, PGM541-CFS did not affect the mRNA expression levels of absorptive enterocyte-related genes ( Alpi , SI , FABP2 ) in organoids (Fig. S2 in Supplementary Material 1, P > 0.05). These results suggest that strain PGM541 may exert probiotic effects in vitro by affecting the proliferation of intestinal epithelial cells and the differentiation of ChgA cells. Fig. 2. Open in a new tab Transcriptomic results of jejunal organoids treated with 0.1% (v/v) PGM541-CFS. A Compared to control organoids, upregulated genes enrichment in Gene Ontology (GO) enrichment analysis were performed in strain PGM541-CFS-treated organoids. B Bubble plot of Gene Set Enrichment Analysis (GSEA) displaying the top 20 enriched gene sets. C GSEA analysis of DNA replication, homologous recombination, and cell cycle in strain PGM541-CFS-treated organoids. D Heatmaps of differentially expressed genes associated with G1 and G2 phase, S phase and DNA replication, M phase, and cell cycle regulation in control and PGM541-CFS-treated organoids ( n = 3). E – G Immunohistochemical images and quantitative analysis of organoids. Proliferating cells (Ki67) and enteroendocrine cells (ChgA) are dark brown; goblet cells (GCs) are blue. Magnified views are displayed in the black box in the upper right corner, n = 3 (× 400 magnification, scale bar, 50 μm). Ns means no significance, * P < 0.05 In vivo validation of the candidate probiotic strain PGM541 To validate the actual probiotic efficacy of the organoid-screened strain, we performed in vivo experiments treating neonatal piglets with strain PGM541 to assess its effects (Fig. 3 A). First, to confirm the direct promotive effect of strain PGM541 on the intestinal epithelium, we isolated crypts from the jejunum and colon of treated and control piglets to generate primary organoids. The results showed that strain PGM541 significantly increased the organoid budding efficiency, crypts per organoid, and crypt depth in primary jejunal organoids ( P < 0.05) (Fig. 3 B), and significantly increased the area of primary colonic organoids ( P < 0.05) (Fig. S3A in Supplementary Material 1). Given that bacterial metabolites are key signals affecting the intestinal epithelium [ 54 ], we further investigated whether the benefits of PGM541 were mediated by changes in metabolically active components within the intestinal contents. In addition, metabolites from the hindgut can be absorbed into the bloodstream and subsequently influence ISCs in the foregut. For instance, it has been demonstrated that infusion of SCFAs into the hindgut affects the VH and the villus-to-crypt ratio in the foregut [ 60 ]. Based on this principle and considering that the jejunum is the primary site for nutrient absorption and thus an ideal target for assessing the function of growth-promoting probiotics, we collected colonic content suspensions (CCS, a mixture containing luminal metabolites) from treated and control piglets and used them to treat organoids derived from the jejunum. The results showed that after the application of strain PGM541, the metabolites present in the colon significantly increased the organoid budding efficiency, crypts per organoid, and crypt depth ( P < 0.05) (Fig. 3 C). H&E staining revealed that compared with the control group, strain PGM541 significantly increased the CD in the colon ( P < 0.05) (Fig. S3B in Supplementary Material 1), significantly increased the VW and CD of the jejunum, but significantly reduced the villus-to-crypt ratio ( P < 0.05), without affecting the VH ( P > 0.05) (Fig. 3 D). Immunohistochemical detection of jejunum cell differentiation showed that the number of ChgA per villus and Ki67-positive cells per crypt in strain PGM541-treated group increased significantly ( P < 0.05), but the ChgA cells per crypt and goblet cells per villus and per crypt were not affected ( P > 0.05) (Fig. 3 E, F). Moreover, strain PGM541 did not affect the mRNA expression levels of absorptive enterocyte-related genes ( Alpi , SI , FABP2 ) in the jejunum of piglets ( P > 0.05) (Fig. S4 in Supplementary Material 1). These results suggested that strain PGM541 likely exerts its probiotic effects in vivo by enhancing the stemness of ISCs and stimulating intestinal epithelial cell proliferation. Fig. 3. Open in a new tab Effects of strain PGM541 on intestinal stem cells (ISCs), morphological structure, proliferation, and differentiation in neonatal piglets. A Control group (CON) received saline via oral gavage; PGM541 group (541) received PGM541 bacterial solution (10 9 CFU/kg body weight/day) via oral gavage for 21 days, n = 8. B Budding efficiency, crypt number per organoid, and crypt depth in primary organoids derived from jejunal crypts isolated from CON and PGM541-treated piglets post-experiment, n = 3 (scale bar, 100 μm, × 50 magnification). C Budding rate, crypt number, and crypt depth of organoids treated with colonic content-derived supernatant (CCS, diluted 1:250; a mixture containing lumen metabolites) collected from CON and PGM541-treated piglets, n = 3 (scale bar, 100 μm, × 50 magnification). D Representative H&E staining of jejunal sections and quantitative analysis of villus height (VH), villus width (VW), crypt depth (CD), and VH/CD ratio. ≥ 30 well-aligned and intact villus-crypt structures were measured (scale bar, 200 μm, × 100 magnification), n = 8. E – F Representative immunohistochemical images and quantification of the number of Ki67-positive cells per crypt, ChgA-positive cells per villus and crypt, and goblet cells (GCs) per villus and crypt, n = 8. Ki67 and ChgA are dark brown; GCs are blue (marked by red arrows). ≥ 30 crypts were counted for Ki67 quantification; ≥ 30 well-oriented villi and crypts were counted for ChgA and GCs analysis. Ki67 cell images: scale bar, 50 μm (× 400 magnification); ChgA and GC cell images: scale bar, 100 μm (× 200 magnification). Ns means no significance, * P < 0.05, ** P < 0.01, and *** P < 0.001 Screening of the active metabolite BA from probiotic PGM541 using intestinal organoids To obtain the metabolites in strain PGM541 that have a positive effect on intestinal epithelial cells, the LB medium and the CFS of strain PGM541 were subjected to fractionation by HPLC. The results showed that there were 17 peaks in the LB sample and 26 peaks in the PGM541 sample (Fig. S5A in Supplementary Material 1). Eight HPLC fractions were obtained at different times for each sample, and they were used to treat intestinal organoids. It was found that compared with the LB group, the 4–6 min fraction of PGM541 significantly increased the organoid budding efficiency and crypt depth ( P < 0.05) (Fig. 4 A and B), while the 10–12 min fraction of PGM541 significantly decreased the organoid budding efficiency ( P < 0.05) (Fig. 4 A). The other fractions showed no significant differences ( P > 0.05) (Fig. 4 A and Fig. S5C in Supplementary Material 1). Fig. 4. Open in a new tab Screening of active metabolites from strain PGM541 using intestinal organoids. A Budding rate, crypt number, and crypt depth of organoids treated with eight fractions (0.1%; v/v) obtained by high-performance liquid chromatography (HPLC) separation of strain PGM541-CFS and LB medium, n = 3. B Representative images of organoids treated with the 4–6 min fraction (scale bar, 100 μm, × 50 magnification). C Budding rate, crypt number, and crypt depth of organoids treated with the top 6 most abundant metabolites in the 4–6 min fraction, n = 3. D Representative images of butyric acid (BA)-treated organoids (scale bar, 100 μm, × 50 magnification). E Proportion of Ki67-positive cells and representative images in BA-treated organoids. Ki67 cells are dark brown, and they are marked by red arrows, n = 3 (× 400 magnification, scale bar, 50 μm). Ns means no significance, * P < 0.05, ** P < 0.01, and *** P < 0.001 Subsequently, non-targeted metabolomics analysis was performed using LC–MS/MS on the 4–6 min fraction. A total of 965 compounds were identified (refer to the Supplementary Material 2), and the six most abundant metabolites were selected for organoid treatment, including dimethyl sulfoxide, lauryldiethanolamine, aspartic acid, di-N-propylamine, BA, and PC (16:0/18:2) (Fig. S5B in Supplementary Material 1). The results showed that compared with the control group, 0.1 mM BA significantly increased the budding rate and bud length of the organoids, but significantly reduced the crypts per organoid ( P < 0.05) (Fig. 4 C and D). Moreover, 1 mM BA significantly increased the budding rate of the organoids ( P < 0.05). Additionally, 10 µm PC (16:0/18:2) significantly decreased the budding rate of the organoids ( P < 0.05). The other metabolites showed no significant differences ( P > 0.05) (Fig. 4 C and Fig. S5D in Supplementary Material 1). The immunohistochemical analysis of the organoids treated with BA showed that 0.1 mM significantly increased the proportion of Ki67-positive cells ( P < 0.05), while 1 mM had no effect ( P > 0.05) (Fig. 4 E). The concentration of BA in the strain PGM541-CFS was also determined. The results showed that the BA content in PGM541-CFS ranged from approximately 0.12 to 0.17 mM (Fig. S6 in Supplementary Material 1). These results suggested that strain PGM541 may promote the proliferation of intestinal epithelial cells by generating BA. Elucidating the BA biosynthesis mechanism in strain PGM541 through genomics and transcriptomics To validate the reliability of the metabolite screened by organoids, we further measured the SCFAs in the intestinal contents of piglets. The results showed that compared with the control group, strain PGM541 treatment significantly increased the concentration of BA, IBA, and VA in the intestinal contents ( P < 0.05), but did not affect the concentrations of AA, PA, IVA, and total volatile fatty acids ( P > 0.05) (Fig. 5 A). However, treatment of organoids with IBA or VA revealed no significant effect on organoid viability ( P > 0.05) (Fig. S7A and B in Supplementary Material 1). Through 16S sequencing of strain PGM541, it was found that PGM541 belongs to Bacillus velezensis strain and is most closely related to Bacillus velezensis strain NRRL B-41580 (the similarity of 16S rRNA gene sequence is 96%) (Fig. 5 B). Subsequently, the whole-genome sequencing of strain PGM541 showed that the number of genes of strain PGM541 is 3746, the total length of the gene sequence is 3,497,958 bp, the average length of the gene is 933 bp, the GC content is 46.58%, and the total length of the repetitive sequence is 4584 bp, containing 86 tRNAs and 27 rRNAs (Table S2, Supplementary Material 1). The above genomic information was drawn into a genome circle diagram using the software Circos v0.66 (Fig. 5 C). The GO annotation function classification statistics graph showed the biological functions of strain PGM541 from the perspectives of cellular components, molecular functions, and biological processes (Fig. S8A in Supplementary Material 1). The specific GO annotations (refer to the Supplementary Material 3) revealed the functions related to BA synthesis, such as the glycolytic process (GO:0006096), and acetyl-CoA C-acetyltransferase activity (GO:0003985), 3-hydroxyacyl-CoA dehydrogenase activity (GO:0003857), enoyl-CoA hydratase activity (GO:0004300), acyl-CoA dehydrogenase activity (GO:0003995), phosphate butyryltransferase activity (GO:0050182), butyrate kinase activity (GO:0047761), acetate kinase activity (GO:0008776), phosphate acetyltransferase activity (GO:0008959), CoA-transferase activity (GO:0008410) (Fig. 5 D), and the KEGG annotation classification statistics graph annotated butanoate metabolism (Fig. S8B in Supplementary Material 1). Additionally, combined with genomic and transcriptomic annotations (refer to the Supplementary Material 4), it indicated that strain PGM541 contains and expresses the key enzyme genes for BA synthesis, including acetyl-CoA acetyltransferase ( thil ; GE000200 ), β-hydroxybutyryl-CoA dehydrogenase ( hbd ; GE000201 ), crotonase ( crt ; GE003623 ), butyryl-CoA dehydrogenase ( bcd ; GE000202 ), electron transferring flavoproteinα ( etfα ; GE003625 ), electron transferring flavoproteinβ ( etfβ ; GE003624 ), phosphotransbutyrylase ( ptb ; GE000208 ), and butyrate kinase ( buk ; GE000210 ) (Fig. 5 E), and the expression levels are shown in Fig. 5 F. These results indicated that strain PGM541 may exert its function by producing BA in vivo, and it possesses a metabolic pathway for synthesizing BA. Fig. 5. Open in a new tab Short-chain fatty acid (SCFA) content in piglet intestinal contents, and genomic and transcriptomic results of strain PGM541. A SCFA content in piglet colonic contents, including acetic acid (AA), propionic acid (PA), BA, isobutyric acid (IBA), valeric acid (VA), isovaleric acid (IVA), and total SCFAs, n = 8. Ns means no significance, * P < 0.05, ** P < 0.01. B Phylogenetic analysis of strain PGM541 with other type strains based on 16S rRNA gene sequences. C Circular genome map of strain PGM541 based on genomic sequence and annotation. From outermost to innermost ring: genome size; forward-strand genes; reverse-strand genes; repeat sequences; tRNA and rRNA; GC content; GC-skew. D BA production metabolic pathway in strain PGM541. Numbers marked in red indicate biological processes and molecular functions of functional enzymes annotated via GO analysis of the whole-genome sequence. E Enzyme genes involved in BA production in strain PGM541 marked in red; gene IDs of required enzymes identified via integrated genomic and transcriptomic analysis marked in blue. F Expression of BA synthesis-related enzyme genes in strain PGM541 Validating organoid-based metabolite screening via receptor inhibition SCFAs affect the stem cell state by activating G protein-coupled receptors ( FFAR2 , free fatty acid receptor 2; FFAR3 , free fatty acid receptor 3; GPR109A , G-protein-coupled receptor 109a) [ 61 – 63 ]. To further verify that BA is a reliable product of strain PGM541 identified by our screening technology, we measured the relative mRNA expression levels of FFAR2 , FFAR3 , and GPR109A in both organoids in vitro and tissue samples in vivo. The results showed that compared with the control group, the relative mRNA expression level of FFAR2 was significantly increased in the PGM541-treated organoids and intestinal tissues ( P < 0.05), while the relative mRNA expression levels of FFAR3 and GPR109A were not affected ( P > 0.05) (Fig. 6 A). GLPG0974 is an antagonist of FFAR2 [ 64 ]. Next, organoids were co-treated with PGM541-CCS and GLPG0974. The results showed that without the use of inhibitors, compared with the CON-CCS, the PGM541-CCS significantly increased the organoid budding efficiency, crypts per organoid, crypt depth, and area ( P < 0.05). When the organoids of the CON-CCS group were treated with GLPG0974, it was found that GLPG0974 significantly reduced the organoid budding efficiency ( P < 0.05), but did not affect the crypts per organoid, crypt depth, and area ( P > 0.05). When the organoids of the PGM541-CCS group were treated with GLPG0974, it was found that GLPG0974 significantly reduced the organoid budding efficiency, crypts per organoid, crypt depth, and area ( P < 0.05) (Fig. 6 B). In addition, immunohistochemical results showed that compared with the CON-CCS group, the strain PGM541-CCS group significantly increased the proportion of Ki67 cells ( P < 0.05), and GLPG0974 did not affect the proportion of Ki67 cells in the CON-CCS group ( P > 0.05), but significantly reduced the proportion of Ki67 cells in the PGM541-CCS group ( P < 0.05) (Fig. 6 C). Additionally, the organoids were co-treated with BA and GLPG0974. The results of this experiment indicated that without the use of inhibitors, compared with the CON group, BA significantly increased the crypts per organoid, organoid crypt depth, and area ( P < 0.05). When the organoids in the CON group were treated with GLPG0974, it was found that GLPG0974 significantly reduced the organoid area ( P < 0.05), but did not affect the organoid budding efficiency, the crypts per organoid, and the organoid crypt depth ( P > 0.05). When GLPG0974 was applied to the organoids in the BA group, it was found that GLPG0974 significantly reduced the organoid budding efficiency, crypts per organoid, organoid crypt depth, and area ( P < 0.05) (Fig. 6 D). Immunohistochemistry was performed on the co-treated organoids, and it was found that compared with the CON group, BA significantly increased the proportion of Ki67 cells ( P < 0.05) (Fig. 6 E). Moreover, regardless of the CON group or the BA group, GLPG0974 significantly reduced the proportion of Ki67 cells ( P < 0.05) (Fig. 6 E). These results demonstrated that strain PGM541 promotes the proliferation of intestinal epithelial cells by producing BA that activates FFAR2 receptor. Fig. 6. Open in a new tab Mechanistic study of BA’s effects on intestinal epithelial cells. A The mRNA expression levels of FFAR2 , FFAR3 , and GPR109A genes in strain PGM541-treated organoids ( n = 12) and piglet jejunal tissues ( n = 8). B The viability and representative images of organoids co-treated with 120 μM GLPG0974 ( FFAR2 antagonist) and CCS (1:250 v/v) from control or PGM541 group piglets, n = 3 (scale bar, 100 μm, × 50 magnification). C Proportion of Ki67-positive cells and representative images in organoids co-treated with 120 μM GLPG0974 and CCS (1:250 v/v), n = 3. Ki67 cells are dark brown, and they are marked by red arrows (× 400 magnification, scale bar, 50 μm). D Viability and representative images of organoids co-treated with 120 μM GLPG0974 and 0.1 mM BA, n = 3 (scale bar, 100 μm, × 50 magnification). E Proportion of Ki67-positive cells and representative images in organoids co-treated with 120 μM GLPG0974 and 0.1 mM BA, n = 3. Ki67 cells are dark brown, and they are marked by red arrows (× 400 magnification, scale bar, 50 μm). Ns means no significance, * P < 0.05, ** P < 0.01, and *** P < 0.001 The candidate strain PGM541 alleviates intestinal inflammation induced by DSS in mice To further verify the reliability of strain PGM541 selected through organoid screening as a probiotic, we examined the intestinal protective efficacy of strain PGM541 in a mouse colitis model (Fig. 7 A). Compared with the control group, DSS significantly reduced the BW of mice on days 27 and 28, as well as the ADG and ADFI on days 25, 27, and 28 ( P < 0.05). Compared with the DSS group, the BW (days 27 and 28), ADFI (days 27 and 28), and ADG (days 25, 27 and 28) of mice supplemented with strain PGM541 significantly increased ( P < 0.05) (Fig. 7 B). Additionally, during the DSS-induced period, compared with the control group, DSS significantly increased the hematochezia score of mice, while compared with the DSS group, strain PGM541 significantly reduced the hematochezia score ( P < 0.05) (Fig. 7 C). The intestinal index results of the small intestine showed that compared with the control group, DSS significantly increased the relative small intestine length and significantly decreased the small intestine weight ( P < 0.05); compared with the DSS group, the addition of strain PGM541 significantly decreased the relative small intestine length, but significantly increased the small intestine weight and the relative small intestine weight ( P < 0.05) (Fig. 7 D). The HE and immunohistochemical results of the jejunum showed that compared with the control group, DSS significantly increased jejunal VH and villus-to-crypt ratio, but significantly decreased jejunal VW, CD, and the number of Ki67-positive cells in crypts ( P < 0.05) (Fig. 7 E–G). However, the VW, CD, and the number of Ki67-positive cells in the crypts of the strain PGM541 treatment group were significantly increased compared to the DSS group ( P < 0.05) (Fig. 7 E–G). We observed that compared to the control group, DSS treatment resulted in a shortening of the large intestine length, whereas supplementing PGM541 increased the shortened length of the large intestine (Fig. 7 H). Representative histological images showed that DSS caused severe epithelial damage, mucosal and submucosal layer damage, and complete loss of crypt morphology in the colon of mice, while the addition of strain PGM541 led to partial inflammatory infiltration, only mucosal damage, and partial loss of crypts (Fig. 7 I). The above results confirmed that strain PGM541 has a protective effect against colitis induced by DSS, indicating that the probiotic screening based on organoids has good reliability. Fig. 7. Open in a new tab The effect of strain PGM541 on colitis in mice. A Control group mice received standard feed and water; DSS group mice received standard feed and water for the first three weeks, followed by DSS induction in the fourth week with standard feed; the DSS + 541 group received a custom diet containing PGM541 (10 9 CFU of strain PGM541 per kilogram of standard chow) along with water for the first 3 weeks, followed by DSS induction in the fourth week with PGM541-mixed feed, n = 16. B Body weight (BW), average daily gain (ADG), and average daily feed intake (ADFI) of mice during the experiment. * denotes significant differences versus CON group; # denotes significant differences versus DSS group, n = 16. C Hematochezia score of mice after DSS induction, n = 16. D Intestinal index of mice after the experiment, n = 16. E – F Intestinal morphology and representative images after the experiment, n = 16. × 200 magnification, scale bar = 100 μm. G Number of Ki67-positive cells in jejunal crypts and representative images, n = 16. × 400 magnification, scale bar = 50 μm. H Large intestine length of mice after the experiment. Vertical blue arrow indicates colon shortening after DSS induction; red arrow indicates alleviation of shortening with strain PGM541 supplementation. I Representative histological images of colonic tissue damage in DSS-treated mice: first row, × 100 magnification, scale bar, 200 μm; second row, × 200 magnification, scale bar, 100 μm. Ns means no significance, * P < 0.05, ** P < 0.01, and *** P < 0.001, n = 16 Discussion and conclusion The intestines contain a large variety of different microorganisms. Increasing evidence indicates that probiotics have significant health-promoting properties for the host [ 65 ]. Due to the long-term stability of Bacilli during storage, they have always been attractive as intestinal probiotics. Traditional screening relies on animal models or two-dimensional cells, while three-dimensional organoid technology has been proven to be able to simulate the components, structure, and function of intestinal tissue cell types [ 66 ], and has been verified as a reliable platform for drug screening [ 67 ]. In this study, we identified strain PGM541 from a porcine-derived Bacillus library by assessing organoid viability. CFS treatment from strain PGM541 significantly increased the crypt depth of the jejunal organoids, with this phenotype being reproducible, thereby providing a usable model for the screening of probiotics. Although strain PGM541 was isolated from colonic contents, accumulating evidence indicates that bacterial metabolites can exert effects both locally and at distant sites to influence host health [ 68 ]. Zhang et al. showed that the metabolites produced in the hindgut can influence the morphology of the foregut [ 60 ]. Moreover, as the primary site for nutrient absorption, the jejunum serves as an ideal target for investigating the health-promoting effects of probiotics. Therefore, this study selected jejunum-derived organoids and tissues as the core evaluation system. To validate the reliability of this probiotic strain screened using organoids, we investigated its mechanism. In an in vitro porcine intestinal crypt-derived organoid model, GO and GSEA analyses revealed that PGM541 treatment significantly enhanced activities related to exonucleases, nucleases, and DNA polymerases, and upregulated gene sets associated with DNA replication, the cell cycle, and homologous recombination. Further heatmap analysis demonstrated marked enrichment of representative genes from all cell cycle phases (G1, S, G2, and M) in the PGM541-treated group. It is well established that the proliferation and differentiation of ISCs are precisely regulated by core biological processes such as DNA replication, cell cycle control, and homologous recombination, which involve the coordinated actions of various enzymes including exonucleases, nucleases, and DNA polymerases [ 69 – 73 ]. These findings suggest that strain PGM541 may influence intestinal epithelial cell proliferation and differentiation by modulating cell cycle progression. Ki67 serves as a general marker for cell proliferation and identifies all cells in a state of active proliferation. Within the intestinal crypts, it primarily labels the transit-amplifying (TA) cells derived from ISCs [ 43 ]. These TA cells undergo rapid proliferation, migrate upward along the crypt-villus axis, and ultimately differentiate into either absorptive enterocytes or secretory lineage cells (goblet cells, enteroendocrine cells) [ 74 ]. Our study showed that strain PGM541-CFS significantly increased the proportions of Ki67- and ChgA-positive cells in organoids but did not affect the proportion of goblet cells or the mRNA expression levels of genes related to enterocytes ( Alpi , SI , FABP2 ), indicating that strain PGM541 may exert its probiotic effects by promoting cell proliferation and differentiation into ChgA-positive cells. Although both goblet cells and ChgA cells belong to the secretory cell lineage, their functions are distinct. ChgA-positive cells act as chemical sensors within the intestinal epithelium, monitor luminal contents, and secrete various digest-regulating hormones [ 75 ]. Strain PGM541-CFS enhanced the differentiation of ChgA cells in jejunal organoids, suggesting its potential to modulate intestinal function by strengthening chemosensory capacity through this specific lineage. This finding aligns with the observed increase in ChgA-positive cells in the jejunal villi of piglets treated with PGM541 in our in vivo experiments. In contrast, goblet cells, which primarily synthesize and secrete mucins to maintain epithelial integrity [ 76 ], were not increased by strain PGM541-CFS treatment. This indicates that under homeostatic conditions, the strain does not exert its primary effects via anti-inflammatory pathways, such as reinforcement of the mucosal barrier. Consistent with this interpretation, our GO and GSEA analyses in Fig. 2 showed no enrichment of anti-inflammatory-related pathways. Furthermore, an enhancement in the proliferation and differentiation activity of ISCs typically manifests morphologically as crypt deepening [ 77 ]. This aligns with the phenotype of increased crypt depth induced by PGM541-CFS in the organoid. However, treatment with strain PGM541-CFS did not significantly increase the relative budding efficiency or the relative crypts per organoid. This may be because the budding process in organoids can be analogized to the expansion of the ISC niche and the formation of new crypts through crypt fission [ 78 ]. Crypt fission is influenced by multiple factors, including cellular composition and relative stiffness [ 79 , 80 ]. Therefore, the unchanged budding efficiency or bud number may reflect the intrinsic complexity of the crypt fission process itself, which requires further investigation. Subsequently, to verify the in vivo relevance of the organoid screening results and the actual probiotic efficacy of strain PGM541, we conducted validation in a piglet animal model. Studies indicate that the intestinal epithelium maintains continuous contact with the gut microbiota, and luminal bacterial metabolites can influence the intestinal epithelium [ 54 ], with renewal mediated by ISCs [ 81 ]. By isolating jejunal and colonic crypts from piglets for organoid culture and treating the blank jejunal organoids with CCS, we confirmed that strain PGM541 treatment significantly enhanced ISC viability (organoid budding efficiency, crypts per organoid, and crypt depth in jejunal organoids; colonic organoids area). This suggests indicating that strain PGM541 might exert a positive effect on ISCs by altering metabolites within the piglet intestinal lumen. VH, VW, CD, and villus-to-crypt ratio are critical indicators of intestinal absorption and digestive function [ 82 ]. In this experiment, the jejunal VW and CD as well as the colonic CD were improved in piglets supplemented with strain PGM541, indicating that this strain may promote nutrient absorption and intestinal health by improving intestinal morphology. Subsequently, the jejunal immunohistochemistry in piglets revealed that strain PGM541 significantly increased the number of ChgA cells in villi and Ki67 cells in crypts, while it did not affect ChgA cells in crypts or goblet cell numbers in villi and crypts. Furthermore, the strain PGM541 had no significant effect on the mRNA expression of enterocyte-related marker genes in the jejunal tissue. Since cell proliferation and differentiation is a dynamic equilibrium process [ 83 ], the absence of change in the number of differentiated cells is possible. However, strain PGM541 increased the number of Ki67 cells both in vivo and in vitro. Therefore, it was hypothesized that strain PGM541 may exert its probiotic action by preferentially enhancing cellular proliferative capacity, and the positive effects of strain PGM541 observed in both in vitro organoids and the in vivo piglet model validate the feasibility of using organoids to screen for probiotics. More and more evidence indicates that bioactive metabolites derived from the intestinal microbiota can affect various physiological functions of the host, including ISC activity [ 84 , 85 ]. To identify the primary effector factor in strain PGM541-CFS, we employed a strategy based on organoid phenotypic screening. First, the PGM541-CFS was separated using HPLC technology, and the fractions of the metabolite mixture at 8 time points were obtained. Subsequently, these fractions were directly applied to treat organoids, and phenotypic assessment of the organoids was performed to rapidly and efficiently narrow down the search for active molecules. Our results showed that treatment with the fraction collected at 4–6 min significantly increased organoid budding efficiency and crypt depth, suggesting that the mixed metabolites eluted during this period contain key components that promote the activity of ISCs. This fractionation targeting strategy based on organoid viability significantly improved screening specificity and efficiency. Non-targeted metabolomics analysis is often used for metabolite analysis [ 86 ]; the metabolite analysis of the 4–6 min fraction showed 965 compounds. In the face of such a complex metabolite spectrum, the strategy of verifying one by one is time-consuming and labor-intensive. We focused on six relatively high-abundance secreted metabolites, adding them individually to the organoid culture system, ultimately proving that BA exerted the most significant promotive effect on ISC viability. It is noteworthy that exogenous BA significantly enhanced organoid budding efficiency, whereas the prior testing with strain PGM541-CFS did not yield a statistically significant effect on budding rates. This discrepancy may be attributed to the considerable metabolic diversity within strain PGM541-CFS, where the complex interplay among metabolites likely resulted in counteracting biological effects [ 87 ]. Importantly, BA increased the proportion of Ki67 cells in the organoids, which was consistent with the treatment results of strain PGM541 in both in vivo and in vitro. Furthermore, strain PGM541 significantly increased the concentration of BA in the colonic content of piglets, and also elevated the levels of IBA and VA, but the latter two did not affect organoid viability. Therefore, screening based on the organoid model strongly suggests that BA is likely the primary active component mediating the probiotic effects of strain PGM541. This study successfully identified bioactive key metabolites by integrating metabolomic analysis with organoid phenotypic screening. This result highlights the practicality of organoid models in screening complex microbial metabolites. By recapitulating the three-dimensional structure and cellular diversity of the intestinal epithelium, and being able to directly correlate metabolite treatment with organoid activity and functional indicators such as the proportion of Ki67-positive cells, this approach provides a pathway to identify key active substances. Based on the successful identification of the active metabolites of strain PGM541, we further verified the reliability of the results from the organoid screening from multiple dimensions. Previous studies indicated that the core BA synthesis pathway in many bacterial strains follows the acetyl-CoA pathway [ 88 , 89 ]. Briefly, the glycolytic intermediate pyruvate is converted to acetyl-CoA via catalysis by pyruvate-ferredoxin oxidoreductase. Acetyl-CoA is then catalyzed by enzymes such as thil , hbd , crt , and bcd to generate butyryl-CoA, and finally converted into BA through ptb and buk . From whole-genome data, molecular functions associated with BA synthesis (Fig. 5 D) and key enzymatic genes ( GE000200 , GE000201 , GE000202 , GE000208 , GE000210 ) were identified. The genome encodes an enoyl-CoA hydratase ( GE003623 ). Given evidence demonstrating that enoyl-CoA hydratase and crt are functionally identical [ 90 ], GE003623 was annotated as crt . Furthermore, genes encoding etfαβ ( GE003625 , GE003624 ) were detected; these form a complex with bcd to facilitate its activity [ 91 ]. Additionally, the transcriptome data confirmed detectable expression levels of these enzymatic genes, indicating the presence and transcriptional activity of BA synthesis-related enzymes in strain PGM541. This finding provides molecular-level support for the reliability of using organoid models to screen for functional metabolites. Indeed, numerous Bacillus strains have been reported to produce BA [ 92 – 94 ]. Next, we conducted receptor-targeted studies to verify the physiological mechanism of the key active substance BA. BA exerts its hormonal signaling effect by acting on G protein-coupled receptors ( FFAR2 / FFAR3 / GPR109A ) located on intestinal cells [ 95 – 97 ]. Quantitative analysis of FFAR2 , FFAR3 , and GPR109A mRNA levels in strain PGM541-treated organoids (in vitro) and pig intestinal tissues (in vivo) revealed that strain PGM541 significantly upregulated FFAR2 mRNA expression both in vivo and in vitro, without affecting FFAR3 and GPR109A mRNA levels. This may be related to the different efficacies of these receptors for each SCFA, as FFAR2 is preferentially activated by shorter SCFAs, whereas FFAR3 preferentially binds SCFAs containing 5–6 carbon atoms [ 98 ]. Additionally, the BA concentration in the PGM541-CFS in this study (approximately 0.12 to 0.17 mM) was well below the known half-maximal effective concentration (EC₅₀ ~ 1.6 mM) required to activate the GPR109A receptor [ 99 ]. Given that the sensitivity of receptors to agonists can vary across species, our results suggest that in the porcine intestinal organoid model, BA exerts its proliferative-promoting effects by activating FFAR2 . This may indicate a higher relative affinity of BA for porcine FFAR2 . However, this hypothesis requires further experimental validation. Furthermore, to directly verify that BA mediated its pro-proliferative effect via FFAR2 , we introduced the FFAR2 antagonist GLPG0974 into the organoid model. Results showed that, compared to the untreated control, strain PGM541-CCS and BA significantly enhanced organoid viability and the proportion of Ki67⁺ cells—consistent with our previous findings. Notably, antagonist treatment alone did not affect control organoid viability or Ki67⁺ cell proportion; however, co-treatment with GLPG0974 abolished the enhancing effects of strain PGM541-CCS or BA on both organoid viability and Ki67⁺ cell proportion. These data indicated that BA derived from strain PGM541 promotes the proliferation of intestinal epithelial cells via the FFAR2 receptor. Collectively, by integrating genomic and transcriptomic analyses to validate the strain PGM541’s BA synthesis potential and utilizing receptor antagonism to directly identify BA’s target site, this multidimensional validation helped to clarify the probiotic mechanism of BA and demonstrated the practical utility of the organoid platform for the effective screening of probiotics and their active metabolites. To comprehensively evaluate the application value of organoid screening technology in probiotic development, we also validated the colitis-alleviating capacity of the candidate strain (strain PGM541) selected through this technology. The DSS model is a common model used to study colitis in mice [ 100 ]; we then applied DSS to C57BL/6 mice in this study. The most prominent features of DSS-induced inflammatory oxidative stress include BW loss and hematochezia [ 101 ]. Consistent with these established characteristics, DSS administration significantly reduced BW and markedly increased hematochezia compared to the control group. Furthermore, DSS significantly decreased ADG, ADFI, small intestine weight, jejunal VW, jejunal CD, and the number of Ki67-positive cells within crypts. These collective inflammatory phenomena indicated that DSS caused damage. However, supplementation with strain PGM541 ameliorated these DSS-impaired indicators. Given that stem cells within crypts undergo self-renewal through proliferation and are crucial for maintaining intestinal architecture [ 102 ], it was speculated that strain PGM541 likely improved intestinal morphology by promoting cellular proliferation, thereby restoring growth performance of mice. Additionally, representative images of the large intestine revealed that DSS caused colonic shortening, cecal congestion, severe damage to colonic epithelial tissue, injury to the mucosa and submucosa, and complete loss of crypt architecture, but supplementation with strain PGM541 mitigated these inflammatory features. These results indicated that strain PGM541 can alleviate the adverse effects of colitis on mice, and our organoid screening technology can identify suitable probiotics. Figure 4 D and E demonstrate that the effect of BA on crypt depth and cell proliferation is concentration-dependent. In the present study, we observed that 0.1 mM exogenous BA promoted the proliferation of intestinal epithelial cells, which aligns with the BA concentration (0.12–0.17 mM) measured in the strain PGM541-CFS. However, this finding contrasts sharply with previous reports indicating an inhibitory effect of BA on intestinal cell proliferation. This apparent discrepancy can be explained by the “BA paradox.” As documented in the literature, high concentrations of BA at millimolar levels can induce cell cycle arrest and apoptosis, particularly in cancer cells [ 103 ], whereas physiologically relevant low concentrations may instead promote the proliferation of normal epithelium. Therefore, precisely defining the concentration range at which BA exerts its physiological pro-proliferative effects in vivo remains a critical objective for future research. Second, most previous inhibitory conclusions were derived from cancer cell line models [ 104 , 105 ]. In contrast, our study utilized homeostatic organoids and a steady-state piglet model, which more closely reflect physiological conditions. Moreover, it has been reported that BA can promote the proliferation of non-cancerous colonic cells [ 106 ]. Notably, while previous classical studies have primarily focused on human or mouse colonic models [ 107 – 109 ], our investigation employed a porcine jejunal system. As the primary site for nutrient absorption, jejunal epithelial cells preferentially utilize BA as an energy source to maintain intestinal health. This specificity across different species and intestinal segments may represent an important mechanism underlying the discrepant findings among various studies. Our study proposed a method for screening probiotics and their active effector molecules using intestinal organoids. Based on organoid viability, we screened candidate probiotic strain PGM541 and identified its bioactive metabolite BA, indicating that strain PGM541 primarily promoted the proliferation of intestinal epithelial cells by producing BA to activate the FFAR2 receptor; and this strain had the potential to alleviate intestinal pathological conditions. By integrating in vitro organoid and in vivo piglet experiments, along with multi-omics analysis and metabolite receptor antagonism, we preliminarily verified the feasibility of this screening approach. We proposed that this strategy could offer a potentially useful platform for probiotic screening under conditions that better simulate the in vivo physiological environment. However, several limitations of this study should be noted. First, our findings were primarily based on the porcine jejunum and corresponding organoid models, and their applicability to other intestinal segments or species requires further validation. Second, while we identified BA- FFAR2 as a relevant pathway, other microbial metabolites and host receptors may also contribute to the observed effects. Finally, extending this organoid-based screening platform to high-throughput applications remains challenging. Supplementary Information Supplementary Material 1. (9.1MB, docx) Supplementary Material 2. (110.3KB, xlsx) Supplementary Material 3. (926.5KB, xls) Supplementary Material 4. (472KB, xlsx) Acknowledgements We thank the support from the Animal Protection and Utilization Committee of Hunan Normal University. Abbreviations AB-PAS Alcian blue-periodic acid Schiff ADG Average daily gain ADFI Average daily feed intake AA Acetic acid ANOVA Analysis of variance BA Butyric acid BW Body weight Bcd Butyryl-CoA dehydrogenase Buk Butyrate kinase COG Clusters of Orthologous Genes CFS Cell-free supernatant CD Crypt depth ChgA Chromogranin A CCS Colonic content-derived supernatant Crt Crotonase DSS Dextran sulfate sodium DAB Diaminobenzidine Etfα Electron transferring flavoproteinα Etfβ Electron transferring flavoproteinβ FFAR2 Free fatty acid receptor 2 FFAR3 Free fatty acid receptor 3 GC Gas chromatography GO Gene Ontology GSEA Gene set enrichment analysis GCs Goblet cells HPLC High-performance liquid chromatography Hbd β-Hydroxybutyryl-CoA dehydrogenase ISC Intestinal stem cell IHC Immunohistochemistry IgG Immunoglobulin G IBA Isobutyric acid IVA Isovaleric acid KEGG Kyoto Encyclopedia of Genes and Genomes Ki67 Proliferating cells LB Lysogeny broth ONT Oxford Nanopore Technologies PA Propionic acid Ptb Phosphotransbutyrylase RT-qPCR Real-time quantitative PCR SCFAs Short-chain fatty acids Thil Acetyl-CoA acetyltransferase VH Villus height VW Villus width VA Valeric acid Authors’ contributions Investigation, data curation, and writing-original draft preparation: YZ. Conceptualization, methodology, software, and writing-review and editing: QH. Visualization and investigation: XZ. Investigation: LY and YT. Resources: QW. Conceptualization and methodology: JH. Project administration: JL. Supervision, funding acquisition, and writing-review and editing: HY. All authors contributed to the article and approved the submitted version. Funding This work was supported by the National Natural Science Foundation of China (Grant No. 32130099), Yuelushan Laboratory Breeding Program (YLS-2025-ZY02041), and the Science and Technology Innovation Program of Hunan Province (Grant No. 2022RC3060). Data availability The data supporting this study include the transcriptomic data of the bacterial strain and porcine intestinal organoids, as well as the genomic data of the strains, which have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject accession numbers PRJNA1321331, PRJNA1321333, and PRJNA1321332 (accessible at: https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA1321331 , https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA1321333 , https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA1321332 ). The metabolomics data have been submitted to the MetaboLights repository under the study identifier MTBLS12956 (available at: https://www.ebi.ac.uk/metabolights/MTBLS12956 ). No custom code was used in this study. Declarations Ethics approval and consent to participate The experimental procedures used in this study were approved by the Animal Care and Use Committee of Hunan Normal University and were conducted following the university’s guidelines for animal research. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Footnotes Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Hickey L, Jacobs SE, Garland SM, ProPrems Study G. Probiotics in neonatology. J Paediatr Child Health. 2012;48(9):777–83. [ DOI ] [ PubMed ] [ Google Scholar ] 2. Ahire JJ, Rohilla A, Kumar V, Tiwari A. Quality management of probiotics: ensuring safety and maximizing health benefits. Curr Microbiol. 2023;81(1):1. [ DOI ] [ PubMed ] [ Google Scholar ] 3. Mishra V, Shah C, Mokashe N, Chavan R, Yadav H, Prajapati J. Probiotics as potential antioxidants: a systematic review. J Agric Food Chem. 2015;63(14):3615–26. [ DOI ] [ PubMed ] [ Google Scholar ] 4. Pahumunto N, Dahlen G, Teanpaisan R. Evaluation of potential probiotic properties of Lactobacillus and Bacillus strains derived from various sources for their potential use in swine feeding. Probiotics Antimicrob Proteins. 2023;15(3):479–90. [ DOI ] [ PubMed ] [ Google Scholar ] 5. Lu S, Na K, Li Y, Zhang L, Fang Y, Guo X. Bacillus-derived probiotics: metabolites and mechanisms involved in bacteria-host interactions. Crit Rev Food Sci Nutr. 2024;64(6):1701–14. [ DOI ] [ PubMed ] [ Google Scholar ] 6. Oniszczuk A, Oniszczuk T, Gancarz M, Szymanska J. Role of gut microbiota, probiotics and prebiotics in the cardiovascular diseases. Molecules. 2021;26(4):1172. [ DOI ] [ PMC free article ] [ PubMed ] 7. Grzeskowiak L, Endo A, Beasley S, Salminen S. Microbiota and probiotics in canine and feline welfare. Anaerobe. 2015;34:14–23. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 8. Dowarah R, Verma AK, Agarwal N, Singh P, Singh BR. Selection and characterization of probiotic lactic acid bacteria and its impact on growth, nutrient digestibility, health and antioxidant status in weaned piglets. PLoS ONE. 2018;13(3):e0192978. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 9. Zhao M, Zhang Y, Li Y, Liu K, Zhang C, Li G. Complete genome sequence and probiotic properties of Pediococcus acidilactici CLP03 isolated from healthy Felis catus. Probiotics Antimicrob Proteins. 2025;17(2):903–17. [ DOI ] [ PubMed ] [ Google Scholar ] 10. Cuozzo S, de Moreno de LeBlanc A, LeBlanc JG, Hoffmann N, Tortella GR. Streptomyces genus as a source of probiotics and its potential for its use in health. Microbiol Res. 2023;266:127248. [ DOI ] [ PubMed ] 11. Angelakis E, Million M, Henry M, Raoult D. Rapid and accurate bacterial identification in probiotics and yoghurts by MALDI-TOF mass spectrometry. J Food Sci. 2011;76(8):M568–72. [ DOI ] [ PubMed ] [ Google Scholar ] 12. Kuebutornye FKA, Abarike ED, Lu Y. A review on the application of Bacillus as probiotics in aquaculture. Fish Shellfish Immunol. 2019;87:820–8. [ DOI ] [ PubMed ] [ Google Scholar ] 13. Raman J, Noh JS, Kim JS, Cho G, Kim DH, Song J, et al. Role of Bacillus species in food industry: advantages and limitations. J Microbiol Biotechnol. 2025;35:e2507043. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 14. Vera-Santander VE, Hernandez-Figueroa RH, Jimenez-Munguia MT, Mani-Lopez E, Lopez-Malo A. Health benefits of consuming foods with bacterial probiotics, postbiotics, and their metabolites: a review. Molecules. 2023;28(3):1230 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 15. Baker SA, Rutter J. Metabolites as signalling molecules. Nat Rev Mol Cell Biol. 2023;24(5):355–74. [ DOI ] [ PubMed ] [ Google Scholar ] 16. Hu Y, Chen Z, Xu C, Kan S, Chen D. Disturbances of the gut microbiota and microbiota-derived metabolites in inflammatory bowel disease. Nutrients. 2022;14(23):5140. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 17. Hao Z, Ding X, Wang J. Effects of gut bacteria and their metabolites on gut health of animals. Adv Appl Microbiol. 2024;127:223–52. [ DOI ] [ PubMed ] [ Google Scholar ] 18. Zolkiewicz J, Marzec A, Ruszczynski M, Feleszko W. Postbiotics-a step beyond pre- and probiotics. Nutrients. 2020;12(8):2189. [ DOI ] [ PMC free article ] [ PubMed ] 19. El Far MS, Zakaria AS, Kassem MA, Wedn A, Guimei M, Edward EA. Promising biotherapeutic prospects of different probiotics and their derived postbiotic metabolites: in-vitro and histopathological investigation. BMC Microbiol. 2023;23(1):122. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 20. Wu H, Xie S, Miao J, Li Y, Wang Z, Wang M, et al. Lactobacillus reuteri maintains intestinal epithelial regeneration and repairs damaged intestinal mucosa. Gut Microbes. 2020;11(4):997–1014. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 21. Xu W, Yu J, Yang Y, Li Z, Zhang Y, Zhang F, et al. Strain-level screening of human gut microbes identifies Blautia producta as a new anti-hyperlipidemic probiotic. Gut Microbes. 2023;15(1):2228045. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. Veiga P, Suez J, Derrien M, Elinav E. Moving from probiotics to precision probiotics. Nat Microbiol. 2020;5(7):878–80. [ DOI ] [ PubMed ] [ Google Scholar ] 23. Lukovac S, Roeselers G. Intestinal Crypt Organoids as Experimental Models. In: Verhoeckx K, Cotter P, Lopez-Exposito I, Kleiveland C, Lea T, Mackie A, Requena T, Swiatecka D, Wichers H, editors. The Impact of Food Bioactives on Health: in vitro and ex vivo models. Cham (CH): Springer; 2015. p. 245–53. [ PubMed ] 24. Sprangers J, Zaalberg IC, Maurice MM. Organoid-based modeling of intestinal development, regeneration, and repair. Cell Death Differ. 2021;28(1):95–107. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 25. Mussard E, Lencina C, Boudry G, Achard CS, Klotz C, Combes S, et al. Culture of piglet intestinal 3D organoids from cryopreserved epithelial crypts and establishment of cell monolayers. J Vis Exp. 2023;(192):10.3791/64917. [ DOI ] [ PubMed ] 26. Beaumont M, Blanc F, Cherbuy C, Egidy G, Giuffra E, Lacroix-Lamande S, et al. Intestinal organoids in farm animals. Vet Res. 2021;52(1):33. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 27. Almeida A, Mitchell AL, Boland M, Forster SC, Gloor GB, Tarkowska A, et al. A new genomic blueprint of the human gut microbiota. Nature. 2019;568(7753):499–504. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 28. Galambos D, Anderson RE, Reveillaud J, Huber JA. Genome-resolved metagenomics and metatranscriptomics reveal niche differentiation in functionally redundant microbial communities at deep-sea hydrothermal vents. Environ Microbiol. 2019;21(11):4395–410. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 29. Zhang L, Wang Y, Jia H, Liu X, Zhang R, Guan J. Transcriptome and metabolome analyses reveal the regulatory effects of compound probiotics on cecal metabolism in heat-stressed broilers. Poult Sci. 2023;102(1):102323. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 30. Palazzotto E, Weber T. Omics and multi-omics approaches to study the biosynthesis of secondary metabolites in microorganisms. Curr Opin Microbiol. 2018;45:109–16. [ DOI ] [ PubMed ] [ Google Scholar ] 31. Liang J, Kou S, Chen C, Raza SHA, Wang S, Ma X, et al. Effects of Clostridium butyricum on growth performance, metabonomics and intestinal microbial differences of weaned piglets. BMC Microbiol. 2021;21(1):85. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 32. Daliri EB, Ofosu FK, Chelliah R, Lee BH, Oh DH. Challenges and perspective in integrated multi-omics in gut microbiota studies. Biomolecules. 2021;11(2):300. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 33. Wang M, Ren Y, Guo X, Ye Y, Zhu H, Zhang J, et al. Postbiotics from Lactobacillus delbrueckii alleviate intestinal inflammation by promoting the expansion of intestinal stem cells in S. typhimurium -induced mice. Foods. 2024;13(6):874. [ DOI ] [ PMC free article ] [ PubMed ] 34. Sato T, Vries RG, Snippert HJ, van de Wetering M, Barker N, Stange DE, et al. Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche. Nature. 2009;459(7244):262–5. [ DOI ] [ PubMed ] [ Google Scholar ] 35. Sato T, Stange DE, Ferrante M, Vries RG, Van Es JH, Van den Brink S, et al. Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett’s epithelium. Gastroenterology. 2011;141(5):1762–72. [ DOI ] [ PubMed ] [ Google Scholar ] 36. Wang H, Gu CM, Xu S, Wang H, Zhao X, Gu L. Measurement of optical density of microbes by multi-light path transmission method. mLife. 2024;3(4):565–72. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 37. Wang Z, Li J, Wang Y, Wang L, Yin Y, Yin L, et al. Dietary vitamin A affects growth performance, intestinal development, and functions in weaned piglets by affecting intestinal stem cells. J Anim Sci. 2020;98(2):skaa020. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 38. Zha A, Tu R, Qi M, Wang J, Tan B, Liao P, et al. Mannan oligosaccharides selenium ameliorates intestinal mucosal barrier, and regulate intestinal microbiota to prevent enterotoxigenic Escherichia coli -induced diarrhea in weaned piglets. Ecotoxicol Environ Saf. 2023;264:115448. [ DOI ] [ PubMed ] [ Google Scholar ] 39. Yan S, Long L, Zong E, Huang P, Li J, Li Y, et al. Dietary sulfur amino acids affect jejunal cell proliferation and functions by affecting antioxidant capacity, Wnt/beta-catenin, and the mechanistic target of rapamycin signaling pathways in weaning piglets. J Anim Sci. 2018;96(12):5124–33. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 40. Wang M, Yang C, Wang Q, Li J, Huang P, Li Y, et al. The relationship between villous height and growth performance, small intestinal mucosal enzymes activities and nutrient transporters expression in weaned piglets. J Anim Physiol Anim Nutr (Berl). 2020;104(2):606–15. [ DOI ] [ PubMed ] [ Google Scholar ] 41. Zeng X, Yin L, Zhang Y, Wang Q, Li J, Yin Y, et al. Dietary iron alleviates dextran sodium sulfate-induced intestinal injury by regulating regeneration of intestinal stem cells in weaned mice. Biol Trace Elem Res. 2025;203(10):5219–34. [ DOI ] [ PubMed ] [ Google Scholar ] 42. Deng Q, Shao Y, Wang Q, Li J, Li Y, Ding X, et al. Effects and interaction of dietary electrolyte balance and citric acid on the intestinal function of weaned piglets. J Anim Sci. 2020;98(5):skaa106. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 43. Yin L, Li J, Zhang Y, Yang Q, Yang C, Yi Z, et al. Changes in progenitors and differentiated epithelial cells of neonatal piglets. Anim Nutr. 2022;8(1):265–76. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 44. Zhou Z, Zhang J, Zhang X, Mo S, Tan X, Wang L, et al. The production of short chain fatty acid and colonic development in weaning piglets. J Anim Physiol Anim Nutr (Berl). 2019;103(5):1530–7. [ DOI ] [ PubMed ] [ Google Scholar ] 45. Mejicanos GA, Gonzalez-Ortiz G, Nyachoti CM. Effect of dietary supplementation of xylanase in a wheat-based diet containing canola meal on growth performance, nutrient digestibility, organ weight, and short-chain fatty acid concentration in digesta when fed to weaned pigs. J Anim Sci. 2020;98(3):skaa064. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 46. Leonard SG, Sweeney T, Bahar B, Lynch BP, O’Doherty JV. Effect of dietary seaweed extracts and fish oil supplementation in sows on performance, intestinal microflora, intestinal morphology, volatile fatty acid concentrations and immune status of weaned pigs. Br J Nutr. 2011;105(4):549–60. [ DOI ] [ PubMed ] [ Google Scholar ] 47. Wang M, Huang H, Wang L, Yang H, He S, Liu F, et al. Herbal extract mixture modulates intestinal antioxidative capacity and microbiota in weaning piglets. Front Microbiol. 2021;12:706758. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 48. Hu M, Li C, Zhou X, Xue Y, Wang S, Hu A, et al. Microbial diversity analysis and genome sequencing identify Xanthomonas perforans as the pathogen of bacterial leaf canker of water spinach ( Ipomoea aquatic ). Front Microbiol. 2021;12:752760. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 49. Liu Y, Fu J, Wang L, Zhao Z, Wang H, Han S, et al. Isolation, identification, and whole-genome sequencing of high-yield protease bacteria from Daqu of ZhangGong Laojiu. PLoS ONE. 2022;17(4):e0264677. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 50. Cheng W, Yan X, Xiao J, Chen Y, Chen M, Jin J, et al. Isolation, identification, and whole genome sequence analysis of the alginate-degrading bacterium Cobetia sp. cqz5-12. Sci Rep. 2020;10(1):10920. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 51. Liu Y, Wu J, Liu R, Li F, Xuan L, Wang Q, et al. Vibrio cholerae virulence is blocked by chitosan oligosaccharide-mediated inhibition of ChsR activity. Nat Microbiol. 2024;9(11):2909–22. [ DOI ] [ PubMed ] [ Google Scholar ] 52. Chandrakasan G, Garcia-Trejo JF, Feregrino-Perez AA, Aguirre-Becerra H, Garcia ER, Nieto-Ramirez MI. Preliminary screening on antibacterial crude secondary metabolites extracted from bacterial symbionts and identification of functional bioactive compounds by FTIR, HPLC and gas chromatography-mass spectrometry. Molecules. 2024;29(12):2914. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 53. Hsieh Y. HPLC-MS/MS in drug metabolism and pharmacokinetic screening. Expert Opin Drug Metab Toxicol. 2008;4(1):93–101. [ DOI ] [ PubMed ] [ Google Scholar ] 54. Beaumont M, Paes C, Mussard E, Knudsen C, Cauquil L, Aymard P, et al. Gut microbiota derived metabolites contribute to intestinal barrier maturation at the suckling-to-weaning transition. Gut Microbes. 2020;11(5):1268–86. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 55. Hasan A, Qazi JI, Tabssum F, Kharabadze N, Hussain A. Effect of organic acids and probiotics on intestinal health of Apis mellifera . Braz J Microbiol. 2023;54(4):3231–6. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 56. Coller HA. DNA replication licensing in stem cells: gatekeeping the commitment to proliferation. J Cell Biol. 2018;217(5):1563–5. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 57. Hocker M, Wiedenmann B. Molecular mechanisms of enteroendocrine differentiation. Ann N Y Acad Sci. 1998;859:160–74. [ DOI ] [ PubMed ] [ Google Scholar ] 58. Basak O, Beumer J, Wiebrands K, Seno H, van Oudenaarden A, Clevers H. Induced quiescence of Lgr5+ stem cells in intestinal organoids enables differentiation of hormone-producing enteroendocrine cells. Cell Stem Cell. 2017;20(2):177–90 e4. [ DOI ] [ PubMed ] 59. Ballweg R, Lee S, Han X, Maini PK, Byrne H, Hong CI, et al. Unraveling the control of cell cycle periods during intestinal stem cell differentiation. Biophys J. 2018;115(11):2250–8. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 60. Zhang Y, Chen H, Zhu W, Yu K. Cecal infusion of sodium propionate promotes intestinal development and jejunal barrier function in growing pigs. Animals (Basel). 2019;9(6):284. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 61. Jeong H, Lee B, Cho SY, Lee Y, Kim J, Hur S, et al. Microbiota-derived short-chain fatty acids determine stem cell characteristics of gastric chief cells. Dev Cell. 2025;60(4):599-612 e6. [ DOI ] [ PubMed ] [ Google Scholar ] 62. Duan C, Wu J, Wang Z, Tan C, Hou L, Qian W, et al. Fucose promotes intestinal stem cell-mediated intestinal epithelial development through promoting Akkermansia -related propanoate metabolism. Gut Microbes. 2023;15(1):2233149. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 63. Yu X, Ou J, Wang L, Li Z, Ren Y, Xie L, et al. Gut microbiota modulate CD8(+) T cell immunity in gastric cancer through butyrate/GPR109A/HOPX. Gut Microbes. 2024;16(1):2307542. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 64. Namour F, Galien R, Van Kaem T, Van der Aa A, Vanhoutte F, Beetens J, et al. Safety, pharmacokinetics and pharmacodynamics of GLPG0974, a potent and selective FFA2 antagonist, in healthy male subjects. Br J Clin Pharmacol. 2016;82(1):139–48. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 65. Mazziotta C, Tognon M, Martini F, Torreggiani E, Rotondo JC. Probiotics mechanism of action on immune cells and beneficial effects on human health. Cells. 2023;12(1):184. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 66. Cho Y, Sung MH, Kang HT, Lee JH. Establishment of an apical-out organoid model for directly assessing the function of postbiotics. J Microbiol Biotechnol. 2024;34(11):2184–91. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 67. Ley S, Galuba O, Salathe A, Melin N, Aebi A, Pikiolek M, et al. Screening of intestinal crypt organoids: a simple readout for complex biology. SLAS Discov. 2017;22(5):571–82. [ DOI ] [ PubMed ] [ Google Scholar ] 68. O’Riordan KJ, Collins MK, Moloney GM, Knox EG, Aburto MR, Fulling C, et al. Short chain fatty acids: microbial metabolites for gut-brain axis signalling. Mol Cell Endocrinol. 2022;546:111572. [ DOI ] [ PubMed ] [ Google Scholar ] 69. Dommann N, Gavini J, Sanchez-Taltavull D, Baier FA, Birrer F, Loforese G, et al. LIM protein Ajuba promotes liver cell proliferation through its involvement in DNA replication and DNA damage control. FEBS Lett. 2022;596(14):1746–64. [ DOI ] [ PubMed ] [ Google Scholar ] 70. Yang W, Yu S, Peng J, Chang P, Chen X. FGF12 regulates cell cycle gene expression and promotes follicular granulosa cell proliferation through ERK phosphorylation in geese. Poult Sci. 2023;102(10):102937. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 71. Choi EH, Yoon S, Kim KP. Combined ectopic expression of homologous recombination factors promotes embryonic stem cell differentiation. Mol Ther. 2018;26(4):1154–65. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 72. Yin Y, Liu W, Shen Q, Zhang P, Wang L, Tao R, et al. The DNA endonuclease Mus81 regulates ZEB1 expression and serves as a target of BET4 inhibitors in gastric cancer. Mol Cancer Ther. 2019;18(8):1439–50. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 73. Bainbridge LJ, Daigaku Y. Bulk synthesis and beyond: the roles of eukaryotic replicative DNA polymerases. DNA Repair (Amst). 2024;141:103740. [ DOI ] [ PubMed ] [ Google Scholar ] 74. Jones JC, Dempsey PJ. Enterocyte progenitors can dedifferentiate to replace lost Lgr5(+) intestinal stem cells revealing that many different progenitor populations can regain stemness. Stem Cell Investig. 2016;3:61. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 75. Lin X, Gaudino SJ, Jang KK, Bahadur T, Singh A, Banerjee A, et al. IL-17RA-signaling in Lgr5(+) intestinal stem cells induces expression of transcription factor ATOH1 to promote secretory cell lineage commitment. Immunity. 2022;55(2):237–53 e8. [ DOI ] [ PMC free article ] [ PubMed ] 76. Moor AE, Harnik Y, Ben-Moshe S, Massasa EE, Rozenberg M, Eilam R, et al. Spatial reconstruction of single enterocytes uncovers broad zonation along the intestinal villus axis. Cell. 2018;175(4):1156–67 e15. [ DOI ] [ PubMed ] 77. Yin YB, Guo SG, Wan D, Wu X, Yin YL. Enteroids: promising in vitro models for studies of intestinal physiology and nutrition in farm animals. J Agric Food Chem. 2019;67(9):2421–8. [ DOI ] [ PubMed ] [ Google Scholar ] 78. Fuller MK, Faulk DM, Sundaram N, Shroyer NF, Henning SJ, Helmrath MA. Intestinal crypts reproducibly expand in culture. J Surg Res. 2012;178(1):48–54. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 79. Almet AA, Hughes BD, Landman KA, Nathke IS, Osborne JM. A Multicellular model of intestinal crypt buckling and fission. Bull Math Biol. 2018;80(2):335–59. [ DOI ] [ PubMed ] [ Google Scholar ] 80. Langlands AJ, Almet AA, Appleton PL, Newton IP, Osborne JM, Nathke IS. Paneth cell-rich regions separated by a cluster of Lgr5+ cells initiate crypt fission in the intestinal stem cell niche. PLoS Biol. 2016;14(6):e1002491. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 81. Hou Q, Ye L, Huang L, Yu Q. The research progress on intestinal stem cells and its relationship with intestinal microbiota. Front Immunol. 2017;8:599. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 82. Yang YK, Ge SJ, Su QL, Chen JJ, Wu J, Kang K. Effects of polyvinyl chloride microplastics on the reproductive system, intestinal structure, and microflora in male and female mice. Vet Sci. 2024;11(10):488. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 83. Santos AJM, Lo YH, Mah AT, Kuo CJ. The intestinal stem cell niche: homeostasis and adaptations. Trends Cell Biol. 2018;28(12):1062–78. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 84. Zheng D, Liwinski T, Elinav E. Interaction between microbiota and immunity in health and disease. Cell Res. 2020;30(6):492–506. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 85. Cox TO, Lundgren P, Nath K, Thaiss CA. Metabolic control by the microbiome. Genome Med. 2022;14(1):80. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 86. Xie S, Li J, Lyu F, Xiong Q, Gu P, Chen Y, et al. Novel tripeptide RKH derived from Akkermansia muciniphila protects against lethal sepsis. Gut. 2023;73(1):78–91. [ DOI ] [ PubMed ] [ Google Scholar ] 87. Nalbantoglu S, Karadag A. Metabolomics bridging proteomics along metabolites/oncometabolites and protein modifications: paving the way toward integrative multiomics. J Pharm Biomed Anal. 2021;199:114031. [ DOI ] [ PubMed ] [ Google Scholar ] 88. Fu H, Lin M, Tang IC, Wang J, Yang ST. Effects of benzyl viologen on increasing NADH availability, acetate assimilation, and butyric acid production by Clostridium tyrobutyricum. Biotechnol Bioeng. 2021;118(2):770–83. [ DOI ] [ PubMed ] [ Google Scholar ] 89. Zhang C, Yang H, Yang F, Ma Y. Current progress on butyric acid production by fermentation. Curr Microbiol. 2009;59(6):656–63. [ DOI ] [ PubMed ] [ Google Scholar ] 90. Kiema TR, Engel CK, Schmitz W, Filppula SA, Wierenga RK, Hiltunen JK. Mutagenic and enzymological studies of the hydratase and isomerase activities of 2-enoyl-CoA hydratase-1. Biochemistry. 1999;38(10):2991–9. [ DOI ] [ PubMed ] [ Google Scholar ] 91. Vigil W Jr, Nguyen D, Niks D, Hille R. Rapid-reaction kinetics of the butyryl-CoA dehydrogenase component of the electron-bifurcating crotonyl-CoA-dependent NADH:ferredoxin oxidoreductase from Megasphaera elsdenii . J Biol Chem. 2023;299(7):104853. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 92. Xu Y, Yu Y, Shen Y, Li Q, Lan J, Wu Y, et al. Effects of Bacillus subtilis and Bacillus licheniformis on growth performance, immunity, short chain fatty acid production, antioxidant capacity, and cecal microflora in broilers. Poult Sci. 2021;100(9):101358. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 93. Bai L, Gao M, Cheng X, Kang G, Cao X, Huang H. Engineered butyrate-producing bacteria prevents high fat diet-induced obesity in mice. Microb Cell Fact. 2020;19(1):94. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 94. Liu F, Yu J, Chen Z, Zhang S, Zhang Y, Zhang L, et al. Isolation of Bacillus cereus and its probiotic effect on growth performance, antioxidant capacity, and intestinal barrier protection of broilers. Poult Sci. 2025;104(4):104944. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 95. Husted AS, Trauelsen M, Rudenko O, Hjorth SA, Schwartz TW. GPCR-mediated signaling of metabolites. Cell Metab. 2017;25(4):777–96. [ DOI ] [ PubMed ] [ Google Scholar ] 96. Shackley M, Ma Y, Tate EW, Brown AJH, Frost G, Hanyaloglu AC. Short chain fatty acids enhance expression and activity of the umami taste receptor in enteroendocrine cells via a galpha(i/o) pathway. Front Nutr. 2020;7:568991. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 97. Chambers ES, Morrison DJ, Frost G. Control of appetite and energy intake by SCFA: what are the potential underlying mechanisms? Proc Nutr Soc. 2015;74(3):328–36. [ DOI ] [ PubMed ] [ Google Scholar ] 98. Lymperopoulos A, Suster MS, Borges JI. Short-chain fatty acid receptors and cardiovascular function. Int J Mol Sci. 2022;23(6):3303. [ DOI ] [ PMC free article ] [ PubMed ] 99. Thangaraju M, Cresci GA, Liu K, Ananth S, Gnanaprakasam JP, Browning DD, et al. GPR109A is a G-protein-coupled receptor for the bacterial fermentation product butyrate and functions as a tumor suppressor in colon. Cancer Res. 2009;69(7):2826–32. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 100. Jeon YD, Lee JH, Lee YM, Kim DK. Puerarin inhibits inflammation and oxidative stress in dextran sulfate sodium-induced colitis mice model. Biomed Pharmacother. 2020;124:109847. [ DOI ] [ PubMed ] [ Google Scholar ] 101. Ordas I, Eckmann L, Talamini M, Baumgart DC, Sandborn WJ. Ulcerative colitis. Lancet. 2012;380(9853):1606–19. [ DOI ] [ PubMed ] [ Google Scholar ] 102. Won JH, Choi JS, Jun JI. Ccn1 interacts with integrins to regulate intestinal stem cell proliferation and differentiation. Nat Commun. 2022;13(1):3117. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 103. Ryu SH, Kaiko GE, Stappenbeck TS. Cellular differentiation: potential insight into butyrate paradox? Mol Cell Oncol. 2018;5(3):e1212685. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 104. Zeng H, Safratowich BD, Wang TTY, Hamlin SK, Johnson LK. Butyrate inhibits deoxycholic-acid-resistant colonic cell proliferation via cell cycle arrest and apoptosis: a potential pathway linking dietary fiber to cancer prevention. Mol Nutr Food Res. 2020;64(8):e1901014. [ DOI ] [ PubMed ] [ Google Scholar ] 105. Zeng H, Claycombe KJ, Reindl KM. Butyrate and deoxycholic acid play common and distinct roles in HCT116 human colon cell proliferation. J Nutr Biochem. 2015;26(10):1022–8. [ DOI ] [ PubMed ] [ Google Scholar ] 106. Hajjar R, Richard CS, Santos MM. The role of butyrate in surgical and oncological outcomes in colorectal cancer. Am J Physiol Gastrointest Liver Physiol. 2021;320(4):G601–8. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 107. Zeng H, Hamlin SK, Safratowich BD, Cheng WH, Johnson LK. Superior inhibitory efficacy of butyrate over propionate and acetate against human colon cancer cell proliferation via cell cycle arrest and apoptosis: linking dietary fiber to cancer prevention. Nutr Res. 2020;83:63–72. [ DOI ] [ PubMed ] [ Google Scholar ] 108. Basson MD, Turowski GA, Rashid Z, Hong F, Madri JA. Regulation of human colonic cell line proliferation and phenotype by sodium butyrate. Dig Dis Sci. 1996;41(10):1989–93. [ DOI ] [ PubMed ] [ Google Scholar ] 109. Hong MY, Turner ND, Murphy ME, Carroll RJ, Chapkin RS, Lupton JR. In vivo regulation of colonic cell proliferation, differentiation, apoptosis, and P27Kip1 by dietary fish oil and butyrate in rats. Cancer Prev Res Phila. 2015;8(11):1076–83. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials Supplementary Material 1. (9.1MB, docx) Supplementary Material 2. (110.3KB, xlsx) Supplementary Material 3. (926.5KB, xls) Supplementary Material 4. (472KB, xlsx) Data Availability Statement The data supporting this study include the transcriptomic data of the bacterial strain and porcine intestinal organoids, as well as the genomic data of the strains, which have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject accession numbers PRJNA1321331, PRJNA1321333, and PRJNA1321332 (accessible at: https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA1321331 , https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA1321333 , https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA1321332 ). The metabolomics data have been submitted to the MetaboLights repository under the study identifier MTBLS12956 (available at: https://www.ebi.ac.uk/metabolights/MTBLS12956 ). No custom code was used in this study. Articles from Microbiome are provided here courtesy of BMC ACTIONS View on publisher site PDF (5.5 MB) Cite Collections Permalink PERMALINK Copy RESOURCES Similar articles Cited by other articles Links to NCBI Databases Cite Copy Download .nbib .nbib Format: AMA APA MLA NLM Add to Collections Create a new collection Add to an existing collection Name your collection * Choose a collection Unable to load your collection due to an error Please try again Add Cancel Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top